@article{Kyono2019,
abstract = {Variation in non-coding DNA, encompassing gene regulatory regions such as enhancers and promoters, contributes to risk for complex disorders, including type 2 diabetes. While genome-wide association studies have successfully identified hundreds of type 2 diabetes loci throughout the genome, the vast majority of these reside in non-coding DNA, which complicates the process of determining their functional significance and level of priority for further study. Here we review the methods used to experimentally annotate these non-coding variants, to nominate causal variants and to link them to diabetes pathophysiology. In recent years, chromatin profiling, massively parallel sequencing, high-throughput reporter assays and CRISPR gene editing technologies have rapidly become indispensable tools. Rather than treating individual variants in isolation, we discuss the importance of accounting for context, both genetic (such as flanking DNA sequence) and environmental (such as cellular state or environmental exposure). Incorporating these features shows promise in terms of revealing biologically convergent molecular signatures across distant and seemingly unrelated loci. Studying regulatory elements in the proper context will be crucial for interpreting the functional significance of disease-associated variants and applying the resulting knowledge to improve patient care.},
author = {Kyono, Yasuhiro and Kitzman, Jacob O and Parker, Stephen C J},
doi = {10.1007/s00125-019-4823-3},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Kyono, Kitzman, Parker - 2019 - Genomic annotation of disease-associated variants reveals shared functional contexts.pdf:pdf},
issn = {1432-0428},
journal = {Diabetologia},
number = {5},
pages = {735--743},
title = {{Genomic annotation of disease-associated variants reveals shared functional contexts}},
url = {https://doi.org/10.1007/s00125-019-4823-3},
volume = {62},
year = {2019}
}
@article{Zhong2010,
abstract = {Author Summary Genome-wide association studies (GWAS) seek to identify loci in which changes in DNA are correlated with disease. However, GWAS do not necessarily lead directly to genes associated with disease, and they do not typically inform the broader context in which disease genes operate, thereby providing limited insights into the mechanisms driving disease. One critical task to providing further insights into GWAS is developing an understanding of the genetics of gene expression (GGE). We present the first empiric study demonstrating that SNPs in human cohorts that associate with gene expression in liver and adipose tissues are enriched for associating with Type 2 Diabetes (T2D) in humans. By filtering “eSNPs” based on causal gene networks defined in an experimental cross population segregating T2D traits, we demonstrate a dramatically increased enrichment of T2D SNPs that enhance our ability to assess T2D risk. We demonstrate the utility of this approach by identifying malic enzyme 1 (ME1) as a novel T2D susceptibility gene in humans and then functionally validating the causal connection between ME1 and T2D in a mouse knockout model for Me1. This approach provides a path to identifying disease susceptibility networks rather than single SNPs or genes traditionally identified through GWAS.},
author = {Zhong, Hua and Beaulaurier, John and Lum, Pek Yee and Molony, Cliona and Yang, Xia and MacNeil, Douglas J and Weingarth, Drew T and Zhang, Bin and Greenawalt, Danielle and Dobrin, Radu and Hao, Ke and Woo, Sangsoon and Fabre-Suver, Christine and Qian, Su and Tota, Michael R and Keller, Mark P and Kendziorski, Christina M and Yandell, Brian S and Castro, Victor and Attie, Alan D and Kaplan, Lee M and Schadt, Eric E},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Zhong et al. - 2010 - Liver and Adipose Expression Associated SNPs Are Enriched for Association to Type 2 Diabetes.pdf:pdf},
journal = {PLOS Genetics},
month = {may},
number = {5},
pages = {e1000932},
publisher = {Public Library of Science},
title = {{Liver and Adipose Expression Associated SNPs Are Enriched for Association to Type 2 Diabetes}},
url = {https://doi.org/10.1371/journal.pgen.1000932},
volume = {6},
year = {2010}
}
@article{Ernst2017,
author = {Ernst, Jason and Kellis, Manolis},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Ernst, Kellis - 2017 - Chromatin-state discovery and genome annotation with ChromHMM.pdf:pdf},
journal = {Nature Protocols},
month = {nov},
pages = {2478},
publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
title = {{Chromatin-state discovery and genome annotation with ChromHMM}},
url = {http://dx.doi.org/10.1038/nprot.2017.124 http://10.0.4.14/nprot.2017.124},
volume = {12},
year = {2017}
}
@article{Shu2009b,
abstract = {Recent human genetics studies have revealed that common variants of the TCF7L2 (T-cell factor 7-like 2, formerly known as TCF4) gene are strongly associated with type 2 diabetes mellitus (T2DM). We have shown that TCF7L2 expression in the $\beta$-cells is correlated with function and survival of the insulin-producing pancreatic $\beta$-cell. In order to understand how variations in TCF7L2 influence diabetes progression, we investigated its mechanism of action in the $\beta$-cell. We show robust differences in TCF7L2 expression between healthy controls and models of T2DM. While mRNA levels were approximately 2-fold increased in isolated islets from the diabetic db/db mouse, the Vancouver Diabetic Fatty (VDF) Zucker rat and the high fat/high sucrose diet-treated mouse compared with the non-diabetic controls, protein levels were decreased. A similar decrease was observed in pancreatic sections from patients with T2DM. In parallel, expression of the receptors for glucagon-like peptide 1 (GLP-1R) and glucose-dependent insulinotropic polypeptide (GIP-R) was decreased in islets from humans with T2DM as well as in isolated human islets treated with siRNA to TCF7L2 (siTCF7L2). Also, insulin secretion stimulated by glucose, GLP-1 and GIP, but not KCl or cyclic adenosine monophosphate (cAMP) was impaired in siTCF7L2-treated isolated human islets. Loss of TCF7L2 resulted in decreased GLP-1 and GIP-stimulated AKT phosphorylation, and AKT-mediated Foxo-1 phosphorylation and nuclear exclusion. Our findings suggest that $\beta$-cell function and survival are regulated through an interplay between TCF7L2 and GLP-1R/GIP-R expression and signaling in T2DM. {\textcopyright} The Author 2009. Published by Oxford University Press. All rights reserved.},
author = {Shu, Luan and Matveyenko, Aleksey V. and Kerr-Conte, Julie and Cho, Jae Hyoung and McIntosh, Christopher H.S. and Maedler, Kathrin},
doi = {10.1093/hmg/ddp178},
issn = {14602083},
journal = {Human Molecular Genetics},
title = {{Decreased TCF7L2 protein levels in type 2 diabetes mellitus correlate with downregulation of GIP- and GLP-1 receptors and impaired beta-cell function}},
year = {2009}
}
@article{TheGTExConsortium2015,
abstract = {Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine.We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project.We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.},
author = {{The GTEx Consortium}},
doi = {10.1126/science.1262110},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/The GTEx Consortium - 2015 - The Genotype-Tissue Expression (GTEx) pilot analysis Multitissue gene regulation in humans.pdf:pdf},
isbn = {0036-8075},
issn = {1095-9203},
journal = {Science},
pages = {648--660},
pmid = {25954001},
title = {{The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/25954001},
volume = {348},
year = {2015}
}
@article{Wu2019,
abstract = {Transcription factor 7-like 2 (TCF7L2), which previously known as TCF-4, is a major form of transcription factor involved in the downstream WNT signaling and exhibits the strongest association to diabetes susceptibility. Although we still do not know mechanistically how TCF7L2 exerts its physiological functions on pancreatic endocrine cells, it had been suggested that TCF7L2 may directly affect $\beta$-cell function by regulating the activation of PI3K/AKT signaling pathway.},
author = {Wu, Hui-Hui and Li, Yan-Liang and Liu, Nai-Jia and Yang, Zhen and Tao, Xiao-Ming and Du, Yan-Ping and Wang, Xuan-Chun and Lu, Bin and Zhang, Zhao-Yun and Hu, Ren-Ming and Wen, Jie},
doi = {10.1186/s13098-019-0449-3},
issn = {1758-5996},
journal = {Diabetology {\&} Metabolic Syndrome},
number = {1},
pages = {55},
title = {{TCF7L2 regulates pancreatic $\beta$-cell function through PI3K/AKT signal pathway}},
url = {https://doi.org/10.1186/s13098-019-0449-3},
volume = {11},
year = {2019}
}
@article{DaSilvaXavier2012a,
abstract = {Aims/hypothesis: Individuals carrying type 2 diabetes risk alleles in TCF7L2 display decreased beta cell levels of T cell factor 7 like-2 (TCF7L2) immunoreactivity, and impaired insulin secretion and beta cell sensitivity to glucagon-like peptide 1 (GLP-1). Here, we sought to determine whether selective deletion of Tcf7l2 in mouse pancreas impairs insulin release and glucose homeostasis. Methods: Pancreas-specific Tcf7l2-null (pTcf7l2) mice were generated by crossing mice carrying conditional knockout alleles of Tcf7l2 (Tcf7l2-flox) with mice expressing Cre recombinase under the control of the Pdx1 promoter (Pdx1.Cre). Gene expression was assessed by real-time quantitative PCR and beta cell mass by optical projection tomography. Glucose tolerance, insulin secretion from isolated islets, and plasma insulin, glucagon and GLP-1 content were assessed by standard protocols. Results: From 12 weeks of age, pTcf7l2 mice displayed decreased oral glucose tolerance vs control littermates; from 20 weeks they had glucose intolerance upon administration of glucose by the intraperitoneal route. pTcf7l2 islets displayed impaired insulin secretion in response to 17 (vs 3.0)∈mmol/l glucose (54.6∈±∈4.6{\%}, p∈{\textless}∈0.01) or to 17 mmol/l glucose plus 100 nmol/l GLP-1 (44.3∈±∈4.9{\%}, p∈{\textless}∈0.01) compared with control islets. Glp1r (42∈±∈0.08{\%}, p∈{\textless}∈0.01) and Ins2 (15.4∈±∈4.6{\%}, p∈{\textless}∈0.01) expression was significantly lower in pTcf7l2 islets than in controls. Maintained on a high-fat (but not on a normal) diet, pTcf7l2 mice displayed decreased expansion of pancreatic beta cell volume vs control littermates. No differences were observed in plasma insulin, proinsulin, glucagon or GLP-1 concentrations. Conclusions/interpretation: Selective deletion of Tcf7l2 in the pancreas replicates key aspects of the altered glucose homeostasis in human carriers of TCF7L2 risk alleles, indicating the direct role of this factor in controlling beta cell function. {\textcopyright} 2012 Springer-Verlag.},
author = {{Da Silva Xavier}, G. and Mondragon, A. and Sun, G. and Chen, L. and McGinty, J. A. and French, P. M. and Rutter, G. A.},
doi = {10.1007/s00125-012-2600-7},
issn = {0012186X},
journal = {Diabetologia},
keywords = {Beta cell mass,GLP-1,GWAS,Glucose tolerance,Insulin,Knockout mouse,Pancreas},
title = {{Abnormal glucose tolerance and insulin secretion in pancreas-specific Tcf7l2-null mice}},
year = {2012}
}
@article{Xue2018a,
abstract = {Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with {\~{}}16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants.},
author = {Xue, Angli and Wu, Yang and Zhu, Zhihong and Zhang, Futao and Kemper, Kathryn E and Zheng, Zhili and Yengo, Loic and Lloyd-Jones, Luke R and Sidorenko, Julia and Wu, Yeda and Agbessi, Mawuss{\'{e}} and Ahsan, Habibul and Alves, Isabel and Andiappan, Anand and Awadalla, Philip and Battle, Alexis and Beutner, Frank and Bonder, Marc Jan and Boomsma, Dorret and Christiansen, Mark and Claringbould, Annique and Deelen, Patrick and Esko, T{\~{o}}nu and Fav{\'{e}}, Marie-Julie and Franke, Lude and Frayling, Timothy and Gharib, Sina and Gibson, Gregory and Hemani, Gibran and Jansen, Rick and K{\"{a}}h{\"{o}}nen, Mika and Kalnapenkis, Anette and Kasela, Silva and Kettunen, Johannes and Kim, Yungil and Kirsten, Holger and Kovacs, Peter and Krohn, Knut and Kronberg-Guzman, Jaanika and Kukushkina, Viktorija and Kutalik, Zoltan and Lee, Bernett and Lehtim{\"{a}}ki, Terho and Loeffler, Markus and Marigorta, Urko M and Metspalu, Andres and Milani, Lili and M{\"{u}}ller-Nurasyid, Martina and Nauck, Matthias and Nivard, Michel and Penninx, Brenda and Perola, Markus and Pervjakova, Natalia and Pierce, Brandon and Powell, Joseph and Prokisch, Holger and Psaty, Bruce and Raitakari, Olli and Ring, Susan and Ripatti, Samuli and Rotzschke, Olaf and Ru{\"{e}}ger, Sina and Saha, Ashis and Scholz, Markus and Schramm, Katharina and Sepp{\"{a}}l{\"{a}}, Ilkka and Stumvoll, Michael and Sullivan, Patrick and Teumer, Alexander and Thiery, Joachim and Tong, Lin and T{\"{o}}njes, Anke and van Dongen, Jenny and van Meurs, Joyce and Verlouw, Joost and V{\"{o}}lker, Uwe and V{\~{o}}sa, Urmo and Yaghootkar, Hanieh and Zeng, Biao and McRae, Allan F and Visscher, Peter M and Zeng, Jian and Yang, Jian and Consortium, EQTLGen},
doi = {10.1038/s41467-018-04951-w},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Xue et al. - 2018 - Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes.pdf:pdf},
issn = {2041-1723},
journal = {Nature Communications},
number = {1},
pages = {2941},
title = {{Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes}},
url = {https://doi.org/10.1038/s41467-018-04951-w},
volume = {9},
year = {2018}
}
@article{Consortium2017,
author = {{GTEx Consortium}},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Consortium et al. - 2017 - Genetic effects on gene expression across human tissues.pdf:pdf},
journal = {Nature},
month = {oct},
pages = {204},
publisher = {The Author(s)},
title = {{Genetic effects on gene expression across human tissues}},
url = {http://dx.doi.org/10.1038/nature24277 http://10.0.4.14/nature24277 https://www.nature.com/articles/nature24277{\#}supplementary-information},
volume = {550},
year = {2017}
}
@article{Chen2018,
abstract = {The gene encoding for transcription factor 7-like 2 (TCF7L2) is the strongest type 2 diabetes mellitus (T2DM) candidate gene discovered to date. The TCF7L2 protein is a key transcriptional effector of the Wnt/$\beta$-catenin signaling pathway, which is an important developmental pathway that negatively regulates adipogenesis. However, the precise role that TCF7L2 plays in the development and function of adipocytes remains largely unknown. Using a combination of in vitro approaches, we first show that TCF7L2 protein is increased during adipogenesis in 3T3-L1 cells and primary adipocyte stem cells and that TCF7L2 expression is required for the regulation of Wnt signaling during adipogenesis. Inactivation of TCF7L2 protein by removing the high-mobility group (HMG)-box DNA binding domain in mature adipocytes in vivo leads to whole-body glucose intolerance and hepatic insulin resistance. This phenotype is associated with increased subcutaneous adipose tissue mass, adipocyte hypertrophy, and inflammation. Finally, we demonstrate that TCF7L2 mRNA expression is downregulated in humans with impaired glucose tolerance and adipocyte insulin resistance, highlighting the translational potential of these findings. In summary, our data indicate that TCF7L2 has key roles in adipose tissue development and function that may reveal, at least in part, how TCF7L2 contributes to the pathophysiology of T2DM.},
author = {Chen, Xi and Ayala, Iriscilla and Shannon, Chris and Fourcaudot, Marcel and Acharya, Nikhil K and Jenkinson, Christopher P and Heikkinen, Sami and Norton, Luke},
doi = {10.2337/db17-0318},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Chen et al. - 2018 - The Diabetes Gene and Wnt Pathway Effector TCF7L2 Regulates Adipocyte Development and Function.pdf:pdf},
journal = {Diabetes},
month = {apr},
number = {4},
pages = {554 LP -- 568},
title = {{The Diabetes Gene and Wnt Pathway Effector TCF7L2 Regulates Adipocyte Development and Function}},
url = {http://diabetes.diabetesjournals.org/content/67/4/554.abstract},
volume = {67},
year = {2018}
}
@article{Greenfield2009,
annote = {doi: 10.1056/NEJMoa0803085},
author = {Greenfield, Jerry R and Miller, Jeffrey W and Keogh, Julia M and Henning, Elana and Satterwhite, Julie H and Cameron, Gregory S and Astruc, Beatrice and Mayer, John P and Brage, Soren and See, Teik Choon and Lomas, David J and O'Rahilly, Stephen and Farooqi, I Sadaf},
doi = {10.1056/NEJMoa0803085},
issn = {0028-4793},
journal = {New England Journal of Medicine},
month = {jan},
number = {1},
pages = {44--52},
publisher = {Massachusetts Medical Society},
title = {{Modulation of Blood Pressure by Central Melanocortinergic Pathways}},
url = {https://doi.org/10.1056/NEJMoa0803085},
volume = {360},
year = {2009}
}
@article{S.C.ElbeinN.RasouliA.Yao-BrengasserN.K.SharmaS.K.Das2011,
author = {{S. C. Elbein  N. Rasouli, A. Yao-Brengasser, N. K. Sharma, S. K. Das}, P A Kern},
journal = {Diabetes},
pages = {1019--1029},
title = {{Global gene expression profiles of subcutaneous adipose and muscle from glucose-tolerant, insulin-sensitive, and insulin-resistant individuals matched for BMI}},
volume = {60},
year = {2011}
}
@article{Ip2015,
abstract = {Investigations on the metabolic role of the Wnt signaling pathway and hepatic transcription factor 7-like 2 (TCF7L2) have generated opposing views. While some studies demonstrated a repressive effect of TCF7L2 on hepatic gluconeogenesis, a recent study using liver-specific Tcf7l2−/− mice suggested the opposite. As a consequence of redundant and bidirectional actions of transcription factor (TCF) molecules and other complexities of the Wnt pathway, knockout of a single Wnt pathway component may not effectively reveal a complete metabolic picture of this pathway. To address this, we generated the liver-specific dominant-negative (DN) TCF7L2 (TCF7L2DN) transgenic mouse model LTCFDN. These mice exhibited progressive impairment in response to pyruvate challenge. Importantly, LTCFDN hepatocytes displayed elevated gluconeogenic gene expression, gluconeogenesis, and loss of Wnt-3a–mediated repression of gluconeogenesis. In C57BL/6 hepatocytes, adenovirus-mediated expression of TCF7L2DN, but not wild-type TCF7L2, increased gluconeogenesis and gluconeogenic gene expression. Our further mechanistic exploration suggests that TCF7L2DN-mediated inhibition of Wnt signaling causes preferential interaction of $\beta$-catenin ($\beta$-cat) with FoxO1 and increased binding of $\beta$-cat/FoxO1 to the Pck1 FoxO binding site, resulting in the stimulation of Pck1 expression and increased gluconeogenesis. Together, our results using TCF7L2DN as a unique tool revealed that the Wnt signaling pathway and its effector $\beta$-cat/TCF serve a beneficial role in suppressing hepatic gluconeogenesis.},
author = {Ip, Wilfred and Shao, Weijuan and Song, Zhuolun and Chen, Zonglan and Wheeler, Michael B and Jin, Tianru},
doi = {10.2337/db14-1329},
journal = {Diabetes},
month = {jun},
number = {6},
pages = {1923 LP  -- 1932},
title = {{Liver-Specific Expression of Dominant-Negative Transcription Factor 7-Like 2 Causes Progressive Impairment in Glucose Homeostasis}},
url = {http://diabetes.diabetesjournals.org/content/64/6/1923.abstract},
volume = {64},
year = {2015}
}
@article{Voight2010b,
abstract = {Mark McCarthy and colleagues identify twelve new risk loci for type 2 diabetes through a large-scale genome-wide association and replication study in individuals of European ancestry. The identified loci affect both beta-cell function and insulin action and are enriched for genes involved in cell cycle regulation.},
author = {Voight, Benjamin F and Scott, Laura J and Steinthorsdottir, Valgerdur and Morris, Andrew P and Dina, Christian and Welch, Ryan P and Zeggini, Eleftheria and Huth, Cornelia and Aulchenko, Yurii S and Thorleifsson, Gudmar and McCulloch, Laura J and Ferreira, Teresa and Grallert, Harald and Amin, Najaf and Wu, Guanming and Willer, Cristen J and Raychaudhuri, Soumya and McCarroll, Steve A and Langenberg, Claudia and Hofmann, Oliver M and Dupuis, Jos{\'{e}}e and Qi, Lu and Segr{\`{e}}, Ayellet V and van Hoek, Mandy and Navarro, Pau and Ardlie, Kristin and Balkau, Beverley and Benediktsson, Rafn and Bennett, Amanda J and Blagieva, Roza and Boerwinkle, Eric and Bonnycastle, Lori L and Bostr{\"{o}}m, Kristina Bengtsson and Bravenboer, Bert and Bumpstead, Suzannah and Burtt, Nois{\"{e}}l P and Charpentier, Guillaume and Chines, Peter S and Cornelis, Marilyn and Couper, David J and Crawford, Gabe and Doney, Alex S F and Elliott, Katherine S and Elliott, Amanda L and Erdos, Michael R and Fox, Caroline S and Franklin, Christopher S and Ganser, Martha and Gieger, Christian and Grarup, Niels and Green, Todd and Griffin, Simon and Groves, Christopher J and Guiducci, Candace and Hadjadj, Samy and Hassanali, Neelam and Herder, Christian and Isomaa, Bo and Jackson, Anne U and Johnson, Paul R V and J{\o}rgensen, Torben and Kao, Wen H L and Klopp, Norman and Kong, Augustine and Kraft, Peter and Kuusisto, Johanna and Lauritzen, Torsten and Li, Man and Lieverse, Aloysius and Lindgren, Cecilia M and Lyssenko, Valeriya and Marre, Michel and Meitinger, Thomas and Midthjell, Kristian and Morken, Mario A and Narisu, Narisu and Nilsson, Peter and Owen, Katharine R and Payne, Felicity and Perry, John R B and Petersen, Ann-Kristin and Platou, Carl and Proen{\c{c}}a, Christine and Prokopenko, Inga and Rathmann, Wolfgang and Rayner, N William and Robertson, Neil R and Rocheleau, Ghislain and Roden, Michael and Sampson, Michael J and Saxena, Richa and Shields, Beverley M and Shrader, Peter and Sigurdsson, Gunnar and Spars{\o}, Thomas and Strassburger, Klaus and Stringham, Heather M and Sun, Qi and Swift, Amy J and Thorand, Barbara and Tichet, Jean and Tuomi, Tiinamaija and van Dam, Rob M and van Haeften, Timon W and van Herpt, Thijs and van Vliet-Ostaptchouk, Jana V and Walters, G Bragi and Weedon, Michael N and Wijmenga, Cisca and Witteman, Jacqueline and Bergman, Richard N and Cauchi, Stephane and Collins, Francis S and Gloyn, Anna L and Gyllensten, Ulf and Hansen, Torben and Hide, Winston A and Hitman, Graham A and Hofman, Albert and Hunter, David J and Hveem, Kristian and Laakso, Markku and Mohlke, Karen L and Morris, Andrew D and Palmer, Colin N A and Pramstaller, Peter P and Rudan, Igor and Sijbrands, Eric and Stein, Lincoln D and Tuomilehto, Jaakko and Uitterlinden, Andre and Walker, Mark and Wareham, Nicholas J and Watanabe, Richard M and Abecasis, Gon{\c{c}}alo R and Boehm, Bernhard O and Campbell, Harry and Daly, Mark J and Hattersley, Andrew T and Hu, Frank B and Meigs, James B and Pankow, James S and Pedersen, Oluf and Wichmann, H-Erich and Barroso, In{\^{e}}s and Florez, Jose C and Frayling, Timothy M and Groop, Leif and Sladek, Rob and Thorsteinsdottir, Unnur and Wilson, James F and Illig, Thomas and Froguel, Philippe and van Duijn, Cornelia M and Stefansson, Kari and Altshuler, David and Boehnke, Michael and McCarthy, Mark I and Investigators, The MAGIC and Consortium, The GIANT},
doi = {10.1038/ng.609},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Voight et al. - 2010 - Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis(3).pdf:pdf},
issn = {1546-1718},
journal = {Nature Genetics},
number = {7},
pages = {579--589},
title = {{Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis}},
url = {https://doi.org/10.1038/ng.609},
volume = {42},
year = {2010}
}
@article{Khetan2018,
abstract = {Type 2 Diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in {\&}gt;200 loci to islet dysfunction and T2D. Identification of the putative causal variants, their target genes, and whether they lead to gain- or loss-of-function remains challenging. Here, we profiled chromatin accessibility in pancreatic islet samples from 19 genotyped individuals and identified 2949 SNPs associated with in vivo cis-regulatory element (RE) use (i.e., chromatin accessibility quantitative trait loci (caQTL)). Among the caQTLs tested (n=13) using luciferase reporter assays in MIN6 beta cells, more than half exhibited effects on enhancer activity that were consistent with in vivo chromatin accessibility changes. Importantly, islet caQTL analysis nominated putative causal SNPs in 13 T2D-associated GWAS loci, linking 7 and 6 T2D risk alleles, respectively, to gain or loss of in vivo chromatin accessibility. By investigating the effect of genetic variants on chromatin accessibility in islets, this study is an important step forward in translating T2D-associated GWAS SNP into functional molecular consequences.},
author = {Khetan, Shubham and Kursawe, Romy and Youn, Ahrim and Lawlor, Nathan and Jillette, Alexandria and Marquez, Eladio J and Ucar, Duygu and Stitzel, Michael L},
doi = {10.2337/db18-0393},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Khetan et al. - 2018 - Type 2 Diabetes Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets.pdf:pdf},
journal = {Diabetes},
month = {aug},
pages = {db180393},
title = {{Type 2 Diabetes Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets}},
url = {http://diabetes.diabetesjournals.org/content/early/2018/08/27/db18-0393.abstract},
year = {2018}
}
@article{Auton2015,
abstract = {The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes {\textgreater}99{\%} of SNP variants with a frequency of {\textgreater}1{\%} for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.},
author = {Auton, Adam and Abecasis, Gon{\c{c}}alo R and Altshuler, David M and Durbin, Richard M and Abecasis, Gon{\c{c}}alo R and Bentley, David R and Chakravarti, Aravinda and Clark, Andrew G and Donnelly, Peter and Eichler, Evan E and Flicek, Paul and Gabriel, Stacey B and Gibbs, Richard A and Green, Eric D and Hurles, Matthew E and Knoppers, Bartha M and Korbel, Jan O and Lander, Eric S and Lee, Charles and Lehrach, Hans and Mardis, Elaine R and Marth, Gabor T and McVean, Gil A and Nickerson, Deborah A and Schmidt, Jeanette P and Sherry, Stephen T and Wang, Jun and Wilson, Richard K and Gibbs, Richard A and Boerwinkle, Eric and Doddapaneni, Harsha and Han, Yi and Korchina, Viktoriya and Kovar, Christie and Lee, Sandra and Muzny, Donna and Reid, Jeffrey G and Zhu, Yiming and Wang, Jun and Chang, Yuqi and Feng, Qiang and Fang, Xiaodong and Guo, Xiaosen and Jian, Min and Jiang, Hui and Jin, Xin and Lan, Tianming and Li, Guoqing and Li, Jingxiang and Li, Yingrui and Liu, Shengmao and Liu, Xiao and Lu, Yao and Ma, Xuedi and Tang, Meifang and Wang, Bo and Wang, Guangbiao and Wu, Honglong and Wu, Renhua and Xu, Xun and Yin, Ye and Zhang, Dandan and Zhang, Wenwei and Zhao, Jiao and Zhao, Meiru and Zheng, Xiaole and Lander, Eric S and Altshuler, David M and Gabriel, Stacey B and Gupta, Namrata and Gharani, Neda and Toji, Lorraine H and Gerry, Norman P and Resch, Alissa M and Flicek, Paul and Barker, Jonathan and Clarke, Laura and Gil, Laurent and Hunt, Sarah E and Kelman, Gavin and Kulesha, Eugene and Leinonen, Rasko and McLaren, William M and Radhakrishnan, Rajesh and Roa, Asier and Smirnov, Dmitriy and Smith, Richard E and Streeter, Ian and Thormann, Anja and Toneva, Iliana and Vaughan, Brendan and Zheng-Bradley, Xiangqun and Bentley, David R and Grocock, Russell and Humphray, Sean and James, Terena and Kingsbury, Zoya and Lehrach, Hans and Sudbrak, Ralf and Albrecht, Marcus W and Amstislavskiy, Vyacheslav S and Borodina, Tatiana A and Lienhard, Matthias and Mertes, Florian and Sultan, Marc and Timmermann, Bernd and Yaspo, Marie-Laure and Mardis, Elaine R and Wilson, Richard K and Fulton, Lucinda and Fulton, Robert and Sherry, Stephen T and Ananiev, Victor and Belaia, Zinaida and Beloslyudtsev, Dimitriy and Bouk, Nathan and Chen, Chao and Church, Deanna and Cohen, Robert and Cook, Charles and Garner, John and Hefferon, Timothy and Kimelman, Mikhail and Liu, Chunlei and Lopez, John and Meric, Peter and O'Sullivan, Chris and Ostapchuk, Yuri and Phan, Lon and Ponomarov, Sergiy and Schneider, Valerie and Shekhtman, Eugene and Sirotkin, Karl and Slotta, Douglas and Zhang, Hua and McVean, Gil A and Durbin, Richard M and Balasubramaniam, Senduran and Burton, John and Danecek, Petr and Keane, Thomas M and Kolb-Kokocinski, Anja and McCarthy, Shane and Stalker, James and Quail, Michael and Schmidt, Jeanette P and Davies, Christopher J and Gollub, Jeremy and Webster, Teresa and Wong, Brant and Zhan, Yiping and Auton, Adam and Campbell, Christopher L and Kong, Yu and Marcketta, Anthony and Gibbs, Richard A and Yu, Fuli and Antunes, Lilian and Bainbridge, Matthew and Muzny, Donna and Sabo, Aniko and Huang, Zhuoyi and Wang, Jun and Coin, Lachlan J M and Fang, Lin and Guo, Xiaosen and Jin, Xin and Li, Guoqing and Li, Qibin and Li, Yingrui and Li, Zhenyu and Lin, Haoxiang and Liu, Binghang and Luo, Ruibang and Shao, Haojing and Xie, Yinlong and Ye, Chen and Yu, Chang and Zhang, Fan and Zheng, Hancheng and Zhu, Hongmei and Alkan, Can and Dal, Elif and Kahveci, Fatma and Marth, Gabor T and Garrison, Erik P and Kural, Deniz and Lee, Wan-Ping and {Fung Leong}, Wen and Stromberg, Michael and Ward, Alistair N and Wu, Jiantao and Zhang, Mengyao and Daly, Mark J and DePristo, Mark A and Handsaker, Robert E and Altshuler, David M and Banks, Eric and Bhatia, Gaurav and del Angel, Guillermo and Gabriel, Stacey B and Genovese, Giulio and Gupta, Namrata and Li, Heng and Kashin, Seva and Lander, Eric S and McCarroll, Steven A and Nemesh, James C and Poplin, Ryan E and Yoon, Seungtai C and Lihm, Jayon and Makarov, Vladimir and Clark, Andrew G and Gottipati, Srikanth and Keinan, Alon and Rodriguez-Flores, Juan L and Korbel, Jan O and Rausch, Tobias and Fritz, Markus H and St{\"{u}}tz, Adrian M and Flicek, Paul and Beal, Kathryn and Clarke, Laura and Datta, Avik and Herrero, Javier and McLaren, William M and Ritchie, Graham R S and Smith, Richard E and Zerbino, Daniel and Zheng-Bradley, Xiangqun and Sabeti, Pardis C and Shlyakhter, Ilya and Schaffner, Stephen F and Vitti, Joseph and Cooper, David N and Ball, Edward V and Stenson, Peter D and Bentley, David R and Barnes, Bret and Bauer, Markus and {Keira Cheetham}, R and Cox, Anthony and Eberle, Michael and Humphray, Sean and Kahn, Scott and Murray, Lisa and Peden, John and Shaw, Richard and Kenny, Eimear E and Batzer, Mark A and Konkel, Miriam K and Walker, Jerilyn A and MacArthur, Daniel G and Lek, Monkol and Sudbrak, Ralf and Amstislavskiy, Vyacheslav S and Herwig, Ralf and Mardis, Elaine R and Ding, Li and Koboldt, Daniel C and Larson, David and Ye, Kai and Gravel, Simon and Consortium, The 1000 Genomes Project and Authors, Corresponding and Committee, Steering and Group, Production and of Medicine, Baylor College and BGI-Shenzhen and and Harvard, Broad Institute of M I T and Research, Coriell Institute for Medical and {European Molecular Biology Laboratory}, European Bioinformatics Institute and Illumina and Genetics, Max Planck Institute for Molecular and University, McDonnell Genome Institute at Washington and of Health, U S National Institutes and of Oxford, University and Institute, Wellcome Trust Sanger and Group, Analysis and Affymetrix and of Medicine, Albert Einstein College and University, Bilkent and College, Boston and Laboratory, Cold Spring Harbor and University, Cornell and Laboratory, European Molecular Biology and University, Harvard and Database, Human Gene Mutation and Sinai, Icahn School of Medicine at Mount and University, Louisiana State and Hospital, Massachusetts General and University, McGill and {National Eye Institute}, N I H},
doi = {10.1038/nature15393},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Auton et al. - 2015 - A global reference for human genetic variation.pdf:pdf},
issn = {1476-4687},
journal = {Nature},
number = {7571},
pages = {68--74},
title = {{A global reference for human genetic variation}},
url = {https://doi.org/10.1038/nature15393},
volume = {526},
year = {2015}
}
@article{Pappalardo2017,
abstract = {Insulin production by the pancreatic $\beta$-cell is required for normal glucose homeostasis. While key transcription factors that bind to the insulin promoter are known, relatively little is known about the upstream regulators of insulin transcription. Using a whole-genome RNA interference screen, we uncovered 26 novel regulators of insulin transcription that regulate diverse processes including oxidative phosphorylation, vesicle traffic, and the unfolded protein response (UPR). We focused on Spry2—a gene implicated in human type 2 diabetes by genome-wide association studies but without a clear connection to glucose homeostasis. We showed that Spry2 is a novel UPR target and its upregulation is dependent on PERK. Knockdown of Spry2 resulted in reduced expression of Serca2, reduced endoplasmic reticulum calcium levels, and induction of the UPR. Spry2 deletion in the adult mouse $\beta$-cell caused hyperglycemia and hypoinsulinemia. Our study greatly expands the compendium of insulin promoter regulators and demonstrates a novel $\beta$-cell link between Spry2 and human diabetes.},
author = {Pappalardo, Zachary and {Gambhir Chopra}, Deeksha and Hennings, Thomas G and Richards, Hunter and Choe, Justin and Yang, Katherine and Baeyens, Luc and Ang, Kenny and Chen, Steven and Arkin, Michelle and German, Michael S and McManus, Michael T and Ku, Gregory M},
doi = {10.2337/db16-0962},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Pappalardo et al. - 2017 - A Whole-Genome RNA Interference Screen Reveals a Role for emSpry2em in Insulin Transcription and the Unfolded.pdf:pdf},
journal = {Diabetes},
month = {jun},
number = {6},
pages = {1703 LP -- 1712},
title = {{A Whole-Genome RNA Interference Screen Reveals a Role for {\textless}em{\textgreater}Spry2{\textless}/em{\textgreater} in Insulin Transcription and the Unfolded Protein Response}},
url = {http://diabetes.diabetesjournals.org/content/66/6/1703.abstract},
volume = {66},
year = {2017}
}
@article{Mitchell2015a,
abstract = {Type 2 diabetes (T2D) is characterized by $\beta$ cell dysfunction and loss. Single nucleotide polymorphisms in the T-cell factor 7-like 2 (TCF7L2) gene, associated with T2D by genome-wide association studies, lead to impaired $\beta$ cell function. While deletion of the homologous murine Tcf7l2 gene throughout the developing pancreas leads to impaired glucose tolerance, deletion in the $\beta$ cell in adult mice reportedly has more modest effects. To inactivate Tcf7l2 highly selectively in $\beta$ cells from the earliest expression of the Ins1 gene (E11.5) we have therefore used a Cre recombinase introduced at the Ins1 locus. Tcfl2fl/fl::Ins1Cre mice display impaired oral and intraperitoneal glucose tolerance by 8 and 16 weeks, respectively, and defective responses to the GLP-1 analogue liraglutide at 8 weeks. Tcfl2fl/fl::Ins1Cre islets displayed defective glucose-and GLP-1-stimulated insulin secretion and the expression of both the Ins2 (20{\%}) and Glp1r (40{\%}) genes were significantly reduced. Glucose-and GLP-1-induced intracellular free Ca2+ increases, and connectivity between individual $\beta$ cells,were both lowered by Tcf7l2 deletion in islets from mice maintained on a high (60{\%}) fat diet. Finally, analysis by optical projection tomography revealed 30{\%} decrease in $\beta$ cell mass in pancreata from Tcfl2fl/fl::Ins1Cre mice. These data demonstrate that Tcf7l2 plays a cell autonomous role in the control of $\beta$ cell function and mass, serving as an important regulator of gene expression and islet cell coordination. The possible relevance of these findings for the action of TCF7L2 polymorphisms associated with Type 2 diabetes in man is discussed.},
author = {Mitchell, Ryan K. and Mondragon, Angeles and Chen, Lingling and Mcginty, James A. and French, Paul M. and Ferrer, Jorge and Thorens, Bernard and Hodson, David J. and Rutter, Guy A. and {Da Silva Xavier}, Gabriela},
doi = {10.1093/hmg/ddu553},
issn = {14602083},
journal = {Human Molecular Genetics},
title = {{Selective disruption of Tcf7l2 in the pancreatic $\beta$ cell impairs secretory function and lowers $\beta$ cell mass}},
year = {2015}
}
@article{Small2011,
abstract = {Genome-wide association studies have identified many genetic variants associated with complex traits. However, at only a minority of loci have the molecular mechanisms mediating these associations been characterized. In parallel, whereas cis regulatory patterns of gene expression have been extensively explored, the identification of trans regulatory effects in humans has attracted less attention. Here we show that the type 2 diabetes and high-density lipoprotein cholesterol-associated cis-acting expression quantitative trait locus (eQTL) of the maternally expressed transcription factor KLF14 acts as a master trans regulator of adipose gene expression. Expression levels of genes regulated by this trans-eQTL are highly correlated with concurrently measured metabolic traits, and a subset of the trans-regulated genes harbor variants directly associated with metabolic phenotypes. This trans-eQTL network provides a mechanistic understanding of the effect of the KLF14 locus on metabolic disease risk and offers a potential model for other complex traits.},
author = {Small, Kerrin S and Hedman, Asa K and Grundberg, Elin and Nica, Alexandra C and Thorleifsson, Gudmar and Kong, Augustine and Thorsteindottir, Unnur and Shin, So-Youn and Richards, Hannah B and Soranzo, Nicole and Ahmadi, Kourosh R and Lindgren, Cecilia M and Stefansson, Kari and Dermitzakis, Emmanouil T and Deloukas, Panos and Spector, Timothy D and McCarthy, Mark I},
doi = {10.1038/ng1011-1040c},
isbn = {1546-1718 (Electronic)$\backslash$r1061-4036 (Linking)},
issn = {1061-4036},
journal = {Nature genetics},
number = {6},
pages = {561--564},
pmid = {21572415},
title = {{Identification of an imprinted master trans regulator at the KLF14 locus related to multiple metabolic phenotypes.}},
volume = {43},
year = {2011}
}
@article{Ashcroft2017,
abstract = {Activating mutations in one of the two subunits of the ATP-sensitive potassium (KATP) channel cause neonatal diabetes (ND). This may be either transient or permanent and, in approximately 20{\%} of patients, is associated with neurodevelopmental delay. In most patients, switching from insulin to oral sulfonylurea therapy improves glycemic control and ameliorates some of the neurological disabilities. Here, we review how KATP channel mutations lead to the varied clinical phenotype, how sulfonylureas exert their therapeutic effects, and why their efficacy varies with individual mutations.},
author = {Ashcroft, Frances M and Puljung, Michael C and Vedovato, Natascia},
doi = {https://doi.org/10.1016/j.tem.2017.02.003},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Ashcroft, Puljung, Vedovato - 2017 - Neonatal Diabetes and the KATP Channel From Mutation to Therapy.pdf:pdf},
issn = {1043-2760},
journal = {Trends in Endocrinology {\&} Metabolism},
number = {5},
pages = {377--387},
title = {{Neonatal Diabetes and the KATP Channel: From Mutation to Therapy}},
url = {http://www.sciencedirect.com/science/article/pii/S104327601730019X},
volume = {28},
year = {2017}
}
@article{Yorifuji2005,
abstract = {Context: Known genes in maturity-onset diabetes of the young account for only a fraction of families with dominantly inherited diabetes in Japan. There should be as-yet-unidentified genes that account for the rest of the patients.Objective: To identify and characterize the mutation responsible for a Japanese family with dominantly inherited diabetes mellitus.Subjects: Members of a four-generation family with dominantly inherited diabetes mellitus observed in three generations. None of the patients in this family had permanent neonatal diabetes. One had transient neonatal diabetes, one had childhood diabetes, and the others had adult-onset diabetes without autoantibodies or insulin resistance.Methods: Screening of the chromosomal location of the gene by a genome-wide linkage analysis followed by candidate gene sequencing. Confirmation of the functional significance of the identified mutation by the population survey and the physiological analysis.Results: We identified a novel mutation (C42R) in the KCNJ11 gene coding for the Kir6.2 subunit of the pancreatic ATP-sensitive potassium channel. The patch-clamp experiments using the mutated KCNJ11 showed that the mutation causes increased spontaneous open probability and reduced ATP sensitivity. The effect, however, was partially compensated by the reduction of functional ATP-sensitive potassium channel expression at the cell surface, which could account for the milder phenotype of our patients.Conclusions: These results broaden the spectrum of diabetes phenotypes caused by mutations of KCNJ11 and suggest that mutations in this gene should be taken into consideration for not only permanent neonatal diabetes but also other forms of diabetes with milder phenotypes and later onset.},
author = {Yorifuji, Tohru and Nagashima, Kazuaki and Kurokawa, Keiji and Kawai, Masahiko and Oishi, Mariko and Akazawa, Yoshiharu and Hosokawa, Masaya and Yamada, Yuichiro and Inagaki, Nobuya and Nakahata, Tatsutoshi},
doi = {10.1210/jc.2005-0096},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Yorifuji et al. - 2005 - The C42R Mutation in the Kir6.2 (KCNJ11) Gene as a Cause of Transient Neonatal Diabetes, Childhood Diabetes, or.pdf:pdf},
issn = {0021-972X},
journal = {The Journal of Clinical Endocrinology {\&} Metabolism},
month = {jun},
number = {6},
pages = {3174--3178},
title = {{The C42R Mutation in the Kir6.2 (KCNJ11) Gene as a Cause of Transient Neonatal Diabetes, Childhood Diabetes, or Later-Onset, Apparently Type 2 Diabetes Mellitus}},
url = {https://doi.org/10.1210/jc.2005-0096},
volume = {90},
year = {2005}
}
@article{Giambartolomei2014b,
abstract = {Author Summary Genome-wide association studies (GWAS) have found a large number of genetic regions (“loci”) affecting clinical end-points and phenotypes, many outside coding intervals. One approach to understanding the biological basis of these associations has been to explore whether GWAS signals from intermediate cellular phenotypes, in particular gene expression, are located in the same loci (“colocalise”) and are potentially mediating the disease signals. However, it is not clear how to assess whether the same variants are responsible for the two GWAS signals or whether it is distinct causal variants close to each other. In this paper, we describe a statistical method that can use simply single variant summary statistics to test for colocalisation of GWAS signals. We describe one application of our method to a meta-analysis of blood lipids and liver expression, although any two datasets resulting from association studies can be used. Our method is able to detect the subset of GWAS signals explained by regulatory effects and identify candidate genes affected by the same GWAS variants. As summary GWAS data are increasingly available, applications of colocalisation methods to integrate the findings will be essential for functional follow-up, and will also be particularly useful to identify tissue specific signals in eQTL datasets.},
author = {Giambartolomei, Claudia and Vukcevic, Damjan and Schadt, Eric E and Franke, Lude and Hingorani, Aroon D and Wallace, Chris and Plagnol, Vincent},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Giambartolomei et al. - 2014 - Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics(3).pdf:pdf},
journal = {PLOS Genetics},
month = {may},
number = {5},
pages = {e1004383},
publisher = {Public Library of Science},
title = {{Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics}},
url = {https://doi.org/10.1371/journal.pgen.1004383},
volume = {10},
year = {2014}
}
@article{Xi2012,
abstract = {BACKGROUND: Genome-wide association studies on Europeans have shown that two polymorphisms (rs17782313, rs12970134) near the melanocortin 4 receptor (MC4R) gene were associated with increased risk of obesity. Subsequently studies among different ethnic populations have shown mixed results with some confirming and others showing inconsistent results, especially among East Asians and Africans. We performed a comprehensive meta-analysis of various studies from different ethnic populations to assess the association of the MC4R polymorphism with obesity risk. METHODS: We retrieved all published literature that investigated association of MC4R variants with obesity from PubMed and Embase. Pooled odds ratio (OR) with 95{\%} confidence interval (CI) was calculated using fixed- or random-effects model. RESULTS: A total of 61 studies (80,957 cases/220,223 controls) for rs17782313 polymorphism (or proxy) were included in the meta-analysis. The results suggested that rs17782313 polymorphism was significantly associated with obesity risk (OR=1.18, 95{\%}CI=1.15-1.21, p{\textless}0.001). Similar trends were observed among subgroups of Europeans and East Asians, adults and children, studies with high quality score, and for each five MC4R polymorphisms independently. CONCLUSIONS: The present meta-analysis confirms the significant association of MC4R polymorphism with risk of obesity. Further studies should be conducted to identify the causal variant and the underlying mechanisms of the identified association.},
author = {Xi, Bo and Chandak, Giriraj R and Shen, Yue and Wang, Qijuan and Zhou, Donghao},
doi = {10.1371/journal.pone.0045731},
edition = {2012/09/25},
issn = {1932-6203},
journal = {PloS one},
keywords = {*Polymorphism, Genetic,Adult,Body Weight,Case-Control Studies,Child,Female,Genetic Predisposition to Disease,Humans,Male,Middle Aged,Models, Statistical,Obesity/*genetics,Odds Ratio,Receptor, Melanocortin, Type 4/*genetics,Risk},
language = {eng},
number = {9},
pages = {e45731--e45731},
publisher = {Public Library of Science},
title = {{Association between common polymorphism near the MC4R gene and obesity risk: a systematic review and meta-analysis}},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23049848 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3458070/},
volume = {7},
year = {2012}
}
@article{Udler2018a,
abstract = {Using a clustering Bayesian approach applied to GWAS, Jose Florez and colleagues identify traits and loci associated with type 2 diabetes that may be used to classify patients.},
author = {Udler, Miriam S and Kim, Jaegil and von Grotthuss, Marcin and Bon{\`{a}}s-Guarch, S{\'{i}}lvia and Cole, Joanne B and Chiou, Joshua and and the ISGC, Christopher D Anderson on behalf of METASTROKE and Boehnke, Michael and Laakso, Markku and Atzmon, Gil and Glaser, Benjamin and Mercader, Josep M and Gaulton, Kyle and Flannick, Jason and Getz, Gad and Florez, Jose C},
file = {:home/jason/science/documents/articles/Udler{\_}2018{\_}PlosMed{\_}t2dPhys.pdf:pdf},
journal = {PLOS Medicine},
month = {sep},
number = {9},
pages = {e1002654},
publisher = {Public Library of Science},
title = {{Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis}},
url = {https://doi.org/10.1371/journal.pmed.1002654},
volume = {15},
year = {2018}
}
@article{Keaton2018,
abstract = {ABSTRACT Although type 2 diabetes (T2D) results from metabolic defects in insulin secretion and insulin sensitivity, most of the genetic risk loci identified to date relates to insulin secretion. We reported that T2D loci influencing insulin sensitivity may be identified through interactions with insulin secretion loci, thereby leading to T2D. Here, we hypothesize that joint testing of variant main effects and interaction effects with an insulin secretion locus increases power to identify genetic interactions leading to T2D. We tested this hypothesis with an intronic MTNR1B SNP, rs10830963, which is associated with acute insulin response to glucose, a dynamic measure of insulin secretion. rs10830963 was tested for interaction and joint (main + interaction) effects with genome-wide data in African Americans (2,452 cases and 3,772 controls) from five cohorts. Genome-wide genotype data (Affymetrix Human Genome 6.0 array) was imputed to a 1000 Genomes Project reference panel. T2D risk was modeled using logistic regression with rs10830963 dosage, age, sex, and principal component as predictors. Joint effects were captured using the Kraft two degrees of freedom test. Genome-wide significant (P {\textless} 5 ? 10?8) interaction with MTNR1B and joint effects were detected for CMIP intronic SNP rs17197883 (Pinteraction = 1.43 ? 10?8; Pjoint = 4.70 ? 10?8). CMIP variants have been nominally associated with T2D, fasting glucose, and adiponectin in individuals of East Asian ancestry, with high-density lipoprotein, and with waist-to-hip ratio adjusted for body mass index in Europeans. These data support the hypothesis that additional genetic factors contributing to T2D risk, including insulin sensitivity loci, can be identified through interactions with insulin secretion loci.},
annote = {doi: 10.1002/gepi.22126},
author = {Keaton, Jacob M and Gao, Chuan and Guan, Meijian and Hellwege, Jacklyn N and Palmer, Nicholette D and Pankow, James S and Fornage, Myriam and Wilson, James G and Correa, Adolfo and Rasmussen-Torvik, Laura J and Rotter, Jerome I and Chen, Yii-Der I and Taylor, Kent D and Rich, Stephen S and Wagenknecht, Lynne E and Freedman, Barry I and Ng, Maggie C Y and Bowden, Donald W},
doi = {10.1002/gepi.22126},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Keaton et al. - 2018 - Genome-wide interaction with the insulin secretion locus MTNR1B reveals CMIP as a novel type 2 diabetes susceptib.pdf:pdf},
issn = {0741-0395},
journal = {Genetic Epidemiology},
keywords = {gene–gene interactions,insulin resistance,insulin sensitivity},
month = {sep},
number = {6},
pages = {559--570},
publisher = {John Wiley {\&} Sons, Ltd},
title = {{Genome-wide interaction with the insulin secretion locus MTNR1B reveals CMIP as a novel type 2 diabetes susceptibility gene in African Americans}},
url = {https://doi.org/10.1002/gepi.22126},
volume = {42},
year = {2018}
}
@article{Thomsen2016a,
abstract = {Most genetic association signals for type 2 diabetes risk are located in noncoding regions of the genome, hindering translation into molecular mechanisms. Physiological studies have shown a majority of disease-associated variants to exert their effects through pancreatic islet dysfunction. Systematically characterizing the role of regional transcripts in $\beta$-cell function could identify the underlying disease-causing genes, but large-scale studies in human cellular models have previously been impractical. We developed a robust and scalable strategy based on arrayed gene silencing in the human $\beta$-cell line EndoC-$\beta$H1. In a screen of 300 positional candidates selected from 75 type 2 diabetes regions, each gene was assayed for effects on multiple disease–relevant phenotypes, including insulin secretion and cellular proliferation. We identified a total of 45 genes involved in $\beta$-cell function, pointing to possible causal mechanisms at 37 disease-associated loci. The results showed a strong enrichment for genes implicated in monogenic diabetes. Selected effects were validated in a follow-up study, including several genes (ARL15, ZMIZ1, and THADA) with previously unknown or poorly described roles in $\beta$-cell biology. We have demonstrated the feasibility of systematic functional screening in a human $\beta$-cell model and successfully prioritized plausible disease-causing genes at more than half of the regions investigated.},
author = {Thomsen, Soren K and Ceroni, Alessandro and van de Bunt, Martijn and Burrows, Carla and Barrett, Amy and Scharfmann, Raphael and Ebner, Daniel and McCarthy, Mark I and Gloyn, Anna L},
doi = {10.2337/db16-0361},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Thomsen et al. - 2016 - Systematic Functional Characterization of Candidate Causal Genes for Type 2 Diabetes Risk Variants(2).pdf:pdf},
journal = {Diabetes},
month = {dec},
number = {12},
pages = {3805 LP -- 3811},
title = {{Systematic Functional Characterization of Candidate Causal Genes for Type 2 Diabetes Risk Variants}},
url = {http://diabetes.diabetesjournals.org/content/65/12/3805.abstract},
volume = {65},
year = {2016}
}
@article{Shao2015,
abstract = {OBJECTIVE: Disruption of TCF7L2 in mouse pancreatic $\beta$-cells has generated different outcomes in several investigations. Here we aim to clarify role of $\beta$-cell TCF7L2 and Wnt signaling using a functional-knockdown approach. METHODS: Adenovirus-mediated dominant negative TCF7L2 (TCF7L2DN) expression was conducted in Ins-1 cells. The fusion gene in which TCF7L2DN expression is driven by P TRE3G was utilized to generate the transgenic mouse line TCF7L2DN Tet . The double transgenic line was created by mating TCF7L2DN Tet with Ins2-rtTA, designated as $\beta$TCFDN. $\beta$-cell specific TCF7L2DN expression was induced in $\beta$TCFDN by doxycycline feeding. RESULTS: TCF7L2DN expression in Ins-1 cells reduced GSIS, cell proliferation and expression of a battery of genes including incretin receptors and $\beta$-cell transcription factors. Inducing TCF7L2DN expression in $\beta$TCFDN during adulthood or immediately after weaning generated no or very modest metabolic defect, while its expression during embryonic development by doxycycline feeding in pregnant mothers resulted in significant glucose intolerance associated with altered $\beta$-cell gene expression and reduced $\beta$-cell mass. CONCLUSIONS: Our observations support a cell autonomous role for TCF7L2 in pancreatic $\beta$-cells suggested by most, though not all, investigations. $\beta$TCFDN is a novel model for further exploring the role of TCF7L2 in $\beta$-cell genesis and metabolic homeostasis.},
author = {Shao, Weijuan and Xiong, Xiaoquan and Ip, Wilfred and Xu, Fenghao and Song, Zhuolun and Zeng, Kejing and Hernandez, Marcela and Liang, Tao and Weng, Jianping and Gaisano, Herbert and Nostro, M Cristina and Jin, Tianru},
doi = {10.1016/j.molmet.2015.01.008},
issn = {2212-8778},
journal = {Molecular metabolism},
keywords = {GLP-1,GSIS,Incretin receptors,Pancreatic $\beta$-cells,TCF7L2,TCF7L2DN,Wnt},
language = {eng},
month = {feb},
number = {4},
pages = {344--352},
publisher = {Elsevier},
title = {{The expression of dominant negative TCF7L2 in pancreatic beta cells during the embryonic stage causes impaired glucose homeostasis}},
url = {https://www.ncbi.nlm.nih.gov/pubmed/25830097 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354927/},
volume = {4},
year = {2015}
}
@article{VandeBunt2015,
abstract = {Author Summary Genetic studies have uncovered many different parts of the genome playing a role in the risk of developing diabetes, or affecting blood sugar levels in the normal population. However, it has so far been difficult to tie these parts of the genome to genes that are responsible for the observed changes in risk and/or blood sugar levels (“effector transcripts”). It is clear from the genetic data that one of the key tissues in these phenotypes is the human pancreatic islet of Langerhans, but the limited availability of this tissue has been a major hurdle in translating the genetics into biology. Here, we present a study linking genetic variation to gene expression changes in 118 islet preparations. Using these cis-eQTLs, we provide candidate effector transcripts at 14 regions of the genome previously associated with glucose phenotypes. Many of the genes implicated through this approach have no known role in the islet. By experimentally changing the expression levels of one of these novel genes, ZMIZ1, in human islets and beta-cells, we uncovered a novel role for ZMIZ1 in exocytosis and insulin secretion. These findings therefore significantly improve the discovery of biology underlying type 2 diabetes and glucose trait association.},
annote = {118 human islets (RNA-seq) 

14 loci with cis-exon-eQTL overlapped T2D/glycemic trait associations 
links betwen GWAS signals and biological candidates; DGKB and ADCY5 

Novel genes, WARS and ZMIZ1 

ZMIZ1 perturbation of expression in human islets --{\textgreater} exocytosis and insulin secretion (novel role) 

genetic studies have uncovered many different parts of genome playing role in risk of T2D or blood sugar; difficult to tie to genes responsible for observed risk ("effector transcripts"). 

Islets important but limited availability; provide candidate effector transcripts at 14 regions of the genome previously associated with glucose phenotypes; novel genes; ZMIZ1 experimentally validated 

Introduction 

80 loci T2D, 70 loci continuous glycemic traits in non-diabetic subjects 
substantial but not nearly complete, physiological studies suggest that most of these loci influence insulin secretion rather than insulin sensitivity; highlighting key role for pancreatic islets of Langerhans in the mechanistic underpinnings of signals 

GWAS signals (T2D/glyc) enriched at islet enhancers 

cis-eQTLs --{\textgreater} implicate effector transcripts and supply direction of effect

Results 

europeon descent (Oxford [n=40], Edmonton [n=78]) 
Illumina HiSeq2000 platform
72 M reads per sample uniquely mapping to exons; GENCODE v18 transcriptome reference
Genotypes Ill. HumanOmni2.5-Exome array (2.5 M SNPs); 1K G imputation 38M SNPs 
exon-level eQTLs; 15 PEER factors; exon counts normalized ; 
all variatns within 1Mb of TSS were tested 
2,341 genes with one exon meeting q-vaue threshold

90{\%} of sig. islet exon-eQTLs w/n 250 kb of the TSS 
735/2341 (31{\%}) SNPS overlapped enhancer or promoter signatures in islet --{\textgreater} 59{\%} overlapped enhancers/promoters

Substantial sharing of islet-exon eQTLs across the full range of GTEx p-values (70{\%} replicaton rate); 309 exons with an islet exon-eQTL not shared in 9 other tissues from GTEx (19{\%}) 

GWAS loci 

Evaluated co-localization with 82 known common variant T2D loci and 49 loci for glycemic traits where Beta cell thought to be main driver (FG, FPI, 2-hour glucose, HOMA-B, insulinogenic index, disposition index, corrected insulin resonse); 17 overlap T2D whereas otehr 32 are independent; 

Strong LD co-localized ( r2{\textgreater}0.8) ; conditional analysis regressing out GWAS variant from eQTL association 

Over 90{\%} of the exon-eQTLs for these genes were statistically independent of the GWAS signal, but 9 (marked by 11 GWAS index variants) met the LD criterion and conditional analysis 

included 10 cis-eQTL where eQTLs were nominally significant 
21 SNPs distributed over 16 loci 

Colocalization at loci for both T2D/gly (ADCY5, ARAP1, DGKB, MTNR1B) 
T2D only (AP3S2, CDC123/CAMK1D, TMEM163, ZMIZ1) 
Remaining 6, glycemic traits 
(AMT, ANK1, FADS1, MADD, PCSK1, WARS) 

Support for strong bio candidates 
ADCY5, DGKB, FADS1,; 
ADCY5, risk allele lower expression, adenylate cyclase family; couples glucose stimulation to insulin secretion; disrupted upon gene knockdown

Two indendent T2D signals at DGKB, both also with raised FG and reduced HOMA-B in non-diabetic; subunit of diacylglycerol kinase, regulator of glucose-responsive secondary messenger diacylglycerol

FADS1, raised FG, risk allele increased islet expression; delta-5 fatty acid desaturase, biosynthesis of highly unsaturated fatty acids 

MTNR1B, t2D risk allele substantial impact on continuous glycemic traits (higher fasting glucose, lower HOMA-B, corr. ins. response. allele assoc with increased expression of melatonin receptor 1B 

At CDC123/CAMK1D (calcium/calmodulin-dependent protein kinase 1D) support CAMK1D as likely effector; T2D-risk allele increased transcription activity in a luceriferasreporter system

While single effector transcript was involved in examples above, less conclusive at other loci, 

Data supports STARD10 over ARAP1 locus; StAR-related lipid transfer (START) domain containing 10, regulation of bile acid metabolism; no reported role in islets

AP3S2 - 

MADD (FG, Ins. processing) MAP-kinase activating death domain, ACP2,

NOvel genes 

WARS (FG raising allele) reduced WARS expression; no known previously role for WARS in pancreatic islet function

ZMIZ1 zinc finger, MIZ-type containing 1, 
overexpression perturbation affects glucose-stimulated- insulin secretion; reduced insulin exocytosis in individual human beta-cells to 29{\%} of},
author = {van de Bunt, Martijn and {Manning Fox}, Jocelyn E and Dai, Xiaoqing and Barrett, Amy and Grey, Caleb and Li, Lei and Bennett, Amanda J and Johnson, Paul R and Rajotte, Raymond V and Gaulton, Kyle J and Dermitzakis, Emmanouil T and MacDonald, Patrick E and McCarthy, Mark I and Gloyn, Anna L},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/van de Bunt et al. - 2015 - Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies f.pdf:pdf},
journal = {PLOS Genetics},
month = {dec},
number = {12},
pages = {e1005694},
publisher = {Public Library of Science},
title = {{Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors}},
url = {https://doi.org/10.1371/journal.pgen.1005694},
volume = {11},
year = {2015}
}
@article{Thurner2018,
abstract = {Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.},
author = {Thurner, Matthias and van de Bunt, Martijn and Torres, Jason M. and Mahajan, Anubha and Nylander, Vibe and Bennett, Amanda J. and Gaulton, Kyle J. and Barrett, Amy and Burrows, Carla and Bell, Christopher G. and Lowe, Robert and Beck, Stephan and Rakyan, Vardhman K. and Gloyn, Anna L. and McCarthy, Mark I.},
doi = {10.7554/eLife.31977},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Thurner et al. - 2018 - Integration of human pancreatic islet genomic data refines regulatory mechanisms at type 2 diabetes susceptibili.pdf:pdf},
issn = {2050084X},
journal = {eLife},
title = {{Integration of human pancreatic islet genomic data refines regulatory mechanisms at type 2 diabetes susceptibility loci}},
year = {2018}
}
@article{DeFronzo2009a,
abstract = {Insulin resistance in muscle and liver and $\beta$-cell failure represent the core pathophysiologic defects in type 2 diabetes. It now is recognized that the $\beta$-cell failure occurs much earlier and is more severe than previously thought. Subjects in the upper tertile of impaired glucose tolerance (IGT) are maximally/near-maximally insulin resistant and have lost over 80{\%} of their $\beta$-cell function. In addition to the muscle, liver, and $\beta$-cell (triumvirate), the fat cell (accelerated lipolysis), gastrointestinal tract (incretin deficiency/resistance), $\alpha$-cell (hyperglucagonemia), kidney (increased glucose reabsorption), and brain (insulin resistance) all play important roles in the development of glucose intolerance in type 2 diabetic individuals. Collectively, these eight players comprise the ominous octet and dictate that: 1) multiple drugs used in combination will be required to correct the multiple pathophysiological defects, 2) treatment should be based upon reversal of known pathogenic abnormalities and not simply on reducing the A1C, and 3) therapy must be started early to prevent/slow the progressive $\beta$-cell failure that already is well established in IGT subjects. A treatment paradigm shift is recommended in which combination therapy is initiated with diet/exercise, metformin (which improves insulin sensitivity and has antiatherogenic effects), a thiazolidinedione (TZD) (which improves insulin sensitivity, preserves $\beta$-cell function, and exerts antiatherogenic effects), and exenatide (which preserves $\beta$-cell function and promotes weight loss). Sulfonylureas are not recommended because, after an initial improvement in glycemic control, they are associated with a progressive rise in A1C and progressive loss of $\beta$-cell function.},
author = {DeFronzo, Ralph A.},
doi = {doi: 10.2337/db09-9028},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/DeFronzo - 2009 - From the Triumvirate to the Ominous Octet A New Paradigm for the Treatment of Type 2 Diabetes Mellitus.pdf:pdf},
isbn = {1939-327X (Electronic)$\backslash$n0012-1797 (Linking)},
issn = {1939-327X},
journal = {Diabetes Care},
number = {4},
pages = {773--795},
pmid = {19336687},
title = {{From the Triumvirate to the Ominous Octet: A New Paradigm for the Treatment of Type 2 Diabetes Mellitus}},
volume = {58},
year = {2009}
}
@article{Lubrano-Berthelier2004,
abstract = {As a mediator of the effects of leptin, the melanocortin-4 receptor (MC4R) is an essential component of the central regulation of long-term energy homeostasis. Heterozygous mutations in this receptor are the most frequent genetic cause of severe obesity in children. The very rare described carriers of homozygous MC4R mutations for whom clinical data were available had a residual receptor activity thus not allowing for the description of the full extent of the role of MC4R in humans. Here, we present the clinical and biological features of a patient with complete absence of MC4R activity and compare the clinical and endocrine characteristics of this patient with those previously observed in leptin receptor-deficient patients. Our data suggest that in humans, the MC4R mediates most of the anorectic effects of leptin in early childhood. In contrast, MC4R does not mediate the effect of leptin on linear growth and other endocrine axes. In addition, complete MC4R deficiency is not a cause of relative hyperinsulinemia as recently observed in children with heterozygous MC4R mutations.},
author = {Lubrano-Berthelier, Cécile and {Le Stunff}, Catherine and Bougnères, Pierre and Vaisse, Christian},
doi = {10.1210/jc.2003-031993},
issn = {0021-972X},
journal = {The Journal of Clinical Endocrinology {\&} Metabolism},
month = {may},
number = {5},
pages = {2028--2032},
title = {{A Homozygous Null Mutation Delineates the Role of the Melanocortin-4 Receptor in Humans}},
url = {https://doi.org/10.1210/jc.2003-031993},
volume = {89},
year = {2004}
}
@article{Farooqi2003,
annote = {doi: 10.1056/NEJMoa022050},
author = {Farooqi, I Sadaf and Keogh, Julia M and Yeo, Giles S H and Lank, Emma J and Cheetham, Tim and O'Rahilly, Stephen},
doi = {10.1056/NEJMoa022050},
issn = {0028-4793},
journal = {New England Journal of Medicine},
month = {mar},
number = {12},
pages = {1085--1095},
publisher = {Massachusetts Medical Society},
title = {{Clinical Spectrum of Obesity and Mutations in the Melanocortin 4 Receptor Gene}},
url = {https://doi.org/10.1056/NEJMoa022050},
volume = {348},
year = {2003}
}
@article{DaSilvaXavier2009a,
abstract = {OBJECTIVE-Polymorphisms in the human TCF7L2 gene are associated with reduced insulin secretion and an increased risk of type 2 diabetes. However, the mechanisms by which TCF7L2 affect insulin secretion are still unclear. We define the effects of TCF7L2 expression level on mature $\beta$-cell function and suggest a potential mechanism for its actions. RESEARCH DESIGN AND METHODS-TCF7L2 expression in rodent islets and $\beta$-cell lines was altered using RNAi or adenoviral transduction. $\beta$-Cell gene profiles were measured by quantitative real-time PCR and the effects on intracellular signaling and exocytosis by live cell imaging, electron microscopy, and patch clamp electrophysiology. RESULTS-Reducing TCF7L2 expression levels by RNAi decreased glucose- but not KCl-induced insulin secretion. The glucose-induced increments in both ATP/ADP ratio and cytosolic free Ca2+ concentration ([Ca 2+]i) were increased compared with controls. Overexpression of TCF7L2 exerted minor inhibitory effects on glucose-regulated changes in [Ca 2+]i and insulin release. Gene expression profiling in TCF7L2-silenced cells revealed increased levels of mRNA encoding syntaxin 1A but decreased Munc18-1 and ZnT8 mRNA. Whereas the number of morphologically docked vesicles was unchanged by TCF7L2 suppression, secretory granule movement increased and capacitance changes decreased, indicative of defective vesicle fusion. CONCLUSION-TCF7L2 is involved in maintaining expression of $\beta$-cell genes regulating secretory granule fusion. Defective insulin exocytosis may thus underlie increased diabetes incidence in carriers of the at-risk TCF7L2 alleles. {\textcopyright} 2009 by the American Diabetes Association.},
author = {{Da Silva Xavier}, Gabriela and Loder, Merewyn K. and McDonald, Angela and Tarasov, Andrei I. and Carzaniga, Raffaella and Kronenberger, Katrin and Barg, Sebastian and Rutter, Guy A.},
doi = {10.2337/db08-1187},
issn = {00121797},
journal = {Diabetes},
title = {{TCF7L2 regulates late events in insulin secretion from pancreatic islet $\beta$-cells}},
year = {2009}
}
@article{Fan1997,
author = {Fan, W and Boston, B A and Kesterson, R A and Hruby, V J and Cone, R D},
journal = {Nature},
pages = {165--168},
title = {{Role of melanocortinergic neurons in feeding and the agouti obesity syndrome}},
volume = {385},
year = {1997}
}
@article{RoadmapEpigenomicsConsortium2015,
abstract = {The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.},
annote = {ERM 2015; disease- and trai- associated geentic variants are enriched in tissue-specific epigenomic marks, --{\textgreater}},
author = {{Roadmap Epigenomics Consortium} and Kundaje, Anshul and Meuleman, Wouter and Ernst, Jason and Bilenky, Misha and Yen, Angela and Heravi-Moussavi, Alireza and Kheradpour, Pouya and Zhang, Zhizhuo and Wang, Jianrong and Ziller, Michael J and Amin, Viren and Whitaker, John W and Schultz, Matthew D and Ward, Lucas D and Sarkar, Abhishek and Quon, Gerald and Sandstrom, Richard S and Eaton, Matthew L and Wu, Yi-Chieh and Pfenning, Andreas R and Wang, Xinchen and Claussnitzer, Melina and Liu, Yaping and Coarfa, Cristian and Harris, R Alan and Shoresh, Noam and Epstein, Charles B and Gjoneska, Elizabeta and Leung, Danny and Xie, Wei and Hawkins, R David and Lister, Ryan and Hong, Chibo and Gascard, Philippe and Mungall, Andrew J and Moore, Richard and Chuah, Eric and Tam, Angela and Canfield, Theresa K and Hansen, R Scott and Kaul, Rajinder and Sabo, Peter J and Bansal, Mukul S and Carles, Annaick and Dixon, Jesse R and Farh, Kai-How and Feizi, Soheil and Karlic, Rosa and Kim, Ah-Ram and Kulkarni, Ashwinikumar and Li, Daofeng and Lowdon, Rebecca and Elliott, GiNell and Mercer, Tim R and Neph, Shane J and Onuchic, Vitor and Polak, Paz and Rajagopal, Nisha and Ray, Pradipta and Sallari, Richard C and Siebenthall, Kyle T and Sinnott-Armstrong, Nicholas A and Stevens, Michael and Thurman, Robert E and Wu, Jie and Zhang, Bo and Zhou, Xin and Beaudet, Arthur E and Boyer, Laurie A and {De Jager}, Philip L and Farnham, Peggy J and Fisher, Susan J and Haussler, David and Jones, Steven J M and Li, Wei and Marra, Marco A and McManus, Michael T and Sunyaev, Shamil and Thomson, James A and Tlsty, Thea D and Tsai, Li-Huei and Wang, Wei and Waterland, Robert A and Zhang, Michael Q and Chadwick, Lisa H and Bernstein, Bradley E and Costello, Joseph F and Ecker, Joseph R and Hirst, Martin and Meissner, Alexander and Milosavljevic, Aleksandar and Ren, Bing and Stamatoyannopoulos, John A and Wang, Ting and Kellis, Manolis and Consortium, Roadmap Epigenomics},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Roadmap Epigenomics Consortium et al. - 2015 - Integrative analysis of 111 reference human epigenomes.pdf:pdf},
issn = {0028-0836},
journal = {Nature},
month = {feb},
number = {7539},
pages = {317--330},
publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
title = {{Integrative analysis of 111 reference human epigenomes}},
url = {http://dx.doi.org/10.1038/nature14248 http://10.0.4.14/nature14248 http://www.nature.com/nature/journal/v518/n7539/abs/nature14248.html{\#}supplementary-information},
volume = {518},
year = {2015}
}
@article{Gloyn2004,
annote = {doi: 10.1056/NEJMoa032922},
author = {Gloyn, Anna L and Pearson, Ewan R and Antcliff, Jennifer F and Proks, Peter and Bruining, G Jan and Slingerland, Annabelle S and Howard, Neville and Srinivasan, Shubha and Silva, Jos{\'{e}} M C L and Molnes, Janne and Edghill, Emma L and Frayling, Timothy M and Temple, I Karen and Mackay, Deborah and Shield, Julian P H and Sumnik, Zdenek and van Rhijn, Adrian and Wales, Jerry K H and Clark, Penelope and Gorman, Shaun and Aisenberg, Javier and Ellard, Sian and Nj{\o}lstad, P{\aa}l R and Ashcroft, Frances M and Hattersley, Andrew T},
doi = {10.1056/NEJMoa032922},
issn = {0028-4793},
journal = {New England Journal of Medicine},
month = {apr},
number = {18},
pages = {1838--1849},
publisher = {Massachusetts Medical Society},
title = {{Activating Mutations in the Gene Encoding the ATP-Sensitive Potassium-Channel Subunit Kir6.2 and Permanent Neonatal Diabetes}},
url = {http://dx.doi.org/10.1056/NEJMoa032922},
volume = {350},
year = {2004}
}
@article{Gaulton2015a,
abstract = {We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.},
author = {Gaulton, Kyle J. and Ferreira, Teresa and Lee, Yeji and Raimondo, Anne and M{\"{a}}gi, Reedik and Reschen, Michael E. and Mahajan, Anubha and Locke, Adam and Rayner, N. William and Robertson, Neil and Scott, Robert A. and Prokopenko, Inga and Scott, Laura J. and Green, Todd and Sparso, Thomas and Thuillier, Dorothee and Yengo, Loic and Grallert, Harald and Wahl, Simone and Fr{\aa}nberg, Mattias and Strawbridge, Rona J. and Kestler, Hans and Chheda, Himanshu and Eisele, Lewin and Gustafsson, Stefan and Steinthorsdottir, Valgerdur and Thorleifsson, Gudmar and Qi, Lu and Karssen, Lennart C. and {Van Leeuwen}, Elisabeth M. and Willems, Sara M. and Li, Man and Chen, Han and Fuchsberger, Christian and Kwan, Phoenix and Ma, Clement and Linderman, Michael and Lu, Yingchang and Thomsen, Soren K. and Rundle, Jana K. and Beer, Nicola L. and {Van De Bunt}, Martijn and Chalisey, Anil and Kang, Hyun Min and Voight, Benjamin F. and Abecasis, Gon{\c{c}}alo R. and Almgren, Peter and Baldassarre, Damiano and Balkau, Beverley and Benediktsson, Rafn and Bl{\"{u}}her, Matthias and Boeing, Heiner and Bonnycastle, Lori L. and Bottinger, Erwin P. and Burtt, No{\"{e}}l P. and Carey, Jason and Charpentier, Guillaume and Chines, Peter S. and Cornelis, Marilyn C. and Couper, David J. and Crenshaw, Andrew T. and {Van Dam}, Rob M. and Doney, Alex S.F. and Dorkhan, Mozhgan and Edkins, Sarah and Eriksson, Johan G. and Esko, Tonu and Eury, Elodie and Fadista, Jo{\~{a}}o and Flannick, Jason and Fontanillas, Pierre and Fox, Caroline and Franks, Paul W. and Gertow, Karl and Gieger, Christian and Gigante, Bruna and Gottesman, Omri and Grant, George B. and Grarup, Niels and Groves, Christopher J. and Hassinen, Maija and Have, Christian T. and Herder, Christian and Holmen, Oddgeir L. and Hreidarsson, Astradur B. and Humphries, Steve E. and Hunter, David J. and Jackson, Anne U. and Jonsson, Anna and J{\o}rgensen, Marit E. and J{\o}rgensen, Torben and Kao, Wen Hong L. and Kerrison, Nicola D. and Kinnunen, Leena and Klopp, Norman and Kong, Augustine and Kovacs, Peter and Kraft, Peter and Kravic, Jasmina and Langford, Cordelia and Leander, Karin and Liang, Liming and Lichtner, Peter and Lindgren, Cecilia M. and Lindholm, Eero and Linneberg, Allan and Liu, Ching Ti and Lobbens, St{\'{e}}phane and Luan, Jian'fan and Lyssenko, Valeriya and M{\"{a}}nnist{\"{o}}, Satu and McLeod, Olga and Meyer, Julia and Mihailov, Evelin and Mirza, Ghazala and M{\"{u}}hleisen, Thomas W. and M{\"{u}}ller-Nurasyid, Martina and Navarro, Carmen and N{\"{o}}then, Markus M. and Oskolkov, Nikolay N. and Owen, Katharine R. and Palli, Domenico and Pechlivanis, Sonali and Peltonen, Leena and Perry, John R.B. and Platou, Carl G.P. and Roden, Michael and Ruderfer, Douglas and Rybin, Denis and {Van Der Schouw}, Yvonne T. and Sennblad, Bengt and Sigurosson, Gunnar and Stan{\v{c}}{\'{a}}kov{\'{a}}, Alena and Steinbach, Gerald and Storm, Petter and Strauch, Konstantin and Stringham, Heather M. and Sun, Qi and Thorand, Barbara and Tikkanen, Emmi and Tonjes, Anke and Trakalo, Joseph and Tremoli, Elena and Tuomi, Tiinamaija and Wennauer, Roman and Wiltshire, Steven and Wood, Andrew R. and Zeggini, Eleftheria and Dunham, Ian and Birney, Ewan and Pasquali, Lorenzo and Ferrer, Jorge and Loos, Ruth J.F. and Dupuis, Jos{\'{e}}e and Florez, Jose C. and Boerwinkle, Eric and Pankow, James S. and {Van Duijn}, Cornelia and Sijbrands, Eric and Meigs, James B. and Hu, Frank B. and Thorsteinsdottir, Unnur and Stefansson, Kari and Lakka, Timo A. and Rauramaa, Rainer and Stumvoll, Michael and Pedersen, Nancy L. and Lind, Lars and Keinanen-Kiukaanniemi, Sirkka M. and Korpi-Hy{\"{o}}v{\"{a}}lti, Eeva and Saaristo, Timo E. and Saltevo, Juha and Kuusisto, Johanna and Laakso, Markku and Metspalu, Andres and Erbel, Raimund and J{\"{o}}ckel, Karl Heinz and Moebus, Susanne and Ripatti, Samuli and Salomaa, Veikko and Ingelsson, Erik and Boehm, Bernhard O. and Bergman, Richard N. and Collins, Francis S. and Mohlke, Karen L. and Koistinen, Heikki and Tuomilehto, Jaakko and Hveem, Kristian and Nj{\o}lstad, Inger and Deloukas, Panagiotis and Donnelly, Peter J. and Frayling, Timothy M. and Hattersley, Andrew T. and {De Faire}, Ulf and Hamsten, Anders and Illig, Thomas and Peters, Annette and Cauchi, Stephane and Sladek, Rob and Froguel, Philippe and Hansen, Torben and Pedersen, Oluf and Morris, Andrew D. and Palmer, Collin N.A. and Kathiresan, Sekar and Melander, Olle and Nilsson, Peter M. and Groop, Leif C. and Barroso, In{\^{e}}s and Langenberg, Claudia and Wareham, Nicholas J. and O'Callaghan, Christopher A. and Gloyn, Anna L. and Altshuler, David and Boehnke, Michael and Teslovich, Tanya M. and McCarthy, Mark I. and Morris, Andrew P.},
doi = {10.1038/ng.3437},
file = {:home/jason/Downloads/Genetic{\_}fine{\_}mapping{\_}and{\_}genomic{\_}annotat.pdf:pdf},
issn = {15461718},
journal = {Nature Genetics},
title = {{Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci}},
year = {2015}
}
@article{Morris2012c,
abstract = {To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis. {\textcopyright} 2012 Nature America, Inc. All rights reserved.},
author = {Morris, Andrew P. and Voight, Benjamin F. and Teslovich, Tanya M. and Ferreira, Teresa and Segr{\`{e}}, Ayellet V. and Steinthorsdottir, Valgerdur and Strawbridge, Rona J. and Khan, Hassan and Grallert, Harald and Mahajan, Anubha and Prokopenko, Inga and Kang, Hyun Min and Dina, Christian and Esko, Tonu and Fraser, Ross M. and Kanoni, Stavroula and Kumar, Ashish and Lagou, Vasiliki and Langenberg, Claudia and Luan, Jian'An and Lindgren, Cecilia M. and M{\"{u}}ller-Nurasyid, Martina and Pechlivanis, Sonali and Rayner, N. William and Scott, Laura J. and Wiltshire, Steven and Yengo, Loic and Kinnunen, Leena and Rossin, Elizabeth J. and Raychaudhuri, Soumya and Johnson, Andrew D. and Dimas, Antigone S. and Loos, Ruth J.F. and Vedantam, Sailaja and Chen, Han and Florez, Jose C. and Fox, Caroline and Liu, Ching Ti and Rybin, Denis and Couper, David J. and Kao, Wen Hong L. and Li, Man and Cornelis, Marilyn C. and Kraft, Peter and Sun, Qi and {Van Dam}, Rob M. and Stringham, Heather M. and Chines, Peter S. and Fischer, Krista and Fontanillas, Pierre and Holmen, Oddgeir L. and Hunt, Sarah E. and Jackson, Anne U. and Kong, Augustine and Lawrence, Robert and Meyer, Julia and Perry, John R.B. and Platou, Carl G.P. and Potter, Simon and Rehnberg, Emil and Robertson, Neil and Sivapalaratnam, Suthesh and Stan{\v{c}}{\'{a}}kov{\'{a}}, Alena and Stirrups, Kathleen and Thorleifsson, Gudmar and Tikkanen, Emmi and Wood, Andrew R. and Almgren, Peter and Atalay, Mustafa and Benediktsson, Rafn and Bonnycastle, Lori L. and Burtt, No{\"{e}}l and Carey, Jason and Charpentier, Guillaume and Crenshaw, Andrew T. and Doney, Alex S.F. and Dorkhan, Mozhgan and Edkins, Sarah and Emilsson, Valur and Eury, Elodie and Forsen, Tom and Gertow, Karl and Gigante, Bruna and Grant, George B. and Groves, Christopher J. and Guiducci, Candace and Herder, Christian and Hreidarsson, Astradur B. and Hui, Jennie and James, Alan and Jonsson, Anna and Rathmann, Wolfgang and Klopp, Norman and Kravic, Jasmina and Krjut{\v{s}}kov, Kaarel and Langford, Cordelia and Leander, Karin and Lindholm, Eero and Lobbens, St{\'{e}}phane and M{\"{a}}Nnist{\"{o}}, Satu and Mirza, Ghazala and M{\"{u}}Hleisen, Thomas W. and Musk, Bill and Parkin, Melissa and Rallidis, Loukianos and Saramies, Jouko and Sennblad, Bengt and Shah, Sonia and Sigursson, Gunnar and Silveira, Angela and Steinbach, Gerald and Thorand, Barbara and Trakalo, Joseph and Veglia, Fabrizio and Wennauer, Roman and Winckler, Wendy and Zabaneh, Delilah and Campbell, Harry and {Van Duijn}, Cornelia and Uitterlinden, Andre G. and Hofman, Albert and Sijbrands, Eric and Abecasis, Goncalo R. and Owen, Katharine R. and Zeggini, Eleftheria and Trip, Mieke D. and Forouhi, Nita G. and Syv{\"{a}}nen, Ann Christine and Eriksson, Johan G. and Peltonen, Leena and N{\"{o}}then, Markus M. and Balkau, Beverley and Palmer, Colin N.A. and Lyssenko, Valeriya and Tuomi, Tiinamaija and Isomaa, Bo and Hunter, David J. and Qi, Lu and Shuldiner, Alan R. and Roden, Michael and Barroso, Ines and Wilsgaard, Tom and Beilby, John and Hovingh, Kees and Price, Jackie F. and Wilson, James F. and Rauramaa, Rainer and Lakka, Timo A. and Lind, Lars and Dedoussis, George and Nj{\o}Lstad, Inger and Pedersen, Nancy L. and Khaw, Kay Tee and Wareham, Nicholas J. and Keinanen-Kiukaanniemi, Sirkka M. and Saaristo, Timo E. and Korpi-Hy{\"{o}}V{\"{a}}Lti, Eeva and Saltevo, Juha and Laakso, Markku and Kuusisto, Johanna and Metspalu, Andres and Collins, Francis S. and Mohlke, Karen L. and Bergman, Richard N. and Tuomilehto, Jaakko and Boehm, Bernhard O. and Gieger, Christian and Hveem, Kristian and Cauchi, Stephane and Froguel, Philippe and Baldassarre, Damiano and Tremoli, Elena and Humphries, Steve E. and Saleheen, Danish and Danesh, John and Ingelsson, Erik and Ripatti, Samuli and Salomaa, Veikko and Erbel, Raimund and J{\"{o}}Ckel, Karl Heinz and Moebus, Susanne and Peters, Annette and Illig, Thomas and Faire, Ulf De and Hamsten, Anders and Morris, Andrew D. and Donnelly, Peter J. and Frayling, Timothy M. and Hattersley, Andrew T. and Boerwinkle, Eric and Melander, Olle and Kathiresan, Sekar and Nilsson, Peter M. and Deloukas, Panos and Thorsteinsdottir, Unnur and Groop, Leif C. and Stefansson, Kari and Hu, Frank and Pankow, James S. and Dupuis, Jos{\'{e}}e and Meigs, James B. and Altshuler, David and Boehnke, Michael and McCarthy, Mark I.},
doi = {10.1038/ng.2383},
file = {:home/jason/Downloads/Large-Scale{\_}Association{\_}Analysis{\_}Provide.pdf:pdf},
issn = {10614036},
journal = {Nature Genetics},
title = {{Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes}},
year = {2012}
}
@article{Koster2008,
abstract = {CONTEXT: Mutations in the Kir6.2 subunit (KCNJ11) of the ATP-sensitive potassium channel (KATP) underlie neonatal diabetes mellitus. In severe cases, Kir6.2 mutations underlie developmental delay, epilepsy, and neonatal diabetes (DEND). All Kir6.2 mutations examined decrease the ATP inhibition of KATP, which is predicted to suppress electrical activity in neurons (peripheral and central), muscle, and pancreas. Inhibitory sulfonylureas (SUs) have been used successfully to treat diabetes in patients with activating Kir6.2 mutations. There are two reports of improved neurological features in SU-treated DEND patients but no report of such improvement in adulthood. OBJECTIVE: The objective of the study was to determine the molecular basis of intermediate DEND in a 27-yr-old patient with a KCNJ11 mutation (G53D) and the patient's response to SU therapy. DESIGN: The G53D patient was transferred from insulin to gliclazide and then to glibenclamide over a 160-d period. Motor function was assessed throughout. Electrophysiology assessed the effect of the G53D mutation on KATP activity. RESULTS: The G53D patient demonstrated improved glycemic control and motor coordination with SU treatment, although glibenclamide was more effective than gliclazide. Reconstituted G53D channels exhibit reduced ATP sensitivity, which is predicted to suppress electrical activity in vivo. G53D channels coexpressed with SUR1 (the pancreatic and neuronal isoform) exhibit high-affinity block by gliclazide but are insensitive to block when coexpressed with SUR2A (the skeletal muscle isoform). High-affinity block by glibenclamide is present in G53D channels coexpressed with either SUR1 or SUR2A. CONCLUSION: The results demonstrate that SUs can resolve motor dysfunction in an adult with intermediate DEND and that this improvement is due to inhibition of the neuronal but not skeletal muscle KATP.},
author = {Koster, Joseph C and Cadario, Francesco and Peruzzi, Cinzia and Colombo, Carlo and Nichols, Colin G and Barbetti, Fabrizio},
doi = {10.1210/jc.2007-1826},
edition = {2007/12/11},
issn = {0021-972X},
journal = {The Journal of clinical endocrinology and metabolism},
keywords = {Adenosine Triphosphate/pharmacology,Adult,Diabetes Mellitus/drug therapy/*genetics/physiopat,Genotype,Humans,Infant, Newborn,Motor Activity,Mutation,Potassium Channels, Inwardly Rectifying/*genetics/,Sulfonylurea Compounds/*therapeutic use},
language = {eng},
month = {mar},
number = {3},
pages = {1054--1061},
publisher = {The Endocrine Society},
title = {{The G53D mutation in Kir6.2 (KCNJ11) is associated with neonatal diabetes and motor dysfunction in adulthood that is improved with sulfonylurea therapy}},
url = {https://www.ncbi.nlm.nih.gov/pubmed/18073297 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2266958/},
volume = {93},
year = {2008}
}
@article{Flanagan2006,
abstract = {Heterozygous activating mutations in KCNJ11, which encodes the Kir6.2 subunit of the pancreatic ATP-sensitive potassium (KATP) channel, cause both permanent and transient neonatal diabetes. A minority of patients also have neurological features. The identification of a KCNJ11 mutation has important therapeutic implications, as many patients can replace insulin injections with sulfonylurea tablets. We aimed to determine the age of presentation of patients with KCNJ11 mutations and to examine if there was a relationship between genotype and phenotype.},
author = {Flanagan, S E and Edghill, E L and Gloyn, A L and Ellard, S and Hattersley, A T},
doi = {10.1007/s00125-006-0246-z},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Flanagan et al. - 2006 - Mutations in KCNJ11, which encodes Kir6.2, are a common cause of diabetes diagnosed in the first 6 months of li.pdf:pdf},
issn = {1432-0428},
journal = {Diabetologia},
number = {6},
pages = {1190--1197},
title = {{Mutations in KCNJ11, which encodes Kir6.2, are a common cause of diabetes diagnosed in the first 6 months of life, with the phenotype determined by genotype}},
url = {https://doi.org/10.1007/s00125-006-0246-z},
volume = {49},
year = {2006}
}
@article{Pasquali2014a,
abstract = {Jorge Ferrer and colleagues have mapped regulatory SNP variants associated in GWAS with type 2 diabetes risk and glycemic traits to large clusters of enhancer elements regulating the transcriptional identity of pancreatic $\beta$ cells via a highly connected transcription factor network.},
author = {Pasquali, Lorenzo and Gaulton, Kyle J and Rodr{\'{i}}guez-Segu{\'{i}}, Santiago A and Mularoni, Loris and Miguel-Escalada, Irene and Akerman, İldem and Tena, Juan J and Mor{\'{a}}n, Ignasi and G{\'{o}}mez-Mar{\'{i}}n, Carlos and van de Bunt, Martijn and Ponsa-Cobas, Joan and Castro, Natalia and Nammo, Takao and Cebola, In{\^{e}}s and Garc{\'{i}}a-Hurtado, Javier and Maestro, Miguel Angel and Pattou, Fran{\c{c}}ois and Piemonti, Lorenzo and Berney, Thierry and Gloyn, Anna L and Ravassard, Philippe and Skarmeta, Jos{\'{e}} Luis G{\'{o}}mez and M{\"{u}}ller, Ferenc and McCarthy, Mark I and Ferrer, Jorge},
doi = {10.1038/ng.2870},
issn = {1546-1718},
journal = {Nature Genetics},
number = {2},
pages = {136--143},
title = {{Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants}},
url = {https://doi.org/10.1038/ng.2870},
volume = {46},
year = {2014}
}
@article{Trynka2013,
abstract = {Soumya Raychaudhuri and colleagues report a broadly applicable method that uses chromatin marks, specifically H3K4me3, to identify critical cell types to fine map complex trait variants.},
author = {Trynka, Gosia and Sandor, Cynthia and Han, Buhm and Xu, Han and Stranger, Barbara E and Liu, X Shirley and Raychaudhuri, Soumya},
doi = {10.1038/ng.2504},
issn = {1546-1718},
journal = {Nature Genetics},
number = {2},
pages = {124--130},
title = {{Chromatin marks identify critical cell types for fine mapping complex trait variants}},
url = {https://doi.org/10.1038/ng.2504},
volume = {45},
year = {2013}
}
@article{Fan2005,
author = {Fan, W and Voss-Andreae, A and Cao, W H and Morrison, S F},
journal = {Peptides},
pages = {1800--1813},
title = {{Regulation of thermogenesis by the central melanocortin system}},
volume = {26},
year = {2005}
}
@article{Shu2008a,
abstract = {OBJECTIVE-Type 2 diabetes is characterized by impaired insulin secretion in response to increased metabolic demand. This defect in $\beta$-cell compensation seems to result from the interplay between environmental factors and genetic predisposition. Genome-wide association studies reveal that common variants in transcription factor 7-like 2 (TCF7L2) are associated with increased risk of type 2 diabetes. The aim of the present study was to establish whether TCF7L2 plays a role in $\beta$-cell function and/or survival. RESEARCH DESIGN AND METHODS- To investigate the effects of TCFL7L2 depletion, isolated islets were exposed to TCF7L2 small interfering RNA (siRNA) versus scrambled siRNA, and $\beta$-cell survival and function were examined. For TCF7L2 overexpression, islets were cultured in glucose concentrations of 5.5-33.3 mmol/1 and the cytokine mix interleukin-1$\beta$/$\gamma$-interferon with or without overexpression of TCF7L2. Subsequently, glucose-stimulated insulin secretion (GSIS), $\beta$-cell apoptosis [by transferase-mediated dUTP nick-end labeling assay and Western blotting for poly(ADP-ribose) polymerase and Caspase-3 cleavage], and $\beta$-cell proliferation (by Ki67 immunostaining) were analyzed. RESULTS-Depleting TCF7L2 by siRNA resulted in a 5.1-fold increase in $\beta$-cell apoptosis, 2.2-fold decrease in $\beta$-cell proliferation (P {\textless} 0.001), and 2.6-fold decrease in GSIS (P {\textless} 0.01) in human islets. Similarly, loss of TCF7L2 resulted in impaired $\beta$-cell function in mouse islets. In contrast, overexpression of TCF7L2 protected islets from glucose and cytokine-induced apoptosis and impaired function. CONCLUSIONS-TCF7L2 is required for maintaining GSIS and $\beta$-cell survival. Changes in the level of active TCF7L2 in $\beta$-cells from carriers of at-risk allele may be the reason for defective insulin secretion and progression of type 2 diabetes. {\textcopyright} 2008 by the American Diabetes Association.},
author = {Shu, Luan and Sauter, Nadine S. and Schulthess, Fabienne T. and Matveyenko, Aleksey V. and Oberholzer, Jose and Maedler, Kathrin},
doi = {10.2337/db07-0847},
issn = {1939327X},
journal = {Diabetes},
title = {{Transcription factor 7-like 2 regulates $\beta$-cell survival and function in human pancreatic islets}},
year = {2008}
}
@article{Parker2013a,
abstract = {Using high-throughput experiments, we determined the functional epigenomic landscape in pancreatic islet cells. Computational integration of these data along with similar data from the ENCODE project revealed the presence of large gene control elements across diverse cell types that we refer to as “stretch enhancers.” Stretch enhancers are cell type specific and are associated with increased expression of genes involved in cell-specific processes. We find that genetic variations associated with common disease are highly enriched in stretch enhancers; notably, stretch enhancers specific to pancreatic islets harbor variants linked to type 2 diabetes and related traits. We propose that stretch enhancers form as pluripotent cells differentiate into committed lineages, to program important cell-specific gene expression.Chromatin-based functional genomic analyses and genomewide association studies (GWASs) together implicate enhancers as critical elements influencing gene expression and risk for common diseases. Here, we performed systematic chromatin and transcriptome profiling in human pancreatic islets. Integrated analysis of islet data with those from nine cell types identified specific and significant enrichment of type 2 diabetes and related quantitative trait GWAS variants in islet enhancers. Our integrated chromatin maps reveal that most enhancers are short (median = 0.8 kb). Each cell type also contains a substantial number of more extended (≥3 kb) enhancers. Interestingly, these stretch enhancers are often tissue-specific and overlap locus control regions, suggesting that they are important chromatin regulatory beacons. Indeed, we show that (i) tissue specificity of enhancers and nearby gene expression increase with enhancer length; (ii) neighborhoods containing stretch enhancers are enriched for important cell type–specific genes; and (iii) GWAS variants associated with traits relevant to a particular cell type are more enriched in stretch enhancers compared with short enhancers. Reporter constructs containing stretch enhancer sequences exhibited tissue-specific activity in cell culture experiments and in transgenic mice. These results suggest that stretch enhancers are critical chromatin elements for coordinating cell type–specific regulatory programs and that sequence variation in stretch enhancers affects risk of major common human diseases.},
author = {Parker, Stephen C J and Stitzel, Michael L and Taylor, D Leland and Orozco, Jose Miguel and Erdos, Michael R and Akiyama, Jennifer A and van Bueren, Kelly Lammerts and Chines, Peter S and Narisu, Narisu and Black, Brian L and Visel, Axel and Pennacchio, Len A and Collins, Francis S},
doi = {10.1073/pnas.1317023110},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Parker et al. - 2013 - Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants(2).pdf:pdf},
journal = {Proceedings of the National Academy of Sciences},
month = {oct},
number = {44},
pages = {17921 LP -- 17926},
title = {{Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants}},
url = {http://www.pnas.org/content/110/44/17921.abstract},
volume = {110},
year = {2013}
}
@article{Khamis2019,
abstract = {Objective Genome wide association studies (GWAS) for type 2 diabetes (T2D) have identified genetic loci that often localise in non-coding regions of the genome, suggesting gene regulation effects. We combined genetic and transcriptomic analysis from human islets obtained from brain-dead organ donors or surgical patients to detect expression quantitative trait loci (eQTLs) and shed light into the regulatory mechanisms of these genes. Methods Pancreatic islets were isolated either by laser capture microdissection (LCM) from surgical specimens of 103 metabolically phenotyped pancreatectomized patients (PPP) or by collagenase digestion of pancreas from 100 brain-dead organ donors (OD). Genotyping ({\textgreater} 8.7 million single nucleotide polymorphisms) and expression ({\textgreater} 47,000 transcripts and splice variants) analyses were combined to generate cis-eQTLs. Results After applying genome-wide false discovery rate significance thresholds, we identified 1,173 and 1,021 eQTLs in samples of OD and PPP, respectively. Among the strongest eQTLs shared between OD and PPP were CHURC1 (OD p-value=1.71 × 10-24; PPP p-value = 3.64 × 10–24) and PSPH (OD p-value = 3.92 × 10−26; PPP p-value = 3.64 × 10−24). We identified eQTLs in linkage-disequilibrium with GWAS loci T2D and associated traits, including TTLL6, MLX and KIF9 loci, which do not implicate the nearest gene. We found in the PPP datasets 11 eQTL genes, which were differentially expressed in T2D and two genes (CYP4V2 and TSEN2) associated with HbA1c but none in the OD samples. Conclusions eQTL analysis of LCM islets from PPP led us to identify novel genes which had not been previously linked to islet biology and T2D. The understanding gained from eQTL approaches, especially using surgical samples of living patients, provides a more accurate 3-dimensional representation than those from genetic studies alone.},
author = {Khamis, Amna and Canouil, Micka{\"{e}}l and Siddiq, Afshan and Crouch, Hutokshi and Falchi, Mario and von Bulow, Manon and Ehehalt, Florian and Marselli, Lorella and Distler, Marius and Richter, Daniela and Weitz, J{\"{u}}rgen and Bokvist, Krister and Xenarios, Ioannis and Thorens, Bernard and Schulte, Anke M and Ibberson, Mark and Bonnefond, Amelie and Marchetti, Piero and Solimena, Michele and Froguel, Philippe},
doi = {https://doi.org/10.1016/j.molmet.2019.03.004},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Khamis et al. - 2019 - Laser capture microdissection of human pancreatic islets reveals novel eQTLs associated with type 2 diabetes.pdf:pdf},
issn = {2212-8778},
journal = {Molecular Metabolism},
keywords = {Genetics,Islets,Laser capture microdissection,Type 2 diabetes,eQTLs},
pages = {98--107},
title = {{Laser capture microdissection of human pancreatic islets reveals novel eQTLs associated with type 2 diabetes}},
url = {http://www.sciencedirect.com/science/article/pii/S2212877819301309},
volume = {24},
year = {2019}
}
@article{Pickrell2014,
abstract = {Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWASs). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. I describe a statistical model that uses association statistics computed across the genome to identify classes of genomic elements that are enriched with or depleted of loci influencing a trait. The model naturally incorporates multiple types of annotations. I applied the model to GWASs of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, body mass index, and Crohn disease. For each trait, I used the model to evaluate the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, and DNase-I hypersensitive sites in over 100 tissues and cell lines. The fraction of phenotype-associated SNPs influencing protein sequence ranged from around 2{\%} (for platelet volume) up to around 20{\%} (for low-density lipoprotein cholesterol), repressed chromatin was significantly depleted for SNPs associated with several traits, and cell-type-specific DNase-I hypersensitive sites were enriched with SNPs associated with several traits (for example, the spleen in platelet volume). Finally, reweighting each GWAS by using information from functional genomics increased the number of loci with high-confidence associations by around 5{\%}.},
author = {Pickrell, Joseph K},
doi = {10.1016/j.ajhg.2014.03.004},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Pickrell - 2014 - Joint Analysis of Functional Genomic Data and Genome-wide Association Studies of 18 Human Traits.pdf:pdf},
issn = {0002-9297},
journal = {American Journal of Human Genetics},
month = {apr},
number = {4},
pages = {559--573},
publisher = {Elsevier},
title = {{Joint Analysis of Functional Genomic Data and Genome-wide Association Studies of 18 Human Traits}},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3980523/},
volume = {94},
year = {2014}
}
@article{Wakefield2007,
abstract = {In light of the vast amounts of genomic data that are now being generated, we propose a new measure, the Bayesian false-discovery probability (BFDP), for assessing the noteworthiness of an observed association. BFDP shares the ease of calculation of the recently proposed false-positive report probability (FPRP) but uses more information, has a noteworthy threshold defined naturally in terms of the costs of false discovery and nondiscovery, and has a sound methodological foundation. In addition, in a multiple-testing situation, it is straightforward to estimate the expected numbers of false discoveries and false nondiscoveries. We provide an in-depth discussion of FPRP, including a comparison with the q value, and examine the empirical behavior of these measures, along with BFDP, via simulation. Finally, we use BFDP to assess the association between 131 single-nucleotide polymorphisms and lung cancer in a case-control study.},
author = {Wakefield, Jon},
doi = {10.1086/519024},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Wakefield - 2007 - A Bayesian Measure of the Probability of False Discovery in Genetic Epidemiology Studies.pdf:pdf},
isbn = {0002-9297},
issn = {00029297},
journal = {The American Journal of Human Genetics},
pmid = {17668372},
title = {{A Bayesian Measure of the Probability of False Discovery in Genetic Epidemiology Studies}},
year = {2007}
}
@article{Akerman2017,
abstract = {Recent studies have uncovered thousands of long non-coding RNAs (lncRNAs) in human pancreatic ? cells. ? cell lncRNAs are often cell type specific and exhibit dynamic regulation during differentiation or upon changing glucose concentrations. Although these features hint at a role of lncRNAs in ? cell gene regulation and diabetes, the function of ? cell lncRNAs remains largely unknown. In this study, we investigated the function of ? cell-specific lncRNAs and transcription factors using transcript knockdowns and co-expression network analysis. This revealed lncRNAs that function in concert with transcription factors to regulate ? cell-specific transcriptional networks. We further demonstrate that the lncRNA PLUTO affects local 3D chromatin structure and transcription of PDX1, encoding a key ? cell transcription factor, and that both PLUTO and PDX1 are downregulated in islets from donors with type 2 diabetes or impaired glucose tolerance. These results implicate lncRNAs in the regulation of ? cell-specific transcription factor networks.},
annote = {doi: 10.1016/j.cmet.2016.11.016},
author = {Akerman, Ildem and Tu, Zhidong and Beucher, Anthony and Rolando, Delphine M Y and Sauty-Colace, Claire and Benazra, Marion and Nakic, Nikolina and Yang, Jialiang and Wang, Huan and Pasquali, Lorenzo and Moran, Ignasi and Garcia-Hurtado, Javier and Castro, Natalia and Gonzalez-Franco, Roser and Stewart, Andrew F and Bonner, Caroline and Piemonti, Lorenzo and Berney, Thierry and Groop, Leif and Kerr-Conte, Julie and Pattou, Francois and Argmann, Carmen and Schadt, Eric and Ravassard, Philippe and Ferrer, Jorge},
doi = {10.1016/j.cmet.2016.11.016},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Akerman et al. - 2017 - Human Pancreatic {\&}{\#}x3b2 Cell lncRNAs Control Cell-Specific Regulatory Networks.pdf:pdf},
issn = {1550-4131},
journal = {Cell Metabolism},
month = {feb},
number = {2},
pages = {400--411},
publisher = {Elsevier},
title = {{Human Pancreatic {\&}{\#}x3b2; Cell lncRNAs Control Cell-Specific Regulatory Networks}},
url = {https://doi.org/10.1016/j.cmet.2016.11.016},
volume = {25},
year = {2017}
}
@article{Dimas2014,
abstract = {Patients with established type 2 diabetes display both $\beta$-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.},
author = {Dimas, Antigone S and Lagou, Vasiliki and Barker, Adam and Knowles, Joshua W and M{\"{a}}gi, Reedik and Hivert, Marie-France and Benazzo, Andrea and Rybin, Denis and Jackson, Anne U and Stringham, Heather M and Song, Ci and Fischer-Rosinsky, Antje and Boesgaard, Trine Well{\o}v and Grarup, Niels and Abbasi, Fahim A and Assimes, Themistocles L and Hao, Ke and Yang, Xia and Lecoeur, C{\'{e}}cile and Barroso, In{\^{e}}s and Bonnycastle, Lori L and B{\"{o}}ttcher, Yvonne and Bumpstead, Suzannah and Chines, Peter S and Erdos, Michael R and Graessler, Jurgen and Kovacs, Peter and Morken, Mario A and Narisu, Narisu and Payne, Felicity and Stancakova, Alena and Swift, Amy J and T{\"{o}}njes, Anke and Bornstein, Stefan R and Cauchi, St{\'{e}}phane and Froguel, Philippe and Meyre, David and Schwarz, Peter E H and H{\"{a}}ring, Hans-Ulrich and Smith, Ulf and Boehnke, Michael and Bergman, Richard N and Collins, Francis S and Mohlke, Karen L and Tuomilehto, Jaakko and Quertemous, Thomas and Lind, Lars and Hansen, Torben and Pedersen, Oluf and Walker, Mark and Pfeiffer, Andreas F H and Spranger, Joachim and Stumvoll, Michael and Meigs, James B and Wareham, Nicholas J and Kuusisto, Johanna and Laakso, Markku and Langenberg, Claudia and Dupuis, Jos{\'{e}}e and Watanabe, Richard M and Florez, Jose C and Ingelsson, Erik and McCarthy, Mark I and Prokopenko, Inga},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Dimas et al. - 2014 - Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogen(3).pdf:pdf;:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Dimas et al. - 2014 - Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogen(2).pdf:pdf},
journal = {Diabetes},
month = {may},
number = {6},
pages = {2158 LP -- 2171},
title = {{Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity}},
url = {http://diabetes.diabetesjournals.org/content/63/6/2158.abstract},
volume = {63},
year = {2014}
}
@article{Stegle2012,
abstract = {We present PEER (probabilistic estimation of expression residuals), a software package implementing statistical models that improve the sensitivity and interpretability of genetic associations in population-scale expression data. This approach builds on factor analysis methods that infer broad variance components in the measurements. PEER takes as input transcript profiles and covariates from a set of individuals, and then outputs hidden factors that explain much of the expression variability. Optionally, these factors can be interpreted as pathway or transcription factor activations by providing prior information about which genes are involved in the pathway or targeted by the factor. The inferred factors are used in genetic association analyses. First, they are treated as additional covariates, and are included in the model to increase detection power for mapping expression traits. Second, they are analyzed as phenotypes themselves to understand the causes of global expression variability. PEER extends previous related surrogate variable models and can be implemented within hours on a desktop computer.},
author = {Stegle, Oliver and Parts, Leopold and Piipari, Matias and Winn, John and Durbin, Richard},
doi = {10.1038/nprot.2011.457},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Stegle et al. - 2012 - Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of g.pdf:pdf},
isbn = {1750-2799 (Electronic)$\backslash$r1750-2799 (Linking)},
issn = {1750-2799},
journal = {Nature protocols},
keywords = {Algorithms,Factor Analysis,Gene Expression Profiling,Gene Expression Profiling: methods,Gene Expression Profiling: statistics {\&} numerical,Genetic Association Studies,Genetic Association Studies: methods,Models,Sensitivity and Specificity,Software,Statistical},
number = {3},
pages = {500--7},
pmid = {22343431},
title = {{Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses.}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3398141{\&}tool=pmcentrez{\&}rendertype=abstract},
volume = {7},
year = {2012}
}
@article{Wood2017a,
abstract = {Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose–raising alleles were associated with a measure of first-phase insulin secretion at P {\&}lt; 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose–raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide–based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.},
author = {Wood, Andrew R and Jonsson, Anna and Jackson, Anne U and Wang, Nan and van Leewen, Nienke and Palmer, Nicholette D and Kobes, Sayuko and Deelen, Joris and Boquete-Vilarino, Lorena and Paananen, Jussi and Stan{\v{c}}{\'{a}}kov{\'{a}}, Alena and Boomsma, Dorret I and de Geus, Eco J C and Eekhoff, Elisabeth M W and Fritsche, Andreas and Kramer, Mark and Nijpels, Giel and Simonis-Bik, Annemarie and van Haeften, Timon W and Mahajan, Anubha and Boehnke, Michael and Bergman, Richard N and Tuomilehto, Jaakko and Collins, Francis S and Mohlke, Karen L and Banasik, Karina and Groves, Christopher J and McCarthy, Mark I and Pearson, Ewan R and Natali, Andrea and Mari, Andrea and Buchanan, Thomas A and Taylor, Kent D and Xiang, Anny H and Gjesing, Anette P and Grarup, Niels and Eiberg, Hans and Pedersen, Oluf and Chen, Yii-Derr and Laakso, Markku and Norris, Jill M and Smith, Ulf and Wagenknecht, Lynne E and Baier, Leslie and Bowden, Donald W and Hansen, Torben and Walker, Mark and Watanabe, Richard M and {‘t Hart}, Leen M and Hanson, Robert L and Frayling, Timothy M},
doi = {10.2337/db16-1452},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Wood et al. - 2017 - A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Phy.pdf:pdf},
journal = {Diabetes},
month = {aug},
number = {8},
pages = {2296 LP -- 2309},
title = {{A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants}},
url = {http://diabetes.diabetesjournals.org/content/66/8/2296.abstract},
volume = {66},
year = {2017}
}
@article{Visscher2017,
abstract = {Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.},
author = {Visscher, Peter M and Wray, Naomi R and Zhang, Qian and Sklar, Pamela and McCarthy, Mark I and Brown, Matthew A and Yang, Jian},
doi = {10.1016/j.ajhg.2017.06.005},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Visscher et al. - 2017 - 10 Years of GWAS Discovery Biology, Function, and Translation.pdf:pdf},
issn = {1537-6605},
journal = {American journal of human genetics},
keywords = {*Genome-Wide Association Study,*Translational Medical Research,Genetic Pleiotropy,Genetic Predisposition to Disease,Humans,Multifactorial Inheritance/genetics,SNP,auto-immune disease,genome-wide association study,heritability,obesity,schizophrenia},
language = {eng},
month = {jul},
number = {1},
pages = {5--22},
publisher = {Elsevier},
title = {{10 Years of GWAS Discovery: Biology, Function, and Translation}},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28686856 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501872/},
volume = {101},
year = {2017}
}
@article{Wainberg2019,
abstract = {Transcriptome-wide association studies (TWAS) integrate genome-wide association studies (GWAS) and gene expression datasets to identify gene–trait associations. In this Perspective, we explore properties of TWAS as a potential approach to prioritize causal genes at GWAS loci, by using simulations and case studies of literature-curated candidate causal genes for schizophrenia, low-density-lipoprotein cholesterol and Crohn's disease. We explore risk loci where TWAS accurately prioritizes the likely causal gene as well as loci where TWAS prioritizes multiple genes, some likely to be non-causal, owing to sharing of expression quantitative trait loci (eQTL). TWAS is especially prone to spurious prioritization with expression data from non-trait-related tissues or cell types, owing to substantial cross-cell-type variation in expression levels and eQTL strengths. Nonetheless, TWAS prioritizes candidate causal genes more accurately than simple baselines. We suggest best practices for causal-gene prioritization with TWAS and discuss future opportunities for improvement. Our results showcase the strengths and limitations of using eQTL datasets to determine causal genes at GWAS loci.},
author = {Wainberg, Michael and Sinnott-Armstrong, Nasa and Mancuso, Nicholas and Barbeira, Alvaro N and Knowles, David A and Golan, David and Ermel, Raili and Ruusalepp, Arno and Quertermous, Thomas and Hao, Ke and Bj{\"{o}}rkegren, Johan L M and Im, Hae Kyung and Pasaniuc, Bogdan and Rivas, Manuel A and Kundaje, Anshul},
doi = {10.1038/s41588-019-0385-z},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Wainberg et al. - 2019 - Opportunities and challenges for transcriptome-wide association studies.pdf:pdf},
issn = {1546-1718},
journal = {Nature Genetics},
number = {4},
pages = {592--599},
title = {{Opportunities and challenges for transcriptome-wide association studies}},
url = {https://doi.org/10.1038/s41588-019-0385-z},
volume = {51},
year = {2019}
}
@article{Greenwald2019,
abstract = {Genetic variants affecting pancreatic islet enhancers are central to T2D risk, but the gene targets of islet enhancer activity are largely unknown. We generate a high-resolution map of islet chromatin loops using Hi-C assays in three islet samples and use loops to annotate target genes of islet enhancers defined using ATAC-seq and published ChIP-seq data. We identify candidate target genes for thousands of islet enhancers, and find that enhancer looping is correlated with islet-specific gene expression. We fine-map T2D risk variants affecting islet enhancers, and find that candidate target genes of these variants defined using chromatin looping and eQTL mapping are enriched in protein transport and secretion pathways. At IGF2BP2, a fine-mapped T2D variant reduces islet enhancer activity and IGF2BP2 expression, and conditional inactivation of IGF2BP2 in mouse islets impairs glucose-stimulated insulin secretion. Our findings provide a resource for studying islet enhancer function and identifying genes involved in T2D risk.},
author = {Greenwald, William W and Chiou, Joshua and Yan, Jian and Qiu, Yunjiang and Dai, Ning and Wang, Allen and Nariai, Naoki and Aylward, Anthony and Han, Jee Yun and Kadakia, Nikita and Regue, Laura and Okino, Mei-Lin and Drees, Frauke and Kramer, Dana and Vinckier, Nicholas and Minichiello, Liliana and Gorkin, David and Avruch, Joseph and Frazer, Kelly A and Sander, Maike and Ren, Bing and Gaulton, Kyle J},
doi = {10.1038/s41467-019-09975-4},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Greenwald et al. - 2019 - Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes.pdf:pdf},
issn = {2041-1723},
journal = {Nature Communications},
number = {1},
pages = {2078},
title = {{Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes risk}},
url = {https://doi.org/10.1038/s41467-019-09975-4},
volume = {10},
year = {2019}
}
@article{Consortium2012,
author = {{The Wellcome Trust Case Control Consortium} and Maller, Julian B and McVean, Gilean and Byrnes, Jake and Vukcevic, Damjan and Palin, Kimmo and Su, Zhan and Howson, Joanna M M and Auton, Adam and Myers, Simon and Morris, Andrew and Pirinen, Matti and Brown, Matthew A and Burton, Paul R and Caulfield, Mark J and Compston, Alastair and Farrall, Martin and Hall, Alistair S and Hattersley, Andrew T and Hill, Adrian V S and Mathew, Christopher G and Pembrey, Marcus and Satsangi, Jack and Stratton, Michael R and Worthington, Jane and Craddock, Nick and Hurles, Matthew and Ouwehand, Willem and Parkes, Miles and Rahman, Nazneen and Duncanson, Audrey and Todd, John A and Kwiatkowski, Dominic P and Samani, Nilesh J and Gough, Stephen C L and McCarthy, Mark I and Deloukas, Panagiotis and Donnelly, Peter},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Consortium et al. - 2012 - Bayesian refinement of association signals for 14 loci in 3 common diseases.pdf:pdf},
journal = {Nature Genetics},
month = {oct},
pages = {1294},
publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
title = {{Bayesian refinement of association signals for 14 loci in 3 common diseases}},
url = {http://dx.doi.org/10.1038/ng.2435 http://10.0.4.14/ng.2435 https://www.nature.com/articles/ng.2435{\#}supplementary-information},
volume = {44},
year = {2012}
}
@article{Fan1997a,
abstract = {DOMINANT alleles at the agouti locus (A) cause an obesity syndrome in the mouse, as a consequence of ectopic expression of the agouti peptide. This peptide, normally only found in the skin, is a high-affinity antagonist of the melanocyte-stimulating hormone receptor (MC1-R), thus explaining the inhibitory effect of agouti on eumelanin pigment synthesis. The agouti peptide is also an antagonist of the hypothalamic melanocortin-4 receptor (MC4-R). To test the hypothesis that agouti causes obesity by antagonism of hypothalamic melanocortin receptors, we identified cyclic melanocortin analogues that are potent agonists or antagonists of the neural MC3 (refs 11, 12) and MC4 receptors. Intracerebroventricular administration of the agonist, MTII, inhibited feeding in four models of hyperphagia: fasted C57BL/6J, ob/ob, and A(Y) mice, and mice injected with neuropeptide Y. Co- administration of the specific melanocortin antagonist and agouti-mimetic SHU9119 completely blocked this inhibition. Furthermore, administration of SHU9119 significantly enhanced nocturnal feeding, or feeding stimulated by a prior fast. Our data show that melanocortinergic neurons exert a tonic inhibition of feeding behaviour. Chronic disruption of this inhibitory signal is a likely explanation of the agouti obesity syndrome.},
author = {Fan, Wei and Boston, Bruce A. and Kesterson, Robert A. and Hruby, Victor J. and Cone, Roger D.},
doi = {10.1038/385165a0},
issn = {00280836},
journal = {Nature},
title = {{Role of melanocortlnergic neurons in feeding and the agouti obesity syndrome}},
year = {1997}
}
@article{Lee2004,
abstract = {We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function. {\textcopyright}2004 by Cold Spring Harbor Laboratory Press.},
author = {Lee, Homin K. and Hsu, Amy K. and Sajdak, Jon and Qin, Jie and Pavlidis, Paul},
doi = {10.1101/gr.1910904},
issn = {10889051},
journal = {Genome Research},
title = {{Coexpresion analysis of human genes across many microarray data sets}},
year = {2004}
}
@misc{Fan2005a,
abstract = {Adaptive thermogenesis represents one of the important homeostatic mechanisms by which the body maintains appropriate levels of stored energy and its core temperature. Dysregulation of adaptive thermogenesis promotes obesity. The central melanocortin system, in particular the melanocortin 4 receptor (MC4R) signaling pathway, influences the regulation of every aspect of energy balance, including thermogenesis, and plays a critical role in energy homeostasis in both rodent and man. This review will outline our current understanding of adaptive thermogenesis, focusing on the role of the central melanocortin pathway in the regulation of thermogenesis. {\textcopyright} 2005 Elsevier Inc. All rights reserved.},
author = {Fan, Wei and Voss-Andreae, Adriana and Cao, Wei Hua and Morrison, Shaun F.},
booktitle = {Peptides},
doi = {10.1016/j.peptides.2004.11.033},
issn = {01969781},
keywords = {AGRP,BAT,Central circuits,Diet-induced thermogenesis,Melanocortin,Obesity,POMC,Pathogenic stimuli,Sympathetic nervous system,Thermogenesis,Thyroid,UCP},
title = {{Regulation of thermogenesis by the central melanocortin system}},
year = {2005}
}
@article{Scott2017,
abstract = {To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P {\&}lt; 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.},
author = {Scott, Robert A and Scott, Laura J and M{\"{a}}gi, Reedik and Marullo, Letizia and Gaulton, Kyle J and Kaakinen, Marika and Pervjakova, Natalia and Pers, Tune H and Johnson, Andrew D and Eicher, John D and Jackson, Anne U and Ferreira, Teresa and Lee, Yeji and Ma, Clement and Steinthorsdottir, Valgerdur and Thorleifsson, Gudmar and Qi, Lu and {Van Zuydam}, Natalie R and Mahajan, Anubha and Chen, Han and Almgren, Peter and Voight, Ben F and Grallert, Harald and M{\"{u}}ller-Nurasyid, Martina and Ried, Janina S and Rayner, Nigel W and Robertson, Neil and Karssen, Lennart C and van Leeuwen, Elisabeth M and Willems, Sara M and Fuchsberger, Christian and Kwan, Phoenix and Teslovich, Tanya M and Chanda, Pritam and Li, Man and Lu, Yingchang and Dina, Christian and Thuillier, Dorothee and Yengo, Loic and Jiang, Longda and Sparso, Thomas and Kestler, Hans A and Chheda, Himanshu and Eisele, Lewin and Gustafsson, Stefan and Fr{\aa}nberg, Mattias and Strawbridge, Rona J and Benediktsson, Rafn and Hreidarsson, Astradur B and Kong, Augustine and Sigurðsson, Gunnar and Kerrison, Nicola D and Luan, Jian{\&}{\#}039;an and Liang, Liming and Meitinger, Thomas and Roden, Michael and Thorand, Barbara and Esko, T{\~{o}}nu and Mihailov, Evelin and Fox, Caroline and Liu, Ching-Ti and Rybin, Denis and Isomaa, Bo and Lyssenko, Valeriya and Tuomi, Tiinamaija and Couper, David J and Pankow, James S and Grarup, Niels and Have, Christian T and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and Linneberg, Allan and Cornelis, Marilyn C and van Dam, Rob M and Hunter, David J and Kraft, Peter and Sun, Qi and Edkins, Sarah and Owen, Katharine R and Perry, John R B and Wood, Andrew R and Zeggini, Eleftheria and Tajes-Fernandes, Juan and Abecasis, Goncalo R and Bonnycastle, Lori L and Chines, Peter S and Stringham, Heather M and Koistinen, Heikki A and Kinnunen, Leena and Sennblad, Bengt and M{\"{u}}hleisen, Thomas W and N{\"{o}}then, Markus M and Pechlivanis, Sonali and Baldassarre, Damiano and Gertow, Karl and Humphries, Steve E and Tremoli, Elena and Klopp, Norman and Meyer, Julia and Steinbach, Gerald and Wennauer, Roman and Eriksson, Johan G and Mӓnnist{\"{o}}, Satu and Peltonen, Leena and Tikkanen, Emmi and Charpentier, Guillaume and Eury, Elodie and Lobbens, St{\'{e}}phane and Gigante, Bruna and Leander, Karin and McLeod, Olga and Bottinger, Erwin P and Gottesman, Omri and Ruderfer, Douglas and Bl{\"{u}}her, Matthias and Kovacs, Peter and Tonjes, Anke and Maruthur, Nisa M and Scapoli, Chiara and Erbel, Raimund and J{\"{o}}ckel, Karl-Heinz and Moebus, Susanne and de Faire, Ulf and Hamsten, Anders and Stumvoll, Michael and Deloukas, Panagiotis and Donnelly, Peter J and Frayling, Timothy M and Hattersley, Andrew T and Ripatti, Samuli and Salomaa, Veikko and Pedersen, Nancy L and Boehm, Bernhard O and Bergman, Richard N and Collins, Francis S and Mohlke, Karen L and Tuomilehto, Jaakko and Hansen, Torben and Pedersen, Oluf and Barroso, In{\^{e}}s and Lannfelt, Lars and Ingelsson, Erik and Lind, Lars and Lindgren, Cecilia M and Cauchi, Stephane and Froguel, Philippe and Loos, Ruth J F and Balkau, Beverley and Boeing, Heiner and Franks, Paul W and {Barricarte Gurrea}, Aurelio and Palli, Domenico and van der Schouw, Yvonne T and Altshuler, David and Groop, Leif C and Langenberg, Claudia and Wareham, Nicholas J and Sijbrands, Eric and van Duijn, Cornelia M and Florez, Jose C and Meigs, James B and Boerwinkle, Eric and Gieger, Christian and Strauch, Konstantin and Metspalu, Andres and Morris, Andrew D and Palmer, Colin N A and Hu, Frank B and Thorsteinsdottir, Unnur and Stefansson, Kari and Dupuis, Jos{\'{e}}e and Morris, Andrew P and Boehnke, Michael and McCarthy, Mark I and Prokopenko, Inga},
doi = {10.2337/db16-1253},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Scott et al. - 2017 - An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.pdf:pdf},
journal = {Diabetes},
month = {nov},
number = {11},
pages = {2888 LP -- 2902},
title = {{An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans}},
url = {http://diabetes.diabetesjournals.org/content/66/11/2888.abstract},
volume = {66},
year = {2017}
}
@article{Martinelli2011,
abstract = {Context: Melanocortin receptor 4 (MC4R) deficiency is characterized by increased linear growth greater than expected for the degree of obesity.Objective: The objective of the investigation was to study the somatotroph axis in obese MC4R-deficient patients and equally obese controls.Patients and Methods: We obtained anthropometric measurements and insulin concentrations in 153 MC4R-deficient subjects and 1392 controls matched for age and severity of obesity. We measured fasting IGF-I, IGF-II, IGF binding protein (IGFBP)-1, IGFBP-3, and acid-labile subunit levels in a subset of 33 MC4R-deficient patients and 36 control subjects. We examined pulsatile GH secretion in six adult MC4R-deficient subjects and six obese controls.Results: Height sd score was significantly greater in MC4R-deficient children under 5 yr of age compared with controls (mean ± sem: 2.3 ± 0.06 vs. 1.8 ± 0.04, P {\textless} 0.001), an effect that persisted throughout childhood. Final height (cm) was greater in MC4R-deficient men (mean ± sem 173 ± 2.5 vs. 168 ± 2.1, P {\textless} 0.001) and women (mean 165 ± 2.1 vs. 158 ± 1.9, P {\textless} 0.001). Fasting IGF-I, IGF-II, acid-labile subunit, and IGFBP-3 concentrations were similar in the two groups. GH levels were markedly suppressed in obese controls, but pulsatile GH secretion was retained in MC4R deficiency. The mean maximal GH secretion rate per burst (P {\textless} 0.05) and mass per burst (P {\textless} 0.05) were increased in MC4R deficiency, consistent with increased pulsatile and total GH secretion. Fasting insulin levels were markedly elevated in MC4R-deficient children.Conclusions: In MC4R deficiency, increased linear growth in childhood leads to increased adult final height, greater than predicted by obesity alone. GH pulsatility is maintained in MC4R deficiency, a finding consistent with animal studies, suggesting a role for MC4R in controlling hypothalamic somatostatinergic tone. Fasting insulin levels are significantly higher in children carrying MC4R mutations. Both of these factors may contribute to the accelerated growth phenotype characteristic of MC4R deficiency.},
author = {Martinelli, Carlos E and Keogh, Julia M and Greenfield, Jerry R and Henning, Elana and van der Klaauw, Agatha A and Blackwood, Anthea and O'Rahilly, Stephen and Roelfsema, Ferdinand and Camacho-Hübner, Cecilia and Pijl, Hanno and Farooqi, I Sadaf},
doi = {10.1210/jc.2010-1369},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Martinelli et al. - 2011 - Obesity due to Melanocortin 4 Receptor (MC4R) Deficiency Is Associated with Increased Linear Growth and Final.pdf:pdf},
issn = {0021-972X},
journal = {The Journal of Clinical Endocrinology {\&} Metabolism},
month = {jan},
number = {1},
pages = {E181--E188},
title = {{Obesity due to Melanocortin 4 Receptor (MC4R) Deficiency Is Associated with Increased Linear Growth and Final Height, Fasting Hyperinsulinemia, and Incompletely Suppressed Growth Hormone Secretion}},
url = {https://doi.org/10.1210/jc.2010-1369},
volume = {96},
year = {2011}
}
@article{Lau2017a,
abstract = {Interpretation of results from genome-wide association studies for T2D is challenging. Only very few loci have been replicated in African ancestry populations and the identification of the implicated functional genes remain largely undefined. We used genetic maps that capture detailed linkage disequilibrium information in European and African Americans and applied these to large T2D case-control samples in order to estimate locations for putative functional variants in both populations. Replicated T2D locations were tested for evidence of being regulatory hotspots using adipose expression. We validated a sample of our co-location intervals using next generation sequencing and functional annotation, including enhancers, transcription, and chromatin modifications. We identified 111 additional disease-susceptibility locations, 93 of which are cosmopolitan and 18 of which are European specific. We show that many previously known signals are also risk loci in African Americans. The majority of the disease locations appear to confer risk of T2D via the regulation of expression levels for a large number (266) of cis-regulated genes, the majority of which are not the nearest genes to the disease loci. Sequencing three cosmopolitan locations provided candidate functional variants that precisely co-locate with cell-specific chromatin domains and pancreatic islet enhancers. These variants have large effect sizes and are common across populations. Results show that disease-associated loci in different populations, gene expression, and cell-specific regulatory annotation can be effectively integrated by localizing these effects on high-resolution genetic maps. The cis-regulated genes provide insights into the complex molecular pathways involved and can be used as targets for sequencing and functional molecular studies.},
author = {Lau, Winston and Andrew, Toby and Maniatis, Nikolas},
doi = {10.1016/j.ajhg.2017.04.007},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Lau, Andrew, Maniatis - 2017 - High-Resolution Genetic Maps Identify Multiple Type 2 Diabetes Loci at Regulatory Hotspots in African (2).pdf:pdf},
issn = {15376605},
journal = {American Journal of Human Genetics},
keywords = {expression quantitative trait loci,gene mapping,linkage disequilibrium maps,regulation,type 2 diabetes},
title = {{High-Resolution Genetic Maps Identify Multiple Type 2 Diabetes Loci at Regulatory Hotspots in African Americans and Europeans}},
year = {2017}
}
@article{Siljee2013,
address = {Bristol, UK},
author = {Siljee, Jacqueline E and Unmehopa, Unga A and Kalsbeek, Andries and Swaab, Dick F and Fliers, Eric and Alkemade, Anneke},
doi = {10.1530/EJE-12-0750},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Siljee et al. - 2013 - Melanocortin 4 receptor distribution in the human hypothalamus.pdf:pdf},
journal = {European Journal of Endocrinology},
language = {English},
number = {3},
pages = {361--369},
publisher = {BioScientifica},
title = {{Melanocortin 4 receptor distribution in the human hypothalamus}},
url = {https://eje.bioscientifica.com/view/journals/eje/168/3/361.xml},
volume = {168},
year = {2013}
}
@article{Spracklen2019,
abstract = {Meta-analyses of genome-wide association studies (GWAS) have identified {\&}gt;240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.Type 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/or secretion by the pancreatic $\beta$ cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified {\&}gt;240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.},
annote = {eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues

three distinct T2D signals, ({\~{}}25Kb for two signals)

Lead signal (rs33981001) high LD with lead cis-eQTL variant for NKX6-3 in pancreatic islets (rs12549902; EAS LD r2=0.79, EUR r2=0.83) and risk allele associated w/ decreased expression of NKX6-3. 
NKX6-3 (NK6 homeobox 3) is pancreatic islet TF required for alpha and beta cell development, influences insulin secretion. 

Second signal; rs62508166 in high LD w/ lead cis-eQTL for ANK1 in subcutaneous adipose tissue and skeletal muscle (rs516946; EAS LD r2=0.96, EUR r2=0.80) and the T2D risk allele is associated w/ increased expression of ANK1. 

ANK1 belongs to ankyrin family of integral membrane proteins that has been shown to affect glucose uptake in skeletal muscle, expression changes may lead to IR, 

"Together, these GWAS and eQTL signals suggest that variants within this {\~{}}25 kb region act to increase or decrease expression levels of two different genes in different tissues to increase T2D risk."},
author = {Spracklen, Cassandra N and Horikoshi, Momoko and Kim, Young Jin and Lin, Kuang and Bragg, Fiona and Moon, Sanghoon and Suzuki, Ken and Tam, Claudia H T and Tabara, Yasuharu and Kwak, Soo-Heon and Takeuchi, Fumihiko and Long, Jirong and Lim, Victor J Y and Chai, Jin-Fang and Chen, Chien-Hsiun and Nakatochi, Masahiro and Yao, Jie and {Sun Choi}, Hyeok and Iyengar, Apoorva K and Perrin, Hannah J and Brotman, Sarah M and van de Bunt, Martijn and Gloyn, Anna L and Below, Jennifer E and Boehnke, Michael and Bowden, Donald W and Chambers, John C and Mahajan, Anubha and McCarthy, Mark I and Ng, Maggie C Y and Petty, Lauren E and Zhang, Weihua and Morris, Andrew P and Adair, Linda S and Bian, Zheng and Chan, Juliana C N and Chang, Li-Ching and Chee, Miao-Li and {Ida Chen}, Yii-Der and Chen, Yuan-Tsong and Chen, Zhengming and Chuang, Lee-Ming and Du, Shufa and Gordon-Larsen, Penny and Gross, Myron and Guo, Xiuqing and Guo, Yu and Han, Sohee and Howard, Annie-Green and Huang, Wei and Hung, Yi-Jen and {Yeong Hwang}, Mi and Hwu, Chii-Min and Ichihara, Sahoko and Isono, Masato and Jang, Hye-Mi and Jiang, Guozhi and Jonas, Jost B and Kamatani, Yoichiro and Katsuya, Tomohiro and Kawaguchi, Takahisa and Khor, Chiea-Chuen and Kohara, Katsuhiko and Lee, Myung-Shik and Lee, Nannette R and Li, Liming and Liu, Jianjun and Luk, Andrea O and Lv, Jun and Okada, Yukinori and Pereira, Mark A and Sabanayagam, Charumathi and Shi, Jinxiu and {Mun Shin}, Dong and {Yee So}, Wing and Takahashi, Atsushi and Tomlinson, Brian and Tsai, Fuu-Jen and van Dam, Rob M and Xiang, Yong-Bing and Yamamoto, Ken and Yamauchi, Toshimasa and Yoon, Kyungheon and Yu, Canqing and Yuan, Jian-Min and Zhang, Liang and Zheng, Wei and Igase, Michiya and {Shin Cho}, Yoon and Rotter, Jerome I and Wang, Ya-Xing and Sheu, Wayne H H and Yokota, Mitsuhiro and Wu, Jer-Yuarn and Cheng, Ching-Yu and Wong, Tien-Yin and Shu, Xiao-Ou and Kato, Norihiro and Park, Kyong-Soo and Tai, E-Shyong and Matsuda, Fumihiko and Koh, Woon-Puay and Ma, Ronald C W and Maeda, Shiro and Millwood, Iona Y and Lee, Juyoung and Kadowaki, Takashi and Walters, Robin G and Kim, Bong-Jo and Mohlke, Karen L and Sim, Xueling},
doi = {10.1101/685172},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Spracklen et al. - 2019 - Identification of type 2 diabetes loci in 433,540 East Asian individuals.pdf:pdf},
journal = {bioRxiv},
month = {jan},
pages = {685172},
title = {{Identification of type 2 diabetes loci in 433,540 East Asian individuals}},
url = {http://biorxiv.org/content/early/2019/06/28/685172.abstract},
year = {2019}
}
@article{Mahajan2018b,
abstract = {We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P {\textless} 2.2 × 10(-7)); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.},
author = {Mahajan, Anubha and Wessel, Jennifer and Willems, Sara M and Zhao, Wei and Robertson, Neil R and Chu, Audrey Y and Gan, Wei and Kitajima, Hidetoshi and Taliun, Daniel and Rayner, N William and Guo, Xiuqing and Lu, Yingchang and Li, Man and Jensen, Richard A and Hu, Yao and Huo, Shaofeng and Lohman, Kurt K and Zhang, Weihua and Cook, James P and Prins, Bram Peter and Flannick, Jason and Grarup, Niels and Trubetskoy, Vassily Vladimirovich and Kravic, Jasmina and Kim, Young Jin and Rybin, Denis V and Yaghootkar, Hanieh and M{\"{u}}ller-Nurasyid, Martina and Meidtner, Karina and Li-Gao, Ruifang and Varga, Tibor V and Marten, Jonathan and Li, Jin and Smith, Albert Vernon and An, Ping and Ligthart, Symen and Gustafsson, Stefan and Malerba, Giovanni and Demirkan, Ayse and Tajes, Juan Fernandez and Steinthorsdottir, Valgerdur and Wuttke, Matthias and Lecoeur, C{\'{e}}cile and Preuss, Michael and Bielak, Lawrence F and Graff, Marielisa and Highland, Heather M and Justice, Anne E and Liu, Dajiang J and Marouli, Eirini and Peloso, Gina Marie and Warren, Helen R and Consortium, ExomeBP and Consortium, MAGIC and Consortium, GIANT and Afaq, Saima and Afzal, Shoaib and Ahlqvist, Emma and Almgren, Peter and Amin, Najaf and Bang, Lia B and Bertoni, Alain G and Bombieri, Cristina and Bork-Jensen, Jette and Brandslund, Ivan and Brody, Jennifer A and Burtt, No{\"{e}}l P and Canouil, Micka{\"{e}}l and Chen, Yii-Der Ida and Cho, Yoon Shin and Christensen, Cramer and Eastwood, Sophie V and Eckardt, Kai-Uwe and Fischer, Krista and Gambaro, Giovanni and Giedraitis, Vilmantas and Grove, Megan L and de Haan, Hugoline G and Hackinger, Sophie and Hai, Yang and Han, Sohee and Tybj{\ae}rg-Hansen, Anne and Hivert, Marie-France and Isomaa, Bo and J{\"{a}}ger, Susanne and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and K{\"{a}}r{\"{a}}j{\"{a}}m{\"{a}}ki, Annemari and Kim, Bong-Jo and Kim, Sung Soo and Koistinen, Heikki A and Kovacs, Peter and Kriebel, Jennifer and Kronenberg, Florian and L{\"{a}}ll, Kristi and Lange, Leslie A and Lee, Jung-Jin and Lehne, Benjamin and Li, Huaixing and Lin, Keng-Hung and Linneberg, Allan and Liu, Ching-Ti and Liu, Jun and Loh, Marie and M{\"{a}}gi, Reedik and Mamakou, Vasiliki and McKean-Cowdin, Roberta and Nadkarni, Girish and Neville, Matt and Nielsen, Sune F and Ntalla, Ioanna and Peyser, Patricia A and Rathmann, Wolfgang and Rice, Kenneth and Rich, Stephen S and Rode, Line and Rolandsson, Olov and Sch{\"{o}}nherr, Sebastian and Selvin, Elizabeth and Small, Kerrin S and Stan{\v{c}}{\'{a}}kov{\'{a}}, Alena and Surendran, Praveen and Taylor, Kent D and Teslovich, Tanya M and Thorand, Barbara and Thorleifsson, Gudmar and Tin, Adrienne and T{\"{o}}njes, Anke and Varbo, Anette and Witte, Daniel R and Wood, Andrew R and Yajnik, Pranav and Yao, Jie and Yengo, Lo{\"{i}}c and Young, Robin and Amouyel, Philippe and Boeing, Heiner and Boerwinkle, Eric and Bottinger, Erwin P and Chowdhury, Rajiv and Collins, Francis S and Dedoussis, George and Dehghan, Abbas and Deloukas, Panos and Ferrario, Marco M and Ferri{\`{e}}res, Jean and Florez, Jose C and Frossard, Philippe and Gudnason, Vilmundur and Harris, Tamara B and Heckbert, Susan R and Howson, Joanna M M and Ingelsson, Martin and Kathiresan, Sekar and Kee, Frank and Kuusisto, Johanna and Langenberg, Claudia and Launer, Lenore J and Lindgren, Cecilia M and M{\"{a}}nnist{\"{o}}, Satu and Meitinger, Thomas and Melander, Olle and Mohlke, Karen L and Moitry, Marie and Morris, Andrew D and Murray, Alison D and de Mutsert, Ren{\'{e}}e and Orho-Melander, Marju and Owen, Katharine R and Perola, Markus and Peters, Annette and Province, Michael A and Rasheed, Asif and Ridker, Paul M and Rivadineira, Fernando and Rosendaal, Frits R and Rosengren, Anders H and Salomaa, Veikko and Sheu, Wayne H-H and Sladek, Rob and Smith, Blair H and Strauch, Konstantin and Uitterlinden, Andr{\'{e}} G and Varma, Rohit and Willer, Cristen J and Bl{\"{u}}her, Matthias and Butterworth, Adam S and Chambers, John Campbell and Chasman, Daniel I and Danesh, John and van Duijn, Cornelia and Dupuis, Jos{\'{e}}e and Franco, Oscar H and Franks, Paul W and Froguel, Philippe and Grallert, Harald and Groop, Leif and Han, Bok-Ghee and Hansen, Torben and Hattersley, Andrew T and Hayward, Caroline and Ingelsson, Erik and Kardia, Sharon L R and Karpe, Fredrik and Kooner, Jaspal Singh and K{\"{o}}ttgen, Anna and Kuulasmaa, Kari and Laakso, Markku and Lin, Xu and Lind, Lars and Liu, Yongmei and Loos, Ruth J F and Marchini, Jonathan and Metspalu, Andres and Mook-Kanamori, Dennis and Nordestgaard, B{\o}rge G and Palmer, Colin N A and Pankow, James S and Pedersen, Oluf and Psaty, Bruce M and Rauramaa, Rainer and Sattar, Naveed and Schulze, Matthias B and Soranzo, Nicole and Spector, Timothy D and Stefansson, Kari and Stumvoll, Michael and Thorsteinsdottir, Unnur and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Wareham, Nicholas J and Wilson, James G and Zeggini, Eleftheria and Scott, Robert A and Barroso, In{\^{e}}s and Frayling, Timothy M and Goodarzi, Mark O and Meigs, James B and Boehnke, Michael and Saleheen, Danish and Morris, Andrew P and Rotter, Jerome I and McCarthy, Mark I},
doi = {10.1038/s41588-018-0084-1},
edition = {2018/04/09},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Mahajan et al. - 2018 - Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.pdf:pdf;:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Mahajan et al. - 2018 - Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabet(2).pdf:pdf},
issn = {1546-1718},
journal = {Nature genetics},
keywords = {Alleles,Chromosome Mapping/statistics {\&} numerical data,Diabetes Mellitus,European Continental Ancestry Group/genetics,Female,Genetic Predisposition to Disease,Genetic Variation,Genome-Wide Association Study/statistics {\&} numeric,Humans,Male,Type 2/classification/*genetics/physiopathology,Whole Exome Sequencing/statistics {\&} numerical data},
language = {eng},
month = {apr},
number = {4},
pages = {559--571},
title = {{Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes}},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29632382 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898373/},
volume = {50},
year = {2018}
}
@article{Varshney2017,
abstract = {Genome-wide association studies (GWAS) have identified {\textgreater}100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.},
annote = {10.1073/pnas.1621192114

pathogenetic mechanisms underlying {\textgreater}100 T2D GWAS associations remains elusive

examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to undestand links; 

112 islet samples --{\textgreater} cis-eQTL mapping; islet cis-eQTLs enriched are enriched at islet stretch enhancers

ATAC-seq (2 samples) --{\textgreater} TF footprinting; open chromatin enriched for cis-eQTLS 

allelic imbalance of TF footprints ; construct TF binding affinities; 

GWAS hits strongly enriched at islet Regulatory Factor X (RFX) footprints; T2D risk alleles disrupt RFX motifs; 

"confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition"},
author = {Varshney, Arushi and Scott, Laura J and Welch, Ryan P and Erdos, Michael R and Chines, Peter S and Narisu, Narisu and Albanus, Ricardo D'O. and Orchard, Peter and Wolford, Brooke N and Kursawe, Romy and Vadlamudi, Swarooparani and Cannon, Maren E and Didion, John P and Hensley, John and Kirilusha, Anthony and Program, NISC Comparative Sequencing and Bonnycastle, Lori L and Taylor, D Leland and Watanabe, Richard and Mohlke, Karen L and Boehnke, Michael and Collins, Francis S and Parker, Stephen C J and Stitzel, Michael L},
doi = {10.1073/pnas.1621192114},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Varshney et al. - 2017 - Genetic regulatory signatures underlying islet gene expression and type 2 diabetes.pdf:pdf;:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Varshney et al. - 2017 - Genetic regulatory signatures underlying islet gene expression and type 2 diabetes(2).pdf:pdf},
journal = {Proceedings of the National Academy of Sciences},
month = {feb},
number = {9},
pages = {2301--2306},
title = {{Genetic regulatory signatures underlying islet gene expression and type 2 diabetes}},
url = {http://www.pnas.org/content/114/9/2301.abstract},
volume = {114},
year = {2017}
}
@article{Boj2012,
abstract = {Most studies on TCF7L2 SNP variants in the pathogenesis of type 2 diabetes (T2D) focus on a role of the encoded transcription factor TCF4 in ? cells. Here, a mouse genetics approach shows that removal of TCF4 from ? cells does not affect their function, whereas manipulating TCF4 levels in the liver has major effects on metabolism. In Tcf7l2?/? mice, the immediate postnatal surge in liver metabolism does not occur. Consequently, pups die due to hypoglycemia. By combining chromatin immunoprecipitation with gene expression profiling, we identify a TCF4-controlled metabolic gene program that is acutely activated in the postnatal liver. In concordance, adult liver-specific Tcf7l2 knockout mice show reduced hepatic glucose production during fasting and display improved glucose homeostasis when maintained on high-fat diet. Furthermore, liver-specific TCF4 overexpression increases hepatic glucose production. These observations imply that TCF4 directly activates metabolic genes and that inhibition of Wnt signaling may be beneficial in metabolic disease.},
annote = {doi: 10.1016/j.cell.2012.10.053},
author = {Boj, Sylvia F. and van Es, Johan H. and Huch, Meritxell and Li, Vivian S.W. and Jos{\'{e}}, Anabel and Hatzis, Pantelis and Mokry, Michal and Haegebarth, Andrea and van den Born, Maaike and Chambon, Pierre and Voshol, Peter and Dor, Yuval and Cuppen, Edwin and Fillat, Cristina and Clevers, Hans},
doi = {10.1016/j.cell.2012.10.053},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Boj et al. - 2012 - Diabetes Risk Gene and Wnt Effector Tcf7l2TCF4 Controls Hepatic Response to Perinatal and Adult Metabolic Demand.pdf:pdf},
issn = {0092-8674},
journal = {Cell},
month = {dec},
number = {7},
pages = {1595--1607},
publisher = {Elsevier},
title = {{Diabetes Risk Gene and Wnt Effector Tcf7l2/TCF4 Controls Hepatic Response to Perinatal and Adult Metabolic Demand}},
url = {https://doi.org/10.1016/j.cell.2012.10.053},
volume = {151},
year = {2012}
}
@article{Vinuela2019,
abstract = {Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues ({\&}lt;73{\%}), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.},
author = {Vi{\~{n}}uela, Ana and Varshney, Arushi and van de Bunt, Martijn and Prasad, Rashmi B and Asplund, Olof and Bennett, Amanda and Boehnke, Michael and Brown, Andrew and Erdos, Michael R and Fadista, Jo{\~{a}}o and Hansson, Ola and Hatem, Gad and Howald, C{\'{e}}dric and Iyengar, Apoorva K and Johnson, Paul and Krus, Ulrika and MacDonald, Patrick E and Mahajan, Anubha and {Manning Fox}, Jocelyn E and Narisu, Narisu and Nylander, Vibe and Orchard, Peter and Oskolkov, Nikolay and Panousis, Nikolaos I and Payne, Anthony and Stitzel, Michael L and Vadlamudi, Swarooparani and Welch, Ryan and Collins, Francis S and Mohlke, Karen L and Gloyn, Anna L and Scott, Laura J and Dermitzakis, Emmanouil T and Groop, Leif and Parker, Stephen C J and McCarthy, Mark I},
doi = {10.1101/655670},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Vi{\~{n}}uela et al. - 2019 - Influence of genetic variants on gene expression in human pancreatic islets – implications for type 2 diabete.pdf:pdf},
journal = {bioRxiv},
month = {jan},
pages = {655670},
title = {{Influence of genetic variants on gene expression in human pancreatic islets – implications for type 2 diabetes}},
url = {http://biorxiv.org/content/early/2019/05/31/655670.abstract},
year = {2019}
}
@article{Hormozdiari2016b,
abstract = {The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding regions of the genome. One possible hypothesis is that these GWAS risk loci alter the individual?s disease risk through their effect on gene expression in different tissues. In order to understand the mechanisms driving a GWAS risk locus, it is helpful to determine which gene is affected in specific tissue types. For example, the relevant gene and tissue could play a role in the disease mechanism if the same variant responsible for a GWAS locus also affects gene expression. Identifying whether or not the same variant is causal in both GWASs and expression quantitative trail locus (eQTL) studies is challenging because of the uncertainty induced by linkage disequilibrium and the fact that some loci harbor multiple causal variants. However, current methods that address this problem assume that each locus contains a single causal variant. In this paper, we present eCAVIAR, a probabilistic method that has several key advantages over existing methods. First, our method can account for more than one causal variant in any given locus. Second, it can leverage summary statistics without accessing the individual genotype data. We use both simulated and real datasets to demonstrate the utility of our method. Using publicly available eQTL data on 45 different tissues, we demonstrate that eCAVIAR can prioritize likely relevant tissues and target genes for a set of glucose- and insulin-related trait loci.},
annote = {doi: 10.1016/j.ajhg.2016.10.003},
author = {Hormozdiari, Farhad and van de Bunt, Martijn and Segr{\`{e}}, Ayellet V. and Li, Xiao and Joo, Jong Wha J. and Bilow, Michael and Sul, Jae Hoon and Sankararaman, Sriram and Pasaniuc, Bogdan and Eskin, Eleazar},
doi = {10.1016/j.ajhg.2016.10.003},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Hormozdiari et al. - 2016 - Colocalization of GWAS and eQTL Signals Detects Target Genes(3).pdf:pdf},
issn = {0002-9297},
journal = {The American Journal of Human Genetics},
month = {dec},
number = {6},
pages = {1245--1260},
publisher = {Elsevier},
title = {{Colocalization of GWAS and eQTL Signals Detects Target Genes}},
url = {https://doi.org/10.1016/j.ajhg.2016.10.003},
volume = {99},
year = {2016}
}
@article{Mahajan2018a,
abstract = {We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9{\%} cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency {\textless}5{\%}, 14 with estimated allelic odds ratio {\textgreater}2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for {\textgreater}80{\%} posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA {\textgreater}80{\%} to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18{\%} of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).},
author = {Mahajan, Anubha and Taliun, Daniel and Thurner, Matthias and Robertson, Neil R and Torres, Jason M and Rayner, N William and Payne, Anthony J and Steinthorsdottir, Valgerdur and Scott, Robert A and Grarup, Niels and Cook, James P and Schmidt, Ellen M and Wuttke, Matthias and Sarnowski, Chlo{\'{e}} and M{\"{a}}gi, Reedik and Nano, Jana and Gieger, Christian and Trompet, Stella and Lecoeur, C{\'{e}}cile and Preuss, Michael H and Prins, Bram Peter and Guo, Xiuqing and Bielak, Lawrence F and Below, Jennifer E and Bowden, Donald W and Chambers, John Campbell and Kim, Young Jin and Ng, Maggie C Y and Petty, Lauren E and Sim, Xueling and Zhang, Weihua and Bennett, Amanda J and Bork-Jensen, Jette and Brummett, Chad M and Canouil, Micka{\"{e}}l and Ec kardt, Kai-Uwe and Fischer, Krista and Kardia, Sharon L R and Kronenberg, Florian and L{\"{a}}ll, Kristi and Liu, Ching-Ti and Locke, Adam E and Luan, Jian'an and Ntalla, Ioanna and Nylander, Vibe and Sch{\"{o}}nherr, Sebastian and Schurmann, Claudia and Yengo, Lo{\"{i}}c and Bottinger, Erwin P and Brandslund, Ivan and Christensen, Cramer and Dedoussis, George and Florez, Jose C and Ford, Ian and Franco, Oscar H and Frayling, Timothy M and Giedraitis, Vilmantas and Hackinger, Sophie and Hattersley, Andrew T and Herder, Christian and Ikram, M Arfan and Ingelsson, Martin and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and Kriebel, Jennifer and Kuusisto, Johanna and Ligthart, Symen and Lindgren, Cecilia M and Linneberg, Allan and Lyssenko, Valeriya and Mamakou, Vasiliki and Meitinger, Thomas and Mohlke, Karen L and Morris, Andrew D and Nadkarni, Girish and Pankow, James S and Peters, Annette and Sattar, Naveed and Stan{\v{c}}{\'{a}}kov{\'{a}}, Alena and Strauch, Konstantin and Taylor, Kent D and Thorand, Barbara and Thorleifsson, Gudmar and Thorsteinsdottir, Unnur and Tuomilehto, Jaakko and Witte, Daniel R and Dupuis, Jos{\'{e}}e and Peyser, Patricia A and Zeggini, Eleftheria and Loos, Ruth J F and Froguel, Philippe and Ingelsson, Erik and Lind, Lars and Groop, Leif and Laakso, Markku and Collins, Francis S and Jukema, J Wouter and Palmer, Colin N A and Grallert, Harald and Metspalu, Andres and Dehghan, Abbas and K{\"{o}}ttgen, Anna and Abecasis, Goncalo R and Meigs, James B and Rotter, Jerome I and Marchini, Jonathan and Pedersen, Oluf and Hansen, Torben and Langenberg, Claudia and Wareham, Nicholas J and Stefansson, Kari and Gloyn, Anna L and Morris, Andrew P and Boehnke, Michael and McCarthy, Mark I},
doi = {10.1038/s41588-018-0241-6},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Mahajan et al. - 2018 - Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific.pdf:pdf;:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Mahajan et al. - 2018 - Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specif(2).pdf:pdf},
issn = {1546-1718},
journal = {Nature Genetics},
number = {11},
pages = {1505--1513},
title = {{Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps}},
url = {https://doi.org/10.1038/s41588-018-0241-6},
volume = {50},
year = {2018}
}
@article{Miguel-Escalada2019,
abstract = {Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed {\textgreater}1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.},
author = {Miguel-Escalada, Irene and Bon{\`{a}}s-Guarch, Silvia and Cebola, In{\^{e}}s and Ponsa-Cobas, Joan and Mendieta-Esteban, Julen and Atla, Goutham and Javierre, Biola M and Rolando, Delphine M Y and Farabella, Irene and Morgan, Claire C and Garc{\'{i}}a-Hurtado, Javier and Beucher, Anthony and Mor{\'{a}}n, Ignasi and Pasquali, Lorenzo and Ramos-Rodr{\'{i}}guez, Mireia and Appel, Emil V R and Linneberg, Allan and Gjesing, Anette P and Witte, Daniel R and Pedersen, Oluf and Grarup, Niels and Ravassard, Philippe and Torrents, David and Mercader, Josep M and Piemonti, Lorenzo and Berney, Thierry and de Koning, Eelco J P and Kerr-Conte, Julie and Pattou, Fran{\c{c}}ois and Fedko, Iryna O and Groop, Leif and Prokopenko, Inga and Hansen, Torben and Marti-Renom, Marc A and Fraser, Peter and Ferrer, Jorge},
doi = {10.1038/s41588-019-0457-0},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Miguel-Escalada et al. - 2019 - Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of t.pdf:pdf},
issn = {1546-1718},
journal = {Nature Genetics},
number = {7},
pages = {1137--1148},
title = {{Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes}},
url = {https://doi.org/10.1038/s41588-019-0457-0},
volume = {51},
year = {2019}
}
@article{Scott2016a,
abstract = {Type 2 diabetes (T2D) results from the combined effects of genetic and environmental factors on multiple tissues over time. Of the {\textgreater}100 variants associated with T2D and related traits in genome-wide association studies (GWAS), {\textgreater}90{\%} occur in non-coding regions, suggesting a strong regulatory component to T2D risk. Here to understand how T2D status, metabolic traits and genetic variation influence gene expression, we analyse skeletal muscle biopsies from 271 well-phenotyped Finnish participants with glucose tolerance ranging from normal to newly diagnosed T2D. We perform high-depth strand-specific mRNA-sequencing and dense genotyping. Computational integration of these data with epigenome data, including ATAC-seq on skeletal muscle, and transcriptome data across diverse tissues reveals that the tissue-specific genetic regulatory architecture of skeletal muscle is highly enriched in muscle stretch/super enhancers, including some that overlap T2D GWAS variants. In one such example, T2D risk alleles residing in a muscle stretch/super enhancer are linked to increased expression and alternative splicing of muscle-specific isoforms of ANK1.},
author = {Scott, Laura J and Erdos, Michael R and Huyghe, Jeroen R and Welch, Ryan P and Beck, Andrew T and Wolford, Brooke N and Chines, Peter S and Didion, John P and Narisu, Narisu and Stringham, Heather M and Taylor, D Leland and Jackson, Anne U and Vadlamudi, Swarooparani and Bonnycastle, Lori L and Kinnunen, Leena and Saramies, Jouko and Sundvall, Jouko and Albanus, Ricardo D'Oliveira and Kiseleva, Anna and Hensley, John and Crawford, Gregory E and Jiang, Hui and Wen, Xiaoquan and Watanabe, Richard M and Lakka, Timo A and Mohlke, Karen L and Laakso, Markku and Tuomilehto, Jaakko and Koistinen, Heikki A and Boehnke, Michael and Collins, Francis S and Parker, Stephen C J},
doi = {10.1038/ncomms11764},
file = {:home/jason/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Scott et al. - 2016 - The genetic regulatory signature of type 2 diabetes in human skeletal muscle(2).pdf:pdf},
issn = {2041-1723},
journal = {Nature Communications},
number = {1},
pages = {11764},
title = {{The genetic regulatory signature of type 2 diabetes in human skeletal muscle}},
url = {https://doi.org/10.1038/ncomms11764},
volume = {7},
year = {2016}
}
