The Concordance and Heritability of Type 2 Diabetes in 34,166 Twin Pairs From International Twin Registers: The Discordant Twin (DISCOTWIN) Consortium.
Twin pairs discordant for disease may help elucidate the epigenetic mechanisms and causal environmental factors in disease development and progression. To obtain the numbers of pairs, especially monozygotic (MZ) twin pairs, necessary for in-depth studies while also allowing for replication, twin studies worldwide need to pool their resources. The Discordant Twin (DISCOTWIN) consortium was established for this goal. Here, we describe the DISCOTWIN Consortium and present an analysis of type 2 diabetes (T2D) data in nearly 35,000 twin pairs. Seven twin cohorts from Europe (Denmark, Finland, Norway, the Netherlands, Spain, Sweden, and the United Kingdom) and one from Australia investigated the rate of discordance for T2D in same-sex twin pairs aged 45 years and older. Data were available for 34,166 same-sex twin pairs, of which 13,970 were MZ, with T2D diagnosis based on self-reported diagnosis and medication use, fasting glucose and insulin measures, or medical records. The prevalence of T2D ranged from 2.6% to 12.3% across the cohorts depending on age, body mass index (BMI), and national diabetes prevalence. T2D discordance rate was lower for MZ (5.1%, range 2.9-11.2%) than for same-sex dizygotic (DZ) (8.0%, range 4.9-13.5%) pairs. Across DISCOTWIN, 720 discordant MZ pairs were identified. Except for the oldest of the Danish cohorts (mean age 79), heritability estimates based on contingency tables were moderate to high (0.47-0.77). From a meta-analysis of all data, the heritability was estimated at 72% (95% confidence interval 61-78%). This study demonstrated high T2D prevalence and high heritability for T2D liability across twin cohorts. Therefore, the number of discordant MZ pairs for T2D is limited. By combining national resources, the DISCOTWIN Consortium maximizes the number of discordant MZ pairs needed for in-depth genotyping, multi-omics, and phenotyping studies, which may provide unique insights into the pathways linking genes to the development of many diseases.