Abstract Aging is the main risk factor for many chronic diseases, including late onset Alzheimer's disease (LOAD) and many age-related metabolic diseases, such as obesity and diabetes. Using AD as an example, the number of people with AD doubles every 5 years beyond age 65. In 2017, 5.3 million Americans 65 years or older are affected by LOAD. The burden of health care costs for LOAD is enormous ? $259 billion in 2017. Thus, early detection and treatment of these age-related diseases should be a core tenet of public health. Research is needed to guide such efforts. Over the last decade, accumulating evidence has linked aging to mitochondrial dysfunction. Mitochondria are tiny powerhouses, generating more than 90% of energy to support normal cellular function. Mitochondria contain their own genome (mtDNA) which is both polymorphic and heteroplasmic, i.e., two or more mtDNA alleles can co-exist in the same cell due to the presence of many mtDNA molecules within any cell. Previous studies in Europeans have found that reduced mtDNA copy number was associated with frailty and higher mortality among elderly. Furthermore, reduced mtDNA copy number in human cerebrospinal fluid was observed at least a decade before clinic AD symptoms develop. These findings in Europeans need to be generalized in other ethnic groups. Several hundreds of mtDNA rare mutations have been described to cause mostly rare, yet severe maternally inherited diseases. A limited number of common mtDNA polymorphisms were examined in relation to metabolic disorders, dementia and cognitive functions. Robust associations, however, haven't been established between common mtDNA polymorphisms and age-related common diseases. In most of these previous studies, heteroplasmic mtDNA mutations haven't been well studied with respect to aging and age-related human diseases because, until recently, sequencing has been extremely costly. Studying a spectrum of mtDNA mutations along with mtDNA copy number in relation to age-related traits in large samples has now become possible thanks to drastically decreased whole genome sequencing costs. This proposed study will leverage five prospective cohorts, each with whole genome sequencing data generated from the National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) and extensive cognitive, brain structure, and cardiometabolic measures. The expected outcomes of the work proposed are to 1) develop a novel statistical method to identify age-related heteroplasmic (i.e., somatic) mtDNA mutations, and 2) develop a statistical framework to analyze mtDNA copy number and heteroplasmic mutations in relation to key age-related disorders, include LOAD and age-related metabolic traits. Results of this investigation are expected to advance understanding of the role of aging on the mitochondrial genome, and in turn, the contributions of mitochondrial genome to age-related traits. Equally important, a positive impact of this project will be advancing knowledge of the role of mtDNA in a spectrum of age-related complex phenotypes.