Mitochondria play an essential role in cellular function and impact human health through varied mechanisms, including energy metabolism, cell signaling, and apoptosis. We have previously demonstrated that mitochondrial DNA copy number (mtDNA-CN), which reflects some aspects of mitochondrial function, can readily be measured from DNA extracted from buffy coat, and is associated with various aging-related diseases and phenotypes. The recent availability of whole-genome sequence (WGS) data in large biobanks, along with plasma metabolomics and proteomics, vastly expands the ability to assess mitochondrial function in large sample sizes. Specifically, we hypothesize that a comprehensive assessment of mtDNA variation, including mtDNA-CN, homoplasmy (inherited variation), and heteroplasmy (somatic variation) in 680,000 subjects, combined with metabolomics/proteomics, will identify novel causal associations between mitochondrial function and all-cause mortality, CVD, and frailty. To test this hypothesis we will first identify plasma metabolites/proteins associated with mitochondrial function. We focus on identifying metabolites/proteins associated with mtDNA sequence variation, leveraging the concept of Mendelian randomization (MR) to avoid confounding. We will study omics measured in up to 300,000 UK Biobank (UKB) participants, with validation in TOPMed samples (n~25,000), and compare associations with mtDNA sequence variation to those for mtDNA-CN. Biomarkers associated with mtDNA genetic variation and not mtDNA-CN will be considered orthogonal biomarkers. Second, we will stablish phenotypic associations between biomarkers of mitochondrial function and aging-related diseases. We will determine the association of mitochondrial function biomarker with all-cause mortality, CVD, CVD risk factors, and frailty in UKB samples, with validation in TOPMed samples. We will also explore multivariable models looking for potential interactions between the various measures of mitochondr