The genetic and phenotypic correlates of mtDNA copy number in a multi-ancestry cohort

Mitochondrial DNA copy number (mtCN) is often treated as a proxy for mitochondrial (dys)function and disease risk. Pathological changes in mtCN are common symptoms of rare mitochondrial disorders but reported associations between mtCN and common diseases vary considerably across studies. We sought to understand the biology of mtCN by carrying out genome and phenome-wide association studies of mtCN in 30,666 individuals from the Penn Medicine BioBank—a large, diverse cohort of largely African and European ancestry. We estimated mtCN in peripheral blood using exome sequence data, taking into account the effects of blood cell composition, particularly neutrophil and platelet counts. We replicated known genetic associations of mtCN in the PMBB and found that their effect sizes are highly correlated between individuals of European and African ancestry. However, the heritability of mtCN was much higher among individuals of largely African ancestry ( h 2 = 0.3) compared to European ancestry individuals ( h 2 = 0.1). Admixture mapping suggests that there are undiscovered variants underlying mtCN that are differentiated in frequency between individuals with African and European ancestry. We further show that mtCN is associated with many health-related phenotypes. We discovered robust associations between mtDNA copy number and diseases of metabolically active tissues, such as cardiovascular disease and liver damage that were consistent across African and European ancestry individuals. Other associations, such as epilepsy, prostate cancer, and disorders of iron metabolism were only discovered in either individuals with European or African ancestry, but not both. Even though we replicate known genetic and phenotypic associations of mtCN, we demonstrate that they are sensitive to blood cell composition and environmental modifiers, explaining why such associations are inconsistent across studies. Peripheral blood mtCN might therefore be used as a biomarker of mitochondrial dysfunction and disease risk, but such associations must be interpreted with care. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The Penn Medicine BioBank is supported by the Perelman School of Medicine at University of Pennsylvania, a gift from the Smilow family, and the National Center for Advancing Translational Sciences of the National Institutes of Health under CTSA award number UL1TR001878. This study was funded by NIGMS awards K99GM137076 (to A.Z.) and R35GM133708 (to I.M.). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB of University of Pennsylvania (protocol #813913) gave ethical approval for the Penn Medicine Biobank. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Individual-level genotype and phenotype data from the PMBB are not publicly available due to privacy concerns. However, all summary statistics relevant to this work are made available in Supplementary Tables S1-S4. The code is publicly available and can be accessed on GitHub (https://github.com/Arslan-Zaidi/mtcn\_pmbb).