Association analysis of mitochondrial DNA heteroplasmic variants: methods and application

ABSTRACT We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on bothpooled samples and within each ancestry group. Our results suggest that mtDNA-Enco ded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the RNR1 and RNR2 genes (p<0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations (p<0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations. Competing Interest Statement The authors have declared no competing interest. Funding Statement We included detailed acknowledgment for each cohort in Supplemental Materials. We thank the staff and participants of the ARIC, CHD, FHS, JHS, and MESA cohorts for phenotype data collections and providing biological samples and data for TOPMed. Whole genome sequencing (WGS) for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). Centralized read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (R01HL-117626-02S1; contract HHSN268201800002I). Phenotype harmonization, data management, sample-identity QC, and general study coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393-02S1; contract HHSN268201800001I). Method development and statistical analysis was supported by R21HL144877 (X.S., K.B., A.P., and C.L.), R01AG059727 (X.L, C.L., and C.S.) and R01HL15569 (M.L.). The views expressed in this manuscript are. those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. 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: We included detailed acknowledgment for each cohort in Supplemental Materials. We thank the staff and participants of the ARIC, CHD, FHS, JHS, and MESA cohorts for phenotype data collections and providing biological samples and data for TOPMed. Whole genome sequencing (WGS) for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). Centralized read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (R01HL-117626-02S1; contract HHSN268201800002I). Phenotype harmonization, data management, sample-identity QC, and general study coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393-02S1; contract HHSN268201800001I). Method development and statistical analysis was supported by R21HL144877 (X.S., K.B., A.P., and C.L.), R01AG059727 (X.L, C.L., and C.S.) and R01HL15569 (M.L.). The views expressed in this manuscript are. those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. 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, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Declaration of interests The authors have nothing to disclose, except for the disclosure from following authors. Dr. Abecasis reports grants from National Heart Lung and Blood Institute (NIH), during the conduct of the study; personal fees and other from Regeneron Pharmaceuticals, outside the submitted work; Dr. Psaty serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson; outside the submitted work. Data Availability All data produced are available online at https://www.ncbi.nlm.nih.gov/gap/