Association Analysis of Mitochondrial DNA Heteroplasmic Variants: Methods and Application

Authors

Xianbang Sun
Katia Bulekova
Jian Yang
Meng Lai
Achilleas N Pitsillides
Xue Liu
Yuankai Zhang
Xiuqing Guo
Qian Yong
Laura M Raffield
Jerome I Rotter
Stephen S Rich
Goncalo Abecasis
April P Carson
Ramachandran S Vasan
Joshua C Bis
Bruce M Psaty
Eric Boerwinkle
Annette L Fitzpatrick
Claudia L Satizabal
Dan E Arking
Jun Ding
Daniel Levy
Chunyu Liu

Language

English

Publication Date

11-1-2024

Journal

Mitochondrion

DOI

10.1016/j.mito.2024.101954

PMID

39245194

PMCID

PMC11568909

PubMedCentral® Posted Date

11-1-2025

PubMedCentral® Full Text Version

Author MSS

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 both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded 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.

Keywords

Humans, DNA, Mitochondrial, Heteroplasmy, Female, Male, Middle Aged, White People, Black People, mitochondrial DNA sequencing, heteroplasmy, association analysis, gene-based test

Published Open-Access

yes

Recommended Citation

Sun, Xianbang; Bulekova, Katia; Yang, Jian; et al., "Association Analysis of Mitochondrial DNA Heteroplasmic Variants: Methods and Application" (2024). Faculty, Staff and Student Publications. 5358.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/5358