@article {9502, title = {Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk.}, journal = {J Am Heart Assoc}, year = {2023}, month = {2023 Oct 07}, pages = {e029090}, abstract = {

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95\% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

}, issn = {2047-9980}, doi = {10.1161/JAHA.122.029090}, author = {Liu, Xue and Sun, Xianbang and Zhang, Yuankai and Jiang, Wenqing and Lai, Meng and Wiggins, Kerri L and Raffield, Laura M and Bielak, Lawrence F and Zhao, Wei and Pitsillides, Achilleas and Haessler, Jeffrey and Zheng, Yinan and Blackwell, Thomas W and Yao, Jie and Guo, Xiuqing and Qian, Yong and Thyagarajan, Bharat and Pankratz, Nathan and Rich, Stephen S and Taylor, Kent D and Peyser, Patricia A and Heckbert, Susan R and Seshadri, Sudha and Boerwinkle, Eric and Grove, Megan L and Larson, Nicholas B and Smith, Jennifer A and Vasan, Ramachandran S and Fitzpatrick, Annette L and Fornage, Myriam and Ding, Jun and Carson, April P and Abecasis, Goncalo and Dupuis, Jos{\'e}e and Reiner, Alexander and Kooperberg, Charles and Hou, Lifang and Psaty, Bruce M and Wilson, James G and Levy, Daniel and Rotter, Jerome I and Bis, Joshua C and Satizabal, Claudia L and Arking, Dan E and Liu, Chunyu} } @article {9323, title = {Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts.}, journal = {Neurology}, year = {2023}, month = {2023 Mar 16}, abstract = {

BACKGROUND AND OBJECTIVES: Previous studies suggest lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer{\textquoteright}s disease (AD) and AD related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.

METHODS: We included dementia-free participants from nine diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within {\textpm}5 years (i.e., cross-sectional analyses) or 5 to 20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (<60 vs. >=60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed Mendelian randomization (MR) analyses to assess causality.

RESULTS: We included up to 19,152 participants (mean age 59 years, 57\% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (Beta=0.04; 95\% CI 0.02, 0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.

DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the US. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.

}, issn = {1526-632X}, doi = {10.1212/WNL.0000000000207157}, author = {Zhang, Yuankai and Liu, Xue and Wiggins, Kerri L and Kurniansyah, Nuzulul and Guo, Xiuqing and Rodrigue, Amanda L and Zhao, Wei and Yanek, Lisa R and Ratliff, Scott M and Pitsillides, Achilleas and Aguirre Pati{\~n}o, Juan Sebastian and Sofer, Tamar and Arking, Dan E and Austin, Thomas R and Beiser, Alexa S and Blangero, John and Boerwinkle, Eric and Bressler, Jan and Curran, Joanne E and Hou, Lifang and Hughes, Timothy M and Kardia, Sharon L and Launer, Lenore and Levy, Daniel and Mosley, Tom H and Nasrallah, Ilya M and Rich, Stephen S and Rotter, Jerome I and Seshadri, Sudha and Tarraf, Wassim and Gonz{\'a}lez, Kevin A and Ramachandran, Vasan and Yaffe, Kristine and Nyquist, Paul A and Psaty, Bruce M and DeCarli, Charles S and Smith, Jennifer A and Glahn, David C and Gonz{\'a}lez, Hector M and Bis, Joshua C and Fornage, Myriam and Heckbert, Susan R and Fitzpatrick, Annette L and Liu, Chunyu and Satizabal, Claudia L} } @article {9580, title = {Association analysis of mitochondrial DNA heteroplasmic variants: methods and application.}, journal = {medRxiv}, year = {2024}, month = {2024 Jan 13}, 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 and genes ( <0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations ( <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.

}, doi = {10.1101/2024.01.12.24301233}, author = {Sun, Xianbang and Bulekova, Katia and Yang, Jian and Lai, Meng and Pitsillides, Achilleas N and Liu, Xue and Zhang, Yuankai and Guo, Xiuqing and Yong, Qian and Raffield, Laura M and Rotter, Jerome I and Rich, Stephen S and Abecasis, Goncalo and Carson, April P and Vasan, Ramachandran S and Bis, Joshua C and Psaty, Bruce M and Boerwinkle, Eric and Fitzpatrick, Annette L and Satizabal, Claudia L and Arking, Dan E and Ding, Jun and Levy, Daniel and Liu, Chunyu} }