Sign in

Abstract

Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell type composition. Here, we studied MT-CN variation in blood-derived DNA from 19,184 Finnish individuals using a combination of genome (N = 4,163) and exome sequencing (N = 19,034) data as well as imputed genotypes (N = 17,718). We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6x10-8), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0x10-8), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0x10-21) and other metabolic syndrome (metS) related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell type composition. These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISZaidi '23Longchamps '21Pecina '23Chong '22Shastry '25Oppong '22
66% semantic matchGenetic & Genomic Medicine
Arslan A. Zaidi, Anurag Verma, Colleen Morse+3 more·Human Genetics and Genomics Advances·May 9, 2023· 12 citations