학술논문

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences
Document Type
article
Source
Human Genomics. 15(1)
Subject
Biological Sciences
Genetics
Human Genome
2.1 Biological and endogenous factors
Aetiology
Metabolic and endocrine
Adult
Aged
Apoptosis Regulatory Proteins
Cell Lineage
DNA Copy Number Variations
DNA
Mitochondrial
Female
GTP-Binding Proteins
Genetic Predisposition to Disease
Genome
Mitochondrial
Genome-Wide Association Study
Humans
Male
Membrane Proteins
Mendelian Randomization Analysis
Middle Aged
Phenotype
Polymorphism
Single Nucleotide
Proto-Oncogene Proteins c-myb
Sequence Analysis
DNA
Exome Sequencing
Metabolic syndrome
Mitochondrial content
Human genetics
Human genome sequencing
Genome-wide association studies
Mendelian randomization
Genetics & Heredity
Biochemistry and cell biology
Language
Abstract
BackgroundMitochondrial 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 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718).ResultsWe identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10-8), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 × 10-8), 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 = 2.0 × 10-21) 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.ConclusionThese 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.