Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences

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http://hdl.handle.net/10138/330957

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Human Genomics. 2021 Jun 07;15(1):34

Titel: Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences
Författare: Ganel, Liron; Chen, Lei; Christ, Ryan; Vangipurapu, Jagadish; Young, Erica; Das, Indraniel; Kanchi, Krishna; Larson, David; Regier, Allison; Abel, Haley; Kang, Chul J.; Scott, Alexandra; Havulinna, Aki; Chiang, Charleston W. K.; Service, Susan; Freimer, Nelson; Palotie, Aarno; Ripatti, Samuli; Kuusisto, Johanna; Boehnke, Michael; Laakso, Markku; Locke, Adam; Stitziel, Nathan O.; Hall, Ira M.
Utgivare: BioMed Central
Datum: 2021-06-07
Permanenta länken (URI): http://hdl.handle.net/10138/330957
Abstrakt: Abstract Background 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 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). Results We 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. Conclusion 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.
Subject: Metabolic syndrome
Mitochondrial content
Human genetics
Human genome sequencing
Genome-wide association studies
Mendelian randomization
Licens: The Author(s)


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