Mitochondrial genome-wide analysis of nuclear DNA methylation quantitative trait loci.
Jaakko LaaksonenPashupati P MishraIlkka SeppäläEmma RaitoharjuSaara MarttilaNina MononenLeo-Pekka LyytikäinenMarcus E KleberGraciela E DelgadoMaija LepistöHenrikki AlmusaPekka EllonenStefan LorkowskiWinfried MärzNina Hutri-KähönenOlli RaitakariMika KähönenJukka T SalonenTerho LehtimäkiPublished in: Human molecular genetics (2022)
Mitochondria have a complex communication network with the surrounding cell and can alter nuclear DNA methylation (DNAm). Variation in the mitochondrial DNA (mtDNA) has also been linked to differential DNAm. Genome-wide association studies have identified numerous DNAm quantitative trait loci, but these studies have not examined the mitochondrial genome. Herein, we quantified nuclear DNAm from blood and conducted a mitochondrial genome-wide association study of DNAm, with an additional emphasis on sex- and prediabetes-specific heterogeneity. We used the Young Finns Study (n = 926) with sequenced mtDNA genotypes as a discovery sample and sought replication in the Ludwigshafen Risk and Cardiovascular Health study (n = 2317). We identified numerous significant associations in the discovery phase (P < 10-9), but they were not replicated when accounting for multiple testing. In total, 27 associations were nominally replicated with a P < 0.05. The replication analysis presented no evidence of sex- or prediabetes-specific heterogeneity. The 27 associations were included in a joint meta-analysis of the two cohorts, and 19 DNAm sites associated with mtDNA variants, while four other sites showed haplogroup associations. An expression quantitative trait methylation analysis was performed for the identified DNAm sites, pinpointing two statistically significant associations. This study provides evidence of a mitochondrial genetic control of nuclear DNAm with little evidence found for sex- and prediabetes-specific effects. The lack of a comparable mtDNA data set for replication is a limitation in our study and further studies are needed to validate our results.
Keyphrases
- mitochondrial dna
- copy number
- genome wide
- dna methylation
- nk cells
- oxidative stress
- genome wide association study
- gene expression
- single cell
- stem cells
- machine learning
- small molecule
- poor prognosis
- cell death
- mesenchymal stem cells
- bone marrow
- long non coding rna
- binding protein
- deep learning
- endoplasmic reticulum
- reactive oxygen species
- case control
- artificial intelligence