Human genetic analyses of organelles highlight the nucleus in age-related trait heritability

Abstract

Aging is associated with defects in many organelles, but an open question is whether the inherited risk for age-related disease is enriched within loci relevant to each organelle. Here, we begin with a focus on mitochondria, as mitochondrial dysfunction is a hallmark of age-related disease. We report a striking lack of enrichment of mitochondria-relevant loci across GWAS for 24 age-related traits. Analyses of nine additional organelles reveal enrichment only for the nucleus, particularly nuclear transcription factors. Consistent with these results, natural selection appears to exert stronger purifying selection against protein-truncating variants for transcription factors compared to mitochondrial pathways, underscoring the importance of inherited variation in gene-regulation in age-related traits.

Precise modulation of transcription factor levels reveals drivers of dosage sensitivity

“…For instance, TFs are strongly enriched for haploinsufficient disease associations, resulting from the loss of one functional allele and ∼50% dosage reduction, and are depleted of loss-of-function (LoF) variants in the general population 7, 8 . Genome-wide association studies have revealed thousands of trait-associated common variants, many of which likely act by modulating RE activity and target gene expression levels 9, 10 ; trait-associated variants are also highly enriched around TF genes 11, 12 . Both experimental and population-level data generally suggest per-allele effects of up to 10-15% 13, 14 , which may be even smaller for important, dosage-sensitive genes such as TFs.…”

Nuclear genetic control of mtDNA copy number and heteroplasmy in humans

“…We next tested mtCN corr for heritability enrichment in genes associated with organelles or organs using stratified LD-score regression (S-LDSC, Finucane et al, 2015, 2018; Gupta et al, 2021), Methods ). Encouragingly, the most significant organelle enrichment was seen for the mitochondrion ( Supplementary figure 4C ).…”

“…Published mtscATACseq data used for chrM:302 analysis can be obtained via approval from dbGaP. Gene-sets for enrichment analyses can be obtained using COMPARTMENTS (https://compartments.jensenlab.org) and MitoCarta 2.0 (https://www.broadinstitute.org/files/shared/metabolism/mitocarta/human.mitocarta2.0.html) as described previously (Gupta et al, 2021). The GRCh37 and GRCh38 reference genomes as well as other standard reference data are available via the GATK resource bundle: https://gatk.broadinstitute.org/hc/en-us/articles/360035890811-Resource-bundle.…”

Precision mitochondrial medicine

“…The majority of candidate gene studies have been underpowered for the effect size being reported, questioning the strength of the original findings, which often did not incorporate well-known nuclear genetic risk loci in the same analyses. Although mitochondrial genes have fallen within high risk loci mapped for common disorders in hypothesis-free genome-wide association studies (as for ATP5G1 in type 2 diabetes) 79 , a recent meta-analysis found no evidence of enrichment for mitochondrial genes in genome-wide association data for 24 age-related human traits 80 . There are therefore no convincing validated examples of specific nuclear alleles associated with common diseases within known mitochondrial genes.…”

“…This is, perhaps, surprising given the previous arguments made in this review. However, functional redundancy of essential metabolic pathways and the semi-autonomous nature of mitochondria are potential explanations 80 .…”