Whole-exome sequencing identifies common and rare variant metabolic QTLs in a Middle Eastern population

Abstract

Metabolomics-genome-wide association studies (mGWAS) have uncovered many metabolic quantitative trait loci (mQTLs) influencing human metabolic individuality, though predominantly in European cohorts. By combining whole-exome sequencing with a high-resolution metabolomics profiling for a highly consanguineous Middle Eastern population, we discover 21 common variant and 12 functional rare variant mQTLs, of which 45% are novel altogether. We fine-map 10 common variant mQTLs to new metabolite ratio associations, and 11 common variant mQTLs to putative protein-altering variants. This is the first work to report common and rare variant mQTLs linked to diseases and/or pharmacological targets in a consanguineous Arab cohort, with wide implications for precision medicine in the Middle East.

Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits

“…Our analysis also highlights the importance of intermediate trait QTL, including QTLs for metabolic traits and gene expression (mQTLs, geQTLs, eeQTLs, sQTLs and aseQTLs). This is not a surprising result as the significant contribution of different intermediate trait QTLs to complex trait variations have been reported in humans (7,26,(39)(40)(41) and cattle (13,(42)(43)(44). To our knowledge, no study has systematically compared the genetic importance of mQTLs with eQTLs.…”

“…Several large-scale human studies have highlighted the importance of mQTLs in various complex traits (7,45).…”

“…Many mutations affecting complex traits regulate gene transcription related activities. This has been demonstrated in many studies of human genomics, including but not limited to the analysis of intermediate trait quantitative trait loci (QTLs), such as metabolic QTLs (mQTLs) (7) and expression QTLs (eQTLs) (8) and analysis of regulatory elements, such as promoters (9) and enhancers (10) which can be identified with chromatin immunoprecipitation sequencing (ChIP-seq). In animals, the Functional Annotation of Animal Genomes (FAANG) project has started (11) and animal functional data species has been accumulating (12)(13)(14).…”

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

“…We identified 16 genotype-metabolite associations. As no previous metabolomewide GWAS in the CSF had been reported to our knowledge, we assessed the validity and novelty of the results by comparing identified loci with previous GWAS of metabolites in blood, urine, and saliva [15][16][17][18][19][43][44][45][46][47] . Many of the loci discovered in this analysis of CSF metabolites replicate loci that have been previously discovered, indicating that some of the regulatory machinery of the metabolome is shared across biological compartments.…”

“…Of these 16 SNP-metabolite associations, 10 (guanosine, ethylmalonate, 3-ureidopropionate, Nacetylhistidine, tryptophan betaine, N-acetyl-beta-alanine, N-delta-acetylornithine, bilirubin, 2'-O-methylcytidine, and methionine sulfone) have been previously identified in GWAS of blood, urine, or saliva samples [15][16][17][18][19][20] . Non-CSF regional association plots manually generated from publicly available summary statistics from Shin et al 2014 16 and Long et al 2017 17 were similar to corresponding CSF regional association plots, although the lead SNPs varied ( Supplementary Figures 18-24).…”