2 items tagged with 'expression quantitative trait locus'.
Abstract (Expand)
Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most … genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.
Authors: H. Kirsten, H. Al-Hasani, L. Holdt, A. Gross, F. Beutner, K. Krohn, K. Horn, P. Ahnert, R. Burkhardt, K. Reiche, J. Hackermuller, M. Loffler, D. Teupser, J. Thiery, M. Scholz
Date Published: 15th Aug 2015
Publication Type: Journal article
PubMed ID: 26019233
Citation: Hum Mol Genet. 2015 Aug 15;24(16):4746-63. doi: 10.1093/hmg/ddv194. Epub 2015 May 27.
Created: 6th May 2019 at 11:51, Last updated: 7th Dec 2021 at 17:58
Abstract (Expand)
Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of … amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.
Authors: R. Burkhardt, H. Kirsten, F. Beutner, L. M. Holdt, A. Gross, A. Teren, A. Tonjes, S. Becker, K. Krohn, P. Kovacs, M. Stumvoll, D. Teupser, J. Thiery, U. Ceglarek, M. Scholz
PubMed ID: 26401656
Citation: PLoS Genet. 2015 Sep 24;11(9):e1005510. doi: 10.1371/journal.pgen.1005510. eCollection 2015 Sep.
Created: 6th May 2019 at 11:37, Last updated: 7th Dec 2021 at 17:58