Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits
(2023) In Nature Communications 14.- Abstract
- We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more... (More)
- We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue. © 2023, Springer Nature Limited. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7d0a1863-4e00-4890-92a3-4e041a7bc2c0
- author
- Brown, A.A.
; Giordano, G.N.
LU
; Ridderstråle, M.
LU
; Franks, P.W.
LU
; Atabaki-Pasdar, N.
LU
; Fitipaldi, H. LU ; Groop, L. LU ; Klintenberg, M. LU ; Pomares-Millan, H. LU
and Viñuela, A.
- author collaboration
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Genomics, Humans, Multifactorial Inheritance, Phenotype, Research Personnel, RNA, Messenger, messenger RNA, plasma protein, protein kinase Lck, transcription factor, blood, gene expression, genetic analysis, phenotype, protein, RNA, 5' untranslated region, adult, aged, Article, biochemical analysis, cohort analysis, DNA extraction, donor, exon, fasting blood glucose level, female, functional enrichment analysis, gene linkage disequilibrium, genetic association, genetic heterogeneity, genetic regulation, genetic variation, genome-wide association study, genotyping, human, impaired glucose tolerance, major clinical study, male, mitochondrion, non insulin dependent diabetes mellitus, pancreas islet, phenotypic variation, pleiotropy, proteomics, quantitative trait locus, RNA sequencing, single nucleotide polymorphism, transcription regulation, Y chromosome, genomics, multifactorial inheritance, personnel
- in
- Nature Communications
- volume
- 14
- article number
- 5062
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85168454423
- pmid:37604891
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-023-40569-3
- language
- English
- LU publication?
- yes
- id
- 7d0a1863-4e00-4890-92a3-4e041a7bc2c0
- date added to LUP
- 2023-12-19 16:52:52
- date last changed
- 2024-05-02 04:08:49
@article{7d0a1863-4e00-4890-92a3-4e041a7bc2c0, abstract = {{We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue. © 2023, Springer Nature Limited.}}, author = {{Brown, A.A. and Giordano, G.N. and Ridderstråle, M. and Franks, P.W. and Atabaki-Pasdar, N. and Fitipaldi, H. and Groop, L. and Klintenberg, M. and Pomares-Millan, H. and Viñuela, A.}}, issn = {{2041-1723}}, keywords = {{Genomics; Humans; Multifactorial Inheritance; Phenotype; Research Personnel; RNA, Messenger; messenger RNA; plasma protein; protein kinase Lck; transcription factor; blood; gene expression; genetic analysis; phenotype; protein; RNA; 5' untranslated region; adult; aged; Article; biochemical analysis; cohort analysis; DNA extraction; donor; exon; fasting blood glucose level; female; functional enrichment analysis; gene linkage disequilibrium; genetic association; genetic heterogeneity; genetic regulation; genetic variation; genome-wide association study; genotyping; human; impaired glucose tolerance; major clinical study; male; mitochondrion; non insulin dependent diabetes mellitus; pancreas islet; phenotypic variation; pleiotropy; proteomics; quantitative trait locus; RNA sequencing; single nucleotide polymorphism; transcription regulation; Y chromosome; genomics; multifactorial inheritance; personnel}}, language = {{eng}}, publisher = {{Nature Publishing Group}}, series = {{Nature Communications}}, title = {{Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits}}, url = {{http://dx.doi.org/10.1038/s41467-023-40569-3}}, doi = {{10.1038/s41467-023-40569-3}}, volume = {{14}}, year = {{2023}}, }