Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility
By T. Zeller, P. Wild, Silke Szymczak, M. Rotival, A. Schillert, R. Castagné, Seraya Maouche, M. Germain, K. Lackner, H. Rossmann and 17 more. PLoS ONE, 2010
678 citations recorded by the source corpus.
Background Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes. Methodology/Principal Findings To get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78×10−12), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9×10−7), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself. Conclusions/Significance This study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment.
Subfields: Epidemiology, Genetics, Immunology
View Paper: https://www.semanticscholar.org/paper/1892e1f445e057dce152a6d8089152894680b504
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Citations in the corpus
- Annotation of functional variation in personal genomes using RegulomeDB (2012, methodology): “We also include a large collection of eQTL (Myers et al. 2007; Stranger et al. 2007; Schadt et al. 2008; Veyrieras et al. 2008; Dimas et al. 2009; Gibbs et al. 2010; Montgomery et al. 2010; Pickrell et al. 2010; Zeller et al. 2010), dsQTL (Degner et al. 2012), and ChIP-exo (Rhee and Pugh 2011) data.”
- A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease (2011, positive): “The risk allele of this SNP has been strongly linked with increased expression level of LIPA mRNA in circulating monocyte”
- A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease (2015, positive): “SNP rs10840293 and other SNPs in strong LD are cis eQTLs for SWAP70 in naive and challenged monocytes 27 , with SNP rs93138 showing strong association with CAD ( P = 5.5 × 10 −8 ) and being a cis eQTL for SWAP70 in naive and challenged monocytes 28 , fat 29 , skin 29 and lung 22 ( Supplementary…”