Mapping complex disease traits with global gene expression

By W. Cookson, L. Liang, Gonçalo R. Abecasis, Miriam Moffatt, M. Lathrop. Nature reviews genetics, 2009

882 citations recorded by the source corpus.

Variation in gene expression is an important mechanism underlying susceptibility to complex disease. The simultaneous genome-wide assay of gene expression and genetic variation allows the mapping of the genetic factors that underpin individual differences in quantitative levels of expression (expression QTLs; eQTLs). The availability of systematically generated eQTL information could provide immediate insight into a biological basis for disease associations identified through genome-wide association (GWA) studies, and can help to identify networks of genes involved in disease pathogenesis. Although there are limitations to current eQTL maps, understanding of disease will be enhanced with novel technologies and international efforts that extend to a wide range of new samples and tissues.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/23957808259d223597f901e670bebd29a9096307

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Citations in the corpus

Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016, methodology): “Given the extensive coverage of the study designs and methods for GWAS and transcriptomic studies from existing literatures (Cookson, Liang, Abecasis, Moffatt, & Lathrop, 2009; Manolio, 2010; Ziegler & Sun, 2012), we focus on the most recent technological development in the context of multi-omic…”
Human genetic variation and its contribution to complex traits (2009, background): “Experiments are being conducted that simultaneously assay global gene expression and genome-wide variation in a large number of individuals to map genetic factors underlying differences in expression level”
A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis (2010, background): “Since loci with weaker associations may contribute to a portion of the so-called ‘missing’ or ‘dark’ heritability [5-7], multiple locus analyses have the potential to provide a more complete picture of heritable variation.”
Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain (2010, background): “This has the potential to inform on several levels; first, it is a critical step toward understanding the pathobiological consequences of genetic variants linked to disease; second, it affords the opportunity to form inferences regarding relationships between genes based on patterns of co-regulation”
Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics (2013, background): “This strategy has been explored before and allowed the identification of the genes and regulatory variations that are important for several diseases (reviewed in [4]).”
GENETICS AND PATHOGENESIS OF INFLAMMATORY BOWEL DISEASE (2016, background): “Expression quantitative trait loci (eQTL) mapping is a method to correlate specific polymorphisms with the abundance of certain gene transcript(s) and identify potential causal variants (57).”
The genetics of quantitative traits: challenges and prospects (2009, background): “Advances in high-throughput genotyping and transcriptional profiling have facilitated an increase in the number of eQTL studie”
Rare and Common Variants: Twenty arguments (2011, background): “Expression quantitative trait locus analysis (eQTL analysis) shows that gene expression and splicing are heavily influenced by common variants, possibly for most transcript”
Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility (2010, background): “which has been further enhanced by the numerous associations between genetic markers and diseases reported in recent genome-wide association studies (GWAS) and the expected relevance of genome wide expression (GWE) to characterize the biological basis of these associations”
Genomic Views of Distant-Acting Enhancers (2009, background): “Support for the latter comes from a rapidly growing number of examples in which non-coding SNPs linked to disease traits through GWAS were found to affect the expression levels of nearby gene”