Common Risk Alleles for Inflammatory Diseases Are Targets of Recent Positive Selection
ABSTRACT Genome-wide association studies (GWASs) have identified hundreds of loci harboring genetic variation influencing inflammatory-disease susceptibility in humans. It has been hypothesized that present day inflammatory diseases may have arisen, in part, due to pleiotropic effects of host resistance to pathogens over the course of human history, with significant selective pressures acting to increase host resistance to pathogens. The extent to which genetic factors underlying inflammatory-disease susceptibility has been influenced by selective processes can now be quantified more comprehensively than previously possible. To understand the evolutionary forces that have shaped inflammatory-disease susceptibility and to elucidate functional pathways affected by selection, we performed a systems-based analysis to integrate (1) published GWASs for inflammatory diseases, (2) a genome-wide scan for signatures of positive selection in a population of European ancestry, (3) functional genomics data comprised of protein-protein interaction networks, and (4) a genome-wide expression quantitative trait locus (eQTL) mapping study in peripheral blood mononuclear cells (PBMCs). We demonstrate that loci for inflammatory-disease susceptibility are enriched for genomic signatures of recent positive natural selection, with selected loci forming a highly interconnected protein-protein interaction network. Further, we identify 21 loci for inflammatory-disease susceptibility that display signatures of recent positive selection, of which 13 also show evidence of cis-regulatory effects on genes within the associated locus. Thus, our integrated analyses highlight a set of susceptibility loci that might subserve a shared molecular function and has experienced selective pressure over the course of human history; today, these loci play a key role in influencing susceptibility to multiple different inflammatory diseases, in part through alterations of gene expression in immune cells.
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ABSTRACT: Most human polymorphisms are neutral or slightly deleterious, but some genetic variation is advantageous and maintained in populations by balancing selection. Considered a rarity and overlooked for years, balanced polymorphisms have recently received renewed attention with several lines of evidence showing their relevance in human evolution. From theoretical work on its role in adaptation to empirical studies that identify its targets, recent developments have showed that balancing selection is more prevalent than previously thought. Here we review these developments and discuss their implications in our understanding of the influence of balancing selection in human evolution. We also review existing evidence on the biological functions that benefit most from advantageous diversity, and the functional consequences of these variants. Overall, we argue that balancing selection must be considered an important selective force in human evolution.Current Opinion in Genetics & Development 08/2014; 29C:45-51. DOI:10.1016/j.gde.2014.08.001 · 8.57 Impact Factor
Dataset: Patsopoulos2013 HLAnonHLA MS
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ABSTRACT: The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles.Current Opinion in Genetics & Development 09/2014; 29C:97-102. DOI:10.1016/j.gde.2014.08.009 · 8.57 Impact Factor