The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5′-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.
The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. We isolated monocytes from 134 genotyped individuals, stimulated the cells with three defined microbe-associated molecular patterns (LPS, MDP, and pppdsRNA), and profiled the transcriptome at three time points. After mapping expression quantitative trait loci (eQTL), we identified 417 response eQTLs (reQTLs) with differing effect between the conditions. We characterized the dynamics of genetic regulation on early and late immune response, and observed an enrichment of reQTLs in distal cis-regulatory elements. Response eQTLs are also enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover novel reQTL effects in multiple GWAS loci, and show a stronger enrichment of response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli modifying genetic predisposition to disease. Main TextAn increasingly popular approach to identify genetic factors affecting interindividual variation in immune response is mapping expression quantitative trait loci (eQTLs) -variants that associate to gene expression -and to identify so-called response eQTLs (reQTLs) where the eQTL effect differs between immune stimuli [1][2][3][4][5][6] .Such genetic variants can impact the transcriptional response to infection, and also represent genetic effects that are modified by the infectious environment via gene-byenvironment interactions. In this study, we create a data set of a large number of . CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/116376 doi: bioRxiv preprint first posted online Mar. 13, 2017; -3 -immune stimulus conditions, with monocytes activated with microbial ligands for three different pattern recognition receptor (PRR) families at two different time points, next to the baseline condition.To examine the time course of innate immune responses, we first profiled gene expression in monocytes of five individuals using Human HT-12 v4 Expression BeadChips (Illumina) at six time points after stimulation with three prototypical microbial ligands: Lipopolysaccharide (LPS) was used to activate TLR4, muramyl-dipeptide (MDP) to stimulate NOD2, and 5'-triphosphate RNA (RNA) to activate RIG-I. Hierarchical clustering revealed early differentially expressed (DE) genes at 45 and 90 minutes after stimulation and late DE genes between 3 and 24 hours ( Supplementary Fig. 1). For the full eQTL cohort, we analyzed primary monocytes isolated from 134 healthy male individuals (185 before quality control), which were either untreated (baseline) or stimulated with the same three pathogenderived stimuli, and gene expression was profiled after 90 ...
The pathogenesis of androgenetic alopecia (AGA, male-pattern baldness) is driven by androgens, and genetic predisposition is the major prerequisite. Candidate gene and genome-wide association studies have reported that single-nucleotide polymorphisms (SNPs) at eight different genomic loci are associated with AGA development. However, a significant fraction of the overall heritable risk still awaits identification. Furthermore, the understanding of the pathophysiology of AGA is incomplete, and each newly associated locus may provide novel insights into contributing biological pathways. The aim of this study was to identify unknown AGA risk loci by replicating SNPs at the 12 genomic loci that showed suggestive association (5 × 10(-8)
Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of singlenucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3′-mRNA transcripts of 288 genes. Hippocampal cismeQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cisacting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders.
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