Biology subjects

Chris Cotsapas

Publications and source records attributed to Chris Cotsapas.

5 recordsLinked to original sources

bioRxiv2016

NR1H3 p.Arg415Gln is not associated to multiple sclerosis risk

A recent study by Wang et al claims the low-frequency variant NR1H3 p.Arg415Gln is pathological for multiple sclerosis and determines a patients likelihood of primary progressive disease. We sought to replicate this finding in the International MS Genetics Consortium (IMSGC) patient collection, which is 13-fold larger than the collection of Wang et al, but we find no evidence that this variant is associated either with MS or disease subtype. Wang et al also report a common variant association in the region, which we show captures the association the IMSGC reported in 2013. Therefore, we conclude that the reported low-frequency association is a false positive, likely generated by insufficient sample size. The claim of NR1H3 mutations describing a Mendelian form of MS - of which no examples exist - can therefore not be substantiated by data.

Genetics↗

bioRxiv2016

Large-scale trans-eQTLs affect hundreds of transcripts and mediate patterns of transcriptional co-regulation

Genetic variation affecting gene regulation is a driver of phenotypic differences between individuals and can be used to uncover how biological processes are organized in a cell. Although detecting cis-eQTLs is now routine, trans-eQTLs have proven more challenging to find due to the modest variance explained and the multiple testing burden when comparing millions of SNPs for association to thousands of transcripts. Here, we provide evidence for the existence of trans-eQTLs by looking for SNPs associated with the expression of multiple genes simultaneously. We find substantial evidence of trans-eQTLs, with an 1.8-fold enrichment in nominally significant markers in all three populations and significant overlap between results across the populations. These trans-eQTLs target the same genes and show the same direction of effect across populations. We define a high-confidence set of eight independent trans-eQTLs which are associated to multiple transcripts in all three populations, and affect the same targets in all three populations with the same direction of effect. We then show that target transcripts of trans-eQTLs encode proteins that interact more frequently than expected by chance, and are enriched for pathway annotations indicative of roles in basic cell homeostasis. Thus, we have demonstrated that trans-eQTLs can be accurately identified even in studies of limited sample size.

Genetics↗

bioRxiv2016

Integrative genetic and epigenetic analysis uncovers regulatory mechanisms of autoimmune disease

Genome-wide association studies in autoimmune and inflammatory diseases (AID) have uncovered hundreds of loci mediating risk1,2. These associations are preferentially located in non-coding DNA regions3,4 and in particular to tissue-specific Dnase I hypersensitivity sites (DHS)5,6. Whilst these analyses clearly demonstrate the overall enrichment of disease risk alleles on gene regulatory regions, they are not designed to identify individual regulatory regions mediating risk or the genes under their control, and thus uncover the specific molecular events driving disease risk. To do so we have departed from standard practice by identifying regulatory regions which replicate across samples, and connect them to the genes they control through robust re-analysis of public data. We find substantial evidence of regulatory potential in 132/301 (44%) risk loci across nine autoimmune and inflammatory diseases, and are able to prioritize a single gene in 104/132 (79%) of these. Thus, we are able to generate testable mechanistic hypotheses of the molecular changes that drive disease risk.

Genetics↗

bioRxiv2016

Shared effect modeling reveals that a fraction of autoimmune disease associations are consistent with eQTLs in three immune cell types

The majority of autoimmune disease risk effects identified by genome-wide association studies (GWAS) localize to open chromatin with gene regulatory activity. GWAS loci are also enriched for expression quantitative trait loci (eQTLs), suggesting that most disease risk variants exert their pathological effects by altering gene expression1,2. However, because causal variants are difficult to identify and cis-eQTLs occur frequently, it remains challenging to translate this bulk observation into specific instances of a disease risk variant driving changes to gene regulation. Here, we use a novel joint likelihood framework with higher resolution than previous methods to identify loci where disease risk and an eQTL are driven by a single, shared genetic effect as opposed to distinct effects in close proximity. We find that approximately 25% of autoimmune disease loci harbor an eQTL driven by the same genetic ...

Genetics↗

bioRxiv2015

Network analysis of genome-wide selective constraint reveals a gene network active in early fetal brain intolerant of mutation

Using robust, integrated analysis of multiple genomic datasets, we show that genes depleted for non-synonymous de novo mutations form a subnetwork of 72 members under strong selective constraint. We further show this subnetwork is preferentially expressed in the early development of the human hippocampus and is enriched for genes mutated in neurological, but not other, Mendelian disorders. We thus conclude that carefully orchestrated developmental processes are under strong constraint in early brain development, and perturbations caused by mutation have adverse outcomes subject to strong purifying selection. Our findings demonstrate that selective forces can act on groups of genes involved in the same process, supporting the notion that adaptation can act coordinately on multiple genes. Our approach provides a statistically robust, interpretable way to identify the tissues and developmental times where groups of disease genes are active. Our findings highlight the importance of considering the interactions between genes when analyzing genome-wide sequence data.

Genetics↗