Somatic evolution of cells within the body is well known to lead to cancers. However, spread of somatic mutations within a tissue over time may also contribute to the pathogenesis of non-neoplastic ...diseases. Recent years have seen the publication of many studies aiming to characterize somatic evolution in healthy tissues. A logical next step is to extend such work to diseased conditions. As our understanding of the interplay between somatic mutations and non-neoplastic disease grows, opportunities for the joint study of germline and somatic variants will present themselves. Here, we present our thoughts on the utility of somatic mutations for understanding both the causes and consequences of common complex disease and the challenges that remain for the joint study of the soma and germline.
Every organ is a micromosaic of cellular clones carrying distinct somatic mutations that compete for space within the tissue but do not always increase cancer risk.Somatic evolution has the potential to affect the disease progress of common complex diseases. There is emerging evidence it can initiate disease, maintain disease once started, and possibly alleviate disease in some cases.The strength of selection of mutations in particular genes appears to vary between individuals. This is likely driven by differences in both lifestyle and environmental factors as well as germline backgrounds.Existing methods for studying somatic evolution in solid tissues do not scale sufficiently to allow for a well-powered genome-wide association study of mutation rates such that further developments are required.
Abstract The exact aetiology of Crohn's disease is unknown, though it is clear from early epidemiological studies that a combination of genetic and environmental risk factors contributes to an ...individual's disease susceptibility. Here, we review the history of gene-mapping studies of Crohn's disease, from the linkage-based studies that first implicated the NOD2 locus, through to modern-day genome-wide association studies that have discovered over 140 loci associated with Crohn's disease and yielded novel insights into the biological pathways underlying pathogenesis. We describe on-going and future gene-mapping studies that utilise next generation sequencing technology to pinpoint causal variants and identify rare genetic variation underlying Crohn's disease risk. We comment on the utility of genetic markers for predicting an individual's disease risk and discuss their potential for identifying novel drug targets and influencing disease management. Finally, we describe how these studies have shaped and continue to shape our understanding of the genetic architecture of Crohn's disease.
Genetic association studies have identified 215 risk loci for inflammatory bowel disease, thereby uncovering fundamental aspects of its molecular biology. We performed a genome-wide association study ...of 25,305 individuals and conducted a meta-analysis with published summary statistics, yielding a total sample size of 59,957 subjects. We identified 25 new susceptibility loci, 3 of which contain integrin genes that encode proteins in pathways that have been identified as important therapeutic targets in inflammatory bowel disease. The associated variants are correlated with expression changes in response to immune stimulus at two of these genes (ITGA4 and ITGB8) and at previously implicated loci (ITGAL and ICAM1). In all four cases, the expression-increasing allele also increases disease risk. We also identified likely causal missense variants in a gene implicated in primary immune deficiency, PLCG2, and a negative regulator of inflammation, SLAMF8. Our results demonstrate that new associations at common variants continue to identify genes relevant to therapeutic target identification and prioritization.
Inflammatory bowel disease (IBD) is a chronic inflammatory disease associated with increased risk of gastrointestinal cancers. We whole-genome sequenced 446 colonic crypts from 46 IBD patients and ...compared these to 412 crypts from 41 non-IBD controls from our previous publication on the mutation landscape of the normal colon. The average mutation rate of affected colonic epithelial cells is 2.4-fold that of healthy colon, and this increase is mostly driven by acceleration of mutational processes ubiquitously observed in normal colon. In contrast to the normal colon, where clonal expansions outside the confines of the crypt are rare, we observed widespread millimeter-scale clonal expansions. We discovered non-synonymous mutations in ARID1A, FBXW7, PIGR, ZC3H12A, and genes in the interleukin 17 and Toll-like receptor pathways, under positive selection in IBD. These results suggest distinct selection mechanisms in the colitis-affected colon and that somatic mutations potentially play a causal role in IBD pathogenesis.
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•IBD-affected colons accrue substitutions and indels 2.4 and 7 times faster than normal•17 signatures of mutational processes, including treatment•Millimeter-scale clonal expansions late in molecular time•Distinct mechanisms of positive selection of mutations in immune-related genes
Whole-genome sequencing of inflammatory bowel disease patient samples allows insight into mutational burdens and processes associated with disease, including putative driver mutations positively selected in the diseased colon.
This protocol details the steps for data quality assessment and control that are typically carried out during case-control association studies. The steps described involve the identification and ...removal of DNA samples and markers that introduce bias. These critical steps are paramount to the success of a case-control study and are necessary before statistically testing for association. We describe how to use PLINK, a tool for handling SNP data, to perform assessments of failure rate per individual and per SNP and to assess the degree of relatedness between individuals. We also detail other quality-control procedures, including the use of SMARTPCA software for the identification of ancestral outliers. These platforms were selected because they are user-friendly, widely used and computationally efficient. Steps needed to detect and establish a disease association using case-control data are not discussed here. Issues concerning study design and marker selection in case-control studies have been discussed in our earlier protocols. This protocol, which is routinely used in our labs, should take approximately 8 h to complete.
For most immune-mediated diseases, the main determinant of patient well-being is not the diagnosis itself but instead the course that the disease takes over time (prognosis). Prognosis may vary ...substantially between patients for reasons that are poorly understood. Familial studies support a genetic contribution to prognosis, but little evidence has been found for a proposed association between prognosis and the burden of susceptibility variants. To better characterize how genetic variation influences disease prognosis, we performed a within-cases genome-wide association study in two cohorts of patients with Crohn's disease. We identified four genome-wide significant loci, none of which showed any association with disease susceptibility. Conversely, the aggregated effect of all 170 disease susceptibility loci was not associated with disease prognosis. Together, these data suggest that the genetic contribution to prognosis in Crohn's disease is largely independent of the contribution to disease susceptibility and point to a biology of prognosis that could provide new therapeutic opportunities.
Furthermore, the proportion of GWAS signals attributable to synthetic associations has profound implications for the design of GWAS follow-up studies. ...while Dickson et al. argue that synthetic ...associations are an "obvious theoretical possibility," it is worthwhile to broadly assess, in light of other theoretical and empirical evidence, the prevalence of synthetic associations in complex human disease. Large-scale sequencing studies of thousands of cases and controls will be required to fully understand the genetic architecture of complex disease. Since the prevalence of synthetic association acutely affects the design of these studies (i.e., in terms of the sample composition and width of genomic region sequenced) it is worth carefully evaluating its contribution to missing heritability.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We present shaPRS, a method that leverages widespread pleiotropy between traits or shared genetic effects across ancestries, to improve the accuracy of polygenic scores. The method uses genome-wide ...summary statistics from two diseases or ancestries to improve the genetic effect estimate and standard error at SNPs where there is homogeneity of effect between the two datasets. When there is significant evidence of heterogeneity, the genetic effect from the disease or population closest to the target population is maintained. We show via simulation and a series of real-world examples that shaPRS substantially enhances the accuracy of polygenic risk scores (PRSs) for complex diseases and greatly improves PRS performance across ancestries. shaPRS is a PRS pre-processing method that is agnostic to the actual PRS generation method, and as a result, it can be integrated into existing PRS generation pipelines and continue to be applied as more performant PRS methods are developed over time.
We introduce shaPRS, a polygenic risk score (PRS) pre-processing method that improves predictive performance of PRSs by leveraging the genetic overlap between traits or ancestries. Importantly, shaPRS requires only GWAS summary statistics of two partially correlated traits or ancestries and is agnostic with respect to the method used to generate the PRSs.
This protocol describes how to perform basic statistical analysis in a population-based genetic association case-control study. The steps described involve the (i) appropriate selection of measures ...of association and relevance of disease models; (ii) appropriate selection of tests of association; (iii) visualization and interpretation of results; (iv) consideration of appropriate methods to control for multiple testing; and (v) replication strategies. Assuming no previous experience with software such as PLINK, R or Haploview, we describe how to use these popular tools for handling single-nucleotide polymorphism data in order to carry out tests of association and visualize and interpret results. This protocol assumes that data quality assessment and control has been performed, as described in a previous protocol, so that samples and markers deemed to have the potential to introduce bias to the study have been identified and removed. Study design, marker selection and quality control of case-control studies have also been discussed in earlier protocols. The protocol should take ~1 h to complete.
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