Genomic architecture of inflammatory bowel disease in five families with multiple affected individuals.

Currently, the best clinical predictor for inflammatory bowel disease (IBD) is family history. Over 163 sequence variants have been associated with IBD in genome-wide association studies, but they have weak effects and explain only a fraction of the observed heritability. It is expected that additional variants contribute to the genomic architecture of IBD, possibly including rare variants with effect sizes larger than the identified common variants. Here we applied a family study design and sequenced 38 individuals from five families, under the hypothesis that families with multiple IBD-affected individuals harbor one or more risk variants that (i) are shared among affected family members, (ii) are rare and (iii) have substantial effect on disease development. Our analysis revealed not only novel candidate risk variants but also high polygenic risk scores for common known risk variants in four out of the five families. Functional analysis of our top novel variant in the remaining family, a rare missense mutation in the ubiquitin ligase TRIM11, suggests that it leads to increased nuclear factor of kappa light chain enhancer in B-cells (NF-κB) signaling. We conclude that an accumulation of common weak-effect variants accounts for the high incidence of IBD in most, but not all families we analyzed and that a family study design can identify novel rare variants conferring risk for IBD with potentially large effect size, such as the TRIM11 p.H414Y mutation

AWclust: point-and-click software for non-parametric population structure analysis

<p>Abstract</p> <p>Background</p> <p>Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually assume Hardy-Weinberg equilibrium (HWE) and linkage equilibrium among loci in sample population individuals. However, the assumptions may not hold and allele frequency estimation may not be accurate in some data sets. The improved version of STRUCTURE (version 2.1) can incorporate linkage information among loci but is still sensitive to high background linkage disequilibrium. Nowadays, large-scale single nucleotide polymorphisms (SNPs) are becoming popular in genetic studies. Therefore, it is imperative to have software that makes full use of these genetic data to generate inference even when model assumptions do not hold or allele frequency estimation suffers from high variation.</p> <p>Results</p> <p>We have developed point-and-click software for non-parametric population structure analysis distributed as an R package. The software takes advantage of the large number of SNPs available to categorize individuals into ethnically similar clusters and it does not require assumptions about population models. Nor does it estimate allele frequencies. Moreover, this software can also infer the optimal number of populations.</p> <p>Conclusion</p> <p>Our software tool employs non-parametric approaches to assign individuals to clusters using SNPs. It provides efficient computation and an intuitive way for researchers to explore ethnic relationships among individuals. It can be complementary to parametric approaches in population structure analysis.</p

Worldwide population differentiation at disease-associated SNPs

<p>Abstract</p> <p>Background</p> <p>Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).</p> <p>Methods</p> <p>We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.</p> <p>Results</p> <p>On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.</p> <p>Conclusion</p> <p>Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.</p

The Impact of Phenocopy on the Genetic Analysis of Complex Traits

A consistent debate is ongoing on genome-wide association studies (GWAs). A key point is the capability to identify low-penetrance variations across the human genome. Among the phenomena reducing the power of these analyses, phenocopy level (PE) hampers very seriously the investigation of complex diseases, as well known in neurological disorders, cancer, and likely of primary importance in human ageing. PE seems to be the norm, rather than the exception, especially when considering the role of epigenetics and environmental factors towards phenotype. Despite some attempts, no recognized solution has been proposed, particularly to estimate the effects of phenocopies on the study planning or its analysis design. We present a simulation, where we attempt to define more precisely how phenocopy impacts on different analytical methods under different scenarios. With our approach the critical role of phenocopy emerges, and the more the PE level increases the more the initial difficulty in detecting gene-gene interactions is amplified. In particular, our results show that strong main effects are not hampered by the presence of an increasing amount of phenocopy in the study sample, despite progressively reducing the significance of the association, if the study is sufficiently powered. On the opposite, when purely epistatic effects are simulated, the capability of identifying the association depends on several parameters, such as the strength of the interaction between the polymorphic variants, the penetrance of the polymorphism and the alleles (minor or major) which produce the combined effect and their frequency in the population. We conclude that the neglect of the possible presence of phenocopies in complex traits heavily affects the analysis of their genetic data

Genome-wide scan reveals association of psoriasis with IL-23 and NF-κB pathways

Psoriasis is a common immune-mediated disorder that affects the skin, nails and joints. To identify psoriasis susceptibility loci, we genotyped 438,670 SNPs in 1,409 psoriasis cases and 1,436 controls of European ancestry. We followed up 21 promising SNPs in 5,048 psoriasis cases and 5,041 controls. Our results provide strong support for the association of at least seven genetic loci and psoriasis (each with combined P less than 5 × 10−8). Loci with confirmed association include HLA-C, three genes involved in IL-23 signaling (IL23A, IL23R, IL12B), two genes that act downstream of TNF-α and regulate NF-κB signaling (TNIP1, TNFAIP3) and two genes involved in the modulation of Th2 immune responses (IL4, IL13). Although the proteins encoded in these loci are known to interact biologically, we found no evidence for epistasis between associated SNPs. Our results expand the catalog of genetic loci implicated in psoriasis susceptibility and suggest priority targets for study in other auto-immune disorders

Inherited determinants of Crohn's disease and ulcerative colitis phenotypes: a genetic association study

Crohn's disease and ulcerative colitis are the two major forms of inflammatory bowel disease; treatment strategies have historically been determined by this binary categorisation. Genetic studies have identified 163 susceptibility loci for inflammatory bowel disease, mostly shared between Crohn's disease and ulcerative colitis. We undertook the largest genotype association study, to date, in widely used clinical subphenotypes of inflammatory bowel disease with the goal of further understanding the biological relations between diseases

Adult Langerhans cell histiocytosis and sclerosing cholangitis: a case report and review of the literature

Sclerosing cholangitis is a rare complication of Langerhans cell histiocytosis in children which can result in liver failure. This combination is even rarer in adults