How genetic risk contributes to autoimmune liver disease

Genome-wide association studies (GWAS) for autoimmune hepatitis (AIH) and GWAS/genome-wide meta-analyses (GWMA) for primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) have been successful over the past decade, identifying about 100 susceptibility loci in the human genome, with strong associations with the HLA locus and many susceptibility variants outside the HLA locus with relatively low risk. However, identifying causative variants and genes and determining their effects on liver cells and their immunological microenvironment is far from trivial. Polygenic risk scores (PRSs) based on current genome-wide data have limited potential to predict individual disease risk. Interestingly, results of mediated expression score regression analysis provide evidence that a substantial portion of gene expression at susceptibility loci is mediated by genetic risk variants, in contrast to many other complex diseases. Genome- and transcriptome-wide comparisons between AIH, PBC, and PSC could help to better delineate the shared inherited component of autoimmune liver diseases (AILDs), and statistical fine-mapping, chromosome X-wide association testing, and genome-wide in silico drug screening approaches recently applied to GWMA data from PBC could potentially be successfully applied to AIH and PSC. Initial successes through single-cell RNA sequencing (scRNA-seq) experiments in PBC and PSC now raise high hopes for understanding the impact of genetic risk variants in the context of liver-resident immune cells and liver cell subpopulations, and for bridging the gap between genetics and disease

LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons

<p>Abstract</p> <p>Background</p> <p>Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs).</p> <p>Results</p> <p>We have developed a software tool <it>LTRharvest </it>for the <it>de novo </it>detection of full length LTR retrotransposons in large sequence sets. <it>LTRharvest </it>efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of <it>LTRharvest </it>against a gold standard annotation for <it>Saccharomyces cerevisae </it>and <it>Drosophila melanogaster </it>shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of <it>LTRharvest </it>over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software.</p> <p>Conclusion</p> <p><it>LTRharvest </it>is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes <it>LTRharvest </it>a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.</p

Parallelizing Epistasis Detection in GWAS on FPGA and GPU-Accelerated Computing Systems

This is a post-peer-review, pre-copyedit version of an article published in IEEE - ACM Transactions on Computational Biology and Bioinformatics. The final authenticated version is available online at: http://dx.doi.org/10.1109/TCBB.2015.2389958[Abstract] High-throughput genotyping technologies (such as SNP-arrays) allow the rapid collection of up to a few million genetic markers of an individual. Detecting epistasis (based on 2-SNP interactions) in Genome-Wide Association Studies is an important but time consuming operation since statistical computations have to be performed for each pair of measured markers. Computational methods to detect epistasis therefore suffer from prohibitively long runtimes; e.g., processing a moderately-sized dataset consisting of about 500,000 SNPs and 5,000 samples requires several days using state-of-the-art tools on a standard 3 GHz CPU. In this paper, we demonstrate how this task can be accelerated using a combination of fine-grained and coarse-grained parallelism on two different computing systems. The first architecture is based on reconfigurable hardware (FPGAs) while the second architecture uses multiple GPUs connected to the same host. We show that both systems can achieve speedups of around four orders-of-magnitude compared to the sequential implementation. This significantly reduces the runtimes for detecting epistasis to only a few minutes for moderatelysized datasets and to a few hours for large-scale datasets.London. Wellcome Trust; 076113London. Wellcome Trust; 08547

FPGA-based Acceleration of Detecting Statistical Epistasis in GWAS

AbstractGenotype-by-genotype interactions (epistasis) are believed to be a significant source of unexplained genetic variation causing complex chronic diseases but have been ignored in genome-wide association studies (GWAS) due to the computational burden of analysis. In this work we show how to benefit from FPGA technology for highly parallel creation of contingency tables in a systolic chain with a subsequent statistical test. We present the implementation for the FPGA-based hardware platform RIVYERA S6-LX150 containing 128 Xilinx Spartan6-LX150 FPGAs. For performance evaluation we compare against the method iLOCi[9]. iLOCi claims to outperform other available tools in terms of accuracy. However, analysis of a dataset from the Wellcome Trust Case Control Consortium (WTCCC) with about 500,000 SNPs and 5,000 samples still takes about 19hours on a MacPro workstation with two Intel Xeon quad-core CPUs, while our FPGA-based implementation requires only 4minutes

Replication study of ulcerative colitis risk loci in a Lithuanian-Latvian case control sample

Background: Differences between populations might be reflected in their different genetic risk maps to complex diseases, for example, inflammatory bowel disease. We here investigated the role of known inflammatory bowel disease associated single nucleotide polymorphisms (SNPs) in a subset of patients with ulcerative colitis (UC) from the Northeastern European countries Lithuania and Latvia and evaluated possible epistatic interactions between these genetic variants. Methods: We investigated 77 SNPs derived from 5 previously published genome-wide association studies for Crohn's disease and UC. Our study panel comprised 444 Lithuanian and Latvian patients with UC and 1154 healthy controls. Single marker case control association and SNP-SNP epistasis analyses were performed. Results: We found 14 SNPs tagging 9 loci, including 21q21.1, NKX2-3, MST1, the HLA region, 1p36.13, IL10, JAK2, ORMDL3, and IL23R, to be associated with UC. Interestingly, the association of UC with previously identified variants in the HLA region was not the strongest association in our study (P = 4.34 × 1023, odds ratio [OR] = 1.25), which is in contrast to all previously published studies. No association with any disease subphenotype was found. SNP-SNP interaction analysis showed significant epistasis between SNPs in the PTPN22 (rs2476601) and C13orf31 (rs3764147) genes and increased risk for UC (P = 1.64 × 1026, OR = 2.44). The association has been confirmed in the Danish study group (P = 0.04, OR = 3.25). Conclusions: We confirmed the association of the 9 loci (21q21.1, 1p36.13, NKX2-3, MST1, the HLA region, IL10, JAK2, ORMDL3, and IL23R) with UC in the Lithuanian Latvian population. SNP-SNP interaction analyses showed that the combination of SNPs in the PTPN22 (rs2476601) and C13orf31 (rs3764147) genes increase the risk for UC.publishersversionPeer reviewe

Whole blood RNA sequencing identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis

Background & Aims: Genetic and microbiome studies across patients with primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) have indicated that UC in PSC is a separate disease entity to primary UC, but expression studies for PSC are lacking. Methods: We conducted whole blood RNA sequencing experiments for 495 patients with UC, 220 patients with PSC (including 177 with UC), and 320 healthy controls from Germany and Norway. Differential expression analyses, gene ontology and coexpression analyses and random forest machine learning were performed to identify genes, ontologies and transcriptional features that discriminate diagnoses. Results: The blood transcriptome in UC and PSC is dominated by neutrophil activation genes (e.g. S100A12). In UC, but not in PSC (neither PSC alone nor patients with an additional diagnosis of UC [PSC/UC]), ribosomal, mitochondrial, and energy metabolism genes are upregulated in conjunction with antibody transcript expression (MZB1, IGJ). In PSC, there is an increase in modules related to apoptosis and expression of genes of interferon-I-related ontologies. Random forest analysis could poorly discriminate PSC alone from PSC/UC (AUROC 0.56), but could discriminate PSC, UC, and controls with high accuracy (AUROC UC vs. controls 0.95, PSC vs. controls 0.88, UC vs. PSC 0.986). The main coexpression modules relevant for distinguishing PSC, UC, and controls are enriched in neutrophil degranulation and antibody production genes. Conclusions: Supported by machine learning results, PSC and UC appear to be separate entities on a molecular level, while PSC/UC and PSC are indistinguishable. Impact and implications: Clinical and genetic studies suggest that the colitis-like symptoms in primary sclerosing cholangitis (PSC) represent a different disease entity from primary ulcerative colitis (UC). The present study supports this assumption with transcriptomic data from whole blood and describes notable differences in gene expression between primary UC and PSC, providing insights into the still unclear pathophysiology of both diseases. These findings are of interest to scientists seeking to decipher the molecular pathophysiology of both diseases and provide evidence that a redefinition of the PSC-UC phenotype should be considered. The study practically supports future molecular research by providing a large transcriptomic whole blood reference cohort.publishedVersio

Response to Comment on "ApoE e4e4 Genotype and Mortality With COVID-19 in UK Biobank" by Kuo et al

This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.C.L.K. and D.M. are supported by an R21 grant (R21AG060018) funded by National Institute on Aging, National Institute of Health, USA. D.M. also is supported by the University of Connecticut School of Medicine.published version, accepted version (12 month embargo), submitted versio

Local genetic variation of inflammatory bowel disease in Basque population and its effect in risk prediction

[EN] Inflammatory bowel disease (IBD) is characterised by chronic inflammation of the gastrointestinal tract. Although its aetiology remains unknown, environmental and genetic factors are involved in its development. Regarding genetics, more than 200 loci have been associated with IBD but the transferability of those signals to the Basque population living in Northern Spain, a population with distinctive genetic background, remains unknown. We have analysed 5,411,568 SNPs in 498 IBD cases and 935 controls from the Basque population. We found 33 suggestive loci (p 0.68. In conclusion, we report on the genetic architecture of IBD in the Basque population, and explore the performance of European-descent genetic risk scores in this population.Samples and data used in the present work were provided by the Basque Biobank (http://www.biobancovasco.org).We want to thank Miguel Angel Vesga from the Basque Centre of Transfusion and Human Tissues for providing the access to control samples. This work was founded to MD by Gipuzkoako Foru Aldundia/Diputacion Foral de Gipuzkoa. The project that gave rise to these results rece

Sex differences in the genetics of sarcoidosis across European and African ancestry populations

Methods A meta-analysis of genome-wide association studies was conducted on Europeans and African Americans, totaling 10,103 individuals from three population-based cohorts, Sweden (n = 3,843), Germany (n = 3,342), and the United States (n = 2,918), followed by an SNP lookup in the UK Biobank (UKB, n = 387,945). A genome-wide association study based on Immunochip data consisting of 141,000 single nucleotide polymorphisms (SNPs) was conducted in the sex groups. The association test was based on logistic regression using the additive model in LS and non-LS sex groups independently. Additionally, gene-based analysis, gene expression, expression quantitative trait loci (eQTL) mapping, and pathway analysis were performed to discover functionally relevant mechanisms related to sarcoidosis and biological sex. Results We identified sex-dependent genetic variations in LS and non-LS sex groups. Genetic findings in LS sex groups were explicitly located in the extended Major Histocompatibility Complex (xMHC). In non-LS, genetic differences in the sex groups were primarily located in the MHC class II subregion and ANXA11. Gene-based analysis and eQTL enrichment revealed distinct sex-specific gene expression patterns in various tissues and immune cell types. In LS sex groups, a pathway map related to antigen presentation machinery by IFN-gamma. In non-LS, pathway maps related to immune response lectin-induced complement pathway in males and related to maturation and migration of dendritic cells in skin sensitization in females were identified. Conclusion Our findings provide new evidence for a sex bias underlying sarcoidosis genetic architecture, particularly in clinical phenotypes LS and non-LS. Biological sex likely plays a role in disease mechanisms in sarcoidosis

Sex differences in the genetics of sarcoidosis across European and African ancestry populations

BACKGROUND: Sex differences in the susceptibility of sarcoidosis are unknown. The study aims to identify sex-dependent genetic variations in two clinical sarcoidosis phenotypes: Löfgren\u27s syndrome (LS) and non-Löfgren\u27s syndrome (non-LS). METHODS: A meta-analysis of genome-wide association studies was conducted on Europeans and African Americans, totaling 10,103 individuals from three population-based cohorts, Sweden (n = 3,843), Germany (n = 3,342), and the United States (n = 2,918), followed by an SNP lookup in the UK Biobank (UKB, n = 387,945). A genome-wide association study based on Immunochip data consisting of 141,000 single nucleotide polymorphisms (SNPs) was conducted in the sex groups. The association test was based on logistic regression using the additive model in LS and non-LS sex groups independently. Additionally, gene-based analysis, gene expression, expression quantitative trait loci (eQTL) mapping, and pathway analysis were performed to discover functionally relevant mechanisms related to sarcoidosis and biological sex. RESULTS: We identified sex-dependent genetic variations in LS and non-LS sex groups. Genetic findings in LS sex groups were explicitly located in the extended Major Histocompatibility Complex (xMHC). In non-LS, genetic differences in the sex groups were primarily located in the MHC class II subregion and ANXA11. Gene-based analysis and eQTL enrichment revealed distinct sex-specific gene expression patterns in various tissues and immune cell types. In LS sex groups, a pathway map related to antigen presentation machinery by IFN-gamma. In non-LS, pathway maps related to immune response lectin-induced complement pathway in males and related to maturation and migration of dendritic cells in skin sensitization in females were identified. CONCLUSION: Our findings provide new evidence for a sex bias underlying sarcoidosis genetic architecture, particularly in clinical phenotypes LS and non-LS. Biological sex likely plays a role in disease mechanisms in sarcoidosis