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

[This corrects the article DOI: 10.3389/fmed.2023.1132799.].

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.

HLA-DPA1*02:01~B1*01:01 is a risk haplotype for primary sclerosing cholangitis mediating activation of NKp44+ NK cells.

OBJECTIVE: Primary sclerosing cholangitis (PSC) is characterised by bile duct strictures and progressive liver disease, eventually requiring liver transplantation. Although the pathogenesis of PSC remains incompletely understood, strong associations with HLA-class II haplotypes have been described. As specific HLA-DP molecules can bind the activating NK-cell receptor NKp44, we investigated the role of HLA-DP/NKp44-interactions in PSC. DESIGN: Liver tissue, intrahepatic and peripheral blood lymphocytes of individuals with PSC and control individuals were characterised using flow cytometry, immunohistochemical and immunofluorescence analyses. HLA-DPA1 and HLA-DPB1 imputation and association analyses were performed in 3408 individuals with PSC and 34 213 controls. NK cell activation on NKp44/HLA-DP interactions was assessed in vitro using plate-bound HLA-DP molecules and HLA-DPB wildtype versus knock-out human cholangiocyte organoids. RESULTS: NKp44+NK cells were enriched in livers, and intrahepatic bile ducts of individuals with PSC showed higher expression of HLA-DP. HLA-DP haplotype analysis revealed a highly elevated PSC risk for HLA-DPA1*02:01~B1*01:01 (OR 1.99, p=6.7×10-50). Primary NKp44+NK cells exhibited significantly higher degranulation in response to plate-bound HLA-DPA1*02:01-DPB1*01:01 compared with control HLA-DP molecules, which were inhibited by anti-NKp44-blocking. Human cholangiocyte organoids expressing HLA-DPA1*02:01-DPB1*01:01 after IFN-γ-exposure demonstrated significantly increased binding to NKp44-Fc constructs compared with unstimulated controls. Importantly, HLA-DPA1*02:01-DPB1*01:01-expressing organoids increased degranulation of NKp44+NK cells compared with HLA-DPB1-KO organoids. CONCLUSION: Our studies identify a novel PSC risk haplotype HLA-DP A1*02:01~DPB1*01:01 and provide clinical and functional data implicating NKp44+NK cells that recognise HLA-DPA1*02:01-DPB1*01:01 expressed on cholangiocytes in PSC pathogenesis.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs)1-3. Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

Genome-wide association analysis reveals the associations of NPHP4, TYW1-AUTS2 and SEMA6D for Behçet's disease and HLA-B*46:01 for its intestinal involvement.

BACKGROUND: Intestinal involvement in Behçet's disease (BD) is associated with poor prognosis and is more prevalent in East Asian than in Mediterranean populations. Identifying the genetic causes of intestinal BD is important for understanding the pathogenesis and for appropriate treatment of BD patients. METHODS: We performed genome-wide association studies (GWAS) and imputation/replication genotyping of human leukocyte antigen (HLA) alleles for 1,689 Korean and Turkish patients with BD (including 379 patients with intestinal BD) and 2,327 healthy controls, followed by replication using 593 Japanese patients with BD (101 patients with intestinal BD) and 737 healthy controls. Stratified cross-phenotype analyses were performed for 1) overall BD, 2) intestinal BD, and 3) intestinal BD without association of overall BD. RESULTS: We identified three novel genome-wide significant susceptibility loci including NPHP4 (rs74566205; P=1.36 × 10-8), TYW1-AUTS2 (rs60021986; P=1.14 × 10-9), and SEMA6D (rs4143322; P=5.54 × 10-9) for overall BD, and a new association with HLA-B*46:01 for intestinal BD (P=1.67 × 10-8) but not for BD without intestinal involvement. HLA peptide binding analysis revealed that Mycobacterial peptides, have a stronger binding affinity to HLA-B*46:01 compared to the known risk allele HLA-B*51:01. CONCLUSIONS: HLA-B*46:01 is associated with the development of intestinal BD; NPHP4, TYW1-AUTS2, and SEMA6D are susceptibility loci for overall BD.

GWAS meta-analysis of psoriasis identifies new susceptibility alleles impacting disease mechanisms and therapeutic targets.

Psoriasis is a common, debilitating immune-mediated skin disease. Genetic studies have identified biological mechanisms of psoriasis risk, including those targeted by effective therapies. However, the genetic liability to psoriasis is not fully explained by variation at robustly identified risk loci. To move towards a saturation map of psoriasis susceptibility we meta-analysed 18 GWAS comprising 36,466 cases and 458,078 controls and identified 109 distinct psoriasis susceptibility loci, including 45 that have not been previously reported. These include susceptibility variants at loci in which the therapeutic targets IL17RA and AHR are encoded, and deleterious coding variants supporting potential new drug targets (including in STAP2, CPVL and POU2F3). We conducted a transcriptome-wide association study to identify regulatory effects of psoriasis susceptibility variants and cross-referenced these against single cell expression profiles in psoriasis-affected skin, highlighting roles for the transcriptional regulation of haematopoietic cell development and epigenetic modulation of interferon signalling in psoriasis pathobiology.

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's syndrome (LS) and non-Löfgren's 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.

Multitrait genome-wide analyses identify new susceptibility loci and candidate drugs to primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5. Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC.

Chemotherapy-related hyperbilirubinemia in pediatric acute lymphoblastic leukemia: a genome-wide association study from the AIEOP-BFM ALL study group.

BACKGROUND: Characterization of clinical phenotypes in context with tumor and host genomic information can aid in the development of more effective and less toxic risk-adapted and targeted treatment strategies. To analyze the impact of therapy-related hyperbilirubinemia on treatment outcome and to identify contributing genetic risk factors of this well-recognized adverse effect we evaluated serum bilirubin levels in 1547 pediatric patients with acute lymphoblastic leukemia (ALL) and conducted a genome-wide association study (GWAS). PATIENTS AND METHODS: Patients were treated in multicenter trial AIEOP-BFM ALL 2000 for pediatric ALL. Bilirubin toxicity was graded 0 to 4 according to the Common Toxicity Criteria (CTC) of the National Cancer Institute. In the GWAS discovery cohort, including 650 of the 1547 individuals, genotype frequencies of 745,895 single nucleotide variants were compared between 435 patients with hyperbilirubinemia (CTC grades 1-4) during induction/consolidation treatment and 215 patients without it (grade 0). Replication analyses included 224 patients from the same trial. RESULTS: Compared to patients with no (grade 0) or moderate hyperbilirubinemia (grades 1-2) during induction/consolidation, patients with grades 3-4 had a poorer 5-year event free survival (76.6 ± 3% versus 87.7 ± 1% for grades 1-2, P = 0.003; 85.2 ± 2% for grade 0, P < 0.001) and a higher cumulative incidence of relapse (15.6 ± 3% versus 9.0 ± 1% for grades 1-2, P = 0.08; 11.1 ± 1% for grade 0, P = 0.007). GWAS identified a strong association of the rs6744284 variant T allele in the UGT1A gene cluster with risk of hyperbilirubinemia (allelic odds ratio (OR) = 2.1, P = 7 × 10- 8). TT-homozygotes had a 6.5-fold increased risk of hyperbilirubinemia (grades 1-4; 95% confidence interval (CI) = 2.9-14.6, P = 7 × 10- 6) and a 16.4-fold higher risk of grade 3-4 hyperbilirubinemia (95% CI 6.1-43.8, P = 2 × 10- 8). Replication analyses confirmed these associations with joint analysis yielding genome-wide significance (allelic OR = 2.1, P = 6 × 10- 11; 95% CI 1.7-2.7). Moreover, rs6744284 genotypes were strongly linked to the Gilbert's syndrome-associated UGT1A1*28/*37 allele (r2 = 0.70), providing functional support for study findings. Of clinical importance, the rs6744284 TT genotype counterbalanced the adverse prognostic impact of high hyperbilirubinemia on therapy outcome. CONCLUSIONS: Chemotherapy-related hyperbilirubinemia is a prognostic factor for treatment outcome in pediatric ALL and genetic variation in UGT1A aids in predicting the clinical impact of hyperbilirubinemia. TRIAL REGISTRATION: http://www. CLINICALTRIALS: gov ; #NCT00430118.

GWAS meta-analysis of 16 790 patients with Barrett's oesophagus and oesophageal adenocarcinoma identifies 16 novel genetic risk loci and provides insights into disease aetiology beyond the single marker level.

OBJECTIVE: Oesophageal cancer (EC) is the sixth leading cause of cancer-related deaths. Oesophageal adenocarcinoma (EA), with Barrett's oesophagus (BE) as a precursor lesion, is the most prevalent EC subtype in the Western world. This study aims to contribute to better understand the genetic causes of BE/EA by leveraging genome wide association studies (GWAS), genetic correlation analyses and polygenic risk modelling. DESIGN: We combined data from previous GWAS with new cohorts, increasing the sample size to 16 790 BE/EA cases and 32 476 controls. We also carried out a transcriptome wide association study (TWAS) using expression data from disease-relevant tissues to identify BE/EA candidate genes. To investigate the relationship with reported BE/EA risk factors, a linkage disequilibrium score regression (LDSR) analysis was performed. BE/EA risk models were developed combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. RESULTS: The GWAS meta-analysis identified 27 BE and/or EA risk loci, 11 of which were novel. The TWAS identified promising BE/EA candidate genes at seven GWAS loci and at five additional risk loci. The LDSR analysis led to the identification of novel genetic correlations and pointed to differences in BE and EA aetiology. Gastro-oesophageal reflux disease appeared to contribute stronger to the metaplastic BE transformation than to EA development. Finally, combining PRS with BE/EA risk factors improved the performance of the risk models. CONCLUSION: Our findings provide further insights into BE/EA aetiology and its relationship to risk factors. The results lay the foundation for future follow-up studies to identify underlying disease mechanisms and improving risk prediction.

Elucidation of the genetic causes of bicuspid aortic valve disease.

AIMS: The present study aims to characterize the genetic risk architecture of bicuspid aortic valve (BAV) disease, the most common congenital heart defect. METHODS AND RESULTS: We carried out a genome-wide association study (GWAS) including 2236 BAV patients and 11 604 controls. This led to the identification of a new risk locus for BAV on chromosome 3q29. The single nucleotide polymorphism rs2550262 was genome-wide significant BAV associated (P = 3.49 × 10-08) and was replicated in an independent case-control sample. The risk locus encodes a deleterious missense variant in MUC4 (p.Ala4821Ser), a gene that is involved in epithelial-to-mesenchymal transformation. Mechanistical studies in zebrafish revealed that loss of Muc4 led to a delay in cardiac valvular development suggesting that loss of MUC4 may also play a role in aortic valve malformation. The GWAS also confirmed previously reported BAV risk loci at PALMD (P = 3.97 × 10-16), GATA4 (P = 1.61 × 10-09), and TEX41 (P = 7.68 × 10-04). In addition, the genetic BAV architecture was examined beyond the single-marker level revealing that a substantial fraction of BAV heritability is polygenic and ∼20% of the observed heritability can be explained by our GWAS data. Furthermore, we used the largest human single-cell atlas for foetal gene expression and show that the transcriptome profile in endothelial cells is a major source contributing to BAV pathology. CONCLUSION: Our study provides a deeper understanding of the genetic risk architecture of BAV formation on the single marker and polygenic level.

COVID-19 host genetics and ABO blood group susceptibility.

Twenty-five susceptibility loci for SARS-CoV-2 infection and/or COVID-19 disease severity have been identified in the human genome by genome-wide association studies, and the most frequently replicated genetic findings for susceptibility are genetic variants at the ABO gene locus on chromosome 9q34.2, which is supported by the association between ABO blood group distribution and COVID-19. The ABO blood group effect appears to influence a variety of disease conditions and pathophysiological mechanisms associated with COVID-19. Transmission models for SARS-CoV-2 combined with observational public health and genome-wide data from patients and controls, as well as receptor binding experiments in cell lines and human samples, indicate that there may be a reduction or slowing of infection events by up to 60% in certain ABO blood group constellations of index and contact person in the early phase of a SARS-CoV-2 outbreak. The strength of the ABO blood group effect on reducing infection rates further depends on the distribution of the ABO blood groups in the respective population and the proportion of blood group O in that population. To understand in detail the effect of ABO blood groups on COVID-19, further studies are needed in relation to different demographic characteristics, but also in relation to recent data on reinfection with new viral variants and in the context of the human microbiome.

Host genetic factors related to innate immunity, environmental sensing and cellular functions are associated with human skin microbiota.

Despite the increasing knowledge about factors shaping the human microbiome, the host genetic factors that modulate the skin-microbiome interactions are still largely understudied. This contrasts with recent efforts to characterize host genes that influence the gut microbiota. Here, we investigated the effect of genetics on skin microbiota across three different skin microenvironments through meta-analyses of genome-wide association studies (GWAS) of two population-based German cohorts. We identified 23 genome-wide significant loci harboring 30 candidate genes involved in innate immune signaling, environmental sensing, cell differentiation, proliferation and fibroblast activity. However, no locus passed the strict threshold for study-wide significance (P < 6.3 × 10-10 for 80 features included in the analysis). Mendelian randomization (MR) analysis indicated the influence of staphylococci on eczema/dermatitis and suggested modulating effects of the microbiota on other skin diseases. Finally, transcriptional profiles of keratinocytes significantly changed after in vitro co-culturing with Staphylococcus epidermidis, chosen as a representative of skin commensals. Seven candidate genes from the GWAS were found overlapping with differential expression in the co-culturing experiments, warranting further research of the skin commensal and host genetic makeup interaction.

MAGScoT: a fast, lightweight and accurate bin-refinement tool.

MOTIVATION: Recovery of metagenome-assembled genomes (MAGs) from shotgun metagenomic data is an important task for the comprehensive analysis of microbial communities from variable sources. Single binning tools differ in their ability to leverage specific aspects in MAG reconstruction, the use of ensemble binning refinement tools is often time consuming and computational demand increases with community complexity. We introduce MAGScoT, a fast, lightweight and accurate implementation for the reconstruction of highest-quality MAGs from the output of multiple genome-binning tools. RESULTS: MAGScoT outperforms popular bin-refinement solutions in terms of quality and quantity of MAGs as well as computation time and resource consumption. AVAILABILITY AND IMPLEMENTATION: MAGScoT is available via GitHub (https://github.com/ikmb/MAGScoT) and as an easy-to-use Docker container (https://hub.docker.com/repository/docker/ikmb/magscot). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DNA methyltransferase 3A controls intestinal epithelial barrier function and regeneration in the colon.

Genetic variants in the DNA methyltransferase 3 A (DNMT3A) locus have been associated with inflammatory bowel disease (IBD). DNMT3A is part of the epigenetic machinery physiologically involved in DNA methylation. We show that DNMT3A plays a critical role in maintaining intestinal homeostasis and gut barrier function. DNMT3A expression is downregulated in intestinal epithelial cells from IBD patients and upon tumor necrosis factor treatment in murine intestinal organoids. Ablation of DNMT3A in Caco-2 cells results in global DNA hypomethylation, which is linked to impaired regenerative capacity, transepithelial resistance and intercellular junction formation. Genetic deletion of Dnmt3a in intestinal epithelial cells (Dnmt3aΔIEC) in mice confirms the phenotype of an altered epithelial ultrastructure with shortened apical-junctional complexes, reduced Goblet cell numbers and increased intestinal permeability in the colon in vivo. Dnmt3aΔIEC mice suffer from increased susceptibility to experimental colitis, characterized by reduced epithelial regeneration. These data demonstrate a critical role for DNMT3A in orchestrating intestinal epithelial homeostasis and response to tissue damage and suggest an involvement of impaired epithelial DNMT3A function in the etiology of IBD.

EagleImp: fast and accurate genome-wide phasing and imputation in a single tool.

MOTIVATION: Reference-based phasing and genotype imputation algorithms have been developed with sublinear theoretical runtime behaviour, but runtimes are still high in practice when large genome-wide reference datasets are used. RESULTS: We developed EagleImp, a software based on the methods used in the existing tools Eagle2 and PBWT, which allows accurate and accelerated phasing and imputation in a single tool by algorithmic and technical improvements and new features. We compared accuracy and runtime of EagleImp with Eagle2, PBWT and prominent imputation servers using whole-genome sequencing data from the 1000 Genomes Project, the Haplotype Reference Consortium and simulated data with 1 million reference genomes. EagleImp was 2-30 times faster (depending on the single or multiprocessor configuration selected and the size of the reference panel) than Eagle2 combined with PBWT, with the same or better phasing and imputation quality in all tested scenarios. For common variants investigated in typical genome-wide association studies, EagleImp provided same or higher imputation accuracy than the Sanger Imputation Service, Michigan Imputation Server and the newly developed TOPMed Imputation Server, despite larger (not publicly available) reference panels. Additional features include automated chromosome splitting and memory management at runtime to avoid job aborts, fast reading and writing of large files and various user-configurable algorithm and output options. Due to the technical optimizations, EagleImp can perform fast and accurate reference-based phasing and imputation and is ready for future large reference panels in the order of 1 million genomes. AVAILABILITY AND IMPLEMENTATION: EagleImp is implemented in C++ and freely available for download at https://github.com/ikmb/eagleimp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Common Variants Near ZIC1 and ZIC4 in Autopsy-Confirmed Multiple System Atrophy.

BACKGROUND: Multiple System Atrophy is a rare neurodegenerative disease with alpha-synuclein aggregation in glial cytoplasmic inclusions and either predominant olivopontocerebellar atrophy or striatonigral degeneration, leading to dysautonomia, parkinsonism, and cerebellar ataxia. One prior genome-wide association study in mainly clinically diagnosed patients with Multiple System Atrophy failed to identify genetic variants predisposing for the disease. OBJECTIVE: Since the clinical diagnosis of Multiple System Atrophy yields a high rate of misdiagnosis when compared to the neuropathological gold standard, we studied only autopsy-confirmed cases. METHODS: We studied common genetic variations in Multiple System Atrophy cases (N = 731) and controls (N = 2898). RESULTS: The most strongly disease-associated markers were rs16859966 on chromosome 3, rs7013955 on chromosome 8, and rs116607983 on chromosome 4 with P-values below 5 × 10-6 , all of which were supported by at least one additional genotyped and several imputed single nucleotide polymorphisms. The genes closest to the chromosome 3 locus are ZIC1 and ZIC4 encoding the zinc finger proteins of cerebellum 1 and 4 (ZIC1 and ZIC4). INTERPRETATION: Since mutations of ZIC1 and ZIC4 and paraneoplastic autoantibodies directed against ZIC4 are associated with severe cerebellar dysfunction, we conducted immunohistochemical analyses in brain tissue of the frontal cortex and the cerebellum from 24 Multiple System Atrophy patients. Strong immunohistochemical expression of ZIC4 was detected in a subset of neurons of the dentate nucleus in all healthy controls and in patients with striatonigral degeneration, whereas ZIC4-immunoreactive neurons were significantly reduced inpatients with olivopontocerebellar atrophy. These findings point to a potential ZIC4-mediated vulnerability of neurons in Multiple System Atrophy. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Detailed stratified GWAS analysis for severe COVID-19 in four European populations.

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.

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.