TY - JOUR T1 - Genome-wide analysis of 944 133 individuals provides insights into the etiology of haemorrhoidal disease JF - Gut JO - Gut SP - 1538 LP - 1549 DO - 10.1136/gutjnl-2020-323868 VL - 70 IS - 8 AU - Tenghao Zheng AU - David Ellinghaus AU - Simonas Juzenas AU - François Cossais AU - Greta Burmeister AU - Gabriele Mayr AU - Isabella Friis Jørgensen AU - Maris Teder-Laving AU - Anne Heidi Skogholt AU - Sisi Chen AU - Peter R Strege AU - Go Ito AU - Karina Banasik AU - Thomas Becker AU - Frank Bokelmann AU - Søren Brunak AU - Stephan Buch AU - Hartmut Clausnitzer AU - Christian Datz AU - DBDS Consortium AU - Frauke Degenhardt AU - Marek Doniec AU - Christian Erikstrup AU - Tõnu Esko AU - Michael Forster AU - Norbert Frey AU - Lars G Fritsche AU - Maiken Elvestad Gabrielsen AU - Tobias Gräßle AU - Andrea Gsur AU - Justus Gross AU - Jochen Hampe AU - Alexander Hendricks AU - Sebastian Hinz AU - Kristian Hveem AU - Johannes Jongen AU - Ralf Junker AU - Tom Hemming Karlsen AU - Georg Hemmrich-Stanisak AU - Wolfgang Kruis AU - Juozas Kupcinskas AU - Tilman Laubert AU - Philip C Rosenstiel AU - Christoph Röcken AU - Matthias Laudes AU - Fabian H Leendertz AU - Wolfgang Lieb AU - Verena Limperger AU - Nikolaos Margetis AU - Kerstin Mätz-Rensing AU - Christopher Georg Németh AU - Eivind Ness-Jensen AU - Ulrike Nowak-Göttl AU - Anita Pandit AU - Ole Birger Pedersen AU - Hans Günter Peleikis AU - Kenneth Peuker AU - Cristina Leal Rodriguez AU - Malte Christoph Rühlemann AU - Bodo Schniewind AU - Martin Schulzky AU - Jurgita Skieceviciene AU - Jürgen Tepel AU - Laurent Thomas AU - Florian Uellendahl-Werth AU - Henrik Ullum AU - Ilka Vogel AU - Henry Volzke AU - Lorenzo von Fersen AU - Witigo von Schönfels AU - Brett Vanderwerff AU - Julia Wilking AU - Michael Wittig AU - Sebastian Zeissig AU - Myrko Zobel AU - Matthew Zawistowski AU - Vladimir Vacic AU - Olga Sazonova AU - Elizabeth S Noblin AU - The 23andMe Research Team AU - Gianrico Farrugia AU - Arthur Beyder AU - Thilo Wedel AU - Volker Kahlke AU - Clemens Schafmayer AU - Mauro D'Amato AU - Andre Franke Y1 - 2021/08/01 UR - http://gut.bmj.com/content/70/8/1538.abstract N2 - Objective Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date.Design We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry.Results We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix.Conclusion HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction.Data are available in a public, open access repository. Genome-wide summary statistics of our analyses are publicly available through our web browser (http://hemorrhoids.online) and have been submitted to the European Bioinformatics Institute (www.ebi.ac.uk/gwas) under the accession number GCST90014033. RNA-seq data have been deposited at NCBI Gene Expression Omnibus (GEO) under the accession number GSE154650. ER -