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1.
Guillaume Butler-Laporte; Gundula Povysil; Jack Kosmicki; Elizabeth T Cirulli; Theodore Drivas; Simone Furini; Chadi Saad; Axel Schmidt; Pawel Olszewski; Urszula Korotko; Mathieu Quinodoz; Elifnaz Celik; Kousik Kundu; Klaudia Walter; Junghyung Jung; Amy D Stockwell; Laura G Sloofman; Alexander W Charney; Daniel Jordan; Noam Beckmann; Bartlomiej Przychodzen; Timothy Chang; Tess D Pottinger; Ning Shang; Fabian Brand; Francesca Fava; Francesca Mari; Karolina Chwialkowska; Magdalena Niemira; Szymon Pula; J Kenneth Baillie; Alex Stuckey; Andrea Ganna; Konrad J Karczewski; Kumar Veerapen; Mathieu Bourgey; Guillaume Bourque; Robert JM Eveleigh; Vincenzo Forgetta; David Morrison; David Langlais; Mark Lathrop; Vincent Mooser; Tomoko Nakanishi; Robert Frithiof; Michael Hultstrom; Miklos Lipcsey; Yanara Marincevic-Zuniga; Jessica Nordlund; Kelly M Schiabor Barrett; William Lee; Alexandre Bolze; Simon White; Stephen Riffle; Francisco Tanudjaja; Efren Sandoval; Iva Neveux; Shaun Dabe; Nicolas Casadei; Susanne Motameny; Manal Alaamery; Salam Massadeh; Nora Aljawini; Mansour S Almutairi; Yaseen M Arab; Saleh A Alqahtan; Fawz S Al Harthi; Amal Almutairi; Fatima Alqubaishi; Sarah Alotaibi; Albandari Binowayn; Ebtehal A Alsolm; Hadeel El Bardisy; Mohammad Fawzy; - COVID-19 Host Genetics Initiative; - DeCOI Host Genetics Group; - GEN-COVID Multicenter Study; - GenOMICC Consortium; - Japan COVID-19 Task Force; - Regeneron Genetics Center; Daniel H Geschwind; Stephanie Arteaga; Alexis Stephens; Manish J Butte; Paul C Boutros; Takafumi N Yamaguchi; Shu Tao; Stefan Eng; Timothy Sanders; Paul J Tung; Michael E Broudy; Yu Pan; Alfredo Gonzalez; Nikhil Chavan; Ruth Johnson; Bogdan Pasaniuc; Brian Yaspan; Sandra Smieszek; Carlo Rivolta; Stephanie Bibert; Pierre-Yves Bochud; Maciej Dabrowski; Pawel Zawadzki; Mateusz Sypniewski; El?bieta Kaja; Pajaree Chariyavilaskul; Voraphoj Nilaratanakul; Nattiya Hirankarn; Vorasuk Shotelersuk; Monnat Pongpanich; Chureerat Phokaew; Wanna Chetruengchai; Yosuke Kawai; Takanori Hasegawa; Tatsuhiko Naito; Ho Namkoong; Ryuya Edahiro; Akinori Kimura; Seishi Ogawa; Takanori Kanai; Koichi Fukunaga; Yukinori Okada; Seiya Imoto; Satoru Miyano; Serghei Mangul; Malak S Abedalthagafi; Hugo Zeberg; Joseph J Grzymski; Nicole L Washington; Stephan Ossowski; Kerstin U Ludwig; Eva C Schulte; Olaf Riess; Marcin Moniuszko; Miroslaw Kwasniewski; Hamdi Mbarek; Said I Ismail; Anurag Verma; David B Goldstein; Krzysztof Kiryluk; Alessandra Renieri; Manuel Ferreira; J Brent Richards.
medrxiv; 2022.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2022.03.28.22273040

RESUMEN

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,048 severe disease cases and 571,009 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p=5.41x10-7). These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.


Asunto(s)
COVID-19
2.
medrxiv; 2020.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2020.11.08.20227884

RESUMEN

To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N>1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use, and alcohol use. COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors.


Asunto(s)
COVID-19 , Trastorno Depresivo
3.
medrxiv; 2020.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2020.10.27.20220665

RESUMEN

Angiotensin-converting enzyme-2 (ACE2) receptor has been identified as the key adhesion molecule for the transmission of the SARS-CoV-2. However, there is no evidence that human genetic variation in ACE2 is singularly responsible for COVID-19 susceptibility. Therefore, we performed a multi-level characterization of genes that interact with ACE2 (ACE2-gene network) for their over-represented biological properties in the context of COVID-19. The phenome-wide association of 51 genes including ACE2 with 4,756 traits categorized into 26 phenotype categories, showed enrichment of immunological, respiratory, environmental, skeletal, dermatological, and metabolic domains (p<4e-4). Transcriptomic regulation of ACE2-gene network was enriched for tissue-specificity in kidney, small intestine, and colon (p<4.7e-4). Leveraging the drug-gene interaction database we identified 47 drugs, including dexamethasone and spironolactone, among others. Considering genetic variants within +/- 10 kb of ACE2-network genes we characterized functional consequences (among others) using miRNA binding-site targets. MiRNAs affected by ACE2-network variants revealed statistical over-representation of inflammation, aging, diabetes, and heart conditions. With respect to variants mapped to the ACE2-network, we observed COVID-19 related associations in RORA, SLC12A6 and SLC6A19 genes. Overall, functional characterization of ACE2-gene network highlights several potential mechanisms in COVID-19 susceptibility. The data can also be accessed at https://gpwhiz.github.io/ACE2Netlas/


Asunto(s)
Diabetes Mellitus , COVID-19 , Inflamación
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