Academic Journal
Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks.
| العنوان: | Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks. |
|---|---|
| المؤلفون: | Lars G Fritsche, Kisung Nam, Jiacong Du, Ritoban Kundu, Maxwell Salvatore, Xu Shi, Seunggeun Lee, Stephen Burgess, Bhramar Mukherjee |
| المصدر: | PLoS Genetics, Vol 19, Iss 12, p e1010907 (2023) |
| بيانات النشر: | Public Library of Science (PLoS), 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Genetics |
| مصطلحات موضوعية: | Genetics, QH426-470 |
| الوصف: | ObjectiveTo overcome the limitations associated with the collection and curation of COVID-19 outcome data in biobanks, this study proposes the use of polygenic risk scores (PRS) as reliable proxies of COVID-19 severity across three large biobanks: the Michigan Genomics Initiative (MGI), UK Biobank (UKB), and NIH All of Us. The goal is to identify associations between pre-existing conditions and COVID-19 severity.MethodsDrawing on a sample of more than 500,000 individuals from the three biobanks, we conducted a phenome-wide association study (PheWAS) to identify associations between a PRS for COVID-19 severity, derived from a genome-wide association study on COVID-19 hospitalization, and clinical pre-existing, pre-pandemic phenotypes. We performed cohort-specific PRS PheWAS and a subsequent fixed-effects meta-analysis.ResultsThe current study uncovered 23 pre-existing conditions significantly associated with the COVID-19 severity PRS in cohort-specific analyses, of which 21 were observed in the UKB cohort and two in the MGI cohort. The meta-analysis yielded 27 significant phenotypes predominantly related to obesity, metabolic disorders, and cardiovascular conditions. After adjusting for body mass index, several clinical phenotypes, such as hypercholesterolemia and gastrointestinal disorders, remained associated with an increased risk of hospitalization following COVID-19 infection.ConclusionBy employing PRS as a proxy for COVID-19 severity, we corroborated known risk factors and identified novel associations between pre-existing clinical phenotypes and COVID-19 severity. Our study highlights the potential value of using PRS when actual outcome data may be limited or inadequate for robust analyses. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1553-7390 1553-7404 |
| Relation: | https://doaj.org/toc/1553-7390; https://doaj.org/toc/1553-7404 |
| DOI: | 10.1371/journal.pgen.1010907 |
| URL الوصول: | https://doaj.org/article/d8658fcbe1c84db1b1d4f20ba8e3cca2 |
| رقم الانضمام: | edsdoj.8658fcbe1c84db1b1d4f20ba8e3cca2 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 15537390 15537404 |
|---|---|
| DOI: | 10.1371/journal.pgen.1010907 |