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Complex patterns of multimorbidity associated with severe COVID-19 and Long COVID.
Pietzner, Maik; Denaxas, Spiros; Yasmeen, Summaira; Ulmer, Maria A; Nakanishi, Tomoko; Arnold, Matthias; Kastenmüller, Gabi; Hemingway, Harry; Langenberg, Claudia.
Affiliation
  • Pietzner M; Computational Medicine, Berlin Institute of Health at Charité - Universitatsmedizin Berlin, Berlin, Germany.
  • Denaxas S; Precision Healthcare University Research Institute, Queen Mary University of London, London, UK.
  • Yasmeen S; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
  • Ulmer MA; Institute of Health Informatics, University College London, London, UK.
  • Nakanishi T; Health Data Research UK, London, UK.
  • Arnold M; British Heart Foundation Data Science Centre, London, UK.
  • Kastenmüller G; National Institute of Health Research University College London Hospitals Biomedical Research Centre.
  • Hemingway H; Computational Medicine, Berlin Institute of Health at Charité - Universitatsmedizin Berlin, Berlin, Germany.
  • Langenberg C; Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
medRxiv ; 2024 Jul 01.
Article in En | MEDLINE | ID: mdl-39006431
ABSTRACT
Early evidence that patients with (multiple) pre-existing diseases are at highest risk for severe COVID-19 has been instrumental in the pandemic to allocate critical care resources and later vaccination schemes. However, systematic studies exploring the breadth of medical diagnoses, including common, but non-fatal diseases are scarce, but may help to understand severe COVID-19 among patients at supposedly low risk. Here, we systematically harmonized >12 million primary care and hospitalisation health records from ~500,000 UK Biobank participants into 1448 collated disease terms to systematically identify diseases predisposing to severe COVID-19 (requiring hospitalisation or death) and its post-acute sequalae, Long COVID. We identified a total of 679 diseases associated with an increased risk for severe COVID-19 (n=672) and/or Long COVID (n=72) that spanned almost all clinical specialties and were strongly enriched in clusters of cardio-respiratory and endocrine-renal diseases. For 57 diseases, we established consistent evidence to predispose to severe COVID-19 based on survival and genetic susceptibility analyses. This included a possible role of symptoms of malaise and fatigue as a so far largely overlooked risk factor for severe COVID-19. We finally observed partially opposing risk estimates at known risk loci for severe COVID-19 for etiologically related diseases, such as post-inflammatory pulmonary fibrosis (e.g., MUC5B, NPNT, and PSMD3) or rheumatoid arthritis (e.g., TYK2), possibly indicating a segregation of disease mechanisms. Our results provide a unique reference that demonstrates how 1) complex co-occurrence of multiple - including non-fatal - conditions predispose to increased COVID-19 severity and 2) how incorporating the whole breadth of medical diagnosis can guide the interpretation of genetic risk loci.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: MedRxiv Year: 2024 Document type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: MedRxiv Year: 2024 Document type: Article Affiliation country: Germany
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