Characterizing Long COVID: Deep Phenotype of a Complex Condition

Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. GreeneWilliam B. Hillegass, Ramakanth Kavuluru, Wesley D. Kimble, Farrukh M. Koraishy, Sebastian Köhler, Chen Liang, Feifan Liu, Hongfang Liu, Vithal Madhira, Charisse R. Madlock-Brown, Nicolas Matentzoglu, Diego R. Mazzotti, Julie A. McMurry, Douglas S. McNair, Richard A. Moffitt, Teshamae S. Monteith, Ann M. Parker, Mallory A. Perry, Emily Pfaff, Justin T. Reese, Joel Saltz, Robert A. Schuff, Anthony E. Solomonides, Julian Solway, Heidi Spratt, Gary S. Stein, Anupam A. Sule, Umit Topaloglu, George D. Vavougios, Liwei Wang, Melissa A. Haendel, Peter N. Robinson

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or “long COVID”), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Findings: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. Funding: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411.

Original languageEnglish (US)
Article number103722
JournalEBioMedicine
Volume74
DOIs
StatePublished - Dec 2021

Keywords

  • COVID-19
  • human phenotype ontology
  • long COVID
  • of post-acute sequelae of SARS-CoV-2
  • phenotyping

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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