A Case-Crossover Phenome-wide association study (PheWAS) for understanding Post-COVID-19 diagnosis patterns

• Published in: Journal of biomedical informatics 2022-12, Vol.136, p.104237, Article 104237
• Main Authors: Haupert, Spencer R., Shi, Xu, Chen, Chen, Fritsche, Lars G., Mukherjee, Bhramar
• Format: Article
• Language: English
• Subjects: Case-Control Studies; Case-crossover; COVID-19 - diagnosis; COVID-19 Testing; Electronic Health Records; Flu positive control; Healthcare utilization; Humans; Multiple testing; Original Research; Phenome-wide association study; Post-COVID-19; Retrospective Studies; SARS-CoV-2; Test-negative controls; Vaccination; Within-subject confounding
• ISSN: 1532-0464; 1532-0480; 1532-0480
• DOI: 10.1016/j.jbi.2022.104237

[Display omitted] •We present a case-crossover PheWAS analysis to study post-COVID-19 symptoms that controls for within-subject time-invariant confounders.•Respiratory, circulatory, and mental health conditions are enriched post-COVID-19.•Comparison to SARS-CoV-2 test negative and SARS-CoV-2 test negative but flu positive controls reveal conditions unique to COVID-19.•This method could be used to understand other emerging infectious diseases. Post COVID-19 condition (PCC) is known to affect a large proportion of COVID-19 survivors. Robust study design and methods are needed to understand post-COVID-19 diagnosis patterns in all survivors, not just those clinically diagnosed with PCC. We applied a case-crossover Phenome-Wide Association Study (PheWAS) in a retrospective cohort of COVID-19 survivors, comparing the occurrences of 1,671 diagnosis-based phenotype codes (PheCodes) pre- and post-COVID-19 infection periods in the same individual using a conditional logistic regression. We studied how this pattern varied by COVID-19 severity and vaccination status, and we compared to test negative and test negative but flu positive controls. In 44,198 SARS-CoV-2-positive patients, we foundenrichment in respiratory,circulatory, and mental health disorders post-COVID-19-infection. Top hits included anxiety disorder (p = 2.8e-109, OR = 1.7 [95 % CI: 1.6–1.8]), cardiac dysrhythmias (p = 4.9e-87, OR = 1.7 [95 % CI: 1.6–1.8]), and respiratory failure, insufficiency, arrest (p = 5.2e-75, OR = 2.9 [95 % CI: 2.6–3.3]). In severe patients, we found stronger associations with respiratory and circulatory disorders compared to mild/moderate patients. Fully vaccinated patients had mental health and chronic circulatory diseases rise to the top of the association list, similar to the mild/moderate cohort. Both control groups (test negative, test negative and flu positive) showed a different pattern of hits to SARS-CoV-2 positives. Patients experience myriad symptoms more than 28 days after SARS-CoV-2 infection, but especially respiratory, circulatory, and mental health disorders. Our case-crossover PheWAS approach controls for within-person confounders that are time-invariant. Comparison to test negatives and test negative but flu positive patients with a similar design helped identify enrichment specific to COVID-19. This design may be applied other emerging diseases with long-lasting effects other than a SARS-CoV-2 infection. Given the potential for bias from observational data,