Ontology-based annotation and analysis of COVID-19 phenotypes

TL;DR

This study systematically analyzes COVID-19 clinical phenotypes using the Human Phenotype Ontology, revealing geographic differences and associations with patient outcomes based on data from 70 articles.

Contribution

It introduces an ontology-based framework for classifying and analyzing COVID-19 phenotypes and comorbidities across different populations.

Findings

Higher nervous and abdominal phenotypes in Europe and USA

Identification of 23 common comorbidities

Patients with certain comorbidities have worse outcomes

Abstract

The epidemic of COVID-19 has caused an unpredictable and devastated disaster to the public health in different territories around the world. Common phenotypes include fever, cough, shortness of breath, and chills. With more cases investigated, other clinical phenotypes are gradually recognized, for example, loss of smell, and loss of tastes. Compared with discharged or cured patients, severe or died patients often have one or more comorbidities, such as hypertension, diabetes, and cardiovascular disease. In this study, we systematically collected and analyzed COVID-19-related clinical phenotypes from 70 articles. The commonly occurring 17 phenotypes were classified into different groups based on the Human Phenotype Ontology (HPO). Based on the HP classification, we systematically analyze three nervous phenotypes (loss of smell, loss of taste, and headache) and four abdominal phenotypes (nausea, vomiting, abdominal pain, and diarrhea) identified in patients, and found that patients from Europe and USA turned to have higher nervous phenotypes and abdominal phenotypes than patients from Asia. A total of 23 comorbidities were found to commonly exist among COVID-19 patients. Patients with these comorbidities such as diabetes and kidney failure had worse outcomes compared with those without these comorbidities.