COVID-19 Biomarkers And Comorbidities In A Disease Biomarker Data Model
Open AccessSignature molecules, including genes, proteins, target panels, and glycans termed as biomarkers, are becoming increasingly significant in the Coronavirus disease 2019 (COVID-19) pandemic. High-throughput molecular characterization technologies have greatly accelerated the development of tests for risk assessment, diagnosis, prognosis, disease monitoring, and therapeutic evaluation. In response to the COVID-19 outbreak, scientists and medical researchers are capturing a wide range of host responses, symptoms, and lingering post-recovery problems within the human population. These variable clinical manifestations suggest differences in influential factors, such as innate and adaptive host immunity, existing or underlying health conditions, comorbidities, genetics, and other factors - compounding the complexity of COVID-19 pathobiology and potential biomarkers associated with the disease, as they become available. The heterogeneous data pose challenges for efficient extrapolation of information into clinical applications. The disease complexity emphasizes the need for biomarker characterization that can help stratify patients based on their variable clinical manifestations and the presence of comorbidities. Further, cross-disciplinary investigation of biomarker resources offers an opportunity to reveal novel clinical insights. We have curated 145 COVID-19 biomarkers by developing a novel cross-cutting disease biomarker data model that allows integration and evaluation of biomarkers in patients with comorbidities. The majority of biomarkers are associated with the immune system (including complement factors, inflammatory modulators, and pro-inflammatory factors) as well as coagulation factors. These trends suggest vascular pathobiology of the COVID-19 disease. Utilizing this collated biomarker data, we propose to identify common features and attributes of COVID-19, with cancer and other metabolic syndromes. Preliminary analysis shows biomarkers such as ACE2, IL-6, IL-4, and IL-2 have similar expression profiles in COVID-19 and cancer. Furthermore, COVID-19 biomarkers such as D-dimer, neutrophil to lymphocyte ratio (NLR), C-reactive protein (CRP), and low-density lipoprotein (LDL) shed light on the underlying physiological or pathological association with metabolic syndrome, diabetes, and hyperlipidemia. The importance of this study lies in identifying specific biomarkers that can successfully stratify patients based on distinct clinical presentations and the presence of comorbidities. We explore these trends as we put forth a COVID-19 biomarker resource ( https://data.oncomx.org/covid19) that will help researchers and diagnosticians alike.
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