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Combinatorial Analysis of Phenotypic and Clinical Risk Factors Associated With Hospitalized COVID-19 Patients

Sayoni Das1, Matthew Pearson1, Krystyna Taylor1

  • 1PrecisionLife Ltd., Oxford, United Kingdom.

Frontiers in Digital Health
|October 29, 2021
PubMed

Insights

Severe COVID-19 risk factors were identified using clinical data. Lower lipid and calcium levels, along with leukocytes, were linked to increased hospitalization risk, suggesting shared biological pathways.

Area of Science:

  • Infectious Diseases
  • Biochemistry
  • Medical Informatics

Background:

  • Understanding risk factors for severe COVID-19 is crucial for patient outcomes.
  • Previous genomic studies suggested a link between calcium/lipid homeostasis and severe COVID-19.
  • Clinical and phenotypic data analysis is needed to validate these findings in diverse populations.

Purpose of the Study:

  • To identify clinical and phenotypic disease signatures associated with severe COVID-19 hospitalization.
  • To analyze combinations of features in a separate patient cohort using clinical data.
  • To explore potential shared mechanisms between calcium, lipid, and immune cell signaling in severe COVID-19.

Main Methods:

  • Utilized the PrecisionLife combinatorial analytics platform on de-identified health records from the UnitedHealth Group COVID-19 Data Suite.
  • Analyzed 836 disease signatures across two cohorts: hospitalized COVID-19 cases vs. mild cases, and a subset with laboratory data.
  • Investigated associations between lipid levels, serum calcium, leukocytes, statin use, and vitamin D deficiency.

Main Results:

  • Identified multiple disease signatures correlating with increased COVID-19 hospitalization risk.
  • Found co-occurrence of lower lipid levels with lower serum calcium and leukocytes in severe cases.
  • Observed that hypocalcemia signatures were frequently linked to vitamin D deficiency and often independent of statin use.

Conclusions:

  • Combinatorial analysis of clinical data can identify severe COVID-19 risk signatures independently of genomic data.
  • Findings support a potential role for calcium and lipid signaling pathways in the pathophysiology of severe COVID-19.
  • The identified signatures offer insights into host-pathogen interactions and potential therapeutic targets.

Keywords:
COVID-19SARS-CoV-2combinatorial analysisdisease riskpatient stratificationreal world data analysissevere COVID-19

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