Association Between Metabolic Syndrome Inflammatory Biomarkers and COVID-19 Severity

Thaidan T Pham; Yuanhao Zu; Farhad Ghamsari; Janice Oh; Franck Mauvais-Jarvis; Hui Zheng; Michael Filbin; Joshua L Denson

doi:10.1210/jendso/bvad029

Association Between Metabolic Syndrome Inflammatory Biomarkers and COVID-19 Severity

J Endocr Soc. 2023 Feb 23;7(5):bvad029. doi: 10.1210/jendso/bvad029. eCollection 2023 Mar 6.

Authors

Thaidan T Pham¹, Yuanhao Zu², Farhad Ghamsari³, Janice Oh⁴, Franck Mauvais-Jarvis^{5

6}, Hui Zheng⁷, Michael Filbin⁸, Joshua L Denson³

Affiliations

¹ Department of Internal Medicine, UC San Diego Health, San Diego, CA 92103, USA.
² Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
³ Section of Pulmonary Diseases, Critical Care and Environmental Medicine, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA 70112, USA.
⁴ Department of Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
⁵ Section of Endocrinology, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA 70112, USA.
⁶ Department of Endocrinology, Southeast Louisiana VA Medical Center, New Orleans, LA 70112, USA.
⁷ Massachusetts General Hospital Biostatistics Center, Massachusetts General Hospital, Boston, MA 02114, USA.
⁸ Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.

Abstract

Context: Metabolic syndrome (MetS) is associated with increased risk of severe COVID-19. MetS inflammatory biomarkers share similarities with those of COVID-19, yet this association is poorly explored.

Objective: Biomarkers of COVID-19 patients with and without MetS, the combination of diabetes, hypertension, obesity, and/or dyslipidemia, were analyzed to identify biological predictors of COVID-19 severity.

Methods: In this prospective observational study, at a large academic emergency department in Boston, Massachusetts, clinical and proteomics data were analyzed from March 24 to April 30, 2020. Patients age ≥18 with a clinical concern for COVID-19 upon arrival and acute respiratory distress were included. The main outcome was severe COVID-19 as defined using World Health Organization COVID-19 outcomes scores ≤4, which describes patients who died, required invasive mechanical ventilation, or required supplemental oxygen.

Results: Among 155 COVID-19 patients, 90 (58.1%) met the definition of MetS and 65 (41.9%) were identified as Control. The MetS cohort was more likely to have severe COVID-19 compared with the Control cohort (OR 2.67 [CI 1.09-6.55]). Biomarkers, including CXCL10 (OR 1.94 [CI 1.38-2.73]), CXCL9 (OR 1.79 [CI 1.09-2.93]), HGF (OR 3.30 [CI 1.65-6.58]), and IL6 (OR 2.09 [CI 1.49-2.94]) were associated with severe COVID-19. However, when stratified by MetS, only CXCL10 (OR 2.39 [CI 1.38-4.14]) and IL6 (OR 3.14 [CI 1.53-6.45]) were significantly associated with severe COVID-19.

Conclusions: MetS-associated severe COVID-19 is characterized by an immune signature of elevated levels of CXCL10 and IL6. Clinical trials targeting CXCL10 or IL6 antagonism in this population may be warranted.

Keywords: COVID-19; metabolic syndrome; proteomics.

Abstract

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