LAUSR

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.