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. 2020 May 8;14(4):671-677.
doi: 10.1016/j.dsx.2020.05.013. Online ahead of print.

Diabetes and Metabolic Syndrome as Risk Factors for COVID-19

Free PMC article

Diabetes and Metabolic Syndrome as Risk Factors for COVID-19

Marko Marhl et al. Diabetes Metab Syndr. .
Free PMC article


Background and aims: Clinical evidence exists that patients with diabetes are at higher risk for Coronavirus disease 2019 (COVID-19). We investigated the physiological origins of this clinical observation linking diabetes with severity and adverse outcome of COVID-19.

Methods: Publication mining was applied to reveal common physiological contexts in which diabetes and COVID-19 have been investigated simultaneously. Overall, we have acquired 1,121,078 publications from PubMed in the time span between 01-01-2000 and 17-04-2020, and extracted knowledge graphs interconnecting the topics related to diabetes and COVID-19.

Results: The Data Mining revealed three pathophysiological pathways linking diabetes and COVID-19. The first pathway indicates a higher risk for COVID-19 because of a dysregulation of Angiotensin-converting enzyme 2. The other two important physiological links between diabetes and COVID-19 are liver dysfunction and chronic systemic inflammation. A deep network analysis has suggested clinical biomarkers predicting the higher risk: Hypertension, elevated serum Alanine aminotransferase, high Interleukin-6, and low Lymphocytes count.

Conclusions: The revealed biomarkers can be applied directly in clinical practice. For newly infected patients, the medical history needs to be checked for evidence of a long-term, chronic dysregulation of these biomarkers. In particular, patients with diabetes, but also those with prediabetic state, deserve special attention.

Keywords: ACE2; Hypertension; Inflammation; Liver dysfunction; SARS-Coronavirus-2.

Conflict of interest statement

Declaration of competing interest The authors declare that they have no conflicts of interest.


Fig. 1
Fig. 1
Results of Data Mining for the ACE2 publication database: Frequency of topic usage for the period before 2020 (A) and for the year 2020 (C), and the corresponding extracted weighted knowledge graph for the period before 2020 (B) and for the year 2020 (D).
Fig. 2
Fig. 2
Merged knowledge graph computed by Data Mining for the SARS, Diabetes, ACE2, ALT, Inflammation, and Liver & Liver disease databases acquired from PubMed for all years.

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    1. Zhou F., Yu T., Du R., Fan G., Liu Y., Liu Z. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. - DOI - PMC - PubMed
    1. Zhang C., Shi L., Wang F.-S. Liver injury in COVID-19: management and challenges. Lancet Gastroenterol Hepatol. 2020;5:428–430. doi: 10.1016/S2468-1253(20)30057-1. - DOI - PMC - PubMed