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The COVID-19 Pandemic during the Time of the Diabetes Pandemic: Likely Fraternal Twins?

ABSTRACT: An altered immune response to pathogens has been suggested to explain increased susceptibility to infectious diseases in patients with diabetes. Recent evidence has documented several immunometabolic pathways in patients with diabetes directly related to the COVID-19 infection. This also seems to be the case for prediabetic subjects with proinflammatory insulin resistance syndrome accompanied with prothrombotic hyperinsulinemic and dysglycemic states. Patients with frank hyperglycemia, dysglycemia and/or hyperinsulinemia develop systemic immunometabolic inflammation with higher levels of circulating cytokines. This deleterious scenario has been proposed as the underlying mechanism enhancing a cytokine storm-like hyperinflammatory state in diabetics infected with severe COVID-19 triggering multi-organ failure. Compared with moderately affected COVID-19 patients, diabetes was found to be highly prevalent among severely affected patients suggesting that this non-communicable disease should be considered as a risk factor for adverse outcomes. The COVID-19 pandemic mirrors with the diabetes pandemic in many pathobiological aspects. Our interest is to emphasize the ties between the immunoinflammatory mechanisms that underlie the morbidity and lethality when COVID-19 meets diabetes. This review brings attention to two pathologies of highly complex, multifactorial, developmental and environmentally dependent manifestations of critical importance to human survival. Extreme caution should be taken with diabetics with suspected symptoms of COVID-19 infection.

SUBMITTER: Cole SA

PROVIDER: S-EPMC7281197 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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The COVID-19 Pandemic during the Time of the Diabetes Pandemic: Likely Fraternal Twins?

Cole Shelley A SA Laviada-Molina Hugo A HA Serres-Perales Jeannette M JM Rodriguez-Ayala Ernesto E Bastarrachea Raul A RA

Pathogens (Basel, Switzerland) 20200519 5

An altered immune response to pathogens has been suggested to explain increased susceptibility to infectious diseases in patients with diabetes. Recent evidence has documented several immunometabolic pathways in patients with diabetes directly related to the COVID-19 infection. This also seems to be the case for prediabetic subjects with proinflammatory insulin resistance syndrome accompanied with prothrombotic hyperinsulinemic and dysglycemic states. Patients with frank hyperglycemia, dysglycem ...[more]

PMID: 32438687

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Project description:BackgroundCOVID-19 pandemic is disaster to public health worldwide. Better perspective on COVID's features early in its course-prior to the development of vaccines and widespread variants-may prove useful in the understanding of future pandemics. Ontology provides a standardized integrative method for knowledge modeling and computer-assisted reasoning. In this study, we systematically extracted and analyzed clinical phenotypes and comorbidities in COVID-19 patients found at different countries and regions during the early pandemic using an ontology-based bioinformatics approach, with the aim to identify new insights and hidden patterns of the COVID-19 symptoms.ResultsA total of 48 research articles reporting analysis of first-hand clinical data from over 40,000 COVID-19 patients were surveyed. The patients studied therein were diagnosed with COVID-19 before May 2020. A total of 18 commonly-occurring phenotypes in these COVID-19 patients were first identified and then classified into different hierarchical groups based on the Human Phenotype Ontology (HPO). This meta-analytic approach revealed that fever, cough, and the loss of smell and taste were ranked as the most commonly-occurring phenotype in China, the US, and Italy, respectively. We also found that the patients from Europe and the US appeared to have more frequent occurrence of many nervous and abdominal symptom phenotypes (e.g., loss of smell, loss of taste, and diarrhea) than patients from China during the early pandemic. A total of 22 comorbidities, such as diabetes and kidney failure, were found to commonly exist in COVID-19 patients and positively correlated with the severity of the disease. The knowledge learned from the study was further modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO), supporting semantic queries and analysis. Furthermore, also considering the symptoms caused by new viral variants at the later stages, a spiral model hypothesis was proposed to address the changes of specific symptoms during different stages of the pandemic.ConclusionsDifferential patterns of symptoms in COVID-19 patients were found given different locations, time, and comorbidity types during the early pandemic. The ontology-based informatics provides a unique approach to systematically model, represent, and analyze COVID-19 symptoms, comorbidities, and the factors that influence the disease outcomes.

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The COVID-19 Pandemic during the Time of the Diabetes Pandemic: Likely Fraternal Twins?

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The COVID-19 Pandemic during the Time of the Diabetes Pandemic: Likely Fraternal Twins?

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