Comparing the gestational diabetes mellitus prevalence and oral glucose tolerance test characteristics before and after the COVID-19 outbreak in Hongshan District of Wuhan, China, 2018- 2021 (preprint)

Background: The Coronavirus Disease 2019 (COVID-19) pandemic has significantly impacted the management and prevalence of gestational diabetes mellitus (GDM) among pregnant women worldwide. This study aimed to investigate the effects of the pandemic on GDM prevalence and oral glucose tolerance test (OGTT) characteristics in Hongshan District, Wuhan, China. Methods: We retrospectively analyzed data from 91,932 pregnant women screened for GDM before (January 1, 2018, to December 31, 2019) and after (January 1, 2020, to December 31, 2021) the onset of the COVID-19 pandemic. The study focused on changes in GDM prevalence, OGTT positive rates and glucose value distribution, and the diagnostic performance of OGTT. Results: The prevalence of GDM increased significantly from 14.5% (95% CI, 14.2-14.8%) pre-pandemic to 21.9% (95% CI, 21.5-22.4%) post-pandemic. A notable rise in OGTT positive rates was observed across all time points, with the most significant increase at the 0-hour mark. Regression analysis indicated a significant risk increase for GDM during the pandemic, even after adjusting for age. Diagnostic accuracy of the 0-hour OGTT improved in the pandemic era, with the area under the curve (AUC) rising from 0.78 to 0.79 and sensitivity from 0.56 to 0.58. Median OGTT values at all time points significantly increased post-pandemic, even after adjusting for age, indicating a shift in glucose metabolism among the study population. Conclusion: The COVID-19 pandemic has led to a significant increase in the prevalence of GDM among pregnant women in Hongshan District, Wuhan. This is evidenced by the elevated rates of positive OGTT and altered median glucose values, indicating a shift in glucose metabolism. These findings underscore the profound impact of the pandemic on maternal and neonatal health. They emphasize the imperative for continuous monitoring and the development of updated, localized diagnostic criteria for OGTT to enhance the identification and treatment of GDM during and after global health crises.

A retrospective clinical study in Graves disease with COVID-19 infection in China (preprint)

Background Corona Virus Disease 2019 (COVID-19) is the most prevalent global pandemic in recent times. Graves disease (GD), an autoimmune thyroid disease, is a clinical syndrome caused by excessive thyroid hormones. Our study is to understand the current epidemiological situation of COVID-19 infection in GD patients, and to analyze whether COVID-19 will affect the thyroid function, thyroid autoantibody and metabolism of GD patients.Methods 109 GD patients were followed by Shanghai General Hospital Thyroid Disease Center (TDC) from November 2022 to June 2023. There were three groups defined, i.e., pre, one-month after and three months after infection with COVID-19. SPSS was used to analyze the recruited data.Results 109 GD patients are infected with COVID-19 (72.48%), uncontrolled GD patients with high FT3 had a higher COVID-19 infection rate (79.31%). As for thyroid function in 35 GD patients with antithyroid drug (ATD) maintenance stage, there were significant differences in FT3, FT4, TT3 and TT4 before and after being infected with COVID-19. What’s more, there’s a significant difference between GD patients in one month and three months after COVID-19 infection of high TSAb group (p = 0.048) but no significant difference between pre and one month. What’s more, there were significant differences in TT3, TT4 of GD patients after infected COVID-19 in non. And Phosphorus (P), 25-hydroxyvitamin D (25-OH-D3), Procollagen type 1 N-terminal propeptide (P1NP) in GD patients were be affected by COVID-19 infection.Conclusion GD patients with uncontrolled thyroid function group are susceptible to COVID-19. COVID-19 may affect the thyroid function of GD in TT3, TT4, TSAb high level group infection. COVID-19 vaccine is conducive to the stability of GD patients' condition. And COVID-19 may affect the bone metabolism in GD patients before and after COVID-19 infection. But there is no effect on glucose metabolism or lipid metabolism.

Immune Correlates of Hyperglycemia and Vaccination in a Non-human Primate Model of Long-COVID (preprint)

Hyperglycemia, and exacerbation of pre-existing deficits in glucose metabolism, are major manifestations of the post-acute sequelae of SARS-CoV-2 (PASC). Our understanding of lasting glucometabolic disruptions after acute COVID-19 remains unclear due to the lack of animal models for metabolic PASC. Here, we report a non-human primate model of metabolic PASC using SARS-CoV-2 infected African green monkeys (AGMs). Using this model, we have identified a dysregulated chemokine signature and hypersensitive T cell population during acute COVID-19 that correlates with elevated and persistent hyperglycemia four months post-infection. This persistent hyperglycemia correlates with elevated hepatic glycogen, but there was no evidence of long-term SARS-CoV-2 replication in the liver and pancreas. Finally, we report a favorable glycemic effect of the SARS-CoV-2 mRNA vaccine, administered on day 4 post-infection. Together, these data suggest that the AGM metabolic PASC model exhibits important similarities to human metabolic PASC and can be utilized to assess therapeutic candidates to combat this syndrome.

A Network Analysis of Molecular Interactions to Study the Development of New-onset Diabetes and Hypertension after COVID-19 Infection Using Bioinformatics Tools. (preprint)

Introduction: The association between COVID-19 infection and the development of new-onset diabetes and hypertension is an emerging area of research. However, a comprehensive understanding of the underlying molecular mechanisms is still lacking. Network analysis using bioinformatics tools can provide valuable insights into the complex molecular interactions involved in these conditions after COVID-19 infection. Objective: This study aims to use bioinformatics tools to analyze the network of molecular interactions related to new-onset diabetes and hypertension following COVID-19 infection. Methods: Data from publicly available databases were utilized, including gene expression profiles and protein-protein interaction information. Differential expression analysis was performed to identify genes that were differentially expressed in individuals with new-onset diabetes and hypertension after COVID-19 infection compared to healthy controls. A protein interaction network was constructed using bioinformatics tools to explore the functional relationships among the identified differentially expressed genes. Results: The network analysis revealed several key proteins and pathways related to the pathogenesis of new-onset diabetes and hypertension after COVID-19 infection. Notably, proteins involved in insulin signaling, glucose metabolism, inflammation, and blood pressure regulation were found to be prominently associated. The signaling pathway and the renin-angiotensin system were identified as key pathways in this context. Conclusion: This study provides insights by showing a network-based perspective on the molecular interactions involved in the development of new-onset diabetes and hypertension after COVID-19 infection. Keywords: COVID-19 infection, diabetes, hypertension, network analysis, bioinformatics.

Post-COVID-19 syndrome and insulin resistance 20 months after a mild COVID-19 (preprint)

Objective SARS-CoV-2 infection is associated with impaired glucose metabolism. Although the mechanisms are not fully understood, insulin resistance (IR) appears to be a central factor. Patients who had a severe acute phase, but even asymptomatic or with mild COVID-19, have an increased risk of T2DM. After the acute phase, post-COVID-19 syndrome (PCS) also seems to be related to this metabolic disturbance, but there is a paucity of studies. This study aims to evaluate a possible relationship between PCS and IR after mild COVID-19 and, if confirmed, whether there are differences by sex. Subjects and methods Retrospective observational cohort study including subjects who had mild COVID-19 between April and September 2020 in a community setting. None had been vaccinated against SARS-CoV-2 at inclusion, and previous T2DM and liver disease were exclusion criteria. Patients who met NICE criteria were classified as PCS+. Epidemiological and laboratory data were analysed. Three assessments were performed: 1E (pre-COVID-19, considered baseline and reference for comparisons), 2E (approximately 3 months after the acute phase), and 3E (approximately 20 months after the acute phase). A triglyceride-to-glucose (TyG) index [≥]8.74 was considered IR. Albumin-to-globulin ratio (AGR) and lactate dehydrogenase (LDH) were assessed as inflammatory markers. Bivariate analyses were performed, using nonparametric and repeated measures tests. A subsample without metabolic disorder or CVD (age< median, BMI<25 kg/m^2, elevated AGR, TyG index=7.80 [0.5]) was generated to reasonably rule out prior baseline IR that could bias the results. The relationships between PCS and TyG in 3E (TyG3) were modeled in 8 multiple regressions, stratifying by sex and BMI combinations. Results A total of 112 subjects (median [IQR] of age= 44 [20] years; 65 women) were analysed. Up to 14.3% was obese and 17% was hypertensive. Significant increases between 1E and 3E were registered regarding (i) basal glycemia (BG), 87 [14] mg/dL vs. 89 [14]; p=0.014, (ii) TyG index (8.25 [0.8] vs. 8.32 [0.7]; p=0.002), and (iii) LDH in 3rd tertile (16.1% vs 32.1%; p=0.007). A total of 8 previously normoglycemic subjects, showed BG2 or BG3 >126 mg/dL. The subgroups with IR highest prevalence at 3E were those of BMI [≥]25 kg/m^2 and PCS+. The subgroup without CVD presented a significant increase in the TyG index (TyG1=7.80 [0.1] vs. TyG3= 8.28 [0.1]; p=0.017). LDH1 was significantly correlated with TyG3 in both sexes (rho=0.214 in women, rho=0.298 in men); in contrast, LDH2 and LDH3 did not present such an association. In multivariable analysis, PCS has shown to be an independent and predictive variable of TyG index in women with BMI<25 kg/m^2, after adjustment for age, hypertension, BMI, Charlson comorbidity index, AGR1, AGR2, LDH1, number of symptoms of acute COVID-19, and number of days of the acute episode (beta coefficient=0.350; p=0.039). Conclusions PCS has played a secondary role in predicting IR, showing a modest effect compared to BMI or prior hypertension. A significant increase in IR has been noted 20 months after mild COVID-19, both in cases of previous baseline IR and in those without previous IR. Basal serum LDH has shown to be predictive of current TyG, regardless of elevated LDH after SARS-CoV-2 infection. There were profound differences between women and men, confirming the need for a sex-stratified analysis when addressing the relation between PCS and glycemic alterations.

Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of COVID-19 Recovery (preprint)

Conventional whole-body 18F-FDG PET imaging provides a semi-quantitative evaluation of overall glucose metabolism without gaining insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included thirteen healthy subjects and twelve recovering COVID-19 subjects within eight weeks of confirmed diagnosis. Each subject had a dynamic 18F-FDG scan on the uEXPLORER total-body PET/CT system for one hour. Semiquantitative standardized uptake value (SUV) and SUV ratio relative to blood (SUVR) were calculated for regions of interest (ROIs) in different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify microparametric rate constants K1 and k3 that characterize 18F-FDG blood-to-tissue delivery and intracellular phosphorylation, respectively, and a macroparameter Ki that represents 18F-FDG net influx rate. Statistical tests were performed to examine differences between the healthy controls and recovering COVID-19 subjects. Impact of COVID-19 vaccination was investigated. We further generated parametric images to confirm the ROI-based analysis. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and Ki in the recovering COVID-19 subjects, indicating an improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k3, but not with the delivery rate K1, which suggests it is glucose phosphorylation, not glucose delivery, that drives the observed difference of glucose metabolism in the lungs. Meanwhile, there was no or little difference in bone marrow metabolism measured with SUV, SUVR and Ki, but a significant increase in bone-marrow 18F-FDG delivery rate K1 in the COVID-19 group (p<0.05), revealing a difference of glucose delivery in this immune-related organ. The observed differences were lower or similar in vaccinated COVID-19 subjects as compared to unvaccinated ones. The organ ROI-based findings were further supported by parametric images. Conclusions: Higher lung glucose metabolism and bone-marrow glucose delivery were observed with total-body multiparametric 18F-FDG PET in recovering COVID-19 subjects as compared to healthy subjects, which suggests continued inflammation due to COVID-19 during the early stages of recovery. Total-body multiparametric PET of 18F-FDG delivery and metabolism can provide a more sensitive tool and more insights than conventional static whole-body 18F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.

New-Onset Diabetes and COVID-19: Evidence from a Global Clinical Registry (preprint)

Background Mounting evidence shows association between COVID-19 and new diagnoses of diabetes. It is unclear, however, if COVID-19 increases detection of pre-existing diabetes or if it can induce new-onset of the disease. Methods We established a global online registry of COVID-19-related diabetes (CoviDIAB) using a web-enabled data capture system (Dendrite Clinical Systems). In this study we aimed to investigate whether COVID-19 can induce new-onset diabetes, its subtypes and clinical manifestations. To this end, we analyzed clinical and laboratory data from cases of newly-diagnosed diabetes occurring during or within four weeks from an episode of COVID-19. To exclude pre-existing hyperglycaemia, new-onset diabetes was defined as: blood sugar levels above diabetes thresholds (fasting glycaemia ≥ 126 mg/dL or non-fasting glycemia > 200 mg/dL), no prior history of the disease or use of glucose-lowering medications, and HbA1c < 6·5% at presentation. Results Between October 2020 and April 2022, 67 contributors from 61 hospitals in 25 countries entered data on 537 eligible cases of newly-diagnosed diabetes. New-onset diabetes was identified in 102 of 473 newly-diagnosed cases with recorded HbA1c (22%). Among adults, diabetes subtypes were type 2 (59%) and “not-yet known” (41%). There were two cases of new-onset type 1 diabetes among children. Hyperglycaemia persisted beyond resolution of the infection in 39 of 89 (45%) patients with new-onset diabetes who survived the episode of COVID-19. Further follow-up data beyond 3-months was available for 28 such cases, showing remission of diabetes in five and persistent diabetes in 23 cases (82%). Conclusions This study shows clinical plausibility for a diabetogenic effect of COVID-19, supporting screening for diabetes in people who contract the infection. Further investigation is warranted to confirm mechanisms of viral interference with glucose metabolism. The CoviDIAB registry is accessible online at http://covidiab.e-dendrite.com.

Diet induced obesity and type 2 diabetes drives exacerbated sex-associated disease profiles in K18-hACE2-mice challenged with SARS-CoV-2 (preprint)

SARS-CoV-2 infection results in wide-ranging disease manifestation from asymptomatic to potentially lethal. Infection poses an increased threat of severity to at-risk populations including those with hypertension, diabetes, and obesity. Type 2 Diabetes (T2DM), is characterized, in part, by insulin insensitivity and impaired glucose regulation. T2DM patients have increased disease severity and poorer outcomes with COVID-19. We utilized the diet-induced obesity (DIO) model of Type 2 Diabetes in SARS-CoV-2-susceptible K18-hACE2 transgenic mice to better understand the obesity co-morbidity. Female DIO, but not male DIO mice challenged with SARS-CoV-2 were observed to have shortened time to morbidity compared to normal diet mice. Increase in susceptibility to SARS-CoV2 in female DIO was associated with increased total viral RNA burden compared to male mice. RNAseq analysis was performed on the lungs of non-challenged, challenged, females, males, of either normal diet or DIO cohorts to determine the disease specific transcriptional profiles. DIO female mice had more total activated genes than normal diet mice after challenge; however, male mice experienced a decrease. GO term analysis revealed the DIO condition increased interferon response signatures and interferon gamma production following challenge. Male challenged mice had robust expression of antibody-related genes suggesting antibody producing cell localization in the lung. DIO reduced antibody gene expression in challenged males. Collectively this study establishes a preclinical T2DM/obesity co-morbidity model of COVID-19 in mice where we observed sex and diet specific responses that begin to explain the effects of obesity and diabetes on COVID-19 disease.

Angiotensin converting enzyme 2 (ACE2): Virus accomplice or host defender (preprint)

The current coronavirus disease-19 (COVID-19) caused by the acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has seriously disrupted the daily life of human, mainly attributed to the fact that we know too little about SARS-CoV-2. Increasing studies show that viral infection alters host cells glucose metabolism, which is crucial for viral nucleic acid replication. Here, we integrated RNA-sequencing results and found that SARS-CoV-2 infection alters the aerobic glycolysis, pentose phosphate pathway (oxiPPP), and DNA replication in lung tissues and cells. However, the direction of metabolic flux and DNA replication were dominated by angiotensin-converting enzyme 2 (ACE2), a host cell-expressed viral receptor protein. More interesting, although hosts with high expression of ACE2 are more likely to be infected with SARS-CoV-2, the invading virus cannot perform nucleic acid replication well due to the restriction of glucose metabolism, and eventually resulting prolonged infection-cycle or infection failure. Our findings, after a typical epidemiological investigation and modeling analysis, preliminarily explain the reasons for the emergence of asymptomatic infections or lower copy virus at early stage in host with higher ACE2 levels, which will provide important help for the development of more accurate and effective detection methods for diagnosing COVID-19.

Abnormal Glucose Metabolism Leads To Severe COVID-19 Due To Hyperinflammation: A Cross-Sectional Study (preprint)

Background: We aimed to describe the clinical features of novel coronavirus disease 2019 (COVID-19) patients with or without diabetes, focusing on the effect of abnormal HbA1c levels on inflammatory reactions and disease severity. Methods: : A total of 190 patients with COVID-19 were included in this cross-sectional study. Clinical and laboratory characteristics were collected and compared among moderate, severe, and critical cases, as well as among diabetes, prediabetes and nondiabetes cases. Receiver operating characteristic (ROC) curves were constructed to determine the diagnostic ability of HbA1c for disease severity. Logistic regression was used to explore the relationship between HbA1c levels and worse prognosis of COVID-19. Results: : HbA1c levels at admission were significantly different in patients with moderate, severe, and critical diseases (P<0.001). The area under the curve (AUC) of HbA1c levels to distinguish between moderate and severe-critical diseases was 0.938 (95% CI 0.906–0.970). After adjustment for confounders, the results showed that the increasing odds of in-hospital deaths were associated with HbA1c levels >6.0% (42 mmol/mol) (aOR 2.971 [95% CI 1.002, 8.804], P=0.049), and the increasing odds of severe or critical COVID-19 were associated with HbA1c levels ≥5.7% (39 mmol/mol) (aOR 29.588 [95% CI 8.285, 105.457], P<0.001). In addition, HbA1c levels strongly correlated with inflammatory markers and cytokines. Conclusions: : Abnormal glucose metabolism can cause a hyperinflammatory state of COVID-19, which manifests as severe disease.

Immune and metabolic beneficial effects of Beta 1,3-1,6 glucans produced by two novel strains of Aureobasidium pullulans in healthy middle-aged Japanese men: An exploratory study (preprint)

Background Imbalances in glucose and lipid metabolism in the background of a declining immune system, along with aging, make one prone to glucolipotoxicity-related diseases such as hepatic steatosis and to high risk of infection-related mortality, as with COVID-19, warranting a safe prophylactic measure to help regulate both metabolism and the immune system. Based on the beneficial effects of the AFO-202 strain of black yeast Aureobasidium pullulans -produced beta 1,3-1,6 glucan in balancing of blood glucose and immune enhancement, and that of the N-163 strain of the same species in lipid metabolism and immune modulation, in this pilot study, we have evaluated their specific benefits in healthy human subjects. Methods Sixteen healthy Japanese male volunteers (aged 40 to 60 years) took part in this clinical trial. They were divided into four groups (n = 4 each): Group I consumed AFO-202 beta glucan (2 sachets of 1 g each per day), IA for 35 days and IB for 21 days; Group II consumed a combination of AFO-202 beta glucan (2 sachets of 1 g each) and N-163 beta glucan (1 sachet of 15 g gel each per day), IIA for 35 days and IIB for 21 days. Investigations for immune stimulation, anti-glycaemic, and anti-cholesterolemia biomarkers were undertaken in all four groups. Results In terms of metabolic control of glucose, the decrease in HbA1C and glycated albumin (GA) was significantly better in Group I compared with the other groups. Immune enhancement in terms of a significant increase of eosinophils and monocytes and marginal decrease in D-dimer levels, decrease in neutrophil-to-lymphocyte ratio (NLR), with an increase in the lymphocyte-to-CRP ratio (LCR) and leukocyte-to-CRP ratio (LeCR) was observed in Group I. Regulation of lipids by decrease in total and LDL cholesterol was better in Group II, and immunomodulation of coagulation-associated and anti-inflammatory markers by a decrease of CD11b, serum ferritin, galectin-3, fibrinogen was profound in Group II. Conclusion A. pullulans, a polythermotolerant black yeast - produced AFO-202 beta glucan has balanced blood glucose with marginal immune enhancement in healthy individuals, which when combined with N-163 beta glucan, balanced the lipid profile and immunomodulation. This outcome warrants larger clinical trials to understand the mechanisms and explore the potentials of these safe food supplements in prevention and prophylaxis of diseases due to dysregulated glucose and lipid metabolism, such as fatty liver disease, and infections such as COVID-19 in which a balanced immune activation and immunomodulation are of utmost importance, besides their administration as an adjunct to existing therapeutic approaches of both communicable and non-communicable diseases.

Multi-Dimensional Reduction Clustering of Complex Carbohydrates Reveal Tissue Metabolism, Heterogeneity and Histopathology (preprint)

Formalin-fixed paraffin-embedded (FFPE) human tissues represent the world's largest collection of accessible clinical specimens with matched, well-annotated clinical course for disease progression. Currently, FFPE sections are limited to low throughput histo- and immunological assessments. Extracting largescale molecular information remains a major technological barrier to uncover the vast potential within FFPE specimens for translation and clinical research. Two critical but understudied facets of glucose metabolism are anabolic pathways for glycogen and N-linked glycan biosynthesis. Together, these complex carbohydrates represent bioenergetics, protein-structure function, and tissue architecture in human biology. Herein, we report the high-dimensional Metabolomics-Assisted Digital pathology Imaging (Madi) workflow that combines matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) with machine learning for the comprehensive assessment of tissue heterogeneity, histopathology, and metabolism in human FFPE sections. In normal human tissue sections, Madi accurately identifies anatomical regions within liver and the brain. In human lung diseases, Madi accurately predicts major lung pathologies such as honeycomb change, late-stage fibrosis, diffuse alveolar damage (DAD), and acute fibrinous and organizing pneumonia (AFOP) from idiopathic pulmonary fibrosis (IPF) and COVID-19 pneumonia specimens with precision. In depth pathway enrichment analyses reveal unique metabolic pathways are associated with distinct pathological regions, which highlight aberrant complex carbohydrate metabolism as a previously unknown molecular event associated with disease progression that could hold key to future therapeutic interventions.

The influence of hypoglycemia and hyperglycemia on the adverse outcome of COVID-19 combined with diabetes mellitus: A protocol for systematic review and meta-analysis.

BACKGROUND: COVID-19 has become a global epidemic, causing huge loss of life and property. Diabetes will affect the prognosis of COVID-19 patients in many ways. Both hyperglycemia and hypoglycemia can affect oxidative stress and lead to the release of inflammatory mediators, leading to multiple organ damage and chronic inflammation. Here, we want to know whether hyperglycemia or hypoglycemia will adversely affect patients with diabetes and COVID-19 comorbidities. This has very important practical significance for the control of blood glucose in the treatment of diabetes combined with SARS-COV-2 infection. METHODS: We will search electronic databases including PubMed, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL), Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), and Wanfang database using keywords related to COVID-19, diabetes mellitus, hyperglycemia and hypoglycemia. We will manually search gray literature, such as conference proceedings and academic degree dissertations, and trial registries. Two independent reviewers will screen studies, extract data, and evaluate risk of bias. Data analysis will be conducted using the Review Manager software version 5.3.5 and STATA4.0 software for Mac. The main outcome was the mortality of COVID-19 which was included in meta-analysis and subgroup analysis. The bias of the study was evaluated independently by NOS scale, and published by funnel chart. The sensitivity was analyzed row by row. RESULTS: This study will provide a high-quality synthesis of hyperglycemia and hypoglycemia in patients with COVID-19 combined with diabetes mellitus. To provide evidence for clinical treatment of diabetes mellitus combined with COVID-19. And the results will be published at a peer-reviewed journal.INPLASY registration number INPLASY 202080096.

Impaired glucose metabolism in patients with diabetes, prediabetes and obesity is associated with severe Covid-19 (preprint)

Background: Identification of risk factors of severe Covid-19 is critical for improving therapies and understanding SARS-CoV-2 pathogenesis. Methods: We analyzed 184 patients hospitalized for Covid-19 in Livingston, New Jersey for clinical characteristics associated with severe disease. Results: The majority of Covid-19 patients had diabetes mellitus (DM) (62.0%), Pre-DM (23.9%) with elevated FBG, or a BMI > 30 with normal HbA1C (4.3%). SARS-CoV-2 infection was associated with new and persistent hyperglycemia in 29 patients, including several with normal HbA1C levels. Forty-four patients required intubation, which occurred significantly more often in patients with DM as compared to non-diabetics. Conclusions: Severe Covid-19 occurs in the presence of impaired glucose metabolism in patients with SARS-CoV-2 infection. The association of dysregulated glucose metabolism and severe Covid-19 suggests a previously unrecognized manifestation of primary SARS-CoV-2 infection. Exploration of pathways by which SARS-CoV-2 impacts glucose metabolism is critical for understanding disease pathogenesis and developing therapies.

Overall reduced lymphocyte subsets worsening disease severity and prognosis in COVID-19 severe cases with diabetes mellitus in Chengdu, China (preprint)

Background The outbreak of coronavirus disease 2019 (COVID-19) is widespread throughout China and the world. Methods Demographic, clinical data of 95 confirmed cases with COVID-19 on admission at the Public and Health Clinic Centre of Chengdu from January 16 to March 16, 2020, were retrospectively collected and analyzed. Of them 76, 19 cases were enrolled in non-DM group (without DM), DM group (with DM), respectively; according to the disease severity 57, 19, 8, 11 cases were further divided into non-severe non-DM subgroup (light and common type and without DM), severe non-DM subgroup (severe and critical illness type and without DM), non-severe DM subgroup (light and common type and with DM), severe DM subgroup (severe and critical illness type and with DM), respectively. The severe rate and the prognosis was compared between two groups. The data of peripheral lymphocyte and subsets, age, glucose metabolism parameters were compared between four subgroups, and its relationship to the disease severity, the viral negative conversion time, and the prognosis were analyzed.Results In this COVID-19 cohort the proportion of DM was 20%. Patients with DM had significantly higher severe rate and worse prognosis than those without DM, the difference was significant (severe rate ,cured, unhealed and death in DM and non-DM groups:61.11%vs.25.00%,26.32%,68.42%;5.26%vs.71.05%,26.32%,2.68%,х2=2.940, 3.394,P=0.003,0.001,respectively),simultaneously the proportion of DM in severe cases was higher than that in non-severe cases, the obvious difference was found (36.67% vs.12.31%,х2=2.744,P=0.006).Severe cases with DM tended to have the lowest lymphocytes count levels and percentage values, as well as the lowest T cells count levels and percentage values, helper T cells count levels and percentage values, suppressor T cells count levels, B cells count levels and percentage values compared with those severe cases without DM and non-severe cases with or without DM. The important influencing factors were that age, DM, lymphocyte percentage values and helper T cells percentage values for the disease severity, lymphocyte percentage values and B cell percentage values for the viral negative conversion time, and age, the disease severity and the viral negative conversion time for the prognosis.Conclusions The COVID-19 severe cases with DM had the lowest lymphocytes count level and percentage value, especially T and B lymphocytes count levels and percentage value. Overall decreased lymphocytes subsets and DM maybe worsen prognosis by worsening the disease severity and prolonging the viral negative conversion time. Combination immunomodulatory therapy based on comprehensive treatment might improve prognosis of the COVID-19 severe cases with DM.