Effect of hyperglycemia on the immune function of COVID-19 patients with type 2 diabetes mellitus: a retrospective study

Hyperglycemia in the diabetic range, but not previous diagnosis of diabetes mellitus, is an independent indicator of poor outcome in patients hospitalized for severe COVID-19

AIMS

Diabetes mellitus (DM) and hyperglycemia are associated with poor outcome(s) in COVID-19 hospitalized patients, but their independent impact on prognosis remains unclear. We aimed to assess the impact of DM and hyperglycemia on COVID-19 outcomes.

METHODS

Clinical data/records from COVID-19 patients admitted to the Parma University-Hospital (February 23rd to March 31st, 2020) were retrieved and analysed (NCT04550403). Fasting plasma glucose (FPG), inflammatory markers and the main biochemical variables were collected at admission. Patients underwent chest high-resolution CT and arterial blood gas analysis to determine the PaO2/FiO2 ratio (P/F ratio). The primary outcome was a composite of intensive care unit admission and/or death.

RESULTS

Among 756 subjects, 143 (19%) had DM. These patients were older with higher comorbidity rates. The primary outcome occurred in 61.5% DM patients versus 43.4% without DM (p < 0.001). In multivariable analysis (accuracy UC = 0.93), older age, cardiovascular and kidney diseases, FPG ≥ 126 mg/dl, C-reactive protein, and P/F ratio, but not previous DM, were independent risk indicators.

CONCLUSIONS

DM indicated poor COVID-19 outcomes, but not when adjusted for other clinical variables/comorbities, suggesting that its impact was mostly driven by concomitant factors. The independent role of fasting hyperglycemia points to the need for further research on its contribution to COVID-19.

Quantitative histopathological analysis of thrombi retrieved by mechanical thrombectomy and their association with stroke aetiology

BACKGROUND AND PURPOSE

Approximately 25% of acute large vessel occlusive (LVO) ischaemic strokes are of unknown thrombotic origin, and there is a need to establish the aetiology to guide subsequent preventative measures. The aim of this study was to quantify thrombus composition in patients with LVO and explore associations between thrombus composition and stroke aetiology.

METHODS

Thrombi were extracted from 132 patients with acute ischaemic stroke. Erythrocytes, leucocytes and F+P (fibrin+platelet) proportions were assessed in tissue sections stained with H&E, while CD3+ T cells and neutrophil extracellular traps (NETs) were quantified in immunohistochemistry-stained sections. Thrombus components, clinical parameters and interventional variables were compared between different stroke subtypes defined by Trial of ORG 10172 in Acute Stroke Treatment criteria.

RESULTS

F+P composition was significantly higher (p<0.001) and erythrocyte proportions were significantly lower (p<0.001) in cardioembolic thrombi than in large artery atherosclerosis thrombi. The composition of thrombi from undetermined aetiology strokes resembled that from cardioembolic strokes. CD3+ T cell and NET proportions were not significantly different between stroke subtypes. CD3+ density per unit area was associated with the occlusive site, being significantly higher in the anterior circulation than the posterior circulation (p=0.004). Cardioembolic strokes were more common in the anterior circulation than large artery atherosclerosis strokes (p=0.002). Recanalisation time was significantly longer for large artery atherosclerosis emboli than for cardioembolic emboli (p=0.032).

CONCLUSION

There is significant heterogeneity in thrombus composition among different stroke subtypes. The quantitative assessment of thrombus composition may be a useful biomarker of stroke aetiology, and strokes of undetermined aetiology may be more likely to have a cardioembolic origin.

Genetic, Epigenetic, and Hormonal Regulation of Stress Phenotypes in Major Depressive Disorder: From Maladaptation to Resilience

Major Depressive Disorder (MDD) is a complex psychiatric disorder with varied molecular mechanisms underlying its aetiology, diagnosis, and treatment. This review explores the crucial roles of stress, genetics, epigenetics, and hormones in shaping susceptibility and resilience to mood disorders. We discuss how acute stress can be beneficial, while prolonged stress disrupts brain function, leading to MDD. The review also highlights the significance of various animal models in understanding depression pathophysiology, including zebrafish, mice, and rats, which exhibit distinct sex differences in stress responses. Furthermore, we delve into the molecular bases of susceptible and resilient phenotypes, focusing on genetic aspects such as gene polymorphisms, mutations, and telomere length alterations. The review also examines epigenetic aspects including DNA methylation, histone acetylation and deacetylation, histone methylation and HMTs, and miRNA, which contribute to the development of MDD. Additionally, we explore the role of hormones such as estrogen, progesterone, and prolactin in modulating stress responses and influencing MDD susceptibility and resilience. Finally, we discuss the clinical implications of these findings, including recent clinical methods for determining MDD susceptibility and resiliency phenotypes. By consolidating the current knowledge and insights, this review aims to provide a comprehensive understanding of the molecular basis of susceptibility and resilience in mood disorders, contributing to the ongoing efforts in combating this debilitating disorder.

Association of glycemic control with Long COVID in patients with type 2 diabetes: findings from the National COVID Cohort Collaborative (N3C)

INTRODUCTION

Elevated glycosylated hemoglobin (HbA1c) in individuals with type 2 diabetes is associated with increased risk of hospitalization and death after acute COVID-19, however the effect of HbA1c on Long COVID is unclear.

OBJECTIVE

Evaluate the association of glycemic control with the development of Long COVID in patients with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

We conducted a retrospective cohort study using electronic health record data from the National COVID Cohort Collaborative. Our cohort included individuals with T2D from eight sites with longitudinal natural language processing (NLP) data. The primary outcome was death or new-onset recurrent Long COVID symptoms within 30-180 days after COVID-19. Symptoms were identified as keywords from clinical notes using NLP in respiratory, brain fog, fatigue, loss of smell/taste, cough, cardiovascular and musculoskeletal symptom categories. Logistic regression was used to evaluate the risk of Long COVID by HbA1c range, adjusting for demographics, body mass index, comorbidities, and diabetes medication. A COVID-negative group was used as a control.

RESULTS

Among 7430 COVID-positive patients, 1491 (20.1%) developed symptomatic Long COVID, and 380 (5.1%) died. The primary outcome of death or Long COVID was increased in patients with HbA1c 8% to <10% (OR 1.20, 95% CI 1.02 to 1.41) and ≥10% (OR 1.40, 95% CI 1.14 to 1.72) compared with those with HbA1c 6.5% to <8%. This association was not seen in the COVID-negative group. Higher HbA1c levels were associated with increased risk of Long COVID symptoms, especially respiratory and brain fog. There was no association between HbA1c levels and risk of death within 30-180 days following COVID-19. NLP identified more patients with Long COVID symptoms compared with diagnosis codes.

CONCLUSION

Poor glycemic control (HbA1c≥8%) in people with T2D was associated with higher risk of Long COVID symptoms 30-180 days following COVID-19. Notably, this risk increased as HbA1c levels rose. However, this association was not observed in patients with T2D without a history of COVID-19. An NLP-based definition of Long COVID identified more patients than diagnosis codes and should be considered in future studies.

Exploring the mechanism of comorbidity in patients with T1DM and COVID-19: Integrating bioinformatics and Mendelian randomization methods

During the coronavirus disease 2019 (COVID-19) pandemic, the incidence of type 1 diabetes mellitus (T1DM) has increased. Additionally, evidence suggests that individuals with diabetes mellitus may have increased susceptibility to severe acute respiratory syndrome coronavirus 2 infection. However, the specific causal relationships and interaction mechanisms between T1DM and COVID-19 remain unclear. This study aims to investigate the causal relationship between T1DM and COVID-19, utilizing differential gene expression and Mendelian randomization analyses. Differentially expressed gene sets from datasets GSE156035 and GSE171110 were intersected to identify shared genes, analyzed for functional enrichment. Mendelian randomization models were employed to assess causal effects, revealing no direct causal link between T1DM and COVID-19 in the European population (P > .05). Notably, DNA replication and sister chromatid cohesion 1 (DSCC1) showed negative causal associations with both diseases (T1DM: OR = 0.943, 95% CI: 0.898-0.991, P = .020; COVID-19: OR = 0.919, 95% CI: 0.882-0.958, P < .001), suggesting a protective effect against their comorbidity. This genetic evidence highlights DSCC1 as a potential target for monitoring and managing the co-occurrence of T1DM and COVID-19.

SARS-CoV-2 Infection Positively Correlates with Hyperglycemia and Inflammatory Markers in COVID-19 Patients: A Clinical Research Study

Diabetes mellitus (DM) is a common comorbidity in COVID-19 subjects. Hyperglycemia at hospital admission identified as a major risk factor and is responsible for poor prognosis. Hematological and inflammatory parameters have been recognized as predictive markers of severity in COVID-19. In this clinical study, we aimed to assess the impact of hyperglycemia at hospital admission on hematological and several inflammatory parameters in COVID-19 patients. A total of 550 COVID-19 subjects were primarily categorized into two major groups (normoglycemic and hyperglycemic) based on random blood sugar levels. On the first day of hospitalization, subjects' oxygen saturation, random blood sugar, hematological variables, and inflammatory parameters were recorded. The hyperglycemic group exhibited higher levels of serum ferritin, total leukocyte count (TLC), lactate dehydrogenase (LDH), neutrophil count, and neutrophil-to-lymphocyte ratio (NLR). In contrast, oxygen saturation and lymphocyte count were lower compared to the normoglycemic group. Significantly elevated levels of hematological variables (TLC, neutrophil count, NLR) and inflammatory parameters (serum ferritin) were observed in the hyperglycemic group. Among inflammatory parameters, only serum ferritin levels showed statistical significance. This study supports the clinical association between hyperglycemia and an increased severity of COVID-19. Consequently, the identification of these parameters is a crucial and valuable prognostic indicator for assessing disease severity in hyperglycemic subjects.

Research Progress on the Weak Immune Response to the COVID-19 Vaccine in Patients with Type 2 Diabetes

Coronavirus Disease 2019 (COVID-19) is generally susceptible to the population, highly infectious, rapidly transmitted, and highly fatal. There is a lack of specific drugs against the virus at present and vaccination is the most effective strategy to prevent infection. However, studies have found that some groups, particularly patients with diabetes, show varying degrees of weak immune reactivity to various COVID-19 vaccines, resulting in poor preventive efficacy against the novel coronavirus in patients with diabetes. Therefore, in this study, patients with type 2 diabetes mellitus (T2DM) who had weak immune response to the COVID-19 vaccine in recent years were analyzed. This article reviews the phenomenon, preliminary mechanism, and related factors affecting weak vaccine response in patients with T2DM, which is expected to help in the development of new vaccines for high-risk groups for COVID-19.

Association between COVID-19 and incidence of cardiovascular disease and all-cause mortality among patients with diabetes

Introduction

Although the risk of coronavirus disease 2019 (COVID-19) infection is higher in patients who are diagnosed with diabetes than in those who are not, research on the risk of cardiovascular disease (CVD) in COVID-19 infected patients diagnosed with diabetes compared to those who are not infected by COVID-19 is lacking. This study aimed to examine the association between COVID-19, incidence of CVD, and all-cause mortality in patients with diabetes.

Methods

This study used data from the Health Insurance Review and Assessment, and included 16,779 patients with COVID-19 and 16,779 matched controls between January 2017 and June 2021. The outcomes included cardiovascular disease (CVD), coronary heart disease, stroke, and all-cause mortality. Cox proportional hazards regression models were used to evaluate these associations.

Results

Patients with diabetes hospitalized because of COVID-19 had a significantly increased risk of CVD (adjusted hazard ratio [AHR], 2.12; 95% confidence interval [CI]: 1.97, 2.27) than those without COVID-19. The risks of coronary heart disease (AHR, 2.00; 95% CI: 1.85, 2.17) and stroke (AHR, 2.21; 95% CI: 1.90, 2.57) were higher in the intervention group than in the control group. In the case of all-cause mortality for middle-aged adults, we observed a higher risk in diabetes patients hospitalized due to COVID-19 than in patients without COVID-19 (AHR, 1.37; 95% CI: 1.18, 1.59).

Conclusions

This study showed that patients with diabetes hospitalized due to COVID-19 had an increased risk of CVD, coronary heart disease, stroke incidence, and mortality than those who were not COVID-19 infected, suggesting more careful prevention and management among patients with COVID-19.