COVID-19: Diabetes Perspective-Pathophysiology and Management.

Recent evidence relating to the impact of COVID-19 on people with diabetes is limited but continues to emerge. COVID-19 pneumonia is a newly identified illness spreading rapidly throughout the world and causes many disabilities and fatal deaths. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery have become prominent, along with the lingering effects of the virus on those directly infected. Diabetes is a commonly identified risk factor that contributes not only to the severity and mortality of COVID-19 patients, but also to the associated complications, including acute respiratory distress syndrome (ARDS) and multi-organ failure. Diabetic patients are highly affected due to increased viral entry into the cells and decreased immunity. Several hypotheses to explain the increased incidence and severity of COVID-19 infection in people with diabetes have been proposed and explained in detail recently. On the other hand, 20-50% of COVID-19 patients reported new-onset hyperglycemia without diabetes and new-onset diabetes, suggesting the two-way interactions between COVID-19 and diabetes. A systematic review is required to confirm diabetes as a complication in those patients diagnosed with COVID-19. Diabetes and diabetes-related complications in COVID-19 patients are primarily due to the acute illness caused during the SARS-CoV-2 infection followed by the release of glucocorticoids, catecholamines, and pro-inflammatory cytokines, which have been shown to drive hyperglycemia positively. This review provides brief insights into the potential mechanisms linking COVID-19 and diabetes, and presents clinical management recommendations for better handling of the disease.

Variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Vaccine Effectiveness.

The incidence and death toll due to SARS-CoV-2 infection varied time-to-time; and depended on several factors, including severity (viral load), immune status, age, gender, vaccination status, and presence of comorbidities. The RNA genome of SARS-CoV-2 has mutated and produced several variants, which were classified by the SARS-CoV-2 Interagency Group (SIG) into four major categories. The first category; "Variant Being Monitored (VBM)", consists of Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), Epsilon (B.1.427, B.1.429), Eta (B.1.525), Iota (B.1.526), Kappa (B.1.617.1), Mu (B.1.621), and Zeta (P.2); the second category; "Variants of Concern" consists of Omicron (B.1.1.529). The third and fourth categories include "Variants of Interest (VOI)", and "Variants of High Consequence (VOHC)", respectively, and contain no variants classified currently under these categories. The surge in VBM and VOC poses a significant threat to public health globally as they exhibit altered virulence, transmissibility, diagnostic or therapeutic escape, and the ability to evade the host immune response. Studies have shown that certain mutations increase the infectivity and pathogenicity of the virus as demonstrated in the case of SARS-CoV-2, the Omicron variant. It is reported that the Omicron variant has >60 mutations with at least 30 mutations in the Spike protein ("S" protein) and 15 mutations in the receptor-binding domain (RBD), resulting in rapid attachment to target cells and immune evasion. The spread of VBM and VOCs has affected the actual protective efficacy of the first-generation vaccines (ChAdOx1, Ad26.COV2.S, NVX-CoV2373, BNT162b2). Currently, the data on the effectiveness of existing vaccines against newer variants of SARS-CoV-2 are very scanty; hence additional studies are immediately warranted. To this end, recent studies have initiated investigations to elucidate the structural features of crucial proteins of SARS-CoV-2 variants and their involvement in pathogenesis. In addition, intense research is in progress to develop better preventive and therapeutic strategies to halt the spread of COVID-19 caused by variants. This review summarizes the structure and life cycle of SARS-CoV-2, provides background information on several variants of SARS-CoV-2 and mutations associated with these variants, and reviews recent studies on the safety and efficacy of major vaccines/vaccine candidates approved against SARS-CoV-2, and its variants.

An Update on Complications Associated with SARS-CoV-2 Infection and COVID-19 Vaccination.

Over the past two years, SARS-CoV-2 has dramatically spread worldwide and emerged as a major pandemic which has left an unprecedented mark on healthcare systems and economies worldwide. As our understanding of the virus and its epidemiology continues to grow, the acute phase clinical symptoms and long-term and vaccine-related complications are becoming more apparent. With heterogeneity in presentations, comparisons may be drawn between COVID-19-related sequelae and vaccination related adverse events. The present review article aims to address the currently available literature on the SARS-CoV-2 virus, immune responses, the pathophysiology of clinical presentations, and available vaccinations with its adverse events for the appraisal of its potential impact on the COVID-19 management system.

Assessment of Clinical Profile and Treatment Outcome in Vaccinated and Unvaccinated SARS-CoV-2 Infected Patients.

Vaccines against severe acute respiratory syndrome-corona virus-2 (SARS-CoV-2) infection, which causes coronavirus disease-19 (COVID-19) in humans, have been developed and are being tested for safety and efficacy. We conducted the cross-sectional prospective cohort study on 820 patients who were positive for SARS-CoV-2 and were admitted to Princess Krishnajammanni trauma care centre (PKTCC), Mysore, which was converted to a designated COVID hospital between April 2021 to July 2021. After obtaining the informed consent, RT-PCR report, vaccination certificate and patient history, patients were classified according to their vaccination status. Results from the study showed decreases in serum ferritin levels, clinical symptoms, improvement in oxygen saturation, early recovery in patients having diabetes and hypertension, and a substantial reduction in the overall duration of hospital stay in vaccinated patients compared to unvaccinated patients. Further, fully vaccinated patients showed better outcomes compared to single dose vaccinated and nonvaccinated patients. Taken together, our findings reaffirm the vaccine's effectiveness in reducing case fatality and promoting faster recovery compared to nonvaccinated patients. Efforts to increase the number of immunized subjects in the community help to achieve herd immunity and offer protection against the severity of COVID-19 and associated complications while minimizing the public health and economic burden.

Success of Current COVID-19 Vaccine Strategies vs. the Epitope Topology of SARS-CoV-2 Spike Protein-Receptor Binding Domain (RBD): A Computational Study of RBD Topology to Guide Future Vaccine Design.

Coronavirus disease-2019 (COVID-19) is a pandemic with a high morbidity rate occurring over recent years. COVID-19 is caused by the severe acute respiratory syndrome causing coronavirus type-2 (SARS-CoV-2). COVID-19 not only challenged mankind but also gave scope to the evolution of various vaccine design technologies. Although these vaccines protected and saved many lives, with the emerging viral strains, some of the strains may pose a threat to the currently existing vaccine design that is primarily based on the wild type spike protein of SARS-CoV-2. To evaluate the risk involved from such mutant viral strains, we performed a systematic in silico amino acid substitution of critical residues in the receptor binding domain (RBD) of the spike protein. Our molecular modeling analysis revealed significant topological changes in the RBD of spike protein suggesting that they could potentially contribute to the loss of antigen specificity for the currently existing therapeutic antibodies/vaccines, thus posing a challenge to the current vaccine strategies that are based on wild type viral spike protein epitopes. The structural deviations discussed in this article should be considered carefully in the future vaccine design.

A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys.

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).