Flow cytometry profiling of cellular immune response in COVID-19 infected, recovered and vaccinated individuals.

INTRODUCTION: SARS-CoV-2 has infected over 753 million individuals and caused more than 6.8 million deaths globally to date. COVID-19 disease severity has been associated with SARS-CoV-2 induced hyper inflammation and the immune correlation with its pathogenesis remains unclear. Acute viral infection is characterised by vigorous coordinated innate and adaptive activation, including an early cellular response that correlates well with the amplitude of virus specific humoral response. OBJECTIVE: The present study covers a wide spectrum of cellular immune response against COVID-19, irrespective of infection and vaccination. METHODS: We analysed immune status of (a) COVID-19 hospitalised patients including deceased and recovered patients, and compared with home isolated and non-infected healthy individuals, and (b) infected home isolated individuals with vaccinated individuals, using flow cytometry. We performed flow cytometry analysis of PBMCs to determine non-specific cell-mediated immune response. RESULTS: The immune response revealed extensive induction and activation of multiple immune lineages, including T and B cells, Th17 regulatory subsets and M1, M2 macrophages in deceased and hospitalised recovered patients, vaccinated and healthy individuals. Compromised immune cell expression was observed in deceased patients even in later stages, while expression was restored in hospitalised recovered patients and home isolated individuals. CONCLUSION: The findings associated with recovery and convalescence define a new signature of cellular immune response that persists in individuals with SARS-CoV-2 infection and vaccination. The findings will help in providing a better understanding of COVID-19 disease and will aid in developing better therapeutic strategies for treatment.

"Mitochondrial pathogenic mutations and metabolic alterations associated with COVID-19 disease severity".

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) caused global pandemic and drastically affected the humankind. Mitochondrial mutations have been found to be associated with several respiratory diseases. Missense mutation and pathogenic mitochondrial variants might unveil the potential involvement of the mitochondrial genome in coronavirus disease 2019 (COVID-19) pathogenesis. The present study aims to elucidate the role of mitochondrial DNA (mtDNA) mutations, mitochondrial haplogroup, and energy metabolism in disease severity. The study was performed on 58 subjects comprising COVID-19-positive (n = 42) and negative (n = 16) individuals. COVID-19-positive subjects were further categorized into severe deceased (SD), severe recovered (SR), moderate (Mo), and mild (Mi) patients, while COVID-19-negative subjects were healthy control (HC) for the study. High throughput next-generation sequencing was done to investigate mtDNA mutations and haplogroups. The computational approach was applied to study the effect of mtDNA mutations on protein secondary structure. Real time polymerase chain reaction was used for mtDNA copy number determination and mitochondrial function parameters were also analyzed. We found 15 mtDNA mutations in MT-ND5, MT-ND4, MT-ND2, and MT-COI genes uniquely associated with COVID-19 severity affecting the secondary structure of proteins in COVID-19-positive subjects. Haplogroup analysis suggests that mtDNA haplogroups M3d1a and W3a1b might be potentially associated with COVID-19 pathophysiology. The mitochondrial function parameters were significantly altered in severe patients (SD and SR; p < 0.05). No significant relationship was found between mtDNA mutations and oxidative stress markers (p > 0.05). The study highlights the importance of mitochondrial reprogramming in COVID-19 patients and may provide a feasible approach toward finding a path for therapeutic interventions to COVID-19 disease.

Evaluation of altered miRNA expression pattern to predict COVID-19 severity.

Outbreak of COVID-19 pandemic in December 2019 affected millions of people globally. After substantial research, several biomarkers for COVID-19 have been validated however no specific and reliable biomarker for the prognosis of patients with COVID-19 infection exists. Present study was designed to identify specific biomarkers to predict COVID-19 severity and tool for formulating treatment. A small cohort of subjects (n = 43) were enrolled and categorized in four study groups; Dead (n = 16), Severe (n = 10) and Moderate (n = 7) patients and healthy controls (n = 10). Small RNA sequencing was done on Illumina platform after isolation of microRNA from peripheral blood. Differential expression (DE) of miRNA (patients groups compared to control) revealed 118 down-regulated and 103 up-regulated known miRNAs with fold change (FC) expression ≥2 folds and p ≤ 0.05. DE miRNAs were then subjected to functional enrichment and network analysis. Bioinformatic analysis resulted in 31 miRNAs (24 Down-regulated; 7 up-regulated) significantly associated with COVID-19 having AUC>0.8 obtained from ROC curve. Seventeen out of 31 DE miRNAs have been linked to COVID-19 in previous studies. Three miRNAs, hsa-miR-147b-5p and hsa-miR-107 (down-regulated) and hsa-miR-1299 (up-regulated) showed significant unique DE in Dead patients. Another set of 4 miRNAs, hsa-miR-224-5p (down-regulated) and hsa-miR-4659b-3p, hsa-miR-495-3p and hsa-miR-335-3p were differentially up-regulated uniquely in Severe patients. Members of three miRNA families, hsa-miR-20, hsa-miR-32 and hsa-miR-548 were significantly down-regulated in all patients group in comparison to healthy controls. Thus a distinct miRNA expression profile was observed in Dead, Severe and Moderate COVID-19 patients. Present study suggests a panel of miRNAs which identified in COVID-19 patients and could be utilized as potential diagnostic biomarkers for predicting COVID-19 severity.

Gene variants in pro-coagulant and anti-coagulant genes could be prognostic genetic markers of COVID-19 susceptibility.

Background: Present study aimed to identify DNA polymorphisms (variants) which can modulate the risk of COVID-19 infection progression to severe condition. TaqMan based SNP genotyping assay was performed for 11 single nucleotide polymorphisms (SNPs) in pro-coagulant and anti-coagulant genes. Methodology: A total of 33 COVID-19 patients, including dead, severe and moderately infected individuals were compared to 35 healthy controls. Both alleles in the SNP were labelled with two different fluorescent dyes (FAM and VIC) during assay formulation. DNA of study subjects were mixed with SNP assay and TaqMan master mix on 96 well PCR plate according to manufacturer's protocol and RT-PCR was performed. Allelic discrimination assay gave clear results for presence of specific allele in each sample. Three SNPs were located in the pro-coagulant genes, another three involved in blood clot dissolution while rest five were in the genes encoding natural anti-coagulants. COVID-19 infected patients were further sub-divided into three groups, deceased (n = 16), severe (n = 10) and moderately infected (n = 7). Results: SNP genotyping showed significant differences between COVID-19 patients and controls in two SNPs, rs6133 in Selectin-P (SELP) and rs5361 in Selectin-E (SELE) gene. Also, rs2020921 and rs8176592, in clot dissolution genes, tissue Plasminogen activator (tPA) and tissue factor pathway inhibitor (TFPI) respectively showed significant genotypic and allelic difference in patients of COVID-19 compared to healthy controls. Further three SNPs rs2227589, rs757583846, and rs121918476 in natural anti-coagulant genes anti-thrombin III (ATIII), protein C (PROC), and protein S (PROS) respectively showed statistically significant difference between the study groups. Conclusion: Our findings indicate that gene variants, those involved in coagulation and anti-coagulation may play a major role in determining individual susceptibility to COVID-19.

Epidemiological trend and clinical profile of COVID-19 patients: Experience from a designated COVID-19 center in Delhi.

Objective: To study the epidemiological characteristics of the pandemic by describing the clinical profile of the COVID-19 patients presenting to a super specialty hospital. Methods: This was a descriptive study using medical records of patients who tested positive for SARS-CoV-2 RNA using reverse transcription-polymerase chain reaction between 17th March and 15th January 2021 while maintaining confidentiality. The clinical and demographic data of all the patients were entered in a Microsoft Excel and statistical analysis was done using SPSS 21 software. Regression analysis was performed and a P value < 0.05 was considered to be statistically significant. Results: A total of 3534 patients were enrolled in this study aged 9-96 years. Among patients with symptoms, fever and cough were the most common presenting symptoms, while 5.6% of the patients were asymptomatic. Hypertension was the most common comorbidity (37%), while no comorbidities were present in 43.0% of the participants and this was statistically significant for age (P = 0.000). Among patient outcomes, >50% of patients were in home isolation, while 11% of patients had a fatal outcome. Elder age group had a higher proportion of expiry among outcomes (P <= 0.001). Most patients had a hospital stay of 9-11 days. A total of 63 health workers were included with male: female ratio being 3.5:1. Conclusion: Our study reflects that majority of the positive cases that presented to the hospital had mild/moderate symptoms. We believe that appropriate triaging of patients followed by early institution of medicine and good critical care services may help to control this epidemic.

Implications of COVID-19 on Thrombotic Profile of Severely Affected Patients.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is a novel viral disease that spread as a global pandemic in 2020 by infecting millions of people across the world. Its clinical prognosis is dependent on various coagulatory parameters since thrombotic events are frequently associated with infection severity. METHODS: A total of 383 COVID-19 patients enrolled in Rajiv Gandhi Super Specialty Hospital, Delhi, India, were included in the present retrospective study. Patients were divided into three categories, severe (n = 141), moderate (n = 138), and mild (n = 104) based on infection severity. Various thrombotic parameters and anticoagulant levels were measured in 70 patients and further analyzed. RESULTS: Coagulopathy is seen in COVID-19 patients (n = 70) with a significant increase in fibrinogen, D-dimer levels, and prothrombin time in patients with severe and moderate disease compared to patients with a mild infection. Approximately, 70% of patients with severe and moderate disease demonstrated fibrinogen levels higher than the standard reference range. 60.41% of patients with severe disease showed significantly higher D-dimer levels. Thrombotic parameters were notably elevated in the nonsurvivors group compared to COVID-19 survivors. Nearly, 91% of patients with severe infection had anticoagulant protein S levels below the reference range. CONCLUSION: COVID-19 infection severely impacts the blood coagulation cascade, which might lead to the manifestation of severe symptoms and increased mortality in patients.

Evaluation of SARS-CoV-2 antibody responses in healthcare workers at a tertiary care COVID 19 dedicated hospital in Delhi.

PURPOSE: Amidst the on-going SARS-CoV-2 pandemic, healthcare workers have been at a greater risk of disease exposure as they are working in environments chiefly involved in the COVID-19 patient care since March 2020. SARS-CoV-2 antibody testing can prove to be a valuable tool for better understanding of prevalence of disease exposure in this population. Therefore, we conducted this study to grasp the sero-prevalence of COVID-19 antibodies in our hospital to better comprehend the duration of IgG response. METHODS: This was a longitudinal study involving 305 healthcare workers at Rajiv Gandhi Super Speciality Hospital spanning over a period of four months starting from October 2020 to January 2021. Serum samples were obtained from the study group taken as Day 0 of the study and were screened for the presence of SARS-CoV-2 IgG antibodies using semi-quantitive enzyme linked immunoassay technology from ERBAlisa (India). The Antibody Index was determined. Those showing reactive in the screening test were further followed up on a monthly basis till January 2021 for serial antibody testing. RESULTS: The overall seroprevalence for IgG response among the workers was found to be 21.96%. Seropositivity rate was observed to be significantly higher in those having a history of RT-PCR confirmed COVID-19 infection (45.09%) CONCLUSIONS: Our study demonstrated that healthcare workers have a higher sero-prevalence. Our study also demonstrated that the antibodies developed following COVID-19 infection had a waning effect of protective response following infection.

Potential association of COVID-19 and ABO blood group: An Indian study.

Coronavirus disease 2019 (COVID-19) transmits from person to person mainly through respiratory droplets and coughing. Infection severity ranges from asymptomatic and mild infection to those with moderate and severe symptoms which may lead to multiple organ failure and mortality. Infection severity largely depends on individual's immune response, age and co-morbidities. Present study categorized COVID-19 infected patients based on their infection severity and linked COVID-19 severity with age, gender and ABO blood group types. Clinical details of 383 COVID-19 patients were collected from Rajiv Gandhi Super Specialty hospital (RGSSH), India; divided into three groups; mild, moderate and severe patients, based on their symptoms. Present analysis revealed that age plays major role in infection severity, as the symptoms are more severe in patients above 45 years. Infection rate was higher in males compared to females. Most patients with A(+ve) and B(+ve) blood group were severely affected compared to those of blood group type O(+ve) and AB(+ve). O(+ve) blood group was least represented in severe patients. Present findings could be helpful in generating awareness amongst the population regarding susceptibility towards the COVID-19 infection. This supportive information would help clinicians and health workers to propose new strategies and tactical solution against COVID-19 infection.

Trends and clinico-epidemiological profile of COVID-19 patients at a designated COVID-19 hospital in Delhi, North India.

BACKGROUND: The coronavirus disease (COVID-19) presents across a spectrum of signs and symptoms and shows clinico-epidemiological predilections (elderly, those with comorbidities). Delhi is among the highest burden states in India. OBJECTIVES: To report the case detection trends and clinico-epidemiological profile of patients tested positive at a designated COVID-19 hospital in Delhi in Northern India. METHODS: Using an observational (descriptive design) we analyzed data from the electronic medical records of the hospital. All individuals testing positive for SARS-CoV-2 RNA using reverse transcription polymerase chain reaction (RT-PCR) between 17th March and 07th May 2020 (both dates inclusive) were included. Case detection trend (7-day moving averages) was plotted. Clinico-epidemiological profile of patients was summarized statistically. RESULTS: Total 308 positive cases were enrolled in this study. The median age of participants was 48 years (09-95 years) men (47.9 ± 16.4 years) and women (43.5 ± 14.0 years). Men to women ratio was 3.4:1 with a statistically significant difference (P < 0.001). During the study timeframe, 166 (54.0%) patients had an outcome: 11 (6.6%; 95% CI: 3.4-11.6) expired and 155 recovered (recovery rate: 93.4%; 95% CI: 88.5-96.7). Chance of death was significantly associated with the higher age group (P = 0.005). The commonest clinical symptoms noted were fever (38.9%) and cough (38.6%). Majority (56.6%) had mild to moderate symptoms, 12.6% had severe symptoms and the remaining were asymptomatic (30.8%). 31 patients (26.05%) needed ICU care. Total 119 patients (38.6%) had various preexisting comorbidities, most commonly diabetes mellitus (35.0%) and hypertension (34.0%). However, the comorbidities were not associated with age (P = 1.000). CONCLUSION: Triangulation of data and careful analysis of trends in designated COVID-19 hospitals and other institutional settings may help inform surge preparedness and care provisioning. Stringent containment strategies must continue as the pandemic is intensifying.