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1.
Front Cell Infect Microbiol ; 12: 868414, 2022.
Article in English | MEDLINE | ID: covidwho-1779936

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an enormous burden on the healthcare system worldwide as a consequence of its new emerging variants of concern (VOCs) since late 2019. Elucidating viral genome characteristics and its influence on disease severity and clinical outcome has been one of the crucial aspects toward pandemic management. Genomic surveillance holds the key to identify the spectrum of mutations vis-à-vis disease outcome. Here, in our study, we performed a comprehensive analysis of the mutation distribution among the coronavirus disease 2019 (COVID-19) recovered and mortality patients. In addition to the clinical data analysis, the significant mutations within the two groups were analyzed for their global presence in an effort to understand the temporal dynamics of the mutations globally in comparison with our cohort. Interestingly, we found that all the mutations within the recovered patients showed significantly low global presence, indicating the possibility of regional pool of mutations and the absence of preferential selection by the virus during the course of the pandemic. In addition, we found the mutation S194L to have the most significant occurrence in the mortality group, suggesting its role toward a severe disease progression. Also, we discovered three mutations within the mortality patients with a high cohort and global distribution, which later became a part of variants of interest (VOIs)/VOCs, suggesting its significant role in enhancing viral characteristics. To understand the possible mechanism, we performed molecular dynamics (MD) simulations of nucleocapsid mutations, S194L and S194*, from the mortality and recovered patients, respectively, to examine its impacts on protein structure and stability. Importantly, we observed the mutation S194* within the recovered to be comparatively unstable, hence showing a low global frequency, as we observed. Thus, our study provides integrative insights about the clinical features, mutations significantly associated with the two different clinical outcomes, its global presence, and its possible effects at the structural level to understand the role of mutations in driving the COVID-19 pandemic.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/genetics , Genome, Viral , Humans , Mutation , Pandemics , Phylogeny , SARS-CoV-2/genetics
2.
Front Microbiol ; 13: 763169, 2022.
Article in English | MEDLINE | ID: covidwho-1753386

ABSTRACT

Vaccine development against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been of primary importance to contain the ongoing global pandemic. However, studies have demonstrated that vaccine effectiveness is reduced and the immune response is evaded by variants of concern (VOCs), which include Alpha, Beta, Delta, and, the most recent, Omicron. Subsequently, several vaccine breakthrough (VBT) infections have been reported among healthcare workers (HCWs) due to their prolonged exposure to viruses at healthcare facilities. We conducted a clinico-genomic study of ChAdOx1 (Covishield) VBT cases in HCWs after complete vaccination. Based on the clinical data analysis, most of the cases were categorized as mild, with minimal healthcare support requirements. These patients were divided into two sub-phenotypes based on symptoms: mild and mild plus. Statistical analysis showed a significant correlation of specific clinical parameters with VBT sub-phenotypes. Viral genomic sequence analysis of VBT cases revealed a spectrum of high- and low-frequency mutations. More in-depth analysis revealed the presence of low-frequency mutations within the functionally important regions of SARS-CoV-2 genomes. Emphasizing the potential benefits of surveillance, low-frequency mutations, D144H in the N gene and D138Y in the S gene, were observed to potentially alter the protein secondary structure with possible influence on viral characteristics. Substantiated by the literature, our study highlights the importance of integrative analysis of pathogen genomic and clinical data to offer insights into low-frequency mutations that could be a modulator of VBT infections.

3.
PLoS One ; 17(3): e0264785, 2022.
Article in English | MEDLINE | ID: covidwho-1745317

ABSTRACT

The variability of clinical course and prognosis of COVID-19 highlights the necessity of patient sub-group risk stratification based on clinical data. In this study, clinical data from a cohort of Indian COVID-19 hospitalized patients is used to develop risk stratification and mortality prediction models. We analyzed a set of 70 clinical parameters including physiological and hematological for developing machine learning models to identify biomarkers. We also compared the Indian and Wuhan cohort, and analyzed the role of steroids. A bootstrap averaged ensemble of Bayesian networks was also learned to construct an explainable model for discovering actionable influences on mortality and days to outcome. We discovered blood parameters, diabetes, co-morbidity and SpO2 levels as important risk stratification features, whereas mortality prediction is dependent only on blood parameters. XGboost and logistic regression model yielded the best performance on risk stratification and mortality prediction, respectively (AUC score 0.83, AUC score 0.92). Blood coagulation parameters (ferritin, D-Dimer and INR), immune and inflammation parameters IL6, LDH and Neutrophil (%) are common features for both risk and mortality prediction. Compared with Wuhan patients, Indian patients with extreme blood parameters indicated higher survival rate. Analyses of medications suggest that a higher proportion of survivors and mild patients who were administered steroids had extreme neutrophil and lymphocyte percentages. The ensemble averaged Bayesian network structure revealed serum ferritin to be the most important predictor for mortality and Vitamin D to influence severity independent of days to outcome. The findings are important for effective triage during strains on healthcare infrastructure.


Subject(s)
COVID-19/mortality , Hospitalization/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Bayes Theorem , COVID-19/epidemiology , COVID-19/etiology , Child , China/epidemiology , Female , Humans , India/epidemiology , Machine Learning , Male , Middle Aged , Models, Statistical , Risk Assessment/methods , Risk Factors , Young Adult
4.
Front Genet ; 12: 753648, 2021.
Article in English | MEDLINE | ID: covidwho-1605591

ABSTRACT

Globally, SARS-CoV-2 has moved from one tide to another with ebbs in between. Genomic surveillance has greatly aided the detection and tracking of the virus and the identification of the variants of concern (VOC). The knowledge and understanding from genomic surveillance is important for a populous country like India for public health and healthcare officials for advance planning. An integrative analysis of the publicly available datasets in GISAID from India reveals the differential distribution of clades, lineages, gender, and age over a year (Apr 2020-Mar 2021). The significant insights include the early evidence towards B.1.617 and B.1.1.7 lineages in the specific states of India. Pan-India longitudinal data highlighted that B.1.36* was the predominant clade in India until January-February 2021 after which it has gradually been replaced by the B.1.617.1 lineage, from December 2020 onward. Regional analysis of the spread of SARS-CoV-2 indicated that B.1.617.3 was first seen in India in the month of October in the state of Maharashtra, while the now most prevalent strain B.1.617.2 was first seen in Bihar and subsequently spread to the states of Maharashtra, Gujarat, and West Bengal. To enable a real time understanding of the transmission and evolution of the SARS-CoV-2 genomes, we built a transmission map available on https://covid19-indiana.soic.iupui.edu/India/EmergingLineages/April2020/to/March2021. Based on our analysis, the rate estimate for divergence in our dataset was 9.48 e-4 substitutions per site/year for SARS-CoV-2. This would enable pandemic preparedness with the addition of future sequencing data from India available in the public repositories for tracking and monitoring the VOCs and variants of interest (VOI). This would help aid decision making from the public health perspective.

5.
Vaccines (Basel) ; 10(1)2021 Dec 31.
Article in English | MEDLINE | ID: covidwho-1580341

ABSTRACT

This study elucidated the clinical, humoral immune response and genomic analysis of vaccine breakthrough (VBT) infections after ChAdOx1 nCoV-19/Covishield vaccine in healthcare workers (HCWs). Amongst 1858 HCWs, 1639 had received either two doses (1346) or a single dose (293) of ChAdOx1 nCoV-19 vaccine. SARS-CoV-2 IgG antibodies and neutralizing antibodies were measured in the vaccinated group and the development of SARS-CoV-2 infection was monitored.Forty-six RT-PCR positive samples from the 203 positive samples were subjected to whole genome sequencing (WGS). Of the 203 (10.92%) infected HCWs, 21.46% (47/219) were non-vaccinated, which was significantly more than 9.52% (156/1639) who were vaccinated and infection was higher in doctors and nurses. Unvaccinated HCWs had 1.57 times higher risk compared to partially vaccinated HCWs and 2.49 times higher risk than those who were fully vaccinated.The partially vaccinated were at higher risk than the fully vaccinated (RR 1.58). Antibody non-response was seen in 3.44% (4/116), low antibody levels in 15.51% (18/116) and medium levels were found in 81.03% (94/116). Fully vaccinated HCWs had a higher antibody response at day 42 than those who were partially vaccinated (8.96 + 4.00 vs. 7.17 + 3.82). Whole genome sequencing of 46 samples revealed that the Delta variant (B.1.617.2) was predominant (69.5%). HCWs who had received two doses of vaccine showed better protection from mild, moderate, or severe infection, with a higher humoral immune response than those who had received a single dose. The genomic analysis revealed the predominance of the Delta variant (B.1.617.2) in the VBT infections.

6.
Science ; 374(6570): 995-999, 2021 Nov 19.
Article in English | MEDLINE | ID: covidwho-1526449

ABSTRACT

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Genome, Viral , Adolescent , Adult , COVID-19/immunology , COVID-19/transmission , Child , Humans , Immune Evasion , India/epidemiology , Molecular Epidemiology , Phylogeny , Reinfection , Seroepidemiologic Studies , Young Adult
7.
Front Immunol ; 12: 738093, 2021.
Article in English | MEDLINE | ID: covidwho-1518484

ABSTRACT

Disease caused by SARS-CoV-2 coronavirus (COVID-19) led to significant morbidity and mortality worldwide. A systemic hyper-inflammation characterizes severe COVID-19 disease, often associated with acute respiratory distress syndrome (ARDS). Blood biomarkers capable of risk stratification are of great importance in effective triage and critical care of severe COVID-19 patients. Flow cytometry and next-generation sequencing were done on peripheral blood cells and urokinase-type plasminogen activator receptor (suPAR), and cytokines were measured from and mass spectrometry-based proteomics was done on plasma samples from an Indian cohort of COVID-19 patients. Publicly available single-cell RNA sequencing data were analyzed for validation of primary data. Statistical analyses were performed to validate risk stratification. We report here higher plasma abundance of suPAR, expressed by an abnormally expanded myeloid cell population, in severe COVID-19 patients with ARDS. The plasma suPAR level was found to be linked to a characteristic plasma proteome, associated with coagulation disorders and complement activation. Receiver operator characteristic curve analysis to predict mortality identified a cutoff value of suPAR at 1,996.809 pg/ml (odds ratio: 2.9286, 95% confidence interval 1.0427-8.2257). Lower-than-cutoff suPAR levels were associated with a differential expression of the immune transcriptome as well as favorable clinical outcomes, in terms of both survival benefit (hazard ratio: 0.3615, 95% confidence interval 0.1433-0.912) and faster disease remission in our patient cohort. Thus, we identified suPAR as a key pathogenic circulating molecule linking systemic hyperinflammation to the hypercoagulable state and stratifying clinical outcomes in severe COVID-19 patients with ARDS.


Subject(s)
COVID-19/blood , Receptors, Urokinase Plasminogen Activator/blood , SARS-CoV-2 , Adult , Aged , Blood Coagulation Disorders/blood , Blood Coagulation Disorders/immunology , Blood Proteins/analysis , COVID-19/immunology , Cytokines/blood , Humans , Inflammation/blood , Inflammation/immunology , Middle Aged , Myeloid Cells/immunology , Proteome/analysis , Randomized Controlled Trials as Topic , Respiratory Distress Syndrome/blood , Respiratory Distress Syndrome/immunology , Severity of Illness Index , Young Adult
8.
Front Med (Lausanne) ; 8: 737007, 2021.
Article in English | MEDLINE | ID: covidwho-1399153

ABSTRACT

Background: Post infection immunity and post vaccination immunity both confer protection against COVID-19. However, there have been many whole genome sequencing proven reinfections and breakthrough infections. Both are most often mild and caused by Variants of Concern (VOC). Methods: The patient in our study underwent serial COVID-19 RT-PCR, blood tests for serology, acute phase reactants, and chest imaging as part of clinical care. We interviewed the patient for clinical history and retrieved reports and case papers. We retrieved stored RT-PCR positive samples for whole genome sequencing (WGS) of SARS-CoV-2 from the patient's breakthrough infections and the presumed index case. Findings: The patient had three RT-PCR confirmed SARS-CoV-2 infections. Two breakthrough infections occurred in quick succession with the first over 3 weeks after complete vaccination with COVISHIELD and despite post-vaccination seroconversion. The first breakthrough infection was due to the Alpha variant and the second due to the Delta variant. The Delta variant infection resulted in hypoxia, hospitalization, and illness lasting seven weeks. Serial serology, acute phase reactants, and chest imaging supported WGS in establishing distinct episodes of infection. WGS established a fully vaccinated family member as the index case. Interpretation: The patient had an Alpha variant breakthrough infection despite past infection, complete vaccination, and seroconversion. Despite boosting after this infection, the patient subsequently had a severe Delta variant breakthrough infection. This was also a WGS proven reinfection and, therefore, a case of breakthrough reinfection. The patient acquired the infection from a fully vaccinated family member.

9.
Pathogens ; 10(9)2021 Aug 31.
Article in English | MEDLINE | ID: covidwho-1390714

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) manifests a broad spectrum of clinical presentations, varying in severity from asymptomatic to mortality. As the viral infection spread, it evolved and developed into many variants of concern. Understanding the impact of mutations in the SARS-CoV-2 genome on the clinical phenotype and associated co-morbidities is important for treatment and preventionas the pandemic progresses. Based on the mild, moderate, and severe clinical phenotypes, we analyzed the possible association between both, the clinical sub-phenotypes and genomic mutations with respect to the severity and outcome of the patients. We found a significant association between the requirement of respiratory support and co-morbidities. We also identified six SARS-CoV-2 genome mutations that were significantly correlated with severity and mortality in our cohort. We examined structural alterations at the RNA and protein levels as a result of three of these mutations: A26194T, T28854T, and C25611A, present in the Orf3a and N protein. The RNA secondary structure change due to the above mutations can be one of the modulators of the disease outcome. Our findings highlight the importance of integrative analysis in which clinical and genetic components of the disease are co-analyzed. In combination with genomic surveillance, the clinical outcome-associated mutations could help identify individuals for priority medical support.

10.
Front Microbiol ; 12: 653399, 2021.
Article in English | MEDLINE | ID: covidwho-1389208

ABSTRACT

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

11.
Front Microbiol ; 12: 664386, 2021.
Article in English | MEDLINE | ID: covidwho-1323083

ABSTRACT

Human host and pathogen interaction is dynamic in nature and often modulated by co-pathogens with a functional role in delineating the physiological outcome of infection. Co-infection may present either as a pre-existing pathogen which is accentuated by the introduction of a new pathogen or may appear in the form of new infection acquired secondarily due to a compromised immune system. Using diverse examples of co-infecting pathogens such as Human Immunodeficiency Virus, Mycobacterium tuberculosis and Hepatitis C Virus, we have highlighted the role of co-infections in modulating disease severity and clinical outcome. This interaction happens at multiple hierarchies, which are inclusive of stress and immunological responses and together modulate the disease severity. Already published literature provides much evidence in favor of the occurrence of co-infections during SARS-CoV-2 infection, which eventually impacts the Coronavirus disease-19 outcome. The availability of biological models like 3D organoids, mice, cell lines and mathematical models provide us with an opportunity to understand the role and mechanism of specific co-infections. Exploration of multi-omics-based interactions across co-infecting pathogens may provide deeper insights into their role in disease modulation.

12.
J Prim Care Community Health ; 12: 21501327211000235, 2021.
Article in English | MEDLINE | ID: covidwho-1138512

ABSTRACT

BACKGROUND: To characterize the experience of converting a geriatrics clinic to telehealth visits in early stages of a pandemic. DESIGN: An organizational case study with mixed methods evaluation from the first 8 weeks of converting a geriatrics clinic from in-person visits to video and telephone visits. SETTING: Veteran's Health Administration in Northern California Participants Community-dwelling older Veterans receiving care at VA Palo Alto Geriatrics clinic. Veterans had a mean age of 85.7 (SD = 6.8) and 72.1% had cognitive impairment. INTERVENTION: Veterans with face-to-face appointments were converted to video or telephone visits to mitigate exposure to community spread of COVID-19. MEASUREMENTS: Thirty-two patient evaluations and 80 clinician feedback evaluations were completed. This provided information on satisfaction, care access during pandemic, and travel and time savings. RESULTS: Of the 62 scheduled appointments, 43 virtual visits (69.4%) were conducted. Twenty-six (60.5%) visits were conducted via video, 17 (39.5%) by telephone. Virtual visits saved patients an average of 118.6 minutes each. Patients and providers had similar, positive perceptions about telehealth to in-person visit comparison, limiting exposure, and visit satisfaction. After the telehealth appointment, patients indicated greater comfort with using virtual visits in the future. Thirty-one evaluations included comments for qualitative analysis. We identified 3 main themes of technology set-up and usability, satisfaction with visit, and clinical assessment and communication. CONCLUSION: During a pandemic that has limited the ability to safely conduct inperson services, virtual formats offer a feasible and acceptable alternative for clinically-complex older patients. Despite potential barriers and additional effort required for telehealth visits, patients expressed willingness to utilize this format. Patients and providers reported high satisfaction, particularly with the ability to access care similar to in-person while staying safe. Investing in telehealth services during a pandemic ensures that vulnerable older patients can access care while maintaining social distancing, an important safety measure.


Subject(s)
Ambulatory Care Facilities/organization & administration , COVID-19/prevention & control , Geriatrics/organization & administration , Telemedicine/organization & administration , Veterans Health Services/organization & administration , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , California/epidemiology , Dementia/therapy , Health Services Accessibility , Humans , Middle Aged , Organizational Case Studies , Primary Health Care/organization & administration , Qualitative Research , Telephone , Videoconferencing
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