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.
The global epidemic of type 2 diabetes mellitus (T2DM) renders its prevention a major public health priority. A key risk factor of diabetes is obesity and poor diets. Food environments have been ...found to influence people's diets and obesity, positing they may play a role in the prevalence of diabetes. Yet, there is scant evidence on the role they may play in the context of low- and middle-income countries (LMICs). We examined the associations of food environments on T2DM among adults and its heterogeneity by income and sex.
We linked individual health outcome data of 12,167 individuals from a network of health surveillance sites (the South Asia Biobank) to the density and proximity of food outlets geolocated around their homes from environment mapping survey data collected between 2018 and 2020 in Bangladesh and Sri Lanka. Density was defined as share of food outlets within 300 m from study participant's home, and proximity was defined as having at least 1 outlet within 100 m from home. The outcome variables include fasting blood glucose level, high blood glucose, and self-reported diagnosed diabetes. Control variables included demographics, socioeconomic status (SES), health status, healthcare utilization, and physical activities. Data were analyzed in ArcMap 10.3 and STATA 15.1. A higher share of fast-food restaurants (FFR) was associated with a 9.21 mg/dl blood glucose increase (95% CI: 0.17, 18.24; p < 0.05). Having at least 1 FFR in the proximity was associated with 2.14 mg/dl blood glucose increase (CI: 0.55, 3.72; p < 0.01). A 1% increase in the share of FFR near an individual's home was associated with 8% increase in the probability of being clinically diagnosed as a diabetic (average marginal effects (AMEs): 0.08; CI: 0.02, 0.14; p < 0.05). Having at least 1 FFR near home was associated with 16% (odds ratio OR: 1.16; CI: 1.01, 1.33; p < 0.05) and 19% (OR: 1.19; CI: 1.03, 1.38; p < 0.05) increases in the odds of higher blood glucose levels and diagnosed diabetes, respectively. The positive association between FFR density and blood glucose level was stronger among women than men, but the association between FFR proximity and blood glucose level was stronger among men as well as among those with higher incomes. One of the study's key limitations is that we measured exposure to food environments around residency geolocation; however, participants may source their meals elsewhere.
Our results suggest that the exposure to fast-food outlets may have a detrimental impact on the risk of T2DM, especially among females and higher-income earners. Policies should target changes in the food environments to promote better diets and prevent T2DM.
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.
The modulators of severe COVID-19 have emerged as the most intriguing features of SARS-CoV-2 pathogenesis. This is especially true as we are encountering variants of concern (VOC) with increased ...transmissibility and vaccination breakthroughs. Microbial co-infections are being investigated as one of the crucial factors for exacerbation of disease severity and complications of COVID-19. A key question remains whether early transcriptionally active microbial signature/s in COVID-19 patients can provide a window for future disease severity susceptibility and outcome? Using complementary metagenomics sequencing approaches, respiratory virus oligo panel (RVOP) and Holo-seq, our study highlights the possible functional role of nasopharyngeal early resident transcriptionally active microbes in modulating disease severity, within recovered patients with sub-phenotypes (mild, moderate, severe) and mortality. The integrative analysis combines patients' clinical parameters, SARS-CoV-2 phylogenetic analysis, microbial differential composition, and their functional role. The clinical sub-phenotypes analysis led to the identification of transcriptionally active bacterial species associated with disease severity. We found significant transcript abundance of Achromobacter xylosoxidans and Bacillus cereus in the mortality, Leptotrichia buccalis in the severe, Veillonella parvula in the moderate, and Actinomyces meyeri and
sp. in the mild COVID-19 patients. Additionally, the metabolic pathways, distinguishing the microbial functional signatures between the clinical sub-phenotypes, were also identified. We report a plausible mechanism wherein the increased transcriptionally active bacterial isolates might contribute to enhanced inflammatory response and co-infections that could modulate the disease severity in these groups. Current study provides an opportunity for potentially using these bacterial species for screening and identifying COVID-19 patient sub-groups with severe disease outcome and priority medical care.
COVID-19 is invariably a disease of diverse clinical manifestation, with multiple facets involved in modulating the progression and outcome. In this regard, we investigated the role of transcriptionally active microbial co-infections as possible modulators of disease pathology in hospital admitted SARS-CoV-2 infected patients. Specifically, can there be early nasopharyngeal microbial signatures indicative of prospective disease severity? Based on disease severity symptoms, the patients were segregated into clinical sub-phenotypes: mild, moderate, severe (recovered), and mortality. We identified significant presence of transcriptionally active isolates, Achromobacter xylosoxidans and Bacillus cereus in the mortality patients. Importantly, the bacterial species might contribute toward enhancing the inflammatory responses as well as reported to be resistant to common antibiotic therapy, which together hold potential to alter the disease severity and outcome.
Saturation suppressor mutagenesis was used to generate thermostable mutants of the SARS-CoV-2 spike receptor-binding domain (RBD). A triple mutant with an increase in thermal melting temperature of ...~7°C with respect to the wild-type B.1 RBD and was expressed in high yield in both mammalian cells and the microbial host,
, was downselected for immunogenicity studies. An additional derivative with three additional mutations from the B.1.351 (beta) isolate was also introduced into this background. Lyophilized proteins were resistant to high-temperature exposure and could be stored for over a month at 37°C. In mice and hamsters, squalene-in-water emulsion (SWE) adjuvanted formulations of the B.1-stabilized RBD were considerably more immunogenic than RBD lacking the stabilizing mutations and elicited antibodies that neutralized all four current variants of concern with similar neutralization titers. However, sera from mice immunized with the stabilized B.1.351 derivative showed significantly decreased neutralization titers exclusively against the B.1.617.2 (delta) VOC. A cocktail comprising stabilized B.1 and B.1.351 RBDs elicited antibodies with qualitatively improved neutralization titers and breadth relative to those immunized solely with either immunogen. Immunized hamsters were protected from high-dose viral challenge. Such vaccine formulations can be rapidly and cheaply produced, lack extraneous tags or additional components, and can be stored at room temperature. They are a useful modality to combat COVID-19, especially in remote and low-resource settings.
SEE PDF The patient demographics and clinical data are summarised in File S1: Table S1, wherein, the median Ct value of E/RdRp gene was significantly different between recovered/mortality and RS/SOB ...patients, respectively (Figure 1B,C). Integration of lncRNA–miRNA–mRNA regulatory potential revealed that by virtue of LINC00174:11 downregulation in mortality, miR-1910-3p-mediated elevation of NF-kB signalling and cytokine storm were possible.1 Downregulation of RNASEH1-AS1:23 and ROR1-AS1:6 may modulate heightened immune, inflammatory and stress response, as well as viral replication during mortality, mediated by miR-218-5p and miR-375.2,3 DEG and GSEA analysis of study cohort in conjunction with LncRNA–miRNA–mRNA interaction network, highlight heightened inflammatory response (Files S3–S5; Figure 2C,D). Downregulation of LINC00504:9 and RNASEH1-AS1:23 suggests a decreased inflammatory and antiviral response in the mortality patients, whereas downregulation of MALAT1:9 suggests an increased innate immune response in the mortality, contrary to other findings.6 Upregulation of LUCAT1:3 in mortality indicates activation of interferon immunity, whereas downregulated LINC01537 reflects increased iNOS-mediated stress and decreased T-cell activation in mortality.7,8 MALAT1:9 upregulation in the severe (vs. moderate) indicates decreased immune response in severe, whereas UGDH-AS1:11 downregulation suggests decreased antiviral response and increased disease severity in the severe.5 Finally, LINC00273 downregulation in the mortality group (vs. severe) could possibly explain the decreased early innate immune response in mortality.
HCQ is a commonly recommended drug for the prophylaxis of COVID-19. One of its rare side-effect includes QTc prolongation.
This was a prospective, cross sectional and observational study conducted on ...Hydroxychloroquine (HCQ) among Healthcare Workers (HCWs) at Max Super Speciality Hospital, Saket, New Delhi, India. A 3-lead ECG (only limb leads, it does not require chest leads) was performed. The QTc cut offs were pre decided, QTC < 470 ms for males and <480 ms for females was considered within the normal limits and anything above this was regarded as QTc prolongation.
There were 274 HCWs enrolled into the study, including 175 males and 99 females. Majority of the HCWs were young and had a mean age of 32.19 ± 9.29 years. Out of these, 218 were taking HCQ as per the Indian Council of Medical Research (ICMR) guidelines. The median cumulative dose being taken was 1600 mg and the median QTc of these participants was 390 ms in males and 391.5 ms in females. Subsequently, 33 participants were followed-up and found to have a median QTc of 389 ms and a cumulative dose of HCQ as 2000 mg.
In conclusion, ours is a first study in the middle of the pandemic which showed that HCQ prophylaxis in young HCWs without comorbidities did not show any QTc prolongation.
South Asians are at high risk of type 2 diabetes (T2D). Lifestyle modification is effective at preventing T2D amongst South Asians, but the approaches to screening and intervention are limited by ...high costs, poor scalability and thus low impact on T2D burden. An intensive family-based lifestyle modification programme for the prevention of T2D was developed. The aim of the iHealth-T2D trial is to compare the effectiveness of this programme with usual care.
The iHealth-T2D trial is designed as a cluster randomised controlled trial (RCT) conducted at 120 sites across India, Pakistan, Sri Lanka and the UK. A total of 3682 South Asian men and women with age between 40 and 70 years without T2D but at elevated risk for T2D defined by central obesity (waist circumference ≥ 95 cm in Sri Lanka or ≥ 100 cm in India, Pakistan and the UK) and/or prediabetes (HbA1c ≥ 6.0%) were included in the trial. Here, we describe in detail the statistical analysis plan (SAP), which was finalised before outcomes were available to the investigators. The primary outcome will be evaluated after 3 years of follow-up after enrolment to the study and is defined as T2D incidence in the intervention arm compared to usual care. Secondary outcomes are evaluated both after 1 and 3 years of follow-up and include biochemical measurements, anthropometric measurements, behavioural components and treatment compliance.
The iHealth-T2D trial will provide evidence of whether an intensive family-based lifestyle modification programme for South Asians who are at high risk for T2D is effective in the prevention of T2D. The data from the trial will be analysed according to this pre-specified SAP.
The trial was approved by the international review board of each participating study site. Study findings will be disseminated through peer-reviewed publications and in conference presentations.
EudraCT 2016-001,350-18 . Registered on 14 April 2016.
gov NCT02949739 . Registered on 31 October 2016.
Of significant interest was the downregulation of MAL (MYD88 adaptor-like), an integral component of Toll-like receptor (TLR) signalling during pathogen invasion,7 and TRIM16, which regulates ...inflammasome activity through NLRP1-dependent production of IL-1B (Interleukin) and IL-18.8 ECM1, HSPB8, TGM3, TMPRSS11B, ITGA2, SLC20A2, ANXA11, S100A10 and IGFP3 were significantly downregulated in mortality patients, highlighting the possibility of a suboptimal innate immune response. Enrichment of pathways associated with antiviral inflammatory immune signalling (Figure 2D) and protein–protein interaction analysis highlighting the cellular stress response (Figure 2E,F) highlights the state of active defence in moderate patients and a suboptimal immune response in mortality. A possible counteractive effect is observed by the upregulation of HSPA1A, where HSPA1A leads to inhibition of-Nuclear factor kappa B (NF-κB)-regulated NLR family pyrin domain containing 3 (NLRP3) inflammasome activation, thereby preventing exacerbation of inflammation.10 The mechanism for the deregulated host response due to downregulation of MAL and TRIM16 in mortality patients is also depicted in Figure 4A.
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