A combination of potently neutralizing monoclonal antibodies isolated from an Indian convalescent donor protects against the SARS-CoV-2 Delta variant.

Although efficacious vaccines have significantly reduced the morbidity and mortality of COVID-19, there remains an unmet medical need for treatment options, which monoclonal antibodies (mAbs) can potentially fill. This unmet need is exacerbated by the emergence and spread of SARS-CoV-2 variants of concern (VOCs) that have shown some resistance to vaccine responses. Here we report the isolation of five neutralizing mAbs from an Indian convalescent donor, out of which two (THSC20.HVTR04 and THSC20.HVTR26) showed potent neutralization of SARS-CoV-2 VOCs at picomolar concentrations, including the Delta variant (B.1.617.2). One of these (THSC20.HVTR26) also retained activity against the Omicron variant. These two mAbs target non-overlapping epitopes on the receptor-binding domain (RBD) of the spike protein and prevent virus attachment to its host receptor, human angiotensin converting enzyme-2 (hACE2). Furthermore, the mAb cocktail demonstrated protection against the Delta variant at low antibody doses when passively administered in the K18 hACE2 transgenic mice model, highlighting their potential as a cocktail for prophylactic and therapeutic applications. Developing the capacity to rapidly discover and develop mAbs effective against highly transmissible pathogens like coronaviruses at a local level, especially in a low- and middle-income country (LMIC) such as India, will enable prompt responses to future pandemics as an important component of global pandemic preparedness.

Correlation of severity & clinical outcomes of COVID-19 with virus variants: A prospective, multicentre hospital network study.

BACKGROUND OBJECTIVES: The clinical course of COVID-19 and its prognosis are influenced by both viral and host factors. The objectives of this study were to develop a nationwide platform to investigate the molecular epidemiology of SARS-CoV-2 (Severe acute respiratory syndrome Corona virus 2) and correlate the severity and clinical outcomes of COVID-19 with virus variants. METHODS: A nationwide, longitudinal, prospective cohort study was conducted from September 2021 to December 2022 at 14 hospitals across the country that were linked to a viral sequencing laboratory under the Indian SARS-CoV-2 Genomics Consortium. All participants (18 yr and above) who attended the hospital with a suspicion of SARS-CoV-2 infection and tested positive by the reverse transcription-PCR method were included. The participant population consisted of both hospitalized as well as outpatients. Their clinical course and outcomes were studied prospectively. Nasopharyngeal samples collected were subjected to whole genome sequencing to detect SARS-CoV-2 variants. RESULTS: Of the 4972 participants enrolled, 3397 provided samples for viral sequencing and 2723 samples were successfully sequenced. From this, the evolution of virus variants of concern including Omicron subvariants which emerged over time was observed and the same reported here. The mean age of the study participants was 41 yr and overall 49.3 per cent were female. The common symptoms were fever and cough and 32.5 per cent had comorbidities. Infection with the Delta variant evidently increased the risk of severe COVID-19 (adjusted odds ratio: 2.53, 95% confidence interval: 1.52, 4.2), while Omicron was milder independent of vaccination status. The independent risk factors for mortality were age >65 yr, presence of comorbidities and no vaccination. INTERPRETATION CONCLUSIONS: The authors believe that this is a first-of-its-kind study in the country that provides real-time data of virus evolution from a pan-India network of hospitals closely linked to the genome sequencing laboratories. The severity of COVID-19 could be correlated with virus variants with Omicron being the milder variant.

Trends of humoral immune responses to heterologous antigenic exposure due to vaccination & omicron SARS-CoV-2 infection: Implications for boosting.

Background & objectives: Vaccination and natural infection can both augment the immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but how omicron infection has affected the vaccine-induced and hybrid immunity is not well studied in Indian population. The present study was aimed to assess the durability and change in responses of humoral immunity with age, prior natural infection, vaccine type and duration with a minimum gap of six months post-two doses with either ChAdOx1 nCov-19 or BBV152 prior- and post-emergence of the omicron variant. Methods: A total of 1300 participants were included in this observational study between November 2021 and May 2022. Participants had completed at least six months after vaccination (2 doses) with either ChAdOx1 nCoV-19 or an inactivated whole virus vaccine BBV152. They were grouped according to their age (≤ or ≥60 yr) and prior exposure of SARS-CoV-2 infection. Five hundred and sixteen of these participants were followed up after emergence of the Omicron variant. The main outcome was durability and augmentation of the humoral immune response as determined by anti-receptor-binding domain (RBD) immunoglobulin G (IgG) concentrations, anti-nucleocapsid antibodies and anti-omicron RBD antibodies. Live virus neutralization assay was conducted for neutralizing antibodies against four variants - ancestral, delta and omicron and omicron sublineage BA.5. Results: Before the omicron surge, serum anti-RBD IgG antibodies were detected in 87 per cent participants after a median gap of eight months from the second vaccine dose, with a median titre of 114 [interquartile range (IQR) 32, 302] BAU/ml. The levels increased to 594 (252, 1230) BAU/ml post-omicron surge (P<0.001) with 97 per cent participants having detectable antibodies, although only 40 had symptomatic infection during the omicron surge irrespective of vaccine type and previous history of infection. Those with prior natural infection and vaccination had higher anti-RBD IgG titre at baseline, which increased further [352 (IQR 131, 869) to 816 (IQR 383, 2001) BAU/ml] (P<0.001). The antibody levels remained elevated after a mean time gap of 10 months, although there was a decline of 41 per cent. The geometric mean titre was 452.54, 172.80, 83.1 and 76.99 against the ancestral, delta, omicron and omicron BA.5 variants in the live virus neutralization assay. Interpretation & conclusions: Anti-RBD IgG antibodies were detected in 85 per cent of participants after a median gap of eight months following the second vaccine dose. Omicron infection probably resulted in a substantial proportion of asymptomatic infection in the first four months in our study population and boosted the vaccine-induced humoral immune response, which declined but still remained durable over 10 months.

Studying the post-COVID-19 condition: research challenges, strategies, and importance of Core Outcome Set development.

BACKGROUND: A substantial portion of people with COVID-19 subsequently experience lasting symptoms including fatigue, shortness of breath, and neurological complaints such as cognitive dysfunction many months after acute infection. Emerging evidence suggests that this condition, commonly referred to as long COVID but also known as post-acute sequelae of SARS-CoV-2 infection (PASC) or post-COVID-19 condition, could become a significant global health burden. MAIN TEXT: While the number of studies investigating the post-COVID-19 condition is increasing, there is no agreement on how this new disease should be defined and diagnosed in clinical practice and what relevant outcomes to measure. There is an urgent need to optimise and standardise outcome measures for this important patient group both for clinical services and for research and to allow comparing and pooling of data. CONCLUSIONS: A Core Outcome Set for post-COVID-19 condition should be developed in the shortest time frame possible, for improvement in data quality, harmonisation, and comparability between different geographical locations. We call for a global initiative, involving all relevant partners, including, but not limited to, healthcare professionals, researchers, methodologists, patients, and caregivers. We urge coordinated actions aiming to develop a Core Outcome Set (COS) for post-COVID-19 condition in both the adult and paediatric populations.

Effects of prenatal exposure to maternal COVID-19 and perinatal care on neonatal outcome: results from the INTERCOVID Multinational Cohort Study.

BACKGROUND: The effect of COVID-19 in pregnancy on maternal outcomes and its association with preeclampsia and gestational diabetes mellitus have been reported; however, a detailed understanding of the effects of maternal positivity, delivery mode, and perinatal practices on fetal and neonatal outcomes is urgently needed. OBJECTIVE: To evaluate the impact of COVID-19 on fetal and neonatal outcomes and the role of mode of delivery, breastfeeding, and early neonatal care practices on the risk of mother-to-child transmission. STUDY DESIGN: In this cohort study that took place from March 2020 to March 2021, involving 43 institutions in 18 countries, 2 unmatched, consecutive, unexposed women were concomitantly enrolled immediately after each infected woman was identified, at any stage of pregnancy or delivery, and at the same level of care to minimize bias. Women and neonates were followed up until hospital discharge. COVID-19 in pregnancy was determined by laboratory confirmation and/or radiological pulmonary findings or ≥2 predefined COVID-19 symptoms. The outcome measures were indices of neonatal and perinatal morbidity and mortality, neonatal positivity and its correlation with mode of delivery, breastfeeding, and hospital neonatal care practices. RESULTS: A total of 586 neonates born to women with COVID-19 diagnosis and 1535 neonates born to women without COVID-19 diagnosis were enrolled. Women with COVID-19 diagnosis had a higher rate of cesarean delivery (52.8% vs 38.5% for those without COVID-19 diagnosis, P<.01) and pregnancy-related complications, such as hypertensive disorders of pregnancy and fetal distress (all with P<.001), than women without COVID-19 diagnosis. Maternal diagnosis of COVID-19 carried an increased rate of preterm birth (P≤.001) and lower neonatal weight (P≤.001), length, and head circumference at birth. In mothers with COVID-19 diagnosis, the length of in utero exposure was significantly correlated to the risk of the neonate testing positive (odds ratio, 4.5; 95% confidence interval, 2.2-9.4 for length of in utero exposure >14 days). Among neonates born to mothers with COVID-19 diagnosis, birth via cesarean delivery was a risk factor for testing positive for COVID-19 (odds ratio, 2.4; 95% confidence interval, 1.2-4.7), even when severity of maternal conditions was considered and after multivariable logistic analysis. In the subgroup of neonates born to women with COVID-19 diagnosis, the outcomes worsened when the neonate also tested positive, with higher rates of neonatal intensive care unit admission, fever, gastrointestinal and respiratory symptoms, and death, even after adjusting for prematurity. Breastfeeding by mothers with COVID-19 diagnosis and hospital neonatal care practices, including immediate skin-to-skin contact and rooming-in, were not associated with an increased risk of newborn positivity. CONCLUSION: In this multinational cohort study, COVID-19 in pregnancy was associated with increased maternal and neonatal complications. Cesarean delivery was significantly associated with newborn COVID-19 diagnosis. Vaginal delivery should be considered the safest mode of delivery if obstetrical and health conditions allow it. Mother-to-child skin-to-skin contact, rooming-in, and direct breastfeeding were not risk factors for newborn COVID-19 diagnosis, thus well-established best practices can be continued among women with COVID-19 diagnosis.

Dynamic Alteration in the Vaginal Secretory Proteome across the Early and Mid-Trimesters of Pregnancy.

Pregnancy is characterized by intense physiological and structural alterations in the vagina, cervix, and overlying fetal membranes. High vaginal fluid (HVF) is a proximal fluid that covers the lower part of the female reproductive system and the severity of vaginal pathology often adversely affects pregnancy outcomes. To identify the correlation of vaginal fluid proteome dynamics and physiological changes during the progression of pregnancy, a longitudinal study was performed on 20 pregnant women who delivered a baby in >37 weeks without any complications. SWATH-MS-based label-free quantitative proteomics was performed to profile the HVF proteome at three time points defined as V1 (7-12 weeks), V2 (18-20 weeks), and V3 (26-28 weeks). Linear mixed-effect models were used to estimate protein abundance as a function of the period of gestational age. In this study, we identified 1015 HVF proteins and 61 of them were significantly altered until late second trimester. Our result demonstrates that the HVF proteins reveal gestational age-specific expression patterns and the function of these proteins is associated with tissue remodeling, organ development, and microbial defense. Our study provides an opportunity to monitor the underlying physiology of pregnancy that may be further probed for the biomarker identification in pregnancy-related adverse outcomes. Data are available via ProteomeXchange with identifiers PXD014846 and PXD021811.

Preeclampsia and COVID-19: results from the INTERCOVID prospective longitudinal study.

BACKGROUND: It is unclear whether the suggested link between COVID-19 during pregnancy and preeclampsia is an independent association or if these are caused by common risk factors. OBJECTIVE: This study aimed to quantify any independent association between COVID-19 during pregnancy and preeclampsia and to determine the effect of these variables on maternal and neonatal morbidity and mortality. STUDY DESIGN: This was a large, longitudinal, prospective, unmatched diagnosed and not-diagnosed observational study assessing the effect of COVID-19 during pregnancy on mothers and neonates. Two consecutive not-diagnosed women were concomitantly enrolled immediately after each diagnosed woman was identified, at any stage during pregnancy or delivery, and at the same level of care to minimize bias. Women and neonates were followed until hospital discharge using the standardized INTERGROWTH-21st protocols and electronic data management system. A total of 43 institutions in 18 countries contributed to the study sample. The independent association between the 2 entities was quantified with the risk factors known to be associated with preeclampsia analyzed in each group. The outcomes were compared among women with COVID-19 alone, preeclampsia alone, both conditions, and those without either of the 2 conditions. RESULTS: We enrolled 2184 pregnant women; of these, 725 (33.2%) were enrolled in the COVID-19 diagnosed and 1459 (66.8%) in the COVID-19 not-diagnosed groups. Of these women, 123 had preeclampsia of which 59 of 725 (8.1%) were in the COVID-19 diagnosed group and 64 of 1459 (4.4%) were in the not-diagnosed group (risk ratio, 1.86; 95% confidence interval, 1.32-2.61). After adjustment for sociodemographic factors and conditions associated with both COVID-19 and preeclampsia, the risk ratio for preeclampsia remained significant among all women (risk ratio, 1.77; 95% confidence interval, 1.25-2.52) and nulliparous women specifically (risk ratio, 1.89; 95% confidence interval, 1.17-3.05). There was a trend but no statistical significance among parous women (risk ratio, 1.64; 95% confidence interval, 0.99-2.73). The risk ratio for preterm birth for all women diagnosed with COVID-19 and preeclampsia was 4.05 (95% confidence interval, 2.99-5.49) and 6.26 (95% confidence interval, 4.35-9.00) for nulliparous women. Compared with women with neither condition diagnosed, the composite adverse perinatal outcome showed a stepwise increase in the risk ratio for COVID-19 without preeclampsia, preeclampsia without COVID-19, and COVID-19 with preeclampsia (risk ratio, 2.16; 95% confidence interval, 1.63-2.86; risk ratio, 2.53; 95% confidence interval, 1.44-4.45; and risk ratio, 2.84; 95% confidence interval, 1.67-4.82, respectively). Similar findings were found for the composite adverse maternal outcome with risk ratios of 1.76 (95% confidence interval, 1.32-2.35), 2.07 (95% confidence interval, 1.20-3.57), and 2.77 (95% confidence interval, 1.66-4.63). The association between COVID-19 and gestational hypertension and the direction of the effects on preterm birth and adverse perinatal and maternal outcomes, were similar to preeclampsia, but confined to nulliparous women with lower risk ratios. CONCLUSION: COVID-19 during pregnancy is strongly associated with preeclampsia, especially among nulliparous women. This association is independent of any risk factors and preexisting conditions. COVID-19 severity does not seem to be a factor in this association. Both conditions are associated independently of and in an additive fashion with preterm birth, severe perinatal morbidity and mortality, and adverse maternal outcomes. Women with preeclampsia should be considered a particularly vulnerable group with regard to the risks posed by COVID-19.

Comparison of first trimester dating methods for gestational age estimation and their implication on preterm birth classification in a North Indian cohort.

BACKGROUND: Different formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This study's data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB. METHODS: Comparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy. RESULTS: Performance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, - 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27-16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by 3 days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB. CONCLUSIONS: An accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae.

Vaginal Microbiome of Pregnant Indian Women: Insights into the Genome of Dominant Lactobacillus Species.

The trillions of microorganisms residing in the human body display varying degrees of compositional and functional diversities within and between individuals and contribute significantly to host physiology and susceptibility to disease. Microbial species present in the vaginal milieu of reproductive age women showed a large personal component and varies widely in different ethnic groups at the taxonomic, genomic, and functional levels. Lactobacillus iners, L. crispatus, L. gasseri, L. jensenii, and L. johnsonii are most frequently detected bacterial species in the vaginal milieu of reproductive age women. However, we currently lack (i) an understanding of the baseline vaginal microbiota of reproductive age Indian women, (ii) the extent of taxonomic and functional variations of vaginal microbiota between individuals and (iii) the genomic repertoires of the dominant vaginal microbiota associated with the Indian subjects. In our study, we analyzed the metagenome of high vaginal swab (HVS) samples collected from 40 pregnant Indian women enrolled in the GARBH-Ini cohort. Composition and abundance of bacterial species was characterized by pyrosequencing 16S rRNA gene. We identified 3067 OTUs with ≥ 10 reads from four different bacterial phyla. Several species of lactobacilli were clustered into three community state types (CSTs). L. iners, L. crispatus, L. gasseri, and L. jensenii are the most frequently detected Lactobacillus species in the vaginal environment of Indian women. Other than Lactobacillus, several species of Halomonas were also identified in the vaginal environment of most of the women sampled. To gain genomic and functional insights, we isolated several Lactobacillus species from the HVS samples and explored their whole genome sequences by shotgun sequencing. We analyzed the genome of dominant Lactobacillus species, L. iners, L. crispatus, L. gasseri, and L. paragesseri to represent the CSTs and identify functions that may influence the composition of complex vaginal microbial ecology. This study reports for the first time the vaginal microbial ecology of Indian women and genomic insights into L. iners, L. crispatus, L. gasseri, and L. paragesseri commonly found in the genital tract of reproductive age women.

Statistical Characterisation of Fetal Anatomy in Simple Obstetric Ultrasound Video Sweeps.

OBJECTIVE: We present a statistical characterisation of fetal anatomies in obstetric ultrasound video sweeps where the transducer follows a fixed trajectory on the maternal abdomen. METHODS: Large-scale, frame-level manual annotations of fetal anatomies (head, spine, abdomen, pelvis, femur) were used to compute common frame-level anatomy detection patterns expected for breech, cephalic, and transverse fetal presentations, with respect to video sweep paths. The patterns, termed statistical heatmaps, quantify the expected anatomies seen in a simple obstetric ultrasound video sweep protocol. In this study, a total of 760 unique manual annotations from 365 unique pregnancies were used. RESULTS: We provide a qualitative interpretation of the heatmaps assessing the transducer sweep paths with respect to different fetal presentations and suggest ways in which the heatmaps can be applied in computational research (e.g., as a machine learning prior). CONCLUSION: The heatmap parameters are freely available to other researchers (https://github.com/agleed/calopus_statistical_heatmaps).

Post-natal gestational age assessment using targeted metabolites of neonatal heel prick and umbilical cord blood: A GARBH-Ini cohort study from North India.

Background: Accurate assessment of gestational age (GA) and identification of preterm birth (PTB) at delivery is essential to guide appropriate post-natal clinical care. Undoubtedly, dating ultrasound sonography (USG) is the gold standard to ascertain GA, but is not accessible to the majority of pregnant women in low- and middle-income countries (LMICs), particularly in rural areas and small secondary care hospitals. Conventional methods of post-natal GA assessment are not reliable at delivery and are further compounded by a lack of trained personnel to conduct them. We aimed to develop a population-specific GA model using integrated clinical and biochemical variables measured at delivery. Methods: We acquired metabolic profiles on paired neonatal heel prick (nHP) and umbilical cord blood (uCB) dried blood spot (DBS) samples (n = 1278). The master data set consists of 31 predictors from nHP and 24 from uCB after feature selection. These selected predictors including biochemical analytes, birth weight, and placental weight were considered for the development of population-specific GA estimation and birth outcome classification models using eXtreme Gradient Boosting (XGBoost) algorithm. Results: The nHP and uCB full model revealed root mean square error (RMSE) of 1.14 (95% confidence interval (CI) = 0.82-1.18) and of 1.26 (95% CI = 0.88-1.32) to estimate the GA as compared to actual GA, respectively. In addition, these models correctly estimated 87.9 to 92.5% of the infants within ±2 weeks of the actual GA. The classification models also performed as the best fit to discriminate the PTB from term birth (TB) infants with an area under curve (AUC) of 0.89 (95% CI = 0.84-0.94) for nHP and an AUC of 0.89 (95% CI = 0.85-0.95) for uCB. Conclusion: The biochemical analytes along with clinical variables in the nHP and uCB data sets provide higher accuracy in predicting GA. These models also performed as the best fit to identify PTB infants at delivery.

Development and external validation of Indian population-specific Garbhini-GA2 model for estimating gestational age in second and third trimesters.

Background: A large proportion of pregnant women in lower and middle-income countries (LMIC) seek their first antenatal care after 14 weeks of gestation. While the last menstrual period (LMP) is still the most prevalent method of determining gestational age (GA), ultrasound-based foetal biometry is considered more accurate in the second and third trimesters. In LMIC settings, the Hadlock formula, originally developed using data from a small Caucasian population, is widely used for estimating GA and foetal weight worldwide as the pre-programmed formula in ultrasound machines. This approach can lead to inaccuracies when estimating GA in a diverse population. Therefore, this study aimed to develop a population-specific model for estimating GA in the late trimesters that was as accurate as the GA estimation in the first trimester, using data from GARBH-Ini, a pregnancy cohort in a North Indian district hospital, and subsequently validate the model in an independent cohort in South India. Methods: Data obtained by longitudinal ultrasonography across all trimesters of pregnancy was used to develop and validate GA models for the second and third trimesters. The gold standard for GA estimation in the first trimester was determined using ultrasonography. The Garbhini-GA2, a polynomial regression model, was developed using the genetic algorithm-based method, showcasing the best performance among the models considered. This model incorporated three of the five routinely measured ultrasonographic parameters during the second and third trimesters. To assess its performance, the Garbhini-GA2 model was compared against the Hadlock and INTERGROWTH-21st models using both the TEST set (N = 1493) from the GARBH-Ini cohort and an independent VALIDATION dataset (N = 948) from the Christian Medical College (CMC), Vellore cohort. Evaluation metrics, including root-mean-squared error, bias, and preterm birth (PTB) rates, were utilised to comprehensively assess the model's accuracy and reliability. Findings: With first trimester GA dating as the baseline, Garbhini-GA2 reduced the GA estimation median error by more than three times compared to the Hadlock formula. Further, the PTB rate estimated using Garbhini-GA2 was more accurate when compared to the INTERGROWTH-21st and Hadlock formulae, which overestimated the rate by 22.47% and 58.91%, respectively. Interpretation: The Garbhini-GA2 is the first late-trimester GA estimation model to be developed and validated using Indian population data. Its higher accuracy in GA estimation, comparable to GA estimation in the first trimester and PTB classification, underscores the significance of deploying population-specific GA formulae to enhance antenatal care. Funding: The GARBH-Ini cohort study was funded by the Department of Biotechnology, Government of India (BT/PR9983/MED/97/194/2013). The ultrasound repository was partly supported by the Grand Challenges India-All Children Thriving Program, Biotechnology Industry Research Assistance Council, Department of Biotechnology, Government of India (BIRAC/GCI/0115/03/14-ACT). The research reported in this publication was made possible by a grant (BT/kiData0394/06/18) from the Grand Challenges India at Biotechnology Industry Research Assistance Council (BIRAC), an operating division jointly supported by DBT-BMGF-BIRAC. The external validation study at CMC Vellore was partly supported by a grant (BT/kiData0394/06/18) from the Grand Challenges India at Biotechnology Industry Research Assistance Council (BIRAC), an operating division jointly supported by DBT-BMGF-BIRAC and by Exploratory Research Grant (SB/20-21/0602/BT/RBCX/008481) from Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras. An alum endowment from Prakash Arunachalam (BIO/18-19/304/ALUM/KARH) partly funded this study at the Centre for Integrative Biology and Systems Medicine, IIT Madras.

A quest for universal anti-SARS-CoV-2 T cell assay: systematic review, meta-analysis, and experimental validation.

Measuring SARS-CoV-2-specific T cell responses is crucial to understanding an individual's immunity to COVID-19. However, high inter- and intra-assay variability make it difficult to define T cells as a correlate of protection against COVID-19. To address this, we performed systematic review and meta-analysis of 495 datasets from 94 original articles evaluating SARS-CoV-2-specific T cell responses using three assays - Activation Induced Marker (AIM), Intracellular Cytokine Staining (ICS), and Enzyme-Linked Immunospot (ELISPOT), and defined each assay's quantitative range. We validated these ranges using samples from 193 SARS-CoV-2-exposed individuals. Although IFNγ ELISPOT was the preferred assay, our experimental validation suggested that it under-represented the SARS-CoV-2-specific T cell repertoire. Our data indicate that a combination of AIM and ICS or FluoroSpot assay would better represent the frequency, polyfunctionality, and compartmentalization of the antigen-specific T cell responses. Taken together, our results contribute to defining the ranges of antigen-specific T cell assays and propose a choice of assay that can be employed to better understand the cellular immune response against viral diseases.

Incidence of and risk factors for small vulnerable newborns in north India: a secondary analysis of a prospective pregnancy cohort.

BACKGROUND: Globally, recent estimates have shown there have been 3·6 million stillbirths and neonatal deaths in 2022, with nearly 60% occurring in low-income and middle-income countries. The Small Vulnerable Newborn Consortium has proposed a framework combining preterm birth (<37 weeks of gestation), small for gestational age (SGA) by INTERGROWTH-21st standard, and low birthweight (<2500 g) under the category small vulnerable newborns (SVN). Reliable data on SVN from sub-Saharan Africa, central Asia, and south Asia are sparse. We aimed to estimate the incidence of SVN and its types, and quantify risk factors, both overall and trimester-specific, from a pregnancy cohort in north India. METHODS: In the GARBH-Ini (Interdisciplinary Group for Advanced Research on Birth Outcomes-DBT India Initiative) pregnancy cohort, 8000 participants were enrolled with less than 20 weeks' gestation between May 11, 2015, and Aug 8, 2020, at a secondary-care hospital in north India. The cohort was followed up across the antenatal period for a detailed study on preterm birth. We conducted a secondary analysis of cohort data for the outcome of SVN, classified into its types: preterm-SGA, preterm-nonSGA, and term-SGA. We estimated the relative risk and population attributable fraction of candidate risk factors for SVN (modified Poisson regression) and its types (multinomial regression). FINDINGS: 7183 (89·9%) of 7990 participants completed the study. Among 6206 newborns included for analysis, the incidence of SVN was 48·4% (35·1% term-SGA newborns [n=2179], 9·7% preterm-nonSGA newborns [n=605], and 3·6% preterm-SGA newborns [n=222]). Compared with term-nonSGA newborns, proportions of stillbirths and neonatal deaths within 72 h of birth among SVN were three times and 2·5 times higher, respectively. Preterm-SGA newborns had the highest incidence of stillbirth (15 [6·8%] of 222) and neonatal deaths (six [4·2%] of 142). Low body-mass index (BMI <18·5 kg/m2) of participants at the start of pregnancy was associated with higher risk for preterm-SGA (adjusted relative risk [RR] 1·61 [95% CI 1·17-2·22]), preterm-nonSGA (1·35 [1·09-1·68]), and term-SGA (1·44 [1·27- 1·64]), with population attributable fraction ranging from 8·7% to 13·8%. Pre-eclampsia (adjusted RR 1·48 [95% CI 1·30-1·71]), short cervical length (1·15 [1·04-1·26]), and bacterial vaginosis (1·13 [0·88-1·45]) were other important antenatal risk factors. INTERPRETATION: In a comprehensive analysis of SVN and its types from north India, we identified risk factors to guide prioritisation of interventions. Complemented with risk-stratification tools, this focused approach will enhance antenatal care, and accelerate achievement of Sustainable Development Goals-namely, to end preventable deaths of newborns and children younger than 5 years by 2030 (target 3·2). FUNDING: Department of Biotechnology, Government of India and Grand Challenges India-Biotechnology Industry Research Assistance Council, Government of India. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.

Genetic variants associated with spontaneous preterm birth in women from India: a prospective cohort study.

Background: Despite having the highest number of preterm births globally, no genomic study on preterm birth was previously published from India or other South-Asian countries. Methods: We conducted a genome-wide association (GWA) study of spontaneous preterm birth (sPTB) on 6211 women from India. We used a novel resampling procedure to identify the associated single nucleotide polymorphisms (SNPs) followed by haplotype association analysis and imputation. Findings: We found that 512 maternal SNPs were associated with sPTB (p < 2.51e-3), of which minor allele at 19 SNPs (after Bonferroni correction) had increased genotype relative risk. Haplotypes containing six of the 19 SNPs (rs13011430, rs8179838, rs2327290, rs4798499, rs7629800, and rs13180906) were associated with sPTB (p < 9.9e-4; Bonferroni adjusted p-value <0.05). After imputation in regions around the 19 SNPs, 15 imputed SNPs were found to be associated with sPTB (Bonferroni adjusted p-value <0.05). One of these imputed SNPs, rs35760881, and three other SNPs (rs17307697, rs4308815, and rs10983507) were also reported to be associated with sPTB in women belonging to European ancestry. Moreover, we found that GG genotype at rs1152954, one of the associated SNPs, enhanced risk of sPTB and reduced telomere length. Interpretation: This is the first study from South Asia on the genome-wide identification of maternal SNPs associated with sPTB. These SNPs are known to alter the expression of genes associated with major pathways in sPTB viz. inflammation, apoptosis, cervical ripening, telomere maintenance, selenocysteine biosynthesis, myometrial contraction, and innate immunity. From a public health perspective, the trans-ethnic association of four SNPs identified in our study may help to stratify women with risk of sPTB in most populations. Funding: Department of Biotechnology (India), Grand Challenges India - All Children Thriving Program and Biotechnology Industry Research Assistance Council (BIRAC).

Genome-wide temporal landscaping of DNA methylation in pregnant women delivering at term: a GARBH-InI study.

Background: We performed an epigenome-wide longitudinal DNA methylation study on an Indian cohort of pregnant women, GARBH-Ini, at three time points during pregnancy and at delivery. Aim & objective: Our aim was to identify temporal DNA methylation changes in maternal peripheral blood during the period of gestation and assess their impact on biological pathways critical for term delivery. Results: Significantly differentially methylated CpGs were identified by linear mixed model analysis (Bonferroni p < 0.01) and classified into two distinct temporal methylation trends: increasing and decreasing during gestation. Genes with upward methylation trend were enriched for T-cell activity, while those with a downward trend were enriched for solute transport and cell structure organization functions. Conclusion: Consistent trends of DNA methylation in maternal peripheral blood point to the sentinel function of T cells in the maintenance of pregnancy, and the importance of coordinated cellular remodeling to facilitate term delivery.

DNA methylation is the addition of a methyl group to the molecular structure of DNA, which then alters the gene expression. The goal of the study was to find out how DNA methylation patterns change over time during pregnancy and how these changes are related to the biological processes that are important for the delivery of a healthy baby at full term. Using statistical modeling, we identified specific patterns of DNA methylation changes during pregnancy and classified them into two groups based on the direction of the changes. The genes associated with increasing methylation levels were related to the activities of T cells, which are important for the immune system. The genes associated with decreasing methylation levels were related to processes like transporting substances and organizing cell structures. In conclusion, our findings suggest that T cells play an important role in maintaining a healthy pregnancy, and the study highlights the importance of coordinated changes in cells to support a successful delivery of a baby at term.

Clinical and experimental evidence suggest omicron variant of SARS-CoV-2 is inherently less pathogenic than delta variant independent of previous immunity.

OBJECTIVES: To study clinical disease outcomes in both human and animal models to understand the pathogenicity of omicron compared to the delta variant. METHODS: In this cross-sectional observational study, clinical outcomes of adults who tested positive at 2 testing centres in Delhi National Capital Region between January 2022 and March 2022 (omicron-infected; N = 2998) were compared to a similar geographical cohort (delta-infected; N = 3292). In addition, disease course and outcomes were studied in SARS-CoV-2-infected golden Syrian hamsters and K-18 humanized ACE2 transgenic mice. RESULTS: Omicron variant infection was associated with a milder clinical course [83% (95% CI 61, 94) reduced risk of severity compared against delta] adjusting for vaccination, age, sex, prior infection and occupational risk. This correlated with lower disease index and vir comparing omicron with other variants in animal models. CONCLUSIONS: Infections caused by the omicron variant were milder compared to those caused by the delta variant independent of previous immunity.

Ancestral SARS-CoV-2-Driven Antibody Repertoire Diversity in an Unvaccinated Individual Correlates with Expanded Neutralization Breadth.

Understanding the quality of immune repertoire triggered during natural infection can provide vital clues that form the basis for development of a humoral immune response in some individuals capable of broadly neutralizing pan-SARS-CoV-2 variants. In the present study, we report variations in neutralization potential against Omicron variants of two novel neutralizing monoclonal antibodies (MAbs), THSC20.HVTR11 and THSC20.HVTR55, isolated from an unvaccinated convalescent individual that represent distinct B cell lineage origins and epitope specificity compared to five MAbs we previously reported that were isolated from the same individual. In addition, we observed neutralization of Omicron variants by plasma antibodies obtained from this particular individual postvaccination with increased magnitude. Interestingly, this observation was found to be comparable with six additional individuals who initially were also infected with ancestral SARS-CoV-2 and then received vaccines, indicating that hybrid immunity can provide robust humoral immunity likely by antibody affinity maturation. Development of a distinct antigen-specific B cell repertoire capable of producing polyclonal antibodies with distinct affinity and specificities offers the highest probability of protecting against evolving SARS-CoV-2 variants. IMPORTANCE Development of robust neutralizing antibodies in SARS-CoV-2 convalescent individuals is known; however, it varies at the population level. We isolated monoclonal antibodies from an individual infected with ancestral SARS-CoV-2 in early 2020 that not only varied in their B cell lineage origin but also varied in their capability and potency to neutralize all the known variants of concern (VOCs) and currently circulating Omicron variants. This indicated establishment of unique lineages that contributed in forming a B cell repertoire in this particular individual immediately following infection, giving rise to diverse antibody responses that could complement each other in providing a broadly neutralizing polyclonal antibody response. Individuals who were able to produce polyclonal antibody responses with higher magnitude have a higher chance of being protected from evolving SARS-CoV-2 variants.

Severity and mortality associated with COVID-19 among children hospitalised in tertiary care centres in India: a cohort study.

Background: It is critical to identify high-risk groups among children with COVID-19 from low-income and middle-income countries (LMICs) to facilitate the optimum use of health system resources. The study aims to describe the severity and mortality of different clinical phenotypes of COVID-19 in a large cohort of children admitted to tertiary care hospitals in India. Methods: Children aged 0-19 years with evidence of SARS-CoV-2 infection (real time polymerase chain reaction or rapid antigen test positive) or exposure (anti-SARS-CoV-2 antibody, or history of contact with SARS-CoV-2) were enrolled in the study, between January 2021 and March 2022 across five tertiary hospitals in India. All study participants enrolled prospectively and retrospectively were followed up for three months after discharge. COVID-19 was classified into severe (Multisystem Inflammatory Syndrome in Children (MIS-C), severe acute COVID-19, 'unclassified') or non-severe disease. The mortality rates were estimated in different phenotypes. Findings: Among 2468 eligible children enrolled, 2148 were hospitalised. Signs of illness were present in 1688 (79%) children with 1090 (65%) having severe disease. High mortality was reported in MIS-C (18.6%), severe acute COVID-19 (13.3%) and the unclassified severe COVID-19 disease (12.3%). Mortality remained high (17.5%) when modified MIS-C criteria was used. Non-severe COVID-19 disease had 14.1% mortality when associated with comorbidity. Interpretation: Our findings have important public health implications for low resource settings. The high mortality underscores the need for better preparedness for timely diagnosis and management of COVID-19. Children with associated comorbidity or coinfections are a vulnerable group and need special attention. MIS-C requires context specific diagnostic criteria for low resource settings. It is important to evaluate the clinical, epidemiological and health system-related risk factors associated with severe COVID-19 and mortality in children from LMICs. Funding: Department of Biotechnology, Govt of India and Department of Maternal, Child and Adolescent Health and Aging, WHO, Geneva, Switzerland.

Longitudinal changes in serum immune markers during normal pregnancy in a North-Indian population.

PROBLEM: The objective of this study was to examine levels of cytokines across normal term pregnancy in an Indian population. Additionally we have also explored for possible associations between inflammatory markers and fetal growth parameters. METHOD OF STUDY: A multiplex panel of 24 analytes was used to examine levels of inflammatory markers in maternal serum at three time points during pregnancy and in cord blood from women with no reported comorbidities who delivered a singleton live baby at term (N = 23), enrolled in the GARBH-Ini pregnancy cohort. Linear mixed models were applied to construct longitudinal cytokine trajectories with gestational age. Pearson correlation was used to calculate intra-visit correlation between cytokines. Principal component analysis (PCA) was performed to examine cytokine combinations prevalent across pregnancy, and their association with fetal growth parameters was determined by multivariable regression. RESULTS: Significant increase in sFLT-1, Flt3L, PLGF, IL-4, and IL-18 and a decrease in VCAM-1 concentrations was seen across pregnancy. The cytokine concentrations in cord blood differed substantially as compared to maternal levels across gestation. Some cytokines were closely correlated with each other in distinct patterns across pregnancy. Gestational age specific combination of cytokines were seen to be associated with different fetal growth parameters. CONCLUSIONS: This study for the first time provides reference concentrations for the longitudinal expression of immune markers across pregnancy in an Indian population providing a much needed baseline to compare with pregnancies leading to adverse outcomes. Growth factors showed maximum longitudinal variation with gestational age and strong correlations were identified between various cytokines at all time points across pregnancy.