An inter-institutional interdisciplinary research program was initiated (and coordinated) by me in 2014, with the ultimate objective of elucidating biological and non-biological risks of preterm birth (PTB) to create important knowledge-driven interventions and technologies that can be sustainably implemented in clinical practice and in the community for this disease.

We began with a hypothesis that the qualitative and quantitative insights obtained on PTB from a time-series study over the entire duration of pregnancy will help in stratifying women into defined risk groups. Such stratification, in turn, will facilitate, development of predictive biomarkers and an effective algorithm for early prediction and timing of intervention of PTB in our settings. The objectives are to identify the multidimensional (clinical, epidemiological, genomic, epigenomic, proteomic and microbial) correlates of PTB, discover molecular biomarkers by using an integrative omics approach, and do an accurate categorization of the PTB phenotype based on pathological factors in addition to gestational age. A cohort was started at the Gurugram Civil Hospital in 2015 (Am J Epidemiol 2019). Pregnant women are enrolled before 20 weeks of gestation and are followed at regular intervals across pregnancy till delivery; Against a committed sample size of 8000 pregnant women 7600 have been enrolled and over 5000 pregnancy outcomes have been determined till now. A large repository consisting over 700,000 biospecimens longitudinally collected and more than 400,000 serial ultrasound images of the cohort participants with well characterized information on environmental, clinical, social and epidemiological determinants at different time points in pregnancy has been established at THSTI. We propose to continue enrolling up to at least 12000 pregnant women in the second phase of the cohort in order to complete our proposed objectives and validate the results of the first phase. This programme has been identified as the flagship programme of THSTI as it an unique example of how biology in humans can be integrated with epidemiology and the clinical phenotypes across multiple DBT research institutions and hospitals. Recently it has been included as one of the Atal Jai-Anusandhan Mission Programmes by the nodal ministry.

Interesting leads from the GARBH-Ini cohort as deliverables for translation

The high proportion of 13.4% preterm birth is remarkable as this is the first such study in the country that has documented preterm birth rate in a longitudinally followed cohort of pregnant women. Importantly, our cohort is showing a still birth rate of 2% and fetal growth restriction of 38% identified in the last trimester of pregnancy; both parameters have crucial public health implications (Am J Epidemiol 2019).

There are interesting leads from the first 5000 pregnant women enrolled in the cohort that can be deliverables for translation, once validated in the 5000 women enrolled in the second phase of the programme. Women who gave history of being exposed to either biomass fuel smoke or passive smoking during pregnancy were at 47% higher risk of PTB after accounting for differences in the sociodemographic characteristics; an implication that nearly one-tenth of all preterm births occurring in our population could be attributed to these exposures. We are evaluating the threshold of PM2.5 exposure and the window of vulnerability during pregnancy to which novel interventions can be designed to prevent preterm birth. Further, profiling sources of air pollutants will inform policy interventions targeted toward source mitigation and help formulate evidence-based health advisory. Our studies on real time placental blood flow associated with exposure to PM2.5 evaluated by ultrasound imaging changes, is aimed to expand mechanistic understanding of this public health problem. The detailed description of dietary intakes during different trimesters of pregnancy is valuable and provides critical inputs on association between dietary patterns and novel micronutrients such as selenium with pregnancy outcomes. We believe this data will facilitate specific dietary recommendations during pregnancy.

Innovative analytical methods are being used to develop new population-specific models (using ultrasound and/or metabolic panels) for dating of pregnancy (medRxiv 2019.12.27.19016006; https://doi.org/10.1101/2019.12.27.19016006;t), and software with built-in artificial intelligence algorithms which automate quality control during antenatal ultrasonography and predicts risk scores for adverse pregnancy outcomes. Prediction tools during 1st trimester to supplement conventional diagnostic tests for efficient diagnosis of GDM are some other important tools that are being studied to inform clinical decision (Utility of Point-of-Care HbA1c Testing for Prediction and Diagnosis of Gestational Diabetes Mellitus in a North Indian population, under preparation).

We have used a multi-omics approach for identification of molecular determinants across normal pregnancy. With this background knowledge we are in the process of identifying omics derived biomarkers for prediction of preterm birth, using robust nested case control designs within the cohort. The initial biomarker discovery will be validated in the women enrolled subsequently in this cohort over the next few years and other population cohorts (Scientific Reports 2020 under review, Human reproduction 2020, under review; Microbial ecology 2020, under review). Our eventual crucial deliverable will be the dynamic risk prediction model for PTB built using this multi-dimensional data from clinical, epidemiological, USG imaging and multiple omics technologies. This will enable early & effective risk stratification of mothers who may deliver preterm and facilitate timely referral to higher level care, which we believe will be a critical public health intervention.

An important public health tool that we envisage to develop is a simple non-invasive and portable point of care solution for triaging women based on their risk for adverse outcomes identified on the antenatal ultrasound images. Once validated it is proposed m that it will be simple enough to be performed by peripheral health workers. Advanced image processing and artificial intelligence technologies are being used on standardized video sweeps captured during different periods of gestation to develop this innovative intervention.

Placenta is the cornerstone of a healthy pregnancy and is the least evaluated organ in the context of early gestation or poor fetal growth. We have initiated a human placenta biology programme that is evaluating surrogate markers of placenta in the maternal blood, studying its functions by real time ultra sound imaging and understanding cellular and biochemical pathways using multi omics approaches (Am J Reprod Immunol 2017, Endocrinology 2019, Endocrinology 2020).

We have documented for the first time in the country, gestational weight gain measured longitudinally across pregnancy. More than 50% of our women gained weight less than 10th centile as compared with the global standards (Gestational weight gain and its association with birthweight- an analysis from GARBH-Ini, an observational cohort study in North India, manuscript under preparation). Data from our well characterised serial ultrasound images shows that the most vulnerable period of fetal growth appears to be the third trimester. These results have highlighted the challenges of maternal and fetal health in our country. The objective over the next few years will be to develop tools based on distinct clinical and biological risk factors for better monitoring of poor maternal weight gain and early and late fetal growth restriction.

The determinants of stunting and developmental delay during infancy may be attributed to multidimensional factors during pregnancy and/or the distinct birth phenotypes. We will study associations between antenatal determinants and those at birth of 5000 babies born in the Garbhini cohort over the coming years for stunting and cognitive functions as they grow over the first two years of their life.

GARBH-Ini is an illustration of how large inter-disciplinary translational programs can be initiated around important public health issues. In the long term this platform will serve as an important national resource for answering additional research questions as new hypotheses emerge around birth, maternal health during pregnancy and questions around fetal origin of adult disease.