The PAthways to Resilience And Mental health (PARAM) project: protocol for a multi-site developmental cohort in India

Psychiatric disorders are increasingly conceptualised within a neurodevelopmental framework, in which genetic liability interacts with environmental exposures across the lifespan to shape brain and behavioural trajectories. Deviations in these trajectories may confer vulnerability or resilience to later psychopathology. Longitudinal cohorts spanning critical developmental windows are required to map these pathways and their associated risk and protective factors.

The PAthways to Resilience And Mental health (PARAM) project is a multi-site longitudinal cohort in India, enrolling approximately 9,000 participants from the antenatal period to 30 years of age. PARAM extends the Consortium on the Vulnerability to Externalizing Disorders and Addictions (cVEDA) cohort, which recruited more than 9,000 individuals aged 6-23 years, by adding intensive follow-up from the fetal period to early childhood. Eight sites across India participate, with five recontacting their original cVEDA participants for repeated assessments. Repeated measures include questionnaires on development, temperament, and mental health; family medical and psychiatric history; assessments of environmental exposures such as adverse experiences, diet, maternal stress, toxic exposures, and screen use; and satellite-derived indicators of urbanisation and air pollution over time. Detailed examinations comprise anthropometry and body composition, neurocognitive testing, neurophysiological measures including heart rate variability and body sway, neuroimaging with 3T MRI and fNIRS, and biospecimen collection (blood, buccal swabs, hair, nails, urine, stool) for genomic, toxicological, and metabolic assays. Data are stored in a harmonised digital archive linked to a barcoded biorepository. Follow-up employs a closed cohort design for children younger than two years and an accelerated longitudinal design for older participants. Planned analyses include mixed-effects and generalized additive models for trajectories, multi-site imaging harmonisation and normative modelling, multivariate integration of multi-omic and imaging features, and predictive modelling with nested cross-validation and external validation where feasible. Missing data and attrition will be addressed using multiple imputation and inverse probability weighting.

PARAM will offer insights into population-based developmental trajectories, identify modifiable risk and protective factors, and support predictive models for psychopathology. The findings are expected to inform precision interventions and public health strategies, while contributing a socio-culturally diverse resource to global mental health research.