Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).

Frequency spectrum of rare and clinically relevant markers in multiethnic Indian populations (ClinIndb): A resource for genomic medicine in India.

There have been concerted efforts toward cataloging rare and deleterious variants in different world populations using high-throughput genotyping and sequencing-based methods. The Indian population is underrepresented or its information with respect to clinically relevant variants is sparse in public data sets. The aim of this study was to estimate the burden of monogenic disease-causing variants in Indian populations. Toward this, we have assessed the frequency profile of monogenic phenotype-associated ClinVar variants. The study utilized a genotype data set (global screening array, Illumina) from 2795 individuals (multiple in-house genomics cohorts) representing diverse ethnic and geographically distinct Indian populations. Of the analyzed variants from Global Screening Array, ~9% were found to be informative and were either not known earlier or underrepresented in public databases in terms of their frequencies. These variants were linked to disorders, namely inborn errors of metabolism, monogenic diabetes, hereditary cancers, and various other hereditary conditions. We have also shown that our study cohort is genetically a better representative of the Indian population than its representation in the 1000 Genome Project (South Asians). We have created a database, ClinIndb, linked to the Leiden Open Variation Database, to help clinicians and researchers in diagnosis, counseling, and development of appropriate genetic screening tools relevant to the Indian populations and Indians living abroad.