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

• Published in: Human mutation Vol. 41; no. 11; pp. 1833 - 1847
• Main Authors: Narang, Ankita, Uppilli, Bharathram, Vivekanand, Asokachandran, Naushin, Salwa, Yadav, Arti, Singhal, Khushboo, Shamim, Uzma, Sharma, Pooja, Zahra, Sana, Mathur, Aradhana, Seth, Malika, Parveen, Shaista, Vats, Archana, Hillman, Sara, Dolma, Padma, Varma, Binuja, Jain, Vandana, Prasher, Bhavana, Sengupta, Shantanu, Mukerji, Mitali, Faruq, Mohammed
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.11.2020
• Subjects: ClinVar variants; Diabetes mellitus; Genetic screening; Genotypes; Genotyping; high‐throughput genotyping; Inborn errors of metabolism; Indian populations; monogenic diseases; Phenotypes; database; ClinVar variants; Indian populations; high-throughput genotyping; monogenic diseases
• ISSN: 1059-7794; 1098-1004; 1098-1004
• DOI: 10.1002/humu.24102

Clinindb, a database to catalogue the allele frequencies of clinically relevant genetic variants among Indians, aims to fill the gap for representation of Indian subjects in public databases. Nearly, 20K clinically variants were analyzed for their polymorphocity across control cohort and among patients pool. It highlights the key differences observed while assessing the genetic variability and the general occurrences of those variants in Indian context. Clinindb will be utilized in present as well as future online resource for Monogenic (Mendelian variants) from 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.