Frequency spectrum of rare and clinically relevant markers in multiethnic Indian populations (ClinIndb): A resource for genomic medicine in India
Autor: | Uzma Shamim, Shantanu Sengupta, Pooja Sharma, Binuja Varma, Vandana Jain, Mohammed Faruq, Sana Zahra, Sara L. Hillman, Khushboo Singhal, Archana Vats, Padma Dolma, Asokachandran Vivekanand, Mitali Mukerji, Aradhana Mathur, Arti Yadav, Ankita Narang, Salwa Naushin, Bhavana Prasher, Bharathram Uppilli, Shaista Parveen, Malika Seth |
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Rok vydání: | 2020 |
Předmět: |
Genetic Markers
0303 health sciences Resource (biology) Genotype 030305 genetics & heredity Ethnic group India Genomics Biology Cohort Studies 03 medical and health sciences Genetics Population Phenotype Evolutionary biology Cohort Ethnicity Genetics Humans 1000 Genomes Project Leiden Open Variation Database Genotyping Genetics (clinical) 030304 developmental biology |
Zdroj: | Human Mutation. 41:1833-1847 |
ISSN: | 1098-1004 1059-7794 |
Popis: | 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. |
Databáze: | OpenAIRE |
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