Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.
Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India.
Hum Mutat. 2020 Nov;41(11):1833-1847. doi: 10.1002/humu.24102. Epub 2020 Sep 9.
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.
人们一直在努力使用高通量基因分型和测序方法来对不同世界人群中的罕见和有害变异进行编目。印度人口在公共数据集的代表性不足,或者其与临床相关变异的信息稀疏。本研究旨在估计印度人群中单基因疾病相关变异的负担。为此,我们评估了单基因表型相关 ClinVar 变异的频率分布。该研究利用了来自代表不同种族和地理位置的印度人群的 2795 个人(多个内部基因组学队列)的基因型数据集(Illumina 全球筛选阵列)。在全球筛选阵列的分析变体中,约 9%的变体是信息性的,它们的频率在公共数据库中要么以前不知道,要么代表性不足。这些变体与疾病有关,即先天性代谢缺陷、单基因糖尿病、遗传性癌症和各种其他遗传性疾病。我们还表明,与 1000 基因组计划(南亚人)相比,我们的研究队列在遗传上更能代表印度人群。我们创建了一个与莱顿开放变异数据库相关联的 ClinIndb 数据库,以帮助临床医生和研究人员进行诊断、咨询和开发与印度人群和在国外的印度人相关的适当遗传筛选工具。