@article {45299, title = {Exome sequencing in families with severe mental illness identifies novel and rare variants in genes implicated in Mendelian neuropsychiatric syndromes.}, journal = {Psychiatry Clin Neurosci}, volume = {73}, year = {2019}, month = {2018 Oct 27}, pages = {11-19}, abstract = {

AIM: Severe Mental Illnesses, such as bipolar disorder and schizophrenia, are highly heritable, and have a complex pattern of inheritance. Genome wide association studies detect a part of the heritability, which can be attributed to common genetic variation. Examination of rare variants with Next Generation Sequencing may add to the understanding of genetic architecture of SMIs.

METHODS: We analyzed 32 ill subjects from 8 multiplex families; and 33 healthy individuals by whole exome sequencing. Prioritized variants were selected by a 3-step filtering process, which included deleteriousness by 5 in silico algorithms; sharing within families by affected individuals, rarity in South Asian sample estimated using the Exome Aggregation Consortium data and complete absence of these variants in a control-individuals from the same gene pool.

RESULTS: We identified 42 rare, non-synonymous deleterious variants (~5 per pedigree) in this study. None of the variants were shared across families, indicating a {\textquoteright}private{\textquoteright} mutational profile. Twenty (47.6\%) of the variant harboring genes were previously reported to contribute to the risk of diverse neuropsychiatric syndromes; 9 (21.4\%) of which were of Mendelian inheritance. These included genes carrying novel deleterious variants such as GRM1 gene implicated in Spinocerebellar ataxia 44 and NIPBL gene implicated in Cornelia de Lange syndrome.

CONCLUSION: NGS approaches in family-based studies are useful to identify novel and rare variants in genes for complex disorders like SMI. The findings of the study suggest a potential phenotypic burden of rare variants in Mendelian disease genes, indicating pleiotropic effects in the etiology of SMI. This article is protected by copyright. All rights reserved.

}, issn = {1440-1819}, doi = {10.1111/pcn.12788}, author = {Ganesh, Suhas and Ahmed P, Husayn and Nadella, Ravi Kumar and More, Ravi Prabhakar and Sheshadri, Manasa and Viswanath, Biju and Rao, Mahendra and Jain, Sanjeev and Mukherjee, Odity} } @article {51000, title = {INDEX-db: The Indian Exome Reference Database (Phase I).}, journal = {J Comput Biol}, year = {2019}, month = {2019 Jan 07}, abstract = {

Deep sequencing-based genetic mapping has greatly enhanced the ability to catalog variants with plausible disease association. Confirming how these identified variants contribute to specific disease conditions, across human populations, poses the next challenge. Differential selection pressure may impact the frequency of genetic variations, and thus detection of association with disease conditions, across populations. To understand genotype to phenotype correlations, it thus becomes important to first understand the spectrum of genetic variation within a population by creating a reference map. In this study, we report the development of phase I of a new database of genetic variations called INDian EXome database (INDEX-db), from the Indian population, with an aim to establish a centralized database of integrated information. This could be useful for researchers involved in studying disease mechanisms at clinical, genetic, and cellular levels.

}, issn = {1557-8666}, doi = {10.1089/cmb.2018.0199}, author = {Ahmed P, Husayn and V, Vidhya and More, Ravi Prabhakar and Viswanath, Biju and Jain, Sanjeev and Rao, Mahendra S and Mukherjee, Odity} }