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    Analysis of Single Nucleotide Polymorphisms of PRNP Gene in twenty-four Ethnic Groups of India

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    Human prion protein (PRNP), a copper binding sialoglycoprotein, is the causative agent for transmissible spongiform encephalopathies (TSEs), a group of neurodegenerative diseases that are generally associated with aggregation of amyloid plaques within the central nervous system disrupting the normal tissue structure (Liberski et al. 2001; Aguzzi et al. 2008). While more than 20 PRNP pathogenic mutations have been reported in patients, polymorphisms in the gene have been suggested to influence the incidence of the diseases with a Met129Val polymorphism (rs1799990) being the most important among them (Soldevila et al. 2006). This particular variant has been found to be associated with different prion related diseases as well as cognitive behaviour and long-term memory. Here, as a part of the effort from Indian Genome Variation Consortium (IGVC), we attempt to establish the baseline allele and genotype frequency of four PRNP SNPs including rs1799990 among 24 ethnic groups representing the Indian population. The allele and genotype frequency of rs1799990 is found to be different among different ethnic groups. This pilot study would serve as a platform for future epidemiologicalworks with respect to PRNP SNPs in India

    DataSheet1_Genetic Risk Prediction of COVID-19 Susceptibility and Severity in the Indian Population.docx

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    Host genetic variants can determine their susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS). Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we compute genetic risk scores in diverse Indian sub-populations that may predict differences in the severity of COVID-19 outcomes. We utilized the top 100 most significantly associated single-nucleotide polymorphisms (SNPs) from a GWAS by Pairo-Castineira et al. determining the genetic susceptibility to severe COVID-19 infection, to compute population-wise polygenic risk scores (PRS) for populations represented in the Indian Genome Variation Consortium (IGVC) database. Using a generalized linear model accounting for confounding variables, we found that median PRS was significantly associated (p −16) with COVID-19 mortality in each district corresponding to the population studied and had the largest effect on mortality (regression coefficient = 10.25). As a control we repeated our analysis on randomly selected 100 non-associated SNPs several times and did not find significant association. Therefore, we conclude that genetic susceptibility may play a major role in determining the differences in COVID-19 outcomes and mortality across the Indian sub-continent. We suggest that combining PRS with other observed risk-factors in a Bayesian framework may provide a better prediction model for ascertaining high COVID-19 risk groups and to design more effective public health resource allocation and vaccine distribution schemes.</p

    Table1_Genetic Risk Prediction of COVID-19 Susceptibility and Severity in the Indian Population.xlsx

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    Host genetic variants can determine their susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS). Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we compute genetic risk scores in diverse Indian sub-populations that may predict differences in the severity of COVID-19 outcomes. We utilized the top 100 most significantly associated single-nucleotide polymorphisms (SNPs) from a GWAS by Pairo-Castineira et al. determining the genetic susceptibility to severe COVID-19 infection, to compute population-wise polygenic risk scores (PRS) for populations represented in the Indian Genome Variation Consortium (IGVC) database. Using a generalized linear model accounting for confounding variables, we found that median PRS was significantly associated (p −16) with COVID-19 mortality in each district corresponding to the population studied and had the largest effect on mortality (regression coefficient = 10.25). As a control we repeated our analysis on randomly selected 100 non-associated SNPs several times and did not find significant association. Therefore, we conclude that genetic susceptibility may play a major role in determining the differences in COVID-19 outcomes and mortality across the Indian sub-continent. We suggest that combining PRS with other observed risk-factors in a Bayesian framework may provide a better prediction model for ascertaining high COVID-19 risk groups and to design more effective public health resource allocation and vaccine distribution schemes.</p

    Utilizing linkage disequilibrium information from Indian genome variation database for mapping mutations: SCA<sub>12</sub> case study

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    Stratification in heterogeneous populations poses an enormous challenge in linkage disequilibrium (LD) based identification of causal loci using surrogate markers. In this study, we demonstrate the enormous potential of endogamous Indian populations for mapping mutations in candidate genes using minimal SNPs, mainly due to larger regions of LD. We show this by a case study of the PPP2R2B gene (∼400 kb) that harbours a CAG repeat, expansion of which has been implicated in spinocerebellar ataxia type 12 (SCA12). Using LD information derived from Indian Genome Variation database (IGVdb) on populations which share similar ethnic and linguistic backgrounds as the SCA12 study population, we could map the causal loci using a minimal set of three SNPs, without the generation of additional basal data from the ethnically matched population. We could also demonstrate transferability of tagSNPs from a related HapMap population for mapping the mutation

    GENOMIC &apos;UNITY IN DIVERSITY&apos; OF INDIA AND ITS IMPLICATIONS FOR GENOMIC MEDICINE

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    The Indian Genome Variation Consortium is one of the most ambitious endeavors taken up by th

    IGVBrowser-a genomic variation resource from diverse Indian populations

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    The Indian Genome Variation Consortium (IGVC) project, an initiative of the Council for Scientific and Industrial Research, has been the first large-scale comprehensive study of the Indian population. One of the major aims of the project is to study and catalog the variations in nearly thousand candidate genes related to diseases and drug response for predictive marker discovery, founder identification and also to address questions related to ethnic diversity, migrations, extent and relatedness with other world population. The Phase I of the project aimed at providing a set of reference populations that would represent the entire genetic spectrum of India in terms of language, ethnicity and geography and Phase II in providing variation data on candidate genes and genome wide neutral markers on these reference set of populations. We report here development of the IGVBrowser that provides allele and genotype frequency data generated in the IGVC project. The database harbors 4229 SNPs from more than 900 candidate genes in contrasting Indian populations. Analysis shows that most of the markers are from genic regions. Further, a large fraction of genes are implicated in cardiovascular, metabolic, cancer and immune system-related diseases. Thus, the IGVC data provide a basal level variation data in Indian population to study genetic diseases and pharmacology. Additionally, it also houses data on ∼50 000 (Affy 50 K array) genome wide neutral markers in these reference populations. In IGVBrowser one can analyze and compare genomic variations in Indian population with those reported in HapMap along with annotation information from various primary data sources

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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