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      Common Variants in CLDN2 and MORC4 Genes Confer Disease Susceptibility in Patients with Chronic Pancreatitis

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          Abstract

          A recent genome-wide association study (GWAS) identified association with variants in X-linked CLDN2 and MORC4, and PRSS1-PRSS2 loci with chronic pancreatitis (CP) in North American patients of European ancestry. We selected 9 variants from the reported GWAS and replicated the association with CP in Indian patients by genotyping 1807 unrelated Indians of Indo-European ethnicity, including 519 patients with CP and 1288 controls. The etiology of CP was idiopathic in 83.62% and alcoholic in 16.38% of 519 patients. Our study confirmed a significant association of 2 variants in CLDN2 gene (rs4409525—OR 1.71, P = 1.38 x 10 -09; rs12008279—OR 1.56, P = 1.53 x 10 -04) and 2 variants in MORC4 gene (rs12688220—OR 1.72, P = 9.20 x 10 -09; rs6622126—OR 1.75, P = 4.04x10 -05) in Indian patients with CP. We also found significant association at PRSS1-PRSS2 locus (OR 0.60; P = 9.92 x 10 -06) and SAMD12-TNFRSF11B (OR 0.49, 95% CI [0.31–0.78], P = 0.0027). A variant in the gene MORC4 (rs12688220) showed significant interaction with alcohol (OR for homozygous and heterozygous risk allele -14.62 and 1.51 respectively, P = 0.0068) suggesting gene-environment interaction. A combined analysis of the genes CLDN2 and MORC4 based on an effective risk allele score revealed a higher percentage of individuals homozygous for the risk allele in CP cases with 5.09 fold enhanced risk in individuals with 7 or more effective risk alleles compared with individuals with 3 or less risk alleles ( P = 1.88 x 10 -14). Genetic variants in CLDN2 and MORC4 genes were associated with CP in Indian patients.

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          Most cited references28

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          PINA v2.0: mining interactome modules

          The Protein Interaction Network Analysis (PINA) platform is a comprehensive web resource, which includes a database of unified protein–protein interaction data integrated from six manually curated public databases, and a set of built-in tools for network construction, filtering, analysis and visualization. The second version of PINA enhances its utility for studies of protein interactions at a network level, by including multiple collections of interaction modules identified by different clustering approaches from the whole network of protein interactions (‘interactome’) for six model organisms. All identified modules are fully annotated by enriched Gene Ontology terms, KEGG pathways, Pfam domains and the chemical and genetic perturbations collection from MSigDB. Moreover, a new tool is provided for module enrichment analysis in addition to simple query function. The interactome data are also available on the web site for further bioinformatics analysis. PINA is freely accessible at http://cbg.garvan.unsw.edu.au/pina/.
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            SAM domains: uniform structure, diversity of function.

            Sterile alpha motif (SAM) domains are known to exhibit diverse protein-protein interaction modes. They can form multiple self-association architectures and also bind to various non-SAM domain-containing proteins. Surprising new work adds a completely unanticipated function for some SAM domains - the ability to bind RNA. Such functional diversity within a homologous protein family presents a significant challenge for bioinformatic function assignment.
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              Impact of Common Variants of PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 on the Risk of Type 2 Diabetes in 5,164 Indians

              OBJECTIVE Common variants in PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 genes have been shown to be associated with type 2 diabetes in European populations by genome-wide association studies. We have studied the association of common variants in these eight genes with type 2 diabetes and related traits in Indians by combining the data from two independent case–control studies. RESEARCH DESIGN AND METHODS We genotyped eight single nucleotide polymorphisms (PPARG-rs1801282, KCNJ11-rs5219, TCF7L2-rs7903146, SLC30A8-rs13266634, HHEX-rs1111875, CDKN2A-rs10811661, IGF2BP2-rs4402960, and CDKAL1-rs10946398) in 5,164 unrelated Indians of Indo-European ethnicity, including 2,486 type 2 diabetic patients and 2,678 ethnically matched control subjects. RESULTS We confirmed the association of all eight loci with type 2 diabetes with odds ratio (OR) ranging from 1.18 to 1.89 (P = 1.6 × 10−3 to 4.6 × 10−34). The strongest association with the highest effect size was observed for TCF7L2 (OR 1.89 [95% CI 1.71–2.09], P = 4.6 × 10−34). We also found significant association of PPARG and TCF7L2 with homeostasis model assessment of β-cell function (P = 6.9 × 10−8 and 3 × 10−4, respectively), which looked consistent with recessive and under-dominant models, respectively. CONCLUSIONS Our study replicates the association of well-established common variants with type 2 diabetes in Indians and shows larger effect size for most of them than those reported in Europeans.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 January 2016
                2016
                : 11
                : 1
                : e0147345
                Affiliations
                [1 ]Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
                [2 ]Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
                [3 ]Department of Gastroenterology, All India Institute of Medical Sciences, New Delhi, India
                [4 ]Human Genetics Unit, Indian Statistical Institute, Kolkata, India
                [5 ]Department of Gastroenterology, Institute of Post Graduate Medical Education and Research, Kolkata, India
                [6 ]Department of Gastroenterology, Sanjay Gandhi Post-graduate Institute of Medical Sciences, Lucknow, India
                [7 ]Department of Gastroenterology, Post-graduate Institute of Medical Education & Research, Chandigarh, India
                Odense University Hospital, DENMARK
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PKG DB. Performed the experiments: SJM RL RKG. Analyzed the data: AKG IK. Contributed reagents/materials/analysis tools: S. Midha RD KD S. Mohindra SR DKB. Wrote the paper: AKG AA PB SJM IK RL RKG SG PKG DB.

                [¤]

                Current address: School of Biotechnology, Jawaharlal Nehru University, New Delhi, India

                ¶ Membership of the INDIPAN and INDICO Consortium is listed in the Acknowledgments.

                Article
                PONE-D-15-27029
                10.1371/journal.pone.0147345
                4731142
                26820620
                55086b52-9e4b-4138-89e0-b164f89ef630
                © 2016 Giri et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 June 2015
                : 31 December 2015
                Page count
                Figures: 2, Tables: 6, Pages: 13
                Funding
                This work was supported by "Genome Wide Association Study of Chronic Pancreatitis" (GAP-83) funded by Department of Biotechnology (DBT) and "Center for Cardiovascular and Metabolic Disease Research" (CARDIOMED) (BSC-0122-3), funded by the Council of Scientific and Industrial Research (CSIR), Government of India.
                Categories
                Research Article
                Medicine and Health Sciences
                Gastroenterology and Hepatology
                Pancreatitis
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Alleles
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Variant Genotypes
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Biology and Life Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Medicine and Health Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Human Genetics
                Genome-Wide Association Studies
                Medicine and Health Sciences
                Clinical Genetics
                X-Linked Traits
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Linkage
                Sex Linkage
                X-Linked Traits
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. SNP data are available through Dryad ( http://dx.doi.org/10.5061/dryad.4t9f3).

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