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Esai Selvan, M.

Publications and source records attributed to Esai Selvan, M..

2 recordsLinked to original sources

ImmuneRegulation: A web-based tool for identifying human immune regulatory elements

Humans can vary considerably in their healthy immune phenotypes and in their immune responses to various stimuli. We have developed an interactive web-based tool, ImmuneRegulation, to enable discovery of human regulatory elements that drive some of the phenotypic differences observed in gene expression profiles. ImmuneRegulation currently provides the largest centrally integrated resource available in the literature on transcriptome regulation in whole blood and blood cell types, including genotype data from 23,040 individuals, with associated gene expression data from 30,562 experiments, that provide genetic variant-gene expression associations on [~]200 million eQTLs. In addition, it includes 14 million transcription factor (TF) binding region hits extracted from 1945 TF ChIP-seq peaks and the latest GWAS catalog of 67,230 published SNP-trait associations. Users can interactively explore ImmuneRegulation to visualize and discover associations between their gene(s) of interest and their regulators (genetic variants or transcription factors) across multiple cohorts and studies. These regulators can explain cohort or cell type dependent gene expression variations and may be critical in selecting the ideal cohorts or cell types for follow-up studies. Overall, ImmuneRegulation aims to contribute to our understanding of the effects of eQTLs and TFs on heterogeneous transcriptional responses reported in studies on the blood; in the development of molecular signatures of immune response; and facilitate their future application in patient management. ImmuneRegulation is freely available at http://icahn.mssm.edu/immuneregulation.

immunology↗

Rare germline variants in Fanconi Anemia genes increase risk for squamous lung cancer

PurposeLung cancer is the leading cause of cancer deaths worldwide, with substantially better prognosis in early stage as opposed to late stage disease. Identifying genetic factors for lung squamous carcinoma (SqCC) risk will enable their use in risk stratification, and personalized intensive surveillance, early detection, and prevention strategies for high-risk individuals.\n\nStudy Design and ParticipantsWe analyzed whole-exome sequencing datasets of 318 cases and 814 controls (discovery cohort) and then validated our findings in an independent cohort of 444 patients and 3,479 controls (validation cohort), all of European descent, totaling a combined cohort of 765 cases and 4,344 controls. We focused on rare pathogenic variants found in the ClinVar database and used penalized logistic regression to identify genes in which such variants are enriched in cases. All statistical tests were two-sided.\n\nResultsWe observed an overall enrichment of rare, deleterious germline variants in Fanconi Anemia genes in cases with SqCC (joint analysis OR=3.08, p=1.4e-09, 95% confidence interval [CI]=2.2-4.3). Consistent with previous studies, BRCA2 in particular exhibited an increased overall burden of rare, deleterious variants (joint OR=3.2, p=8.7e-08, 95% CI=2.1-4.7). More importantly, rare deleterious germline variants were enriched in Fanconi Anemia genes even without the BRCA2 rs11571833 variant that is strongly enriched in lung SqCC cases (joint OR=2.76, p=7.0e-04, 95% CI=1.6-4.7).\n\nConclusionsThese findings can be used towards the development of a genetic diagnostic test in the clinic to identify SqCC high-risk individuals, who can benefit from personalized programs, improving prognosis.

genomics↗