13
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Human gene and disease associations for clinical‐genomics and precision medicine research

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We are entering the era of personalized medicine in which an individual's genetic makeup will eventually determine how a doctor can tailor his or her therapy. Therefore, it is becoming critical to understand the genetic basis of common diseases, for example, which genes predispose and rare genetic variants contribute to diseases, and so on. Our study focuses on helping researchers, medical practitioners, and pharmacists in having a broad view of genetic variants that may be implicated in the likelihood of developing certain diseases. Our focus here is to create a comprehensive database with mobile access to all available, authentic and actionable genes, SNPs, and classified diseases and drugs collected from different clinical and genomics databases worldwide, including Ensembl, GenCode, ClinVar, GeneCards, DISEASES, HGMD, OMIM, GTR, CNVD, Novoseek, Swiss‐Prot, LncRNADisease, Orphanet, GWAS Catalog, SwissVar, COSMIC, WHO, and FDA. We present a new cutting‐edge gene‐SNP‐disease‐drug mobile database with a smart phone application, integrating information about classified diseases and related genes, germline and somatic mutations, and drugs. Its database includes over 59 000 protein‐coding and noncoding genes; over 67 000 germline SNPs and over a million somatic mutations reported for over 19 000 protein‐coding genes located in over 1000 regions, published with over 3000 articles in over 415 journals available at the PUBMED; over 80 000 ICDs; over 123 000 NDCs; and over 100 000 classified gene‐SNP‐disease associations. We present an application that can provide new insights into the information about genetic basis of human complex diseases and contribute to assimilating genomic with phenotypic data for the availability of gene‐based designer drugs, precise targeting of molecular fingerprints for tumor, appropriate drug therapy, predicting individual susceptibility to disease, diagnosis, and treatment of rare illnesses are all a few of the many transformations expected in the decade to come.

          Related collections

          Most cited references94

          • Record: found
          • Abstract: found
          • Article: not found

          SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

          Summary The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

            The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Patterns of somatic mutation in human cancer genomes.

              Cancers arise owing to mutations in a subset of genes that confer growth advantage. The availability of the human genome sequence led us to propose that systematic resequencing of cancer genomes for mutations would lead to the discovery of many additional cancer genes. Here we report more than 1,000 somatic mutations found in 274 megabases (Mb) of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancers reflecting different exposures, DNA repair defects and cellular origins. Most somatic mutations are likely to be 'passengers' that do not contribute to oncogenesis. However, there was evidence for 'driver' mutations contributing to the development of the cancers studied in approximately 120 genes. Systematic sequencing of cancer genomes therefore reveals the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.
                Bookmark

                Author and article information

                Contributors
                zahmed@ifh.rutgers.edu
                Journal
                Clin Transl Med
                Clin Transl Med
                10.1002/(ISSN)2001-1326
                CTM2
                Clinical and Translational Medicine
                John Wiley and Sons Inc. (Hoboken )
                2001-1326
                03 May 2020
                Jan-Dec 2020
                : 10
                : 1 ( doiID: 10.1002/ctm2.v10.1 )
                : 297-318
                Affiliations
                [ 1 ] Institute for Health, Health Care Policy and Aging Research, Rutgers The State University of New Jersey New Brunswick New Jersey USA
                [ 2 ] Department of Medicine, Rutgers Robert Wood Johnson Medical School Rutgers Biomedical and Health Sciences New Brunswick New Jersey USA
                [ 3 ] Rutgers Cancer Institute of New Jersey, Rutgers The State University of New Jersey New Brunswick New Jersey USA
                Author notes
                [*] [* ] Correspondence

                Zeeshan Ahmed, Institute for Health, Health Care Policy and Aging Research, Rutgers, The State University of New Jersey, 112 Paterson Street, New Brunswick, NJ 08901, USA.

                Email: zahmed@ 123456ifh.rutgers.edu

                Author information
                https://orcid.org/0000-0002-7065-1699
                Article
                CTM228
                10.1002/ctm2.28
                7240856
                32508008
                e8564c7b-b7b7-426d-bc09-2b90f455bf80
                © 2020 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 February 2020
                : 02 April 2020
                : 03 April 2020
                Page count
                Figures: 7, Tables: 4, Pages: 22, Words: 13336
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                January/December 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.2 mode:remove_FC converted:21.05.2020

                Medicine
                clinical‐genomics,database,diseases,drugs,genes,germline mutations,precision medicine,somatic mutations

                Comments

                Comment on this article