Literature DB >> 24834846

The genome revolution and its role in understanding complex diseases.

Marten H Hofker1, Jingyuan Fu2, Cisca Wijmenga2.   

Abstract

The completion of the human genome sequence in 2003 clearly marked the beginning of a new era for biomedical research. It spurred technological progress that was unprecedented in the life sciences, including the development of high-throughput technologies to detect genetic variation and gene expression. The study of genetics has become "big data science". One of the current goals of genetic research is to use genomic information to further our understanding of common complex diseases. An essential first step made towards this goal was by the identification of thousands of single nucleotide polymorphisms showing robust association with hundreds of different traits and diseases. As insight into common genetic variation has expanded enormously and the technology to identify more rare variation has become available, we can utilize these advances to gain a better understanding of disease etiology. This will lead to developments in personalized medicine and P4 healthcare. Here, we review some of the historical events and perspectives before and after the completion of the human genome sequence. We also describe the success of large-scale genetic association studies and how these are expected to yield more insight into complex disorders. We show how we can now combine gene-oriented research and systems-based approaches to develop more complex models to help explain the etiology of common diseases. This article is part of a Special Issue entitled: From Genome to Function.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Complex disease; Disease etiology; Functional analysis; Genetic variation; Genome

Year:  2014        PMID: 24834846     DOI: 10.1016/j.bbadis.2014.05.002

Source DB:  PubMed          Journal:  Biochim Biophys Acta        ISSN: 0006-3002


  18 in total

1.  Quality control, imputation and analysis of genome-wide genotyping data from the Illumina HumanCoreExome microarray.

Authors:  Jonathan R I Coleman; Jack Euesden; Hamel Patel; Amos A Folarin; Stephen Newhouse; Gerome Breen
Journal:  Brief Funct Genomics       Date:  2015-10-05       Impact factor: 4.241

2.  Lifestyle Medicine: A Brief Review of Its Dramatic Impact on Health and Survival.

Authors:  Balazs I Bodai; Therese E Nakata; William T Wong; Dawn R Clark; Steven Lawenda; Christine Tsou; Raymond Liu; Linda Shiue; Neil Cooper; Michael Rehbein; Benjamin P Ha; Anne Mckeirnan; Rajiv Misquitta; Pankaj Vij; Andrew Klonecke; Carmelo S Mejia; Emil Dionysian; Sean Hashmi; Michael Greger; Scott Stoll; Thomas M Campbell
Journal:  Perm J       Date:  2018

Review 3.  The ABCC6 Transporter as a Paradigm for Networking from an Orphan Disease to Complex Disorders.

Authors:  Eva Y G De Vilder; Mohammad Jakir Hosen; Olivier M Vanakker
Journal:  Biomed Res Int       Date:  2015-08-18       Impact factor: 3.411

4.  Haplotype-based approach to known MS-associated regions increases the amount of explained risk.

Authors:  Pouya Khankhanian; Pierre-Antoine Gourraud; Antoine Lizee; Douglas S Goodin
Journal:  J Med Genet       Date:  2015-07-16       Impact factor: 6.318

5.  Big genomics and clinical data analytics strategies for precision cancer prognosis.

Authors:  Ghim Siong Ow; Vladimir A Kuznetsov
Journal:  Sci Rep       Date:  2016-11-07       Impact factor: 4.379

6.  Yeast genetic interaction screen of human genes associated with amyotrophic lateral sclerosis: identification of MAP2K5 kinase as a potential drug target.

Authors:  Myungjin Jo; Ah Young Chung; Nozomu Yachie; Minchul Seo; Hyejin Jeon; Youngpyo Nam; Yeojin Seo; Eunmi Kim; Quan Zhong; Marc Vidal; Hae Chul Park; Frederick P Roth; Kyoungho Suk
Journal:  Genome Res       Date:  2017-06-08       Impact factor: 9.043

7.  Genetic susceptibility to multiple sclerosis: interactions between conserved extended haplotypes of the MHC and other susceptibility regions.

Authors:  D S Goodin; P Khankhanian; P A Gourraud; N Vince
Journal:  BMC Med Genomics       Date:  2021-07-10       Impact factor: 3.063

8.  The nature of genetic susceptibility to multiple sclerosis: constraining the possibilities.

Authors:  Douglas S Goodin
Journal:  BMC Neurol       Date:  2016-04-27       Impact factor: 2.474

9.  Systems Genetic Validation of the SNP-Metabolite Association in Rice Via Metabolite-Pathway-Based Phenome-Wide Association Scans.

Authors:  Yaping Lu; Yemao Liu; Xiaohui Niu; Qingyong Yang; Xuehai Hu; Hong-Yu Zhang; Jingbo Xia
Journal:  Front Plant Sci       Date:  2015-11-27       Impact factor: 5.753

10.  A non-threshold region-specific method for detecting rare variants in complex diseases.

Authors:  Ai-Ru Hsieh; Dao-Peng Chen; Amrita Sengupta Chattopadhyay; Ying-Ju Li; Chien-Ching Chang; Cathy S J Fann
Journal:  PLoS One       Date:  2017-11-30       Impact factor: 3.240

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