The genome revolution and its role in understanding complex diseases

Marten H. Hofker*, Jingyuan Fu, Cisca Wijmenga

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

42 Citations (Scopus)

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. (C) 2014 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)1889-1895
Number of pages7
JournalBiochimica et biophysica acta-Molecular basis of disease
Volume1842
Issue number10
DOIs
Publication statusPublished - Oct-2014

Keywords

  • Genome
  • Genetic variation
  • Complex disease
  • Disease etiology
  • Functional analysis
  • GENETIC-LINKAGE MAP
  • WIDE ASSOCIATION
  • CHILDHOOD OBESITY
  • HUMAN-POPULATIONS
  • APOLIPOPROTEIN-E
  • STEM-CELLS
  • COMMON
  • VARIANT
  • RISK
  • EXPRESSION

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