Cited by 621Bioinformatics and Genomic NetworksGenetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Systems genetics approaches to understand complex traits

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Civelek, Mete, Lusis, Aldons J.·2014·Nature Reviews Genetics

Abstract

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease.

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  • Incorporating multi-omic measures into network and system analyses will address gaps in knowledge about molecular mediation, gene-environment interactions, and longitudinal effects in chronic disease development.

    “Incorporating multi-omic measures of population samples into multidimensional network and system analyses (Figure 1), will address the gaps in our current knowledge of molecular mediation mechanisms, gene-environment interactions, and longitudinal effects during the development of chronic diseases”
  • One of the greatest challenges is to systematically infer causality in molecular networks with a systems genetics approach.

    “One of the greatest challenges is to systematically infer causality in molecular networks with a systems genetics approach168,169.”
  • Most molecular profiling studies, especially those using post-mortem tissue, cannot show causality without follow-up controlled experiments or genetic evidence.

    “As far as causality is concerned, most molecular profiling studies, especially those using post-mortem tissue, cannot show causality without follow-up controlled experiments or genetic evidence169–171.”

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  1. [63]Pearl J Causality Cambridge Univ. Press 2009

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Authors
Civelek, M., & Lusis, A. J.
Affiliations
University of California, Los Angeles (US)
Corresponding author
Lusis, Aldons J.
Venue
Nature Reviews Genetics
Published
2013-12-03
Volume
15
Issue
1
Pages
34-48
ISSN
  • 1471-0056 (ISSN-L)
  • 1471-0064
OpenAlex
W2006810478
Cited by
621
References
141
Citations by year
2026: 16 · 2025: 38 · 2024: 37 · 2023: 44 · 2022: 35 · 2021: 59 · 2020: 39 · 2019: 57 · 2018: 54 · 2017: 68 · 2016: 71 · 2015: 71 · 2014: 30 · 2013: 1
FWCI
5.42
Type
journal article
Language
en
Open access
Locations
  • Nature Reviews Genetics (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • National Institutes of Health
  • National Heart, Lung, and Blood Institute (HL3 0568, T32 HL-69766, HL28481, R01HL094322, P01HL030568, R21HL110667, HL110667, HL094322, T32HL069766, R01HL123295, P01HL028481)
  • National Center for Chronic Disease Prevention and Health Promotion (DP3 D094311)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
systems genetics, complex traits, endophenotypes, gene-environment interaction, gene-gene interaction, transcriptomics, proteomics, metabolomics, molecular networks, disease susceptibility, genome-wide association study, human disease
MeSH terms
Animals, Epistasis, Genetic, Gene Expression Regulation, Genetic Techniques, Humans, Models, Genetic, Phenotype, Genetic Predisposition to Disease, Systems Biology, Gene Regulatory Networks, Genome-Wide Association Study, Genetic Loci

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