Evidence map›Paper›PMID 22703998›Full record

ArticleGenome biology2012

Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms.

Fredrik Barrenäs, Sreenivas Chavali, Alexessander Couto Alves, Lachlan Coin, Marjo-Riitta Jarvelin, Rebecka Jörnsten, Michael A Langston, Adaikalavan Ramasamy, Gary Rogers, Hui Wang and 1 more

Abstract read
In one paragraph

Article in Genome biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Investigating the Causal Effects of Exercise-Induced Genes on Sarcopenia.International journal of molecular sciences · 2024
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  16. Proteomics ofMolecular & cellular proteomics : MCP · 2018
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  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Fredrik BarrenäsThe Centre for Individualized Medication, Linköping University Hospital, Linköping University, Linköping, Sweden.
Sreenivas Chavali
Alexessander Couto Alves
Lachlan Coin
Marjo-Riitta Jarvelin
Rebecka Jörnsten
Michael A Langston
Adaikalavan Ramasamy
Gary Rogers
Hui Wang
Mikael Benson

Funding

Training/Education CoreP20MD000516 · NIMHD · MEHARRY MEDICAL COLLEGE · PI ZOOROB, ROGER J · 2003 to 2013
$14.2M
Data Structures, Algorithms and Tools for Ontological DiscoveryR01AA018776 · NIAAA · JACKSON LABORATORY · PI CHESLER, ELISSA J · 2010 to 2019
$3.9M
NIAAA NIH HHS R01 AA018776NIAAA NIH HHS R01-AA-018776NIMHD NIH HHS 3P20MD000516-07S1
6 · The paper itself

Abstract

backgroundComplex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.

resultsWe identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.

conclusionsModules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.

Indexed as

Genome, HumanGenome-Wide Association StudyPolymorphism, Single NucleotideProtein Interaction MapsDatabases, GeneticFibroblast Growth Factor 2Gene Expression ProfilingGene Expression RegulationGene Regulatory NetworksGenetic PleiotropyGenetic Predisposition to DiseaseHumansInflammationOligonucleotide Array Sequence AnalysisRhinitis, Allergic, SeasonalRNA, Small InterferingFibroblast Growth Factor 2RNA, Small Interfering

Identifiers

PMID22703998
PMCPMC3446318

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.