Evidence map›Paper›PMID 22839596›Full record

ArticleBioData mining2012

Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS.

Nora Chung Kim, Peter C Andrews, Folkert W Asselbergs, H Robert Frost, Scott M Williams, Brent T Harris, Cynthia Read, Kathleen D Askland, Jason H Moore

Abstract read
In one paragraph

Article in BioData mining, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Article
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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

9 authors.

Nora Chung KimInstitute for Quantitative Biomedical Sciences, Department of Genetics, Dartmouth Medical School, One Medical Center Dr,, Lebanon, NH 03756, USA. Jason.H.Moore@dartmouth.edu.
Peter C Andrews
Folkert W Asselbergs
H Robert Frost
Scott M Williams
Brent T Harris
Cynthia Read
Kathleen D Askland
Jason H Moore

Funding

Quantitative Biology Research InstituteP20GM103534 · NIGMS · DARTMOUTH COLLEGE · PI AMOS, CHRISTOPHER I. · 2012 to 2016
$8.6M
Bioinformatics Strategies for Genome-Wide Association StudiesR01LM010098 · NLM · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H., WILLIAMS, SCOTT MATTHEW · 2009 to 2023
$5.1M
Bioinformatics Strategies: Biodefense Vaccine ResearchR01AI059694 · NIAID · DARTMOUTH COLLEGE · PI MOORE, JASON H. · 2004 to 2012
$4.5M
Machine Learning Prediction of Cancer SusceptibilityR01LM009012 · NLM · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H. · 2006 to 2014
$3.3M
NIAID NIH HHS R01 AI059694NIGMS NIH HHS P20 GM103534NLM NIH HHS R01 LM009012NLM NIH HHS R01 LM010098
6 · The paper itself

Abstract

backgroundIt is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO).

resultsWe first estimated all pairwise additive and nonadditive genetic effects using the multifactor dimensionality reduction (MDR) method that makes few assumptions about the underlying genetic model. Statistical significance was evaluated using permutation testing in two genome-wide association studies of ALS. The detection data consisted of 276 subjects with ALS and 271 healthy controls while the replication data consisted of 221 subjects with ALS and 211 healthy controls. Both studies included genotypes from approximately 550,000 single-nucleotide polymorphisms (SNPs). Each SNP was mapped to a gene if it was within 500 kb of the start or end. Each SNP was assigned a p-value based on its strongest joint effect with the other SNPs. We then used the Exploratory Visual Analysis (EVA) method and software to assign a p-value to each gene based on the overabundance of significant SNPs at the α = 0.05 level in the gene. We also used EVA to assign p-values to each GO group based on the overabundance of significant genes at the α = 0.05 level. A GO category was determined to replicate if that category was significant at the α = 0.05 level in both studies. We found two GO categories that replicated in both studies. The first, 'Regulation of Cellular Component Organization and Biogenesis', a GO Biological Process, had p-values of 0.010 and 0.014 in the detection and replication studies, respectively. The second, 'Actin Cytoskeleton', a GO Cellular Component, had p-values of 0.040 and 0.046 in the detection and replication studies, respectively.

conclusionsPathway analysis of pairwise genetic associations in two GWAS of sporadic ALS revealed a set of genes involved in cellular component organization and actin cytoskeleton, more specifically, that were not reported by prior GWAS. However, prior biological studies have implicated actin cytoskeleton in ALS and other motor neuron diseases. This study supports the idea that pathway-level analysis of GWAS data may discover important associations not revealed using conventional one-SNP-at-a-time approaches.

Identifiers

PMID22839596
PMCPMC3463436

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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.