Evidence map›Paper›PMID 26110739›Full record

ArticleBMC genomics2015

Insights from GWAS: emerging landscape of mechanisms underlying complex trait disease.

Lipika R Pal, Chen-Hsin Yu, Stephen M Mount, John Moult

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

11 citing papers in PubMed, 29 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Lipika R Pal
Chen-Hsin Yu
Stephen M Mount
John Moult
University of Maryland, College Park · USNational Institute of Standards and Technology · USUniversity of Maryland, Baltimore · US

Funding

Analysis of the Functional Impact of Coding Region SNPsR01LM007174 · NLM · UNIV OF MARYLAND, COLLEGE PARK · PI MOULT, JOHN · 2001 to 2010
$2.5M
Morphogenetic Tissue Movements in Early EmbryosR01GM102801 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI CZIROK, ANDRAS · 2014 to 2017
$1.1M
Identification and in vitro experimental investigation of missense SNPs implicateR01GM102810 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI HERZBERG, OSNAT, MOULT, JOHN · 2012 to 2015
$1.1M
Mechanisms underlying complex trait human diseaseR01GM104436 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI MOULT, JOHN · 2013 to 2016
$1.1M
NIGMS NIH HHS GM102801NIGMS NIH HHS GM104436NIGMS NIH HHS R01 GM102810NIGMS NIH HHS R01 GM104436NLM NIH HHS LM007174
6 · The paper itself

Abstract

backgroundThere are now over 2000 loci in the human genome where genome wide association studies (GWAS) have found one or more SNPs to be associated with altered risk of a complex trait disease. At each of these loci, there must be some molecular level mechanism relevant to the disease. What are these mechanisms and how do they contribute to disease?

resultsHere we consider the roles of three primary mechanism classes: changes that directly alter protein function (missense SNPs), changes that alter transcript abundance as a consequence of variants close-by in sequence, and changes that affect splicing. Missense SNPs are divided into those predicted to have a high impact on in vivo protein function, and those with a low impact. Splicing is divided into SNPs with a direct impact on splice sites, and those with a predicted effect on auxiliary splicing signals. The analysis was based on associations found for seven complex trait diseases in the classic Wellcome Trust Case Control Consortium (WTCCC1) GWA study and subsequent studies and meta-analyses, collected from the GWAS catalog. Linkage disequilibrium information was used to identify possible candidate SNPs for involvement in disease mechanism in each of the 356 loci associated with these seven diseases. With the parameters used, we find that 76% of loci have at least of these mechanisms. Overall, except for the low incidence of direct impact on splice sites, the mechanisms are found at similar frequencies, with changes in transcript abundance the most common. But the distribution of mechanisms over diseases varies markedly, as does the fraction of loci with assigned mechanisms. Many of the implicated proteins have previously been suggested as relevant, but the specific mechanism assignments are new. In addition, a number of new disease relevant proteins are proposed.

conclusionsThe high fraction of GWAS loci with proposed mechanisms suggests that these classes of mechanism play a major role. Other mechanism types, such as variants affecting expression of genes remote in the DNA sequence, will contribute in other loci. Each of the identified putative mechanisms provides a hypothesis for further investigation.

Indexed as

Gene ExpressionGenome-Wide Association StudyMutation, MissensePolymorphism, Single NucleotideRNA SplicingGenotypeHumansMetabolic DiseasesPhenotypeProtein IsoformsQuantitative Trait LociProtein Isoforms

Identifiers

PMID26110739
PMCPMC4480957
OpenAlexW1509816035

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.