Evidence map›Paper›PMID 23193196›Full record

ArticleHuman molecular genetics2013

Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis.

S Hong Lee, Denise Harold, Dale R Nyholt, ANZGene Consortium, International Endogene Consortium, Genetic and Environmental Risk for Alzheimer's disease Consortium, Michael E Goddard, Krina T Zondervan, Julie Williams, Grant W Montgomery and 2 more

Abstract read
In one paragraph

Article in Human molecular genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
133citing papers in PubMed, 11 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

133 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  10. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2016
    Pooled it
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  17. Can classical statistics and deep learning converge on explainable, causally driven target discovery?DNA research : an international journal for rapid publication of reports on genes and genomes · 2025
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73 more citing papers are in PubMed but not listed here.

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

12 authors.

S Hong LeeThe University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia.
Denise Harold
Dale R Nyholt
ANZGene Consortium
International Endogene Consortium
Genetic and Environmental Risk for Alzheimer's disease Consortium
Michael E Goddard
Krina T Zondervan
Julie Williams
Grant W Montgomery
Naomi R Wray
Peter M Visscher

Funding

Medical Research Council G0902227Medical Research Council MC_U123160651Medical Research Council MC_U123192748Medical Research Council MR/K013041/1Wellcome Trust 084766Wellcome Trust 085235Wellcome Trust 090532Wellcome Trust 095317Wellcome Trust WT085235/Z/08/Z
6 · The paper itself

Abstract

Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

Indexed as

Models, GeneticPolymorphism, Single NucleotideAlzheimer DiseaseCase-Control StudiesChromosomes, HumanEndometriosisFemaleGene FrequencyGenetic VariationGenotypeHumansMaleMolecular Sequence AnnotationMultifactorial InheritanceMultiple Sclerosis

Identifiers

PMID23193196
PMCPMC3554206

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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.