Evidence map›Paper›PMID 28024155›Full record

ArticleNature genetics2017

A method for identifying genetic heterogeneity within phenotypically defined disease subgroups.

James Liley, John A Todd, Chris Wallace

Abstract read
In one paragraph

Article in Nature genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Pooled it
  2. Context-specific genetic effects inform endotypes and treatment in asthma.The Journal of allergy and clinical immunology · 2026
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  8. E96V Mutation in theInternational journal of molecular sciences · 2023
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  9. Rs864745 inFrontiers in endocrinology · 2022
    Article
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  11. FKBP5 Genotype Linked to Combined PTSD-Depression Symptom in Chinese Earthquake Survivors.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2019
    Article
  12. Article
  13. Article
  14. Article
  15. Article
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  17. 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

3 authors.

James LileyJDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
John A ToddJDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
Chris WallaceJDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-9755-1703

Funding

Medical Research Council MC_UP_1302/5Medical Research Council MC_UU_00002/4Wellcome Trust
6 · The paper itself

Abstract

Many common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximizing power in comparison to standard variant-by-variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post hoc identification of the contributing genetic variants. We demonstrate the method on a range of simulated and test data sets, for which expected results are already known. We investigate subgroups of individuals with type 1 diabetes (T1D) defined by autoantibody positivity, establishing evidence for differential genetic architecture with positivity for thyroid-peroxidase-specific antibody, driven generally by variants in known T1D-associated genomic regions.

Indexed as

Diabetes Mellitus, Type 1Genetic HeterogeneityGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyGenomicsHumansModels, GeneticPhenotype

Identifiers

PMID28024155
PMCPMC5357574

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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.