Evidence map›Paper›PMID 29429966›Full record

ArticleGenetics2018

Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

Luke R Lloyd-Jones, Matthew R Robinson, Jian Yang, Peter M Visscher

Abstract read
In one paragraph

Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

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

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  4. Genome-wide meta-analysis of alcohol use disorder in East Asians.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Pooled it
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  6. Pathway Analysis of Renal Cell Carcinoma Genome-Wide Association Studies Identifies Novel Associations.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
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  20. Controlling for polygenic genetic confounding in epidemiologic association studies.Proceedings of the National Academy of Sciences of the United States of America · 2024
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3 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

4 authors.

Luke R Lloyd-JonesInstitute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia l.lloydjones@uq.edu.au.ORCID 0000-0002-0229-0625
Matthew R RobinsonInstitute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia.
Jian YangInstitute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia.
Peter M VisscherInstitute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia.

Funding

A Resource for Genetic Epidemiology Research in Adult Health and AgingRC2AG036607 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI RISCH, NEIL J., SCHAEFER, CATHERINE ANN · 2009 to 2010
$24.8M
Increasing the power of GxE detection by using multi-locus genome-wide predictorsR21ES025052 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2015 to 2017
$434k
Medical Research Council MC_QA137853NIA NIH HHS RC2 AG036607NIEHS NIH HHS R21 ES025052Wellcome Trust
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure (

Indexed as

Genetic Association StudiesLinear ModelsModels, GeneticMultifactorial InheritanceQuantitative Trait, HeritableAlgorithmsComputer SimulationDiabetes Mellitus, Type 2Genome-Wide Association StudyHumansOdds Ratiocomplex diseasesgenome-wide association studieslinear mixed modelsORsummary statistics

Identifiers

PMID29429966
PMCPMC5887138

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.