Evidence map›Paper›PMID 15877278›Full record

ArticleAmerican journal of human genetics2005

Joint modeling of linkage and association: identifying SNPs responsible for a linkage signal.

Mingyao Li, Michael Boehnke, Goncalo R Abecasis

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in American journal of human genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 1 pooled it
11.3field-weighted citation impact, top 1% 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

71 citing papers in PubMed, 1 synthesis or guideline pooled it, 124 citations in OpenAlex.

  1. Pooled it
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  8. Genetics of Smoking Behaviors in American Indians.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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  12. Fine mapping under linkage peaks for symptomatic or asymptomatic outcomes of Leishmania infantum infection in Brazil.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2016
    Article
  13. Relationship between cytokine expression patterns and clinical outcomes: two population-based birth cohorts.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2015
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  14. Article
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  16. Fine mapping on chromosome 13q32-34 and brain expression analysis implicates MYO16 in schizophrenia.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2014
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11 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

3 authors at 1 institution in 2 countries.

Mingyao LiDepartment of Biostatistics, School of Public Health, and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109-2029, USA. myli@umich.edu
Michael Boehnke
Goncalo R Abecasis
University of Michigan · US

Funding

DESIGN AND ANALYSIS OF HUMAN GENE MAPPING STUDIESR01HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 1993 to 2016
$5.5M
Computational and Statistical Models for Human PedigreesR01HG002651 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2003 to 2008
$2.9M
Design and Analysis of Human Gene Mapping StudiesR56HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 2017 to 2017
$400k
DESIGN ISSUES IN GENETIC LINKAGE AND SEGREGATION STUDIESR29HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL · 1990 to 1992
–
NHGRI NIH HHS HG00376NHGRI NIH HHS HG02651NHGRI NIH HHS R01 HG000376NHGRI NIH HHS R01 HG002651NHGRI NIH HHS R56 HG000376
6 · The paper itself

Abstract

Once genetic linkage has been identified for a complex disease, the next step is often association analysis, in which single-nucleotide polymorphisms (SNPs) within the linkage region are genotyped and tested for association with the disease. If a SNP shows evidence of association, it is useful to know whether the linkage result can be explained, in part or in full, by the candidate SNP. We propose a novel approach that quantifies the degree of linkage disequilibrium (LD) between the candidate SNP and the putative disease locus through joint modeling of linkage and association. We describe a simple likelihood of the marker data conditional on the trait data for a sample of affected sib pairs, with disease penetrances and disease-SNP haplotype frequencies as parameters. We estimate model parameters by maximum likelihood and propose two likelihood-ratio tests to characterize the relationship of the candidate SNP and the disease locus. The first test assesses whether the candidate SNP and the disease locus are in linkage equilibrium so that the SNP plays no causal role in the linkage signal. The second test assesses whether the candidate SNP and the disease locus are in complete LD so that the SNP or a marker in complete LD with it may account fully for the linkage signal. Our method also yields a genetic model that includes parameter estimates for disease-SNP haplotype frequencies and the degree of disease-SNP LD. Our method provides a new tool for detecting linkage and association and can be extended to study designs that include unaffected family members.

Indexed as

Genetic LinkageModels, GeneticModels, StatisticalPolymorphism, Single NucleotideAllelesChromosome MappingComputer SimulationGene FrequencyGenetic MarkersGenetic Predisposition to DiseaseGenetics, MedicalHaplotypesHumansLikelihood FunctionsLinkage DisequilibriumResearch DesignGenetic Markers

Identifiers

PMID15877278
PMCPMC1196453
OpenAlexW2128995957

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.