Evidence map›Paper›PMID 16642430›Full record

ArticleAmerican journal of human genetics2006

Contrasting linkage-disequilibrium patterns between cases and controls as a novel association-mapping method.

Dmitri V Zaykin, Zhaoling Meng, Margaret G Ehm

Abstract read
In one paragraph

Article in American journal of human genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

53 citing papers in PubMed.

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  5. Genetic and regulatory architecture of Alzheimer's disease in theAlzheimer's & dementia (Amsterdam, Netherlands) · 2020
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  6. Haplotype architecture of the Alzheimer's risk in theAlzheimer's & dementia (Amsterdam, Netherlands) · 2020
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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

3 authors.

Dmitri V ZaykinNational Institute of Environmental Health Sciences, National Institutes of Health. Electronic address: zaykind@niehs.nih.gov.
Zhaoling MengDepartment of Biostatistics and Programming, Sanofi-Aventis, Bridgewater, NJ.
Margaret G EhmDepartment of Genetics Research, GlaxoSmithKline, Research Triangle Park, NC.

Funding

Statistical, population genetics and genetic epidemiologyZ01ES101866 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI ZAYKIN, DMITRI V · 2005 to 2008
$911k
Intramural NIH HHS Z01 ES101866
6 · The paper itself

Abstract

Identification and description of genetic variation underlying disease susceptibility, efficacy, and adverse reactions to drugs remains a difficult problem. One of the important steps in the analysis of variation in a candidate region is the characterization of linkage disequilibrium (LD). In a region of genetic association, the extent of LD varies between the case and the control groups. Separate plots of pairwise standardized measures of LD (e.g., D') for cases and controls are often presented for a candidate region, to graphically convey case-control differences in LD. However, the observed graphic differences lack statistical support. Therefore, we suggest the "LD contrast" test to compare whole matrices of disequilibrium between two samples. A common technique of assessing LD when the haplotype phase is unobserved is the expectation-maximization algorithm, with the likelihood incorporating the assumption of Hardy-Weinberg equilibrium (HWE). This approach presents a potential problem in that, in the region of genetic association, the HWE assumption may not hold when samples are selected on the basis of phenotypes. Here, we present a computationally feasible approach that does not assume HWE, along with graphic displays and a statistical comparison of pairwise matrices of LD between case and control samples. LD-contrast tests provide a useful addition to existing tools of finding and characterizing genetic associations. Although haplotype association tests are expected to provide superior power when susceptibilities are primarily determined by haplotypes, the LD-contrast tests demonstrate substantially higher power under certain haplotype-driven disease models.

Indexed as

Case-Control StudiesLinkage DisequilibriumPolymorphism, Single NucleotideChromosome MappingComputational BiologyComputer SimulationCytochrome P-450 CYP2D6Genetic MarkersGenetic Predisposition to DiseaseGenetic VariationHaplotypesHumansModels, StatisticalQuantitative Trait, HeritableCytochrome P-450 CYP2D6Genetic Markers

Identifiers

PMID16642430
PMCPMC1474029

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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.