Evidence map›Paper›PMID 21754915›Full record

ArticleFrontiers in genetics2011

Capitalizing on admixture in genome-wide association studies: a two-stage testing procedure and application to height in African-Americans.

Guolian Kang, Guimin Gao, Sanjay Shete, David T Redden, Bao-Li Chang, Timothy R Rebbeck, Jill S Barnholtz-Sloan, Nicholas M Pajewski, David B Allison

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
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

9 authors at 5 institutions in 1 country.

Guolian KangSection on Statistical Genetics, Department of Biostatistics, The University of Alabama at Birmingham, Birmingham, AL, USA.
Guimin Gao
Sanjay Shete
David T Redden
Bao-Li Chang
Timothy R Rebbeck
Jill S Barnholtz-Sloan
Nicholas M Pajewski
David B Allison
University of Alabama at Birmingham · USUniversity of Pennsylvania · USCalifornia University of Pennsylvania · USCase Western Reserve University · USThe University of Texas MD Anderson Cancer Center · US

Funding

Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BARBARA A GOWER · 2000 to 2026
$31.9M
UAB Statistical Genetics Post-Doctoral Training ProgramT32HL072757 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI TIWARI, HEMANT K. · 2003 to 2016
$3.8M
Haplotyping and QTL Mapping in Pedigrees with Missing DataR01GM073766 · NIGMS · VIRGINIA COMMONWEALTH UNIVERSITY · PI GAO, GUIMIN · 2007 to 2011
$1.3M
Genome-wide Structured Association Testing & Regional Admixture MappingR01GM077490 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI LIU, NIANJUN · 2007 to 2010
$1.1M
NHLBI NIH HHS T32 HL072757NIDDK NIH HHS P30 DK056336NIGMS NIH HHS R01 GM073766NIGMS NIH HHS R01 GM077490
6 · The paper itself

Abstract

As genome-wide association studies expand beyond populations of European ancestry, the role of admixture will become increasingly important in the continued discovery and fine-mapping of variation influencing complex traits. Although admixture is commonly viewed as a confounding influence in association studies, approaches such as admixture mapping have demonstrated its ability to highlight disease susceptibility regions of the genome. In this study, we illustrate a powerful two-stage testing strategy designed to uncover trait-associated single nucleotide polymorphisms in the presence of ancestral allele frequency differentiation. In the first stage, we conduct an association scan by using predicted genotypic values based on regional admixture estimates. We then select a subset of promising markers for inclusion in a second-stage analysis, where association is tested between the observed genotype and the phenotype conditional on the predicted genotype. We prove that, under the null hypothesis, the test statistics used in each stage are orthogonal and asymptotically independent. Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture. We apply the proposed procedure to a study of height in 201 African-Americans genotyped at 108 ancestry informative markers. The two-stage procedure identified two statistically significant markers rs1985080 (PTHB1/BBS9) and rs952718 (ABCA12). PTHB1/BBS9 is downregulated by parathyroid hormone in osteoblastic cells and is thought to be involved in parathyroid hormone action in bones and may play a role in height. ABCA12 is a member of the superfamily of ATP-binding cassette transporters and its potential involvement in height is unclear.

Identifiers

PMID21754915
PMCPMC3132882
OpenAlexW1976667546

What Socratic 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 Socratic graph.