Evidence map›Paper›PMID 19797906›Full record

ArticleHuman heredity2010

Correcting for cryptic relatedness in population-based association studies of continuous traits.

Feng Zhang, Hong-Wen Deng

Abstract read
In one paragraph

Article in Human heredity, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. 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

2 authors.

Feng ZhangThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China.
Hong-Wen Deng

Funding

Proteome-wide Expression Study of Osteogenic CellsP50AR055081 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2007 to 2012
$5.0M
ROBUST AND POWERFUL TEST OF CANDIDATE GENES TO BONE MASSR01AR050496 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2004 to 2013
$3.8M
Identification of Proteins Important for Male OsteoporosisR01AR057049 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2009 to 2013
$2.4M
Genomic search for bone mass QTLsR01AG026564 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2007 to 2010
$2.3M
Proteomics Study of Peripheral Blood Monocytes on OsteroporsisR21AG027110 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2006 to 2007
$367k
Alcohol Dependence Genetics in a Large Chinese PedigreeR21AA015973 · NIAAA · YALE UNIVERSITY · PI GELERNTER, JOEL · 2007 to 2008
$345k
NIAAA NIH HHS R21 AA015973NIAMS NIH HHS P50 AR055081NIAMS NIH HHS R01 AR050496NIAMS NIH HHS R01 AR057049NIA NIH HHS R01 AG026564NIA NIH HHS R21 AG027110
6 · The paper itself

Abstract

Cryptic relatedness was suggested to be an important source of confounding in population-based association studies (PBAS). The magnitude and manner of cryptic relatedness affecting the performance of PBAS of continuous traits remain to be investigated. We simulated a set of related samples through biased sampling and inbreeding, and evaluated the power and type I error rates of simple association tests (SAT) without correcting for cryptic relatedness. We also used extended likelihood ratio tests (ELRT) to conduct PBAS accounting for cryptic relatedness, and compared it with genomic control (GC). Cryptic relatedness decreased the power as well as increased the type I error rates of SAT in both biased sampling and inbreeding models. The impact of cryptic relatedness on the performance of SAT appeared to be limited in the biased sampling model. However, cryptic relatedness in inbred populations may result in excessive false positive results of SAT. Compared with SAT and GC, ELRT obtained improved power and type I error rates under various scenarios. Ignoring cryptic relatedness may increase spurious association results in PBAS. Our ELRT provides a novel approach to control cryptic relatedness in PBAS of human continuous traits.

Indexed as

AlgorithmsModels, GeneticComputer SimulationFamily HealthGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansQuantitative Trait LociSample SizeSiblings

Identifiers

PMID19797906
PMCPMC2880733

What OpenQuestion holds

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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.