Studying the joint effects of population stratification and sampling in case-control association studies

K. F. Cheng, J. Y. Lee, J. H. Chen

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Population stratification (PS) is referred to the systematic difference in allele frequencies between subpopulations in a population. It could cause a false-positive conclusion in a case-control association study, where the association is due to the structure of the underlying population, not a disease-associated locus. In this paper, we study the joint effects of PS and data sampling when the genetic effect is null. The level of the PS effect depends on the variation of the baseline genotype frequency across subpopulations and matching effectiveness of the sampling. In the case of simple random sampling (SRS), the matching effectiveness equals the inverse of the variation of the disease odds, and thus the PS bias is null under constant disease risk. However, if the latter condition holds but the sampling is not SRS, the bias may still exist. The magnitude of the bias increases as the deviation between the true sampling and SRS increases. We also derive bounds for the bias. If the bounds are approximately known or estimable, we show that this information can be used to compute a conservative p value for the usual association test. We give two real examples to demonstrate the application of the new method.

Original languageEnglish
Pages (from-to)254-261
Number of pages8
JournalHuman Heredity
Volume69
Issue number4
DOIs
Publication statusPublished - Apr 2010
Externally publishedYes

Fingerprint

Case-Control Studies
Population
Selection Bias
Gene Frequency
Genotype

Keywords

  • Association
  • Case-control study
  • Population stratification
  • Sampling scheme
  • Type I error

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics

Cite this

Studying the joint effects of population stratification and sampling in case-control association studies. / Cheng, K. F.; Lee, J. Y.; Chen, J. H.

In: Human Heredity, Vol. 69, No. 4, 04.2010, p. 254-261.

Research output: Contribution to journalArticle

@article{09f1d6ef75554cb8b39208f148c833dd,
title = "Studying the joint effects of population stratification and sampling in case-control association studies",
abstract = "Population stratification (PS) is referred to the systematic difference in allele frequencies between subpopulations in a population. It could cause a false-positive conclusion in a case-control association study, where the association is due to the structure of the underlying population, not a disease-associated locus. In this paper, we study the joint effects of PS and data sampling when the genetic effect is null. The level of the PS effect depends on the variation of the baseline genotype frequency across subpopulations and matching effectiveness of the sampling. In the case of simple random sampling (SRS), the matching effectiveness equals the inverse of the variation of the disease odds, and thus the PS bias is null under constant disease risk. However, if the latter condition holds but the sampling is not SRS, the bias may still exist. The magnitude of the bias increases as the deviation between the true sampling and SRS increases. We also derive bounds for the bias. If the bounds are approximately known or estimable, we show that this information can be used to compute a conservative p value for the usual association test. We give two real examples to demonstrate the application of the new method.",
keywords = "Association, Case-control study, Population stratification, Sampling scheme, Type I error",
author = "Cheng, {K. F.} and Lee, {J. Y.} and Chen, {J. H.}",
year = "2010",
month = "4",
doi = "10.1159/000297658",
language = "English",
volume = "69",
pages = "254--261",
journal = "Human Heredity",
issn = "0001-5652",
publisher = "S. Karger AG",
number = "4",

}

TY - JOUR

T1 - Studying the joint effects of population stratification and sampling in case-control association studies

AU - Cheng, K. F.

AU - Lee, J. Y.

AU - Chen, J. H.

PY - 2010/4

Y1 - 2010/4

N2 - Population stratification (PS) is referred to the systematic difference in allele frequencies between subpopulations in a population. It could cause a false-positive conclusion in a case-control association study, where the association is due to the structure of the underlying population, not a disease-associated locus. In this paper, we study the joint effects of PS and data sampling when the genetic effect is null. The level of the PS effect depends on the variation of the baseline genotype frequency across subpopulations and matching effectiveness of the sampling. In the case of simple random sampling (SRS), the matching effectiveness equals the inverse of the variation of the disease odds, and thus the PS bias is null under constant disease risk. However, if the latter condition holds but the sampling is not SRS, the bias may still exist. The magnitude of the bias increases as the deviation between the true sampling and SRS increases. We also derive bounds for the bias. If the bounds are approximately known or estimable, we show that this information can be used to compute a conservative p value for the usual association test. We give two real examples to demonstrate the application of the new method.

AB - Population stratification (PS) is referred to the systematic difference in allele frequencies between subpopulations in a population. It could cause a false-positive conclusion in a case-control association study, where the association is due to the structure of the underlying population, not a disease-associated locus. In this paper, we study the joint effects of PS and data sampling when the genetic effect is null. The level of the PS effect depends on the variation of the baseline genotype frequency across subpopulations and matching effectiveness of the sampling. In the case of simple random sampling (SRS), the matching effectiveness equals the inverse of the variation of the disease odds, and thus the PS bias is null under constant disease risk. However, if the latter condition holds but the sampling is not SRS, the bias may still exist. The magnitude of the bias increases as the deviation between the true sampling and SRS increases. We also derive bounds for the bias. If the bounds are approximately known or estimable, we show that this information can be used to compute a conservative p value for the usual association test. We give two real examples to demonstrate the application of the new method.

KW - Association

KW - Case-control study

KW - Population stratification

KW - Sampling scheme

KW - Type I error

UR - http://www.scopus.com/inward/record.url?scp=77950038300&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77950038300&partnerID=8YFLogxK

U2 - 10.1159/000297658

DO - 10.1159/000297658

M3 - Article

C2 - 20357476

AN - SCOPUS:77950038300

VL - 69

SP - 254

EP - 261

JO - Human Heredity

JF - Human Heredity

SN - 0001-5652

IS - 4

ER -