Ordered subset analysis identifies loci influencing lung cancer risk on chromosomes 6q and 12q

Shenying Fang, Susan M. Pinney, Joan E. Bailey-Wilson, Mariza De Andrade, Yafang Li, Elena Kupert, Ming You, Ann G. Schwartz, Ping Yang, Marshall W. Anderson, Christopher I. Amos

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Background: Genetic susceptibility for cancer can differ substantially among families. We use trait-related covariates to identify a genetically homogeneous subset of families with the best evidence for linkage in the presence of heterogeneity. Methods: We performed a genome-wide linkage screen in 93 families. Samples and data were collected by the familial lung cancer recruitment sites of the Genetic Epidemiology of Lung Cancer Consortium. We estimated linkage scores for each family by the Markov chain Monte Carlo procedure using SimWalk2 software. We used ordered subset analysis (OSA) to identify genetically homogenous families by ordering families based on a disease-associated covariate. We performed permutation tests to determine the relationship between the trait-related covariate and the evidence for linkage. Results: A genome-wide screen for lung cancer loci identified strong evidence for linkage to 6q23-25 and suggestive evidence for linkage to 12q24 using OSA, with peak logarithm of odds (LOD) scores of 4.19 and 2.79, respectively. We found other chromosomes also suggestive for linkages, including 5q31-q33, 14q11, and 16q24. Conclusions: Our OSA results support 6q as a lung cancer susceptibility locus and provide evidence for disease linkage on 12q24. This study further increased our understanding of the inheritability for lung cancer. Validation studies using larger sample size are needed to verify the presence of several other chromosomal regions suggestive of an increased risk for lung cancer and/or other cancers. Impact: OSA can reduce genetic heterogeneity in linkage study and may assist in revealing novel susceptibility loci.

Original languageEnglish (US)
Pages (from-to)3157-3166
Number of pages10
JournalCancer Epidemiology Biomarkers and Prevention
Volume19
Issue number12
DOIs
StatePublished - Dec 2010

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Lung Neoplasms
Chromosomes
Genome
Markov Chains
Genetic Heterogeneity
Molecular Epidemiology
Validation Studies
Genetic Predisposition to Disease
Sample Size
Neoplasms
Software

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

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Ordered subset analysis identifies loci influencing lung cancer risk on chromosomes 6q and 12q. / Fang, Shenying; Pinney, Susan M.; Bailey-Wilson, Joan E.; De Andrade, Mariza; Li, Yafang; Kupert, Elena; You, Ming; Schwartz, Ann G.; Yang, Ping; Anderson, Marshall W.; Amos, Christopher I.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 19, No. 12, 12.2010, p. 3157-3166.

Research output: Contribution to journalArticle

Fang, S, Pinney, SM, Bailey-Wilson, JE, De Andrade, M, Li, Y, Kupert, E, You, M, Schwartz, AG, Yang, P, Anderson, MW & Amos, CI 2010, 'Ordered subset analysis identifies loci influencing lung cancer risk on chromosomes 6q and 12q', Cancer Epidemiology Biomarkers and Prevention, vol. 19, no. 12, pp. 3157-3166. https://doi.org/10.1158/1055-9965.EPI-10-0792
Fang, Shenying ; Pinney, Susan M. ; Bailey-Wilson, Joan E. ; De Andrade, Mariza ; Li, Yafang ; Kupert, Elena ; You, Ming ; Schwartz, Ann G. ; Yang, Ping ; Anderson, Marshall W. ; Amos, Christopher I. / Ordered subset analysis identifies loci influencing lung cancer risk on chromosomes 6q and 12q. In: Cancer Epidemiology Biomarkers and Prevention. 2010 ; Vol. 19, No. 12. pp. 3157-3166.
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abstract = "Background: Genetic susceptibility for cancer can differ substantially among families. We use trait-related covariates to identify a genetically homogeneous subset of families with the best evidence for linkage in the presence of heterogeneity. Methods: We performed a genome-wide linkage screen in 93 families. Samples and data were collected by the familial lung cancer recruitment sites of the Genetic Epidemiology of Lung Cancer Consortium. We estimated linkage scores for each family by the Markov chain Monte Carlo procedure using SimWalk2 software. We used ordered subset analysis (OSA) to identify genetically homogenous families by ordering families based on a disease-associated covariate. We performed permutation tests to determine the relationship between the trait-related covariate and the evidence for linkage. Results: A genome-wide screen for lung cancer loci identified strong evidence for linkage to 6q23-25 and suggestive evidence for linkage to 12q24 using OSA, with peak logarithm of odds (LOD) scores of 4.19 and 2.79, respectively. We found other chromosomes also suggestive for linkages, including 5q31-q33, 14q11, and 16q24. Conclusions: Our OSA results support 6q as a lung cancer susceptibility locus and provide evidence for disease linkage on 12q24. This study further increased our understanding of the inheritability for lung cancer. Validation studies using larger sample size are needed to verify the presence of several other chromosomal regions suggestive of an increased risk for lung cancer and/or other cancers. Impact: OSA can reduce genetic heterogeneity in linkage study and may assist in revealing novel susceptibility loci.",
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AU - Pinney, Susan M.

AU - Bailey-Wilson, Joan E.

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AU - Li, Yafang

AU - Kupert, Elena

AU - You, Ming

AU - Schwartz, Ann G.

AU - Yang, Ping

AU - Anderson, Marshall W.

AU - Amos, Christopher I.

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