Parametric Linkage Analysis Identifies Five Novel Genome-Wide Significant Loci for Familial Lung Cancer

Anthony M. Musolf, Claire L. Simpson, Mariza De Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Yafang Li, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Objective: One of four American cancer patients dies of lung cancer. Environmental factors such as tobacco smoking are known to affect lung cancer risk. However, there is a genetic factor to lung cancer risk as well. Here, we perform parametric linkage analysis on family-based genotype data in an effort to find genetic loci linked to the disease. Methods: 197 individuals from families with a high-risk history of lung cancer were recruited and genotyped using an Illumina array. Parametric linkage analyses were performed using an affected-only phenotype model with an autosomal dominant inheritance using a disease allele frequency of 0.01. Three types of analyses were performed: single variant two-point, collapsed haplotype pattern variant two-point, and multipoint analysis. Results: Five novel genome-wide significant loci were identified at 18p11.23, 2p22.2, 14q13.1, 16p13, and 20q13.11. The families most informative for linkage were also determined. Conclusions: The 5 novel signals are good candidate regions, containing genes that have been implicated as having somatic changes in lung cancer or other cancers (though not in germ line cells). Targeted sequencing on the significant loci is planned to determine the causal variants at these loci.

Original languageEnglish (US)
Pages (from-to)64-74
Number of pages11
JournalHuman Heredity
Volume82
Issue number1-2
DOIs
StatePublished - Sep 1 2017

Keywords

  • Family studies
  • Genetic linkage
  • Genome-wide scan
  • Heterogeneity LOD score
  • LOD score
  • Linkage analysis
  • Lung cancer
  • Parametric (model-based) analysis

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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