Dataset Information

Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci.

ABSTRACT: Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants. This study represents a significant advance over previous research by investigating a large number of novel, rare variants, as well as their underlying mechanisms through telomere length. Variants for this fine-mapping study were identified through a targeted deep sequencing (average depth of coverage greater than 4000×) of 576 individuals. Subsequently, 4652 SNPs, including 1108 novel SNPs, were genotyped in 5164 cases and 5716 controls of European ancestry. After adjusting for known risk loci, rs2736100 and rs401681, we identified a new, independent lung cancer susceptibility variant in LPCAT1: rs139852726 (OR = 0.46, P = 4.73×10(-9)), and three new adenocarcinoma risk variants in TERT: rs61748181 (OR = 0.53, P = 2.64×10(-6)), rs112290073 (OR = 1.85, P = 1.27×10(-5)), rs138895564 (OR = 2.16, P = 2.06×10(-5); among young cases, OR = 3.77, P = 8.41×10(-4)). In addition, we found that rs139852726 (P = 1.44×10(-3)) was associated with telomere length in a sample of 922 healthy individuals. The gene-based SKAT-O analysis implicated TERT as the most relevant gene in the 5p15.33 region for adenocarcinoma (P = 7.84×10(-7)) and lung cancer (P = 2.37×10(-5)) risk. In this largest fine-mapping study to investigate a large number of rare and novel variants within 5p15.33, we identified novel lung and adenocarcinoma susceptibility loci with large effects and provided support for the role of telomere length as the potential underlying mechanism.

SUBMITTER: Kachuri L

PROVIDER: S-EPMC4715236 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci.

Kachuri Linda L Amos Christopher I CI McKay James D JD Johansson Mattias M Vineis Paolo P Bueno-de-Mesquita H Bas HB Boutron-Ruault Marie-Christine MC Johansson Mikael M Quirós J Ramón JR Sieri Sabina S Travis Ruth C RC Weiderpass Elisabete E Le Marchand Loic L Henderson Brian E BE Wilkens Lynne L Goodman Gary E GE Chen Chu C Doherty Jennifer A JA Christiani David C DC Wei Yongyue Y Su Li L Tworoger Shelley S Zhang Xuehong X Kraft Peter P Zaridze David D Field John K JK Marcus Michael W MW Davies Michael P A MPA Hyde Russell R Caporaso Neil E NE Landi Maria Teresa MT Severi Gianluca G Giles Graham G GG Liu Geoffrey G McLaughlin John R JR Li Yafang Y Xiao Xiangjun X Fehringer Gord G Zong Xuchen X Denroche Robert E RE Zuzarte Philip C PC McPherson John D JD Brennan Paul P Hung Rayjean J RJ

Carcinogenesis 20151120 1

Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants. This study represents a significant advance over previous research by investigating a large number of novel, rare variants, as well as their underlying mechanisms through telomere length. Variants for this fine-mapping study w ...[more]

PMID: 26590902

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Project description:Recent genome-wide association studies have identified 78 loci associated with Parkinson's disease susceptibility but the underlying mechanisms remain largely unclear. To identify likely causal variants for disease risk, we fine-mapped these Parkinson's-associated loci using four different fine-mapping methods. We then integrated multi-assay cell type-specific epigenomic profiles to pinpoint the likely mechanism of action of each variant, allowing us to identify Consensus single nucleotide polymorphism (SNPs) that disrupt LRRK2 and FCGR2A regulatory elements in microglia, an MBNL2 enhancer in oligodendrocytes, and a DYRK1A enhancer in neurons. This genome-wide functional fine-mapping investigation of Parkinson's disease substantially advances our understanding of the causal mechanisms underlying this complex disease while avoiding focus on spurious, non-causal mechanisms. Together, these results provide a robust, comprehensive list of the likely causal variants, genes and cell-types underlying Parkinson's disease risk as demonstrated by consistently greater enrichment of our fine-mapped SNPs relative to lead GWAS SNPs across independent functional impact annotations. In addition, our approach prioritized an average of 3/85 variants per locus as putatively causal, making downstream experimental studies both more tractable and more likely to yield disease-relevant, actionable results. Large-scale studies comparing individuals with Parkinson's disease to age-matched controls have identified many regions of the genome associated with the disease. However, there is widespread correlation between different parts of the genome, making it difficult to tell which genetic variants cause Parkinson's and which are simply co-inherited with causal variants. We therefore applied a suite of statistical models to identify the most likely causal genetic variants (i.e. fine-mapping). We then linked these genetic variants with epigenomic and gene expression signatures across a wide variety of tissues and cell types to identify how these variants cause disease. Therefore, this study provides a comprehensive and robust list of cellular and molecular mechanisms that may serve as targets in the development of more effective Parkinson's therapeutics.

Dataset Information

Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci.

Publications

Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci.

Similar Datasets

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