Hierarchical modeling identifies novel lung cancer susceptibility variants in inflammation pathways among 10,140 cases and 11,012 controls.
Recent evidence suggests that inflammation plays a pivotal role in the development of lung cancer. In this study, we used a two-stage approach to investigate associations between genetic variants in inflammation pathways and lung cancer risk based on genome-wide association study (GWAS) data. A total of 7,650 sequence variants from 720 genes relevant to inflammation pathways were identified using keyword and pathway searches from Gene Cards and Gene Ontology databases. In Stage 1, six GWAS datasets from the International Lung Cancer Consortium were pooled (4,441 cases and 5,094 controls of European ancestry), and a hierarchical modeling (HM) approach was used to incorporate prior information for each of the variants into the analysis. The prior matrix was constructed using (1) role of genes in the inflammation and immune pathways; (2) physical properties of the variants including the location of the variants, their conservation scores and amino acid coding; (3) LD with other functional variants and (4) measures of heterogeneity across the studies. HM affected the priority ranking of variants particularly among those having low prior weights, imprecise estimates and/or heterogeneity across studies. In Stage 2, we used an independent NCI lung cancer GWAS study (5,699 cases and 5,818 controls) for in silico replication. We identified one novel variant at the level corrected for multiple comparisons (rs2741354 in EPHX2 at 8p21.1 with p value = 7.4 × 10(-6)), and confirmed the associations between TERT (rs2736100) and the HLA region and lung cancer risk. HM allows for prior knowledge such as from bioinformatic sources to be incorporated into the analysis systematically, and it represents a complementary analytical approach to the conventional GWAS analysis.
International Agency for Research on Cancer, Lyon, France. brenner.darren@gmail.com
Darren R
DR
Brenner
Paul
P
Brennan
Paolo
P
Boffetta
Christopher I
CI
Amos
Margaret R
MR
Spitz
Chu
C
Chen
Gary
G
Goodman
Joachim
J
Heinrich
Heike
H
Bickeböller
Albert
A
Rosenberger
Angela
A
Risch
Thomas
T
Muley
John R
JR
McLaughlin
Simone
S
Benhamou
Christine
C
Bouchardy
Juan Pablo
JP
Lewinger
John S
JS
Witte
Gary
G
Chen
Shelley
S
Bull
Rayjean J
RJ
Hung
D000483:Alleles; D002170:Canada / Q000453:epidemiology; D016022:Case-Control Studies; D005060:Europe / Q000453:epidemiology; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation / Q000235:genetics*; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D007249:Inflammation / Q000235:genetics; D016013:Likelihood Functions; D008175:Lung Neoplasms / Q000453:epidemiology / Q000235:genetics*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012306:Risk; D014481:United States / Q000453:epidemiology; D044465:White People / Q000235:genetics*