The primary circulating form of vitamin D, 25-hydroxy-vitamin D [25(OH)D], is associated with multiple medical outcomes, including rickets, osteoporosis, multiple sclerosis and cancer. In a genome-wide association study (GWAS) of 4501 persons of European ancestry drawn from five cohorts, we identified single-nucleotide polymorphisms (SNPs) in the gene encoding group-specific component (vitamin D binding) protein, GC, on chromosome 4q12-13 that were associated with 25(OH)D concentrations: rs2282679 (P = 2.0 × 10−30), in linkage disequilibrium (LD) with rs7041, a non-synonymous SNP (D432E; P = 4.1 × 10−22) and rs1155563 (P = 3.8 × 10−25). Suggestive signals for association with 25(OH)D were also observed for SNPs in or near three other genes involved in vitamin D synthesis or activation: rs3829251 on chromosome 11q13.4 in NADSYN1 [encoding nicotinamide adenine dinucleotide (NAD) synthetase; P = 8.8 × 10−7], which was in high LD with rs1790349, located in DHCR7, the gene encoding 7-dehydrocholesterol reductase that synthesizes cholesterol from 7-dehydrocholesterol; rs6599638 in the region harboring the open-reading frame 88 (C10orf88) on chromosome 10q26.13 in the vicinity of ACADSB (acyl-Coenzyme A dehydrogenase), involved in cholesterol and vitamin D synthesis (P = 3.3 × 10−7); and rs2060793 on chromosome 11p15.2 in CYP2R1 (cytochrome P450, family 2, subfamily R, polypeptide 1, encoding a key C-25 hydroxylase that converts vitamin D3 to an active vitamin D receptor ligand; P = 1.4 × 10−5). We genotyped SNPs in these four regions in 2221 additional samples and confirmed strong genome-wide significant associations with 25(OH)D through meta-analysis with the GWAS data for GC (P = 1.8 × 10−49), NADSYN1/DHCR7 (P = 3.4 × 10−9) and CYP2R1 (P = 2.9 × 10−17), but not C10orf88 (P = 2.4 × 10−5).

Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types, genotyping 515,922 single-nucleotide polymorphisms (SNPs) in 5739 lung cancer cases and 5848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from ten additional studies, for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication, resulting in 3333 adenocarcinomas (AD), 2589 squamous cell carcinomas (SQ), and 1418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT), on chromosome 5p15.33, was associated with risk of adenocarcinoma (odds ratio [OR]=1.23, 95% confidence interval [CI]=1.13-1.33, p=3.02x10(-7)), but not with other histologic types (OR=1.01, p=0.84 and OR=1.00, p=0.93 for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95% CI=1.17-1.31, p=3.74x10(-14) for AD; OR=0.99, p=0.69 and OR=0.97, p=0.48 for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma.

It is increasingly recognized that pathway analyses-a joint test of association between the outcome and a group of single nucleotide polymorphisms (SNPs) within a biological pathway-could potentially complement single-SNP analysis and provide additional insights for the genetic architecture of complex diseases. Building upon existing P-value combining methods, we propose a class of highly flexible pathway analysis approaches based on an adaptive rank truncated product statistic that can effectively combine evidence of associations over different SNPs and genes within a pathway. The statistical significance of the pathway-level test statistics is evaluated using a highly efficient permutation algorithm that remains computationally feasible irrespective of the size of the pathway and complexity of the underlying test statistics for summarizing SNP-and gene-level associations. We demonstrate through simulation studies that a gene-based analysis that treats the underlying genes, as opposed to the underlying SNPs, as the basic units for hypothesis testing, is a very robust and powerful approach to pathway-based association testing. We also illustrate the advantage of the proposed methods using a study of the association between the nicotinic receptor pathway and cigarette smoking behaviors. Genet. Epidemiol.