We conducted a multi-stage, genome-wide association study (GWAS) of bladder cancer with a primary scan of 589,299 single nucleotide polymorphisms (SNPs) in 3,532 cases and 5,120 controls of European descent (5 studies) followed by a replication strategy, which included 8,381 cases and 48,275 controls (16 studies). In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1; rs1014971, (P=8×10−12) maps to a non-genic region of chromosome 22q13.1; rs8102137 (P=2×10−11) on 19q12 maps to CCNE1; and rs11892031 (P=1×10−7) maps to the UGT1A cluster on 2q37.1. We confirmed four previous GWAS associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P=4×10−11) and a tag SNP for NAT2 acetylation status (P=4×10−11), as well as demonstrated smoking interactions with both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into mechanisms of carcinogenesis.
Three genome-wide association studies in Europe and the USA have reported eight urinary bladder cancer (UBC) susceptibility loci. Using extended case and control series and 1000 Genomes imputations of 5 340 737 single-nucleotide polymorphisms (SNPs), we searched for additional loci in the European GWAS. The discovery sample set consisted of 1631 cases and 3822 controls from the Netherlands and 603 cases and 37 781 controls from Iceland. For follow-up, we used 3790 cases and 7507 controls from 13 sample sets of European and Iranian ancestry. Based on the discovery analysis, we followed up signals in the urea transporter (UT) gene SLC14A. The strongest signal at this locus was represented by a SNP in intron 3, rs17674580, that reached genome-wide significance in the overall analysis of the discovery and follow-up groups: odds ratio = 1.17, P = 7.6 × 10(-11). SLC14A1 codes for UTs that define the Kidd blood group and are crucial for the maintenance of a constant urea concentration gradient in the renal medulla and, through this, the kidney's ability to concentrate urine. It is speculated that rs17674580, or other sequence variants in LD with it, indirectly modifies UBC risk by affecting urine production. If confirmed, this would support the 'urogenous contact hypothesis' that urine production and voiding frequency modify the risk of UBC.
Polymorphisms within the estrogen metabolic pathway are prime candidates for a possible association with breast cancer risk. We investigated 11 genes encoding key proteins of this pathway for their potential contribution to breast cancer risk. Of these CYP17A1, CYP19A1, EPHX1, HSD17B1, SRD5A2, and PPARG2 participate in biosynthesis, CYP1A1, CYP1B1, COMT, GSTP1, and SOD2 in catabolism and detoxification. We performed a population-based case-control study with 688 incident breast cancer cases and 724 controls from Germany and genotyped 18 polymorphisms by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR based RFLP (restriction fragment length polymorphism), and TaqMan allelic discrimination. Genotype frequencies were compared between cases and controls and odds ratios were calculated by conditional logistic regression. Further statistical analyses were based on cluster analysis, multifactor dimensionality reduction, logic regression, and global testing. Single factor analyses pointed to CYP1B1_1294_GG as a possible breast cancer risk modulator (OR = 2.57; 95% CI: 1.34-4.93) and two way stratification suggested associations between BMI > or = 30 kg/m(2) and COMT_472_GG (P = 0.0076 and P = 0.0026), BMI < 20 kg/m(2) and HSD17B1_937_GG (P = 0.0082) as well as CYP17A1_-34_CC and HRT use > or =10 years (P = 0.0063). Following correction for multiple testing none of these associations remained significant. No significant association between breast cancer risk and genetic polymorphisms was observed in multifactor analyses. The tested polymorphisms of the estrogen metabolic pathway may not play a direct role in breast cancer risk. Therefore, future association studies should be extended to other polymorphisms and other regulatory pathways.
Background and Aims Non‐alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children and adolescents today. In comparison with adult disease, paediatric NAFLD may show a periportal localization, which is associated with advanced fibrosis. This study aimed to assess the role of genetic risk variants for histological disease pattern and severity in childhood NAFLD. Methods We studied 14 single nucleotide polymorphisms (SNP) in a cohort of 70 adolescents with biopsy‐proven NAFLD. Genotype was compared to an adult control cohort (n = 200) and analysed in relation to histological disease severity and liver tissue proteomics. Results Three of the 14 SNPs were significantly associated with paediatric NAFLD after FDR adjustment, rs738409 (PNPLA3, P = 2.80 × 10−06), rs1044498 (ENPP1, P = 0.0091) and rs780094 (GCKR, P = 0.0281). The severity of steatosis was critically associated with rs738409 (OR=3.25; 95% CI: 1.72‐6.52, FDR‐adjusted P = 0.0070). The strongest variants associated with severity of fibrosis were rs1260326, rs780094 (both GCKR) and rs659366 (UCP2). PNPLA3 was associated with a portal pattern of steatosis, inflammation and fibrosis. Proteome profiling revealed decreasing levels of GCKR protein with increasing carriage of the rs1260326/rs780094 minor alleles and downregulation of the retinol pathway in rs738409 G/G carriers. Computational metabolic modelling highlighted functional relevance of PNPLA3, GCKR and UCP2 for NAFLD development. Conclusions This study provides evidence for the role of PNPLA3 as a determinant of portal NAFLD localization and severity of portal fibrosis in children and adolescents, the risk variant being associated with an impaired hepatic retinol metabolism.
Polymorphisms of N-acetyltransferase 2 (NAT2) are well known to modify urinary bladder cancer risk as well as efficacy and toxicity of pharmaceuticals via reduction in the enzyme's acetylation capacity. Nevertheless, the discussion about optimal NAT2 phenotype prediction, particularly differentiation between different degrees of slow acetylation, is still controversial. Therefore, we investigated the impact of single nucleotide polymorphisms and their haplotypes on slow acetylation in vivo and on bladder cancer risk. For this purpose, we used a study cohort of 1,712 bladder cancer cases and 2,020 controls genotyped for NAT2 by RFLP-PCR and for the tagSNP rs1495741 by TaqMan(®) assay. A subgroup of 344 individuals was phenotyped by the caffeine test in vivo. We identified an 'ultra-slow' acetylator phenotype based on combined *6A/*6A, *6A/*7B and *7B/*7B genotypes containing the homozygous minor alleles of C282T (rs1041983, *6A, *7B) and G590A (rs1799930, *6A). 'Ultra-slow' acetylators have significantly about 32 and 46 % lower activities of caffeine metabolism compared with other slow acetylators and with the *5B/*5B genotypes, respectively (P < 0.01, both). The 'ultra-slow' genotype showed an association with bladder cancer risk in the univariate analysis (OR = 1.31, P = 0.012) and a trend adjusted for age, gender and smoking habits (OR = 1.22, P = 0.082). In contrast, slow acetylators in general were not associated with bladder cancer risk, neither in the univariate (OR = 1.02, P = 0.78) nor in the adjusted (OR = 0.98, P = 0.77) analysis. In conclusion, this study suggests that NAT2 phenotype prediction should be refined by consideration of an 'ultra-slow' acetylation genotype.
Background: Arylamine N-acetyltransferase 2 (CoASAc; NAT2, EC 2.3.1.5) is a drug-metabolizing enzyme that displays common polymorphisms leading to impaired drug metabolism and adverse drug effects. Determination of the N-acetyltransferase 2 (arylamine N-acetyltransferase) (NAT2) genotype in clinical practice is hampered by the occurrence of ambiguous haplotype combinations that may lead to patient misclassification. We determined the frequencies for ambiguous NAT2 haplotypes and diplotypes in a white population and investigated the use of PHASE v2.1.1, a statistical program for haplotype reconstruction, to clarify this ambiguity and classify individuals according to their acetylation status. Methods: By means of allele-specific haplotype mapping and sequencing, we determined the haplotypes for 7 common single-nucleotide polymorphisms in the NAT2 gene (n = 2624 haplotypes). To test the performance of PHASE, actual genotypes were deconstructed and then reconstructed by haplotype prediction. Results: We identified 21 NAT2 allelic variants, including a new variant allele that combines the single-nucleotide polymorphisms rs1801279, rs1799929, and rs1208. In contrast, the previously described variant alleles *5G, *5J, *6E, *7A, *11A, *11B, and *14B were not identified in the study population. Ambiguous haplotypes were observed in 98 alleles (3.7%), and ambiguous diplotypes were observed in 64 individuals (4.9%). Eleven individuals (0.8%) were misclassified by the use of haplotype prediction. Conclusions: Ambiguous NAT2 genotyping data are common. Actual NAT2 genotypes cannot be fully determined by haplotype prediction techniques. This study provides real haplotype data that can be used as a guide to convert NAT2 haplotypes and diplotypes into actual genotypes in white individuals.
Glycerophosphodiesterase EDI3 (GPCPD1; GDE5; GDPD6) has been suggested to promote cell migration, adhesion, and spreading, but its mechanisms of action remain uncertain. In this study, we targeted the glycerol-3-phosphate acyltransferase GPAM along with choline kinase-a (CHKA), the enzymes that catabolize the products of EDI3 to determine which downstream pathway is relevant for migration. Our results clearly showed that GPAM influenced cell migration via the signaling lipid lysophosphatidic acid (LPA), linking it with GPAM to cell migration. Analysis of GPAM expression in different cancer types revealed a significant association between high GPAM expression and reduced overall survival in ovarian cancer. Silencing GPAM in ovarian cancer cells decreased cell migration and reduced the growth of tumor xenografts. In contrast to these observations, manipulating CHKA did not influence cell migration in the same set of cell lines. Overall, our findings show how GPAM influences intracellular LPA levels to promote cell migration and tumor growth.
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