Little is known whether genetic variants identified in genome-wide association studies interact to increase bladder cancer risk. Recently, we identified two- and three-variant combinations associated with a particular increase of bladder cancer risk in a urinary bladder cancer case-control series (Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), 1501 cases, 1565 controls). In an independent case-control series (Nijmegen Bladder Cancer Study, NBCS, 1468 cases, 1720 controls) we confirmed these two- and three-variant combinations. Pooled analysis of the two studies as discovery group (IfADo-NBCS) resulted in sufficient statistical power to test up to four-variant combinations by a logistic regression approach. The New England and Spanish Bladder Cancer Studies (2080 cases and 2167 controls) were used as a replication series. Twelve previously identified risk variants were considered. The strongest four-variant combination was obtained in never smokers. The combination of rs1014971[AA] near apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A) and chromobox homolog 6 (CBX6), solute carrier family 1s4 (urea transporter), member 1 (Kidd blood group) (SLC14A1) exon single nucleotide polymorphism (SNP) rs1058396[AG, GG], UDP glucuronosyltransferase 1 family, polypeptide A complex locus (UGT1A) intron SNP rs11892031[AA] and rs8102137[CC, CT] near cyclin E1 (CCNE1) resulted in an unadjusted odds ratio (OR) of 2.59 (95% CI = 1.93-3.47; P = 1.87 × 10-10), while the individual variant ORs ranged only between 1.11 and 1.30. The combination replicated in the New England and Spanish Bladder Cancer Studies (ORunadjusted = 1.60, 95% CI = 1.10-2.33; P = 0.013). The four-variant combination is relatively frequent, with 25% in never smoking cases and 11% in never smoking controls (total study group: 19% cases, 14% controls). In conclusion, we show that four high-risk variants can statistically interact to confer increased bladder cancer risk particularly in never smokers.
Introduction: Theoretically, some metabolic traits may predispose older individuals to weight loss during aging, leading to increased all-cause mortality and many serious health issues. Biomarkers to robustly predict progressive weight loss during aging are, however, lacking. We prospectively assessed if urinary levels of F2-isoprostanes and their peroxisomal -oxidation metabolite, 2,3-dinor-5,6-dihydro-15-F2t-isoprostane (F2-IsoP-M), were associated with subsequent weight loss in middle-aged and older women. Methods: Included in the analysis were 2066 women aged 40-70 years, a subset of a prospective cohort study. F2-isoprostanes (F2-IsoPs) and its β-oxidation metabolite F2-IsoP-M were measured in urine using gas chromatography-mass spectrometry. Measurements of anthropometry and exposures to major determinants of body weight were performed at baseline and repeated thrice over 15-year follow-up. The longitudinal associations of F2-IsoP-M and the F2-IsoP-M to its parent compound F2-IsoP ratio (MPR) with repeatedly measured weight changes were examined using linear mixed-effect models. Results: After adjusting for time-varying covariates energy intake, physical activity, and comorbidity index, among others, levels of F2-IsoP-M and the MPR were both inversely associated with percentage of weight change. Weight in the highest quartile of these two biomarkers was 1.33% (95% CI = -2.41, -0.24) and 1.09% (95% CI = -2.16, -0.02) lower than those in the lowest quartile group, with P for trend of 0.01 and 0.03, respectively. The inverse association was consistently seen across follow-up periods, although appearing stronger with prolonged follow-up. There was no association between the parent compound F2-IsoPs and weight change. Conclusion: This study demonstrates the first piece of evidence to associate F2-IsoP metabolism, peroxisomal β-oxidation, with weight loss in older women. Further investigations into the role of lipid peroxidation and peroxisomal β-oxidation in weight change among older individuals are warranted.
Abstract Outdoor air pollution is a growing public health concern, particularly in urban settings. However, there are limited epidemiological data on outdoor air pollution in rural areas with substantial levels of air pollution attributed to solid fuel burning for household cooking and heating. Xuanwei and Fuyuan are rural counties in China where the domestic combustion of locally sourced bituminous (“smoky”) coal has been associated with the highest lung cancer rates in China. We previously assessed indoor and personal air pollution exposures in this area; however, the influence of indoor coal combustion and household ventilation on outdoor air pollution has not been assessed. Therefore, we measured outdoor fine particulate matter (PM 2.5 ), species of polycyclic aromatic hydrocarbons (PAHs) including naphthalene (NAP) and the known carcinogen benzo(a)pyrene (BaP), sulfur dioxide (SO 2 ), and nitrogen dioxide (NO 2 ) over two consecutive 24-h sampling periods in 29 villages. Just over half of the villages were revisited two to nine months after the initial sampling period to repeat all measurements. The overall geometric mean (GM) of outdoor PM 2.5 , BaP, NAP, and NO 2 were 45.3 µg/m 3 , 9.7 ng/m 3 , 707.7 ng/m 3 , and 91.5 µg/m 3 , respectively. Using linear mixed effects models, we found that burning smoky coal was associated with higher outdoor BaP concentrations [GM ratio (GMR) = 2.79] and lower outdoor SO 2 detection rates (GMR = 0.43), compared to areas burning smokeless coal. Areas with predominantly ventilated stoves (> 50% of stoves) had higher outdoor BaP (GMR = 1.49) compared to areas with fewer ventilated stoves. These results show that outdoor air pollution in a rural region of China was associated with the type of coal used for cooking and heating indoors and the presence of stove ventilation. Our findings suggest that efforts of household stove improvement to reduce indoor air pollution have resulted in higher outdoor air pollution levels. Further reducing adverse health effects in rural villages from household coal combustion will require the use of cleaner fuel types.
Autoimmune conditions and immune system–related genetic variations are associated with risk of non-Hodgkin lymphoma (NHL). In a pooled analysis of 8,692 NHL cases and 9,260 controls from 14 studies (1988–2007) within the International Lymphoma Epidemiology Consortium, we evaluated the interaction between immune system genetic variants and autoimmune conditions in NHL risk. We evaluated the immunity-related single nucleotide polymorphisms rs1800629 (tumor necrosis factor gene (TNF) G308A), rs1800890 (interleukin-10 gene (IL10) T3575A), rs6457327 (human leukocyte antigen gene (HLA) class I), rs10484561 (HLA class II), and rs2647012 (HLA class II)) and categorized autoimmune conditions as primarily mediated by B-cell or T-cell responses. We constructed unconditional logistic regression models to measure associations between autoimmune conditions and NHL with stratification by genotype. Autoimmune conditions mediated by B-cell responses were associated with increased NHL risk, specifically diffuse large B-cell lymphoma (odds ratio (OR) = 3.11, 95% confidence interval (CI): 2.25, 4.30) and marginal zone lymphoma (OR = 5.80, 95% CI: 3.82, 8.80); those mediated by T-cell responses were associated with peripheral T-cell lymphoma (OR = 2.14, 95% CI: 1.35, 3.38). In the presence of the rs1800629 AG/AA genotype, B-cell-mediated autoimmune conditions increased NHL risk (OR = 3.27, 95% CI: 2.07, 5.16; P-interaction = 0.03) in comparison with the GG genotype (OR = 1.82, 95% CI: 1.31, 2.53). This interaction was consistent across major B-cell NHL subtypes, including marginal zone lymphoma (P-interaction = 0.02) and follicular lymphoma (P-interaction = 0.04).
<div>Abstract<p>Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and <i>P</i> < 5 × 10<sup>–8</sup> was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82–0.93; former smokers 1.00, 95% CI, 0.91–1.07; current smokers 1.25, 95% CI 1.12–1.40, <i>P</i><sub>interaction</sub> = 3.08 × 10<sup>–9</sup>). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (<i>r</i><sup>2</sup> = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings.</p>Significance:<p>This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.</p></div>
<p>Supplementary Figure 1: Electrophoretic mobility shift assays (EMSA) for CCNE1 SNPs rs8102137 and rs7257330. Supplementary Figure 2: Alignment of cyclin E protein isoforms - WT1, WT2 and ES and ET. Supplementary Figure 3: Functional analysis of cyclin E isoforms.Supplementary Table 1: Description of sub-studies included in NCI-GWAS1 and GWAS2 of bladder cancer. Supplementary Table 2: Characteristics of bladder tissue samples used for mRNA expression analysis. Supplementary Table 3: PCR primers, genotyping and gene expression assays, EMSA probes and antibodies. Supplementary Table 4: Bladder cancer stage and grade information for patients in the combined GWAS1+2 set. Supplementary Table 6: Association with bladder cancer risk with mutual adjustment for CCNE1 variants. Supplementary Table 7: Association with bladder cancer risk for CCNE1 variants previously associated with other cancers and for two non-synonymous coding variants. Supplementary Table 8: Association between cyclin E protein expression (IHC scores), bladder cancer patient characteristics and CCNE1 variants.</p>
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