Search

PDF file - 132K, Affymetrix Probesets Differentially Expressed in Stage I Lung Adenocarcinoma Cases Compared to Controls in Current Smokers and All Subjects Combined, Italy, 2002-2005.

Affordable early screening in subjects with high risk of lung cancer has great potential to improve survival from this deadly disease. We measured gene expression from lung tissue and peripheral whole blood (PWB) from adenocarcinoma cases and controls to identify dysregulated lung cancer genes that could be tested in blood to improve identification of at-risk patients in the future. Genome-wide mRNA expression analysis was conducted in 153 subjects (73 adenocarcinoma cases, 80 controls) from the Environment And Genetics in Lung cancer Etiology study using PWB and paired snap-frozen tumor and noninvolved lung tissue samples. Analyses were conducted using unpaired t tests, linear mixed effects, and ANOVA models. The area under the receiver operating characteristic curve (AUC) was computed to assess the predictive accuracy of the identified biomarkers. We identified 50 dysregulated genes in stage I adenocarcinoma versus control PWB samples (false discovery rate ≤0.1, fold change ≥1.5 or ≤0.66). Among them, eight (TGFBR3, RUNX3, TRGC2, TRGV9, TARP, ACP1, VCAN, and TSTA3) differentiated paired tumor versus noninvolved lung tissue samples in stage I cases, suggesting a similar pattern of lung cancer–related changes in PWB and lung tissue. These results were confirmed in two independent gene expression analyses in a blood-based case–control study (n = 212) and a tumor–nontumor paired tissue study (n = 54). The eight genes discriminated patients with lung cancer from healthy controls with high accuracy (AUC = 0.81, 95% CI = 0.74–0.87). Our finding suggests the use of gene expression from PWB for the identification of early detection markers of lung cancer in the future. Cancer Prev Res; 4(10); 1599–608. ©2011 AACR.

PDF file - 222K, Affymetrix Quality Assessment for the Gene Expression Data from Peripheral Whole Blood in Cases and Controls, Italy, 2002-2005.

PDF file - 386K

Background: Epidemiologic studies have reported that frequent consumption of quercetin-rich foods is inversely associated with lung cancer incidence. A quercetin-rich diet might modulate microRNA (miR) expression; however, this mechanism has not been fully examined.Methods: miR expression data were measured by a custom-made array in formalin-fixed paraffin-embedded tissue samples from 264 lung cancer cases (144 adenocarcinomas and 120 squamous cell carcinomas). Intake of quercetin-rich foods was derived from a food-frequency questionnaire. In individual-miR–based analyses, we compared the expression of miRs (n = 198) between lung cancer cases consuming high versus low quercetin-rich food intake using multivariate ANOVA tests. In family-miR–based analyses, we used Functional Class Scoring (FCS) to assess differential effect on biologically functional miR families. We accounted for multiple testing using 10,000 global permutations (significance at Pglobal < 0.10). All multivariate analyses were conducted separately by histology and by smoking status (former and current smokers).Results: Family-based analyses showed that a quercetin-rich diet differentiated miR expression profiles of the tumor suppressor let-7 family among adenocarcinomas (PFCS < 0.001). Other significantly differentiated miR families included carcinogenesis-related miR-146, miR-26, and miR-17 (PFCS < 0.05). In individual-based analyses, we found that among former and current smokers with adenocarcinoma, 33 miRs were observed to be differentiated between highest and lowest quercetin-rich food consumers (23 expected by chance; Pglobal = 0.047).Conclusions: We observed differential expression of key biologically functional miRs between high versus low consumers of quercetin-rich foods in adenocarcinoma cases.Impact: Our findings provide preliminary evidence on the mechanism underlying quercetin-related lung carcinogenesis. Cancer Epidemiol Biomarkers Prev; 21(12); 2176–84. ©2012 AACR.

Odds ratios and Hazard ratios (95% Confidence Intervals) for lung cancer and nut consumption in EAGLE and AARP, by smoking intensity

Odds ratios and Hazard ratios (95% Confidence Intervals) for lung cancer and nut consumption in EAGLE and AARP, by histology subtypes

PDF file - 80K, List of miRs (N=198) retained from chip array analysis

PDF file - 54K, All identified miR groups based on "seed" sequence (2-7nt)

PDF file - 47K, Food groups and individual food items

PDF file - 5418K, Hierarchical clustering heat map of miR expression levels for 25 miRs that displayed significant differential expression among former smokers with adenocarcinoma in the individual miR-based analysis. Average linkage was used to cluster miRs and samples with a distance metric of 1 minus centered correlation using BRB-ArrayTools version 4.2. Tertiles define subjects with low (Tertile 1) and high (Tertile 3) consumption of quercetin-rich food.

Purpose: The molecular drivers that determine histology in lung cancer are largely unknown. We investigated whether microRNA (miR) expression profiles can differentiate histologic subtypes and predict survival for non–small cell lung cancer.Experimental Design: We analyzed miR expression in 165 adenocarcinoma and 125 squamous cell carcinoma (SQ) tissue samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study using a custom oligo array with 440 human mature antisense miRs. We compared miR expression profiles using t tests and F tests and accounted for multiple testing using global permutation tests. We assessed the association of miR expression with tobacco smoking using Spearman correlation coefficients and linear regression models, and with clinical outcome using log-rank tests, Cox proportional hazards, and survival risk prediction models, accounting for demographic and tumor characteristics.Results: MiR expression profiles strongly differed between adenocarcinoma and SQ (Pglobal < 0.0001), particularly in the early stages, and included miRs located on chromosome loci most often altered in lung cancer (e.g., 3p21-22). Most miRs, including all members of the let-7 family, were downregulated in SQ. Major findings were confirmed by quantitative real time-polymerase chain reaction (qRT-PCR) in EAGLE samples and in an independent set of lung cancer cases. In SQ, the low expression of miRs that are downregulated in the histology comparison was associated with 1.2- to 3.6-fold increased mortality risk. A five-miR signature significantly predicted survival for SQ.Conclusions: We identified a miR expression profile that strongly differentiated adenocarcinoma from SQ and had prognostic implications. These findings may lead to histology-based therapeutic approaches. Clin Cancer Res; 16(2); 430–41

PDF file - 3580K, Hierarchical clustering heat map of miR expression levels for 10 miRs that displayed significant differential expression among former smokers with squamous cell carcinoma in the individual miR-based analysis. Average linkage was used to cluster miRs and samples with a distance metric of 1 minus centered correlation using BRB-ArrayTools version 4.2. Tertiles define subjects with low (Tertile 1) and high (Tertile 3) consumption of quercetin-rich food.

Odds ratios and Hazard ratios (95% Confidence Intervals) for lung cancer and nut consumption in EAGLE and AARP, by smoking status

Pearson's correlation and covariance between nuts consumption and nutrients and smoking variables in controls

PDF file - 51K, Selected characteristics of included and excluded EAGLE cases

Hazard ratios (95% Confidence Intervals) for the lag analyses by 5 years and 10 years for lung cancer and nut consumption in AARP, by smoking status

Supplementary Data from MicroRNA Expression Differentiates Histology and Predicts Survival of Lung Cancer

Hazard ratios (95% Confidence Intervals) for the lag analyses by 5 years and 10 years for lung cancer and nut consumption in AARP, by histologic subtypes

Supplementary Table 1 from Intakes of Red Meat, Processed Meat, and Meat Mutagens Increase Lung Cancer Risk

Supplementary Table 2 from Intakes of Red Meat, Processed Meat, and Meat Mutagens Increase Lung Cancer Risk

Red and processed meat intake may increase lung cancer risk. However, the epidemiologic evidence is inconsistent and few studies have evaluated the role of meat mutagens formed during high cooking temperatures. We investigated the association of red meat, processed meat, and meat mutagen intake with lung cancer risk in Environment And Genetics in Lung cancer Etiology, a population-based case-control study. Primary lung cancer cases (n = 2,101) were recruited from 13 hospitals within the Lombardy region of Italy examining ∼80% of the cases from the area. Noncancer population controls (n = 2,120), matched to cases on gender, residence, and age, were randomly selected from the same catchment area. Diet was assessed in 1,903 cases and 2,073 controls and used in conjunction with a meat mutagen database to estimate intake of heterocyclic amines (HCA) and benzo(a)pyrene (BaP). Multivariable odds ratios (OR) and 95% confidence intervals (95% CI) for sex-specific tertiles of intake were calculated using unconditional logistic regression. Red and processed meat were positively associated with lung cancer risk (highest-versus-lowest tertile: OR, 1.8; 95% CI, 1.5–2.2; P trend < 0.001 and OR, 1.7; 95% CI, 1.4–2.1; P trend < 0.001, respectively); the risks were strongest among never smokers (OR, 2.4; 95% CI, 1.4–4.0; P trend = 0.001 and OR, 2.5; 95% CI, 1.5–4.2; P trend = 0.001, respectively). HCAs and BaP were significantly associated with increased risk of lung cancer. When separated by histology, significant positive associations for both meat groups were restricted to adenocarcinoma and squamous cell carcinoma but not small cell carcinoma of the lung. In summary, red meat, processed meat, and meat mutagens were independently associated with increased risk of lung cancer. [Cancer Res 2009;69(3):932–9]

The CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública. CIBERESP, SPAIN (...), Ji, X., Mukherjee, S., Landi, M.T., Bosse, Y., Joubert, P., Zhu, D., Gorlov, I., Xiao, X., Han, Y., Gorlova, O., Hung, R.J., Brhane, Y., Carreras-Torres, R., Christiani, D.C., Caporaso, N., Johansson, M., Liu, G., Bojesen, S.E., Le Marchand, L., Albanes, D., Bickeböller, H., Aldrich, M.C., Bush, W.S., Tardon, A., Rennert, G., Chen, C., Byun, J., Dragnev, K.H., Field, J.K., Kiemeney, L.F., Lazarus, P., Zienolddiny, S., Lam, S., Schabath, M.B., Andrew, A.S., Bertazzi, P.A., Pesatori, A.C., Diao, N., Su, L., Song, L., Zhang, R., Leighl, N., Johansen, J.S., Mellemgaard, A., Saliba, W., Haiman, C., Wilkens, L., Fernandez-Somoano, A., Fernandez-Tardon, G., Heijden, E.H.F.M., Kim, J.H., Davies, M.P.A., Marcus, M.W., Brunnström, H., Manjer, J., Melander, O., Muller, D.C., Overvad, K., Trichopoulou, A., Tumino, R., Goodman, G.E., Cox, A., Taylor, F., Woll, P., Wichmann, E., Muley, T., Risch, A., Rosenberger, A., Grankvist, K., Johansson, M., Shepherd, F., Tsao, M.-S., Arnold, S.M., Haura, E.B., Bolca, C., Holcatova, I., Janout, V., Kontic, M., Lissowska, J., Mukeria, A., Ognjanovic, S., Orlowski, T.M., Scelo, G., Swiatkowska, B., Zaridze, D., Bakke, P., Skaug, V., Butler, L.M., Offit, K., Srinivasan, P., Bandlamudi, C., Hellmann, M.D., Solit, D.B., Robson, M.E., Rudin, C.M., Stadler, Z.K., Taylor, B.S., Berger, M.F., Houlston, R., McLaughlin, J., Stevens, V., Nickle, D.C., Obeidat, M., Timens, W., Artigas, M.S., Shete, S., Brenner, H., Chanock, S., Brennan, P., McKay, J.D., Amos, C.I.

Objectives: To conduct a cross-sectional morbidity survey among 245 former employees of a pesticide production plant exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in New Zealand. Methods: Demographic factors and health information were collected in face-to-face interviews. TCDD, lipids, thyroid hormones, glucose and immunoglobulin G (IgG) were determined in non-fasting blood. For 111 participants, a neurological examination was conducted. Associations between health outcomes and working in a TCDD exposed job (prevalence 49%) and serum TCDD concentration≥10pg/g lipid (18%) were assessed using logistic regression whilst controlling for age, gender, smoking, body mass index and ethnicity. Results: Diabetes was more common in those who had worked in TCDD exposed jobs (OR 4.0, 95%CI 1.0–15.4) and in those with serum TCDD ≥10pg/g (OR 3.1, 95%CI 0.9–10.7). Non-fasting glucose levels >6.6mmol/l were more common in those with TCDD exposed jobs (OR 3.6, 95%CI 1.0–12.9), as were serum free thyroxine 41.7mmol/l (OR 2.5, 95%CI 1.1–5.7) and high density lipoprotein cholesterol (HDL)

Introduction Exposure to particulate matter with diameter ≤10 μm (PM10) entails well documented adverse effects on human health. In the last decade, concentration of PM10 in Lombardy (10 million inhabitants), Italy, has been gradually decreasing. We evaluated how the mortality burden due to PM10 varied in that same period. Methods We focused on 13 areas of the Region in 2003–2014: 11 cities with more than 50,000 inhabitants, 1 smaller alpine town and 1 agricultural province. For each area, we collected PM10 annual average concentrations and natural mortality data, and we used the posterior area-specific effects from a previous Bayesian meta-analysis to estimate the short-term impact of PM10 on mortality, in terms of deaths attributable (AD) to annual average exposures exceeding the WHO threshold of 20 μg/m3. Results PM10 annual average values showed a non-homogenous decreasing trend in the investigated time period in most of the areas. Overall, the population-weighted exposure levels decreased, except for a peak in 2011, but never met the WHO threshold. In 2003–2006, PM10 levels were responsible, on average, for 343.0 annual AD from natural causes that decreased to 253.5 in 2007–2010 and to 208.3 in 2011–2014. Overall we estimated that PM10 was responsible for about 1% of all natural deaths (min-max range: 0.86%–1.42%); the impact was heterogeneous among areas. Conclusions By collecting routinely available data for the most populated areas in Lombardy, we returned a picture of air pollution and health trends in the last decade. Notwithstanding the observed reduction in PM10 between 2003 and 2014 and the resulting decline in the number of AD, the impact is still relevant. Hence, appropriate policies for emission reduction could have a further beneficial effect on population health. Studies based on routine data and local effect estimates are recommended to properly inform the policy-making process.

Background Airborne particulate matter (PM) may induce epigenetic changes that potentially lead to chronic diseases. Histone modifications regulate gene expression by influencing chromatin structure that can change gene expression status. We evaluated whether traffic-derived PM exposure is associated with four types of environmentally inducible global histone H3 modifications. Methods The Beijing Truck Driver Air Pollution Study included 60 truck drivers and 60 office workers examined twice, 1–2 weeks apart, for ambient PM10 (both day-of and 14-day average exposures), personal PM2.5, black carbon (BC), and elemental components (potassium, sulfur, iron, silicon, aluminum, zinc, calcium, and titanium). For both PM10 measures, we obtained hourly ambient PM10 data for the study period from the Beijing Municipal Environmental Bureau's 27 representatively distributed monitoring stations. We then calculated a 24 h average for each examination day and a moving average of ambient PM10 measured in the 14 days prior to each examination. Examinations measured global levels of H3 lysine 9 acetylation (H3K9ac), H3 lysine 9 tri-methylation (H3K9me3), H3 lysine 27 tri-methylation (H3K27me3), and H3 lysine 36 tri-methylation (H3K36me3) in blood leukocytes collected after work. We used adjusted linear mixed-effect models to examine percent changes in histone modifications per each μg/m3 increase in PM exposure. Results In all participants each μg/m3 increase in 14-day average ambient PM10 exposure was associated with lower H3K27me3 (β=−1.1%, 95% CI: −1.6, −0.6) and H3K36me3 levels (β=−0.8%, 95% CI: −1.4, −0.1). Occupation-stratified analyses showed associations between BC and both H3K9ac and H3K36me3 that were stronger in office workers (β=4.6%, 95% CI: 0.9, 8.4; and β=4.1%, 95% CI: 1.3; 7.0 respectively) than in truck drivers (β=0.1%, 95% CI: −1.3, 1.5; and β=0.9%, 95% CI: −0.9, 2.7, respectively; both pinteraction Conclusions Our results suggest a possible role of global histone H3 modifications in effects of traffic-derived PM exposures, particularly BC exposure. Future studies should assess the roles of these modifications in human diseases and as potential mediators of air pollution-induced disease, in particular BC exposure.

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

The aims of this study were (1) to explore the behavioral and sociodemographic factors influencing urinary cotinine (COT-U) levels in active smokers and in environmental tobacco smoke (ETS)-exposed individuals, (2) to assess the specificity and sensitivity of the questionnaire for identifying active smokers and nonsmokers, and (3) to derive the upper reference value of COT-U in non-ETS exposed individuals. The COT-U levels of 495 adults (age range 18-69 years) who classified themselves as active smokers (29%) or as nonsmokers with (17%) or without (83%) ETS exposure were quantified by LC-MS-MS (quantification limit: 0.1µg/L, range of linearity: 0.1-4000µg/L). Median COT-U levels in these groups were 883, 1.38, and 0.39µg/L, respectively. Significant determinants of COT-U levels in active smokers were the number of cigarettes per day, type of smoking product, smoking environment, as well as time between the last cigarette and urine collection. Among ETS-exposed nonsmokers, significant determinants were living with smokers, being exposed to smoke at home, ETS exposure duration, as well as time between the last exposure and urine collection. When a 30-µg/L COT-U cut-off value was used to identify active daily smoking, the sensitivity and specificity of the questionnaire were 94% and 98%, respectively. For ETS exposure, the COT-U value of 1.78 (0.90 confidence interval 1.75-1.78) µg/L, corresponding to the 95th percentiles of the COT-U distribution in non-ETS-exposed participants, is proposed as upper reference value to identify environmental exposure.

Background MicroRNAs (miRNAs) are post-transcriptional gene suppressors and potential mediators of environmental effects. In addition to human miRNAs, viral miRNAs expressed from latent viral sequences are detectable in human cells. Objective In a highly exposed population in Beijing, China, we evaluated the associations of particulate air pollution exposure on blood miRNA profiles. Methods The Beijing Truck Driver Air Pollution Study (BTDAS) included 60 truck drivers and 60 office workers. We investigated associations of short-term air pollution exposure, using measures of personal PM2.5 (particulate matter ≤ 2.5 μm) and elemental carbon (EC), and ambient PM10 (≤ 10 μm), with blood NanoString nCounter miRNA profiles at two exams separated by 1–2 weeks. Results No miRNA was significantly associated with personal PM2.5 at a false discovery rate (FDR) of 20%. Short-term ambient PM10 was associated with the expression of 12 miRNAs in office workers only (FDR < 20%). Short-term EC was associated with differential expression of 46 human and 7 viral miRNAs, the latter including 3 and 4 viral miRNAs in office workers and truck drivers, respectively. EC-associated miRNAs differed between office workers and truck drivers with significant effect modification by occupational group. Functional interaction network analysis suggested enriched cellular proliferation/differentiation pathways in truck drivers and proinflammation pathways in office workers. Conclusions Short-term EC exposure was associated with the expression of human and viral miRNAs that may influence immune responses and other biological pathways. Associations between EC exposure and viral miRNA expression suggest that latent viral miRNAs are potential mediators of air pollution–associated health effects. PM2.5/PM10 exposures showed no consistent relationships with miRNA expression. Citation Hou L, Barupal J, Zhang W, Zheng Y, Liu L, Zhang X, Dou C, McCracken JP, Díaz A, Motta V, Sanchez-Guerra M, Wolf KR, Bertazzi PA, Schwartz JD, Wang S, Baccarelli AA. 2016. Particulate air pollution exposure and expression of viral and human microRNAs in blood: the Beijing Truck Driver Air Pollution Study. Environ Health Perspect 124:344–350; http://dx.doi.org/10.1289/ehp.1408519

Supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA) of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública., Ji, X., Bossé, Y., Landi, M.T., Gui, J., Xiao, X., Qian, D., Joubert, P., Lamontagne, M., Li, Y., Gorlov, I., de Biasi, M., Han, Y., Gorlova, O., Hung, R.J., Wu, X., McKay, J., Zong, X., Carreras-Torres, R., Christiani, D.C., Caporaso, N., Johansson, M., Liu, G., Bojesen, S.E., Le Marchand, L., Albanes, D., Bickeböller, H., Aldrich, M.C., Bush, W.S., Tardon, A., Rennert, G., Chen, C., Teare, M.D., Field, J.K., Kiemeney, L.A., Lazarus, P., Haugen, A., Lam, S., Schabath, M.B.,,rew, A.S., Shen, H., Hong, Y.-C., Yuan, J.-M., Bertazzi, P.A., Pesatori, A.C., Ye, Y., Diao, N., Su, L., Zhang, R., Brhane, Y., Leighl, N., Johansen, J.S., Mellemgaard, A., Saliba, W., Haiman, C., Wilkens, L., Fernandez-Somoano, A., Fernandez-Tardon, G., van der Heijden, E.H.F.M., Kim, J.H., Dai, J., Hu, Z., Davies, M.P.A., Marcus, M.W., Brunnström, H., Manjer, J., Melander, O., Muller, D.C., Overvad, K., Trichopoulou, A., Tumino, R., Doherty, J., Goodman, G.E., Cox, A., Taylor, F., Woll, P., Brüske, I., Manz, J., Muley, T., Risch, A., Rosenberger, A., Grankvist, K., Johansson, M., Shepherd, F., Tsao, M.-S., Arnold, S.M., Haura, E.B., Bolca, C., Holcatova, I., Janout, V., Kontic, M., Lissowska, J., Mukeria, A., Ognjanovic, S., Orlowski, T.M., Scelo, G., Swiatkowska, B., Zaridze, D., Bakke, P., Skaug, V., Zienolddiny, S., Duell, E.J., Butler, L.M., Koh, W.-P., Gao, Y.-T., Houlston, R., McLaughlin, J., Stevens, V., Nickle, D.C., Obeidat, M., Timens, W., Zhu, B., Song, L., Artigas, M.S., Tobin, M.D., Wain, L.V., Gu, F., Byun, J., Kamal, A., Zhu, D., Tyndale, R.F., Wei, W.-Q., Chanock, S., Brennan, P., Amos, C.I.

Background Indian Asians, who make up a quarter of the world's population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes. Methods We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p

Airborne exposure to particulate matter with diameter

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never-versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13 336 non-small cell lung cancer cases. Candidate SNPs with P-value

The P-value is widely used as a summary statistics of scientific results. Unfortunately, there is a widespread tendency to dichotomize its value in "P0.05" (defined as "statistically significant") and "P0.05" ("statistically not significant"), with the former implying a "positive" result and the latter a "negative" one.To show the unsuitability of such an approach when evaluating the effects of environmental and occupational risk factors.We provide examples of distorted use of P-value and of the negative consequences for science and public health of such a black-and-white vision.The rigid interpretation of P-value as a dichotomy favors the confusion between health relevance and statistical significance, discourages thoughtful thinking, and distorts attention from what really matters, the health significance.A much better way to express and communicate scientific results involves reporting effect estimates (e.g., risks, risks ratios or risk differences) and their confidence intervals (CI), which summarize and convey both health significance and statistical uncertainty. Unfortunately, many researchers do not usually consider the whole interval of CI but only examine if it includes the null-value, therefore degrading this procedure to the same P-value dichotomy (statistical significance or not).In reporting statistical results of scientific research present effects estimates with their confidence intervals and do not qualify the P-value as "significant" or "not significant".