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Introduction: We investigated the impact of changes in lifestyle habits on colorectal cancer (CRC) risk in a multicountry European cohort. Methods: We used baseline and follow-up questionnaire data from the European Prospective Investigation into Cancer cohort to assess changes in lifestyle habits and their associations with CRC development. We calculated a healthy lifestyle index (HLI) score based on smoking status, alcohol consumption, body mass index, and physical activity collected at the 2 time points. HLI ranged from 0 (most unfavorable) to 16 (most favorable). We estimated the association between HLI changes and CRC risk using Cox regression models and reported hazard ratios (HR) with 95% confidence intervals (CI). Results: Among 295,865 participants, 2,799 CRC cases were observed over a median of 7.8 years. The median time between questionnaires was 5.7 years. Each unit increase in HLI from the baseline to the follow-up assessment was associated with a statistically significant 3% lower CRC risk. Among participants in the top tertile at baseline (HLI > 11), those in the bottom tertile at follow-up (HLI ≤ 9) had a higher CRC risk (HR 1.34; 95% CI 1.02-1.75) than those remaining in the top tertile. Among individuals in the bottom tertile at baseline, those in the top tertile at follow-up had a lower risk (HR 0.77; 95% CI 0.59-1.00) than those remaining in the bottom tertile. Discussion: Improving adherence to a healthy lifestyle was inversely associated with CRC risk, while worsening adherence was positively associated with CRC risk. These results justify and support recommendations for healthy lifestyle changes and healthy lifestyle maintenance for CRC prevention.

The COVID-19 pandemic introduced changes in people’s lives that affected their mental health. Our study aimed to explore the level of psychological distress in the academic population during the lockdown period and investigate its association with the new working or studying conditions. The study sample included 9364 students and 2159 employees from five Italian universities from the study IO CONTO 2020. We applied linear regression models to investigate the association between home learning or remote working conditions and psychological distress, separately for students and employees. Psychological distress was assessed using the Hospital Anxiety and Depression Scale (HADS). In both students and employees, higher levels of distress were significantly associated with study/work–family conflicts, concerns about their future careers, and inadequacy of equipment; in employees, higher levels of distress were significantly associated with a lack of clarity on work objectives. Our results are in line with previous research on the impact of spaces and equipment in remote working/studying from home. Moreover, the study contributes to deepening the association between well-being and telework–family conflict, which in the literature is still equivocal. Practical implications require academic governance to promote sustainable environments both in remote and hybrid work conditions, by referring to a specific management by objectives approach.

Experimental evidence suggests that alcohol induces cutaneous carcinogenesis, yet epidemiological studies on the link between alcohol intake and skin cancer have been inconsistent. The European Prospective Investigation into Cancer and Nutrition (EPIC) is a prospective cohort initiated in 1992 in 10 European countries. Alcohol intake at baseline and average lifetime alcohol intake were assessed using validated country-specific dietary and lifestyle questionnaires. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated in Cox models. A total of 14 037 skin cancer cases (melanoma: n = 2457; basal-cell carcinoma (BCC): n = 8711; squamous-cell carcinoma (SCC): n = 1928; unknown: n = 941) were identified among 450 112 participants (average follow-up: 15 years). Baseline alcohol intake was positively associated with SCC (>15 vs 0.1-4.9 g/day: HR = 1.44, 95% CI = 1.17-1.77; Ptrend = .001), BCC (HR = 1.12, 95% CI = 1.01-1.23; Ptrend = .04), and melanoma risks in men (HR = 1.17, 95% CI = 0.95-1.44; Ptrend = .17), while associations were more modest in women (SCC: HR = 1.09, 95% CI = 0.90-1.30; Ptrend = .13; BCC: HR = 1.08, 95% CI = 1.00-1.17, Ptrend = .03; melanoma: HR = 0.93, 95% CI = 0.80-1.08, Ptrend = .13). Associations were similar for lifetime alcohol intake, with an attenuated linear trend. Lifetime liquor/spirit intake was positively associated with melanoma (fourth vs first quartile: HR = 1.47, 95% CI = 1.08-1.99; Ptrend = .0009) and BCC risks in men (HR = 1.17, 95% CI = 1.04-1.31; Ptrend = .14). Baseline and lifetime intakes of wine were associated with BCC risk (HR = 1.25 in men; HR = 1.11-1.12; in women). No statistically significant associations were found between beverage types and SCC risk. Intake of beer was not associated with skin cancer risk. Our study suggests positive relationships between alcohol intake and skin cancer risk, which may have important implications for the primary prevention of skin cancer.

Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case-control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1-1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B-cell neoplasms: +8%). Methylation scores for smoking, BMI and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.

Background: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. Methods: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. Results: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and

BACKGROUND: Brominated flame retardants (BFR) and per- and polyfluorinated alkylated substances (PFAS) are two groups of substances suspected to act as endocrine disruptors. Such substances could therefore be implicated in the occurrence of breast cancer, nevertheless, previous studies have led to inconstant results. Due to the large correlation between these substances, and the possibly non-linear effects they exert, evaluating their joint impact as mixtures on health remains challenging. This exploratory study aimed to generate hypotheses on the relationship between circulating levels of 7 BFR (6 polybrominated diphenyl ethers and 1 polybrominated biphenyls) and 11 PFAS and the risk of breast cancer in a case-control study nested in the E3N French prospective cohort by performing two methods: Principal Component Regression (PCR) models, and Bayesian Kernel Machine Regression (BKMR) models. METHODS: 194 post-menopausal breast cancer cases and 194 controls were included in the present study. Circulating levels of BFR and PFAS were measured by gas chromatography coupled to high-resolution mass spectrometry and liquid chromatography coupled to tandem mass spectrometry, respectively. The first statistical approach was based on Principal Component Analysis (PCA) followed by logistic regression models that included the identified principal components as main exposure variables. The second approach used BKMR models with hierarchical variable selection, this latter being suitable for highly correlated exposures. Both approaches were also run separately for Estrogen Receptor positive (ER +) and Estrogen Receptor negative (ER-) breast cancer cases. RESULTS: PCA identified four principal components accounting for 67% of the total variance. Component 3 showed a marginal association with ER + breast cancer risk. No clear association between BFR and PFAS mixtures and breast cancer was identified using BKMR models, and the credible intervals obtained were very wide. Finally, the

BACKGROUND: Many patients report persistent symptoms after COVID-19. Our aim was to determine whether some of these symptoms were more associated with past SARS-CoV-2 infection compared to other conditions. METHODS: This prospective survey was nested in CONSTANCES, a randomly selected French population-based cohort, started in 2012. All participants being followed-up by internet completed 2 questionnaires during the first wave of the pandemic focusing on the acute symptoms of their COVID-19-like illness. Serological tests for SARS-CoV-2 were then performed (May-Nov 2020). Between December 2020 and January 2021, participants completed a third questionnaire about symptoms that had lasted more than 2 months. Participants were classified into four groups according to both European Center for Diseases Control (ECDC) criteria for COVID-19 (ECDC+ or ECDC-) and serological SARS-CoV-2 test results (Sero+ or Sero-). To compare the risk of each persistent symptom among the groups, logistic regression models were adjusted for age, sex, educational level, comorbidities, and the number of acute symptoms declared during the first wave of the epidemic. A mediation analysis was performed to estimate the direct effect of the infection on persistent symptoms and its indirect effect via the initial clinical presentation. FINDINGS: The analysis was performed in 25,910 participants. There was a higher risk of persistent dysgeusia/anosmia, dyspnea and asthenia in the ECDC+/Sero+ group than in the ECDC+/Sero- group (OR: 6.83 [4.47-10.42], 1.69 [1.07-2.6] and 1.48 [1.05-2.07], respectively). Abdominal pain, sensory symptoms or sleep disorders were at lower risk in the ECDC+/Sero+ group than in the ECDC+/Sero- group (0.51 [0.24-0.96], 0.40 [0.16-0.85], and 0.69 [0.49-0.95], respectively). The mediation analysis revealed that the association of the serological test results with each symptom was mainly mediated by ECDC symptoms (proportion mediated range 50-107%). CONCLUSION: A greater risk of

BACKGROUND: Few studies have examined the interactions between individual socioeconomic position and neighbourhood deprivation and the findings so far are heterogeneous. Using a large sample of diverse cohorts, we investigated the interaction effect of neighbourhood socioeconomic deprivation and individual socioeconomic position, assessed using education, on mortality. METHODS: We did a longitudinal multicohort analysis that included six cohort studies participating in the European LIFEPATH consortium: the CoLaus (Lausanne, Switzerland), E3N (France), EPIC-Turin (Turin, Italy), EPIPorto (Porto, Portugal), Melbourne Collaborative Cohort Study (Melbourne, VIC, Australia), and Whitehall II (London, UK) cohorts. All participants with data on mortality, educational attainment, and neighbourhood deprivation were included in the present study. The data sources were the databases of each cohort study. Poisson regression was used to estimate the mortality rates and associations (relative risk, 95% CIs) with neighbourhood deprivation (Q1 being least deprived to Q5 being the most deprived). Baseline educational attainment was used as an indicator of individual socioeconomic position. Estimates were combined using pooled analysis and the relative excess risk due to the interaction was computed to identify additive interactions. FINDINGS: The cohorts comprised a total population of 168 801 individuals. The recruitment dates were 2003-06 for CoLaus, 1989-91 for E3N, 1992-98 for EPIC-Turin, 1999-2003 for EPIPorto, 1990-94 for MCCS, and 1991-94 for Whitehall II. We use baseline data only and mortality data obtained using record linkage. Age-adjusted mortality rates were higher among participants residing in more deprived neighbourhoods than those in the least deprived neighbourhoods (Q1 least deprived neighbourhoods, 369·7 per 100 000 person-years [95% CI 356·4-383·2] vs Q5-most deprived neighbourhoods 445·7 per 100 000 person-years [430·2-461·7]), but the magnitude of the associat

BACKGROUND & AIMS: Gastrointestinal cancer risk is influenced by the presence of metabolic syndrome (MetS). However, previous epidemiologic studies lacked full serological biomarker data for the classification of MetS, and the interaction of MetS with germline cancer risk variants is unknown. METHODS: We investigated the associations between MetS and gastrointestinal cancer risk (overall, colorectal, pancreatic, esophageal adenocarcinoma, esophageal squamous cell carcinoma, stomach cardia, stomach non-cardia, hepatocellular carcinoma, and intrahepatic bile duct cancer) in 366,016 United Kingdom Biobank participants with comprehensive serum biomarker and genotype data. MetS status was determined by 3 different definitions at baseline, and, in 15,152 participants, at a repeat assessment after a median of 4.3 years of follow-up. Multivariable hazard ratios and 95% confidence intervals for cancer outcomes were estimated using Cox proportional hazards models. Analyses stratified by polygenic risk score were conducted for colorectal and pancreatic cancers. RESULTS: During a median follow-up of 7.1 years, 4238 incident cases of a gastrointestinal cancer occurred. MetS at baseline was associated with higher risk of overall gastrointestinal cancer by any definition (hazard ratio, 1.21; 95% confidence interval, 1.13-1.29, harmonized definition). MetS was associated with increased risks of colorectal cancer, colon cancer, rectal cancer, hepatocellular carcinoma, pancreatic cancer in women, and esophageal adenocarcinoma in men. Associations for colorectal cancer and pancreatic cancer did not differ by polygenic risk score strata (P-heterogeneity 0.70 and 0.69, respectively), and 80% of participants with MetS at baseline retained this status at the repeat assessment. CONCLUSIONS: These findings underscore the importance of maintaining good metabolic health in reducing the burden of gastrointestinal cancers, irrespective of genetic predisposition.

BACKGROUND & AIMS: Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort. METHODS: Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression. RESULTS: Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants. CONCLUSIONS: Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.

Contains fulltext : 252185.pdf (Publisher’s version ) (Open Access), BACKGROUND: The role of elevated pre-diagnostic C-reactive protein (CRP) concentrations on mortality in individuals with colorectal cancer (CRC) remains unclear. METHODS: We investigated the association between pre-diagnostic high-sensitivity CRP concentrations and CRP genetic variation associated with circulating CRP and CRC-specific and all-cause mortality based on data from 1,235 individuals with CRC within the European Prospective Investigation into Cancer and Nutrition cohort using multivariable-adjusted Cox proportional hazards regression. RESULTS: During a median follow-up of 9.3 years, 455 CRC-specific deaths were recorded, out of 590 deaths from all causes. Pre-diagnostic CRP concentrations were not associated with CRC-specific (hazard ratio, HR highest versus lowest quintile 0.92, 95% confidence interval, CI 0.66, 1.28) or all-cause mortality (HR 0.91, 95% CI 0.68, 1.21). Genetic predisposition to higher CRP (weighted score based on alleles of four CRP SNPs associated with higher circulating CRP) was not significantly associated with CRC-specific mortality (HR per CRP-score unit 0.95, 95% CI 0.86, 1.05) or all-cause mortality (HR 0.98, 95% CI 0.90, 1.07). Among four investigated CRP genetic variants, only SNP rs1205 was significantly associated with CRC-specific (comparing the CT and CC genotypes with TT genotype, HR 0.54, 95% CI 0.35, 0.83 and HR 0.58, 95% CI 0.38, 0.88, respectively) and all-cause mortality (HR 0.58, 95% CI 0.40, 0.85 and 0.64, 95% CI 0.44, 0.92, respectively). CONCLUSIONS: The results of this prospective cohort study do not support a role of pre-diagnostic CRP concentrations on mortality in individuals with CRC. The observed associations with rs1205 deserve further scientific attention.

BACKGROUND: The role of elevated pre-diagnostic C-reactive protein (CRP) concentrations on mortality in individuals with colorectal cancer (CRC) remains unclear. METHODS: We investigated the association between pre-diagnostic high-sensitivity CRP concentrations and CRP genetic variation associated with circulating CRP and CRC-specific and all-cause mortality based on data from 1,235 individuals with CRC within the European Prospective Investigation into Cancer and Nutrition cohort using multivariable-adjusted Cox proportional hazards regression. RESULTS: During a median follow-up of 9.3 years, 455 CRC-specific deaths were recorded, out of 590 deaths from all causes. Pre-diagnostic CRP concentrations were not associated with CRC-specific (hazard ratio, HR highest versus lowest quintile 0.92, 95% confidence interval, CI 0.66, 1.28) or all-cause mortality (HR 0.91, 95% CI 0.68, 1.21). Genetic predisposition to higher CRP (weighted score based on alleles of four CRP SNPs associated with higher circulating CRP) was not significantly associated with CRC-specific mortality (HR per CRP-score unit 0.95, 95% CI 0.86, 1.05) or all-cause mortality (HR 0.98, 95% CI 0.90, 1.07). Among four investigated CRP genetic variants, only SNP rs1205 was significantly associated with CRC-specific (comparing the CT and CC genotypes with TT genotype, HR 0.54, 95% CI 0.35, 0.83 and HR 0.58, 95% CI 0.38, 0.88, respectively) and all-cause mortality (HR 0.58, 95% CI 0.40, 0.85 and 0.64, 95% CI 0.44, 0.92, respectively). CONCLUSIONS: The results of this prospective cohort study do not support a role of pre-diagnostic CRP concentrations on mortality in individuals with CRC. The observed associations with rs1205 deserve further scientific attention.

Assessment of the intensity, dynamics and determinants of the antibody response after SARS-CoV-2 infection or vaccination in the general population is critical to guide vaccination policies. This study characterized the anti-spike IgG titers in 13,971 participants included in a French multicohort population-based serological survey on COVID-19 between April and October 2020 and followed-up with serological testing between May and October 2021. Eight follow-up profiles were defined depending on SARS-CoV-2 infection (0, 1 or 2) and COVID-19 vaccination (0, 1, 2 or 3). The anti-spike titer was lower in adults with no vaccination even in case of infection or reinfection, while it was higher in adults with infection followed by vaccination. The anti-spike titer was negatively correlated with age in vaccinated but uninfected adults, whereas it was positively correlated with age in unvaccinated but infected adults. In adults with 2 vaccine injections and no infection, the vaccine protocol, age, gender, and time since the last vaccine injection were independently associated with the anti-spike titer. The decrease in anti-spike titer was much more rapid in vaccinated than in infected subjects. These results highlight the strong heterogeneity of the antibody response against SARS-CoV-2 in the general population depending on previous infection and vaccination.

BACKGROUND: Little is known about the association between physical activity before cancer diagnosis and survival among lung cancer patients. In this pooled analysis of 11 prospective cohorts, we investigated associations of prediagnosis leisure-time physical activity (LTPA) with all-cause and lung cancer-specific mortality among incident lung cancer patients. METHODS: Using self-reported data on regular engagement in exercise and sports activities collected at study enrollment, we assessed metabolic equivalent hours (MET-h) of prediagnosis LTPA per week. According to the Physical Activity Guidelines for Americans, prediagnosis LTPA was classified into inactivity, less than 8.3 and at least 8.3 MET-h per week (the minimum recommended range). Cox regression was used to estimate hazard ratios (HRs) and 95% confidence interval (CIs) for all-cause and lung cancer-specific mortality after adjustment for major prognostic factors and lifetime smoking history. RESULTS: Of 20 494 incident lung cancer patients, 16 864 died, including 13 596 deaths from lung cancer (overall 5-year relative survival rate = 20.9%, 95% CI = 20.3% to 21.5%). Compared with inactivity, prediagnosis LTPA of more than 8.3 MET-h per week was associated with a lower hazard of all-cause mortality (multivariable-adjusted HR = 0.93, 95% CI = 0.88 to 0.99), but not with lung cancer-specific mortality (multivariable-adjusted HR = 0.99, 95% CI = 0.95 to 1.04), among the overall population. Additive interaction was found by tumor stage (Pinteraction = .008 for all-cause mortality and .003 for lung cancer-specific mortality). When restricted to localized cancer, prediagnosis LTPA of at least 8.3 MET-h per week linked to 20% lower mortality: multivariable-adjusted HRs were 0.80 (95% CI = 0.67 to 0.97) for all-cause mortality and 0.80 (95% CI = 0.65 to 0.99) for lung cancer-specific mortality. CONCLUSIONS: Regular participation in LTPA that met or exceeded the minimum Physical Activity Guidelines was associated wi

BACKGROUND: DNA methylation in blood may reflect adverse exposures accumulated over the lifetime and could therefore provide potential improvements in the prediction of cancer risk. A substantial body of research has shown associations between epigenetic aging and risk of disease, including cancer. Here we aimed to study epigenetic measures of aging and lifestyle-related factors in association with risk of breast cancer. METHODS: Using data from four prospective case-control studies nested in three cohorts of European ancestry participants, including a total of 1,655 breast cancer cases, we calculated three methylation-based measures of lifestyle factors (body mass index [BMI], tobacco smoking and alcohol consumption) and seven measures of epigenetic aging (Horvath-based, Hannum-based, PhenoAge and GrimAge). All measures were regression-adjusted for their respective risk factors and expressed per standard deviation (SD). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional or unconditional logistic regression and pooled using fixed-effects meta-analysis. Subgroup analyses were conducted by age at blood draw, time from blood sample to diagnosis, oestrogen receptor-positivity status and tumour stage. RESULTS: None of the measures of epigenetic aging were associated with risk of breast cancer in the pooled analysis: Horvath 'age acceleration' (AA): OR per SD = 1.02, 95%CI: 0.95-1.10; AA-Hannum: OR = 1.03, 95%CI:0.95-1.12; PhenoAge: OR = 1.01, 95%CI: 0.94-1.09 and GrimAge: OR = 1.03, 95%CI: 0.94-1.12, in models adjusting for white blood cell proportions, body mass index, smoking and alcohol consumption. The BMI-adjusted predictor of BMI was associated with breast cancer risk, OR per SD = 1.09, 95%CI: 1.01-1.17. The results for the alcohol and smoking methylation-based predictors were consistent with a null association. Risk did not appear to substantially vary by age at blood draw, time to diagnosis or tumour characteristics. CONCLUSION

Smoking-related epigenetic changes have been linked to lung cancer, but the contribution of epigenetic alterations unrelated to smoking remains unclear. We sought for a sparse set of CpG sites predicting lung cancer and explored the role of smoking in these associations. We analysed CpGs in relation to lung cancer in participants from two nested case-control studies, using (LASSO)-penalised regression. We accounted for the effects of smoking using known smoking-related CpGs, and through conditional-independence network. We identified 29 CpGs (8 smoking-related, 21 smoking-unrelated) associated with lung cancer. Models additionally adjusted for Comprehensive Smoking Index-(CSI) selected 1 smoking-related and 49 smoking-unrelated CpGs. Selected CpGs yielded excellent discriminatory performances, outperforming information provided by CSI only. Of the 8 selected smoking-related CpGs, two captured lung cancer-relevant effects of smoking that were missed by CSI. Further, the 50 CpGs identified in the CSI-adjusted model complementarily explained lung cancer risk. These markers may provide further insight into lung cancer carcinogenesis and help improving early identification of high-risk patients.

BACKGROUND: Current epidemiologic evidence indicates that smoking is associated with a lower endometrial cancer risk. However, it is unknown if this association is causal or confounded. To further elucidate the role of smoking in endometrial cancer risk, we conducted complementary observational and Mendelian randomization (MR) analyses. METHODS: The observational analyses included 286,415 participants enrolled in the European Prospective Investigation into Cancer and Nutrition and 179,271 participants in the UK Biobank, and multivariable Cox proportional hazards models were used. In two-sample MR analyses, genetic variants robustly associated with lifetime amount of smoking (n = 126 variants) and ever having smoked regularly (n = 112 variants) were selected and their association with endometrial cancer risk (12,906 cancer/108,979 controls from the Endometrial Cancer Association Consortium) was examined. RESULTS: In the observational analysis, lifetime amount of smoking and ever having smoked regularly were associated with a lower endometrial cancer risk. In the MR analysis accounting for body mass index, a genetic predisposition to a higher lifetime amount of smoking was not associated with endometrial cancer risk (OR per 1-SD increment: 1.15; 95% confidence interval: 0.91-1.44). Genetic predisposition to ever having smoked regularly was not associated with risk of endometrial cancer. CONCLUSIONS: Smoking was inversely associated with endometrial cancer in the observational analyses, although unsupported by the MR. Additional studies are required to better understand the possible confounders and mechanisms underlying the observed associations between smoking and endometrial cancer. IMPACT: The results from this analysis indicate that smoking is unlikely to be causally linked with endometrial cancer risk.

BACKGROUND: Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS: We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS: Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS: These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

BACKGROUND: The interplay between age and symptoms intensity on antibody response to SARS-CoV-2 infection has not been studied in a general population setting. METHODS: We explored the serologic profile of anti-SARS-CoV-2 antibodies after the first wave of the pandemic, by assessing IgG against the spike protein (ELISA-S), IgG against the nucleocapsid protein (ELISA-NP) and neutralizing antibodies (SN) in 82,126 adults from a French population-based multi-cohort study. RESULTS: ELISA-S positivity was increased in 30- to 49-year-old adults (8.5%) compared to other age groups (5.6% in 20- to 29-year-olds, 2.8% in ≥ 50-year-olds). In the 3681 ELISA-S positive participants, ELISA-NP and SN positivity exhibited a U-shaped relationship with age, with a lower rate in 30- to 49-year-old adults, and was strongly associated with COVID-19-like symptoms. CONCLUSION: Our study confirms the independent role of age and symptoms on the serologic profile of anti-SARS-CoV-2 antibodies, but the non-linear relationship with age deserves further investigation.

Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene-environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10-14), ~0.6% (P = 2 × 10-7), and ~8.7% (P = 7 × 10-87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: -0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: -0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.

Background: Alcohol intake is an established risk factor for colorectal cancer (CRC); however, there is limited knowledge on whether changing alcohol drinking habits during adulthood modifies CRC risk. Objective: Leveraging longitudinal exposure assessments on alcohol intake at different ages, we examined the relationship between change in alcohol intake and subsequent CRC risk. Methods: Within the European Prospective Investigation into Cancer and Nutrition, changes in alcohol intake comparing follow-up with baseline assessments were investigated in relation to CRC risk. The analysis included 191,180, participants and 1530 incident CRC cases, with exclusion of the first three years of follow-up to minimize reverse causation. Trajectory profiles of alcohol intake, assessed at ages 20, 30, 40, 50 years, at baseline and during follow-up, were estimated using latent class mixed models and related to CRC risk, including 407,605 participants and 5,008 incident CRC cases. Results: Mean age at baseline was 50.2 years and the follow-up assessment occurred on average 7.1 years later. Compared to stable intake, a 12 g/day increase in alcohol intake during follow-up was positively associated with CRC risk (HR = 1.15, 95%CI 1.04, 1.25), while a 12 g/day reduction was inversely associated with CRC risk (HR = 0.86, 95%CI 0.78, 0.95). Trajectory analysis showed that compared to low alcohol intake, men who increased their alcohol intake from early- to mid- and late-adulthood by up to 30 g/day on average had significantly increased CRC risk (HR = 1.24; 95%CI 1.08, 1.42), while no associations were observed in women. Results were consistent by anatomical subsite. Conclusions: Increasing alcohol intake during mid-to-late adulthood raised CRC risk, while reduction lowered risk.