Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

Association of body shape phenotypes and body fat distribution indexes with inflammatory biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank.

BACKGROUND: The allometric body shape index (ABSI) and hip index (HI), as well as multi-trait body shape phenotypes, have not yet been compared in their associations with inflammatory markers. The aim of this study was to examine the relationship between novel and traditional anthropometric indexes with inflammation using data from the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. METHODS: Participants from EPIC (n = 17,943, 69.1% women) and UK Biobank (n = 426,223, 53.2% women) with data on anthropometric indexes and C-reactive protein (CRP) were included in this cross-sectional analysis. A subset of women in EPIC also had at least one measurement for interleukins, tumour necrosis factor alpha, interferon gamma, leptin, and adiponectin. Four distinct body shape phenotypes were derived by a principal component (PC) analysis on height, weight, body mass index (BMI), waist (WC) and hip circumferences (HC), and waist-to-hip ratio (WHR). PC1 described overall adiposity, PC2 tall with low WHR, PC3 tall and centrally obese, and PC4 high BMI and weight with low WC and HC, suggesting an athletic phenotype. ABSI, HI, waist-to-height ratio and waist-to-hip index (WHI) were also calculated. Linear regression models were carried out separately in EPIC and UK Biobank stratified by sex and adjusted for age, smoking status, education, and physical activity. Results were additionally combined in a random-effects meta-analysis. RESULTS: Traditional anthropometric indexes, particularly BMI, WC, and weight were positively associated with CRP levels, in men and women. Body shape phenotypes also showed distinct associations with CRP. Specifically, PC2 showed inverse associations with CRP in EPIC and UK Biobank in both sexes, similarly to height. PC3 was inversely associated with CRP among women, whereas positive associations were observed among men. CONCLUSIONS: Specific indexes of body size and body fat distribution showed differential associations with inflammation in adults. Notably, our results suggest that in women, height may mitigate the impact of a higher WC and HC on inflammation. This suggests that subtypes of adiposity exhibit substantial variation in their inflammatory potential, which may have implications for inflammation-related chronic diseases.

The association of overweight, obesity, and long-term obesity with SARS-CoV-2 infection: a meta-analysis of 9 population-based cohorts from the Netherlands Cohorts Consortium.

BACKGROUND: Obesity may affect an individual's immune response and subsequent risk of infection, such as a SARS-CoV-2 infection. It is less clear whether overweight and long-term obesity also constitute risk factors. We investigated the association between the degree and duration of overweight and obesity and SARS-CoV-2 infection. METHODS: We analyzed data from nine prospective population-based cohorts of the Netherlands Cohorts Consortium, with a total of 99,570 participants, following a standardized procedure. Body mass index (BMI) and waist circumference (WC) were assessed two times before the pandemic, with approximately 5 years between measurements. SARS-CoV-2 infection was defined by self-report as a positive PCR or rapid-antigen test or as COVID-19 ascertained by a physician between March 2020 and January 2023. For three cohorts, information on SARS-CoV-2 infection by serology was available. Results were pooled using random-effects meta-analyses and adjusted for age, sex, educational level, and number of SARS-CoV-2 infection measurements. RESULTS: Individuals with overweight (25 ≤ BMI < 30 kg/m2) (odds ratio (OR) = 1.08, 95%-confidence interval (CI) 1.04-1.13) or obesity (BMI ≥ 30 kg/m2) (OR = 1.43, 95%-CI 1.18-1.75) were more likely to report SARS-CoV-2 infection than individuals with a healthy body weight. We observed comparable ORs for abdominal overweight (men: 94 cm≤WC < 102 cm, women: 80 cm≤WC < 88 cm) (OR = 1.09, 95%-CI 1.04-1.14, I2 = 0%) and abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) (OR = 1.24, 95%-CI 0.999-1.55, I2 = 57%). Individuals with obesity long before the pandemic, but with a healthy body weight or overweight just before the pandemic, were not at increased risk. CONCLUSION: Overweight and obesity were associated with increased risk of SARS-CoV-2 infection with stronger associations for obesity. Individuals with a healthier weight prior to the pandemic but previous obesity did not have an increased risk of SARS-CoV-2, suggesting that weight loss in those with obesity reduces infection risk. These results underline the importance of obesity prevention and weight management for public health.

The role of ultra-processed foods in plant-based diets: associations with human health and environmental sustainability.

PURPOSE: Investigate the associations of ultra-processed foods (UPF) in healthful (hPDI) and unhealthful (uPDI) plant-based diets with all-cause mortality, greenhouse gas emissions (GHGE), and blue water consumption (BWC). METHODS: Analyses were based on 35,030 participants (20-70 years; 74% females) from the EPIC-NL cohort who were followed up from 1993 to 1997 through 2014. Plant-based diet indices (hPDI and uPDI) and UPF consumption were calculated from a validated FFQ, assessed at baseline. Cox proportional hazard and multiple linear regression models were used to estimate associations between combined quartiles of the PDI indices and UPF consumption. RESULTS: With lower hPDI and higher UPF diets as the reference, we observed the following. Risk estimates of all-cause mortality were 0.98 (95% CI: 0.83, 1.16) for lower UPF consumption, 0.86 (95% CI: 0.68, 1.08) for higher hPDI, and 0.78 (95% CI: 0.66, 0.89) for combined higher hPDI and lower UPF consumption. Results with the uPDI were inconclusive. Mean differences in GHGE and BWC were 1.4% (95% CI: 0.3, 2.4) and 1.6% (95% CI: -0.5, 3.7) for lower UPF consumption, -7.4% (95% CI: -8.6, -6.4) and 9.6% (95% CI: 7.2, 12.0) for higher hPDI, and - 6.8% (95% CI: -7.4, -6.1) and 13.1% (95% CI: 11.6, 14.8) for combined higher hPDI and lower UPF consumption. No apparent conflict between environmental impacts was observed for the uPDI; GHGE and BWC were lower for higher uPDI scores. CONCLUSION: Mortality risk and environmental impacts were mostly associated with the amount of plant-based foods and to a lesser extent UPF in the diet. Shifting to a more healthful plant-based diet could improve human health and reduce most aspects of environmental impact (GHGE, but not BWC) irrespective of UPF consumption.

Dietary amino acids and risk of stroke subtypes: a prospective analysis of 356,000 participants in seven European countries.

PURPOSE: Previously reported associations of protein-rich foods with stroke subtypes have prompted interest in the assessment of individual amino acids. We examined the associations of dietary amino acids with risks of ischaemic and haemorrhagic stroke in the EPIC study. METHODS: We analysed data from 356,142 participants from seven European countries. Dietary intakes of 19 individual amino acids were assessed using validated country-specific dietary questionnaires, calibrated using additional 24-h dietary recalls. Multivariable-adjusted Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of ischaemic and haemorrhagic stroke in relation to the intake of each amino acid. The role of blood pressure as a potential mechanism was assessed in 267,642 (75%) participants. RESULTS: After a median follow-up of 12.9 years, 4295 participants had an ischaemic stroke and 1375 participants had a haemorrhagic stroke. After correction for multiple testing, a higher intake of proline (as a percent of total protein) was associated with a 12% lower risk of ischaemic stroke (HR per 1 SD higher intake 0.88; 95% CI 0.82, 0.94). The association persisted after mutual adjustment for all other amino acids, systolic and diastolic blood pressure. The inverse associations of isoleucine, leucine, valine, phenylalanine, threonine, tryptophan, glutamic acid, serine and tyrosine with ischaemic stroke were each attenuated with adjustment for proline intake. For haemorrhagic stroke, no statistically significant associations were observed in the continuous analyses after correcting for multiple testing. CONCLUSION: Higher proline intake may be associated with a lower risk of ischaemic stroke, independent of other dietary amino acids and blood pressure.

Self-Rated Health among Older Adults: Longitudinal Analyses Examining Sex Differences across Different Birth Cohorts and Educational Levels.

INTRODUCTION: Given the known female disadvantage in physical and mental health, this study aimed to investigate sex differences in self-rated health (SRH) among older adults, considering the longitudinal course by age, birth cohort, and educational level. METHODS: Data from birth cohort 1911-1937 with baseline age 55-81 years (n = 3,107) and birth cohort 1938-1947 with baseline age 55-65 years (n = 1,002) from the Longitudinal Aging Study Amsterdam (LASA) were used. Mixed model analyses were used to examine sex differences in SRH (RAND General Health Perception Questionnaire [RAND-GHPQ], range 0-16) over the age course, testing for effect modification by the birth cohort and educational level (low, middle, high). RESULTS: For both sexes, a decline in SRH was seen with increasing age. Over the age course, there was no significant sex difference in SRH within the older (1911-1937) birth cohort (0.13 lower score on SRH for women compared to men, 95% CI: -0.35 to 0.09) and only a small sex difference in the more recent (1938-1947) birth cohort (0.35 lower score on SRH for women compared to men [95% CI: -0.69 to -0.02], p = 0.04). There was no significant cohort difference in the size of the sex difference (p = 0.279). Those with a higher level of education reported a higher SRH, but between educational levels, there was no significant difference in the size of the sex difference in SRH. DISCUSSION: In this study, no relevant sex difference in SRH over the age course was observed among older adults. Future research on SRH trajectories by sex during aging should take health-related, cognitive, psychosocial, and behavioral factors into account.

Health characteristics associated with persistence of SARS-CoV-2 antibody responses after repeated vaccinations in older persons over time: the Doetinchem cohort study.

BACKGROUND: Older persons elicit heterogeneous antibody responses to vaccinations that generally are lower than those in younger, healthier individuals. As older age and certain comorbidities can influence these responses we aimed to identify health-related variables associated with antibody responses after repeated SARS-CoV-2 vaccinations and their persistence thereafter in SARS-CoV-2 infection-naïve and previously infected older persons. METHOD: In a large longitudinal study of older persons of the general population 50 years and over, a sub-cohort of the longitudinal Doetinchem cohort study (n = 1374), we measured IgG antibody concentrations in serum to SARS-CoV-2 Spike protein (S1) and Nucleoprotein (N). Samples were taken following primary vaccination with BNT162b2 or AZD1222, pre- and post-vaccination with a third and fourth BNT162b2 or mRNA-1273 (Wuhan), and up to a year after a fifth BNT162b2 bivalent (Wuhan/Omicron BA.1) vaccine. Associations between persistence of antibody concentrations over time and age, sex, health characteristics including cardiometabolic and inflammatory diseases as well as a frailty index were tested using univariable and multivariable models. RESULTS: The booster doses substantially increased anti-SARS-CoV-2 Spike S1 (S1) antibody concentrations in older persons against both the Wuhan and Omicron strains. Older age was associated with decreased antibody persistence both after the primary vaccination series and up to 1 year after the fifth vaccine dose. In infection-naïve persons the presence of inflammatory diseases was associated with an increased antibody response to the third vaccine dose (Beta = 1.53) but was also associated with reduced persistence over the 12 months following the fifth (bivalent) vaccine dose (Beta = -1.7). The presence of cardiometabolic disease was associated with reduced antibody persistence following the primary vaccination series (Beta = -1.11), but this was no longer observed after bivalent vaccination. CONCLUSION: Although older persons with comorbidities such as inflammatory and cardiometabolic diseases responded well to SARS-CoV-2 booster vaccinations, they showed a reduced persistence of these responses. This might indicate that especially these more vulnerable older persons could benefit from repeated booster vaccinations.

Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis.

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.

Potential determinants of antibody responses after vaccination against SARS-CoV-2 in older persons: the Doetinchem Cohort Study.

BACKGROUND: Immune responses to vaccination vary widely between individuals. The aim of this study was to identify health-related variables potentially underlying the antibody responses to SARS-CoV-2 vaccination in older persons. We recruited participants in the long-running Doetinchem Cohort Study (DCS) who underwent vaccination as part of the national COVID-19 program, and measured antibody concentrations to SARS-CoV-2 Spike protein (S1) and Nucleoprotein (N) at baseline (T0), and a month after both the first vaccination (T1), and the second vaccination (T2). Associations between the antibody concentrations and demographic variables, including age, sex, socio-economic status (SES), comorbidities (cardiovascular diseases and immune mediated diseases), various health parameters (cardiometabolic markers, inflammation markers, kidney- and lung function) and a composite measure of frailty ('frailty index', ranging from 0 to 1) were tested using multivariate models. RESULTS: We included 1457 persons aged 50 to 92 years old. Of these persons 1257 were infection naïve after their primary vaccination series. The majority (N = 954) of these individuals were vaccinated with two doses of BNT162b2 (Pfizer) and their data were used for further analysis. A higher frailty index was associated with lower anti-S1 antibody responses at T1 and T2 for both men (RT1 = -0.095, PT1 = 0.05; RT2 = -0.11, PT2 = 0.02) and women (RT1 = -0.24, PT1 < 0.01; RT2 = -0.15, PT2 < 0.01). After correcting for age and sex the frailty index was also associated with the relative increase in anti-S1 IgG concentrations between the two vaccinations (ß = 1.6, P < 0.01). Within the construct of frailty, history of a cardiac catheterization, diabetes, gastrointestinal disease, a cognitive speed in the lowest decile of the population distribution, and impaired lung function were associated with lower antibody responses after both vaccinations. CONCLUSIONS: Components of frailty play a key role in the primary vaccination response to the BNT162b2 vaccine within an ageing population. Older persons with various comorbidities have a lowered immune response after their first vaccination, and while frail and sick older persons see a stronger increase after their second vaccination compared to healthy people, they still have a lower antibody response after their second vaccination.

Long-term Air Pollution Exposure and Pneumonia-related Mortality in a Large Pooled European Cohort.

Rationale: Ambient air pollution exposure has been linked to mortality from chronic cardiorespiratory diseases, while evidence on respiratory infections remains more limited. Objectives: We examined the association between long-term exposure to air pollution and pneumonia-related mortality in adults in a pool of eight European cohorts. Methods: Within the multicenter project ELAPSE (Effects of Low-Level Air Pollution: A Study in Europe), we pooled data from eight cohorts among six European countries. Annual mean residential concentrations in 2010 for fine particulate matter, nitrogen dioxide (NO2), black carbon (BC), and ozone were estimated using Europe-wide hybrid land-use regression models. We applied stratified Cox proportional hazard models to investigate the associations between air pollution and pneumonia, influenza, and acute lower respiratory infections (ALRI) mortality. Measurements and Main Results: Of 325,367 participants, 712 died from pneumonia and influenza combined, 682 from pneumonia, and 695 from ALRI during a mean follow-up of 19.5 years. NO2 and BC were associated with 10-12% increases in pneumonia and influenza combined mortality, but 95% confidence intervals included unity (hazard ratios, 1.12 [0.99-1.26] per 10 µg/m3 for NO2; 1.10 [0.97-1.24] per 0.5 10-5m-1 for BC). Associations with pneumonia and ALRI mortality were almost identical. We detected effect modification suggesting stronger associations with NO2 or BC in overweight, employed, or currently smoking participants compared with normal weight, unemployed, or nonsmoking participants. Conclusions: Long-term exposure to combustion-related air pollutants NO2 and BC may be associated with mortality from lower respiratory infections, but larger studies are needed to estimate these associations more precisely.

Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study.

BACKGROUND: Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations. METHODS: Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20-29/30-39/40-49/50-59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46-85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors. RESULTS: The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model's performance was modest with an R2 of 17%. CONCLUSIONS: Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations.

Predicting self-perceived general health status using machine learning: an external exposome study.

BACKGROUND: Self-perceived general health (SPGH) is a general health indicator commonly used in epidemiological research and is associated with a wide range of exposures from different domains. However, most studies on SPGH only investigated a limited set of exposures and did not take the entire external exposome into account. We aimed to develop predictive models for SPGH based on exposome datasets using machine learning techniques and identify the most important predictors of poor SPGH status. METHODS: Random forest (RF) was used on two datasets based on personal characteristics from the 2012 and 2016 editions of the Dutch national health survey, enriched with environmental and neighborhood characteristics. Model performance was determined using the area under the curve (AUC) score. The most important predictors were identified using a variable importance procedure and individual effects of exposures using partial dependence and accumulated local effect plots. The final 2012 dataset contained information on 199,840 individuals and 81 variables, whereas the final 2016 dataset had 244,557 individuals with 91 variables. RESULTS: Our RF models had overall good predictive performance (2012: AUC = 0.864 (CI: 0.852-0.876); 2016: AUC = 0.890 (CI: 0.883-0.896)) and the most important predictors were "Control of own life", "Physical activity", "Loneliness" and "Making ends meet". Subjects who felt insufficiently in control of their own life, scored high on the De Jong-Gierveld loneliness scale or had difficulty in making ends meet were more likely to have poor SPGH status, whereas increased physical activity per week reduced the probability of poor SPGH. We observed associations between some neighborhood and environmental characteristics, but these variables did not contribute to the overall predictive strength of the models. CONCLUSIONS: This study identified that within an external exposome dataset, the most important predictors for SPGH status are related to mental wellbeing, physical exercise, loneliness, and financial status.

Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts.

AIMS/HYPOTHESIS: Type 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts. METHODS: We conducted a meta-analysis of EWASs in blood collected 7-10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK). RESULTS: The meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values <1.1 × 10-7). Sixty-four out of 76 (84.2%) CpG sites were confirmed by directionally consistent effects and p values <0.05 in an independent cohort of Indian Asians. However, on adjustment for baseline BMI only four CpG sites remained genome-wide significant, and addition of the 76 CpG methylation risk score to a prediction model including established predictors of type 2 diabetes (age, sex, BMI and HbA1c) showed no improvement (AUC 0.757 vs 0.753). Gene set enrichment analysis of the full epigenome-wide results clearly showed enrichment of processes linked to insulin signalling, lipid homeostasis and inflammation. CONCLUSIONS/INTERPRETATION: By combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development.

Long-term exposure to ambient air pollution and bladder cancer incidence in a pooled European cohort: the ELAPSE project.

BACKGROUND: The evidence linking ambient air pollution to bladder cancer is limited and mixed. METHODS: We assessed the associations of bladder cancer incidence with residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3) and eight PM2.5 elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in a pooled cohort (N = 302,493). Exposures were primarily assessed based on 2010 measurements and back-extrapolated to the baseline years. We applied Cox proportional hazard models adjusting for individual- and area-level potential confounders. RESULTS: During an average of 18.2 years follow-up, 967 bladder cancer cases occurred. We observed a positive though statistically non-significant association between PM2.5 and bladder cancer incidence. Hazard Ratios (HR) were 1.09 (95% confidence interval (CI): 0.93-1.27) per 5 µg/m3 for 2010 exposure and 1.06 (95% CI: 0.99-1.14) for baseline exposure. Effect estimates for NO2, BC and O3 were close to unity. A positive association was observed with PM2.5 zinc (HR 1.08; 95% CI: 1.00-1.16 per 10 ng/m3). CONCLUSIONS: We found suggestive evidence of an association between long-term PM2.5 mass exposure and bladder cancer, strengthening the evidence from the few previous studies. The association with zinc in PM2.5 suggests the importance of industrial emissions.

A Multipollutant Approach to Estimating Causal Effects of Air Pollution Mixtures on Overall Mortality in a Large, Prospective Cohort.

BACKGROUND: Several studies have confirmed associations between air pollution and overall mortality, but it is unclear to what extent these associations reflect causal relationships. Moreover, few studies to our knowledge have accounted for complex mixtures of air pollution. In this study, we evaluate the causal effects of a mixture of air pollutants on overall mortality in a large, prospective cohort of Dutch individuals. METHODS: We evaluated 86,882 individuals from the LIFEWORK study, assessing overall mortality between 2013 and 2017 through national registry linkage. We predicted outdoor concentration of five air pollutants (PM2.5, PM10, NO2, PM2.5 absorbance, and oxidative potential) with land-use regression. We used logistic regression and mixture modeling (weighted quantile sum and boosted regression tree models) to identify potential confounders, assess pollutants' relevance in the mixture-outcome association, and investigate interactions and nonlinearities. Based on these results, we built a multivariate generalized propensity score model to estimate the causal effects of pollutant mixtures. RESULTS: Regression model results were influenced by multicollinearity. Weighted quantile sum and boosted regression tree models indicated that all components contributed to a positive linear association with the outcome, with PM2.5 being the most relevant contributor. In the multivariate propensity score model, PM2.5 (OR=1.18, 95% CI: 1.08-1.29) and PM10 (OR=1.02, 95% CI: 0.91-1.14) were associated with increased odds of mortality per interquartile range increase. CONCLUSION: Using novel methods for causal inference and mixture modeling in a large prospective cohort, this study strengthened the causal interpretation of air pollution effects on overall mortality, emphasizing the primary role of PM2.5 within the pollutant mixture.

Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women.

STUDY QUESTION: Can additional genetic variants for circulating anti-Müllerian hormone (AMH) levels be identified through a genome-wide association study (GWAS) meta-analysis including a large sample of premenopausal women? SUMMARY ANSWER: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. WHAT IS KNOWN ALREADY: AMH is expressed by antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with disease outcomes. However, the physiological mechanisms underlying these AMH-disease associations are largely unknown. STUDY DESIGN, SIZE, DURATION: We performed a GWAS meta-analysis in which we combined summary statistics of a previous AMH GWAS with GWAS data from 3705 additional women from three different cohorts. PARTICIPANTS/MATERIALS, SETTING, METHODS: In total, we included data from 7049 premenopausal female participants of European ancestry. The median age of study participants ranged from 15.3 to 48 years across cohorts. Circulating AMH levels were measured in either serum or plasma samples using different ELISA assays. Study-specific analyses were adjusted for age at blood collection and population stratification, and summary statistics were meta-analysed using a standard error-weighted approach. Subsequently, we functionally annotated GWAS variants that reached genome-wide significance (P < 5 × 10-8). We also performed a gene-based GWAS, pathway analysis and linkage disequilibrium score regression and Mendelian randomization (MR) analyses. MAIN RESULTS AND THE ROLE OF CHANCE: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among single nucleotide polymorphisms for AMH levels and for age at menopause (rg = 0.82, FDR = 0.003). Exploratory two-sample MR analyses did not support causal effects of AMH on breast cancer or polycystic ovary syndrome risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. LARGE SCALE DATA: The full AMH GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION: Whilst this study doubled the sample size of the most recent GWAS, the statistical power is still relatively low. As a result, we may still lack power to identify more genetic variants for AMH and to determine causal effects of AMH on, for example, breast cancer. Also, follow-up studies are needed to investigate whether the signal for the AMH gene is caused by reduced AMH detection by certain assays instead of actual lower circulating AMH levels. WIDER IMPLICATIONS OF THE FINDINGS: Genes mapped to the MCM8, TEX41 and CDCA7 loci are involved in the cell cycle and processes such as DNA replication and apoptosis. The mechanism underlying their associations with AMH may affect the size of the ovarian follicle pool. Altogether, our results provide more insight into the biology of AMH and, accordingly, the biological processes involved in ovarian ageing. STUDY FUNDING/COMPETING INTEREST(S): Nurses' Health Study and Nurses' Health Study II were supported by research grants from the National Institutes of Health (CA172726, CA186107, CA50385, CA87969, CA49449, CA67262, CA178949). The UK Medical Research Council and Wellcome (217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the listed authors, who will serve as guarantors for the contents of this article. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). Funding for the collection of genotype and phenotype data used here was provided by the British Heart Foundation (SP/07/008/24066), Wellcome (WT092830M and WT08806) and UK Medical Research Council (G1001357). M.C.B., A.L.G.S. and D.A.L. work in a unit that is funded by the University of Bristol and UK Medical Research Council (MC_UU_00011/6). M.C.B.'s contribution to this work was funded by a UK Medical Research Council Skills Development Fellowship (MR/P014054/1) and D.A.L. is a National Institute of Health Research Senior Investigator (NF-0616-10102). A.L.G.S. was supported by the study of Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739). The Doetinchem Cohort Study was financially supported by the Ministry of Health, Welfare and Sports of the Netherlands. The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Ansh Labs performed the AMH measurements for the Doetinchem Cohort Study free of charge. Ansh Labs was not involved in the data analysis, interpretation or reporting, nor was it financially involved in any aspect of the study. R.M.G.V. was funded by the Honours Track of MSc Epidemiology, University Medical Center Utrecht with a grant from the Netherlands Organization for Scientific Research (NWO) (022.005.021). The Study of Women's Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR) and the NIH Office of Research on Women's Health (ORWH) (U01NR004061; U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495). The SWAN Genomic Analyses and SWAN Legacy have grant support from the NIA (U01AG017719). The Generations Study was funded by Breast Cancer Now and the Institute of Cancer Research (ICR). The ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the funders. The Sister Study was funded by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (Z01-ES044005 to D.P.S.); the AMH assays were supported by the Avon Foundation (02-2012-065 to H.B. Nichols and D.P.S.). The breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the 'Ministère de l'Économie, de la Science et de l'Innovation du Québec' through Genome Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Michailidou et al. (Nature, 2017). F.J.M.B. has received fees and grant support from Merck Serono and Ferring BV. D.A.L. has received financial support from several national and international government and charitable funders as well as from Medtronic Ltd and Roche Diagnostics for research that is unrelated to this study. N.S. is scientific consultant for Ansh Laboratories. The other authors declare no competing interests.

Long-Term Exposure to Source-Specific Fine Particles and Mortality─A Pooled Analysis of 14 European Cohorts within the ELAPSE Project.

We assessed mortality risks associated with source-specific fine particles (PM2.5) in a pooled European cohort of 323,782 participants. Cox proportional hazard models were applied to estimate mortality hazard ratios (HRs) for source-specific PM2.5 identified through a source apportionment analysis. Exposure to 2010 annual average concentrations of source-specific PM2.5 components was assessed at baseline residential addresses. The source apportionment resulted in the identification of five sources: traffic, residual oil combustion, soil, biomass and agriculture, and industry. In single-source analysis, all identified sources were significantly positively associated with increased natural mortality risks. In multisource analysis, associations with all sources attenuated but remained statistically significant with traffic, oil, and biomass and agriculture. The highest association per interquartile increase was observed for the traffic component (HR: 1.06; 95% CI: 1.04 and 1.08 per 2.86 µg/m3 increase) across five identified sources. On a 1 µg/m3 basis, the residual oil-related PM2.5 had the strongest association (HR: 1.13; 95% CI: 1.05 and 1.22), which was substantially higher than that for generic PM2.5 mass, suggesting that past estimates using the generic PM2.5 exposure response function have underestimated the potential clean air health benefits of reducing fossil-fuel combustion. Source-specific associations with cause-specific mortality were in general consistent with findings of natural mortality.

Sex Differences in Cognitive Functioning with Aging in the Netherlands.

INTRODUCTION: Dementia prevalence in older women is higher than that in men. The purpose of the present study was to investigate whether there is a female disadvantage in cognitive functioning at adult age and/or whether a female disadvantage develops with age. METHODS: Data of 5,135 women and 4,756 men from the Longitudinal Aging Study Amsterdam (LASA) and the Doetinchem Cohort Study (DCS) were used. In the LASA, memory, processing speed, fluid intelligence, and global cognitive function were measured every 3-4 years since 1992 in persons aged 55+ years for up to 23 years. In the DCS, memory, processing speed, cognitive flexibility, and global cognitive function were measured every 5 years since 1995 in persons aged 45+ years for up to 20 years. Sex differences in cognitive aging were analyzed using linear mixed models and also examined by the 10-year birth cohort or level of education. RESULTS: Women had a better memory, processing speed, flexibility, and, in the DCS only, global cognitive function than men (p's < 0.01). However, women showed up to 10% faster decline in these cognitive domains, except for flexibility, where women showed 9% slower decline. In the LASA, women scored poorer on fluid intelligence (p < 0.01), but their decline was 10% slower than that in men. Female advantage was larger in later born cohorts; adjustment for the educational level increased the female advantage. CONCLUSION: Women have better memory and processing speed than men at middle age. This female advantage becomes smaller with aging and has increased in more recent birth cohorts.

Impaired JAK-STAT pathway signaling in leukocytes of the frail elderly.

BACKGROUND: Elderly often show reduced immune functioning and can develop chronic low-grade inflammation. Why some elderly are more prone to become frail is unknown. We investigated whether frailty is associated with altered cytokine signaling through the JAK-STAT pathway in leukocytes of 34 individuals aged 65-74 years. In addition, we investigated how this relation is affected by chronic low-grade inflammation during the previous 20 years. Cytokine signaling was quantified by measuring intracellular STAT1, STAT3, and STAT5 phosphorylation in monocytes, B cells, CD4+ T cells and CD8+ T cells upon stimulation with IL-2, IL-6, IL-10, IFNα and IFNγ, using phospho-flow cytometry. Presence of chronic low-grade inflammation was investigated by evaluating 18 different plasma inflammatory markers that had been measured repeatedly in the same individuals over the previous 20 years. Frailty was assessed as a score on a frailty index. RESULTS: We found that lower cytokine-induced pSTAT responsiveness in the various cell subsets was seen with higher frailty scores in both men and women, indicative of dysfunctional pSTAT responses in frailer individuals. Associations differed between men and women, with frailer women showing lower pSTAT1 responses in monocytes and frailer men showing lower pSTAT5 responses in CD4+ and CD8+ T cells. Notably, lower IL-10-induced pSTAT3 responses in men were related to both higher frailty scores and higher CRP levels over the past 20 years. This might indicate poor resolution of low-grade inflammation due to defective regulatory pSTAT signaling in older men. CONCLUSIONS: Our results emphasize the importance of preserved JAK-STAT pathway signaling in healthy aging and reveal cellular pSTAT levels as a candidate biomarker of frailty.