Adherence to 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer: The Melbourne Collaborative Cohort Study.

BACKGROUND: We examined associations between adherence to adaptations of the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations and total, exposure-related and site-specific cancer risk. METHODS: A total of 20,001 participants ages 40 to 69 years at enrollment into the Melbourne Collaborative Cohort Study in 1990 to 1994, who had diet, body size, and lifestyle reassessed in 2003 to 2007 ("baseline"), were followed-up through June 2021. We constructed diet and standardized lifestyle scores based on core WCRF/AICR recommendations on diet, alcohol intake, body size and physical activity, and additional scores incorporating weight change, sedentary behavior, and smoking. Associations with cancer risk were estimated using Cox regression, adjusting for confounders. RESULTS: During follow-up (mean = 16 years), 4,710 incident cancers were diagnosed. For highest quintile ("most adherent") of the standardized lifestyle score, compared with lowest ("least adherent"), a HR of 0.82 [95% confidence interval (CI): 0.74-0.92] was observed for total cancer. This association was stronger with smoking included in the score (HR = 0.74; 95% CI: 0.67-0.81). A higher score was associated with lower breast and prostate cancer risk for the standardized score, and with lung, stomach, rectal, and pancreatic cancer risk when the score included smoking. Our analyses identified alcohol use, waist circumference and smoking as key drivers of associations with total cancer risk. CONCLUSIONS: Adherence to WCRF/AICR cancer prevention recommendations is associated with lower cancer risk. IMPACT: With <0.2% of our sample fully adherent to the recommendations, the study emphasizes the vast potential for preventing cancer through modulation of lifestyle habits.

Role of Polyunsaturated Fat in Modifying Cardiovascular Risk Associated With Family History of Cardiovascular Disease: Pooled De Novo Results From 15 Observational Studies.

BACKGROUND: It is unknown whether dietary intake of polyunsaturated fatty acids (PUFA) modifies the cardiovascular disease (CVD) risk associated with a family history of CVD. We assessed interactions between biomarkers of low PUFA intake and a family history in relation to long-term CVD risk in a large consortium. METHODS: Blood and tissue PUFA data from 40 885 CVD-free adults were assessed. PUFA levels ≤25th percentile were considered to reflect low intake of linoleic, alpha-linolenic, and eicosapentaenoic/docosahexaenoic acids (EPA/DHA). Family history was defined as having ≥1 first-degree relative who experienced a CVD event. Relative risks with 95% CI of CVD were estimated using Cox regression and meta-analyzed. Interactions were assessed by analyzing product terms and calculating relative excess risk due to interaction. RESULTS: After multivariable adjustments, a significant interaction between low EPA/DHA and family history was observed (product term pooled RR, 1.09 [95% CI, 1.02-1.16]; P=0.01). The pooled relative risk of CVD associated with the combined exposure to low EPA/DHA, and family history was 1.41 (95% CI, 1.30-1.54), whereas it was 1.25 (95% CI, 1.16-1.33) for family history alone and 1.06 (95% CI, 0.98-1.14) for EPA/DHA alone, compared with those with neither exposure. The relative excess risk due to interaction results indicated no interactions. CONCLUSIONS: A significant interaction between biomarkers of low EPA/DHA intake, but not the other PUFA, and a family history was observed. This novel finding might suggest a need to emphasize the benefit of consuming oily fish for individuals with a family history of CVD.

Estimating cancers attributable to physical inactivity in Australia.

OBJECTIVES: It was previously estimated that 1814 (1.6 % of incident cancers) were attributable to physical inactivity in Australia in 2010, when only three sites were considered. We estimated the burden of cancer due to physical inactivity in Australia for 13 sites. DESIGN: The population attributable fraction estimated site-specific cancer cases attributable to physical inactivity for 13 cancers. The potential impact fraction was used to estimate cancers that could have been prevented in 2015 if Australian adults had increased their physical activity by a modest amount in 2004-05. METHODS: We used 2004-05 national physical activity prevalence data, 2015 national cancer incidence data, and contemporary relative-risk estimates for physical inactivity and cancer. We assumed a 10-year latency period. RESULTS: An estimated 6361 of the cancers observed in 2015 were attributable to physical inactivity, representing 4.8 % of all cancers diagnosed. If Australian adults had increased their physical activity by one category in 2004-05, 2564 cases (1.9 % of all cancers) could have been prevented in 2015. CONCLUSIONS: More than three times as many cancers are attributable to physical inactivity than previously reported. Physical activity promotion should be a central component of cancer prevention programmes in Australia.

Modifiable lifestyle risk factors and survival after diagnosis with multiple myeloma.

BACKGROUND: While remaining incurable, median overall survival for MM now exceeds 5 years. Yet few studies have investigated how modifiable lifestyle factors influence survival. We investigate whether adiposity, diet, alcohol, or smoking are associated with MM-related fatality. RESEARCH DESIGN AND METHODS: We recruited 760 incident cases of MM via cancer registries in two Australian states during 2010-2016. Participants returned questionnaires on health and lifestyle. Follow-up ended in 2020. Flexible parametric survival models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for lifestyle exposures and risk of all-cause and MM-specific fatality. RESULTS: Higher pre-diagnosis Alternative Healthy Eating Index (AHEI) scores were associated with reduced MM-specific fatality (per 10-unit score, HR = 0.84, 95%CI = 0.70-0.99). Pre-diagnosis alcohol consumption was inversely associated with MM-specific fatality, compared with nondrinkers (0.1-20 g per day, HR = 0.59, 95%CI = 0.39-0.90; >20 g per day, HR = 0.67, 95%CI = 0.40-1.13). Tobacco smoking was associated with increased all-cause fatality compared with never smoking (former smokers: HR = 1.44, 95%CI = 1.10-1.88; current smokers: HR = 1.30, 95%CI = 0.80-2.10). There was no association between pre-enrollment body mass index (BMI) and MM-specific or all-cause fatality. CONCLUSIONS: Our findings support established recommendations for healthy diets and against smoking. Higher quality diet, as measured by the AHEI, may improve survival post diagnosis with MM.

Intake of polyphenols from cereal foods and colorectal cancer risk in the Melbourne Collaborative Cohort Study.

BACKGROUND: Cereal-derived polyphenols have demonstrated protective mechanisms in colorectal cancer (CRC) models; however, confirmation in human studies is lacking. Therefore, this study examined the association between cereal polyphenol intakes and CRC risk in the Melbourne Collaborative Cohort Study (MCCS), a prospective cohort study in Melbourne, Australia that recruited participants between 1990 and 1994 to investigate diet-disease relationships. METHODS: Using food frequency questionnaire diet data matched to polyphenol data, dietary intakes of alkylresorcinols, phenolic acids, lignans, and total polyphenols from cereals were estimated. Hazard ratios (HRs) and 95% confidence intervals for CRC risk were estimated for quintiles of intake with the lowest quintile as the comparison category, using multivariable adjusted Cox proportional hazards models with age as the time axis adjusted for sex, socio-economic status, alcohol consumption, fibre intake, country of birth, total energy intake, physical activity and smoking status. RESULTS: From 35,245 eligible adults, mean (SD) age 54.7 (8.6) years, mostly female (61%) and Australian-born (69%), there were 1394 incident cases of CRC (946 colon cancers and 448 rectal cancers). Results for total cereal polyphenol intake showed reduced HRs in Q2 (HR: 0.80; 95% CI, 0.68-0.95) and Q4 (HR: 0.75; 95% CI, 0.62-0.90), and similar for phenolic acids. Alkylresorcinol intake showed reduced HR in Q3 (HR: 0.80; 95% CI, 0.67-0.95) and Q4 (HR: 0.79; 95% CI, 0.66-0.95). CONCLUSIONS: Overall, the present study showed little evidence of association between intakes of cereal polyphenols and CRC risk. Future investigations may be useful to understand associations between cereal-derived polyphenols and additional cancers in different populations.

Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools.

BACKGROUND: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test. METHODS: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided. RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model. CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.

Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis.

BACKGROUND: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis. METHODS: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only. FINDINGS: There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10-1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61-0.66), compared with 0.62 (95% CI: 0.59-0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: -0.003 to 0.035). INTERPRETATION: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information. FUNDING: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute (U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden (AMP19-962), and Swedish Department of Health Ministry.

Estimated dietary intake of polyphenols from cereal foods and associated lifestyle and demographic factors in the Melbourne Collaborative Cohort Study.

Cereal foods are consumed globally and are important sources of polyphenols with potential health benefits, yet dietary intakes are unclear. We aimed to calculate the dietary intakes of polyphenols from cereal foods in the Melbourne Collaborative Cohort Study (MCCS), and describe intakes by demographic and lifestyle factors. We estimated intakes of alkylresorcinols, lignans and phenolic acids in n = 39,892 eligible MCCS participants, using baseline dietary data (1990-1994) from a 121-item FFQ containing 17 cereal foods, matched to a polyphenol database developed from published literature and Phenol-Explorer Database. Intakes were estimated within groups according to lifestyle and demographic factors. The median (25th-75th percentile) intake of total polyphenols from cereal foods was 86.9 mg/day (51.4-155.8). The most consumed compounds were phenolic acids, with a median intake of 67.1 mg (39.5-118.8), followed by alkylresorcinols of 19.7 mg (10.8-34.6). Lignans made the smallest contribution of 0.50 mg (0.13-0.87). Higher polyphenol intakes were associated with higher relative socio-economic advantage and prudent lifestyles, including lower body mass index (BMI), non-smoking and higher physical activity scores. The findings based on polyphenol data specifically matched to the FFQ provide new information on intakes of cereal polyphenols, and how they might vary according to lifestyle and demographic factors.

Alcohol and tobacco use and risk of multiple myeloma: A case-control study.

Multiple myeloma (MM) is the second most common hematological cancer and causes significant mortality and morbidity. Knowledge regarding modifiable risk factors for MM remains limited. This analysis of an Australian population-based case-control family study investigates whether smoking or alcohol consumption is associated with risk of MM and related diseases. Incident cases (n = 789) of MM were recruited via cancer registries in Victoria and New South Wales. Controls (n = 1,113) were either family members of cases (n = 696) or controls recruited for a similarly designed study of renal cancers (n = 417). Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional multivariable logistic regression. Heavy intake (>20 g ethanol/day) of alcohol had a lower risk of MM compared with nondrinkers (OR = 0.68, 95% CI: 0.50-0.93), and there was an inverse dose-response relationship for average daily alcohol intake (OR per 10 g ethanol per day = 0.92, 95% CI: 0.86-0.99); there was no evidence of an interaction with sex. There was no evidence of an association with MM risk for smoking-related exposures (p > 0.18). The associations between smoking and alcohol with MM are similar to those with non-Hodgkin lymphoma. Further research into potential underlying mechanisms is warranted.

Television viewing time and all-cause mortality: interactions with BMI, physical activity, smoking, and dietary factors.

BACKGROUND: Higher levels of time spent sitting (sedentary behavior) contribute to adverse health outcomes, including earlier death. This effect may be modified by other lifestyle factors. We examined the association of television viewing (TV), a common leisure-time sedentary behavior, with all-cause mortality, and whether this is modified by body mass index (BMI), physical activity, smoking, alcohol intake, soft drink consumption, or diet-associated inflammation. METHODS: Using data from participants in the Melbourne Collaborative Cohort Study, flexible parametric survival models assessed the time-dependent association of self-reported TV time (three categories: < 2 h/day, 2-3 h/day, > 3 h/day) with all-cause mortality. Interaction terms were fitted to test whether there was effect modification of TV time by the other risk factors. RESULTS: From 19,570 participants, 4,417 deaths were reported over a median follow up of 14.5 years. More TV time was associated with earlier mortality; however, this relationship diminished with increasing age. The hazard ratio (HR) and 95% confidence interval (95% CI) for > 3 h/day compared with < 2 h/day of TV time was 1.34 (1.16, 1.55) at 70 years, 1.14 (1.04, 1.23) at 80 years, and 0.95 (0.84, 1.06) at 90 years. The TV time/mortality relationship was more evident in participants who were physically inactive (compared with active; p for interaction < 0.01) or had a higher dietary inflammatory index score (compared with a lower score; p for interaction = 0.03). No interactions were detected between TV time and BMI, smoking, alcohol intake, nor soft-drink consumption (all p for interaction > 0.16). CONCLUSIONS: The relationship between TV time and all-cause mortality may change with age. It may also be more pronounced in those who are otherwise inactive or who have a pro-inflammatory diet.

Alcohol intake trajectories during the life course and risk of alcohol-related cancer: A prospective cohort study.

We examined associations between sex-specific alcohol intake trajectories and alcohol-related cancer risk using data from 22 756 women and 15 701 men aged 40 to 69 years at baseline in the Melbourne Collaborative Cohort Study. Alcohol intake for 10-year periods from age 20 until the decade encompassing recruitment, calculated using recalled beverage-specific frequency and quantity, was used to estimate group-based sex-specific intake trajectories. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for primary invasive alcohol-related cancer (upper aerodigestive tract, breast, liver and colorectum). Three distinct alcohol intake trajectories for women (lifetime abstention, stable light, increasing moderate) and six for men (lifetime abstention, stable light, stable moderate, increasing heavy, early decreasing heavy, late decreasing heavy) were identified. 2303 incident alcohol-related cancers were diagnosed during 485 525 person-years in women and 789 during 303 218 person-years in men. For men, compared with lifetime abstention, heavy intake (mean ≥ 60 g/day) at age 20 to 39 followed by either an early (from age 40 to 49) (early decreasing heavy; HR = 1.75, 95% CI: 1.25-2.44) or late decrease (from age 60 to 69) (late decreasing heavy; HR = 1.94, 95% CI: 1.28-2.93), and moderate intake (mean <60 g/day) at age 20 to 39 increasing to heavy intake in middle-age (increasing heavy; HR = 1.45, 95% CI: 1.06-1.97) were associated with increased risk of alcohol-related cancer. For women, compared with lifetime abstention, increasing intake from age 20 (increasing moderate) was associated with increased alcohol-related cancer risk (HR = 1.25, 95% CI: 1.06-1.48). Similar associations were observed for colorectal (men) and breast cancer. Heavy drinking during early adulthood might increase cancer risk later in life.

Trans Fatty Acid Biomarkers and Incident Type 2 Diabetes: Pooled Analysis of 12 Prospective Cohort Studies in the Fatty Acids and Outcomes Research Consortium (FORCE).

OBJECTIVE: Trans fatty acids (TFAs) have harmful biologic effects that could increase the risk of type 2 diabetes (T2D), but evidence remains uncertain. We aimed to investigate the prospective associations of TFA biomarkers and T2D by conducting an individual participant-level pooled analysis. RESEARCH DESIGN AND METHODS: We included data from an international consortium of 12 prospective cohorts and nested case-control studies from six nations. TFA biomarkers were measured in blood collected between 1990 and 2008 from 25,126 participants aged ≥18 years without prevalent diabetes. Each cohort conducted de novo harmonized analyses using a prespecified protocol, and findings were pooled using inverse-variance weighted meta-analysis. Heterogeneity was explored by prespecified between-study and within-study characteristics. RESULTS: During a mean follow-up of 13.5 years, 2,843 cases of incident T2D were identified. In multivariable-adjusted pooled analyses, no significant associations with T2D were identified for trans/trans-18:2, relative risk (RR) 1.09 (95% CI 0.94-1.25); cis/trans-18:2, 0.89 (0.73-1.07); and trans/cis-18:2, 0.87 (0.73-1.03). Trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated with T2D (RR 0.81 [95% CI 0.67-0.99], 0.86 [0.75-0.99], and 0.84 [0.74-0.96], respectively). Findings were not significantly different according to prespecified sources of potential heterogeneity (each P ≥ 0.1). CONCLUSIONS: Circulating individual trans-18:2 TFA biomarkers were not associated with risk of T2D, while trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated. Findings may reflect the influence of mixed TFA sources (industrial vs. natural ruminant), a general decline in TFA exposure due to policy changes during this period, or the relatively limited range of TFA levels.

Dietary intake of animal-based products and likelihood of follicular lymphoma and survival: A population-based family case-control study.

Background: The association between dietary intake of foods of animal origin and follicular lymphoma (FL) risk and survival is uncertain. In this study, we examined the relationship between dietary intake of dairy foods and fats, meat, fish and seafoods, and the likelihood of FL and survival. Methods: We conducted a population-based family case-control study in Australia between 2011 and 2016 and included 710 cases, 303 siblings and 186 spouse/partner controls. We assessed dietary intake of animal products prior to diagnosis (the year before last) using a structured food frequency questionnaire and followed-up cases over a median of 6.9 years using record linkage to national death data. We examined associations with the likelihood of FL using logistic regression and used Cox regression to assess association with all-cause and FL-specific mortality among cases. Results: We observed an increased likelihood of FL with increasing daily quantity of oily fish consumption in the year before last (highest category OR = 1.96, CI = 1.02-3.77; p-trend 0.06) among cases and sibling controls, but no associations with spouse/partner controls. We found no association between the likelihood of FL and the consumption of other types of fish or seafood, meats or dairy foods and fats. In FL cases, we found no association between meat or oily fish intake and all-cause or FL-specific mortality. Conclusion: Our study showed suggestive evidence of a positive association between oily fish intake and the likelihood of FL, but findings varied by control type. Further investigation of the potential role of environmental contaminants in oily fish on FL etiology is warranted.

Smoking Methylation Marks for Prediction of Urothelial Cancer Risk.

BACKGROUND: Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction. METHODS: Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case-control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC). RESULTS: The meta-analysis identified associations (P < 4.7 × 10-5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00-1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91-1.30). CONCLUSIONS: Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets. IMPACT: DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.

Inflammation-Related Marker Profiling of Dietary Patterns and All-cause Mortality in the Melbourne Collaborative Cohort Study.

BACKGROUND: Nutritional epidemiology research using self-reported dietary intake is prone to measurement error. Objective methods are being explored to overcome this limitation. OBJECTIVES: We aimed to examine 1) the association between plasma markers related to inflammation and derive marker scores for dietary patterns [Mediterranean dietary score (MDS), energy-adjusted Dietary Inflammatory Index (E-DIITM), Alternative Healthy Eating Index 2010 (AHEI)] and 2) the associations of these marker scores with mortality. METHODS: Weighted marker scores were derived from the cross-sectional association between 30 plasma markers and each dietary score (assessed using food-frequency questionnaires) using linear regression for 770 participants in the Melbourne Collaborative Cohort Study (aged 50-82 y). Prospective associations between marker scores and mortality (n = 249 deaths) were assessed using Cox regression (median follow-up: 14.4 y). RESULTS: The MDS, E-DII, and AHEI were associated (P < 0.05) with 9, 14, and 11 plasma markers, respectively. Healthier diets (higher MDS and AHEI, and lower anti-inflammatory, E-DII) were associated with lower concentrations of kynurenines, neopterin, IFN-γ, cytokines, and C-reactive protein. Five of 6 markers common to the 3 dietary scores were components of the kynurenine pathway. The 3 dietary-based marker scores were highly correlated (Spearman ρ: -0.74, -0.82, and 0.93). Inverse associations (for 1-SD increment) were observed with all-cause mortality for the MDS marker score (HR: 0.84; 95% CI: 0.72-0.98) and the AHEI marker score (HR: 0.76; 95% CI: 0.66-0.89), whereas a positive association was observed with the E-DII marker score (HR: 1.18; 95% CI: 1.01-1.39). The same magnitude of effect was not observed for the respective dietary patterns. CONCLUSIONS: Markers involved in inflammation-related processes are associated with dietary quality, including a substantial overlap between markers associated with the MDS, the E-DII, and the AHEI, especially kynurenines. Unfavorable marker scores, reflecting poorer-quality diets, were associated with increased mortality.

Blood n-3 fatty acid levels and total and cause-specific mortality from 17 prospective studies.

The health effects of omega-3 fatty acids have been controversial. Here we report the results of a de novo pooled analysis conducted with data from 17 prospective cohort studies examining the associations between blood omega-3 fatty acid levels and risk for all-cause mortality. Over a median of 16 years of follow-up, 15,720 deaths occurred among 42,466 individuals. We found that, after multivariable adjustment for relevant risk factors, risk for death from all causes was significantly lower (by 15-18%, at least p < 0.003) in the highest vs the lowest quintile for circulating long chain (20-22 carbon) omega-3 fatty acids (eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids). Similar relationships were seen for death from cardiovascular disease, cancer and other causes. No associations were seen with the 18-carbon omega-3, alpha-linolenic acid. These findings suggest that higher circulating levels of marine n-3 PUFA are associated with a lower risk of premature death.

n-3 Fatty Acid Biomarkers and Incident Type 2 Diabetes: An Individual Participant-Level Pooling Project of 20 Prospective Cohort Studies.

OBJECTIVE: Prospective associations between n-3 fatty acid biomarkers and type 2 diabetes (T2D) risk are not consistent in individual studies. We aimed to summarize the prospective associations of biomarkers of α-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with T2D risk through an individual participant-level pooled analysis. RESEARCH DESIGN AND METHODS: For our analysis we incorporated data from a global consortium of 20 prospective studies from 14 countries. We included 65,147 participants who had blood measurements of ALA, EPA, DPA, or DHA and were free of diabetes at baseline. De novo harmonized analyses were performed in each cohort following a prespecified protocol, and cohort-specific associations were pooled using inverse variance-weighted meta-analysis. RESULTS: A total of 16,693 incident T2D cases were identified during follow-up (median follow-up ranging from 2.5 to 21.2 years). In pooled multivariable analysis, per interquintile range (difference between the 90th and 10th percentiles for each fatty acid), EPA, DPA, DHA, and their sum were associated with lower T2D incidence, with hazard ratios (HRs) and 95% CIs of 0.92 (0.87, 0.96), 0.79 (0.73, 0.85), 0.82 (0.76, 0.89), and 0.81 (0.75, 0.88), respectively (all P < 0.001). ALA was not associated with T2D (HR 0.97 [95% CI 0.92, 1.02]) per interquintile range. Associations were robust across prespecified subgroups as well as in sensitivity analyses. CONCLUSIONS: Higher circulating biomarkers of seafood-derived n-3 fatty acids, including EPA, DPA, DHA, and their sum, were associated with lower risk of T2D in a global consortium of prospective studies. The biomarker of plant-derived ALA was not significantly associated with T2D risk.

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study.

Background: We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods: We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results: We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions: The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.