Melbourne Collaborative Cohort Study Research Articles

Prediagnosis alcohol intake and metachronous cancer risk in cancer survivors: A prospective cohort study.

Alcohol consumption is a known cause of cancer, but its role in the etiology of second primary (metachronous) cancer is uncertain. Associations between alcohol intake up until study enrollment (prediagnosis) and risk of metachronous cancer were estimated using 9435 participants in the Melbourne Collaborative Cohort Study who were diagnosed with their first invasive cancer after enrollment (1990-1994). Follow-up was from date of first invasive cancer until diagnosis of metachronous cancer, death or censor date (February 2018), whichever came first. Alcohol intake for 10-year periods from age 20 until decade encompassing baseline using recalled beverage-specific frequency and quantity was used to calculate baseline and lifetime intakes, and group-based intake trajectories. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs), adjusted for potential confounders. After a mean follow-up of 7 years, 1512 metachronous cancers were identified. A 10 g/d increment in prediagnosis lifetime alcohol intake (HR = 1.03, 95% CI = 1.00-1.06; Pvalue = .02) and an intake of ≥60 g/d (HR = 1.32, 95% CI = 1.01-1.73) were associated with increased metachronous cancer risk. We observed positive associations (per 10 g/d increment) for metachronous colorectal (HR = 1.07, 95% CI = 1.00-1.14), upper aero-digestive tract (UADT) (HR = 1.16, 95% CI = 1.00-1.34) and kidney cancer (HR = 1.24, 95% CI = 1.10-1.39). Although these findings were partly explained by effects of smoking, the association for kidney cancer remained unchanged when current smokers or obese individuals were excluded. Alcohol intake trajectories over the life course confirmed associations with metachronous cancer risk. Prediagnosis long-term alcohol intake, and particularly heavy drinking, may increase the risk of metachronous cancer, particularly of the colorectum, UADT and kidney.

Diet scores and prediction of general and abdominal obesity in the Melbourne collaborative cohort study.

To ascertain which of the Alternative Healthy Eating Index (AHEI) 2010, Dietary Inflammatory Index (DII®) and Mediterranean Diet Score (MDS) best predicted BMI and waist-to-hip circumference ratio (WHR). Body size was measured at baseline (1990-1994) and in 2003-2007. Diet was assessed at baseline using a FFQ, along with age, sex, socio-economic status, smoking, alcohol drinking, physical activity and country of birth. Regression coefficients and 95 % CI for the association of baseline dietary scores with follow-up BMI and WHR were generated using multivariable linear regression, adjusting for baseline body size, confounders and energy intake. Population-based cohort in Melbourne, Australia. Included were data from 11 030 men and 16 774 women aged 40-69 years at baseline. Median (IQR) follow-up was 11·6 (10·7-12·8) years. BMI and WHR at follow-up were associated with baseline DII® (Q5 v. Q1 (BMI 0·41, 95 % CI 0·21, 0·61) and WHR 0·009, 95 % CI 0·006, 0·013)) and AHEI (Q5 v. Q1 (BMI -0·51, 95 % CI -0·68, -0·35) and WHR -0·011, 95 % CI -0·013, -0·008)). WHR, but not BMI, at follow-up was associated with baseline MDS (Group 3 most Mediterranean v. G1 (BMI -0·05, 95 % CI -0·23, 0·13) and WHR -0·004, 95 % CI -0·007, -0·001)). Based on Akaike's Information Criterion and Bayesian Information Criterion statistics, AHEI was a stronger predictor of body size than the other diet scores. Poor quality or pro-inflammatory diets predicted overall and central obesity. The AHEI may provide the best way to assess the obesogenic potential of diet.

Predicting Australian Adults at High Risk of Cardiovascular Disease Mortality Using Standard Risk Factors and Machine Learning.

Effective cardiovascular disease (CVD) prevention relies on timely identification and intervention for individuals at risk. Conventional formula-based techniques have been demonstrated to over- or under-predict the risk of CVD in the Australian population. This study assessed the ability of machine learning models to predict CVD mortality risk in the Australian population and compare performance with the well-established Framingham model. Data is drawn from three Australian cohort studies: the North West Adelaide Health Study (NWAHS), the Australian Diabetes, Obesity, and Lifestyle study, and the Melbourne Collaborative Cohort Study (MCCS). Four machine learning models for predicting 15-year CVD mortality risk were developed and compared to the 2008 Framingham model. Machine learning models performed significantly better compared to the Framingham model when applied to the three Australian cohorts. Machine learning based models improved prediction by 2.7% to 5.2% across three Australian cohorts. In an aggregated cohort, machine learning models improved prediction by up to 5.1% (area-under-curve (AUC) 0.852, 95% CI 0.837–0.867). Net reclassification improvement (NRI) was up to 26% with machine learning models. Machine learning based models also showed improved performance when stratified by sex and diabetes status. Results suggest a potential for improving CVD risk prediction in the Australian population using machine learning models.

Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models.

BackgroundThe Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm and the International Breast Cancer Intervention Study breast cancer risk models are used to provide advice on screening intervals and chemoprevention. We evaluated the performance of these models, which now incorporate polygenic risk scores (PRSs), using a prospective cohort study.MethodsWe used a case-cohort design, involving women in the Melbourne Collaborative Cohort Study aged 50-75 years when surveyed in 2003-2007, of whom 408 had a first primary breast cancer diagnosed within 10 years (cases), and 2783 were from the subcohort. Ten-year risks were calculated based on lifestyle factors, family history data, and a 313-variant PRS. Discrimination was assessed using a C-statistic compared with 0.50 and calibration using the ratio of expected to observed number of cases (E/O).ResultsWhen the PRS was added to models with lifestyle factors and family history, the C-statistic (95% confidence interval [CI]) increased from 0.57 (0.54 to 0.60) to 0.62 (0.60 to 0.65) using IBIS and from 0.56 (0.53 to 0.59) to 0.62 (0.59 to 0.64) using BOADICEA. IBIS underpredicted risk (E/O = 0.62, 95% CI = 0.48 to 0.80) for women in the lowest risk category (<1.7%) and overpredicted risk (E/O = 1.40, 95% CI = 1.18 to 1.67) in the highest risk category (≥5%), using the Hosmer-Lemeshow test for calibration in quantiles of risk and a 2-sided P value less than .001. BOADICEA underpredicted risk (E/O = 0.82, 95% CI = 0.67 to 0.99) in the second highest risk category (3.4%-5%); the Hosmer-Lemeshow test and a 2-sided P value was equal to .02.ConclusionsAlthough the inclusion of a 313 genetic variant PRS doubles discriminatory accuracy (relative to reference 0.50), models with and without this PRS have relatively modest discrimination and might require recalibration before their clinical and wider use are promoted.

Lifetime alcohol intake, drinking patterns over time and risk of stomach cancer: A pooled analysis of data from two prospective cohort studies.

Alcohol consumption is causally linked to several cancers but the evidence for stomach cancer is inconclusive. In our study, the association between long‐term alcohol intake and risk of stomach cancer and its subtypes was evaluated. We performed a pooled analysis of data collected at baseline from 491 714 participants in the European Prospective Investigation into Cancer and Nutrition and the Melbourne Collaborative Cohort Study. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for incident stomach cancer in relation to lifetime alcohol intake and group‐based life course intake trajectories, adjusted for potential confounders including Helicobacter pylori infection. In all, 1225 incident stomach cancers (78% noncardia) were diagnosed over 7 094 637 person‐years; 984 in 382 957 study participants with lifetime alcohol intake data (5 455 507 person‐years). Although lifetime alcohol intake was not associated with overall stomach cancer risk, we observed a weak positive association with noncardia cancer (HR = 1.03, 95% CI: 1.00‐1.06 per 10 g/d increment), with a HR of 1.50 (95% CI: 1.08‐2.09) for ≥60 g/d compared to 0.1 to 4.9 g/d. A weak inverse association with cardia cancer (HR = 0.93, 95% CI: 0.87‐1.00) was also observed. HRs of 1.48 (95% CI: 1.10‐1.99) for noncardia and 0.51 (95% CI: 0.26‐1.03) for cardia cancer were observed for a life course trajectory characterized by heavy decreasing intake compared to light stable intake (P homogeneity = .02). These associations did not differ appreciably by smoking or H pylori infection status. Limiting alcohol use during lifetime, particularly avoiding heavy use during early adulthood, might help prevent noncardia stomach cancer. Heterogeneous associations observed for cardia and noncardia cancers may indicate etiologic differences.

Latent Class Trajectory Modeling of Adult Body Mass Index and Risk of Obesity-Related Cancer: Findings from the Melbourne Collaborative Cohort Study.

Obesity increases the risk of 13 cancer types. Given the long process of carcinogenesis, it is important to determine the impact of patterns of body mass over time. Using data from 30,377 participants in the Melbourne Collaborative Cohort Study, we identified body mass index (BMI) trajectories across adulthood and examined their association with the risk of obesity-related cancer. Participants completed interviews and questionnaires at baseline (1990-1994, age 40-69 years), follow-up 1 (1995-1998), and follow-up 2 (2003-2005). Body mass was recalled for age 18 to 21 years, measured at baseline, self-reported at follow-up 1, and measured at follow-up 2. Height was measured at baseline. Cancer diagnoses were ascertained from the Victorian Cancer Registry and the Australian Cancer Database. A latent class trajectory model was used to identify BMI trajectories that were not defined a priori. Cox regression was used to estimate HRs and 95% confidence intervals (CI) of obesity-related cancer risks by BMI trajectory. Six distinct BMI trajectories were identified. Compared with people who maintained lower normal BMI, higher risks of developing obesity-related cancer were observed for participants who transitioned from normal to overweight (HR, 1.29; 95% CI, 1.13-1.47), normal to class I obesity (HR, 1.50; 95% CI, 1.28-1.75), or from overweight to class II obesity (HR, 1.66; 95% CI, 1.32-2.08). Our findings suggest that maintaining a healthy BMI across the adult lifespan is important for cancer prevention. Categorization of BMI by trajectory allowed us to identify specific risk groups to target with public health interventions.

DNA Methylation in Peripheral Blood and Risk of Gastric Cancer: A Prospective Nested Case-control Study.

DNA methylation in peripheral blood is a potential biomarker of gastric cancer risk which could be used for early detection. We conducted a prospective case-control study nested within the Melbourne Collaborative Cohort Study. Genomic DNA was prepared from blood samples collected a median of 12 years before diagnosis for cases (N = 168). Controls (N = 163) were matched to cases on sex, year of birth, country of birth, and blood sample type using incidence density sampling. Genome-wide DNA methylation was measured using the Infinium HumanMethylation450K Beadchip. Global measures of DNA methylation were defined as the median methylation M value, calculated for each of 13 CpG subsets representing genomic function, mean methylation and location, and reliability of measurement. Conditional logistic regression was conducted to assess associations between these global measures of methylation and gastric cancer risk, adjusting for Helicobacter pylori and other potential confounders. We tested nonlinear associations using quintiles of the global measure distribution. A genome-wide association study of DNA methylation and gastric cancer risk was also conducted (N = 484,989 CpGs) using conditional logistic regression, adjusting for potential confounders. Differentially methylated regions (DMR) were investigated using the R package DMRcate We found no evidence of associations with gastric cancer risk for individual CpGs or DMRs (P > 7.6 × 10-6). No evidence of association was observed with global measures of methylation (OR 1.07 per SD of overall median methylation; 95% confidence interval, 0.80-1.44; P = 0.65). We found no evidence that blood DNA methylation is prospectively associated with gastric cancer risk.Prevention Relevance: We studied DNA methylation in blood to try and predict who was at risk of gastric cancer before symptoms developed, by which stage survival is poor. We did not find any such markers, but the importance of early diagnosis in gastric cancer remains, and the search for markers continues.

Diet and risk of gastro-oesophageal reflux disease in the Melbourne Collaborative Cohort Study.

To examine associations between diet and risk of developing gastro-oesophageal reflux disease (GERD). Prospective cohort with a median follow-up of 15·8 years. Baseline diet was measured using a FFQ. GERD was defined as self-reported current or history of daily heartburn or acid regurgitation beginning at least 2 years after baseline. Sex-specific logistic regressions were performed to estimate OR for GERD associated with diet quality scores and intakes of nutrients, food groups and individual foods and beverages. The effect of substituting saturated fat for monounsaturated or polyunsaturated fat on GERD risk was examined. Melbourne, Australia. A cohort of 20 926 participants (62 % women) aged 40-59 years at recruitment between 1990 and 1994. For men, total fat intake was associated with increased risk of GERD (OR 1·05 per 5 g/d; 95 % CI 1·01, 1·09; P = 0·016), whereas total carbohydrate (OR 0·89 per 30 g/d; 95 % CI 0·82, 0·98; P = 0·010) and starch intakes (OR 0·84 per 30 g/d; 95 % CI 0·75, 0·94; P = 0·005) were associated with reduced risk. Nutrients were not associated with risk for women. For both sexes, substituting saturated fat for polyunsaturated or monounsaturated fat did not change risk. For both sexes, fish, chicken, cruciferous vegetables and carbonated beverages were associated with increased risk, whereas total fruit and citrus were associated with reduced risk. No association was observed with diet quality scores. Diet is a possible risk factor for GERD, but food considered as triggers of GERD symptoms might not necessarily contribute to disease development. Potential differential associations for men and women warrant further investigation.

Association of variably methylated tumour DNA regions with overall survival for invasive lobular breast cancer

BackgroundTumour DNA methylation profiling has shown potential to refine disease subtyping and improve the diagnosis and prognosis prediction of breast cancer. However, limited data exist regarding invasive lobular breast cancer (ILBC). Here, we investigated the genome-wide variability of DNA methylation levels across ILBC tumours and assessed the association between methylation levels at the variably methylated regions and overall survival in women with ILBC.MethodsTumour-enriched DNA was prepared by macrodissecting formalin-fixed paraffin embedded (FFPE) tumour tissue from 130 ILBCs diagnosed in the participants of the Melbourne Collaborative Cohort Study (MCCS). Genome-wide tumour DNA methylation was measured using the HumanMethylation 450K (HM450K) BeadChip array. Variably methylated regions (VMRs) were identified using the DMRcate package in R. Cox proportional hazards regression models were used to assess the association between methylation levels at the ten most significant VMRs and overall survival. Gene set enrichment analyses were undertaken using the web-based tool Metaspace. Replication of the VMR and survival analysis findings was examined using data retrieved from The Cancer Genome Atlas (TCGA) for 168 ILBC cases. We also examined the correlation between methylation and gene expression for the ten VMRs of interest using TCGA data.ResultsWe identified 2771 VMRs (P < 10−8) in ILBC tumours. The ten most variably methylated clusters were predominantly located in the promoter region of the genes: ISM1, APC, TMEM101, ASCL2, NKX6, HIST3H2A/HIST3H2BB, HCG4P3, HES5, CELF2 and EFCAB4B. Higher methylation level at several of these VMRs showed an association with reduced overall survival in the MCCS. In TCGA, all associations were in the same direction, however stronger than in the MCCS. The pooled analysis of the MCCS and TCGA data showed that methylation at four of the ten genes was associated with reduced overall survival, independently of age and tumour stage; APC: Hazard Ratio (95% Confidence interval) per one-unit M-value increase: 1.18 (1.02–1.36), TMEM101: 1.23 (1.02–1.48), HCG4P3: 1.37 (1.05–1.79) and CELF2: 1.21 (1.02–1.43). A negative correlation was observed between methylation and gene expression for CELF2 (R = − 0.25, P = 0.001), but not for TMEM101 and APC.ConclusionsOur study identified regions showing greatest variability across the ILBC tumour genome and found methylation at several genes to potentially serve as a biomarker of survival for women with ILBC.

Obesity defined by body mass index and waist circumference and risk of total knee arthroplasty for osteoarthritis: A prospective cohort study.

To examine the risk of total knee arthroplasty (TKA) due to osteoarthritis associated with obesity defined by body mass index (BMI) or waist circumference (WC) and whether there is discordance between these measures in assessing this risk. 36,784 participants from the Melbourne Collaborative Cohort Study with BMI and WC measured at 1990-1994 were included. Obesity was defined by BMI (≥30 kg/m2) or WC (men ≥102cm, women ≥88cm). The incidence of TKA between January 2001 and December 2018 was determined by linking participant records to the National Joint Replacement Registry. Over 15.4±4.8 years, 2,683 participants underwent TKA. There were 20.4% participants with BMI-defined obesity, 20.8% with WC-defined obesity, and 73.6% without obesity defined by either BMI or WC. Obesity was classified as non-obese (misclassified obesity) in 11.7% of participants if BMI or WC alone was used to define obesity. BMI-defined obesity (HR 2.69, 95%CI 2.48-2.92), WC-defined obesity (HR 2.28, 95%CI 2.10-2.48), and obesity defined by either BMI or WC (HR 2.53, 95%CI 2.33-2.74) were associated with an increased risk of TKA. Compared with those without obesity, participants with misclassified obesity had an increased risk of TKA (HR 2.06, 95%CI 1.85-2.30). 22.7% of TKA in the community can be attributable to BMI-defined obesity, and a further 3.3% of TKA can be identified if WC was also used to define obesity. Both BMI and WC should be used to identify obese individuals who are at risk of TKA for osteoarthritis and should be targeted for prevention and treatment.

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

BackgroundWe 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.MethodsWe 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.ResultsWe 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).ConclusionsThe 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.

Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood.

Prenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood. Eight prospective case-control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (n = 406 cases), colorectal (n = 814), gastric (n = 166), kidney (n = 139), lung (n = 327), prostate (n = 847) and urothelial (n = 404) cancer and B-cell lymphoma (n = 426). We used conditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28 and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting) and methylation scores for personal smoking. All methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential negative associations were observed with risk of lung cancer and B-cell lymphoma. No associations were observed for other cancers. We found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer. Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.

Stochastic Epigenetic Mutations Are Associated with Risk of Breast Cancer, Lung Cancer, and Mature B-cell Neoplasms.

Age-related epigenetic dysregulations are associated with several diseases, including cancer. The number of stochastic epigenetic mutations (SEM) has been suggested as a biomarker of life-course accumulation of exposure-related DNA damage; however, the predictive role of SEMs in cancer has seldom been investigated. A SEM, at a given CpG site, was defined as an extreme outlier of DNA methylation value distribution across individuals. We investigated the association of the total number of SEMs with the risk of eight cancers in 4,497 case-control pairs nested in three prospective cohorts. Furthermore, we investigated whether SEMs were randomly distributed across the genome or enriched in functional genomic regions. In the three-study meta-analysis, the estimated ORs per one-unit increase in log(SEM) from logistic regression models adjusted for age and cancer risk factors were 1.25; 95% confidence interval (CI), 1.11-1.41 for breast cancer, and 1.23; 95% CI, 1.07-1.42 for lung cancer. In the Melbourne Collaborative Cohort Study, the OR for mature B-cell neoplasm was 1.46; 95% CI, 1.25-1.71. Enrichment analyses indicated that SEMs frequently occur in silenced genomic regions and in transcription factor binding sites regulated by EZH2 and SUZ12 (P < 0.0001 and P = 0.0005, respectively): two components of the polycomb repressive complex 2 (PCR2). Finally, we showed that PCR2-specific SEMs are generally more stable over time compared with SEMs occurring in the whole genome. The number of SEMs is associated with a higher risk of different cancers in prediagnostic blood samples. We identified a candidate biomarker for cancer early detection, and we described a carcinogenesis mechanism involving PCR2 complex proteins worthy of further investigations.

Domain-specific Physical Activity, Pain Interference, And Muscle Pain After Activity

PURPOSE: The context in which physical activity is performed may affect self-reported indicators of pain. Using the Melbourne Collaborative Cohort Study, we examined associations between occupation, household, transport, and leisure physical activity with pain interference and muscle pain after activity. METHODS: The analysis included 9,577 working and 12,281 non-working participants. Physical activity was assessed using the International Physical Activity Questionnaire-Long Form. Pain interference was assessed using SF-12, and muscle pain after activity was assessed using Sphere-12. Ordered logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), and restricted cubic splines were used to graphically represent the dose-response association between each physical activity domain and pain outcome. RESULTS: Compared to those in the lowest quartile, participants in the highest quartile for transport activity had less pain interference (workers OR: 0.84, 95% CI: 0.74, 0.95; non-workers OR: 0.80, 95% CI: 0.71, 0.89) and muscle pain after activity (workers OR: 0.82; 95% CI: 0.69, 0.98; non-workers OR: 0.81, 95% CI: 0.71, 0.93). Similarly, participants in the highest quartile of leisure activity had less pain interference (workers: OR: 0.82; 95% CI: 0.69, 0.98; non-workers OR: 0.81, 95% CI: 0.71, 0.93) and muscle pain after activity (workers OR: 0.79; 95% CI: 0.64, 0.96; non-workers: OR: 0.89, 95% CI: 0.76, 1.03). In workers only, participants in the highest quartile of household activity reported more pain interference (OR: 1.37; 95% CI: 1.20, 1.57) and muscle pain after activity (OR: 1.34; 95% CI: 1.12, 1.61) than those in the lowest quartile. Occupational activity was not associated with either pain outcome. CONCLUSIONS: Within the transport and leisure domains, physical activity was inversely associated with pain-related outcomes, whereas more household physical activity was positively associated with pain scores within the working sample.

714-P: Dietary Pattern and Risk of Type 2 Diabetes In Melbourne Collaborative Cohort

Identification of healthy dietary patterns associated with reduced diabetes risk may contribute to diabetes prevention initiatives. The aim of the current study was to investigate whether there is an association between different dietary patterns and incident diabetes in an Australian population. We analysed data of 5,916 eligible Melbourne Collaborative Cohort Study (MCCS) participants, who contributed 343836.6 person-years of follow up with an average 9.4±3.7 years. Dietary patterns for individuals were assessed with three commonly used indices namely, Dietary Inflammatory Index (DII), the Alternative Healthy Eating Index-10 (AHEI-10) and the Mediterranean Diet Score (MDS). Cox proportional hazard regression was used to assess the associations between dietary indices and diabetes risk, adjusted for plausible confounders both with and without baseline body size. At baseline, the average age of the cohort was 55.1 ±8.7 years and 59.9% were female. The incidence rate of diabetes was 4.8 (95% CI 4.6, 5.1) per 1000 person-years. Adjusting for age, sex, socioeconomic status, ethnicity, family history of diabetes, physical activity status, smoking and alcohol consumption status, DII quintile 5 (HR 1.2; 95%CI 1.1, 1.5) and AEHI quintile 5 (HR 0.63; 95%CI 0.53, 0.75)) showed significant associations with diabetes. After additionally adjusting for BMI (HR 0.75; 95%CI 0.74, 0.76) or WHR (HR 0.72; 95%CI 0.71, 0.74), AHEI showed statistically significant inverse associations with diabetes risk. A healthier diet, as assessed by AHEI-10, was associated with a lower risk of diabetes incidence in the MCCS, and this did not appear to be completely explained by an association between diet quality and body size. Disclosure B. de Courten: None. M. Karim: None. A. Hodge: None.

715-P: Diet Scores Associated with Increases in General and Abdominal Obesity in the Melbourne Collaborative Cohort

The prevalence of obesity is increasing rapidly worldwide, increasing the risk of several common chronic diseases. To ascertain which of the three diet scores - Alternative Healthy Eating Index 2010 (AHEI), Dietary Inflammatory Index (DII) and Mediterranean Diet Score (MDS) was a better predictor of future obesity, assessed as body mass index (BMI) or waist to hip circumference ratio (WHR), in the Melbourne Collaborative Cohort Study (MCCS).Prospective cohort study in 27,834 men and women aged between 40 and 69 years at baseline (1990-94). Body size measures were taken at baseline and follow-up in 2003-7. Diet was measure at baseline using a 121-item food frequency questionnaire, along with confounders - age, sex, measure of socioeconomic status, smoking status, alcohol drinking status, physical activity level, country of birth, baseline body size measure (BMI or WHR as applicable). Regression coefficients and 95% confidence intervals for the association of dietary scores at baseline with BMI and WHR at follow-up 2 were generated separately using multivariate linear regression models adjusting for variables listed above and dietary energy intake. Both BMI and WHR at follow-up increased across quintiles of baseline DII (Q5 vs. Q1 BMI 0.4102 (0.2060, 0.6145); WHR 0.0094 (0.0061, 0.0128)), while for AHEI the association was inverse (Q5 vs. Q1 BMI -0.5139 (-0.6791, -0.3487); WHR -0.0107 (-0.0134, -0.0080). Only WHR at follow-up was inversely associated with categories of baseline MDS (G3 vs. G1 BMI -0.0540 (-0.2349, 0.1270); WHR -0.0040 (-0.0070, -0.0010)). Based on Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC) statistics, AHEI was a stronger predictor of increased body size at follow-up than the other diet scores. Poor quality/pro-inflammatory diets predicted future overall and abdominal obesity. The AHEI may provide the best way to operationalise this and capture subtle differences between the scores. Disclosure B. de Courten: None. M. Karim: None. A. Hodge: None.

Domain-Specific Physical Activity, Pain Interference, and Muscle Pain after Activity.

Using the Melbourne Collaborative Cohort Study, we examined the associations of occupation, household, transport, and leisure physical activity with pain interference with normal work and muscle pain after activity. This cross-sectional analysis included 7655 working and 11,766 nonworking participants. Physical activity was assessed using the long-form International Physical Activity Questionnaire. Pain interference was assessed with the Short-Form 12-Item Health Survey version 2.0, and muscle pain after activity was assessed using the 12-item Somatic and Psychological Health Report. Ordered logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), and restricted cubic splines were used to graphically represent the shape of associations. All physical activity domain-pain outcome associations were nonlinear. Compared with participants who reported the lowest level of activity, participants who reported the median level of transport physical activity (10 MET·h·wk) reported less pain interference (workers: OR, 0.86 [95% CI, 0.77-0.97]; nonworkers: OR, 0.88 [95% CI, 0.79-0.97]) and muscle pain after activity (workers: OR, 0.81 [95% CI, 0.70-0.95]; nonworkers: OR, 0.86 [95% CI, 0.77-0.95]). Higher levels of leisure time activity (20 MET·h·wk) were associated with less pain interference in nonworkers (OR, 0.87; 95% CI, 0.77-0.98) and muscle pain after activity in workers (OR, 0.67; 95% CI, 0.56-0.80). Workers who reported the median level of household activity (16 MET·h·wk) had increased pain interference (OR, 1.19; 95% CI, 1.07-1.32) and muscle pain after activity (OR, 1.23; 95% CI, 1.06-1.42) than did those who reported the least household activity. Associations between domain-specific physical activity and pain outcomes were not uniform. Within the transport and leisure domains, physical activity was inversely associated with pain-related outcomes, whereas household physical activity was positively associated with pain scores within the working sample.

Circulating 25-hydroxyvitamin D concentration and cause-specific mortality in the Melbourne Collaborative Cohort Study

Vitamin D deficiency is associated with higher all-cause mortality, but associations with specific causes of death are unclear. We investigated the association between circulating 25-hydroxyvitamin D (25(OH)D) concentration and cause-specific mortality using a case-cohort study within the Melbourne Collaborative Cohort Study (MCCS). Eligibility for the case-cohort study was restricted to participants with baseline dried blood spot samples and no pre-baseline diagnosis of cancer. These analyses included participants who died (n = 2307) during a mean follow-up of 14 years and a sex-stratified random sample of eligible cohort participants (‘subcohort’, n = 2923). Concentration of 25(OH)D was measured using liquid chromatography-tandem mass spectrometry. Cox regression, with Barlow weights and robust standard errors to account for the case-cohort design, was used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for cause-specific mortality in relation to 25(OH)D concentration with adjustment for confounders.Circulating 25(OH)D concentration was inversely associated with risk of death due to cancer (HR per 25 nmol/L increment = 0.88, 95 % CI 0.78–0.99), particularly colorectal cancer (HR = 0.75, 95 % CI 0.57–0.99). Higher 25(OH)D concentrations were also associated with a lower risk of death due to diseases of the respiratory system (HR = 0.62, 95 % CI 0.43–0.88), particularly chronic obstructive pulmonary disease (HR = 0.53, 95 % CI 0.30–0.94), and diseases of the digestive system (HR = 0.44, 95 % CI 0.26–0.76). Estimates for diabetes mortality (HR = 0.64, 95 % CI 0.33–1.26) and cardiovascular disease mortality (HR = 0.90, 95 % CI 0.76–1.07) lacked precision.The findings suggest that vitamin D might be important for preventing death due to some cancers, respiratory diseases, and digestive diseases.

Analysis of retrotransposon subfamily DNA methylation reveals novel early epigenetic changes in chronic lymphocytic leukemia.

Retrotransposons such as LINE-1 and Alu comprise >25% of the human genome. While global hypomethylation of these elements has been widely reported in solid tumours, their epigenetic dysregulation is yet to be characterised in chronic lymphocytic leukemia (CLL), and there has been scant consideration of their evolutionary history that mediates sensitivity to hypomethylation. Here, we developed an approach for locus- and evolutionary subfamily-specific analysis of retrotransposons using the Illumina Infinium Human Methylation 450K microarray platform, which we applied to publicly-available datasets from CLL and other haematological malignancies. We identified 9,797 microarray probes mapping to 117 LINE-1 subfamilies and 13,130 mapping to 37 Alu subfamilies. Of these, 10,782 were differentially methylated (PFDR<0.05) in CLL patients (n=139) compared with healthy individuals (n=14), with enrichment at enhancers (P=0.002). Differential methylation was associated with evolutionary age of LINE-1 (r2=0.31, P=0.003) and Alu (r2=0.74, P=0.002) elements, with greater hypomethylation of older subfamilies (L1M, AluJ). Locus-specific hypomethylation was associated with differential expression of proximal genes, including DCLK2, HK1, ILRUN, TANK, TBCD, TNFRSF1B and TXNRD2, with higher expression of DCLK2 and TNFRSF1B associated with reduced patient survival. Hypomethylation at nine loci was highly frequent in CLL (>90% patients) but not observed in healthy individuals or other leukaemias, and was detectable in blood samples taken prior to CLL diagnosis in 9 of 82 individuals from the Melbourne Collaborative Cohort Study. Our results demonstrate differential methylation of retrotransposons in CLL by their evolutionary heritage that modulates expression of proximal genes.

Alcohol consumption is associated with widespread changes in blood DNA methylation: Analysis of cross-sectional and longitudinal data.

DNA methylation may be one of the mechanisms by which alcohol consumption is associated with the risk of disease. We conducted a large-scale, cross-sectional, genome-wide DNA methylation association study of alcohol consumption and a longitudinal analysis of repeated measurements taken several years apart. Using the Illumina HumanMethylation450 BeadChip, DNA methylation was measured in blood samples from 5606 Melbourne Collaborative Cohort Study (MCCS) participants. For 1088 of them, these measures were repeated using blood samples collected a median of 11 years later. Associations between alcohol intake and blood DNA methylation were assessed using linear mixed-effects regression models. Independent data from the London Life Sciences Prospective Population (LOLIPOP) (N = 4042) and Cooperative Health Research in the Augsburg Region (KORA) (N = 1662) cohorts were used to replicate associations discovered in the MCCS. Cross-sectional analyses identified 1414 CpGs associated with alcohol intake at P < 10-7 , 1243 of which had not been reported previously. Of these novel associations, 1078 were replicated (P < .05) using LOLIPOP and KORA data. Using the MCCS data, we also replicated 403 of 518 previously reported associations. Interaction analyses suggested that associations were stronger for women, non-smokers, and participants genetically predisposed to consume less alcohol. Of the 1414 CpGs, 530 were differentially methylated (P < .05) in former compared with current drinkers. Longitudinal associations between the change in alcohol intake and the change in methylation were observed for 513 of the 1414 cross-sectional associations. Our study indicates that alcohol intake is associated with widespread changes in DNA methylation across the genome. Longitudinal analyses showed that the methylation status of alcohol-associated CpGs may change with alcohol consumption changes in adulthood.