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1.
Clin Epigenetics ; 13(1): 11, 2021 Jan 18.
Artigo em Inglês | MEDLINE | ID: mdl-33461604

RESUMO

BACKGROUND: Tumour 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. METHODS: Tumour-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. RESULTS: We 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. CONCLUSIONS: Our 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.

2.
Addict Biol ; 26(1): e12855, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-31789449

RESUMO

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.

3.
Artigo em Inglês | MEDLINE | ID: mdl-33268487

RESUMO

BACKGROUND: 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. METHODS: 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 18-21 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 which were not defined a priori. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of obesity-related cancer risks by BMI trajectory. RESULTS: 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). CONCLUSION: Our findings suggest that maintaining a healthy BMI across the adult lifespan is important for cancer prevention. IMPACT: Categorisation of BMI by trajectory allowed us to identify specific risk groups to target with public health interventions.

4.
Int J Epidemiol ; 2020 Nov 10.
Artigo em Inglês | MEDLINE | ID: mdl-33169152

RESUMO

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

5.
Int J Cancer ; 2020 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-33197272

RESUMO

Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P ≤ 10-12 ), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.

6.
Clin Epigenetics ; 12(1): 158, 2020 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-33092643

RESUMO

BACKGROUND: DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan. RESULTS: In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0-92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent-offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were - 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent-offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent-offspring pairs. Genetic factors explained 13% (95% CI - 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation. CONCLUSIONS: Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.

7.
Med Sci Sports Exerc ; 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32870614

RESUMO

INTRODUCTION: Long-term effects of physical activity and TV viewing on mortality have been inferred from observational studies. The associations observed do not allow inferences about the effects of population interventions and could be subject to bias due to time-varying confounding. METHODS: Using data from the Australian Diabetes, Obesity and Lifestyle Study, collected in 1999-2000 (T0), 2004-05 (T1), and 2011-12 (T2), we applied the parametric g-formula to estimate cumulative risks of death under hypothetical interventions on physical activity and/or TV viewing determined from self-report, while adjusting for time-varying confounding. RESULTS: In the 6,377 participants followed for 13 years from 2004-05 to death or censoring in 2017, 781 participants died. The observed cumulative risk of death was 12.2%. The most effective hypothetical intervention was to increase weekly physical activity to >300 minutes (RR=0.66, 0.46 to 0.86 compared with a 'worst-case' scenario; and RR=0.83, 0.73 to 0.94 compared with no intervention). Reducing daily TV viewing to <2 hours in addition to physical activity interventions did not show added survival benefits. Reducing TV viewing alone was least effective in reducing mortality (RR=0.85, 0.60 to 1.10 compared with the worst-case scenario; and RR=1.06, 0.93 to 1.20 compared with no intervention). CONCLUSION: Our findings suggested that sustained interventions to increase physical activity could lower all-cause mortality over a 13-year period and there might be limited gain from intervening to reduce TV viewing time in a relatively healthy population.

8.
Artigo em Inglês | MEDLINE | ID: mdl-32958588

RESUMO

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 non-linear 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 (DMRs) 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 (Odds ratio (OR) 1.07 per SD of overall median methylation, 95% CI 0.80-1.44, p=0.65). We found no evidence that blood DNA methylation is prospectively associated with gastric cancer risk.

9.
Cancer Epidemiol Biomarkers Prev ; 29(10): 2026-2037, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32788174

RESUMO

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The number of SEMs is associated with a higher risk of different cancers in prediagnostic blood samples. IMPACT: We identified a candidate biomarker for cancer early detection, and we described a carcinogenesis mechanism involving PCR2 complex proteins worthy of further investigations.

13.
Int J Cancer ; 147(2): 375-382, 2020 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-31609476

RESUMO

Interval breast cancers (those diagnosed between recommended mammography screens) generally have poorer outcomes and are more common among women with dense breasts. We aimed to develop a risk model for interval breast cancer. We conducted a nested case-control study within the Melbourne Collaborative Cohort Study involving 168 interval breast cancer patients and 498 matched control subjects. We measured breast density using the CUMULUS software. We recorded first-degree family history by questionnaire, measured body mass index (BMI) and calculated age-adjusted breast tissue aging, a novel measure of exposure to estrogen and progesterone based on the Pike model. We fitted conditional logistic regression to estimate odds ratio (OR) or odds ratio per adjusted standard deviation (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). The stronger risk associations were for unadjusted percent breast density (OPERA = 1.99; AUC = 0.66), more so after adjusting for age and BMI (OPERA = 2.26; AUC = 0.70), and for family history (OR = 2.70; AUC = 0.56). When the latter two factors and their multiplicative interactions with age-adjusted breast tissue aging (p = 0.01 and 0.02, respectively) were fitted, the AUC was 0.73 (95% CI 0.69-0.77), equivalent to a ninefold interquartile risk ratio. In summary, compared with using dense breasts alone, risk discrimination for interval breast cancers could be doubled by instead using breast density, BMI, family history and hormonal exposure. This would also give women with dense breasts, and their physicians, more information about the major consequence of having dense breasts-an increased risk of developing an interval breast cancer.

14.
Int J Cancer ; 147(3): 766-776, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31721182

RESUMO

Men with prostate cancer experience side effects for which a supportive social environment may be beneficial. We examined the association between four measures of social connectedness and mortality after a prostate cancer diagnosis. Male participants in the Melbourne Collaborative Cohort Study in 1990-1994, who developed incident prostate cancer and attended follow-up in 2003-2007, were eligible for the study. Information on social connectedness, collected at follow-up, included (i) living arrangement; (ii) frequency of visits to friends/relatives and (iii) from friends/relatives; (iv) weekly hours of social activities. A total of 1,421 prostate cancer cases was observed (338 all-cause deaths, 113 from prostate cancer), including 867 after follow-up (150 all-cause deaths, 55 from prostate cancer) and 554 before follow-up (188 all-cause deaths, 58 from prostate cancer). Cox models stratified by tumour Gleason score and stage, and sequentially adjusted for socioeconomic, health- and lifestyle-related confounders, were used to calculate hazard ratios (HR) and 95% confidence intervals (95% CI) for the association between social connectedness and all-cause mortality after prostate cancer. Men who reported living alone before diagnosis had higher overall mortality (HR = 1.6, 95% CI: 1.0-2.5), after adjustment for socioeconomic, health and lifestyle confounders. Lower mortality was observed for men with more social activities (p-trend = 0.07), but not in comprehensively adjusted models. Consistent with these findings, men living alone after prostate cancer diagnosis had higher mortality (HR = 1.3, 95% CI: 0.9-1.9). Lower mortality was observed with increasing socializing hours in the age-adjusted model (p-trend = 0.06) but not after more comprehensive adjustment. Our findings suggest that living with someone, but not other aspects of social connectedness, may be associated with decreased mortality for men with prostate cancer.

15.
Int J Epidemiol ; 49(2): 497-510, 2020 04 01.
Artigo em Inglês | MEDLINE | ID: mdl-31855265

RESUMO

BACKGROUND: Socio-economic inequalities in mortality are well established, yet the contribution of intermediate risk factors that may underlie these relationships remains unclear. We evaluated the role of multiple modifiable intermediate risk factors underlying socio-economic-associated mortality and quantified the potential impact of reducing early all-cause mortality by hypothetically altering socio-economic risk factors. METHODS: Data were from seven cohort studies participating in the LIFEPATH Consortium (total n = 179 090). Using both socio-economic position (SEP) (based on occupation) and education, we estimated the natural direct effect on all-cause mortality and the natural indirect effect via the joint mediating role of smoking, alcohol intake, dietary patterns, physical activity, body mass index, hypertension, diabetes and coronary artery disease. Hazard ratios (HRs) were estimated, using counterfactual natural effect models under different hypothetical actions of either lower or higher SEP or education. RESULTS: Lower SEP and education were associated with an increase in all-cause mortality within an average follow-up time of 17.5 years. Mortality was reduced via modelled hypothetical actions of increasing SEP or education. Through higher education, the HR was 0.85 [95% confidence interval (CI) 0.84, 0.86] for women and 0.71 (95% CI 0.70, 0.74) for men, compared with lower education. In addition, 34% and 38% of the effect was jointly mediated for women and men, respectively. The benefits from altering SEP were slightly more modest. CONCLUSIONS: These observational findings support policies to reduce mortality both through improving socio-economic circumstances and increasing education, and by altering intermediaries, such as lifestyle behaviours and morbidities.

16.
Epigenetics ; 15(4): 358-368, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-31552803

RESUMO

We conducted a genome-wide association study of blood DNA methylation and smoking, attempted replication of previously discovered associations, and assessed the reversibility of smoking-associated methylation changes. DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study. For 1,032 participants, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. A cross-sectional analysis of the association between smoking and DNA methylation and a longitudinal analysis of changes in smoking status and changes in DNA methylation were conducted. We used our cross-sectional analysis to replicate previously reported associations for current (N = 3,327) and former (N = 172) smoking. A comprehensive smoking index accounting for the biological half-life of smoking compounds and several aspects of smoking history was constructed to assess the reversibility of smoking-induced methylation changes. This measure of lifetime exposure to smoking allowed us to detect more associations than comparing current with never smokers. We identified 4,496 cross-sectional associations at P < 10-7, including 3,296 annotated to 1,326 genes that were not previously implicated in smoking-associated DNA methylation changes at this significance threshold. We replicated the majority of previously reported associations (P < 10-7) for current and former smokers. In our data, we observed for former smokers a substantial degree of return to the methylation levels of never smokers, compared with current smokers (median: 74%, IQR = 63-86%), corresponding to small values (median: 2.75, IQR = 1.5-5.25) for the half-life parameter of the comprehensive smoking index. Longitudinal analyses identified 368 sites at which methylation changed upon smoking cessation. Our study demonstrates the usefulness of the comprehensive smoking index to detect associations between smoking and DNA methylation at CpGs across the genome, replicates the vast majority of previously reported associations, and quantifies the reversibility of smoking-induced methylation changes.

17.
Sci Rep ; 9(1): 15055, 2019 10 21.
Artigo em Inglês | MEDLINE | ID: mdl-31636290

RESUMO

DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk.


Assuntos
Envelhecimento/genética , Neoplasias da Mama/genética , Metilação de DNA/genética , Genoma Humano , Adulto , Idoso , Austrália , Neoplasias da Mama/diagnóstico por imagem , Feminino , Humanos , Mamografia , Metanálise como Assunto , Pessoa de Meia-Idade , Fatores de Risco , Irmãos , Gêmeos
18.
BMJ Open ; 9(8): e030078, 2019 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-31401610

RESUMO

OBJECTIVE: Limited research has assessed the association between patterns of body mass index (BMI) change across adulthood and mortality. We aimed to identify groups of individuals who followed specific group-based BMI trajectories across adulthood, using weight collected on three occasions and recalled data from early adulthood, and to examine associations with all-cause and cause-specific mortality. DESIGN: Prospective cohort study. SETTING: Melbourne, Australia. PARTICIPANTS: Adults (n=29 881) enrolled in the Melbourne Collaborative Cohort Study, who were aged from 40 to 70 years between 1990 and 1994, and had BMI data for at least three time points. OUTCOME: Deaths from any cause before 31 March 2017 and deaths from obesity-related cancers, cardiovascular diseases (CVDs) and other causes before 31 December 2013. RESULTS: We identified six group-based BMI trajectories: lower-normal stable (TR1), higher-normal stable (TR2), normal to overweight (TR3), chronic borderline obesity (TR4), normal to class I obesity (TR5) and overweight to class II obesity (TR6). Generally, compared with maintaining lower-normal BMI throughout adulthood, the lowest mortality was experienced by participants who maintained higher-normal BMI (HR 0.90; 95% CI 0.84 to 0.97); obesity during midlife was associated with higher all-cause mortality even when BMI was normal in early adulthood (HR 1.09; 95% CI 0.98 to 1.21) and prolonged borderline obesity from early adulthood was also associated with elevated mortality (HR 1.16; 95% CI 1.01 to 1.33). These associations were stronger for never-smokers and for death due to obesity-related cancers. Being overweight in early adulthood and becoming class II obese was associated with higher CVD mortality relative to maintaining lower-normal BMI (HR 2.27; 95% CI 1.34 to 3.87). CONCLUSION: Our findings highlight the importance of weight management throughout adulthood to reduce mortality.


Assuntos
Índice de Massa Corporal , Mortalidade , Adulto , Fatores Etários , Idoso , Causas de Morte , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Obesidade/mortalidade , Sobrepeso/mortalidade , Estudos Prospectivos , Fatores de Risco , Magreza/mortalidade , Vitória/epidemiologia
19.
Breast Cancer Res ; 21(1): 62, 2019 05 17.
Artigo em Inglês | MEDLINE | ID: mdl-31101124

RESUMO

BACKGROUND: Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. METHODS: We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis (< 50, ≥ 50), estrogen receptor (ER) status (+/-), and time since blood collection (< 5, 5-10, > 10 years). The false discovery rate (q value) was used to account for multiple testing. RESULTS: The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). CONCLUSIONS: Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.


Assuntos
Neoplasias da Mama/genética , DNA Tumoral Circulante , Metilação de DNA , DNA de Neoplasias , Epigênese Genética , Neoplasias da Mama/sangue , Estudos de Casos e Controles , Ilhas de CpG , Feminino , Perfilação da Expressão Gênica , Humanos , Pessoa de Meia-Idade , Razão de Chances , Estudos Prospectivos , Medição de Risco , Fatores de Risco
20.
Clin Epigenetics ; 11(1): 66, 2019 04 30.
Artigo em Inglês | MEDLINE | ID: mdl-31039828

RESUMO

BACKGROUND: It is well established that estrogens and other hormonal factors influence breast cancer susceptibility. We hypothesized that a woman's total lifetime estrogen exposure accumulates changes in DNA methylation, detectable in the blood, which could be used in risk assessment for breast cancer. METHODS: An estimated lifetime estrogen exposure (ELEE) model was defined using epidemiological data from EPIC-Italy (n = 31,864). An epigenome-wide association study (EWAS) of ELEE was performed using existing Illumina HumanMethylation450K Beadchip (HM450K) methylation data obtained from EPIC-Italy blood DNA samples (n = 216). A methylation index (MI) of ELEE based on 31 CpG sites was developed using HM450K data from EPIC-Italy and the Generations Study and evaluated for association with breast cancer risk in an independent dataset from the Generations Study (n = 440 incident breast cancer cases matched to 440 healthy controls) using targeted bisulfite sequencing. Lastly, a meta-analysis was conducted including three additional cohorts, consisting of 1187 case-control pairs. RESULTS: We observed an estimated 5% increase in breast cancer risk per 1-year longer ELEE (OR = 1.05, 95% CI 1.04-1.07, P = 3 × 10-12) in EPIC-Italy. The EWAS identified 694 CpG sites associated with ELEE (FDR Q < 0.05). We report a DNA methylation index (MI) associated with breast cancer risk that is validated in the Generations Study targeted bisulfite sequencing data (ORQ4_vs_Q1 = 1.77, 95% CI 1.07-2.93, P = 0.027) and in the meta-analysis (ORQ4_vs_Q1 = 1.43, 95% CI 1.05-2.00, P = 0.024); however, the correlation between the MI and ELEE was not validated across study cohorts. CONCLUSION: We have identified a blood DNA methylation signature associated with breast cancer risk in this study. Further investigation is required to confirm the interaction between estrogen exposure and DNA methylation in the blood.


Assuntos
Neoplasias da Mama/genética , Metilação de DNA , Estrogênios/efeitos adversos , Estudo de Associação Genômica Ampla/métodos , Estudos de Casos e Controles , Ilhas de CpG , Metilação de DNA/efeitos dos fármacos , Epigênese Genética , Feminino , Predisposição Genética para Doença , Humanos , Itália , Pessoa de Meia-Idade , Estudos Prospectivos
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