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Background: Multigene panel tests for breast cancer predisposition routinely include ATM as it is now a well-established breast cancer predisposition gene.Methods: We included ATM in a multigene panel test applied to the Australian Breast Cancer Family Registry (ABCFR), a population-based case-control-family study of breast cancer, with the purpose of estimating the prevalence and penetrance of heterozygous ATM pathogenic variants from the family data, using segregation analysis.Results: The estimated breast cancer hazard ratio for carriers of pathogenic ATM variants in the ABCFR was 1.32 (95% confidence interval 0.45-3.87; P = 0.6). The estimated cumulative risk of breast cancer to age 80 years for heterozygous ATM pathogenic variant carriers was estimated to be 13% (95% CI 4.6-30).Conclusions: Although ATM has been definitively identified as a breast cancer predisposition gene, further evidence, such as variant-specific penetrance estimates, are needed to inform risk management strategies for carriers of pathogenic variants to increase the clinical utility of population testing of this gene. [ABSTRACT FROM AUTHOR]

Background: In a previous paper, we had assumed that the risk of screen-detected breast cancer mostly reflects inherent risk, and the risk of whether a breast cancer is interval versus screen-detected mostly reflects risk of masking. We found that inherent risk was predicted by body mass index (BMI) and dense area (DA) or percent dense area (PDA), but not by non-dense area (NDA). Masking, however, was best predicted by PDA but not BMI. In this study, we aimed to investigate if these associations vary by tumor characteristics and mode of detection.Methods: We conducted a case-control study nested within the Melbourne Collaborative Cohort Study of 244 screen-detected cases matched to 700 controls and 148 interval cases matched to 446 controls. DA, NDA and PDA were measured using the Cumulus software. Tumor characteristics included size, grade, lymph node involvement, and ER, PR, and HER2 status. Conditional and unconditional logistic regression were applied as appropriate to estimate the Odds per Adjusted Standard Deviation (OPERA) adjusted for age and BMI, allowing the association with BMI to be a function of age at diagnosis.Results: For screen-detected cancer, both DA and PDA were associated to an increased risk of tumors of large size (OPERA ~ 1.6) and positive lymph node involvement (OPERA ~ 1.8); no association was observed for BMI and NDA. For risk of interval versus screen-detected breast cancer, the association with risk for any of the three mammographic measures did not vary by tumor characteristics; an association was observed for BMI for positive lymph nodes (OPERA ~ 0.6). No associations were observed for tumor grade and ER, PR and HER2 status of tumor.Conclusions: Both DA and PDA were predictors of inherent risk of larger breast tumors and positive nodal status, whereas for each of the three mammographic density measures the association with risk of masking did not vary by tumor characteristics. This might raise the hypothesis that the risk of breast tumours with poorer prognosis, such as larger and node positive tumours, is intrinsically associated with increased mammographic density and not through delay of diagnosis due to masking. [ABSTRACT FROM AUTHOR]

Background: Mammographic density defined by the conventional pixel brightness threshold, and adjusted for age and body mass index (BMI), is a well-established risk factor for breast cancer. We asked if higher thresholds better separate women with and without breast cancer.Methods: We studied Australian women, 354 with breast cancer over-sampled for early-onset and family history, and 944 unaffected controls frequency-matched for age at mammogram. We measured mammographic dense area and percent density using the CUMULUS software at the conventional threshold, which we call Cumulus , and at two increasingly higher thresholds, which we call Altocumulus and Cirrocumulus , respectively. All measures were Box-Cox transformed and adjusted for age and BMI. We estimated the odds per adjusted standard deviation (OPERA) using logistic regression and the area under the receiver operating characteristic curve (AUC).Results: Altocumulus and Cirrocumulus were correlated with Cumulus (r ∼ 0.8 and 0.6 , respectively) . For dense area, the OPERA was 1.62, 1.74 and 1.73 for Cumulus, Altocumulus and Cirrocumulus , respectively (all P  < 0.001). After adjusting for Altocumulus and Cirrocumulus , Cumulus was not significant ( P  > 0.6). The OPERAs for percent density were less but gave similar findings. The mean of the standardized adjusted Altocumulus and Cirrocumulus dense area measures was the best predictor; OPERA = 1.87 [95% confidence interval (CI): 1.64-2.14] and AUC = 0.68 (0.65-0.71).Conclusions: The areas of higher mammographically dense regions are associated with almost 30% stronger breast cancer risk gradient, explain the risk association of the conventional measure and might be more aetiologically important. This has substantial implications for clinical translation and molecular, genetic and epidemiological research. [ABSTRACT FROM AUTHOR]

Background: Women with breast cancer who have multiple affected relatives are more likely to have inherited genetic risk factors for the disease. All the currently known genetic risk factors for breast cancer account for less than half of the average familial risk. Furthermore, the genetic factor(s) underlying an increased cancer risk for many women from multiple-case families remain unknown. Rare genomic duplications and deletions, known as copy number variants (CNVs), cover more than 10% of a human genome, are often not assessed in studies of genetic predisposition, and could account for some of the so-called "missing heritability".Methods: We carried out a hypothesis-generating case-control study of breast cancer diagnosed before age 40 years (200 cases, 293 controls) using population-based cases from the Australian Breast Cancer Family Study. Genome-wide scanning for CNVs was performed using the Human610-Quad BeadChip and fine-mapping was conducted using PennCNV.Results: We identified deletions overlapping two known cancer susceptibility genes, (BRCA1 and BLM), and a duplication overlapping SMARCB1, associated with risk. The number of deletions across the genome was 1.5-fold higher for cases than controls (P = 10-16), and 2-fold higher when only rare deletions overlapping genes (frequency <1%) were assessed (P = 5 × 10-4). Association tests of CNVs, followed by experimental validation of CNV calls, found deletions overlapping the OR4C11 and OR4P4 genes were associated with breast cancer (P = 0.02 and P = 0.03, respectively).Conclusion: These results suggest rare CNVs might have a role in breast cancer susceptibility, at least for disease at a young age. [ABSTRACT FROM AUTHOR]

Initially submitted February 1, 2016; accepted for publication August 4, 2016. The ability to classify people according to their underlying genetic susceptibility to a disease is increasing with new knowledge, better family data, and more sophisticated risk prediction models, allowing for more effective prevention and screening. To do so, however, we need to know whether risk associations are the same for people with different genetic susceptibilities. To illustrate one way to estimate such gene-environment interactions, we used prospective data from 3 Australian family cancer cohort studies, 2 enriched for familial risk of breast cancer. There were 288 incident breast cancers in 9,126 participants from 3,222 families. We used Cox proportional hazards models to investigate whether associations of breast cancer with body mass index (BMI; weight (kg)/height (m)2) at age 18-21 years, BMI at baseline, and change in BMI differed according to genetic risk based on lifetime breast cancer risk from birth, as estimated by BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) software, adjusted for age at baseline data collection. Although no interactions were statistically significant, we have demonstrated the power with which gene-environment interactions can be investigated using a cohort enriched for persons with increased genetic risk and a continuous measure of genetic risk based on family history. [ABSTRACT FROM AUTHOR]

Background: A previous Australian population-based breast cancer case-control study found indirect evidence that control participation, although high, was not random. We hypothesized that unaffected sisters may provide a more appropriate comparison group than unrelated population controls.Methods: Three population-based case-control-family studies of breast cancer in women of white European origin were carried out by the Australian, Ontario and Northern California sites of the Breast Cancer Family Registry. We compared risk factors between 3643 cases, 2444 of their unaffected sisters and 2877 population controls and conducted separate case-control analyses based on population and sister controls using unconditional multivariable logistic regression.Results: Compared with sister controls, population controls were more highly educated, had an earlier age at menarche, fewer births, their first birth at a later age and their last birth more recently. The established breast cancer associations detected using sister controls, but not detected using population controls, were decreasing risk with each of later age at menarche, more births, younger age at first birth and greater time since last birth.Conclusions: Since participation of population controls might be unintentionally related to some risk factors, we hypothesize that sister controls could provide more valid relative risk estimates and be recruited at lower cost. Given declining study participation by population controls, this contention is highly relevant to epidemiologic research. [ABSTRACT FROM AUTHOR]

Inherited predisposition to breast cancer is explained only in part by mutations in the BRCA1 and BRCA2 genes. Most families with an apparent familial clustering of breast cancer who are investigated through Australia's network of genetic services and familial cancer centres do not have mutations in either of these genes. More recently, additional breast cancer predisposition genes, such as PALB2, have been identified. New genetic technology allows a panel of multiple genes to be tested for mutations in a single test. This enables more women and their families to have risk assessment and risk management, in a preventive approach to predictable breast cancer. Predictive testing for a known family-specific mutation in a breast cancer predisposition gene provides personalised risk assessment and evidence-based risk management. Breast cancer predisposition gene panel tests have a greater diagnostic yield than conventional testing of only the BRCA1 and BRCA2 genes. The clinical validity and utility of some of the putative breast cancer predisposition genes is not yet clear. Ethical issues warrant consideration, as multiple gene panel testing has the potential to identify secondary findings not originally sought by the test requested. Multiple gene panel tests may provide an affordable and effective way to investigate the heritability of breast cancer. [ABSTRACT FROM AUTHOR]

Little is known about the association between ambient temperature and DNA methylation, which is a potential biological process through which ambient temperature affects health. This study aimed to evaluate the association between ambient temperature and DNA methylation across human genome. We included 479 Australian women, including 132 twin pairs and 215 sisters of these twins. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on average ambient temperature during eight different exposure windows [lag0d (the blood draw day), lag0-7d (the current day and previous seven days prior to blood draw), lag0-14d, lag0-21d, lag0-28d, lag0-90d, lag0-180d, and lag0-365d)] was linked to each participant's home address. For each cytosine-guanine dinucleotide (CpG), we evaluated the association between its methylation level and temperature using generalized estimating equations (GEE), adjusting for important covariates. We used comb-p and DMRcate to identify differentially methylated regions (DMRs). We identified 31 CpGs at which blood DNA methylation were significantly associated with ambient temperature with false discovery rate [FDR] < 0.05. There were 82 significant DMRs identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Most of these CpGs and DMRs only showed association with temperature during one specific exposure window. These CpGs and DMRs were mapped to 85 genes. These related genes have been related to many human chronic diseases or phenotypes (e.g., diabetes, arthritis, breast cancer, depression, asthma, body height) in previous studies. The signals of short-term windows (lag0d and lag0-21d) showed enrichment in biological processes related to cell adhesion. In conclusion, short-, medium-, and long-term exposures to ambient temperature were all associated with blood DNA methylation, but the target genomic loci varied by exposure window. These differential methylation signals may serve as potential biomarkers to understand the health impacts of temperature. [Display omitted] • Ambient temperature was associated with human blood DNA methylation. • The association was significant for 31 CpGs and 82 DMRs across human genome. • The target genomic loci varied by exposure windows from one day to one year. • Those loci are mapped to many genes related to many human diseases and phenotypes. [ABSTRACT FROM AUTHOR]

Background To improve melanoma early detection, tools to predict personal risk based on genetic information (polygenic risk scores, PRS) have been developed, but require external validation. Methods We analysed invasive melanoma incidence in UK Biobank (UKB; n = 395,647; 1,651 cases) and the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4,765; 303 cases). Three PRS were evaluated: 68 genetic variants (SNPs) at 54 loci from a 2020 meta-analysis (PRS68); 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50); 45 SNPs at 21 loci known pre-2020 (PRS45). 10-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. Results All PRS were strongly associated with melanoma incidence, including after adjustment for age, sex, ethnicity, and ease of tanning. Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in UKB (ratio expected/observed cases E/O=0.65, 95% confidence interval 0.62-0.68) and MCCS (E/O=0.65, 0.57-0.73). For UKB, this was reduced by PRS-adjustment, e.g. PRS50-adjusted risks E/O=0.91 (0.87-0.95). Discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (deltaAUC 0.07-0.1, p < 0.0001), and higher than for PRS45-adjusted risks (deltaAUC 0.02-0.04, p < 0.001). Conclusions A PRS derived from a larger, more diverse meta-analysis improves melanoma risk prediction compared to an earlier PRS. Re-calibration of absolute risks may be necessary for application to specific populations. Key messages A genetic score can improve prediction of melanoma risk and might help tailor melanoma prevention and early detection strategies to different risk levels. [ABSTRACT FROM AUTHOR]

Background: We conducted a population-based, case-control-family study to determine whether androgen receptor (AR) exon 1 polymorphic CAG repeat length (CAGn) was a risk factor for early-onset breast cancer in the Australian population.Methods: Case subjects under 40 years of age at diagnosis of a first primary breast cancer and age-matched control subjects were interviewed to assess family history and other risk factors. AR CAGn length was determined for 368 case subjects and 284 control subjects. Distributions in the two groups were compared by linear and logistic regression, allowing adjustment for measured risk factors. All statistical tests were two-tailed.Results: When analyzed as either a continuous or a dichotomous variable, there was no association between CAG, length and breast cancer risk, before or after adjustment for risk factors. Mean (95% confidence interval [CI]) CAGn lengths were 22.0 (21.8-22.2) for case subjects and 22.0 (21.7-22.3) for control subjects (P = .9). The frequency (95% CI) of alleles with 22 or more CAGn repeats was 0.531 (0.494-0.568) for case subjects and 0.507 (0.465-0.549) for control subjects (P = .4). After adjustment, the average effect on log OR (odds ratio) per allele was 0.16 (95% CI = -0.03 to 0.40; P = .2), and the effect of any allele was equivalent to an OR of 1.40 (95% CI = 0.94-2.09; P = .1). Stratification by family history also failed to reveal any association. Similar results were obtained when alleles were defined by other cutoff points.Conclusion: We found no evidence for an association between AR exon 1 CAGn length and breast cancer risk in women under the age of 40, despite having 80% power to detect modest effects. [ABSTRACT FROM AUTHOR]

Simple Summary: It is well established that women who carry pathogenic CHEK2 variants have about a 3-fold increased risk of developing breast cancer. CHEK2 is now commonly included in genetic tests for breast cancer predisposition and increasingly used to inform the clinical management of women who are identified to carry pathogenic variants. Important information for counselling these women includes knowing how breast cancer risk, due to having a pathogenic variant in CHEK2, changes over a woman's lifetime. This information is currently not well established. By conducting a population-based case-control-family study of pathogenic CHEK2 variants we aimed to provide this information and estimated the penetrance (age-specific cumulative risk) of breast cancer to be 18% (95% CI 11–30%) to age 60 years and 33% (95% CI 21–48%) to age 80 years. These findings provide new and important information for the clinical management of breast cancer risk for women carrying pathogenic variants in CHEK2. Case-control studies of breast cancer have consistently shown that pathogenic variants in CHEK2 are associated with about a 3-fold increased risk of breast cancer. Information about the recurrent protein-truncating variant CHEK2 c.1100delC dominates this estimate. There have been no formal estimates of age-specific cumulative risk of breast cancer for all CHEK2 pathogenic (including likely pathogenic) variants combined. We conducted a population-based case-control-family study of pathogenic CHEK2 variants (26 families, 1071 relatives) and estimated the age-specific cumulative risk of breast cancer using segregation analysis. The estimated hazard ratio for carriers of pathogenic CHEK2 variants (combined) was 4.9 (95% CI 2.5–9.5) relative to non-carriers. The HR for carriers of the CHEK2 c.1100delC variant was estimated to be 3.5 (95% CI 1.02–11.6) and the HR for carriers of all other CHEK2 variants combined was estimated to be 5.7 (95% CI 2.5–12.9). The age-specific cumulative risk of breast cancer was estimated to be 18% (95% CI 11–30%) and 33% (95% CI 21–48%) to age 60 and 80 years, respectively. These findings provide important information for the clinical management of breast cancer risk for women carrying pathogenic variants in CHEK2. [ABSTRACT FROM AUTHOR]

Background: The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers.Methods: We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for ≥1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically).Results: From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33-1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57-0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15-0.97; combined HR = 0.29; 95% CI = 0.23-0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associations were not modified by familial risk, and consistent patterns were found by BRCA1 and BRCA2 carrier status, estrogen receptor status, and attained age.Conclusion: Regular use of aspirin and COX-2 inhibitors might reduce breast cancer risk for women at familial or genetic risk. [ABSTRACT FROM AUTHOR]

Background: Breast cancer risk for BRCA1 and BRCA2 pathogenic mutation carriers is modified by risk factors that cluster in families, including genetic modifiers of risk. We considered genetic modifiers of risk for carriers of high-risk mutations in other breast cancer susceptibility genes.Methods: In a family known to carry the high-risk mutation PALB2:c.3113G>A (p.Trp1038*), whole-exome sequencing was performed on germline DNA from four affected women, three of whom were mutation carriers.Results: RNASEL:p.Glu265* was identified in one of the PALB2 carriers who had two primary invasive breast cancer diagnoses before 50 years. Gene-panel testing of BRCA1, BRCA2, PALB2 and RNASEL in the Australian Breast Cancer Family Registry identified five carriers of RNASEL:p.Glu265* in 591 early onset breast cancer cases. Three of the five women (60%) carrying RNASEL:p.Glu265* also carried a pathogenic mutation in a breast cancer susceptibility gene compared with 30 carriers of pathogenic mutations in the 586 non-carriers of RNASEL:p.Glu265* (5%) (p < 0.002). Taqman genotyping demonstrated that the allele frequency of RNASEL:p.Glu265* was similar in affected and unaffected Australian women, consistent with other populations.Conclusion: Our study suggests that RNASEL:p.Glu265* may be a genetic modifier of risk for early-onset breast cancer predisposition in carriers of high-risk mutations. Much larger case-case and case-control studies are warranted to test the association observed in this report. [ABSTRACT FROM AUTHOR]

Presents segregation analyses which investigated models of familial aggregation of female breast cancer that consider together different modes of inheritance in Australia. Percentage of women with breast cancer by age at diagnosis for different categories of family members; Cumulative probability of breast cancer for the Australian population; Comparison between the segregation analyses of two-locus models and the single-locus models.

In the genomic era, the availability of gene panel and whole genome/exome sequencing is rapidly increasing. Opportunities for providing former patients with new genetic information are also increasing over time and recontacting former patients with new information is likely to become more common. Breast cancer Refined Analysis of Sequence Tests-Risk And Penetrance (BRA-STRAP) is an Australian study of individuals who had previously undertaken BRCA1 and BRCA2 genetic testing, with no pathogenic variants detected. Using a waiver of consent, stored DNA samples were retested using a breast/ovarian cancer gene panel and clinically significant results returned to the patient (or next of kin, if deceased). This qualitative study aimed to explore patient experiences, opinions, and expectations of recontacting in the Australian hereditary cancer setting. Participants were familial cancer clinic patients (or next of kin) who were notified of a new pathogenic variant identified via BRA-STRAP. In-depth, semi-structured interviews were conducted approximately 6 weeks post-result. Interviews were transcribed verbatim and analyzed using an inductive thematic approach. Thirty participants (all female; average age = 57; range 36-84) were interviewed. Twenty-five were probands, and five were next of kin. Most women reported initial shock upon being recontacted with unexpected news, after having obtained a sense of closure related to their initial genetic testing experiences and cancer diagnosis. For most, this initial distress was short-lived, followed by a process of readjustment, meaning-making and adaptation that was facilitated by perceived clinical and personal utility of the information. Women were overall satisfied with the waiver of consent approach and recontacting process. Results are in line with previous studies suggesting that patients have positive attitudes about recontacting. Women in this study valued new genetic information gained from retesting and were satisfied with the BRA-STRAP recontact model. Practice implications to facilitate readjustment and promote psychosocial adaptation were identified., (© 2023 The Authors. Journal of Genetic Counseling published by Wiley Periodicals LLC on behalf of National Society of Genetic Counselors.)

Self-rated health (SRH) is a subjective indicator of overall health based on a single questionnaire item. Previous evidence found that it is a strong predictor of mortality, although the underlying mechanism is poorly understood. Epigenetic age is an objective, emerging biomarker of health, estimated using DNA methylation data at hundreds of sites across the genome. This study aimed to assess the overlap and interaction between SRH and epigenetic ageing in predicting mortality risk. We used DNA methylation data from 1059 participants in the Melbourne Collaborative Cohort Study (mean age: 69 years) to calculate three age-adjusted measures of epigenetic ageing: GrimAge, PhenoAge, and DunedinPACE. SRH was assessed using a five-category questionnaire item ("excellent, very good, good, fair, poor"). Cox models were used to assess the associations of SRH, epigenetic ageing, and their interaction, with all-cause mortality over up to 17 years of follow-up (N deaths  = 345). The association of SRH with mortality per category increase was HR = 1.29; 95%CI: 1.14-1.46. The association was slightly attenuated after adjusting for all three epigenetic ageing measures (HR = 1.25, 95%CI: 1.10-1.41). A strong gradient was observed in the association of GrimAge (P interaction  = 0.006) and DunedinPACE (P interaction  = 0.002) with mortality across worsening SRH strata. For example, the association between DunedinPACE and mortality in participants with "excellent" SRH was HR = 1.02, 95%CI: 0.73-1.43 and for "fair/poor" HR = 1.72, 95%CI: 1.35-2.20. SRH and epigenetic ageing were synergistic risk factors of mortality in our study. These findings suggest that consideration of subjective and objective factors may improve general health assessment, which has implications for the ongoing development of molecular markers of ageing., (© 2024. The Author(s).)

Introduction: Established personal and familial risk factors contribute collectively to a woman's risk of breast or ovarian cancer. Existing clinical services offer genetic testing for pathogenic variants in high-risk genes to investigate these risks but recent information on the role of common genomic variants, in the form of a Polygenic Risk Score (PRS), has provided the potential to further personalise breast and ovarian cancer risk assessment. Data from cohort studies support the potential of an integrated risk assessment to improve targeted risk management but experience of this approach in clinical practice is limited., Methods and Analysis: The polygenic risk modification trial is an Australian multicentre prospective randomised controlled trial of integrated risk assessment including personal and family risk factors with inclusion of breast and ovarian PRS vs standard care. The study will enrol women, unaffected by cancer, undergoing predictive testing at a familial cancer clinic for a pathogenic variant in a known breast cancer (BC) or ovarian cancer (OC) predisposition gene ( BRCA1 , BRCA2 , PALB2 , CHEK2 , ATM , RAD51C , RAD51D ). Array-based genotyping will be used to generate breast cancer (313 SNP) and ovarian cancer (36 SNP) PRS. A suite of materials has been developed for the trial including an online portal for patient consent and questionnaires, and a clinician education programme to train healthcare providers in the use of integrated risk assessment. Long-term follow-up will evaluate differences in the assessed risk and management advice, patient risk management intentions and adherence, patient-reported experience and outcomes, and the health service implications of personalised risk assessment., Ethics and Dissemination: This study has been approved by the Human Research Ethics Committee of Peter MacCallum Cancer Centre and at all participating centres. Study findings will be disseminated via peer-reviewed publications and conference presentations, and directly to participants., Trial Registration Number: ACTRN12621000009819., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Differentially methylated CpG sites (dmCpGs) that distinguish prostate tumour from adjacent benign tissue could aid in the diagnosis and prognosis of prostate cancer. Previously, the identification of such dmCpGs has only been undertaken in radical prostatectomy (RP) samples and not primary diagnostic tumour samples (needle biopsy or transurethral resection of the prostate). We interrogated an Australian dataset comprising 125 tumour and 43 adjacent histologically benign diagnostic tissue samples, including 41 paired samples, using the Infinium Human Methylation450 BeadChip. Regression analyses of paired tumour and adjacent benign samples identified 2,386 significant dmCpGs (Bonferroni p < 0.01; delta-β ≥ 40%), with LASSO regression selecting 16 dmCpGs that distinguished tumour samples in the full Australian diagnostic dataset (AUC = 0.99). Results were validated in independent North American (n paired  = 19; AUC = 0.87) and The Cancer Genome Atlas (TCGA; n paired  = 50; AUC = 0.94) RP datasets. Two of the 16 dmCpGs were in genes that were significantly down-regulated in Australian tumour samples (Bonferroni p < 0.01; GSTM2 and PRKCB). Ten additional dmCpGs distinguished low (n = 34) and high Gleason (n = 88) score tumours in the diagnostic Australian dataset (AUC = 0.95), but these performed poorly when applied to the RP datasets (North American: AUC = 0.66; TCGA: AUC = 0.62). The DNA methylation marks identified here could augment and improve current diagnostic tests and/or form the basis of future prognostic tests., (© 2024. The Author(s).)

Background: Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology., Methods: We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method., Results: The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P < 0.005). We estimated that 28-92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively)., Conclusions: In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Glioma accounts for approximately 80% of malignant adult brain cancer and its most common subtype, glioblastoma, has one of the lowest 5-year cancer survivals. Fifty risk-associated variants within 34 glioma genetic risk regions have been found by genome-wide association studies (GWAS) with a sex difference reported for 8q24.21 region. We conducted an Australian GWAS by glioma subtype and sex., Methods: We analyzed genome-wide data from the Australian Genomics and Clinical Outcomes of Glioma (AGOG) consortium for 7 573 692 single nucleotide polymorphisms (SNPs) for 560 glioma cases and 2237 controls of European ancestry. Cases were classified as glioblastoma, non-glioblastoma, astrocytoma or oligodendroglioma. Logistic regression analysis was used to assess the associations of SNPs with glioma risk by subtype and by sex., Results: We replicated the previously reported glioma risk associations in the regions of 2q33.3 C2orf80, 2q37.3 D2HGDH, 5p15.33 TERT, 7p11.2 EGFR, 8q24.21 CCDC26, 9p21.3 CDKN2BAS, 11q21 MAML2, 11q23.3 PHLDB1, 15q24.2 ETFA, 16p13.3 RHBDF1, 16p13.3 LMF1, 17p13.1 TP53, 20q13.33 RTEL, and 20q13.33 GMEB2 (P < .05). We also replicated the previously reported sex difference at 8q24.21 CCDC26 (P = .0024) with the association being nominally significant for both sexes (P < .05)., Conclusions: Our study supports a stronger female risk association for the region 8q24.21 CCDC26 and highlights the importance of analyzing glioma GWAS by sex. A better understanding of sex differences could provide biological insight into the cause of glioma with implications for prevention, risk prediction and treatment., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

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.

Background: Wildfire-related fine particulate matter (PM 2.5 ) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM 2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM 2.5 ., Methods: We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM 2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM 2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate., Results: The 3-year average wildfire-related PM 2.5 (range: 0.3 to 7.6 µg/m 3 , mean: 1.6 µg/m 3 ) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM 2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM 2.5 ., Conclusions: Long-term exposure to wildfire-related PM 2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM 2.5 ., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Michael Abramson holds investigator initiated grants from Pfizer, Boehringer-Ingelheim and Sanofi for unrelated research. He has undertaken an unrelated consultancy for and received assistance with conference attendance from Sanofi. He also received a speaker’s fee from GSK. The other authors declare no competing interests]., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation., Methods: Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant's home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0-1 to TV 0-7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied., Results: Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0-3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0-3)., Conclusions: Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Michael J. Abramson reports a relationship with Pfizer and Boehringer-Ingelheim that includes: funding grants. Michael J. Abramson reports a relationship with Sanofi that includes: consulting or advisory. Michael J. Abramson reports a relationship with GlaxoSmithKline that includes: speaking and lecture fees., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks)., Objectives: To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry., Methods: We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment., Results: Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P < 0·001)., Conclusions: A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations., (© 2022 The Authors. British Journal of Dermatology published by John Wiley & Sons Ltd on behalf of British Association of Dermatologists.)

Background: DNA methylation is a potential biological mechanism through which residential greenness affects health, but little is known about its association with greenness and whether the association could be modified by genetic background. We aimed to evaluate the association between surrounding greenness and genome-wide DNA methylation and potential gene-greenness interaction effects on DNA methylation., Methods: We measured blood-derived DNA methylation using the HumanMethylation450 BeadChip array (Illumina) for 479 Australian women, including 66 monozygotic, 66 dizygotic twin pairs, and 215 sisters of these twins. Surrounding greenness was represented by Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) within 300, 500, 1000 or 2000 m surrounding participants' home addresses. For each cytosine-guanine dinucleotide (CpG), the associations between its methylation level and NDVI or EVI were evaluated by generalized estimating equations, after adjusting for age, education, marital status, area-level socioeconomic status, smoking behavior, cell-type proportions, and familial clustering. We used comb-p and DMRcate to identify significant differentially methylated regions (DMRs). For each significant CpG, we evaluated the interaction effects of greenness and single-nucleotide polymorphisms (SNPs) within ±1 Mb window on its methylation level., Results: We found associations between surrounding greenness and blood DNA methylation for one CpG (cg04720477, mapped to the promoter region of CNP gene) with false discovery rate [FDR] < 0.05, and for another 9 CpGs with 0.05 ≤ FDR < 0.10. For two of these CpGs, we found 33 SNPs significantly (FDR < 0.05) modified the greenness-methylation association. There were 35 significant DMRs related to surrounding greenness that were identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Those CpGs and DMRs were mapped to genes related to many human diseases, such as mental health disorders and neoplasms as well as nutritional and metabolic diseases., Conclusions: Surrounding greenness was associated with blood DNA methylation of many loci across human genome, and this association could be modified by genetic variations., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics., Objectives: We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation., Methods: We derived Horvath's DNA methylation age (DNAmAge), Hannum's DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000 -m buffers surrounding participant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates., Results: Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300 - 2,000 m buffer areas. For example, each interquartile range increase in NDVI within 1,000 m was associated with a 0.59 (95% CI: 0.18, 1.01)-year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath's and Hannum's DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration., Discussion: Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.

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., (© 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Our aim was to estimate how long-term mortality following breast cancer diagnosis depends on age at diagnosis, tumor estrogen receptor (ER) status, and the time already survived. We used the population-based Australian Breast Cancer Family Study which followed-up 1,196 women enrolled during 1992-1999 when aged <60 years at diagnosis with a first primary invasive breast cancer, over-sampled for younger ages at diagnosis, for whom tumor pathology features and ER status were measured. There were 375 deaths (median follow-up = 15.7; range = 0.8-21.4, years). We estimated the mortality hazard as a function of time since diagnosis using a flexible parametric survival analysis with ER status a time-dependent covariate. For women with ER-negative tumors compared with those with ER-positive tumors, 5-year mortality was initially higher (p < 0.001), similar if they survived to 5 years (p = 0.4), and lower if they survived to 10 years (p = 0.02). The estimated mortality hazard for ER-negative disease peaked at ~3 years post-diagnosis, thereafter declined with time, and at 7 years post-diagnosis became lower than that for ER-positive disease. This pattern was more pronounced for women diagnosed at younger ages. Mortality was also associated with lymph node count (hazard ratio (HR) per 10 nodes = 2.52 [95% CI:2.11-3.01]) and tumor grade (HR per grade = 1.62 [95% CI:1.34-1.96]). The risk of death following a breast cancer diagnosis differs substantially and qualitatively with diagnosis age, ER status and time survived. For women who survive >7 years, those with ER-negative disease will on average live longer, and more so if younger at diagnosis., (© 2019 UICC.)

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.

Age- and body mass index (BMI)-adjusted mammographic density is one of the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie inter-individual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, nondense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant (p < 10 -7 ) association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all p > 0.05/299 = 1.7 × 10 -4 ). In summary, our study did not find evidence for associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk., (© 2019 UICC.)

Introduction: Physical activity may affect health via DNA methylation. The epigenetic influences of sedentary behaviors such as television viewing are unknown. We performed a genomewide study of DNA methylation in peripheral blood in relation to physical activity and television viewing time., Methods: DNA methylation was measured using the Illumina Infinium HumanMethylation450K BeadChip array in blood samples collected at baseline (N = 5513) and follow-up (N = 1249) from participants in the Melbourne Collaborative Cohort Study. At baseline, times per week of leisure-time physical activity were self-reported. At follow-up, the International Physical Activity Questionnaire was used to assess MET-hours per week of total and leisure-time physical activity and hours per day of television viewing time. Linear mixed models were used to assess associations between physical activity and television viewing measures and DNA methylation at individual CpG sites, adjusted for potential confounders and batch effects., Results: At follow-up, total physical activity was associated with DNA methylation at cg10266336 (P = 6.0 × 10), annotated to the SAA2 gene. Weaker evidence of associations (P < 1.0 × 10) were observed for an additional 14 CpG sites with total physical activity, for 7 CpG sites with leisure-time physical activity, and for 9 CpG sites with television viewing time. Changes in leisure-time physical activity between baseline and follow-up were associated with methylation changes (P < 0.05) at four of the seven CpG sites with weaker evidence of cross-sectional associations with leisure-time physical activity., Conclusion: Physical activity and television viewing may be associated with blood DNA methylation, a potential pathway to chronic disease development. Further research using accelerometer data and larger sample sizes is warranted.

Background: Several studies have reported DNA methylation in blood to be associated with body mass index (BMI), but few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to appraise the evidence for causality., Methods: The methylation profile of DNA from peripheral blood was measured for 479 Australian women from 130 twin families. Linear regression was used to estimate the associations of DNA methylation at ~410,000 cytosine-guanine dinucleotides (CpGs), and of the average DNA methylation at ~20,000 genes, with current BMI, BMI at age 18-21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation., Results: At a 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18-21 years and BMI change, respectively. The average DNA methylation of the BHLHE40 and SOCS3 loci was associated with current BMI, and of the PHGDH locus with BMI change. From the ICE FALCON analyses with BMI as the predictor and DNA methylation as the outcome, a woman's DNA methylation level was associated with her co-twin's BMI, and the association disappeared after conditioning on her own BMI, consistent with BMI causing DNA methylation. To the contrary, using DNA methylation as the predictor and BMI as the outcome, a woman's BMI was not associated with her co-twin's DNA methylation level, consistent with DNA methylation not causing BMI., Conclusion: For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18-21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

Dietary intakes of B vitamins and other components involved in one-carbon metabolism, which is necessary for DNA replication, DNA repair, and regulation of gene expression, may be associated with carcinogenesis. We investigated associations between intakes of 11 nutrients (thiamine, riboflavin, niacin, pantothenic acid, vitamin B6, biotin, folate, vitamin B12, methionine, choline, and betaine) and gastric cancer risk. A total of 159 incident gastric cancer cases were identified from the Melbourne Collaborative Cohort Study (N = 41,513) and matched with 159 controls on year of birth, sex, and country of birth using incidence density sampling. Dietary intakes of nutrients were estimated at baseline (1990-1994) using a 121-item food frequency questionnaire. Odds ratios (ORs) and 95% confidence intervals were estimated using conditional logistic regression models adjusting for Helicobacter pylori infection, and other potential confounders. We observed a positive association between intake of niacin and overall gastric cancer risk (OR = 1.33, 95%CI: 1.01-1.75 per SD increment). For thiamine, heterogeneity by subtype (cardia and non-cardia) was found (P het  = 0.05), with weak evidence of an inverse association with cardia cancer risk. Our results do not support increasing intakes of B vitamins or other nutrients involved in one-carbon metabolism to reduce gastric cancer risk in a well-nourished population.

Breast cancers arising in women carrying a germline mutation in BRCA1 are typically high-grade, early-onset and have distinct morphological features (BRCA1-like). However, the majority of early-onset breast cancers of this morphological type are not associated with germline BRCA1 mutations or constitutional BRCA1 promoter methylation. We aimed to assess DNA methylation across the genome for associations with the "BRCA1-like" morphology. Genome-wide methylation in blood-derived DNA was measured using the Infinium HumanMethylation450K BeadChip assay for women under the age of 40 years participating in the Australian Breast Cancer Family Study (ABCFS) diagnosed with: i) BRCA1-like breast cancer (n = 30); and ii) breast cancer without BRCA1-like morphological features (non BRCA1-like; n = 30), and age-matched unaffected women (controls; n = 30). Corresponding tumour-derived DNA from 43 of the affected women was also assessed. Methylation of blood-derived DNA was found to be elevated across 17 consecutive marks in the BRCA1 promoter region and decreased at several other genomic regions (including TWIST2 and CTBP1) for 7 women (23%) diagnosed with BRCA1-like breast cancer compared with women in the other groups. Corresponding tumour-derived DNA available from 5 of these 7 women had elevated methylation within the BRCA1 and SPHK2 promoter region and decreased methylation within the ADAP1, IGF2BP3 and SPATA13 promoter region when compared with the other breast tumours. These methylation marks could be biomarkers of risk for BRCA1-like breast cancer, and could be responsible in part for their distinctive morphological features and biology. As such, they may assist with prevention and targeted therapies for this cancer subtype., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk., Methods: We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline., Results: The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk., Conclusions: The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.

Background: Folate and other one-carbon metabolism nutrients are essential to enable DNA methylation to occur, but the extent to which their dietary intake influences methylation in adulthood is unclear., Objective: We assessed associations between dietary intake of these nutrients and DNA methylation in peripheral blood, overall and at specific genomic locations., Design: We conducted a cross-sectional study using baseline data and samples from 5186 adult participants in the Melbourne Collaborative Cohort Study (MCCS). Nutrient intake was estimated from a food-frequency questionnaire. DNA methylation was measured by using the Illumina Infinium HumanMethylation450 BeadChip array (HM450K). We assessed associations of intakes of folate, riboflavin, vitamins B-6 and B-12, methionine, choline, and betaine with methylation at individual cytosine-guanine dinucleotides (CpGs), and with median (genome-wide) methylation across all CpGs, CpGs in gene bodies, and CpGs in gene promoters. We also assessed associations with methylation at long interspersed nuclear element 1 (LINE-1), satellite 2 (Sat2), and Arthrobacter luteus restriction endonuclease (Alu) repetitive elements for a subset of participants. We used linear mixed regression, adjusting for age, sex, country of birth, smoking, energy intake from food, alcohol intake, Mediterranean diet score, and batch effects to assess log-linear associations with dietary intake of each nutrient. In secondary analyses, we assessed associations with low or high intakes defined by extreme quintiles., Results: No evidence of log-linear association was observed at P < 10-7 between the intake of one-carbon metabolism nutrients and methylation at individual CpGs. Low intake of riboflavin was associated with higher methylation at CpG cg21230392 in the first exon of PROM1 (P = 5.0 × 10-8). No consistent evidence of association was observed with genome-wide or repetitive element measures of methylation., Conclusion: Our findings suggest that dietary intake of one-carbon metabolism nutrients in adulthood, as measured by a food-frequency questionnaire, has little association with blood DNA methylation. An association with low intake of riboflavin requires replication in independent cohorts. This study was registered at http://www.clinicaltrials.gov as NCT03227003.

Background: Smoking has been reported to be associated with peripheral blood DNA methylation, but the causal aspects of the association have rarely been investigated. We aimed to investigate the association and underlying causation between smoking and blood methylation., Methods: The methylation profile of DNA from the peripheral blood, collected as dried blood spots stored on Guthrie cards, was measured for 479 Australian women including 66 monozygotic twin pairs, 66 dizygotic twin pairs, and 215 sisters of twins from 130 twin families using the Infinium HumanMethylation450K BeadChip array. Linear regression was used to estimate associations between methylation at ~ 410,000 cytosine-guanine dinucleotides (CpGs) and smoking status. A regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess putative causation., Results: At a 5% false discovery rate, 39 CpGs located at 27 loci, including previously reported AHRR , F2RL3 , 2q37.1 and 6p21.33 , were found to be differentially methylated across never, former and current smokers. For all 39 CpG sites, current smokers had the lowest methylation level. Our study provides the first replication for two previously reported CpG sites, cg06226150 ( SLC2A4RG ) and cg21733098 ( 12q24.32 ). From the ICE FALCON analysis with smoking status as the predictor and methylation score as the outcome, a woman's methylation score was associated with her co-twin's smoking status, and the association attenuated towards the null conditioning on her own smoking status, consistent with smoking status causing changes in methylation. To the contrary, using methylation score as the predictor and smoking status as the outcome, a woman's smoking status was not associated with her co-twin's methylation score, consistent with changes in methylation not causing smoking status., Conclusions: For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with smoking. Our study suggests that smoking has a causal effect on peripheral blood DNA methylation, but not vice versa., Competing Interests: The study was approved by the Human Research Ethics Committee of the University of Melbourne. All participants provided written informed consent.Not applicable.The authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

We asked if twin birth influences the DNA methylation of subsequent siblings. We measured whole blood methylation using the HumanMethylation450 array for siblings from two twin and family studies in Australia and Korea. We compared the means and correlations in methylation between pairs of siblings born before a twin birth (BT siblings), born on either side of a twin birth (B/AT pairs) and born after a twin birth (AT siblings). For the genome-wide average DNA methylation, the correlation for AT pairs (r AT ) was larger than the correlation for BT pairs (r BT ) in both studies, and from the meta-analysis, r AT  = 0.46 (95% CI: 0.26, 0.63) and r BT  = -0.003 (95% CI: -0.30, 0.29) (P = 0.02). B/AT pairs were not correlated (from the meta-analysis r BAT  = 0.08; 95% CI: -0.31, 0.45). Similar results were found for the average methylation of several genomic regions, e.g., CpG shelf and gene body. BT and AT pairs were differentially correlated in methylation for 15 probes (all P < 10 -7 ), and the top 152 differentially correlated probes (at P < 10 -4 ) were enriched in cell signalling and breast cancer regulation pathways. Our observations are consistent with a twin birth changing the intrauterine environment such that siblings both born after a twin birth are correlated in DNA methylation.

Mammographic density (MD) is an intermediate phenotype for breast cancer. Previous studies have identified genetic variants associated with MD; however, much of the genetic contribution to MD is unexplained. We conducted a two-stage genome-wide association analysis among the participants in the "Determinants of Density in Mammographies in Spain" study, together with a replication analysis in women from the Australian MD Twins and Sisters Study. Our discovery set covered a total of 3,351 Caucasian women aged 45 to 68 years, recruited from Spanish breast cancer screening centres. MD was blindly assessed by a single reader using Boyd's scale. A two-stage approach was employed, including a feature selection phase exploring 575,374 SNPs in 239 pairs of women with extreme phenotypes and a verification stage for the 183 selected SNPs in the remaining sample (2,873 women). Replication was conducted in 1,786 women aged 40 to 70 years old recruited via the Australian Twin Registry, where MD were measured using Cumulus-3.0, assessing 14 SNPs with a p value <0.10 in stage 2. Finally, two genetic variants in high linkage disequilibrium with our best hit were studied using the whole Spanish sample. Evidence of association with MD was found for variant rs11205277 (OR = 0.74; 95% CI = 0.67-0.81; p = 1.33 × 10(-10) ). In replication analysis, only a marginal association between this SNP and absolute dense area was found. There were also evidence of association between MD and SNPs in high linkage disequilibrium with rs11205277, rs11205303 in gene MTMR11 (OR = 0.73; 95% CI = 0.66-0.80; p = 2.64 × 10(-11) ) and rs67807996 in gene OTUD7B (OR = 0.72; 95% CI = 0.66-0.80; p = 2.03 × 10(-11)). Our findings provide additional evidence on common genetic variations that may contribute to MD., (© 2014 UICC.)

It has been shown that, for women aged 50 years or older, the discriminatory accuracy of the Breast Cancer Risk Prediction Tool (BCRAT) can be modestly improved by the inclusion of information on common single nucleotide polymorphisms (SNPs) that are associated with increased breast cancer risk. We aimed to determine whether a similar improvement is seen for earlier onset disease. We used the Australian Breast Cancer Family Registry to study a population-based sample of 962 cases aged 35-59 years, and 463 controls frequency matched for age and for whom genotyping data was available. Overall, the inclusion of data on seven SNPs improved the area under the receiver operating characteristic curve (AUC) from 0.58 (95 % confidence interval [CI] 0.55-0.61) for BCRAT alone to 0.61 (95 % CI 0.58-0.64) for BCRAT and SNP data combined (p < 0.001). For women aged 35-39 years at interview, the corresponding improvement in AUC was from 0.61 (95 % CI 0.56-0.66) to 0.65 (95 % CI 0.60-0.70; p = 0.03), while for women aged 40-49 years at diagnosis, the AUC improved from 0.61 (95 % CI 0.55-0.66) to 0.63 (95 % CI 0.57-0.69; p = 0.04). Using previously used classifications of low, intermediate and high risk, 2.1 % of cases and none of the controls aged 35-39 years, and 10.9 % of cases and 4.0 % of controls aged 40-49 years were classified into a higher risk group. Including information on seven SNPs associated with breast cancer risk, improves the discriminatory accuracy of BCRAT for women aged 35-39 years and 40-49 years. Given, the low absolute risk for women in these age groups, only a small proportion are reclassified into a higher category for predicted 5-year risk of breast cancer.

The HOXB13 missense mutation G84E (rs138213197) is associated with increased risk of prostate cancer, but the current estimate of increased risk has a wide confidence interval (width of 95% confidence interval (CI) >200-fold) so the point estimate of 20-fold increased risk could be misleading. Population-based family studies can be more informative for estimating risks for rare variants, therefore, we screened for mutations in an Australian population-based series of early-onset prostate cancer cases (probands). We found that 19 of 1,384 (1.4%) probands carried the missense mutation, and of these, six (32%) had a family history of prostate cancer. We tested the 22 relatives of carriers diagnosed from 1998 to 2008 for whom we had a DNA sample, and found seven more carriers and one obligate carrier. The age-specific incidence for carriers was estimated to be, on average, 16.4 (95% CI 2.5-107.2) times that for the population over the time frame when the relatives were at risk prior to baseline. We then estimated the age and birth year- specific cumulative risk of prostate cancer (penetrance) for carriers. For example, the penetrance for an unaffected male carrier born in 1950 was 19% (95% CI 5-46%) at age 60 years, 44% (95% CI 18-74%) at age 70 years and 60% (95% CI 30-85%) at age 80 years. Our study has provided a population-based estimate of the average risk of prostate cancer for HOXB13 missense mutation G84E carriers that can be used to guide clinical practice and research. This study has also shown that the majority of hereditary prostate cancers due to the HOXB13 missense mutation are 'sporadic' in the sense that unselected cases with the missense mutation do not typically report having a family history of prostate cancer.

Introduction: We hypothesised that breast cancer risk for relatives of women with early-onset breast cancer could be predicted by tumour morphological features., Methods: We studied female first-degree relatives of a population-based sample of 452 index cases with a first primary invasive breast cancer diagnosed before the age of 40 years. For the index cases, a standardised tumour morphology review had been conducted for all; estrogen (ER) and progesterone receptor (PR) status was available for 401 (89%), and 77 (17%) had a high-risk mutation in a breast cancer susceptibility gene or methylation of the BRCA1 promoter region in peripheral blood DNA. We calculated standardised incidence ratios (SIR) by comparing the number of mothers and sisters with breast cancer with the number expected based on Australian incidence rates specific for age and year of birth., Results: Using Cox proportional hazards modelling, absence of extensive sclerosis, extensive intraductal carcinoma, absence of acinar and glandular growth patterns, and the presence of trabecular and lobular growth patterns were independent predictors with between a 1.8- and 3.1-fold increased risk for relatives (all P <0.02). Excluding index cases with known genetic predisposition or BRCA1 promoter methylation, absence of extensive sclerosis, circumscribed growth, extensive intraductal carcinoma and lobular growth pattern were independent predictors with between a 2.0- and 3.3-fold increased risk for relatives (all P <0.02). Relatives of the 128 (34%) index cases with none of these four features were at population risk (SIR = 1.03, 95% CI = 0.57 to 1.85) while relatives of the 37 (10%) index cases with two or more features were at high risk (SIR = 5.18, 95% CI = 3.22 to 8.33)., Conclusions: This wide variation in risks for relatives based on tumour characteristics could be of clinical value, help discover new breast cancer susceptibility genes and be an advance on the current clinical practice of using ER and PR as pathology-based predictors of familial and possibly genetic risks.

Background: How body size influences risk of molecular subtypes of colorectal cancer (CRC) is unclear. We investigated whether measures of anthropometry differentially influence risk of tumours according to BRAF c.1799T>A p.V600E mutation (BRAF) and microsatellite instability (MSI) status., Methods: Data from The Netherlands Cohort Study (n = 120,852) and Melbourne Collaborative Cohort Study (n = 40,514) were pooled and included 734 and 717 colorectal cancer cases from each study, respectively. Hazard ratios (HRs) and 95% confidence intervals (CIs) for body mass index (BMI), waist measurement and height were calculated and compared for subtypes defined by BRAF mutation and MSI status, measured from archival tissue., Results: Results were consistent between studies. When pooled, BMI modelled in 5 kg/m(2) increments was positively associated with BRAF wild-type (HR: 1.16, 95% CI: 1.08-1.26) and MS-stable tumours (HR: 1.15, 95% CI: 1.06-1.24). Waist measurement was also associated with BRAF wild-type (highest vs lowest quartile, HR: 1.59, 95% CI: 1.33-1.90) and MS-stable tumours (highest vs lowest quartile HR: 1.68, 95% CI: 1.31-2.15). The HRs for BRAF mutation tumours and MSI tumours were smaller and non-significant, but differences between the HRs by tumour subtypes were not significant. Height, modelled per 5-cm increase, was positively associated with BRAF wild-type and BRAF mutation tumours, but the HR was greater for tumours with a BRAF mutation than BRAF wild-type (HR: 1.23, 95% CI: 1.11-1.37, P(heterogeneity) = 0.03). Similar associations were observed with respect to height and MSI tumours (HR: 1.26, 95% CI: 1.13-1.40, P(heterogeneity) = 0.02)., Conclusions: Generally, overweight increases the risk of CRC. Taller individuals have an increased risk of developing a tumour with a BRAF mutation or MSI.

Purpose: To compare breast cancer prognosis in BRCA1 and BRCA2 mutation carriers with that in patients with sporadic disease., Patients and Methods: An international population-based cohort study was conducted in Canada, the United States, and Australia of 3,220 women with incident breast cancer diagnosed between 1995 and 2000 and observed prospectively. Ninety-three had BRCA1 mutations; 71, BRCA2 mutations; one, both mutations; 1,550, sporadic breast cancer; and 1,505, familial breast cancer (without known BRCA1 or BRCA2 mutation). Distant recurrence and death were analyzed., Results: Mean age at diagnosis was 45.3 years; mean follow-up was 7.9 years. Risks of distant recurrence and death did not differ significantly between BRCA1 mutation carriers and those with sporadic disease in univariable and multivariable analyses. Risk of distant recurrence was higher for BRCA2 mutation carriers compared with those with sporadic disease in univariable analysis (hazard ratio [HR], 1.63; 95% CI, 1.02 to 2.60; P = .04). Risk of death was also higher in BRCA2 carriers in univariable analysis (HR, 1.81; 95% CI, 1.15 to 2.86; P = .01). After adjustment for age, tumor stage and grade, nodal status, hormone receptors, and year of diagnosis, no differences were observed for distant recurrence (HR, 1.00; 95% CI, 0.62 to 1.61; P = 1.00) or death (HR, 1.12; 95% CI, 0.70 to 1.79; P = .64)., Conclusion: Outcomes of BRCA1 mutation carriers were similar to those of patients with sporadic breast cancer. Worse outcomes in BRCA2 mutation carriers in univariable analysis seem to reflect the presence of more adverse tumor characteristics in these carriers. Similar outcomes were identified in BRCA2 carriers and those with sporadic disease in multivariable analyses.

We are interested in the characterisation of previously undescribed contributions to the heritable component of human cancers. To this end, we applied whole-exome capture, followed by massively parallel sequence analysis to the germline DNA of two greater than third-degree affected relatives from four multiple-case, early-onset breast cancer families. Prior testing for variants in known breast cancer susceptibility, genes in these families did not identify causal mutations. We detected and confirmed two different variants in the DNA damage repair gene FAN1 (R377W, chr15:31197995 C>T and R507H, chr15:31202961 G>A [hg19]) which were not present in dbSNP131. In one family, FAN1 R377W, predicted to be damaging by SIFT and PolyPhen2, was present in all six tested members with cancer (five with breast cancer, one with malignant melanoma). In another family, FAN1 R507H, predicted to be damaging by SIFT but benign by PolyPhen2, was observed in one of two tested members with breast cancer. We genotyped FAN1 R377W and R507H variants across 1417 population-based cases and 1490 unaffected population-based controls (frequency-matched for age). These variants were rare in the Australian population (minor allele frequencies of 0.0064 and 0.010, respectively) and were not associated with breast cancer risk (OR = 0.80, 95% CI[0.39-1.61], P = 0.50 and OR = 0.74, 95% CI[0.41-1.29], P = 0.26, respectively). Analysis of breast cancer risks for relatives of case and control carriers did not find evidence of an increased risk. Despite the biological role of FAN1, the plausibility of its role as a breast cancer predisposition gene, and the possible deleterious nature of the identified variants, these two variants do not appear to be causal for breast cancer. Future studies to extend the genetic analysis of FAN1 will further explore its possible role as a breast cancer susceptibility gene.

Cancer risks for a person who has inherited a MUTYH mutation from only one parent (monoallelic mutation carrier) are uncertain. Using the Colon Cancer Family Registry and Newfoundland Familial Colon Cancer Registry, we identified 2,179 first- and second-degree relatives of 144 incident colorectal cancer (CRC) cases who were monoallelic or biallelic mutation carriers ascertained by sampling population complete cancer registries in the United States, Canada and Australia. Using Cox regression weighted to adjust for sampling on family history, we estimated that the country-, age- and sex-specific standardized incidence ratios (SIRs) for monoallelic mutation carriers, compared to the general population, were: 2.04 (95% confidence interval, CI 1.56-2.70; p < 0.001) for CRC, 3.24 (95%CI 2.18-4.98; p < 0.001) for gastric cancer, 3.09 (95%CI 1.07-12.25; p = 0.07) for liver cancer and 2.33 (95%CI 1.18-5.08; p = 0.02) for endometrial cancer. Age-specific cumulative risks to age 70 years, estimated using the SIRs and US population incidences, were: for CRC, 6% (95%CI 5-8%) for men and 4% (95%CI 3-6%) for women; for gastric cancer, 2% (95%CI 1-3%) for men and 0.7% (95%CI 0.5-1%) for women; for liver cancer, 1% (95%CI 0.3-3%) for men and 0.3% (95%CI 0.1-1%) for women and for endometrial cancer, 4% (95%CI 2-8%). There was no evidence of increased risks for cancers of the brain, pancreas, kidney, lung, breast or prostate. Monoallelic MUTYH mutation carriers with a family history of CRC, such as those identified from screening multiple-case CRC families, are at increased risk of colorectal, gastric, endometrial and possibly liver cancers., (Copyright © 2010 UICC.)

Genetic diseases associated with dynamic mutations in microsatellite DNA often display parent-of-origin effects (POEs) in which the risk of disease depends on the sex of the parent from whom the disease allele was inherited. Carriers of germline mutations in mismatch repair (MMR) genes have high risks of colorectal carcinoma (CRC). We investigated whether these risks depend on the parent-of-origin of the mutation. We studied 422 subjects, including 89 MMR gene mutation carriers, from 17 population-based families who were each recruited via a CRC case diagnosed before age 45 years and found to carry a MMR gene mutation. The POE hazard ratio (HR(POE)), defined to be the CRC incidence for carriers with maternally derived mutations divided by the corresponding paternal incidence, was estimated using a novel application of modified segregation analysis. HR(POE) (95% confidence interval) was estimated to be 3.2 (1.1-9.8) for males (P = 0.03) and 0.8 (0.2-2.8) for females (P = 0.5) and the corresponding cumulative risks to age 80 years were 88% (54%-100%) for male carriers with maternally derived mutations and 38-48% for all other carriers. If confirmed by larger studies, these results will have important implications for the etiology of CRC and for the clinical management of MMR gene mutation carriers., (© 2011 Wiley-Liss, Inc.)