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Current risk prediction models estimate the probability of developing breast cancer over a defined period based on information such as family history, non-genetic breast cancer risk factors, genetic information from high and moderate risk breast cancer susceptibility genes and, over the past several years, polygenic risk scores (PRS) from more than 300 common variants. The inclusion of additional data such as PRS improves risk stratification, but it is anticipated that the inclusion of epigenetic marks could further improve model performance accuracy. Here, we present the case for including information on DNA methylation marks to improve the accuracy of these risk prediction models, and consider how this approach contrasts genetic information, as identifying DNA methylation marks associated with breast cancer risk differs inherently according to the source of DNA, approaches to the measurement of DNA methylation, and the timing of measurement. We highlight several DNA-methylation-specific challenges that should be considered when incorporating information on DNA methylation marks into risk prediction models, using BRCA1, a highly penetrant breast cancer susceptibility gene, as an example. Only after careful consideration of study design and DNA methylation measurement will prospective performance of the incorporation of information regarding DNA methylation marks into risk prediction models be valid. [ABSTRACT FROM AUTHOR]

PALB2 has taken its place with bona fide breast cancer susceptibility genes. It is now well established that women who carry loss-of-function mutations in the PALB2 gene are at similarly elevated breast cancer risks to those who carry mutations in BRCA2. Information about PALB2 is now being used in breast cancer clinical genetics practice and is routinely included in breast cancer predisposition gene panel tests. Tens of thousands of women worldwide have now had genetic tests for PALB2 mutations in the context of breast cancer susceptibility. However, prospective data related to the clinical outcomes of PALB2 mutation carriers is lacking and very little information (beyond mutation penetrance) is available to guide current clinical management for carriers (affected and unaffected by cancer). In addition, clinical classification of the vast array of non-loss-of-function genetic variants identified in PALB2 is in its infancy. These are key areas of current research efforts and are important foundations on which to move information about PALB2 into the precision public health arena. [ABSTRACT FROM AUTHOR]

Background: The distribution of ovarian tumour characteristics differs between germline BRCA1 and BRCA2 pathogenic variant carriers and non-carriers. In this study, we assessed the utility of ovarian tumour characteristics as predictors of BRCA1 and BRCA2 variant pathogenicity, for application using the American College of Medical Genetics and the Association for Molecular Pathology (ACMG/AMP) variant classification system. Methods: Data for 10,373 ovarian cancer cases, including carriers and non-carriers of BRCA1 or BRCA2 pathogenic variants, were collected from unpublished international cohorts and consortia and published studies. Likelihood ratios (LR) were calculated for the association of ovarian cancer histology and other characteristics, with BRCA1 and BRCA2 variant pathogenicity. Estimates were aligned to ACMG/AMP code strengths (supporting, moderate, strong). Results: No histological subtype provided informative ACMG/AMP evidence in favour of BRCA1 and BRCA2 variant pathogenicity. Evidence against variant pathogenicity was estimated for the mucinous and clear cell histologies (supporting) and borderline cases (moderate). Refined associations are provided according to tumour grade, invasion and age at diagnosis. Conclusions: We provide detailed estimates for predicting BRCA1 and BRCA2 variant pathogenicity based on ovarian tumour characteristics. This evidence can be combined with other variant information under the ACMG/AMP classification system, to improve classification and carrier clinical management. [ABSTRACT FROM AUTHOR]

Simple Summary: Studies of genetic predisposition to renal cell carcinoma (RCC) have been highly variable in design and have reported similarly highly variable rates of cases identified as carrying pathogenic variants in cancer susceptibility genes (4–26%). The aim of our study was to conduct a population-based study of genetic predisposition to RCC. We conducted a 21-gene panel sequencing study and identified that 18/1029 participants (1.7%) carried a pathogenic or likely pathogenic (PLP) variant. Genes with PLP variants included BAP1, FH, FLCN, MITF, MSH6, SDHB, TSC1, and VHL. This study provides further evidence that family history alone may not be sufficient for identifying all individuals who are at increased genetic risk of renal cell carcinoma, and further research is urgently needed to understand how to target genetic testing to identify those at high genetic risk of kidney cancer. Renal cell carcinoma (RCC) has been associated with germline pathogenic or likely pathogenic (PLP) variants in recognised cancer susceptibility genes. Studies of RCC using gene panel sequencing have been highly variable in terms of study design, genes included, and reported prevalence of PLP variant carriers (4–26%). Studies that restricted their analysis to established RCC predisposition genes identified variants in 1–6% of cases. This work assessed the prevalence of clinically actionable PLP variants in renal cancer predisposition genes in an Australian population-based sample of RCC cases. Germline DNA from 1029 individuals diagnosed with RCC who were recruited through the Victoria and Queensland cancer registries were screened using a custom amplicon-based panel of 21 genes. Mean age at cancer diagnosis was 60 ± 10 years, and two-thirds (690, 67%) of the participants were men. Eighteen participants (1.7%) were found to carry a PLP variant. Genes with PLP variants included BAP1, FH, FLCN, MITF, MSH6, SDHB, TSC1, and VHL. Most carriers of PLP variants did not report a family history of the disease. Further exploration of the clinical utility of gene panel susceptibility testing for all RCCs is warranted. [ABSTRACT FROM AUTHOR]

Kratz and colleagues ([1]) asked if pathogenic variants (PVs) in adult cancer predisposition genes are associated with the risk of childhood and adolescent cancers. We found that, for PVs in breast cancer susceptibility genes, using older control participants with an age adjustment gave breast cancer risk estimates consistent with those estimated using age-matched control participants ([6]). [Extracted from the article]

Clonal haematopoiesis of indeterminate potential (CHIP) has been associated with many adverse health outcomes. However, further research is required to understand the critical genes and pathways relevant to CHIP subtypes, evaluate how CHIP clones evolve with time, and further advance functional characterisation and therapeutic studies. Large epidemiological studies are well placed to address these questions but often collect saliva rather than blood from participants. Paired saliva- and blood-derived DNA samples from 94 study participants were sequenced using a targeted CHIP-gene panel. The ten genes most frequently identified to carry CHIP-associated variants were analysed. Fourteen unique variants associated with CHIP, ten in DNMT3A, two in TP53 and two in TET2, were identified with a variant allele fraction (VAF) between 0.02 and 0.2 and variant depth ≥ 5 reads. Eleven of these CHIP-associated variants were detected in both the blood- and saliva-derived DNA sample. Three variants were detected in blood with a VAF > 0.02 but fell below this threshold in the paired saliva sample (VAF 0.008—0.013). Saliva-derived DNA is suitable for detecting CHIP-associated variants. Saliva can offer a cost-effective biospecimen that could both advance CHIP research and facilitate clinical translation into settings such as risk prediction, precision prevention, and treatment monitoring. [ABSTRACT FROM AUTHOR]

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 (npaired = 19; AUC = 0.87) and The Cancer Genome Atlas (TCGA; npaired = 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. [ABSTRACT FROM AUTHOR]

Epigenetic age is an emerging marker of health that is highly predictive of disease and mortality risk. There is a lack of evidence on whether lifestyle changes are associated with changes in epigenetic aging. We used data from 1 041 participants in the Melbourne Collaborative Cohort Study with blood DNA methylation measures at baseline (1990–1994, mean age: 57.4 years) and follow-up (2003–2007, mean age: 68.8 years). The Alternative Healthy Eating Index-2010 (AHEI-2010), the Mediterranean Dietary Score, and the Dietary Inflammatory Index were used as measures of diet quality, and weight, waist circumference, and waist-to-hip ratio as measures of body size. Five age-adjusted epigenetic aging measures were considered: GrimAge , PhenoAge , PCGrimAge, PCPhenoAge, and DunedinPACE. Multivariable linear regression models including restricted cubic splines were used to assess the cross-sectional and longitudinal associations of body size and diet quality with epigenetic aging. Associations between weight and epigenetic aging cross-sectionally at both time points were positive and appeared greater for DunedinPACE (per SD : β ~0.24) than for GrimAge and PhenoAge (β ~0.10). The longitudinal associations with weight change were markedly nonlinear (U-shaped) with stable weight being associated with the lowest epigenetic aging at follow-up, except for DunedinPACE , for which only weight gain showed a positive association. We found negative, linear associations for AHEI-2010 both cross-sectionally and longitudinally. Other adiposity measures and dietary scores showed similar results. In middle-aged to older adults, declining diet quality and weight gain may increase epigenetic age, while the association for weight loss may require further investigation. Our study sheds light on the potential of weight management and dietary improvement in slowing aging processes. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate clinicopathological and molecular tumour features associated with intratumoral pks+Escherichia coli (pks+E.coli+), pks+E.coli- (non-E.coli bacteria harbouring the pks island), Enterotoxigenic Bacteroides fragilis (ETBF) and Fusobacterium nucleatum (F. nucleatum). Methods: We screened 1697 tumour-derived DNA samples from the Australasian Colorectal Cancer Family Registry, Melbourne Collaborative Cohort Study and the ANGELS study using targeted PCR. Results: Pks+E.coli+ was associated with male sex (P < 0.01) and APC:c.835-8 A > G somatic mutation (P = 0.03). The association between pks+E.coli+ and APC:c.835-8 A > G was specific to early-onset CRCs (diagnosed<45years, P = 0.02). The APC:c.835-A > G was not associated with pks+E.coli- (P = 0.36). F. nucleatum was associated with DNA mismatch repair deficiency (MMRd), BRAF:c.1799T>A p.V600E mutation, CpG island methylator phenotype, proximal tumour location, and high levels of tumour infiltrating lymphocytes (Ps < 0.01). In the stratified analysis by MMRd subgroups, F. nucleatum was associated with Lynch syndrome, MLH1 methylated and double MMR somatic mutated MMRd subgroups (Ps < 0.01). Conclusion: Intratumoral pks+E.coli+ but not pks+E.coli- are associated with CRCs harbouring the APC:c.835-8 A > G somatic mutation, suggesting that this mutation is specifically related to DNA damage from colibactin-producing E.coli exposures. F. nucleatum was associated with both hereditary and sporadic MMRd subtypes, suggesting the MMRd tumour microenvironment is important for F. nucleatum colonisation irrespective of its cause. [ABSTRACT FROM AUTHOR]

Background The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. Development We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID's building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(r Δ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher's classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors. Application For female breast cancer, VALID quantified how much variance in risk is explained—at different ages—by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors. Conclusion VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk. [ABSTRACT FROM AUTHOR]

Limited evidence exists on the link between inflammation and epigenetic aging. We aimed to (a) assess the cross-sectional and prospective associations of 22 inflammation-related plasma markers and a signature of inflammaging with epigenetic aging and (b) determine whether epigenetic aging and inflammaging are independently associated with mortality. Blood samples from 940 participants in the Melbourne Collaborative Cohort Study collected at baseline (1990–1994) and follow-up (2003–2007) were assayed for DNA methylation and 22 inflammation-related markers, including well-established markers (eg, interleukins and C-reactive protein) and metabolites of the tryptophan–kynurenine pathway. Four measures of epigenetic aging (PhenoAge , GrimAge , DunedinPoAm , and Zhang) and a signature of inflammaging were considered, adjusted for age, and transformed to Z scores. Associations were assessed using linear regression, and mortality hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated using Cox regression. Cross-sectionally, most inflammation-related markers were associated with epigenetic aging measures, although with generally modest effect sizes (regression coefficients per SD ≤ 0.26) and explaining altogether between 1% and 11% of their variation. Prospectively, baseline inflammation-related markers were not, or only weakly, associated with epigenetic aging after 11 years of follow-up. Epigenetic aging and inflammaging were strongly and independently associated with mortality, for example, inflammaging: HR = 1.41, 95% CI = 1.27–1.56, p = 2 × 10−10, which was only slightly attenuated after adjustment for 4 epigenetic aging measures: HR = 1.35, 95% CI = 1.22–1.51, p = 7 × 10−9). Although cross-sectionally associated with epigenetic aging, inflammation-related markers accounted for a modest proportion of its variation. Inflammaging and epigenetic aging are essentially nonoverlapping markers of biological aging and may be used jointly to predict mortality. [ABSTRACT FROM AUTHOR]

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1 , BRCA2 , PALB2 , CHEK2 , ATM , and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20–29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%–5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%–95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%–1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20–29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age. A large population-based family study, with gene-panel sequencing data, investigated the genetic models that explain the residual breast cancer familial aggregation after considering known susceptibility genes. The results may have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age. [ABSTRACT FROM AUTHOR]

This case reports peripheral blood mononuclear cell (PBMC) transcriptomic changes in a pair of male monozygotic pediatric twins with metabolic syndrome (MetS) undertaking assisted weight loss. These 14-year-old boys presented with similar baseline biochemistry and body composition. After a 16-week weight-loss intervention, percent body weight loss was similar (Twin A 12%, and Twin B 13%). MetS resolved in Twin A but Twin B maintained elevated triglycerides after weight loss. Analysis of the PBMC transcriptome before and after weight loss revealed very different changes in gene expression including differences in the direction of expression of genes related to immune cell activation. 48.7% of genes that were downregulated in Twin A were upregulated in Twin B. This case highlights a novel approach to report the influence of chronic low-grade inflammation and metabolic dysfunction on the PBMC transcriptome. It explores whether expression of genes related to immune functions may underlie the differences in response to weight loss or whether transcriptomic alterations in immune cells may precede more traditional biomarkers of chronic pro-inflammation. These monozygotic twins present an example of divergence of phenotypic outcomes despite identical genetic background and similar treatment response. [ABSTRACT FROM AUTHOR]

The practice of clinical genetics in the context of breast cancer predisposition has reached another critical point in its evolution. For the past two decades, genetic testing offered to women attending clinics has been limited to BRCA1 and BRCA2 unless other syndromic indicators have been evident (e.g. PTEN and TP53 for Cowden and Li-Fraumeni syndrome, respectively). Women (and their families) who are concerned about their personal and/or family history of breast and ovarian cancer have enthusiastically engaged with clinical genetics services, anticipating a genetic cause for their cancer predisposition will be identified and to receive clinical guidance for their risk management and treatment options. Genetic testing laboratories have demonstrated similar enthusiasm for transitioning from single gene to gene panel testing that now provide opportunities for the large number of women found not to carry mutations in BRCA1 and BRCA2, enabling them to undergo additional genetic testing. However, these panel tests have limited clinical utility until more is understood about the cancer risks (if any) associated with the genetic variation observed in the genes included on these panels. New data is urgently needed to improve the interpretation of the genetic variation data that is already reported from these panels and to inform the selection of genes included in gene panel tests in the future. To address this issue, large internationally coordinated research studies are required to provide the evidence-base from which clinical genetics for breast cancer susceptibility can be practiced in the era of gene panel testing and oncogenetic practice. Two significant steps associated with this process include i) validating the genes on these panels (and those likely to be added in the future) as bona fide breast cancer predisposition genes and ii) interpreting the variation, on a variant-by-variant basis in terms of their likely "pathogenicity" -- a process commonly referred to as "variant classification" that will enable this new genetic information to be used at an individual level in clinical genetics services. Neither of these fundamental steps have been achieved for the majority of genes included on the panels. We are thus at a critical point for translational research in breast cancer clinical genetics -- how can rare genetic variants be interpreted such that they can be used in clinical genetics services and oncogenetic practice to identify and to inform the management of families that carry these variants? [ABSTRACT FROM AUTHOR]

Simple Summary: Mammogram risk scores, based on the area of a mammogram covered by white or bright areas defined at different levels of pixel brightness, predict breast cancer risk. They are correlated in relatives, and this might be due to genetic factors that cause breast cancer. We found that the known genetic markers associated with breast cancer risk were weakly correlated with the studied mammogram risk scores. Our findings suggest that less than 1% of the variance of the studied mammogram risk scores is explained by the known genetic markers associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of a mammogram could reveal new information about the genetic causes of breast cancer. Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05–0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the "white but not bright area" (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer. [ABSTRACT FROM AUTHOR]

Summary: 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. [ABSTRACT FROM AUTHOR]

Background: Inflammation is a key feature of aging. We aimed to (i) investigate the association of 34 blood markers potentially involved in inflammatory processes with age and mortality and (ii) develop a signature of "inflammaging."Methods: Thirty-four blood markers relating to inflammation, B vitamin status, and the kynurenine pathway were measured in 976 participants in the Melbourne Collaborative Cohort Study at baseline (median age = 59 years) and follow-up (median age = 70 years). Associations with age and mortality were assessed using linear and Cox regression, respectively. A parsimonious signature of inflammaging was developed and its association with mortality was compared with 2 marker scores calculated across all markers associated with age and mortality, respectively.Results: The majority of markers (30/34) were associated with age, with stronger associations observed for neopterin, cystatin C, interleukin (IL)-6, tumor necrosis factor alpha (TNF-α), several markers of the kynurenine pathway and derived indices KTR (kynurenine/tryptophan ratio), PAr index (ratio of 4-pyridoxic acid and the sum of pyridoxal 5'-phosphate and pyridoxal), and HK:XA (3-hydroxykynurenine/xanthurenic acid ratio). Many markers (17/34) showed an association with mortality, in particular IL-6, neopterin, C-reactive protein, quinolinic acid, PAr index, and KTR. The inflammaging signature included 10 markers and was strongly associated with mortality (hazard ratio [HR] per SD = 1.40, 95% CI: 1.24-1.57, p = 2 × 10-8), similar to scores based on all age-associated (HR = 1.38, 95% CI: 1.23-1.55, p = 4 × 10-8) and mortality-associated markers (HR = 1.43, 95% CI: 1.28-1.60, p = 1 × 10-10), respectively. Strong evidence of replication of the inflammaging signature association with mortality was found in the Hordaland Health Study.Conclusion: Our study highlights the key role of the kynurenine pathway and vitamin B6 catabolism in aging, along with other well-established inflammation-related markers. A signature of inflammaging based on 10 markers was strongly associated with mortality. [ABSTRACT FROM AUTHOR]

Simple Summary: Cumulus, Cumulus-percent, Altocumulus, Cirrocumulus, and Cumulus-white are mammogram risk scores (MRSs) that predict a woman's risk of breast cancer based on mammographically dense areas when defined by different levels of brightness. We measured these MRS for 593 monozygotic (MZ) and 326 dizygotic (DZ) female twin pairs and 1592 of their sisters. We estimated how much these MRSs were correlated in relatives (ρ), how much of the differences between women were due to genetic factors (heritability), and how much these MRS explained why breast cancer runs in families. The ρ estimates ranged from: 0.41 to 0.60 for MZ pairs, 0.16 to 0.26 for DZ pairs, and 0.19 to 0.29 sister pairs, respectively. Heritability estimates were 36% to 69%. Genetic factors explain most of why twins and sisters are similar in their MRS, and these genetic factors explain one-quarter to one-half as much breast cancer risk as to the current best genetic risk score. Cumulus, Cumulus-percent, Altocumulus, Cirrocumulus, and Cumulus-white are mammogram risk scores (MRSs) for breast cancer based on mammographic density defined in effect by different levels of pixel brightness and adjusted for age and body mass index. We measured these MRS from digitized film mammograms for 593 monozygotic (MZ) and 326 dizygotic (DZ) female twin pairs and 1592 of their sisters. We estimated the correlations in relatives (r) and the proportion of variance due to genetic factors (heritability) using the software FISHER and predicted the familial risk ratio (FRR) associated with each MRS. The ρ estimates ranged from: 0.41 to 0.60 (standard error [SE] 0.02) for MZ pairs, 0.16 to 0.26 (SE 0.05) for DZ pairs, and 0.19 to 0.29 (SE 0.02) for sister pairs (including pairs of a twin and her non-twin sister), respectively. Heritability estimates were 39% to 69% under the classic twin model and 36% to 56% when allowing for shared non-genetic factors specific to MZ pairs. The FRRs were 1.08 to 1.17. These MRSs are substantially familial, due mostly to genetic factors that explain one-quarter to one-half as much of the familial aggregation of breast cancer that is explained by the current best polygenic risk score. [ABSTRACT FROM AUTHOR]

Massively Parallel Sequencing (MPS) allows sequencing of entire exomes and genomes to now be done at reasonable cost, and its utility for identifying genes responsible for rare Mendelian disorders has been demonstrated. However, for a complex disease, study designs need to accommodate substantial degrees of locus, allelic, and phenotypic heterogeneity, as well as complex relationships between genotype and phenotype. Such considerations include careful selection of samples for sequencing and a well-developed strategy for identifying the few ''true'' disease susceptibility genes from among the many irrelevant genes that will be found to harbor rare variants. To examine these issues we have performed simulation-based analyses in order to compare several strategies for MPS sequencing in complex disease. Factors examined include genetic architecture, sample size, number and relationship of individuals selected for sequencing, and a variety of filters based on variant type, multiple observations of genes and concordance of genetic variants within pedigrees. A two-stage design was assumed where genes from the MPS analysis of high-risk families are evaluated in a secondary screening phase of a larger set of probands with more modest family histories. Designs were evaluated using a cost function that assumes the cost of sequencing the whole exome is 400 times that of sequencing a single candidate gene. Results indicate that while requiring variants to be identified in multiple pedigrees and/or in multiple individuals in the same pedigree are effective strategies for reducing false positives, there is a danger of over-filtering so that most true susceptibility genes are missed. In most cases, sequencing more than two individuals per pedigree results in reduced power without any benefit in terms of reduced overall cost. Further, our results suggest that although no single strategy is optimal, simulations can provide important guidelines for study design. [ABSTRACT FROM AUTHOR]

Background: Chronic inflammation is considered to be implicated in the development of prostate cancer. In this study we are the first to investigate a potential association between variants in an autoimmune related region on chromosome 4q27 and prostate cancer risk. This region harbors two cytokine genes IL-2 and the recently described IL-21. Methods: We genotyped six variants previously associated with autoimmune disease (namely rs13151961, rs13119723, rs17388568, rs3136534, rs6822844 and rs6840978) and one functional IL-2 promoter variant (rs2069762) for possible association with prostate cancer risk using the Australian Risk Factors for Prostate Cancer case-control Study. Results: Overall, our results do not support an association between the seven variants at position 4q27 and prostate cancer risk. Per allele odds ratios (ORs) were not significantly different from 1 (all P-values = 0.06). However, we found suggestive evidence for a significant association between the presence of the rs13119723 variant (located in a protein of unknown function) and men with a family history of prostate cancer in first-degree relatives (P-value for interaction 0.02). The per allele OR associated with this variant was significantly higher than 1 (2.37; 95% C.I. = 1.01-5.57). Conclusions: We suggest that genetic variation within the chromosome 4q27 locus might be associated with prostate cancer susceptibility in men with a family history of the disease. Furthermore, our study alludes to a potential role of unknown protein KIAA1109 in conferring this risk. [ABSTRACT FROM AUTHOR]

Background: The ELAC2 gene has been proposed to be a prostate cancer susceptibility gene and is being referred to as HPC2, in part because three case-control studies suggested that two common polymorphisms (Ser217Leu and Ala541Thr) are associated with risk. However, four subsequent larger studies have not confirmed this association. In five of the seven total studies, subject selection was influenced by prostate-specific antigen (PSA) levels. We examined the association and possible effect of subject selection in a larger study and a meta-analysis.Methods: In a population-based study in Australia, 825 case patients and 732 control subjects were genotyped for the Ser217Leu and Ala541Thr polymorphisms of ELAC2. Odds ratios (ORs) for prostate cancer were estimated by unconditional logistic and polytomous regression. A meta-analysis was conducted combining our data with those from seven published studies. The association of genotype with the logarithm of plasma PSA levels in control subjects was analyzed by linear regression.Results: The ORs for prostate cancer were 0.74 (95% confidence interval [CI] = 0.50 to 1.09) for Leu217 homozygotes and 1.01 (95% CI = 0.68 to 1.50) for Thr541 heterozygotes and homozygotes compared with Ser217 and Ala541 homozygotes, respectively. ORs were not changed by excluding control subjects with elevated PSA levels. Among control subjects, there were no statistically significant associations between genotype frequencies and PSA level for either polymorphism (both P>.4). The meta-analysis gave pooled OR estimates of 1.04 (95% CI = 0.85 to 1.26) for Leu217 homozygotes and 1.18 (OR = 0.98 to 1.42) for Thr541 homozygotes and heterozygotes.Conclusion: There is no evidence that either ELAC2 polymorphism is associated with prostate cancer or PSA level. [ABSTRACT FROM AUTHOR]

If the risk of disease is not the same for all germline mutations in a given gene, or if there are other familial modifiers of risk in carriers, then family-history-based estimates of average risk for detected mutations in that gene will depend on how carriers are sampled. Risk may also depend on the site or type of mutation. We studied 51 families with strong histories of breast cancer who attended Australian family cancer clinics and in which a germline mutation in BRCA1 or BRCA2 had been identified (28 and 23 families, respectively). Breast cancer risk in carriers was estimated under maximum likelihood theory, using information from all family members including those not tested, with adjustment for ascertainment by conditioning on genotype of the proband and family phenotype. The average cumulative risk of breast cancer for mutations in either BRCA1 or BRCA2 was 27% (95% confidence interval 16–43%) to age 50 and 64% (44–83%) to age 70. When grouped, the incidence in carriers was on average 17 (10–30) times that in non-carriers, independent of gene or mutation type (hazard ratios: 11 (4–29) for BRCA1, 23 (12–43) for BRCA2 (P for difference = 0.23); 13 (6–29) for protein-truncating mutations, 30 (9–104) for missense mutations and 30 (10–90) for splice-site mutations). For missense mutations, this was equivalent to a cumulative risk to age 70 of 83% (40–100%) and was due in part, but not totally, to the missense mutations 300 T>G in BRCA1 and 4486 G>T in BRCA2, which were individually found to be associated with high risk (P<0.001). Mutations in the central region of BRCA1 may be associated with a lower risk. The issue of the pathogenicity of specific variants may be addressed analytically providing there are one or more suitably informative families with that mutation. [ABSTRACT FROM AUTHOR]

Background: Having a family history of breast cancer, particularly if it involves early-onset disease, is a risk factor for breast cancer, but little is known about specific causes of this association. Consequently, we studied mothers, sisters, and aunts of an age-stratified sample of 1567 unselected case patients diagnosed with breast cancer before age 60 years, recruited to a population-based, case-controlfamily study, in which case patients, control subjects, and their relatives were administered the same questionnaire. Methods: Extensive BRCA1 and BRCA2 mutation testing was carried out for 788 case patients diagnosed before age 40 years, including manual sequencing of DNA from 72 patients with two or more affected relatives. Standardized morbidity ratios, age-specific cumulative risks, and hazard ratios were calculated for groupings of relatives. Results: Cumulative risks of breast cancer to age 50 years in the sisters, mothers, and aunts of the case patients, respectively, were 6, 3, and 2 times the population risk if the case patient was younger than age 40 years at diagnosis but were considerably lower if the case patient was older at diagnosis. When relatives of the case patients with a BRCA1 or BRCA2 mutation were excluded, these risks fell by, at most, 20%. Sisters and aunts, but not mothers, who had an additional first-degree relative with breast cancer were at increased risk, and the risk was greater when that relative was younger at diagnosis. Hazard ratios were 10.7 (95% confidence interval [CI] = 4.2 to 26.8) for sisters and 4.2 (95% CI = 2.2 to 8.1) for aunts, if the relative was aged 40 years at diagnosis. Fewer than one-third of the excess of breast cancers in relatives of case patients diagnosed before age 40 years that are attributed to familial factors are BRCA1- or BRCA2-related. Conclusion: Mutations in genes other than BRCA1 and BRCA2 may be associated with a high risk of breast cancer, especially in young women. [ABSTRACT FROM AUTHOR]

Mutations in BRCA1 (ref. 1) confer an increased risk of female breast cancer. In a genome-wide scan of linkage disequilibrium (LD), a high level of LD was detected among microsatellite markers flanking BRCA1 (ref. 3), raising the prospect that positive natural selection may have acted on this gene. We have used the predictions of evolutionary genetic theory to investigate this further. Using phylogeny-based maximum likelihood analysis of the BRCA1 sequences from primates and other mammals, we found that the ratios of replacement to silent nucleotide substitutions on the human and chimpanzee lineages were not different from one another (P=-0.8), were different from those of other primate lineages (P=-0.004) and were greater than 1 (P=-0.04). This is consistent with the historic occurrence of positive darwinian selection pressure on the BRCA1 protein in the human and chimpanzee lineages. Analysis of genetic variation in a sample of female Australians of Northern European origin showed evidence for Hardy-Weinberg (HW) disequilibrium at polymorphic sites in BRCA1, consistent with the possibility that natural selection is affecting genotype frequencies in modern Europeans. The clustering of between-species variation in the region of the gene encoding the RAD51-interaction domain of BRCA1 suggests the maintenance of genomic integrity as a possible target of selection. [ABSTRACT FROM AUTHOR]

Background Social media is a relatively new means to recruit research participants. Methods The Australian Breakthrough Cancer (ABC) Study is a prospective cohort study that recruited people aged 40-74 years over 2014-2018. A range of recruitment methods, including 'traditional' (e.g. print media, electoral roll, word of mouth) and newer methods (i.e. social media, particularly Facebook) were used. Here we describe and compare these methods of recruitment. Results 52,614 (66%) of ABC Study registrants indicated they had heard about the study via Facebook (36,672 clicked through from an advertisement for the study and 15,942 through users 'sharing' content). Overall, 51,586 (64%) participants (58% female, 42% male) completed baseline study components (online questionnaires and provided a DNA sample). 58% of Facebook registrants completed baseline components, compared with 75% of those recruited by traditional methods. The cost per acquisition using Facebook was $1.66 whereas the cost per acquisition using traditional methods (e.g. via the electoral roll) was up to $30. Facebook recruitment initially attracted more female registrants but targeted advertising dramatically increased the proportion of men. Conclusions Targeted advertising can be used to modify the types of respondents obtained via Facebook. Although the proportion completing baseline study components was lower than for traditional methods of recruitment, the cost per acquisition was cheaper making it feasible to recruit a larger number of participants to obtain the desired study size. Key messages Facebook is a viable and economical source of recruits to large prospective research studies. [ABSTRACT FROM AUTHOR]

Objective: In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE). Results: The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62–0.81), 0.59 (0.47–0.71) and 0.80 (0.73–0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39–0.68), 0.43 (0.31–0.56) and 0.70 (0.59–0.80), respectively. Bland–Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined. [ABSTRACT FROM AUTHOR]

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

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. [ABSTRACT FROM AUTHOR]

Proliferation and survival of prostate cancer cells are driven by the androgen receptor (AR) upon binding to androgen steroid hormones. Manipulating the AR signalling axis is the focus for prostate cancer therapy; thus, it is crucial to understand the role of androgens and AR on extracellular vesicle (EV) secretion and cargo. In this study, we report that plasma‐derived circulating vesicles consisting of CD9 and double‐positive for CD9 and Prostate Specific Membrane Antigen (PSMA) are increased in patients with advanced metastatic prostate cancer, whereas double positives for CD9 and CD63 small extracellular vesicles (S‐EVs) are significantly higher in patients with localised prostate cancer. Androgen manipulation by dihydrotestosterone (DHT) and the clinical antagonist enzalutamide (ENZ) altered the heterogeneity and size of CD9 positive S‐EVs in AR expressing prostate cancer cells, while assessment of the total number and protein cargo of total S‐EVs was unaltered across different treatment groups. Furthermore, hormone stimulation caused strong and specific effects on the small RNA cargo of S‐EVs. A total of 543 small RNAs were found to be regulated by androgens including miR‐19‐3p and miR‐361‐5p. Analysis of S‐EVs heterogeneity and small RNA cargo may provide clinical utility for prostate cancer and be informative to understand further the mechanism of resistance to androgen targeted therapy in castration‐resistant prostate cancer. [ABSTRACT FROM AUTHOR]

Background: Clinical guidelines often use predicted lifetime risk from birth to define criteria for making decisions regarding breast cancer screening rather than thresholds based on absolute 5-year risk from current age.Methods: We used the Prospective Family Cohort Study of 14 657 women without breast cancer at baseline in which, during a median follow-up of 10 years, 482 women were diagnosed with invasive breast cancer. We examined the performances of the International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk models when using the alternative thresholds by comparing predictions based on 5-year risk with those based on lifetime risk from birth and remaining lifetime risk. All statistical tests were 2-sided.Results: Using IBIS, the areas under the receiver-operating characteristic curves were 0.66 (95% confidence interval = 0.63 to 0.68) and 0.56 (95% confidence interval = 0.54 to 0.59) for 5-year and lifetime risks, respectively (Pdiff < .001). For equivalent sensitivities, the 5-year incidence almost always had higher specificities than lifetime risk from birth. For women aged 20-39 years, 5-year risk performed better than lifetime risk from birth. For women aged 40 years or older, receiver-operating characteristic curves were similar for 5-year and lifetime IBIS risk from birth. Classifications based on remaining lifetime risk were inferior to 5-year risk estimates. Results were similar using BOADICEA.Conclusions: Our analysis shows that risk stratification using clinical models will likely be more accurate when based on predicted 5-year risk compared with risks based on predicted lifetime and remaining lifetime, particularly for women aged 20-39 years. [ABSTRACT FROM AUTHOR]

States that the estrogen receptor (ER) protein is believed to play a role in the development and progression of breast cancer. Highlights of a study in which a polymorphism in the ER gene was found to be more common in 34 case studies with a family history of breast cancer than in 154 case subjects with such a history; What was done to determine if this polymorphism is a risk factor for earlyonset breast cancer.

Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. Eleven genes previously reported to be associated with PCa were detected (ATM , BRCA2 , HOXB13 , FAM111A , EMSY, HNF1B, KLK3, MSMB , PCAT1 , PRSS3 , and TERT), as well as an additional 10 novel genes (PABPC1 , QK1 , FAM114A1 , MUC6 , MYCBP2 , RAPGEF4 , RNASEH2B , ULK4 , XPO7 , and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa. Family history of prostate cancer (PCa) is a well-known risk factor. By capitalizing on affected men with a strong family history of disease or with more aggressive disease, we identified 10 novel genes, with eight of these primarily associated with aggressive PCa. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Both colorectal (CRC, 15%) and endometrial cancers (EC, 30%) exhibit microsatellite instability (MSI) due to MLH1 hypermethylation and silencing. The MLH1 promoter polymorphism, rs1800734 is associated with MSI CRC risk, increased methylation and reduced MLH1 expression. In EC samples, we investigated rs1800734 risk using MSI and MSS cases and controls. We found no evidence that rs1800734 or other MLH1 SNPs were associated with the risk of MSI EC. We found the rs1800734 risk allele had no effect on MLH1 methylation or expression in ECs. We propose that MLH1 hypermethylation occurs by different mechanisms in CRC and EC. [ABSTRACT FROM AUTHOR]

Purpose. To characterize the spectrum of BRCA1 and BRCA2 pathogenic germline variants in women from south-west Poland and west Ukraine affected with breast or ovarian cancer. Testing in women at high risk of breast and ovarian cancer in these regions is currently mainly limited to founder mutations. Methods. Unrelated women affected with breast and/or ovarian cancer from Poland (n = 337) and Ukraine (n = 123) were screened by targeted sequencing. Excluded from targeted sequencing were 34 Polish women who had previously been identified as carrying a founder mutation in BRCA1. No prior testing had been conducted among the Ukrainian women. Thus, this study screened BRCA1 and BRCA2 in the germline DNA of 426 women in total. Results. We identified 31 and 18 women as carriers of pathogenic/likely pathogenic (P/LP) genetic variants in BRCA1 and BRCA2, respectively. We observed five BRCA1 and eight BRCA2 P/LP variants (13/337, 3.9%) in the Polish women. Combined with the 34/337 (10.1%) founder variants identified prior to this study, the overall P/LP variant frequency in the Polish women was thus 14% (47/337). Among the Ukrainian women, 16/123 (13%) women were identified as carrying a founder mutation and 20/123 (16.3%) were found to carry non-founder P/LP variants (10 in BRCA1 and 10 in BRCA2). Conclusions. These results indicate that genetic testing in women at high risk of breast and ovarian cancer in Poland and Ukraine should not be limited to founder mutations. Extended testing will enhance risk stratification and management for these women and their families. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Chronological age is a prominent risk factor for many types of cancers including colorectal cancer (CRC). Yet, the risk of CRC varies substantially between individuals, even within the same age group, which may reflect heterogeneity in biological tissue aging between people. Epigenetic clocks based on DNA methylation are a useful measure of the biological aging process with the potential to serve as a biomarker of an individual's susceptibility to age-related diseases such as CRC. Methods: We conducted a genome-wide DNA methylation study on samples of normal colon mucosa (N = 334). Subjects were assigned to three cancer risk groups (low, medium, and high) based on their personal adenoma or cancer history. Using previously established epigenetic clocks (Hannum, Horvath, PhenoAge, and EpiTOC), we estimated the biological age of each sample and assessed for epigenetic age acceleration in the samples by regressing the estimated biological age on the individual's chronological age. We compared the epigenetic age acceleration between different risk groups using a multivariate linear regression model with the adjustment for gender and cell-type fractions for each epigenetic clock. An epigenome-wide association study (EWAS) was performed to identify differential methylation changes associated with CRC risk. Results: Each epigenetic clock was significantly correlated with the chronological age of the subjects, and the Horvath clock exhibited the strongest correlation in all risk groups (r > 0.8, p < 1 × 10−30). The PhenoAge clock (p = 0.0012) revealed epigenetic age deceleration in the high-risk group compared to the low-risk group. Conclusions: Among the four DNA methylation-based measures of biological age, the Horvath clock is the most accurate for estimating the chronological age of individuals. Individuals with a high risk for CRC have epigenetic age deceleration in their normal colons measured by the PhenoAge clock, which may reflect a dysfunctional epigenetic aging process. [ABSTRACT FROM AUTHOR]

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 (Phet = 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. [ABSTRACT FROM AUTHOR]

Background: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance.Methods: In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and participants younger than 50 years at recruitment. We also assessed the effect that limited data input (eg, restriction of the amount of family history and non-genetic information included) had on the models' performance.Findings: After median follow-up of 11·1 years (IQR 6·0-14·4), 619 (4%) of 15 732 women selected from the ProF-SC cohort study were prospectively diagnosed with breast cancer after recruitment, of whom 519 (84%) had histologically confirmed disease. BOADICEA and IBIS were well calibrated in the overall validation cohort, whereas BRCAPRO and BCRAT underpredicted risk (ratio of expected cases to observed cases 1·05 [95% CI 0·97-1·14] for BOADICEA, 1·03 [0·96-1·12] for IBIS, 0·59 [0·55-0·64] for BRCAPRO, and 0·79 [0·73-0·85] for BRCAT). The estimated C-statistics for the complete validation cohort were 0·70 (95% CI 0·68-0·72) for BOADICEA, 0·71 (0·69-0·73) for IBIS, 0·68 (0·65-0·70) for BRCAPRO, and 0·60 (0·58-0·62) for BCRAT. In subgroup analyses by BRCA mutation status, the ratio of expected to observed cases for BRCA-negative women was 1·02 (95% CI 0·93-1·12) for BOADICEA, 1·00 (0·92-1·10) for IBIS, 0·53 (0·49-0·58) for BRCAPRO, and 0·97 (0·89-1·06) for BCRAT. For BRCA-positive participants, BOADICEA and IBIS were well calibrated, but BRCAPRO underpredicted risk (ratio of expected to observed cases 1·17 [95% CI 0·99-1·38] for BOADICEA, 1·14 [0·96-1·35] for IBIS, and 0·80 [0·68-0·95] for BRCAPRO). We noted similar patterns of calibration for women younger than 50 years at recruitment. Finally, BOADICEA and IBIS predictive scores were not appreciably affected by limiting input data to family history for first-degree and second-degree relatives.Interpretation: Our results suggest that models that include multigenerational family history, such as BOADICEA and IBIS, have better ability to predict breast cancer risk, even for women at average or below-average risk of breast cancer. Although BOADICEA and IBIS performed similarly, further improvements in the accuracy of predictions could be possible with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS.Funding: US National Institutes of Health, National Cancer Institute, Breast Cancer Research Foundation, Australian National Health and Medical Research Council, Victorian Health Promotion Foundation, Victorian Breast Cancer Research Consortium, Cancer Australia, National Breast Cancer Foundation, Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and Cancer Foundation of Western Australia. [ABSTRACT FROM AUTHOR]

Supplemental digital content is available in the text. 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 × 10−9), annotated to the SAA2 gene. Weaker evidence of associations (P < 1.0 × 10−5) 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. [ABSTRACT FROM AUTHOR]

There remains debate about whether risk-reducing salpingo-oophorectomy (RRSO), which reduces ovarian cancer risk, also reduces breast cancer risk. We examined the association between RRSO and breast cancer risk using a prospective cohort of 17 917 women unaffected with breast cancer at baseline (7.2% known carriers of BRCA1 or BRCA2 mutations). During a median follow-up of 10.7 years, 1046 women were diagnosed with incident breast cancer. Modeling RRSO as a time-varying exposure, there was no association with breast cancer risk overall (hazard ratio [HR] = 1.04, 95% confidence interval [CI] = 0.87 to 1.24) or by tertiles of predicted absolute risk based on family history (HR = 0.68, 95% CI = 0.32 to 1.47, HR = 0.94, 95% CI = 0.70 to 1.26, and HR = 1.10, 95% CI = 0.88 to 1.39, for lowest, middle, and highest tertile of risk, respectively) or for BRCA1 and BRCA2 mutation carriers when examined separately. There was also no association after accounting for hormone therapy use after RRSO. These findings suggest that RRSO should not be considered efficacious for reducing breast cancer risk. [ABSTRACT FROM AUTHOR]

Abstract 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. Highlights • Some young women have widespread blood derived DNA methylation at the BRCA1 promoter • These women also have reduced blood derived DNA methylation at TWIST2 and CTBP1 • Corresponding tumour DNA from these women have elevated methylation at BRCA1 • These tumours also have other DMR when compared to other breast cancer molecular subtypes. [ABSTRACT FROM AUTHOR]

Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors.Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status.Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests).Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease. [ABSTRACT FROM AUTHOR]

Measures of biological age based on blood DNA methylation, referred to as age acceleration (AA), have been developed. We examined whether AA was associated with health risk factors and overall and cause-specific mortality. At baseline (1990-1994), blood samples were drawn from 2,818 participants in the Melbourne Collaborative Cohort Study (Melbourne, Victoria, Australia). DNA methylation was determined using the Infinium Human Methylation 450 BeadChip array (Illumina Inc., San Diego, California). Mixed-effects models were used to examine the association of AA with health risk factors. Cox models were used to assess the association of AA with mortality. A total of 831 deaths were observed during a median 10.7 years of follow-up. Associations of AA were observed with male sex, Greek nationality (country of birth), smoking, obesity, diabetes, lower education, and meat intake. AA measures were associated with increased mortality, and this was only partly accounted for by known determinants of health (hazard ratios were attenuated by 20%-40%). Weak evidence of heterogeneity in the association was observed by sex (P = 0.06) and cause of death (P = 0.07) but not by other factors. DNA-methylation-based AA measures are associated with several major health risk factors, but these do not fully explain the association between AA and mortality. Future research should investigate what genetic and environmental factors determine AA. [ABSTRACT FROM AUTHOR]

Background: FANCM and RECQL have recently been reported as breast cancer susceptibility genes and it has been suggested that they should be included on gene panel tests for breast cancer predisposition. However, the clinical value of testing for mutations in RECQL and FANCM remains to be determined. In this study, we have characterised the spectrum of FANCM and RECQL mutations in women affected with breast or ovarian cancer from South-West Poland and West Ukraine. Methods: We applied Hi-Plex, an amplicon-based enrichment method for targeted massively parallel sequencing, to screen the coding exons and proximal intron-exon junctions of FANCM and RECQL in germline DNA from unrelated women affected with breast cancer (n = 338) and ovarian cancer (n = 89) from Poland (n = 304) and Ukraine (n = 123). These women were at high-risk of carrying a genetic predisposition to breast and/or ovarian cancer due to a family history and/or early-onset disease. Results: Among 427 women screened, we identified one carrier of the FANCM:c.1972C > T nonsense mutation (0.23%), and two carriers of the frameshift insertion FANCM:c.1491dup (0.47%). None of the variants we observed in RECQL were predicted to be loss-of-function mutations by standard variant effect prediction tools. Conclusions: Our study of the Polish and Ukrainian populations has identified a carrier frequency of truncating mutations in FANCM consistent with previous reports. Although initial reports suggesting that mutations in RECQL could be associated with increased breast cancer risk included women from Poland and identified the RECQL:c.1667_1667 + 3delAGTA mutation in 0.23-0.35% of breast cancer cases, we did not observe any carriers in our study cohort. Continued screening, both in research and diagnostic settings, will enable the accumulation of data that is needed to establish the clinical utility of including RECQL and FANCM on gene panel tests. [ABSTRACT FROM AUTHOR]

Objective: The study aimed to investigate the suitability of DNA extracted from saliva for high throughput molecular genotyping and DNA methylation platforms by comparing its performance with that of DNA extracted from blood. The genome-wide methylation profile, using the Infinium HumanMethylation450 Beadchip array ® (Illumina, San Diego, CA), was measured for 20 DNA samples. Common genetic variation was measured, using the Infinium Human-Core Beadchip ® (Illumina, San Diego, CA) for 4 samples (matching samples from 2 people). Results: DNA from blood and saliva returned genotyping call rates and reproducibility frequencies of > 99%. Highquality DNA methylation data was obtained from both saliva and blood DNA, with average detection p-values for each sample ranging from 0.001 to 0.006. Slightly higher global DNA methylation levels were observed in whole blood DNA than saliva DNA. Correlations between individuals for each sample type were generally greater than correlations between two sample types from the same individual (Pearson's correlation, r = 0.9696 in 10 pairs of matched blood and saliva derived DNA, r = 0.9702 between saliva samples, and r = 0.9769 between blood derived DNA). Saliva yields DNA of sufficient quantity and quality to compare favourably with blood as a source of DNA for genetic and epigenetic research purposes. [ABSTRACT FROM AUTHOR]