Controlled versus free breathing for multiple-breath nitrogen washout in asthma.

The lack of comparability in indices of ventilation heterogeneity between free- and controlled-breathing MBNW protocols is confirmed in asthma https://bit.ly/3lmri4A

Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies

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

Fgfr3 Is a Transcriptional Target of Ap2δ and Ash2l-Containing Histone Methyltransferase Complexes

Polycomb (PcG) and trithorax (trxG) proteins play important roles in establishing lineage-specific genetic programs through induction of chromatin modifications that lead to gene silencing or activation. Previously, we described an association between the MLL/SET1 complexes and a highly restricted, gene-specific DNA-binding protein Ap2δ that is required for recruitment of the MLL/SET1 complex to target Hoxc8 specifically. Here, we reduced levels of Ap2δ and Ash2l in the neuroblastoma cell line, Neuro2A, and analyzed their gene expression profiles using whole-genome mouse cDNA microarrays. This analysis yielded 42 genes that are potentially co-regulated by Ap2δ and Ash2l, and we have identified evolutionarily conserved Ap2-binding sites in 20 of them. To determine whether some of these were direct targets of the Ap2δ-Ash2l complex, we analyzed several promoters for the presence of Ap2δ and Ash2l by chromatin immunoprecipitation (ChIP). Among the targets we screened, we identified Fgfr3 as a direct transcriptional target of the Ap2δ-Ash2l complex. Additionally, we found that Ap2δ is necessary for the recruitment of Ash2l-containing complexes to this promoter and that this recruitment leads to trimethylation of lysine 4 of histone H3 (H3K4me3). Thus, we have identified several candidate targets of complexes containing Ap2δ and Ash2l that can be used to further elucidate their roles during development and showed that Fgfr3 is a novel direct target of these complexes

Testing for Gene-Environment Interactions Using a Prospective Family Cohort Design: Body Mass Index in Early and Later Adulthood and Risk of Breast Cancer

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 signifi- cant, 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.The Australian Breast Cancer Family Registry (ABCFR) was supported in Australia by the National Health and Medical Research Council, the New South Wales Cancer Council, the Victorian Health Promotion Foundation, the Victorian Breast Cancer Research Consortium, Cancer Australia, and the National Breast Cancer Foundation. The ABCFR was also supported by the National Cancer Institute, US National Institutes of Health, under Request for Application CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry: the University of Melbourne (Melbourne, Victoria, Australia) (grant U01 CA69638); the Fox Chase Cancer Center (Philadelphia, Pennsylvania) (grant U01 CA69631); the Huntsman Cancer Institute (Salt Lake City, Utah) (grant U01 CA69446); Columbia University (New York, New York) (grant U01 CA69398); the Cancer Prevention Institute of California (Fremont, California) (grant U01 CA69417); and Cancer Care Ontario (Toronto, Ontario, Canada) (grant U01 CA69467). The Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) was supported by a grant from the Australian National Breast Cancer Foundation and previously by the National Health and Medical Research Council, the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and the Cancer Foundation of Western Australia. The Australasian Colorectal Cancer Family Registry (ACCFR) was supported by grant UM1 CA167551 from the National Cancer Institute, US National Institutes of Health, and through cooperative agreements with the members and Principal Investigators of the ACCFR (grants U01 CA074778 and U01/U24 CA097735). A.K.W. is a National Health and Medical Research Council Early Career Fellow. M.A.J. is a National Health and Medical Research Council Senior Research Fellow. K.A.P. is an Australian National Breast Cancer Foundation Fellow

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk

Adult weight change and premenopausal breast cancer risk: A prospective pooled analysis of data from 628,463 women.

Early-adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual-level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18-24 years and other breast cancer risk factors showed that weight gain from ages 18-24 to 35-44 or to 45-54 years was inversely associated with breast cancer overall (e.g., HR per 5 kg to ages 45-54: 0.96, 95% CI: 0.95-0.98) and with oestrogen-receptor(ER)-positive breast cancer (HR per 5 kg to ages 45-54: 0.96, 95% CI: 0.94-0.98). Weight gain from ages 25-34 was inversely associated with ER-positive breast cancer only and weight gain from ages 35-44 was not associated with risk. None of these weight gains were associated with ER-negative breast cancer. Weight loss was not consistently associated with overall or ER-specific risk after adjusting for initial weight. Weight increase from early-adulthood to ages 45-54 years is associated with a reduced premenopausal breast cancer risk independently of early-adulthood weight. Biological explanations are needed to account for these two separate factors

Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach

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

Ovarian cancer risk factors by tumor aggressiveness: an analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n=864), very aggressive (death in 1-<3 years, n=1,390), moderately aggressive (death in 3-<5 years, n=639), and less aggressive (lived 5+ years, n=1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (phet =0.01), family history of ovarian cancer (phet =0.02), body mass index (BMI; phet ≤0.04) and smoking (phet <0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20-<25 kg/m2 , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted