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Background Genome‐wide association studies (GWAS) have made little progress in identifying variants linked to depression. We hypothesized that examining depressive symptoms and considering gene–environment interaction (GxE) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome‐wide by environment interaction study (GWEIS) of depressive symptoms. Methods Using data from the SHARe cohort of the Women's Health Initiative, comprising African Americans (n = 7,179) and Hispanics/Latinas (n = 3,138), we examined genetic main effects and GxE with stressful life events and social support. We also conducted a heritability analysis using genome‐wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. Results No SNPs achieved genome‐wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20 kb from GPR139, P = 5.75 × 10−8) and rs75407252 (intronic to CACNA2D3, P = 6.99 × 10−7). In Hispanics/Latinas, the top signals were rs2532087 (located 27 kb from CD38, P = 2.44 × 10−7) and rs4542757 (intronic to DCC, P = 7.31 × 10−7). In the GEWIS with stressful life events, one interaction signal was genome‐wide significant in African Americans (rs4652467; P = 4.10 × 10−10; located 14 kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG = 0.95), suggesting that common variation underlying self‐reported depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Conclusions Our results underscore the need for larger samples, more GEWIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities.

Background Mechanisms underlying the adiposity–cancer relationship are incompletely understood. We quantified the mediating roles of C‐reactive protein (CRP), leptin, fasting insulin, and estradiol in the effect of adiposity on estrogen receptor (ER)‐positive breast, endometrial, and colorectal cancer risk in postmenopausal women. Methods We used a case–cohort study within the Women's Health Initiative Observational Study, analyzed as a cumulative sampling case–control study. The study included 188 breast cancer cases, 98 endometrial cancer cases, 193 colorectal cancer cases, and 285 controls. Interventional indirect and direct effects on the risk ratio (RR) scale were estimated using causal mediation analysis. Results For breast cancer, the total effect RR for BMI ≥30 versus ≥18.5–<25 kg/m2 was 1.87 (95%CI,1.11–3.13). The indirect effect RRs were 1.38 (0.79–2.33) through leptin and CRP, 1.58 (1.17–2.43) through insulin, and 1.11 (0.98–1.30) through estradiol. The direct effect RR was 0.82 (0.39–1.68). For endometrial cancer, the total effect RR was 2.12 (1.12–4.00). The indirect effect RRs were 1.72 (0.85–3.98) through leptin and CRP, 1.42 (0.96–2.26) through insulin, and 1.24 (1.03–1.65) through estradiol. The direct effect RR was 0.70 (0.23–2.04). For colorectal cancer, the total effect RR was 1.70 (1.03–2.79). The indirect effect RRs were 1.04 (0.61–1.72) through leptin and CRP, 1.36 (1.00–1.88) through insulin, and 1.02 (0.88–1.17) through estradiol. The direct effect RR was 1.16 (0.58–2.43). Conclusion Leptin, CRP, fasting insulin, and estradiol appear to mediate the effect of high BMI on cancer risk to different extents, with likely varying degrees of importance between cancers. These insights might be important in developing interventions to modify obesity‐associated cancer risk in postmenopausal women.

Introduction Blood metabolomics‐based biomarkers may be useful to predict measures of neurocognitive aging. Methods We tested the association between 707 blood metabolites measured in 1451 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), with mild cognitive impairment (MCI) and global cognitive change assessed 7 years later. We further used Lasso penalized regression to construct a metabolomics risk score (MRS) that predicts MCI, potentially identifying a different set of metabolites than those discovered in individual‐metabolite analysis. Results We identified 20 metabolites predicting prevalent MCI and/or global cognitive change. Six of them were novel and 14 were previously reported as associated with neurocognitive aging outcomes. The MCI MRS comprised 61 metabolites and improved prediction accuracy from 84% (minimally adjusted model) to 89% in the entire dataset and from 75% to 87% among apolipoprotein E ε4 carriers. Discussion Blood metabolites may serve as biomarkers identifying individuals at risk for MCI among US Hispanics/Latinos.

Background Most studies demonstrating an association between excess adiposity and postmenopausal breast cancer have used anthropometric measures, particularly body mass index (BMI). However, more direct body fat measures may more accurately determine the relationship between body fat distribution and breast cancer risk. Methods Cox proportional hazards regression models were created to examine the associations of dual‐energy x‐ray absorptiometry (DXA) body fat measures (at baseline and during follow‐up) with breast cancer risk among 10 931 postmenopausal women from the Women's Health Initiative cohort. A total of 639 incident invasive breast cancer cases (including 484 estrogen receptor positive (ER+) cases) were ascertained after a median follow‐up of 15.0 years. Results Excess whole body fat mass and trunk fat mass were positively associated with risk invasive breast cancer risk. These associations persisted even after additional adjustment for standard anthropometric measures. In time‐dependent analyses, we observed that both whole body fat mass and trunk fat mass, in the highest versus lowest category, were associated with a doubling of risk of invasive breast cancer overall (HR: 2.17; 95% CI: 1.54‐3.05 and 2.20; 1.55‐3.14, respectively) and of ER+ breast cancer (2.05; 1.37‐3.05 and 2.03; 1.34‐3.07, respectively). The remaining DXA measures were also positively associated with breast cancer risk in baseline and time‐dependent analyses. Conclusion These findings suggest that DXA‐derived body fat measures are positively associated with breast cancer risk after adjustment for BMI and other conventional breast cancer risk factors. Our study demonstrated that DXA‐derived body fat measures were positively associated with breast cancer risk after adjustment for BMI and other conventional breast cancer risk factors. These findings suggest that DXA‐derived measures of overall and central adiposity may explain invasive breast cancer risk beyond that of BMI and other risk factors.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality among older postmenopausal women. The impact of postmenopausal breast cancer on CVD for older women is uncertain. We hypothesized that older postmenopausal women with breast cancer would be at a higher risk of CVD than similar aged women without breast cancer and that CVD would be a major contributor to the subsequent morbidity and mortality. In a prospective Women's Health Initiative study, incident CVD events and total and cause-specific death rates were compared between postmenopausal women with (n = 4,340) and without (n = 97,576) incident invasive breast cancer over 10 years post-diagnosis, stratified by 3 age groups (50-59, 60-69, and 70-79). Postmenopausal women, regardless of breast cancer diagnosis, had similar and high levels of CVD risk factors (e.g., smoking and hypertension) at baseline prior to breast cancer, which were strong predictors of CVD and total mortality over time. CVD affected mostly women age 70-79 with localized breast cancer (79% of breast cancer cases in 70-79 age group): only 17% died from breast cancer and CVD was the leading cause of death (22%) over the average 10 years follow up. Compared to age-matched women without breast cancer, women age 70-79 at diagnosis of localized breast cancer had a similar multivariate-adjusted hazard ratio (HR) of 1.01 (95% confidence interval [CI]: 0.76-1.33) for coronary heart disease, a lower risk of composite CVD (HR = 0.84, 95% CI: 0.70-1.00), and a higher risk of total mortality (HR = 1.20, 95% CI: 1.04-1.39). CVD was a major contributor to mortality in women with localized breast cancer at age 70-79. Further studies are needed to evaluate both screening and treatment of localized breast cancer tailored to the specific health issues of older women.

Background: This study aims to investigate the association between statin use and all-cancer survival in a prospective cohort of postmenopausal women, using data from the Women’s Health Initiative Observational Study (WHI-OS) and Clinical Trial (WHI-CT). Methods: The WHI study enrolled women aged 50–79 years from 1993 to 1998 at 40 US clinical centres. Among 146 326 participants with median 14.6 follow-up years, 23 067 incident cancers and 3152 cancer deaths were observed. Multivariable-adjusted Cox proportional hazards models were used to investigate the relationship between statin use and cancer survival. Results: Compared with never-users, current statin use was associated with significantly lower risk of cancer death (hazard ratio (HR), 0.78; 95% confidence interval (CI), 0.71–0.86, P <0.001) and all-cause mortality (HR, 0.80; 95% CI, 0.74–0.88). Use of other lipid-lowering medications was also associated with increased cancer survival ( P -interaction (int)=0.57). The lower risk of cancer death was not dependent on statin potency ( P -int=0.22), lipophilicity/hydrophilicity ( P -int=0.43), type ( P -int=0.34) or duration ( P -int=0.33). However, past statin users were not at lower risk of cancer death compared with never-users (HR, 1.06; 95% CI, 0.85–1.33); in addition, statin use was not associated with a reduction of overall cancer incidence despite its effect on survival (HR, 0.96; 95% CI, 0.92–1.001). Conclusions: In a cohort of postmenopausal women, regular use of statins or other lipid-lowering medications was associated with decreased cancer death, regardless of the type, duration, or potency of statin medications used.

Background Case-cohort studies have become common in epidemiological studies of rare disease, with Cox regression models the principal method used in their analysis. However, no appropriate procedures to assess the assumption of proportional hazards of case-cohort Cox models have been proposed. Methods We extended the correlation test based on Schoenfeld residuals, an approach used to evaluate the proportionality of hazards in standard Cox models. Specifically, pseudolikelihood functions were used to define “case-cohort Schoenfeld residuals”, and then the correlation of these residuals with each of three functions of event time (i.e., the event time itself, rank order, Kaplan-Meier estimates) was determined. The performances of the proposed tests were examined using simulation studies. We then applied these methods to data from a previously published case-cohort investigation of the insulin/IGF-axis and colorectal cancer. Results Simulation studies showed that each of the three correlation tests accurately detected non-proportionality. Application of the proposed tests to the example case-cohort investigation dataset showed that the Cox proportional hazards assumption was not satisfied for certain exposure variables in that study, an issue we addressed through use of available, alternative analytical approaches. Conclusions The proposed correlation tests provide a simple and accurate approach for testing the proportional hazards assumption of Cox models in case-cohort analysis. Evaluation of the proportional hazards assumption is essential since its violation raises questions regarding the validity of Cox model results which, if unrecognized, could result in the publication of erroneous scientific findings.

INTRODUCTION The potential utility of subjective cognitive decline (SCD) as an early risk marker of Alzheimer's disease and related dementias is under consideration. We examined associations between SCD and cognitive change among middle‐aged and older Hispanic/Latino adults living in the United States. METHODS The short‐form Everyday Cognition Scale (ECog‐12) was assessed to generate global, executive function, and memory‐related SCD scores. We used survey generalized regressions to model the change in learning, memory, verbal fluency, executive function, and global cognitive performance over 7 years as a function of SCD (at Visit 2). RESULTS The mean age was 56.37 ± 8.10 years at Visit 1 (n = 6225). Higher ECog‐12 was associated with greater decline in global cognitive performance (ECog‐12 global: B = –0.17, standard error [SE] = 0.02; ECog‐12 executive: B = –0.15, SE = 0.02; ECog‐12 memory: B = –0.14, SE = 0.02, p’s < 0.001). DISCUSSION These results support the link between subjective reports of cognitive decline and objectively measured 7‐year cognitive decline in community‐dwelling, middle‐aged, and older Hispanic/Latino adults. Highlights We found that nearly two‐thirds of diverse middle‐aged and older Hispanics/Latinos reported cognitive concerns in a large and representative population study. Self‐reported subjective experiences of cognitive decline reflect objective cognitive decline in US Hispanics/Latinos. The relationship is stronger among men compared to women. The relationship between subjective and objective changes to memory are stronger in those with cognitive concerns, and remain even in cognitively healthy individuals.

Religion plays an important role in the lives of people in the United States. We examined the prevalence of religiosity among Hispanic/Latinos in four regions of the United States and looked at its correlation to depression and anxiety symptoms. The population-based Hispanic Community Health Study/ Study of Latinos enrolled a cohort of Hispanic/Latino adults (N = 16,415) ages 18-74 in four US cities from June 2008 to June 2011. Participants with complete data on religiosity (i.e., religious affiliation, frequency of attending religious activities and importance of religion), depression (assessed with the CESD-10), and trait anxiety (assessed with the STAI-10) were included in the present study. Distribution of religiosity is described by sociodemographic characteristics. Associations between religiosity with depression and anxiety were examined with logistic regression models controlling for sex, age group, education, Hispanic/Latino background, clinical center, and nativity. The majority of the population (89.5%) reported having a religious affiliation. Weekly attendance at religious activities was reported by 41.6% of participants, while 20.6% did not attend any religious activities. Religion was very important to 63.9% and not at all important to 6.7% of the population. The CES-D scores and trait anxiety scores were not significantly related in the overall group to frequency of attending religious activity or perceived importance of religion. However, in age-stratified analyses, among older individuals (65+ years old) reporting \"never\" participating in religious activities compared to more than once per week was associated with an 80% higher likelihood of having high depressive symptomatology. Similarly, in the older age group, no religious affiliation or reporting that religion is \"not at all important\" was associated with greater anxiety symptomatology. Religiosity varied by Hispanic/Latino background. Lack of religiosity was associated with elevated depressive or anxiety symptomology in older adults but not in young or middle-aged adults.