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IntroductionEarly-onset Alzheimer's disease (EOAD) shows a higher burden of neuropsychiatric symptoms than late-onset Alzheimer's disease (LOAD). We aim to determine the differences in the severity of neuropsychiatric symptoms and locus coeruleus (LC) integrity between EOAD and LOAD accounting for disease stage.MethodsOne hundred four subjects with AD diagnosis and 32 healthy controls were included. Participants underwent magnetic resonance imaging (MRI) to measure LC integrity, measures of noradrenaline levels in cerebrospinal fluid (CSF) and Neuropsychiatric Inventory (NPI). We analyzed LC-noradrenaline measurements and clinical and Alzheimer's disease (AD) biomarker associations.ResultsEOAD showed higher NPI scores, lower LC integrity, and similar levels of CSF noradrenaline compared to LOAD. Notably, EOAD exhibited lower LC integrity independently of disease stage. LC integrity negatively correlated with neuropsychiatric symptoms. Noradrenaline levels were increased in AD correlating with AD biomarkers.DiscussionDecreased LC integrity negatively contributes to neuropsychiatric symptoms. The higher LC degeneration in EOAD compared to LOAD could explain the more severe neuropsychiatric symptoms in EOAD.HighlightsLC degeneration is greater in early-onset AD (EOAD) compared to late-onset AD. Tau-derived LC degeneration drives a higher severity of neuropsychiatric symptoms. EOAD harbors a more profound selective vulnerability of the LC system. LC degeneration is associated with an increase of cerebrospinal fluid noradrenaline levels in AD.

PurposeThis study estimated associations between neighborhood socioeconomic status (NSES), walkability, green space, and incident falls among postmenopausal women and evaluated modifiers of these associations, including study arm, race and ethnicity, baseline household income, baseline walking, age at enrollment, baseline low physical functioning, baseline fall history, climate region, and urban-rural residence.MethodsThe Women's Health Initiative recruited a national sample of postmenopausal women (50-79 years) across 40 U.S. clinical centers and conducted yearly assessments from 1993 to 2005 (n = 161,808). Women reporting a history of hip fracture or walking limitations were excluded, yielding a final sample of 157,583 participants. Falling was reported annually. NSES (income/wealth, education, occupation), walkability (population density, diversity of land cover, nearby high-traffic roadways), and green space (exposure to vegetation) were calculated annually and categorized into tertiles (low, intermediate, high). Generalized estimating equations assessed longitudinal relationships.ResultsNSES was associated with falling before adjustment (high vs. low, odds ratio, 1.01; 95% confidence interval, 1.00-1.01). Walkability was significantly associated with falls after adjustment (high vs. low, odds ratio, 0.99; 95% confidence interval, 0.98-0.99). Green space was not associated with falling before or after adjustment. Study arm, race and ethnicity, household income, age, low physical functioning, fall history, and climate region modified the relationship between NSES and falling. Race and ethnicity, age, fall history, and climate region modified relationships between walkability and green space and falling.ConclusionsOur results did not show strong associations of NSES, walkability, or green space with falling. Future research should incorporate granular environmental measures that may directly relate to physical activity and outdoor engagement.

BackgroundStudies of cancer mutations have typically focused on identifying cancer driving mutations that confer growth advantage to cancer cells. However, cancer genomes accumulate a large number of passenger somatic mutations resulting from various endogenous and exogenous causes, including normal DNA damage and repair processes or cancer-related aberrations of DNA maintenance machinery as well as mutations triggered by carcinogenic exposures. Different mutagenic processes often produce characteristic mutational patterns called mutational signatures. Identifying mutagenic processes underlying mutational signatures shaping a cancer genome is an important step towards understanding tumorigenesis.MethodsTo investigate the genetic aberrations associated with mutational signatures, we took a network-based approach considering mutational signatures as cancer phenotypes. Specifically, our analysis aims to answer the following two complementary questions: (i) what are functional pathways whose gene expression activities correlate with the strengths of mutational signatures, and (ii) are there pathways whose genetic alterations might have led to specific mutational signatures? To identify mutated pathways, we adopted a recently developed optimization method based on integer linear programming.ResultsAnalyzing a breast cancer dataset, we identified pathways associated with mutational signatures on both expression and mutation levels. Our analysis captured important differences in the etiology of the APOBEC-related signatures and the two clock-like signatures. In particular, it revealed that clustered and dispersed APOBEC mutations may be caused by different mutagenic processes. In addition, our analysis elucidated differences between two age-related signatures-one of the signatures is correlated with the expression of cell cycle genes while the other has no such correlation but shows patterns consistent with the exposure to environmental/external processes.ConclusionsThis work investigated, for the first time, a network-level association of mutational signatures and dysregulated pathways. The identified pathways and subnetworks provide novel insights into mutagenic processes that the cancer genomes might have undergone and important clues for developing personalized drug therapies.

Phenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. We develop a computational method, named NETPHIX (NETwork-to-PHenotype association with eXclusivity) to identify subnetworks of genes whose genetic alterations are associated with drug response or other continuous cancer phenotypes. Leveraging interaction information among genes and properties of cancer mutations such as mutual exclusivity, we formulate the problem as an integer linear program and solve it optimally to obtain a subnetwork of associated genes. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with drug responses. Utilizing interaction information, NETPHIX modules are functionally coherent and can thus provide important insights into drug action. In addition, we show that modules identified by NETPHIX together with their association patterns can be leveraged to suggest drug combinations.

Short sleep duration, recognized as a public health epidemic, is associated with adverse health conditions, yet little is known about the association between sleep and bone health. We tested the associations of usual sleep behavior and bone mineral density (BMD) and osteoporosis. In a sample of 11,084 postmenopausal women from the Women's Health Initiative (WHI; mean age 63.3 years, SD = 7.4), we performed a cross-sectional study of the association of self-reported usual hours of sleep and sleep quality (WHI Insomnia Rating Score) with whole body, total hip, femoral neck, and spine BMD using linear regression models. We also studied the association of sleep duration and quality with dual-energy X-ray absorptiometry (DXA)-defined low bone mass (T-score

Purpose: This study aims to combine open innovation (OI) and organizational learning (OL) literature in the context of strategic alliances. Design/methodology/approach: The authors develop a conceptual framework that links OI to OL literatures. The authors empirically validate this framework through four representative cases of dyadic strategic alliances in which the allied partners have (mainly) adopted an inbound or outbound OI strategy and (mainly) used an experiential or experimental learning approach to access knowledge in the alliance. Findings: The authors propose and validate a framework that links two well-known OI strategies (inbound and outbound) and two types of OL, namely, experiential and experimental learning. This, in turn, allows us to propose four different typologies of learning opportunities that could be pursued by alliance partners. Research limitations/implications: The research offers a framework that links experiential and experimental learning to inbound and outbound OI strategies. However, the authors focused on inbound and outbound OI. The authors are aware that sometimes coupled innovation could take place in alliances. Practical implications: This study proposes best practices for companies willing to open their innovation processes with alliance partners by bearing in mind the learning outcomes that may be exploited through the alliance. Originality/value: This study highlights four alliance archetypes emerging from the nexus between OI strategies to OL methods.

Recent large cancer studies have measured somatic alterations in an unprecedented number of tumours. These large datasets allow the identification of cancer-related sets of genetic alterations by identifying relevant combinatorial patterns. Among such patterns, mutual exclusivity has been employed by several recent methods that have shown its effectiveness in characterizing gene sets associated to cancer. Mutual exclusivity arises because of the complementarity, at the functional level, of alterations in genes which are part of a group (e.g., a pathway) performing a given function. The availability of quantitative target profiles, from genetic perturbations or from clinical phenotypes, provides additional information that can be leveraged to improve the identification of cancer related gene sets by discovering groups with complementary functional associations with such targets. In this work we study the problem of finding groups of mutually exclusive alterations associated with a quantitative (functional) target. We propose a combinatorial formulation for the problem, and prove that the associated computational problem is computationally hard. We design two algorithms to solve the problem and implement them in our tool UNCOVER. We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. In addition, our algorithms are much faster than the state-of-the-art, allowing the analysis of large datasets of thousands of target profiles from cancer cell lines. We show that on two such datasets, one from project Achilles and one from the Genomics of Drug Sensitivity in Cancer project, UNCOVER identifies several significant gene sets with complementary functional associations with targets. Software available at: https://github.com/VandinLab/UNCOVER.

Women with history of pregnancy loss (PL) have higher burden of cardiovascular disease (CVD) later in life, yet it is unclear whether this is attributable to an association with established CVD risk factors (RFs). We examined whether PL is associated with CVD RFs and biomarkers in parous postmenopausal women in the Women's Health Initiative, and whether the association between PL and CVD RFs accounted for the association between PL and incident CVD. Linear and logistic regressions were used to estimate associations between baseline history of PL and CVD RFs. Cox proportional hazards regression models were used to estimate the associations between baseline history of PL and incident CVD after adjustment for baseline RFs. Of 79,121 women, 27,272 (35%) had experienced PL. History of PL was associated with higher body mass index (p < 0.0001), hypertension (p < 0.0001), diabetes (p = 0.003), depression (p < 0.0001), and lower income (p < 0.0001), physical activity (p = 0.01), poorer diet (p < 0.0001), smoking (p < 0.0001), and alcohol use (p < 0.0001). After adjustment for CVD RFs, PL was significantly associated with incident CVD over mean follow up of 16 years (hazard ratio 1.11, 95% confidence interval 1.06 to 1.16). In conclusion, several CVD RFs are associated with PL, but they do not entirely account for the association between PL and incident CVD.

Background: Practice effects are a well‐known cognitive phenomenon that is reduced in patients with Alzheimer's disease (AD). We aimed to investigate whether cognitively unimpaired (CU) individuals within the Alzheimer's continuum (i.e., positive amyloid‐β biomarker) display decreased practice effects on serial neuropsychological testing. Methods: We included 310 CU from four Spanish research centers, classified into controls (n = 250) or Aβ+ (n = 60). In the main cohort (Cohort A; n = 209), participants underwent neuropsychological assessment at baseline and annually during a 2‐year follow‐up (FU1 and FU2). A "long‐term cohort" (Cohort B; n = 101) was employed to assess practice effects over longer time periods (i.e., two follow‐up sessions at years 3 and 6 from baseline). Practice effects were defined as simple discrepancy scores (SDS) by subtracting Z‐scores at FU2 from Z‐scores at baseline for each neuropsychological variable, and linear mixed effects models (LME) were run to assess the temporal evolution of practice effects according to the two groups. Results: There were no cross‐sectional differences between the control and Aβ+ groups in none of the neuropsychological scores at baseline (Fig. 1). The Aβ+ group displayed lower practice effects than the controls in terms of SDS in several neuropsychological outcomes (Fig. 2). In Cohort A, LME showed negative slopes by the Aβ+ group in verbal memory measures such as the free learning score (β = ‐0.37, SD = 0.12, p = 0.0034), delayed free recall (β = ‐0.43, SD = 0.15, p = 0.0047) and delayed total recall (β = ‐0.46, SD = 0.17, p = 0.0069) from the Free and Cued Selective Reminding Test; as well as in language tasks (Boston Naming Test; β = ‐0.26, SD = 0.087, p = 0.0025) and executive function measures (Trail Making Test; β = ‐0.33, SD = 0.12, p = 0.0094) (Fig. 3A). In Cohort B, similar findings were observed in visual memory measures, such as the Rey‐Osterrieth Complex Figure immediate (β = ‐0.80, SD = 0.35, p = 0.024) and delayed (β = ‐1.25, SD = 0.34, p = 0.00038) recall (Fig. 3B). Conclusions: Individuals with normal cognition who are in the Alzheimer's continuum show decreased practice effects over serial neuropsychological testing. Our findings suggest the reduction of practice effects, particularly in memory measures, as an indicator of subtle cognitive decline in the earliest phase of the Alzheimer's continuum and could be particularly relevant for the design and interpretation of primary prevention trials on disease‐modifying therapies. [ABSTRACT FROM AUTHOR]

Recent large cancer studies have measured somatic alterations in an unprecedented number of tumours. These large datasets allow the identification of cancer-related sets of genetic alterations by identifying relevant combinatorial patterns. Among such patterns, mutual exclusivity has been employed by several recent methods that have shown its effectiveness in characterizing gene sets associated to cancer. Mutual exclusivity arises because of the complementarity, at the functional level, of alterations in genes which are part of a group (e.g., a pathway) performing a given function. The availability of quantitative target profiles, from genetic perturbations or from clinical phenotypes, provides additional information that can be leveraged to improve the identification of cancer related gene sets by discovering groups with complementary functional associations with such targets. In this work we study the problem of finding groups of mutually exclusive alterations associated with a quantitative (functional) target. We propose a combinatorial formulation for the problem, and prove that the associated computational problem is computationally hard. We design two algorithms to solve the problem and implement them in our tool UNCOVER. We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. In addition, our algorithms are much faster than the state-of-the-art, allowing the analysis of large datasets of thousands of target profiles from cancer cell lines. We show that on two such datasets, one from project Achilles and one from the Genomics of Drug Sensitivity in Cancer project, UNCOVER identifies several significant gene sets with complementary functional associations with targets. Software available at: https://github.com/ VandinLab/UNCOVER.

BackgroundDietary energy density, or energy available in relation to gram intake, can inform disease risk.ObjectiveThe objective of this study was to investigate the association between baseline dietary energy density and risk of incident type 2 diabetes in postmenopausal women.DesignDietary energy density, weight status, and type 2 diabetes incidence were prospectively characterized in a large cohort of postmenopausal women participating in one or more clinical trials or an observational study.Participants/settingThe study involved 161,808 postmenopausal women recruited to the Women's Health Initiative observational study or clinical trials at 40 centers across the United States between 1993 and 1998.Main outcome measuresThe primary outcome was incident type 2 diabetes.Statistical analyses performedThe association between dietary energy density quintiles and incident diabetes was tested using Cox proportional hazards regression.ResultsA total of 143,204 participants without self-reported diabetes at enrollment completed baseline dietary assessment and were followed for 12.7±4.6 years. Risk of diabetes developing was 24% greater for women in the highest dietary energy density quintile compared with the lowest after adjusting for confounders (95% CI 1.17 to 1.32). Body mass index (calculated as kg/m2) and waist circumference mediated the relationship between dietary energy density and diabetes. In waist circumference-stratified analysis, women in dietary energy density quintiles 2 to 5 with waist circumferences >88 cm were at 9% to 12% greater risk of diabetes developing compared with women with waist circumference ≤88 cm.ConclusionsIn this prospective study, a higher baseline dietary energy density was associated with higher incidence of type 2 diabetes among postmenopausal women, both overall, and in women with elevated waist circumference.

BACKGROUND:Reproductive factors reflective of endogenous sex hormone exposure might have an effect on cardiac remodeling and the development of heart failure (HF). OBJECTIVES:This study examined the association between key reproductive factors and the incidence of HF. METHODS:Women from a cohort of the Women's Health Initiative were systematically evaluated for the incidence of HF hospitalization from study enrollment through 2014. Reproductive factors (number of live births, age at first pregnancy, and total reproductive duration [time from menarche to menopause]) were self-reported at study baseline in 1993 to 1998. We employed Cox proportional hazards regression analysis in age- and multivariable-adjusted models. RESULTS:Among 28,516 women, with an average age of 62.7 ± 7.1 years at baseline, 1,494 (5.2%) had an adjudicated incident HF hospitalization during an average follow-up of 13.1 years. After adjusting for covariates, total reproductive duration in years was inversely associated with incident HF: hazard ratios (HRs) of 0.99 per year (95% confidence interval [CI]: 0.98 to 0.99 per year) and 0.95 per 5 years (95% CI: 0.91 to 0.99 per 5 years). Conversely, early age at first pregnancy and nulliparity were significantly associated with incident HF in age-adjusted models, but not after multivariable adjustment. Notably, nulliparity was associated with incident HF with preserved ejection fraction in the fully adjusted model (HR: 2.75; 95% CI: 1.16 to 6.52). CONCLUSIONS:In post-menopausal women, shorter total reproductive duration was associated with higher risk of incident HF, and nulliparity was associated with higher risk for incident HF with preserved ejection fraction. Whether exposure to endogenous sex hormones underlies this relationship should be investigated in future studies.

ObjectiveIn postmenopausal black women in the Women's Health Initiative randomized trial, estrogen alone reduced breast cancers but its comprehensive influence on health outcomes in black women is unknown. Therefore, we examined this issue in the Women's Health Initiative overall and by African ancestry.MethodsA total of 1,616 black women with prior hysterectomy, including 1,061 with percent African ancestry determination, at 40 US centers were randomly assigned to conjugated equine estrogen (0.625 mg/d) or placebo for 7.2 years' (median) intervention with 13 years' cumulative follow-up. Coronary heart disease (CHD) and breast cancer were primary efficacy and safety outcomes, respectively. A global index also included stroke, colorectal cancer, hip fracture, pulmonary embolism, and death.ResultsBlack women in the estrogen-alone group compared with black women in the placebo group had fewer breast cancers (17 vs 40, hazard ratio [HR] 0.47, 95% CI 0.26-0.82). In women with more than 80% African ancestry, breast cancer HR was lower (0.32, 95% CI 0.12-0.86, trend P = 0.04 for ancestry effect). Most other outcomes including CHD, stroke, hip fracture, and the global index were null with estrogen use in black women; a global index effect was more favorable in younger black women (HR 0.65, 95% CI 0.43-0.98).ConclusionsIn black postmenopausal women with prior hysterectomy, estrogen alone significantly reduced breast cancer incidence with no adverse influence on CHD, venous thromboembolism, or all-cause mortality. Favorable estrogen-alone global index effects in younger black women warrant further study.