253 research outputs found

    Investigations into the effects of cyclical rhythm and hormonal contraception on serum fat-mobilizing activity, glycerol, cholesterol and blood glucose.

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    The effects were investigated of cyclical rhythm and hormonal contraception on serum fat-mobilizing activity, glycerol, cholesterol and whole blood glucose during 2 menstrual cycles in a group of normally menstruating young women and a second group of young women using hormonal contraception. A control group of normal young men was also investigated. There was no evidence of any change in mean level of any of the parameters measured, among the follicular, ovulatory and luteal phases. No cyclical pattern was discernable in the male subjects. The mean value for serum cholesterol concentration in women using hormonal contraception was higher than the value for the untreated human female group. The overall mean value for serum glycerol concentration in the women was significantly (0.01 > P > 0.001) higher than the mean value obtaining in the men

    “Being Guided”: What Oncofertility Patients’ Decisions Can Teach Us About the Efficacy of Autonomy, Agency, and Decision-Making Theory in the Contemporary Critical Encounter

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    Recent research on patient decision-making reveals a disconnect between theories of autonomy, agency, and decision-making and their practice in contemporary clinical encounters. This study examines these concepts in the context of female patients making oncofertility decisions in the United Kingdom in light of the phenomenon of “being guided.” Patients experience being guided as a way to cope with, understand, and defer difficult treatment decisions. Previous discussions condemn guided decision-making, but this research suggests that patients make an informed, autonomous decision to be guided by doctors. Thus, bioethicists must consider the multifaceted ways that patients enact their autonomy in medical encounters

    Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score

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    Background Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Methods and findings Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10−5 ). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer’s Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer’s Disease Center [NIA ADC], and Alzheimer’s Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62–4.24, p = 1.0 × 10−22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10−26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran–Armitage trend test, p = 1.5 × 10−10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10−6 , and Consortium to Establish a Registry for Alzheimer’s Disease score for neuritic plaques, p = 6.8 × 10−6 ) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10−6 , and hippocampus, p = 7.9 × 10−5 ). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. Conclusions We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials
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