Dataset Information

Sex differences in brain aging among adults with family history of Alzheimer's disease and APOE4 genetic risk.

ABSTRACT: Emerging evidence suggests that Alzheimer's Disease (AD) risk factors may differentially contribute to disease trajectory in women than men. Determining the effect of AD risk factors on brain aging in women, compared to men, is critical for understanding whether there are sex differences in the pathways towards AD in cognitively intact but at-risk adults. Brain Age Gap (BAG) is a concept used increasingly as a measure of brain health; BAG is defined as the difference between predicted age (based on structural MRI) and chronological age, with negative values reflecting preserved brain health with age. Using BAG, we investigated whether there were sex differences in the brain effects of AD risk factors (i.e., family history of AD, and carrying an apolipoprotein E ε4 allele [+APOE4]) in cognitively intact adults, and if this relationship was moderated by modifiable factors (i.e. body mass index [BMI], blood pressure and physical activity). We undertook a cross-sectional study of structural MRIs from 1067 cognitively normal adults across four neuroimaging datasets. An elastic net regression model found that women with a family history of AD and +APOE4 genotype had more advanced brain aging than their male counterparts. In a sub-cohort of women with those risk factors, higher BMI was associated with less brain aging whereas lower BMI was not. In a sub-cohort of women and men with +APOE4, engaging in physical activity was more beneficial to men's brain aging than women's. Our results demonstrate that AD risk factors are associated with greater brain aging in women than men, although there may be more unexplored modifiable factors that influence this relationship. These findings suggest that the complex interplay between unmodifiable and modifiable AD risk factors can potentially protect against brain aging in women and men.

SUBMITTER: Subramaniapillai S

PROVIDER: S-EPMC8065341 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Despite recent advances in the understanding of clinical aspects of sex differences in Alzheimer's disease (AD), the underlying mechanisms, for instance, how sex modifies AD risk and why the female brain is more susceptible to AD, are not clear. The purpose of this study is to elucidate sex disparities in brain aging profiles focusing on 2 major areas-energy and amyloid metabolism-that are most significantly affected in preclinical development of AD. Total RNA isolated from hippocampal tissues of both female and male 129/C57BL/6 mice at ages of 6, 9, 12, or 15 months were comparatively analyzed by custom-designed Taqman low-density arrays for quantitative real-time polymerase chain reaction detection of a total of 182 genes involved in a broad spectrum of biological processes modulating energy production and amyloid homeostasis. Gene expression profiles revealed substantial differences in the trajectory of aging changes between female and male brains. In female brains, 44.2% of genes were significantly changed from 6 months to 9 months and two-thirds showed downregulation. In contrast, in male brains, only 5.4% of genes were significantly altered at this age transition. Subsequent changes in female brains were at a much smaller magnitude, including 10.9% from 9 months to 12 months and 6.1% from 12 months to 15 months. In male brains, most changes occurred from 12 months to 15 months and the majority were upregulated. Furthermore, gene network analysis revealed that clusterin appeared to serve as a link between the overall decreased bioenergetic metabolism and increased amyloid dyshomeostasis associated with the earliest transition in female brains. Together, results from this study indicate that: (1) female and male brains follow profoundly dissimilar trajectories as they age; (2) female brains undergo age-related changes much earlier than male brains; (3) early changes in female brains signal the onset of a hypometabolic phenotype at risk for AD. These findings provide a mechanistic rationale for female susceptibility to AD and suggest a potential window of opportunity for AD prevention and risk reduction in women.

Project description:BackgroundGenome-wide association studies have identified numerous single nucleotide polymorphisms associated with type 2 diabetes through the past years. In previous studies, the usefulness of these genetic markers for prediction of diabetes was found to be limited. However, differences may exist between substrata of the population according to the presence of major diabetes risk factors. This study aimed to investigate the added predictive value of genetic information (42 single nucleotide polymorphisms) in subgroups of sex, age, family history of diabetes, and obesity.MethodsA case-cohort study (random subcohort N?=?1,968; incident cases: N?=?578) within the European Prospective Investigation into Cancer and Nutrition Potsdam study was used. Prediction models without and with genetic information were evaluated in terms of the area under the receiver operating characteristic curve and the integrated discrimination improvement. Stratified analyses included subgroups of sex, age (<50 or ?50 years), family history (positive if either father or mother or a sibling has/had diabetes), and obesity (BMI< or ?30 kg/m(2)).ResultsA genetic risk score did not improve prediction above classic and metabolic markers, but - compared to a non-invasive prediction model - genetic information slightly improved the area under the receiver operating characteristic curve (difference [95%-CI]: 0.007 [0.002-0.011]). Stratified analyses showed stronger improvement in the older age group (0.010 [0.002-0.018]), the group with a positive family history (0.012 [0.000-0.023]) and among obese participants (0.015 [-0.005-0.034]) compared to the younger participants (0.005 [-0.004-0.014]), participants with a negative family history (0.003 [-0.001-0.008]) and non-obese (0.007 [0.000-0.014]), respectively. No difference was found between men and women.ConclusionThere was no incremental value of genetic information compared to standard non-invasive and metabolic markers. Our study suggests that inclusion of genetic variants in diabetes risk prediction might be useful for subgroups with already manifest risk factors such as older age, a positive family history and obesity.

Dataset Information

Sex differences in brain aging among adults with family history of Alzheimer's disease and APOE4 genetic risk.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets