Network Modeling Sex Differences in Brain Integrity and Metabolic Health

Hypothesis-driven studies have demonstrated that sex moderates many of the relationships between brain health and cardiometabolic disease, which impacts risk for later-life cognitive decline. In the present study, we sought to further our understanding of the associations between multiple markers of brain integrity and cardiovascular risk in a midlife sample of 266 individuals by using network analysis, a technique specifically designed to examine complex associations among multiple systems at once. Separate network models were constructed for male and female participants to investigate sex differences in the biomarkers of interest, selected based on evidence linking them with risk for late-life cognitive decline: all components of metabolic syndrome (obesity, hypertension, dyslipidemia, and hyperglycemia); neuroimaging-derived brain-predicted age minus chronological age; ratio of white matter hyperintensities to whole brain volume; seed-based resting state functional connectivity in the Default Mode Network, and ratios of N-acetyl aspartate, glutamate and myo-inositol to creatine, measured through proton magnetic resonance spectroscopy. Males had a sparse network (87.2% edges = 0) relative to females (69.2% edges = 0), indicating fewer relationships between measures of cardiometabolic risk and brain integrity. The edges in the female network provide meaningful information about potential mechanisms between brain integrity and cardiometabolic health. Additionally, Apolipoprotein ϵ4 (ApoE ϵ4) status and waist circumference emerged as central nodes in the female model. Our study demonstrates that network analysis is a promising technique for examining relationships between risk factors for cognitive decline in a midlife population and that investigating sex differences may help optimize risk prediction and tailor individualized treatments in the future.

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Role of sex in the association between childhood socioeconomic position and cognitive ageing in later life

Scientific Reports ◽

10.1038/s41598-021-84022-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Katrin Wolfova ◽

Zsofia Csajbok ◽

Anna Kagstrom ◽

Ingemar Kåreholt ◽

Pavla Cermakova

Keyword(s):

Sex Differences ◽

Cognitive Decline ◽

Cognitive Performance ◽

Socioeconomic Position ◽

Structural Equation ◽

Later Life ◽

Delayed Recall ◽

Immediate Recall ◽

Rate Of Decline ◽

Multilevel Linear Regression

AbstractWe aimed to explore sex differences in the association of childhood socioeconomic position (SEP) with the level of cognitive performance and the rate of cognitive decline. We studied 84,059 individuals (55% women; mean age 64 years) from the Survey on Health, Ageing and Retirement in Europe. Sex differences in the association of childhood SEP (household characteristics at age 10) with the level of cognitive performance (verbal fluency, immediate recall, delayed recall) were analysed using multilevel linear regression. Structural equation modelling tested education, depressive symptoms and physical state as mediators. The relationship between childhood socioeconomic advantage and disadvantage and the rate of cognitive decline was assessed using linear mixed-effects models. Higher childhood SEP was associated with a higher level of cognitive performance to a greater extent in women (B = 0.122; 95% CI 0.092–0.151) than in men (B = 0.109; 95% CI 0.084–0.135). The strongest mediator was education. Childhood socioeconomic disadvantage was related to a higher rate of decline in delayed recall in both sexes, with a greater association in women. Strategies to prevent impaired late-life cognitive functioning, such as reducing childhood socioeconomic disadvantages and improving education, might have a greater benefit for women.

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The Role of Stressful Childhood Experiences in Shaping Later-Life Memory Loss Among Black and White U.S. Adults

Innovation in Aging ◽

10.1093/geroni/igaa057.948 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 296-296

Author(s):

Caroline Hartnett

Keyword(s):

Cognitive Decline ◽

Memory Loss ◽

Later Life ◽

Behavioral Risk ◽

Black Adults ◽

Childhood Experiences ◽

White Children ◽

Black And White ◽

Stressful Experiences ◽

White Adults

Abstract Cognitive decline common in the U.S. and greatly impacts quality of life, both for those who experience it and for those who care for them. Black Americans experience higher burdens of cognitive decline but the mechanisms underlying this disparity have not been fully elucidated. Stress experienced in early life is a promising explanatory factor, since stress and cognition are linked, childhood stressors been shown to have a range of negative implications later in life, and Black children experience more childhood stressors than White children, on average. In this paper, we use data from the Behavioral Risk Factor Surveillance System (BRFSS) to examine whether stressful experiences in childhood help explain Black-White disparities in memory loss. These data were available for 5 state-years between 2011 and 2017 (n=11,708). Preliminary results indicate that, while stressful childhood experiences are strongly associated with memory loss, stressful experiences do not mediate the association between race and memory loss. However, race does appear to moderate the association between stressful childhood experiences and memory loss. Specifically, stressful experiences are associated with a higher likelihood of memory loss for Black adults compared to White adults.In addition, there seem to be some noteworthy patterns across different types of experiences (i.e. parental drinking may predict later memory loss more strongly for Black adults than White adults, but parental hitting may predict memory loss more strongly for White adults than Black adults).

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Subjective Cognitive Decline and its Relation to Verbal Memory and Sex in Cognitively Unimpaired Individuals from a Colombian Cohort with Autosomal-Dominant Alzheimer’s Disease

Journal of the International Neuropsychological Society ◽

10.1017/s1355617721000801 ◽

2021 ◽

pp. 1-9

Author(s):

Jairo E. Martinez ◽

Enmanuelle Pardilla-Delgado ◽

Edmarie Guzmán-Vélez ◽

Clara Vila-Castelar ◽

Rebecca Amariglio ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Sex Differences ◽

Cognitive Decline ◽

Verbal Memory ◽

Autosomal Dominant ◽

Memory Performance ◽

Subjective Cognitive Decline ◽

Mutation Carriers ◽

Study Partner

Abstract Objective: Subjective Cognitive Decline (SCD) may be an early indicator of risk for Alzheimer’s disease (AD). Findings regarding sex differences in SCD are inconsistent. Studying sex differences in SCD within cognitively unimpaired individuals with autosomal-dominant AD (ADAD), who will develop dementia, may inform sex-related SCD variations in preclinical AD. We examined sex differences in SCD within cognitively unimpaired mutation carriers from the world’s largest ADAD kindred and sex differences in the relationship between SCD and memory performance. Methods: We included 310 cognitively unimpaired Presenilin-1 (PSEN-1) E280A mutation carriers (51% females) and 1998 noncarrier family members (56% females) in the study. Subjects and their study partners completed SCD questionnaires and the CERAD word list delayed recall test. ANCOVAs were conducted to examine group differences in SCD, sex, and memory performance. In carriers, partial correlations were used to examine associations between SCD and memory performance covarying for education. Results: Females in both groups had greater self-reported and study partner-reported SCD than males (all p < 0.001). In female mutation carriers, greater self-reported (p = 0.02) and study partner-reported SCD (p < 0.001) were associated with worse verbal memory. In male mutation carriers, greater self-reported (p = 0.03), but not study partner-reported SCD (p = 0.11) was associated with worse verbal memory. Conclusions: Study partner-reported SCD may be a stronger indicator of memory decline in females versus males in individuals at risk for developing dementia. Future studies with independent samples and preclinical trials should consider sex differences when recruiting based on SCD criteria.

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Sex differences in the associations between adiposity distribution and cardiometabolic risk factors in overweight or obese individuals: a cross-sectional study

BMC Public Health ◽

10.1186/s12889-021-11316-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yide Yang ◽

Ming Xie ◽

Shuqian Yuan ◽

Yuan Zeng ◽

Yanhui Dong ◽

...

Keyword(s):

Risk Factors ◽

Sex Differences ◽

Body Fat ◽

Regression Models ◽

Cardiometabolic Risk ◽

Cardiometabolic Risk Factors ◽

Whole Body ◽

Anthropometric Measurement ◽

Cardiometabolic Health ◽

Lower Odds

Abstract Background We aimed to assess the associations between adiposity distribution and cardiometabolic risk factors among overweight and obese adults in China, and to demonstrate the sex differences in these associations. Methods A total of 1221 participants (455 males and 766 females) were included in this study. Percentage of body fat (PBF) of the whole body and regional areas, including arm, thigh, trunk, android, and gynoid, were measured by the dual-energy X-ray absorptiometry method. Central adiposity was measured by waist circumference. Clustered cardiometabolic risk was defined as the presence of two or more of the six cardiometabolic risk factors, namely, high triglyceride, low high density lipoprotein, elevated glucose, elevated blood pressure, elevated high sensitivity C-reactive protein, and low adiponectin. Linear regression models and multivariate logistic regression models were used to assess the associations between whole body or regional PBF and cardiometabolic risk factors. Results In females, except arm adiposity, other regional fat (thigh, trunk, android, gynoid) and whole-body PBF are significantly associated with clustered cardiometabolic risk, adjusting for age, smoking, alcohol drinking, physical activity, and whole-body PBF. One-SD increase in Z scores of the thigh and gynoid PBF were significantly associated with 80 and 78% lower odds of clustered cardiometabolic risk (OR: 0.20, 95%CI: 0.12–0.35 and OR: 0.22, 95%CI: 0.12–0.41). Trunk, android and whole-body PBF were significantly associated with higher odds of clustered risk with OR of 1.90 (95%CI:1.02–3.55), 2.91 (95%CI: 1.75–4.85), and 2.01 (95%CI: 1.47–2.76), respectively. While in males, one-SD increase in the thigh and gynoid PBF are associated with 94% (OR: 0.06, 95%CI: 0.02–0.23) and 83% lower odds (OR: 0.17, 95%CI: 0.05–0.57) of clustered cardiometabolic risk, respectively. Android and whole-body PBF were associated with higher odds of clustered cardiometabolic risk (OR: 3.39, 95%CI: 1.42–8.09 and OR: 2.45, 95%CI: 1.53–3.92), but the association for trunk PBF was not statistically significant (OR: 1.16, 95%CI: 0.42–3.19). Conclusions Adiposity distribution plays an important role in the clustered cardiometabolic risk in participants with overweight and obese and sex differences were observed in these associations. In general, central obesity (measured by android PBF) could be the best anthropometric measurement for screening people at risk for CVD risk factors for both men and women. Upper body fat tends to be more detrimental to cardiometabolic health in women than in men, whereas lower body fat is relatively more protective in men than in women.

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Perception of Neighborhood Characteristics During Childhood and Cognitive Health Among Older Adults in China

Innovation in Aging ◽

10.1093/geroni/igaa057.1419 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 439-439

Author(s):

Changmin Peng ◽

Sae Hwang Han ◽

Jeffrey Burr

Keyword(s):

Cognitive Function ◽

Cognitive Decline ◽

Cognitive Functioning ◽

Social Cohesion ◽

Later Life ◽

Neighborhood Characteristics ◽

Neighborhood Safety ◽

Cognitive Health ◽

Childhood Conditions ◽

Neighborhood Environments

Abstract Neighborhood environments shape the availability of resources for social engagement and social interaction, which are associated with better health outcomes. However, these contextual factors are also considered sources of potential social distress and tension, increasing the risk of subsequent health deficits, including cognitive decline. Our understanding of the linkage between childhood neighborhood environments and cognitive functioning in later life is limited. This study employed three waves of nationally representative data from the China Health and Retirement Longitudinal Study (2011-2015; N = 11,105) to investigate the relationship between self-reported neighborhood social cohesion during childhood (i.e., neighborhood safety, neighbors willing to help, and close-knit neighborhood) and cognitive functioning (Chinese version of TICS). We employed latent growth curve modeling to test hypotheses relating to life course models of childhood conditions and later life cognitive functioning (the long arm of childhood). The results showed that perceptions regarding the willingness of neighbors to help and close-knit neighborhood characteristics during childhood were positively associated with levels of later life cognitive function. Further, growing up in a neighborhood characterized by the willingness of neighbors to help others was negatively associated with the rate of cognitive decline, net of childhood and adulthood covariates. Self-report of neighborhood safety during childhood was unrelated to cognitive function (level and change). These findings underscored the long-term ramifications of childhood conditions as potential risk factors for later-life cognitive health. Social cohesion at the neighborhood level as experienced during childhood may be a protective factor for healthy cognitive aging among older Chinese adults.

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Bayesian Network Structure and Predictability of Autistic Traits

Psychological Reports ◽

10.1177/0033294120978159 ◽

2020 ◽

pp. 003329412097815

Author(s):

Giovanni Briganti ◽

Donald R. Williams ◽

Joris Mulder ◽

Paul Linkowski

Keyword(s):

Sex Differences ◽

Network Analysis ◽

Bayesian Network ◽

Network Structure ◽

Network Connectivity ◽

Autistic Traits ◽

Data Set ◽

Conditional Dependence ◽

Bayesian Network Structure ◽

Male Subjects

The aim of this work is to explore the construct of autistic traits through the lens of network analysis with recently introduced Bayesian methods. A conditional dependence network structure was estimated from a data set composed of 649 university students that completed an autistic traits questionnaire. The connectedness of the network is also explored, as well as sex differences among female and male subjects in regard to network connectivity. The strongest connections in the network are found between items that measure similar autistic traits. Traits related to social skills are the most interconnected items in the network. Sex differences are found between female and male subjects. The Bayesian network analysis offers new insight on the connectivity of autistic traits as well as confirms several findings in the autism literature.

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Later life sex differences in sexual psychology and behavior

Personality and Individual Differences ◽

10.1016/j.paid.2019.109730 ◽

2020 ◽

Vol 157 ◽

pp. 109730 ◽

Cited By ~ 1

Author(s):

Gavin Vance ◽

Todd K. Shackelford ◽

Viviana A. Weekes-Shackelford ◽

Mohaned G. Abed

Keyword(s):

Sex Differences ◽

Later Life ◽

And Behavior

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Studying at university in later life slows cognitive decline: A long‐term prospective study

Alzheimer s & Dementia Translational Research & Clinical Interventions ◽

10.1002/trc2.12207 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Aidan D. Bindoff ◽

Mathew J. Summers ◽

Edward Hill ◽

Jane Alty ◽

James C. Vickers

Keyword(s):

Prospective Study ◽

Cognitive Decline ◽

Later Life

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Abstract 313: Visualizing Out-Of-Hospital Cardiac Arrest in the Young: A Network Analysis of the Cardiac Arrest Registry for Enhanced Survival in Chicago

Circulation ◽

10.1161/circ.140.suppl_2.313 ◽

2019 ◽

Vol 140 (Suppl_2) ◽

Author(s):

Alyssa Vermeulen ◽

Marina Del Rios ◽

Teri L Campbell ◽

Hai Nguyen ◽

Hoang H Nguyen

Keyword(s):

Cardiac Arrest ◽

Network Analysis ◽

Emergency Room ◽

American Indians ◽

Network Models ◽

Spontaneous Circulation ◽

Data Set ◽

Qualitative And Quantitative ◽

Complex Network Models ◽

Hospital Cardiac Arrest

Introduction: The interactions of various variables on out-of-hospital cardiac arrest (OHCA) in the young (1-35 years old) outcomes are complex. Network models have emerged as a way to abstract complex systems and gain insights into relational patterns among observed variables. Hypothesis: Network analysis helps provide qualitative and quantitative insights into how various variables interact with each other and affect outcomes in OHCA in the young. Methods: A mixed graphical network analysis was performed using variables collected by CARES. The network allows the visualization and quantification of each unique interaction between two variables that cannot be explained away by other variables in the data set. The strength of the underlying interaction is proportional to the thickness of the connections (edges) between the variables (nodes). We used the mgm package in R. Results: Figure 1 shows the network of the OHCA in the young cases in Chicago from 2013 to 2017. There are apparent clusters. Sustained return of spontaneous circulation and hypothermia are strongly correlated with survival and neurological outcomes. This cluster is in turn connected to the rest of the network by survival to emergency room. The interaction between any two variables can also be quantified. For example, American Indians cases occur more often in disadvantaged locations when compared to Whites (OR 4.5). The network also predicts how much one node can be explained by adjacent nodes. Only 20% of survival to emergency room is explained by its adjacent nodes. The remaining 80% is attributed to variables not represented in this network. This suggests that interventions to improve this node is difficult unless further data is available. Conclusion: Network analysis provides both a qualitative and quantitative evaluation of the complex system governing OHCA in the young. The networks predictive capability could help in identifying the most effective interventions to improve outcomes.

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