Network Modeling Sex Differences in Brain Integrity and Metabolic Health

Abstract

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.

Sex‐ and age‐specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort

“…Unlike females, it is possible that the combined effect of all three CMRs on males' higher BAG as early as midlife may, in turn, be associated with their earlier cardiometabolic disease risk. However, these measures of body adiposity may also be more sensitive to males (Foret et al, 2021 ), while other unexplored CMRs, such as hypertension, may be more robust in capturing females' health risk earlier in adulthood (Gilsanz et al, 2017 ; Wei et al, 2017 ). Furthermore, sex differences in adipose fat distribution may differentially contribute to brain age, with males more likely having fat distributed in the visceral adipose tissue surrounding the abdominal organs, while females tend to have more subcutaneous adipose tissue (Bredella, 2017 ; Chang et al, 2018 ).…”

Psychometric Networks and Their Implications for the Treatment and Diagnosis of Psychopathologies

“…The research by Foret et al [74] composed of adults with no neurological or psychiatric history aimed to compare two simultaneous networks in men and women that included biomarkers of cognitive impairment risk, components of the metabolic syndrome (obesity, hypertension, dyslipidemia, and hyperglycemia), neuroimagingbased brain age minus chronological age, ratio of white matter hyperintensities to total brain volume, resting-state brain connectivity based on default mode network seed analysis, and ratios of N-acetyl aspartate, glutamate, and myo-inositol to creatine, which were measured by proton magnetic resonance spectroscopy [74]. Differences were found in the connectivity of both networks where women report lower relationships between cardiometabolic risk variables and brain functioning, furthermore, the most influential measures are shown to be apolipoprotein status and waist circumference.…”

Towards a Deeper Understanding: Utilizing Machine Learning to Investigate the Association between Obesity and Cognitive Decline—A Systematic Review

“…Research shows that men may be more vulnerable to the direct consequences of metabolic health on brain damage and cognitive decline. On the other hand, women's cognitive decline may be associated with more complex interactions that involve brain health, metabolism, and possibly genetics [55]. This highlights the need for personalized approaches to address the unique needs of each individual.…”

“…Additionally, three studies [44,53,56] displayed some concerns about bias due to confounding. Further, the studies conducted by Govindarajan et al (2022) [53] and Foret et al (2021) [55] exhibited some concerns about bias in the selection of participants for the study (or for the analysis). Moreover, some concerns about bias arising from the measurement of the exposure were found in the study of Gharbi-Meliani et al ( 2023) [45].…”