The Impact of Common Epidemiological Factors on Gray and White Matter Volumes in Magnetic Resonance Imaging-Is Prevention of Brain Degeneration Possible?

Narcissus reflected: Grey and white matter features joint contribution to the default mode network in predicting narcissistic personality traits

Despite the clinical significance of narcissistic personality, its neural bases have not been clarified yet, primarily because of methodological limitations of the previous studies, such as the low sample size, the use of univariate techniques and the focus on only one brain modality. In this study, we employed for the first time a combination of unsupervised and supervised machine learning methods, to identify the joint contributions of grey matter (GM) and white matter (WM) to narcissistic personality traits (NPT). After preprocessing, the brain scans of 135 participants were decomposed into eight independent networks of covarying GM and WM via parallel ICA. Subsequently, stepwise regression and Random Forest were used to predict NPT. We hypothesized that a fronto-temporo parietal network, mainly related to the default mode network, may be involved in NPT and associated WM regions. Results demonstrated a distributed network that included GM alterations in fronto-temporal regions, the insula and the cingulate cortex, along with WM alterations in cerebellar and thalamic regions. To assess the specificity of our findings, we also examined whether the brain network predicting narcissism could also predict other personality traits (i.e., histrionic, paranoid and avoidant personalities). Notably, this network did not predict such personality traits. Additionally, a supervised machine learning model (Random Forest) was used to extract a predictive model for generalization to new cases. Results confirmed that the same network could predict new cases. These findings hold promise for advancing our understanding of personality traits and potentially uncovering brain biomarkers associated with narcissism.

Sex Differences in the Association of Age at Hypertension Diagnosis With Brain Structure

BACKGROUND

Sex differences exist in the likelihood of cognitive decline. The age at hypertension diagnosis is a unique contributor to brain structural changes associated with cerebral small vessel disease. However, whether this relationship differs between sexes remains unclear. Therefore, our objective was to evaluate sex differences in the association between the age at hypertension diagnosis and cerebral small vessel disease-related brain structural changes.

METHODS

We used data from the UK Biobank to select participants with a known age at hypertension diagnosis and brain magnetic resonance imaging (n=9430) and stratified them by sex and age at hypertension diagnosis. Control participants with magnetic resonance imaging scans but no hypertension were chosen at random matched by using propensity score matching. For morphological brain structural changes, generalized linear models were used while adjusting for other vascular risk factors. For the assessment of white matter microstructure, principal component analysis led to a reduction in the number of fractional anisotropy variables, followed by regression analysis with major principal components as outcomes.

RESULTS

Males but not females with a younger age at hypertension diagnosis exhibited lower brain gray and white matter volume compared with normotensive controls. The volume of white matter hyperintensities was greater in both males and females with hypertension than normotensive controls, significantly higher in older females with hypertension. Compared with normotensive controls, white matter microstructural integrity was lower in individuals with hypertension, which became more prominent with increasing age.

CONCLUSIONS

Our study demonstrates that the effect of hypertension on cerebral small vessel disease-related brain structure differs by sex and by age at hypertension diagnosis.

The iron burden of cerebral microbleeds contributes to brain atrophy through the mediating effect of white matter hyperintensity

The goal of this work was to explore the total iron burden of cerebral microbleeds (CMBs) using a semi-automatic quantitative susceptibility mapping and to establish its effect on brain atrophy through the mediating effect of white matter hyperintensities (WMH). A total of 95 community-dwelling people were enrolled. Quantitative susceptibility mapping (QSM) combined with a dynamic programming algorithm (DPA) was used to measure the characteristics of 1309 CMBs. WMH were evaluated according to the Fazekas scale, and brain atrophy was assessed using a 2D linear measurement method. Histogram analysis was used to explore the distribution of CMBs susceptibility, volume, and total iron burden, while a correlation analysis was used to explore the relationship between volume and susceptibility. Stepwise regression analysis was used to analyze the risk factors for CMBs and their contribution to brain atrophy. Mediation analysis was used to explore the interrelationship between CMBs and brain atrophy. We found that the frequency distribution of susceptibility of the CMBs was Gaussian in nature with a mean of 201 ppb and a standard deviation of 84 ppb; however, the volume and total iron burden of CMBs were more Rician in nature. A weak but significant correlation between the susceptibility and volume of CMBs was found (r = -0.113, P < 0.001). The periventricular WMH (PVWMH) was a risk factor for the presence of CMBs (number: β = 0.251, P = 0.014; volume: β = 0.237, P = 0.042; total iron burden: β = 0.238, P = 0.020) and was a risk factor for brain atrophy (third ventricle width: β = 0.325, P = 0.001; Evans's index: β = 0.323, P = 0.001). PVWMH had a significant mediating effect on the correlation between CMBs and brain atrophy. In conclusion, QSM along with the DPA can measure the total iron burden of CMBs. PVWMH might be a risk factor for CMBs and may mediate the effect of CMBs on brain atrophy.

Unraveling the Protective Effects of Cognitive Reserve on Cognition and Brain: A Cross-Sectional Study

This study aimed to investigate the hypothesis that brain maintenance expressed in white matter hyperintensities and brain reserves, defined as gray and white matter volumes, mediate the association between cognitive reserve (CR) and cognitive performance. A cross-sectional population-based observational study was conducted, and the final study sample consisted of 763 participants (282 men and 481 women) with a mean age of 61.11 years (±9.0). Data from different categories were collected from study participants, such as demographic, lifestyle, medical, and psycho-social characteristics. All participants underwent a detailed psychometric evaluation (MoCA and DSST) followed by a brain MRI. Volumetric measurements of the total gray matter (GMvol), total white matter (WMvol), and white matter hyperintensities (WMHvol) were performed using the Computational Anatomy Toolbox 12 (CAT12) and Statistical Parametric Maps 12 (SPM12) based on 3D T1-weighted sequence. Significant direct and indirect effects of cognitive reserve on cognitive functioning were measured with both scales-the MoCA and DSST. In each mediation model, the volumes of WMH and GM were significant mediators for the association between cognitive reserve and cognitive performance. This study confirms the importance of strengthening the cognitive reserve in the course of life through potentially modifiable effects on both cognition and the brain.