To model cognitive reserve (CR) longitudinally in a neurodiverse pediatric sample using a residual index approach, and to test the criterion and construct validity of this index.

Participants were N = 115 children aged 9.5–13 years at baseline (MAge = 10.48 years, SDAge = 0.61), and n = 43 (37.4%) met criteria for ADHD. The CR index represented variance in Matrix Reasoning scores from the WASI that was unexplained by MRI-based brain variables (bilateral hippocampal volumes, total gray matter volumes, and total white matter hypointensity volumes) or demographics (age and sex).

At baseline, the CR index predicted math computation ability (estimate = 0.50, SE = 0.07, p < .001), and word reading ability (estimate = 0.26, SE = 0.10, p = .012). Longitudinally, change in CR over time was not associated with change in math computation ability (estimate = −0.02, SE = 0.03, p < .513), but did predict change in word reading ability (estimate = 0.10, SE = 0.03, p < .001). Change in CR was also found to moderate the relationship between change in word reading ability and white matter hypointensity volume (estimate = 0.10, SE = 0.05, p = .045).

Evidence for the criterion validity of this CR index is encouraging, but somewhat mixed, while construct validity was evidenced through interaction between CR, brain, and word reading ability. Future research would benefit from optimization of the CR index through careful selection of brain variables for a pediatric sample.

Geriatric depression (GD) is associated with significant medical comorbidity, cognitive impairment, brain atrophy, premature mortality, and suboptimal treatment response. While apathy and anxiety are common comorbidities, resilience is a protective factor. Understanding the relationships between brain morphometry, depression, and resilience in GD could inform clinical treatment. Only few studies have addressed gray matter volume (GMV) associations with mood and resilience.

Forty-nine adults aged >60 years (38 women) with major depressive disorder undergoing concurrent antidepressant treatment participated in the study.

Anatomical T1-weighted scans, apathy, anxiety, and resilience data were collected. Freesurfer 6.0 was used to preprocess T1-weighted images and qdec to perform voxel-wise whole-brain analyses. Partial Spearman correlations controlling for age and sex tested the associations between clinical scores, and general linear models identified clusters of associations between GMV and clinical scores, with age and sex as covariates. Cluster correction and Monte-Carlo simulations were applied (corrected alpha = 0.05).

Greater depression severity was associated with greater anxiety (r = 0.53, p = 0.0001), lower resilience (r = −0.33, p = 0.03), and greater apathy (r = 0.39, p = 0.01). Greater GMV in widespread, partially overlapping clusters across the brain was associated with reduced anxiety and apathy, as well as increased resilience.

Our results suggest that greater GMV in extended brain regions is a potential marker for resilience in GD, while GMV in more focal and overlapping regions may be markers for depression and anxiety. Interventions focused on improving symptoms in GD may seek to examine their effects on these brain regions.

Major depressive disorder (MDD) is a serious psychiatric disorder marked by low mood and anhedonia. Understanding the neural mechanism of MDD is essential for the treatment of depression. White matter fibres, connecting different computational units in the brain, have an important effect on brain function; however, the mechanism of white matter fibre abnormality in MDD is still unclear.

Our study expected to find white matter abnormalities associated with the frontal lobe and hippocampus in individuals with MDD.

Using diffusion tensor imaging data and tract-based spatial statistics, we investigated the microstructural differences in white matter fibre tracts between 30 adults with MDD compared with 31 healthy controls, and calculated the association between MDD-related microstructural changes and illness duration.

It was found that patients with MDD showed reduced fractional anisotropy in the genu and body of the corpus callosum, right corona radiata and part of the thalamic radiations, suggesting lower fibrous myelination levels in these regions; the decreased fractional anisotropy in these regions was associated with longer illness duration.

Our results suggest that MDD may be associated with microstructural damage of key fibre tracts, which could provide insights into the understanding and treatment of MDD.

Previous studies have shown that socioeconomically deprived groups exhibit higher lesion load of the white matter (WM) in aging. The aim of this study was to (i) investigate to what extent education and income may contribute to differences in white matter hyperintensities (WMHs) and (ii) identify risk profiles related to a higher prevalence of age-associated WMH.

Population-based adult study of the Leipzig Research Centre for Civilization Diseases (LIFE) in Leipzig, Germany.

Dementia-free sample aged 40–80 years (n = 1,185) derived from the population registry.

Information was obtained in standardized interviews. WMH (including the derived Fazekas scores) were assessed using automated segmentation of high-resolution T1-weighted anatomical and fluid-attenuated inversion recovery (FLAIR) MRI acquired at 3T.

Despite a significant association between income and WMH in univariate analyses, results from adjusted models (age, gender, arterial hypertension, heart disease, and APOE e4 allele) indicated no association between income and WMH. Education was associated with Fazekas scores, but not with WMH and not after Bonferroni correction. Prevalence of some health-related risk factors was significantly higher among low-income/education groups. After combining risk factors in a factor analysis, results from adjusted models indicated significant associations between higher distress and more WMH as well as between obesity and more deep WMH.

Previously observed differences in WMH between socioeconomically deprived groups might stem from differences in health-related risk factors. These risk factors should be targeted in prevention programs tailored to socioeconomically deprived individuals.

Childhood trauma and adversity are common across societies and have strong associations with physical and psychiatric morbidity throughout the life-course. One possible mechanism through which childhood trauma may predispose individuals to poor psychiatric outcomes is via associations with brain structure. This study aimed to elucidate the associations between childhood trauma and brain structure across two large, independent community cohorts.

The two samples comprised (i) a subsample of Generation Scotland (n=1,024); and (ii) individuals from UK Biobank (n=27,202). This comprised n=28,226 for mega-analysis. MRI scans were processed using Free Surfer, providing cortical, subcortical, and global brain metrics. Regression models were used to determine associations between childhood trauma measures and brain metrics and psychiatric phenotypes.

Childhood trauma associated with lifetime depression across cohorts (OR 1.06 GS, 1.23 UKB), and related to early onset and recurrent course within both samples. There was evidence for associations between childhood trauma and structural brain metrics. This included reduced global brain volume, and reduced cortical surface area with highest effects in the frontal (β=−0.0385, SE=0.0048, p(FDR)=5.43x10−15) and parietal lobes (β=−0.0387, SE=0.005, p(FDR)=1.56x10−14). At a regional level the ventral diencephalon (VDc) displayed significant associations with childhood trauma measures across both cohorts and at mega-analysis (β=−0.0232, SE=0.0039, p(FDR)=2.91x10−8). There were also associations with reduced hippocampus, thalamus, and nucleus accumbens volumes.

Associations between childhood trauma and reduced global and regional brain volumes were found, across two independent UK cohorts, and at mega-analysis. This provides robust evidence for a lasting effect of childhood adversity on brain structure.