Alterations in white matter microarchitecture in adolescents and young adults with major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging

Association between segmental alterations of white matter bundles and cognitive performance in first-episode, treatment-naïve young adults with major depressive disorder

BACKGROUND

Cumulative evidence has consistently shown that white matter (WM) disruption is associated with cognitive decline in geriatric depression. However, limited research has been conducted on the correlation between these lesions and cognitive performance in untreated young adults with major depressive disorder (MDD), particularly with the specific segmental alterations of the fibers.

METHOD

iffusion tensor images were performed on 60 first-episode, treatment-naïve young adult patients with MDD and 54 matched healthy controls (HCs). Automated fiber quantification was applied to calculate the tract profiles of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) to evaluate the WM microstructural organization. Correlation analysis was performed to find the associations between the diffusion properties and cognitive performance.

RESULTS

Compared with HCs, patients with MDD exhibited predominantly different diffusion properties in bilateral uncinate fasciculus (UF), corticospinal tracts (CSTs), left superior longitudinal fasciculus and anterior thalamic radiation. The FA of the temporal cortex portion of right UF was positively correlated with working memory. The MD of the temporal component of left UF was negatively correlated with working memory and positively correlated with symptom severity. Additionally, a positive correlation between the MD of left CST and the psychomotor speed, negative correlation between the MD of left CST and the executive functions and complex attentional processes were observed.

CONCLUSIONS

Our study validated the alterations in spatial localization of WM microstructure and its correlations with cognitive performance in first-episode, treatment-naïve young adults with MDD. This study added to the knowledge of the neuropathological basis of MDD.

Association Between White Matter Tract Integrity and Frontal-Executive Function in Non-Geriatric Adult Patients With Major Depressive Disorder

OBJECTIVE

This study investigated the association between white matter tract integrity and frontal executive function in adult non-geriatric patients with major depressive disorder (MDD) and healthy controls (HCs) using diffusion tensor imaging (DTI).

METHODS

In total, 57 patients with MDD and 115 HCs participated in this study. We calculated the integrity of the white matter tracts using the Tracts Constrained by Underlying Anatomy tool (TRACULA) from FreeSurfer. We performed cognitive function tests. Oneway analysis of covariance was used to investigate the DTI parameters as dependent variables; diagnosis of MDD as an independent variable; and age, sex, and education level as covariates. For correlation analysis between the DTI parameters and cognitive function tests, Pearson's partial correlation analyses were performed in the MDD and HC groups.

RESULTS

The patients with MDD showed significantly decreased axial diffusivity (AD) in forceps major (FMajor), left corticospinal tract (CST), left superior longitudinal fasciculus-parietal bundle (SLFP), right anterior thalamic radiation (ATR), right CST, right inferior longitudinal fasciculus (ILF) and right superior longitudinal fasciculus-temporal bundle (SLFT) and mean diffusivity (MD) in the left CST, right CST, and right SLFT compared to HCs. We found that non-geriatric patients with MDD showed a significant negative correlation between the response time in the Stroop task and the AD value of the FMajor.

CONCLUSION

Our findings suggest that impaired structural connectivity in the FMajor may be associated with cognitive dysfunction in non-geriatric patients with MDD.

Systematic Review: White Matter Microstructural Organization in Adolescents With Depression

Objective

A growing body of literature has focused on the neural mechanisms of depression. Our goal was to conduct a systematic review on the white matter microstructural differences in adolescents with depressive disorders vs adolescents without depressive disorders.

Method

We searched PubMed and PsycINFO for publications on August 3, 2022 (original search conducted in July 2021). The review was registered on PROSPERO (registration number: CRD42021268200), and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Eligible studies were original research papers comparing diffusion tensor/spectrum imaging findings in adolescents with vs without depression (originally ages 12-19 years, later expanded to 11-21 years). Studies were excluded if they focused on depression exclusively in the context of another condition, used only dimensional depressive symptom assessment(s), or used the same dataset as another included publication.

Results

The search yielded 575 unique records, of which 14 full-text papers were included (824 adolescents with depression and 686 without depression). The following white matter regions showed significant differences in fractional anisotropy in at least 3 studies: uncinate fasciculus, cingulum, anterior corona radiata, inferior fronto-occipital fasciculus, and corpus callosum (genu and body). Most studies reported decreased, rather than increased, fractional anisotropy in adolescents with depression. Limitations include the possibility for selective reporting bias and risk of imprecision, given the small sample sizes in some studies.

Conclusion

Our systematic review suggests aberrant white matter microstructure in limbic-cortical-striatal-thalamic circuits, and the corpus callosum, in adolescents with depression. Future research should focus on developmental trajectories in depression, identifying sources of heterogeneity and integrating findings across imaging modalities.

Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits

BACKGROUND

The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders.

METHODS

We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits.

RESULTS

We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10-8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10-6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = -0.09, SE = 0.03; p = 5.9 × 10-3) and drinks consumed per week (rg = -0.09, SE = 0.02; p = 4.8 × 10-4), and volume of the mid-anterior subregion with BD (rg = -0.12, SE = 0.02; p = 2.5 × 10-4), major depressive disorder (MDD) (rg = -0.12, SE = 0.04; p = 3.6 × 10-3), drinks consumed per week (rg = -0.13, SE = 0.04; p = 1.8 × 10-3) and cannabis use (rg = -0.09, SE = 0.03; p = 8.4 × 10-3).

CONCLUSIONS

Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

A meta-analysis on the uncinate fasciculus in depression

Aberrant microstructure of the uncinate fasciculus (UNC), a white matter (WM) tract implicated in emotion regulation, has been hypothesized as a neurobiological mechanism of depression. However, studies testing this hypothesis have yielded inconsistent results. The present meta-analysis consolidates evidence from 44 studies comparing fractional anisotropy (FA) and radial diffusivity (RD), two metrics characterizing WM microstructure, of the UNC in individuals with depression (n = 5016) to healthy individuals (n = 18 425). We conduct meta-regressions to identify demographic and clinical characteristics that contribute to cross-study heterogeneity in UNC findings. UNC FA was reduced in individuals with depression compared to healthy individuals. UNC RD was comparable between individuals with depression and healthy individuals. Comorbid anxiety explained inter-study heterogeneity in UNC findings. Depression is associated with perturbations in UNC microstructure, specifically with respect to UNC FA and not UNC RD. The association between depression and UNC microstructure appears to be moderated by anxiety. Future work should unravel the cellular mechanisms contributing to aberrant UNC microstructure in depression; clarify the relationship between UNC microstructure, depression, and anxiety; and link UNC microstructure to psychological processes, such as emotion regulation.

Personalized Diagnosis and Treatment for Neuroimaging in Depressive Disorders

Depressive disorders are highly heterogeneous in nature. Previous studies have not been useful for the clinical diagnosis and prediction of outcomes of major depressive disorder (MDD) at the individual level, although they provide many meaningful insights. To make inferences beyond group-level analyses, machine learning (ML) techniques can be used for the diagnosis of subtypes of MDD and the prediction of treatment responses. We searched PubMed for relevant studies published until December 2021 that included depressive disorders and applied ML algorithms in neuroimaging fields for depressive disorders. We divided these studies into two sections, namely diagnosis and treatment outcomes, for the application of prediction using ML. Structural and functional magnetic resonance imaging studies using ML algorithms were included. Thirty studies were summarized for the prediction of an MDD diagnosis. In addition, 19 studies on the prediction of treatment outcomes for MDD were reviewed. We summarized and discussed the results of previous studies. For future research results to be useful in clinical practice, ML enabling individual inferences is important. At the same time, there are important challenges to be addressed in the future.