White Matter Microstructure and Its Relation to Longitudinal Measures of Depressive Symptoms in Mid- and Late Life

The neurostructural consequences of glaucoma and their overlap with disorders exhibiting emotional dysregulations: A voxel-based meta-analysis and tripartite system model

BACKGROUND

Glaucoma, a progressive neurodegenerative disorder leading to irreversible blindness, is associated with heightened rates of generalized anxiety and depression. This study aims to comprehensively investigate brain morphological changes in glaucoma patients, extending beyond visual processing areas, and explores overlaps with morphological alterations observed in anxiety and depression.

METHODS

A comparative meta-analysis was conducted, using case-control studies of brain structural integrity in glaucoma patients. We aimed to identify regions with gray matter volume (GMV) changes, examine their role within distinct large-scale networks, and assess overlap with alterations in generalized anxiety disorder (GAD) and major depressive disorder (MDD).

RESULTS

Glaucoma patients exhibited significant GMV reductions in visual processing regions (lingual gyrus, thalamus). Notably, volumetric reductions extended beyond visual systems, encompassing the left putamen and insula. Behavioral and functional network decoding revealed distinct large-scale networks, implicating visual, motivational, and affective domains. The insular region, linked to pain and affective processes, displayed reductions overlapping with alterations observed in GAD.

LIMITATIONS

While the study identified significant morphological alterations, the number of studies from both the glaucoma and GAD cohorts remains limited due to the lack of independent studies meeting our inclusion criteria.

CONCLUSION

The study proposes a tripartite brain model for glaucoma, with visual processing changes related to the lingual gyrus and additional alterations in the putamen and insular regions tied to emotional or motivational functions. These neuroanatomical changes extend beyond the visual system, implying broader implications for brain structure and potential pathological developments, providing insights into the overall neurological consequences of glaucoma.

Associations of depression and perceived physical fatigability with white matter integrity in older adults

BACKGROUNDS

Fatigability is prevalent in older adults. However, it is often associated with depressed mood. We aim to investigate these two psychobehavioral constructs by examining their underpinning of white matter structures in the brain and their associations with different medical conditions.

METHODS

Twenty-seven older adults with late-life depression (LLD) and 34 cognitively normal controls (CN) underwent multi-shell diffusion MRI. Fatigability was measured with the Pittsburgh Fatigability Scale. We examined white matter integrity by measuring the quantitative anisotropy (QA), a fiber tracking parameter with better accuracy than the traditional imaging technique.

RESULTS

We found those with LLD had lower QA in the 2nd branch of the left superior longitudinal fasciculus (SLF-II), and those with more physical fatigability had lower QA in more widespread brain regions. In tracts associated with more physical fatigability, the lower QA in left acoustic radiation and left superior thalamic radiation correlated with higher blood glucose (r = - 0.46 and - 0.49). In tracts associated with depression, lower QA in left SLF-II correlated with higher bilirubin level (r = - 0.58).

DISCUSSION

Depression and fatigability were associated with various white matter integrity changes, which correlated with biochemistry biomarkers all related to inflammation.

Research status and global trends of late-life depression from 2004 to 2023: bibliometric analysis

Background

Global research hotspots and future research trends in the neurobiological mechanisms of late-life depression (LLD) as well as its diagnosis and treatment are not yet clear.

Objectives

This study profiled the current state of global research on LLD and predicted future research trends in the field.

Methods

Literature with the subject term LLD was retrieved from the Web of Science Core Collection, and CiteSpace software was used to perform econometric and co-occurrence analyses. The results were visualized using CiteSpace, VOSviewer, and other software packages.

Results

In total, 10,570 publications were included in the analysis. Publications on LLD have shown an increasing trend since 2004. The United States and the University of California had the highest number of publications, followed consecutively by China and England, making these countries and institutions the most influential in the field. Reynolds, Charles F. was the author with the most publications. The International Journal of Geriatric Psychiatry was the journal with the most articles and citations. According to the co-occurrence analysis and keyword/citation burst analysis, cognitive impairment, brain network dysfunction, vascular disease, and treatment of LLD were research hotspots.

Conclusion

Late-life depression has attracted increasing attention from researchers, with the number of publications increasing annually. However, many questions remain unaddressed in this field, such as the relationship between LLD and cognitive impairment and dementia, or the impact of vascular factors and brain network dysfunction on LLD. Additionally, the treatment of patients with LLD is currently a clinical challenge. The results of this study will help researchers find suitable research partners and journals, as well as predict future hotspots.

Preliminary Study of White Matter Abnormalities and Associations With the Metabotropic Glutamate Receptor 5 to Distinguish Bipolar and Major Depressive Disorders

Background

Understanding distinct neurobiological mechanisms underlying bipolar disorder (BD) and major depressive disorder (MDD) is crucial for accurate diagnosis and the discovery of novel and more effective targeted treatments. Previous diffusion-weighted MRI studies have suggested some common frontotemporal corticolimbic system white matter (WM) abnormalities across the disorders. However, critical to the development of more precise diagnosis and treatment is identifying distinguishing abnormalities. Promising candidates include more prominent frontotemporal WM abnormalities observed in BD in the uncinate fasciculus (UF) that have been associated with frontal-amygdala functional dysconnectivity, and with suicide that is especially high in BD. Prior work also showed differentiation in metabotropic glutamate receptor 5 (mGlu5) abnormalities in BD versus MDD, which could be a mechanism affected in the frontotemporal system. However, associations between WM and mGlu5 have not been examined previously as a differentiator of BD. Using a multimodal neuroimaging approach, we examined WM integrity alterations in the disorders and their associations with mGluR5 levels.

Methods

Individuals with BD (N = 21), MDD (N = 10), and HC (N = 25) participated in structural and diffusion-weighted MRI scanning, and imaging with [18F]FPEB PET for quantification of mGlu5 availability. Whole-brain analyses were used to assess corticolimbic WM matter fractional anisotropy (FA) across BD and MDD relative to HC; abnormalities were tested for associations with mGlu5 availability.

Results

FA corticolimbic reductions were observed in both disorders and altered UF WM integrity was observed only in BD. In BD, lower UF FA was associated with lower amygdala mGlu5 availability (p < .05).

Conclusions

These novel preliminary findings suggest important associations between lower UF FA and lower amygdala mGlu5 levels that could represent a disorder-specific neural mechanism in which mGluR5 is associated with the frontotemporal dysconnectivity of the disorder.

Vascular risk factors, white matter microstructure, and depressive symptoms: a longitudinal analysis in the UK Biobank

BACKGROUND

Cumulative burden from vascular risk factors (VRFs) has been associated with an increased risk of depressive symptoms in mid- and later life. It has been hypothesised that this association arises because VRFs disconnect fronto-subcortical white matter tracts involved in mood regulation, which puts older adults at higher risk of developing depressive symptoms. However, evidence for the hypothesis that disconnection of white matter tracts underlies the association between VRF burden and depressive symptoms from longitudinal studies is scarce.

METHODS

This preregistered study analysed longitudinal data from 6,964 middle-aged and older adults from the UK Biobank who participated in consecutive assessments of VRFs, brain imaging, and depressive symptoms. Using mediation modelling, we directly tested to what extend white matter microstructure mediates the longitudinal association between VRF burden and depressive symptoms.

RESULTS

VRF burden showed a small association with depressive symptoms at follow-up. However, there was no evidence that fractional anisotropy (FA) of white matter tracts mediated this association. Additional analyses also yielded no mediating effects using alternative operationalisations of VRF burden, mean diffusivity (MD) of single tracts, or overall average of tract-based white matter microstructure (global FA, global MD, white matter hyperintensity volume).

CONCLUSIONS

Our results lend no support to the hypothesis that disconnection of white matter tracts underlies the association between VRF burden and depressive symptoms, while highlighting the relevance of using longitudinal data to directly test pathways linking vascular and mental health.

Brain multi-contrast, multi-atlas segmentation of diffusion tensor imaging and ensemble learning automatically diagnose late-life depression

We investigated the potential of machine learning for diagnostic classification in late-life major depression based on an advanced whole brain white matter segmentation framework. Twenty-six late-life depression and 12 never depressed individuals aged > 55 years, matched for age, MMSE, and education underwent brain diffusion tensor imaging and a multi-contrast, multi-atlas segmentation in MRIcloud. Fractional anisotropy volume, mean fractional anisotropy, trace, axial and radial diffusivity (RD) extracted from 146 white matter parcels for each subject were used to train and test the AdaBoost classifier using stratified 12-fold cross validation. Performance was evaluated using various measures. The statistical power of the classifier was assessed using label permutation test. Statistical analysis did not yield significant differences in DTI measures between the groups. The classifier achieved a balanced accuracy of 71% and an Area Under the Receiver Operator Characteristic Curve (ROC-AUC) of 0.81 by trace, and a balanced accuracy of 70% and a ROC-AUC of 0.80 by RD, in limbic, cortico-basal ganglia-thalamo-cortical loop, brainstem, external and internal capsules, callosal and cerebellar structures. Both indices shared important structures for classification, while fornix was the most important structure for classification by both indices. The classifier proved statistically significant, as trace and RD ROC-AUC scores after permutation were lower than those obtained with the actual data (P = 0.022 and P = 0.024, respectively). Similar results were obtained with the Gradient Boosting classifier, whereas the RBF-kernel Support Vector Machine with k-best feature selection did not exceed the chance level. Finally, AdaBoost significantly predicted the class using all features together. Limitations are discussed. The results encourage further investigation of the implemented methods for computer aided diagnostics and anatomically informed therapeutics.

Pathway-Based Polygenic Risk Scores for Schizophrenia and Associations With Reported Psychotic-like Experiences and Neuroimaging Phenotypes in the UK Biobank

Background

Schizophrenia is a heritable psychiatric disorder with a polygenic architecture. Genome-wide association studies have reported that an increasing number of risk-associated variants and polygenic risk scores (PRSs) explain 17% of the variance in the disorder. Substantial heterogeneity exists in the effect of these variants, and aggregating them based on biologically relevant functions may provide mechanistic insight into the disorder.

Methods

Using the largest schizophrenia genome-wide association study conducted to date, we associated PRSs based on 5 gene sets previously found to contribute to schizophrenia pathophysiology-postsynaptic density of excitatory synapses, postsynaptic membrane, dendritic spine, axon, and histone H3-K4 methylation-along with respective whole-genome PRSs, with neuroimaging (n > 29,000) and reported psychotic-like experiences (n > 119,000) variables in healthy UK Biobank subjects.

Results

Several variables were significantly associated with the axon gene-set (psychotic-like communications, parahippocampal gyrus volume, fractional anisotropy thalamic radiations, and fractional anisotropy posterior thalamic radiations (β range -0.016 to 0.0916, false discovery rate-corrected p [pFDR] ≤ .05), postsynaptic density gene-set (psychotic-like experiences distress, global surface area, and cingulate lobe surface area [β range -0.014 to 0.0588, pFDR ≤ .05]), and histone gene set (entorhinal surface area: β = -0.016, pFDR = .035). From these, whole-genome PRSs were significantly associated with psychotic-like communications (β = 0.2218, pFDR = 1.34 × 10-7), distress (β = 0.1943, pFDR = 7.28 × 10-16), and fractional anisotropy thalamic radiations (β = -0.0143, pFDR = .036). Permutation analysis revealed that these associations were not due to chance.

Conclusions

Our results indicate that genetic variation in 3 gene sets relevant to schizophrenia may confer risk for the disorder through effects on previously implicated neuroimaging variables. Because associations were stronger overall for whole-genome PRSs, findings here highlight that selection of biologically relevant variants is not yet sufficient to address the heterogeneity of the disorder.

Associations of neuroimaging markers with depressive symptoms over time in middle-aged and elderly persons

BACKGROUND

Cerebrovascular disease is regarded as a potential cause of late-life depression. Yet, evidence for associations of neuroimaging markers of vascular brain disease with depressive symptoms is inconclusive. We examined the associations of neuroimaging markers and depressive symptoms in a large population-based study of middle-aged and elderly persons over time.

METHODS

A total of 4943 participants (mean age = 64.6 ± 11.1 years, 55.7% women) from the Rotterdam Study were included. At baseline, total brain volume, gray matter volume, white matter volume, white matter hyperintensities volume, cortical infarcts, lacunar infarcts, microbleeds, white matter fractional anisotropy, and mean diffusivity (MD) were measured with a brain MRI (1.5T). Depressive symptoms were assessed twice with the Center for Epidemiologic Studies Depression scale (median follow-up time: 5.5 years, IQR = 0.9). To assess temporal associations of neuroimaging markers and depressive symptoms, linear mixed models were used.

RESULTS

A smaller total brain volume (β = -0.107, 95% CI -0.192 to -0.022), larger white matter hyperintensities volume (β = 0.047, 95% CI 0.010-0.084), presence of cortical infarcts (β = 0.194, 95% CI 0.047-0.341), and higher MD levels (β = 0.060, 95% CI 0.022-0.098) were cross-sectionally associated with more depressive symptoms. Longitudinal analyses showed that small total brain volume (β = -0.091, 95% CI -0.167 to -0.015) and presence of cortical infarcts (β = 0.168, 95% CI 0.022-0.314) were associated with increasing depressive symptoms over time. After stratification on age, effect sizes were more pronounced at older ages.

CONCLUSIONS

Neuroimaging markers of white matter microstructural damage were associated with depressive symptoms longitudinally in this study of middle-aged and elderly persons. These associations were more pronounced at older ages, providing evidence for the role of white matter structure in late-life depressive symptomatology.

The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder

Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.

The impact of loneliness and social adaptation on depressive symptoms: Behavioral and brain measures evidence from a brain health perspective

Introduction

Early detection of depression is a cost-effective way to prevent adverse outcomes on brain physiology, cognition, and health. Here we propose that loneliness and social adaptation are key factors that can anticipate depressive symptoms.

Methods

We analyzed data from two separate samples to evaluate the associations between loneliness, social adaptation, depressive symptoms, and their neural correlates.

Results

For both samples, hierarchical regression models on self-reported data showed that loneliness and social adaptation have negative and positive effects on depressive symptoms. Moreover, social adaptation reduces the impact of loneliness on depressive symptoms. Structural connectivity analysis showed that depressive symptoms, loneliness, and social adaptation share a common neural substrate. Furthermore, functional connectivity analysis demonstrated that only social adaptation was associated with connectivity in parietal areas.

Discussion

Altogether, our results suggest that loneliness is a strong risk factor for depressive symptoms while social adaptation acts as a buffer against the ill effects of loneliness. At the neuroanatomical level, loneliness and depression may affect the integrity of white matter structures known to be associated to emotion dysregulation and cognitive impairment. On the other hand, socio-adaptive processes may protect against the harmful effects of loneliness and depression. Structural and functional correlates of social adaptation could indicate a protective role through long and short-term effects, respectively. These findings may aid approaches to preserve brain health via social participation and adaptive social behavior.

Altered MRI Diffusion Properties of the White Matter Tracts Connecting Frontal and Thalamic Brain Regions in First-Episode, Drug-Naïve Patients With Postpartum Depression

BACKGROUND

Although progress has been made in exploring postpartum depression (PPD), the involvement of cerebral structure connectivity in PPD patients keeps unclear.

PURPOSE

To explore structural connectivity alternations in mothers with PPD, diffusion tensor imaging (DTI) and automated fiber quantification (AFQ) were used to calculate brain white matter microstructure properties.

STUDY TYPE

Cross-sectional.

POPULATION

A total of 51 women with first-episode, treatment-näive PPD, and 49 matched healthy postpartum women (HPW) controls.

FIELD STRENGTH

A 3.0 T; single-shot echo-planar imaging sequence.

ASSESSMENT

DTI measurements of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) were obtained for 18 specific white matter tracts. The relationship between PDD symptoms, hormone levels, and postpartum days was also investigated.

STATISTICAL TESTS

Two sample t test and Pearson's correlation analysis. The analysis was performed by using a permutation-based multiple-comparison correction approach, with the threshold of P < 0.05 (family wise error corrected [FWE-corrected]) separately across the four different outcome measures.

RESULTS

Women with PPD showed significantly increased FA and AD in right anterior thalamic radiation (ATR) tract and significantly increased FA and significantly reduced RD in the cingulum tract, compared to women without PPD. The RD values of right cingulum were significantly positively correlated with postpartum days in HPW (r = 0.39). There were no significant relationships between brain measures and hormone levels in either patients or controls.

DATA CONCLUSIONS

DTI measures have revealed altered integrity in the white matter of the cortical-thalamic circuits in women with PPD compared to HPW. Damage to these circuits may be a structural basis for the impaired emotional regulation and blunted mother-infant bonding in mothers with PPD and a potential target for the development of new treatments.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 3.

The role of brain structure in the association between pubertal timing and depression risk in an early adolescent sample (the ABCD Study®): A registered report

BACKGROUND

Earlier pubertal timing is associated with higher rates of depressive disorders in adolescence. Neuroimaging studies report brain structural associations with both pubertal timing and depression. However, whether brain structure mediates the relationship between pubertal timing and depression remains unclear.

METHODS

The current registered report examined associations between pubertal timing (indexed via perceived pubertal development), brain structure (cortical and subcortical metrics, and white matter microstructure) and depressive symptoms in a large sample (N = ∼5000) of adolescents (aged 9-13 years) from the Adolescent Brain Cognitive Development (ABCD) Study. We used three waves of follow-up data when the youth were aged 10-11 years, 11-12 years, and 12-13 years, respectively. We used generalised linear-mixed models (H1) and structural equation modelling (H2 & H3) to test our hypotheses.

HYPOTHESES

We hypothesised that earlier pubertal timing at Year 1 would be associated with increased depressive symptoms at Year 3 (H1), and that this relationship would be mediated by global (H2a-b) and regional (H3a-g) brain structural measures at Year 2. Global measures included reduced cortical volume, thickness, surface area and sulcal depth. Regional measures included reduced cortical thickness and volume in temporal and fronto-parietal areas, increased cortical volume in the ventral diencephalon, increased sulcal depth in the pars orbitalis, and reduced fractional anisotropy in the cortico-striatal tract and corpus callosum. These regions of interest were informed by our pilot analyses using baseline ABCD data when the youth were aged 9-10 years.

RESULTS

Earlier pubertal timing was associated with increased depressive symptoms two years later. The magnitude of effect was stronger in female youth and the association remained significant when controlling for parental depression, family income, and BMI in females but not in male youth. Our hypothesised brain structural measures did not however mediate the association between earlier pubertal timing and later depressive symptoms.

CONCLUSION

The present results demonstrate that youth, particularly females, who begin puberty ahead of their peers are at an increased risk for adolescent-onset depression. Future work should explore additional biological and socio-environmental factors that may affect this association so that we can identify targets for intervention to help these at-risk youth.

Elevated homocysteine levels, white matter abnormalities and cognitive impairment in patients with late-life depression

Background

Cognitive impairment in late−life depression (LLD) is considered to be caused by neurodegenerative changes. Elevated homocysteine (Hcy) levels may be linked to cognitive abnormalities associated with LLD. The important role of white matter (WM) damage in cognitive impairment and pathogenesis in patients with LLD has been widely reported. However, no research has explored the interrelationships of these features in patients with LLD.

Objective

The goal of the study was to examine the interrelationship between Hcy levels, cognition, and variations in WM microstructure detected by diffusion tensor imaging (DTI) in patients with LLD.

Methods

We recruited 89 healthy controls (HCs) and 113 patients with LLD; then, we measured the plasma Hcy levels of participants in both groups. All individuals performed a battery of neuropsychological tests to measure cognitive ability. Seventy-four patients with LLD and 68 HCs experienced a DTI magnetic resonance imaging (MRI) scan.

Results

Patients with LLD showed significantly lower fractional anisotropy (FA) values in the bilateral inferior longitudinal fasciculus than those of healthy participants. Only in LLD patients was Hcy concentration inversely associated to FA values in the forceps minor. Finally, multiple regression analyses showed that an interaction between Hcy levels and FA values in the right cingulum of the cingulate cortex and right inferior longitudinal fasciculus were independent contributors to the executive function of patients with LLD.

Conclusion

Our results highlight the complex interplay between elevated homocysteine levels and WM abnormalities in the pathophysiology of LLD-related cognitive impairment, consistent with the neurodegeneration hypothesis.

The enigma of vascular depression in old age: a critical update

Depression is common in older individuals and is associated with high disability and increased mortality, yet the factors predicting late-life depression (LLD) are poorly understood. The relationship between of depressive disorder, age- and disease-related processes have generated pathogenic hypotheses and provided new treatment options. LLD syndrome is often related to a variety of vascular mechanisms, in particular hypertension, cerebral small vessel disease, white matter lesions, subcortical vascular impairment, and other processes (e.g., inflammation, neuroimmune regulatory dysmechanisms, neurodegenerative changes, amyloid accumulation) that may represent etiological factors by affecting frontolimbic and other neuronal networks predisposing to depression. The "vascular depression" hypothesis suggests that cerebrovascular disease (CVD) and vascular risk factors may predispose, induce or perpetuate geriatric depressive disorders. It is based on the presence of various cerebrovascular risk factors in many patients with LLD, its co-morbidity with cerebrovascular lesions, and the frequent development of depression after stroke. Other findings related to vascular depression are atrophy of the medial temporal cortex or generalized cortical atrophy that are usually associated with cognitive impairment. Other pathogenetic hypotheses of LLD, such as metabolic or inflammatory ones, are briefly discussed. Treatment planning should consider there may be a modest response to antidepressants, but several evidence-based and novel treatment options for LLD exist, such as electroconvulsive therapy, transcranial magnetic stimulation, neurobiology-based psychotherapy, as well as antihypertension and antiinflammatory drugs. However, their effectiveness needs further investigation, and new methodologies for prevention and treatment of depression in older individuals should be developed.

White matter fiber microstructure is associated with prior hospitalizations rather than acute symptomatology in major depressive disorder

BACKGROUND

Eighty percent of all patients suffering from major depressive disorder (MDD) relapse at least once in their lifetime. Thus, understanding the neurobiological underpinnings of the course of MDD is of utmost importance. A detrimental course of illness in MDD was most consistently associated with superior longitudinal fasciculus (SLF) fiber integrity. As similar associations were, however, found between SLF fiber integrity and acute symptomatology, this study attempts to disentangle associations attributed to current depression from long-term course of illness.

METHODS

A total of 531 patients suffering from acute (N = 250) or remitted (N = 281) MDD from the FOR2107-cohort were analyzed in this cross-sectional study using tract-based spatial statistics for diffusion tensor imaging. First, the effects of disease state (acute v. remitted), current symptom severity (BDI-score) and course of illness (number of hospitalizations) on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity were analyzed separately. Second, disease state and BDI-scores were analyzed in conjunction with the number of hospitalizations to disentangle their effects.

RESULTS

Disease state (p_FWE < 0.042) and number of hospitalizations (p_FWE< 0.032) were associated with decreased FA and increased MD and RD in the bilateral SLF. A trend was found for the BDI-score (p_FWE > 0.067). When analyzed simultaneously only the effect of course of illness remained significant (p_FWE < 0.040) mapping to the right SLF.

CONCLUSIONS

Decreased FA and increased MD and RD values in the SLF are associated with more hospitalizations when controlling for current psychopathology. SLF fiber integrity could reflect cumulative illness burden at a neurobiological level and should be targeted in future longitudinal analyses.

Brain structural associations with depression in a large early adolescent sample (the ABCD study®)

BACKGROUND

Depression is the leading cause of disability worldwide with > 50% of cases emerging before the age of 25 years. Large-scale neuroimaging studies in depression implicate robust structural brain differences in the disorder. However, most studies have been conducted in adults and therefore, the temporal origins of depression-related imaging features remain largely unknown. This has important implications for understanding aetiology and informing timings of potential intervention.

METHODS

Here, we examine associations between brain structure (cortical metrics and white matter microstructural integrity) and depression ratings (from caregiver and child), in a large sample (N = 8634) of early adolescents (9 to 11 years old) from the US-based, Adolescent Brain and Cognitive Development (ABCD) Study®. Data was collected from 2016 to 2018.

FINDINGS

We report significantly decreased global cortical and white matter metrics, and regionally in frontal, limbic and temporal areas in adolescent depression (Cohen's d = -0⋅018 to -0⋅041, β = -0·019 to -0⋅057). Further, we report consistently stronger imaging associations for caregiver-reported compared to child-reported depression ratings. Divergences between reports (caregiver vs child) were found to significantly relate to negative socio-environmental factors (e.g., family conflict, absolute β = 0⋅048 to 0⋅169).

INTERPRETATION

Depression ratings in early adolescence were associated with similar imaging findings to those seen in adult depression samples, suggesting neuroanatomical abnormalities may be present early in the disease course, arguing for the importance of early intervention. Associations between socio-environmental factors and reporter discrepancy warrant further consideration, both in the wider context of the assessment of adolescent psychopathology, and in relation to their role in aetiology.

FUNDING

Wellcome Trust (References: 104036/Z/14/Z and 220857/Z/20/Z) and the Medical Research Council (MRC, Reference: MC_PC_17209).

Brain-based mechanisms of late-life depression: Implications for novel interventions

Late-life depression (LLD) is a particularly debilitating illness. Older adults suffering from depression commonly experience poor outcomes in response to antidepressant treatments, medical comorbidities, and declines in daily functioning. This review aims to further our understanding of the brain network dysfunctions underlying LLD that contribute to disrupted cognitive and affective processes and corresponding clinical manifestations. We provide an overview of a network model of LLD that integrates the salience network, the default mode network (DMN) and the executive control network (ECN). We discuss the brain-based structural and functional mechanisms of LLD with an emphasis on their link to clinical subtypes that often fail to respond to available treatments. Understanding the brain networks that underlie these disrupted processes can inform the development of targeted interventions for LLD. We propose behavioral, cognitive, or computational approaches to identifying novel, personalized interventions that may more effectively target the key cognitive and affective symptoms of LLD.

Digital sleep measures and white matter health in the Framingham Heart Study

AIM

Impaired sleep quality and sleep oxygenation are common sleep pathologies. This study assessed the impact of these abnormalities on white matter (WM) integrity in an epidemiological cohort.

METHODS

The target population was the Framingham Heart Study Generation-2/Omni-1 Cohorts. Magnetic resonance imaging (diffusion tensor imaging) was used to assess WM integrity. Wearable digital devices were used to assess sleep quality: the (M1-SleepImage™ system) and the Nonin WristOx for nocturnal oxygenation. The M1 device collects trunk actigraphy and the electrocardiogram (ECG); sleep stability indices were computed using cardiopulmonary coupling using the ECG. Two nights of recording were averaged.

RESULTS

Stable sleep was positively associated with WM health. Actigraphic periods of wake during the sleep period were associated with increased mean diffusivity. One marker of sleep fragmentation which covaries with respiratory chemoreflex activation was associated with reduced fractional anisotropy and increased mean diffusivity. Both oxygen desaturation index and oxygen saturation time under 90% were associated with pathological directions of diffusion tensor imaging signals. Gender differences were noted across most variables, with female sex showing the larger and significant impact.

CONCLUSIONS

Sleep quality assessed by a novel digital analysis and sleep hypoxia was associated with WM injury, especially in women.

White matter abnormalities in adults with bipolar disorder type-II and unipolar depression

Discerning distinct neurobiological characteristics of related mood disorders such as bipolar disorder type-II (BD-II) and unipolar depression (UD) is challenging due to overlapping symptoms and patterns of disruption in brain regions. More than 60% of individuals with UD experience subthreshold hypomanic symptoms such as elevated mood, irritability, and increased activity. Previous studies linked bipolar disorder to widespread white matter abnormalities. However, no published work has compared white matter microstructure in individuals with BD-II vs. UD vs. healthy controls (HC), or examined the relationship between spectrum (dimensional) measures of hypomania and white matter microstructure across those individuals. This study aimed to examine fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) across BD-II, UD, and HC groups in the white matter tracts identified by the XTRACT tool in FSL. Individuals with BD-II (n = 18), UD (n = 23), and HC (n = 24) underwent Diffusion Weighted Imaging. The categorical approach revealed decreased FA and increased RD in BD-II and UD vs. HC across multiple tracts. While BD-II had significantly lower FA and higher RD values than UD in the anterior part of the left arcuate fasciculus, UD had significantly lower FA and higher RD values than BD-II in the area of intersections between the right arcuate, inferior fronto-occipital and uncinate fasciculi and forceps minor. The dimensional approach revealed the depression-by-spectrum mania interaction effect on the FA, RD, and AD values in the area of intersection between the right posterior arcuate and middle longitudinal fasciculi. We propose that the white matter microstructure in these tracts reflects a unique pathophysiologic signature and compensatory mechanisms distinguishing BD-II from UD.

Myelin deficits in patients with recurrent major depressive disorder: An inhomogeneous magnetization transfer study

PURPOSES

The recently developed myelin imaging method, inhomogeneous magnetization transfer (ihMT), is a surrogate measure of myelin content. The goal of the current study was to investigate alterations in myelin integrity in patients with recurrent major depressive disorder (rMDD).

METHODS

Fifty-two patients with rMDD (36 female and 16 male) and 42 healthy controls (HC, 29 female and 13 male) were included. Two ihMT indices, quantitative ihMT (qihMT) and quantitative MT (qMT), were estimated from the ihMT data. A 50 white matter atlas was used to extract the regional quantitative values for each subject. The differences in qihMT and qMT values between the rMDD and HC groups were compared by a general linear model. Pearson correlation analyses were conducted to investigate associations between the significantly altered ihMT indices and clinical measures (Hamilton Depression Rating Scale scores and disease duration) in rMDD group.

RESULTS

The rMDD group showed significantly lower qihMT values in the fornix, left anterior limb of internal capsule, and left sagittal stratum, and lower qMT values in the fornix and left anterior limb of internal capsule than those of the HC group (p < 0.05, false discovery rate corrected). Both the qihMT and qMT values in the fornix of patients with rMDD were negatively correlated with disease duration (qihMT: r = -0.478, p < 0.001, Bonferroni corrected; qMT: r = -0.433, p = 0.001, Bonferroni corrected).

CONCLUSION

Our findings suggested that rMDD is associated with myelin impairment in the fornix, left anterior limb of internal capsule, and left sagittal stratum. In addition, this disruption of myelin integrity in the fornix could be cumulative as the disease progresses.

Ketamine Normalizes the Structural Alterations of Inferior Frontal Gyrus in Depression

Background

Ketamine is a novel fast-acting antidepressant. Acute ketamine treatment can reverse microstructure deficits and normalize functional alterations in the brain, but little is known about the impacts of ketamine on brain volumes in individuals with depression.

Methods

We used 3 T magnetic resonance imaging (MRI) and tensorbased morphological methods to investigate the regional volume differences for 29 healthy control (HC) subjects and 21 subjects with major depressive disorder (MDD), including 10 subjects with comorbid post-traumatic stress disorder (PTSD). All the subjects participated in MRI scanning before and 24 h post intravenous ketamine infusion. The effects of acute ketamine administration on HC, MDD, and MDD/PTSD groups were examined separately by whole-brain voxel-wise t-tests.

Results

Our data showed smaller volume of inferior frontal gyrus (IFG, opercular part) in MDD and MDD/PTSD subjects compared to HC, and a significant correlation between opercular IFG volume and depressive severity in MDD subjects only. Ketamine administration normalized the structural alterations of opercular IFG in both MDD and MDD/PTSD groups, and significantly improved depressive and PTSD symptoms. Twenty-four hours after a single ketamine infusion, there were two clusters of voxels with volume changes in MDD subjects, including significantly increased volumes of opercular IFG. No significant structural alterations were found in the MDD/PTSD or HC groups.

Conclusion

These findings provide direct evidence that acute ketamine administration can normalize structural alterations associated with depression and highlight the importance of IFG in the guidance of future therapeutic targets.

Neural substrates for late-life depression: A selective review of structural neuroimaging studies

Recent neuroimaging studies have characterized the pathophysiology of late-life depression (LLD) as a dysfunction of the brain networks involved in the regulation of emotion, motivational behavior, cognitive control, executive function, and self-referential thinking. In this article, we reviewed LLD-associated structural neuroimaging markers such as white matter hyperintensity (WMH), white matter integrity measured by diffusion tensor imaging, cortical and subcortical volumes, and cortical thickness, which may provide a structural basis for brain network dysfunction in LLD. LLD was associated with greater severity or volumes of deep, periventricular, or overall WMH and with decreased white matter integrity in the brain regions belonging to the fronto-striatal-limbic circuits and reduced white matter tract integrity which connects these circuits, such as the cingulum, corpus callosum, or uncinate fasciculus. Decreased volumes or cortical thickness in the prefrontal cortex, orbitofrontal cortex, anterior and posterior cingulate cortex, several temporal and parietal regions, hippocampus, amygdala, striatum, thalamus, and the insula were associated with LLD. These structural neuroimaging findings were also associated with cognitive dysfunction, which is a prominent clinical feature in LLD. Several structural neuroimaging markers including the WMH burden, white matter integrity, and cortical and subcortical volumes predicted antidepressant response in LLD. These structural neuroimaging findings support the hypothesis that disruption of the brain networks involved in emotion regulation and cognitive processing by impaired structural connectivity is strongly associated with the pathophysiology of LLD.

Automated classification of depression from structural brain measures across two independent community-based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case-control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically-ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well-phenotyped community-based group of current MDD cases with clinical interview-based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, 'STRADL'). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types-SVM, penalised logistic regression or decision tree-either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population-based sample with self-reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses-remitted MDD in STRADL, and lifetime-experienced MDD in UK Biobank. The highest cross-validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self-reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime-experienced MDD (52.68-60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.

Aging and Positive Mood: Longitudinal Neurobiological and Cognitive Correlates

OBJECTIVE

Despite the losses commonly associated with aging, older adults seem to possess particularly preserved emotional regulation. To further understand this phenomenon, the authors examined longitudinal trajectories between age, depressive symptoms, brain structure, and cognition.

METHODS

Seven hundred and sixteen functionally intact older adults (age M = 67.9, 56.8% female), followed longitudinally (visit range: 1-13, M = 2.5), completed cognitive testing and the Geriatric Depression Scale (GDS). A subset (N = 327) underwent 3T brain MRI. Mixed-effects linear regression models were conducted controlling for sex, education, and total intracranial volume.

RESULTS

There was a significant interaction between age and time on GDS, such that GDS improved with increasing age over time, but attenuated around age 71 (age*time b = 0.10, p <0.001). Fractional anisotropy (FA) and mean diffusivity interacted with age to predict longitudinal changes in GDS (FA: b = -0.02, p = 0.01; MD: b = 0.03, p = 0.007), such that age-related benefits on GDS were attenuated in those with declining FA. Executive function (EF) and processing speed also interacted with age to predict longitudinal changes in GDS (EF: b = -0.04, p = 0.03; speed: b = 0.04, p = 0.04). Again, the positive effect of age on GDS attenuated in those with worsening EF and speed. There were no associations with memory, semantic fluency, or gray matter (p values >0.05).

CONCLUSION

EF, processing speed, and white matter integrity moderated the longitudinal relationship between age and mood. Previous studies demonstrate the link between positivity and better cognitive control, leading to improved mood in older adults. Our results are not only consistent, but establish a potential neurobiological correlate. Future research further exploring biological mechanisms driving psychological processes may have important therapeutic implications.

A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank

Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery (N = 10,674) and replication (N = 11,214) imaging sample from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure (β: 0.125 to 0.868, p_FDR < 0.043). Several behavioural traits are also associated with depression-PRS (β: 0.014 to 0.180, p_FDR: 0.049 to 1.28 × 10⁻¹⁴) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

Age-Related Changes of Peak Width Skeletonized Mean Diffusivity (PSMD) Across the Adult Lifespan: A Multi-Cohort Study

Parameters of water diffusion in white matter derived from diffusion-weighted imaging (DWI), such as fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, AD, and RD), and more recently, peak width of skeletonized mean diffusivity (PSMD), have been proposed as potential markers of normal and pathological brain ageing. However, their relative evolution over the entire adult lifespan in healthy individuals remains partly unknown during early and late adulthood, and particularly for the PSMD index. Here, we gathered and analyzed cross-sectional diffusion tensor imaging (DTI) data from 10 population-based cohort studies in order to establish the time course of white matter water diffusion phenotypes from post-adolescence to late adulthood. DTI data were obtained from a total of 20,005 individuals aged 18.1 to 92.6 years and analyzed with the same pipeline for computing skeletonized DTI metrics from DTI maps. For each individual, MD, AD, RD, and FA mean values were computed over their FA volume skeleton, PSMD being calculated as the 90% peak width of the MD values distribution across the FA skeleton. Mean values of each DTI metric were found to strongly vary across cohorts, most likely due to major differences in DWI acquisition protocols as well as pre-processing and DTI model fitting. However, age effects on each DTI metric were found to be highly consistent across cohorts. RD, MD, and AD variations with age exhibited the same U-shape pattern, first slowly decreasing during post-adolescence until the age of 30, 40, and 50 years, respectively, then progressively increasing until late life. FA showed a reverse profile, initially increasing then continuously decreasing, slowly until the 70s, then sharply declining thereafter. By contrast, PSMD constantly increased, first slowly until the 60s, then more sharply. These results demonstrate that, in the general population, age affects PSMD in a manner different from that of other DTI metrics. The constant increase in PSMD throughout the entire adult life, including during post-adolescence, indicates that PSMD could be an early marker of the ageing process.