Serum Glial Fibrillary Acidic Protein and Neurofilament Light Chain Levels Reflect Different Mechanisms of Disease Progression under B-Cell Depleting Treatment in Multiple Sclerosis.

OBJECTIVE: To investigate the longitudinal dynamics of serum glial fibrillary acidic protein (sGFAP) and serum neurofilament light chain (sNfL) levels in people with multiple sclerosis (pwMS) under B-cell depleting therapy (BCDT) and their capacity to prognosticate future progression independent of relapse activity (PIRA) events. METHODS: A total of 362 pwMS (1,480 samples) starting BCDT in the Swiss Multiple Sclerosis (MS) Cohort were included. sGFAP levels in 2,861 control persons (4,943 samples) provided normative data to calculate adjusted Z scores. RESULTS: Elevated sGFAP levels (Z score >1) at 1 year were associated with a higher hazard for PIRA (hazard ratio [HR]: 1.80 [95% CI: 1.17-2.78]; p = 0.0079) than elevated sNfL levels (HR, 1.45 [0.95-2.24], p = 0.0886) in a combined model. Independent of PIRA events, sGFAP levels longitudinally increased by 0.49 Z score units per 10 years follow-up (estimate, 0.49 [0.29, 0.69], p < 0.0001). In patients experiencing PIRA, sGFAP Z scores were 0.52 Z score units higher versus stable patients (0.52 [0.22, 0.83], p = 0.0009). Different sNfL Z score trajectories were found in pwMS with versus without PIRA (interaction p = 0.0028), with an average decrease of 0.92 Z score units per 10 years observed without PIRA (-0.92 [-1.23, -0.60], p < 0.0001), whereas levels in patients with PIRA remained high. INTERPRETATION: Elevated sGFAP and lack of drop in sNfL after BCDT start are associated with increased risk of future PIRA. These findings provide a rationale for combined monitoring of sNfL and sGFAP in pwMS starting BCDT to predict the risk of PIRA, and to use sGFAP as an outcome in clinical trials aiming to impact on MS progressive disease biology. ANN NEUROL 2024.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders : Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group.

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Major depressive disorder: Findings of reduced homotopic connectivity and investigation of underlying structural mechanisms.

Depression has been associated with various alterations in magnetic resonance imaging (MRI) derived resting-state functional connectivity. Recently, homotopic connectivity, defined as functional connectivity between homotopic regions across hemispheres, has been reported to be reduced in patients with major depressive disorder (MDD). However, little is known about structural factors underlying alterations of homotopic connectivity, which would contribute to the understanding of the altered neurophysiological architecture in patients with MDD. We compared 368 patients with MDD and 461 never-depressed controls regarding voxel-mirrored homotopic connectivity (VMHC) and potential underlying mechanisms such as the structural connectivity of the corpus callosum, measured by DTI-derived fractional anisotropy (FA), and left-right symmetries in homotopic gray matter volumes. Compared to controls, patients with MDD exhibited reduced VMHC in the cuneus, putamen, superior temporal gyrus, insula, and precuneus. Within these regions, no differences in left-right symmetries in homotopic gray matter volumes were evident across cohorts. FA of the corpus callosum correlated with VMHC in the entire sample. However, patients with MDD and controls did not differ with regard to callosal FA. The findings indicate that MDD is associated with a loss of interhemispheric synchrony in regions known to be implicated in self-referential and reward processing. They also suggest that additional mechanisms are implicated in altered homotopic connectivity of patients with MDD, other than direct callosal fiber pathways or asymmetries in homotopic gray matter volumes.

Serum neurofilament light and white matter characteristics in the general population: a longitudinal analysis.

Neurofilament light polypeptide (NfL) is a component of the neuronal cytoskeleton and particularly abundant in large-caliber axons. When axonal injury occurs, NfL is released and reaches the cerebrospinal fluid and the blood. Associations between NfL and white matter alterations have previously been observed in studies based on patients with neurological diseases. The current study aimed to explore the relationship between serum NfL (sNfL) and white matter characteristics in a population-based sample. The cross-sectional associations between sNfL as dependent variable, fractional anisotropy (FA), and white matter lesion (WML) volume were analyzed with linear regression models in 307 community-dwelling adults aged between 35 and 65 years. These analyses were repeated with additional adjustment for the potential confounders age, sex, and body mass index (BMI). Longitudinal associations over a mean follow-up of 5.39 years were analyzed with linear mixed models. The unadjusted cross-sectional models yielded significant associations between sNfL, WML volume, and FA, respectively. However, after the adjustment for confounders, these associations did not reach significance. In the longitudinal analyses, the findings corroborated the baseline findings showing no significant associations between sNfL and white matter macrostructure and microstructure beyond the effects of age. In synopsis with previous studies in patients with acute neurological diseases showing a significant association of sNfL with white matter changes beyond the effects of age, the present results based on a sample from the general population suggest the perspective that changes in sNfL reflect age-related effects that also manifest in altered white matter macrostructure and microstructure.

Phenotypic and genome-wide studies on dicarbonyls: major associations to glomerular filtration rate and gamma-glutamyltransferase activity.

BACKGROUND: The dicarbonyl compounds methylglyoxal (MG), glyoxal (GO) and 3-deoxyglucosone (3-DG) have been linked to various diseases. However, disease-independent phenotypic and genotypic association studies with phenome-wide and genome-wide reach, respectively, have not been provided. METHODS: MG, GO and 3-DG were measured by LC-MS in 1304 serum samples of two populations (KORA, n = 482; BiDirect, n = 822) and assessed for associations with genome-wide SNPs (GWAS) and with phenome-wide traits. Redundancy analysis (RDA) was used to identify major independent trait associations. FINDINGS: Mutual correlations of dicarbonyls were highly significant, being stronger between MG and GO (ρ = 0.6) than between 3-DG and MG or GO (ρ = 0.4). Significant phenotypic results included associations of all dicarbonyls with sex, waist-to-hip ratio, glomerular filtration rate (GFR), gamma-glutamyltransferase (GGT), and hypertension, of MG and GO with age and C-reactive protein, of GO and 3-DG with glucose and antidiabetics, of MG with contraceptives, of GO with ferritin, and of 3-DG with smoking. RDA revealed GFR, GGT and, in case of 3-DG, glucose as major contributors to dicarbonyl variance. GWAS did not identify genome-wide significant loci. SNPs previously associated with glyoxalase activity did not reach nominal significance. When multiple testing was restricted to the lead SNPs of GWASs on the traits selected by RDA, 3-DG was found to be associated (p = 2.3 × 10-5) with rs1741177, an eQTL of NF-κB inhibitor NFKBIA. INTERPRETATION: This large-scale, population-based study has identified numerous associations, with GFR and GGT being of pivotal importance, providing unbiased perspectives on dicarbonyls beyond the current state. FUNDING: Deutsche Forschungsgemeinschaft, Helmholtz Munich, German Centre for Cardiovascular Research (DZHK), German Federal Ministry of Research and Education (BMBF).

The association of body mass index and body composition with plasma amyloid beta levels.

Blood-based analysis of amyloid-ß is increasingly applied to incrementally establish diagnostic tests for Alzheimer's disease. To this aim, it is necessary to determine factors that can alter blood-based concentrations of amyloid-ß. We cross-sectionally analysed amyloid-ß-40 and amyloid-ß-42 concentrations and the 40/42 ratio in 440 community-dwelling adults and associations with body mass index, waist-to-height ratio and body composition assessed using bioelectrical impedance analysis. Body mass index and waist-to-height ratio were inversely associated with plasma amyloid-ß-42 concentrations. Body fat mass, but not body cell mass and extracellular mass, was inversely associated with amyloid-ß-42 levels. The results indicate that plasma concentrations of amyloid-ß-42 are lower in those with increased body mass index and body fat, and associations with amyloid-ß-40 did not reach significance after controlling for multiple testing. The findings support the use of body mass index as an easy-to-measure factor that should be accounted for in diagnostic models for plasma amyloid-ß.

Periodic limb movements in sleep are linked to decreased hippocampus and amygdala volumes in the population-based BiDirect Study.

STUDY OBJECTIVES: Even though numerous studies indicate that sleep disorders are associated with altered brain morphology, MRI studies focusing on periodic limb movements in sleep (PLMS) are scarce. Our aim was to investigate the association of PLMS with global and regional gray matter volumes as well as white matter hyperintensity (WMH) volume. METHODS: One hundred and eighty-nine subjects (57.0 ± 7.8 years, women: 50.5%) of the population-based BiDirect Study underwent a single-night polysomnography (PSG). Standard criteria of the American Academy of Sleep Medicine were applied to evaluate sleep characteristics and calculate the PLMS index (PLMSI). T1w and FLAIR images were acquired with cerebral MRI at 3 Tesla. Voxel-based morphometry was performed to determine the total gray matter volume as well as the volume of cortical segments and subcortical gray matter areas using SPM12 and CAT12. The WMH volume was quantified with the Brain Intensity AbNormality Classification Algorithm. The independent relationship between MRI markers and PLMSI was analyzed using multivariable linear regression with adjustment for age, sex, body mass index, intracranial volume, PSG scorer, PSG device, sleep apnea, and the use of antidepressants. RESULTS: PLMSI was not significantly related to global gray matter volume and WMH volume. However, significant inverse associations of the PLMSI with the volume of the hippocampus (left and right hemisphere) and left amygdala were observed. CONCLUSIONS: A significant relationship between a higher PLMSI and lower volumes of the hippocampus and amygdala was found among the participants of the BiDirect Study. Since these associations are based on exploratory analyses, further replications are required before drawing firm conclusions.

Serum Glial Fibrillary Acidic Protein Compared With Neurofilament Light Chain as a Biomarker for Disease Progression in Multiple Sclerosis.

Importance: There is a lack of validated biomarkers for disability progression independent of relapse activity (PIRA) in multiple sclerosis (MS). Objective: To determine how serum glial fibrillary acidic protein (sGFAP) and serum neurofilament light chain (sNfL) correlate with features of disease progression vs acute focal inflammation in MS and how they can prognosticate disease progression. Design, Setting, and Participants: Data were acquired in the longitudinal Swiss MS cohort (SMSC; a consortium of tertiary referral hospitals) from January 1, 2012, to October 20, 2022. The SMSC is a prospective, multicenter study performed in 8 centers in Switzerland. For this nested study, participants had to meet the following inclusion criteria: cohort 1, patients with MS and either stable or worsening disability and similar baseline Expanded Disability Status Scale scores with no relapses during the entire follow-up; and cohort 2, all SMSC study patients who had initiated and continued B-cell-depleting treatment (ie, ocrelizumab or rituximab). Exposures: Patients received standard immunotherapies or were untreated. Main Outcomes and Measures: In cohort 1, sGFAP and sNfL levels were measured longitudinally using Simoa assays. Healthy control samples served as the reference. In cohort 2, sGFAP and sNfL levels were determined cross-sectionally. Results: This study included a total of 355 patients (103 [29.0%] in cohort 1: median [IQR] age, 42.1 [33.2-47.6] years; 73 female patients [70.9%]; and 252 [71.0%] in cohort 2: median [IQR] age, 44.3 [33.3-54.7] years; 156 female patients [61.9%]) and 259 healthy controls with a median [IQR] age of 44.3 [36.3-52.3] years and 177 female individuals (68.3%). sGFAP levels in controls increased as a function of age (1.5% per year; P < .001), were inversely correlated with BMI (-1.1% per BMI unit; P = .01), and were 14.9% higher in women than in men (P = .004). In cohort 1, patients with worsening progressive MS showed 50.9% higher sGFAP levels compared with those with stable MS after additional sNfL adjustment, whereas the 25% increase of sNfL disappeared after additional sGFAP adjustment. Higher sGFAP at baseline was associated with accelerated gray matter brain volume loss (per doubling: 0.24% per year; P < .001) but not white matter loss. sGFAP levels remained unchanged during disease exacerbations vs remission phases. In cohort 2, median (IQR) sGFAP z scores were higher in patients developing future confirmed disability worsening compared with those with stable disability (1.94 [0.36-2.23] vs 0.71 [-0.13 to 1.73]; P = .002); this was not significant for sNfL. However, the combined elevation of z scores of both biomarkers resulted in a 4- to 5-fold increased risk of confirmed disability worsening (hazard ratio [HR], 4.09; 95% CI, 2.04-8.18; P < .001) and PIRA (HR, 4.71; 95% CI, 2.05-9.77; P < .001). Conclusions and Relevance: Results of this cohort study suggest that sGFAP is a prognostic biomarker for future PIRA and revealed its complementary potential next to sNfL. sGFAP may serve as a useful biomarker for disease progression in MS in individual patient management and drug development.

Longitudinal analyses of serum neurofilament light and associations with obesity indices and bioelectrical impedance parameters.

Neurofilament light is a constituent of the neuronal cytoskeleton and released into the blood following neuro-axonal damage. It has previously been reported that NfL measured in blood serum is inversely related to body mass index. However, no reports exist with regard to body composition assessed using bioelectrical impedance analysis or other indicators of obesity beyond BMI. We analyzed the relationship between sNfL and body composition according to the three compartment model. Additionally, associations between sNfL, body shape index, waist-to-height ratio, and BMI were examined. The sample consisted of 769 participants assessed during the baseline examination and 693 participants examined in the course of the follow-up of the BiDirect Study. Associations between sNfL, BMI, BSI, and WtHR were separately analyzed using linear mixed models. Body compartments operationalized as fat mass, extracellular cell mass, and body cell mass were derived using BIA and the relationship with sNfL was analyzed with a linear mixed model. Lastly, we also analyzed the association between total body water and sNfL. We found significant inverse associations of sNfL with BMI and WtHR. The analysis of the three compartment model yielded significant inverse associations between sNfL, body cell mass and body fat mass, but not extracellular mass. Furthermore, total body water was also inversely related to sNfL. A potential mechanism could involve body cell mass and body fat mass as highly adaptive body constituents that either directly absorb sNfL, or promote the formation of new vasculature and thereby increase blood volume.

The role of educational attainment and brain morphology in major depressive disorder: Findings from the ENIGMA major depressive disorder consortium.

Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Sleep characteristics, cognitive performance, and gray matter volume: findings from the BiDirect Study.

STUDY OBJECTIVES: Sleep is essential for restorative metabolic changes and its physiological correlates can be examined using overnight polysomnography. However, the association between physiological sleep characteristics and brain structure is not well understood. We aimed to investigate gray matter volume and cognitive performance related to physiological sleep characteristics. METHODS: Polysomnographic recordings from 190 community-dwelling participants were analyzed with a principal component analysis in order to identify and aggregate shared variance into principal components. The relationship between aggregated sleep components and gray matter volume was then analyzed using voxel-based morphometry. In addition, we explored how cognitive flexibility, selective attention, and semantic fluency were related to aggregated sleep components and gray matter volume. RESULTS: Three principal components were identified from the polysomnographic recordings. The first component, primarily described by apnea events and cortical arousal, was significantly associated with lower gray matter volume in the left frontal pole. This apnea-related component was furthermore associated with lower cognitive flexibility and lower selective attention. CONCLUSIONS: Sleep disrupted by cortical arousal and breathing disturbances is paralleled by lower gray matter volume in the frontal pole, a proposed hub for the integration of cognitive processes. The observed effects provide new insights on the interplay between disrupted sleep, particularly breathing disturbances and arousal, and the brain.

Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts.

BACKGROUND: Neuroimaging studies of suicidal behavior have so far been conducted in small samples, prone to biases and false-positive associations, yielding inconsistent results. The ENIGMA-MDD Working Group aims to address the issues of poor replicability and comparability by coordinating harmonized analyses across neuroimaging studies of major depressive disorder and related phenotypes, including suicidal behavior. METHODS: Here, we pooled data from 18 international cohorts with neuroimaging and clinical measurements in 18,925 participants (12,477 healthy control subjects and 6448 people with depression, of whom 694 had attempted suicide). We compared regional cortical thickness and surface area and measures of subcortical, lateral ventricular, and intracranial volumes between suicide attempters, clinical control subjects (nonattempters with depression), and healthy control subjects. RESULTS: We identified 25 regions of interest with statistically significant (false discovery rate < .05) differences between groups. Post hoc examinations identified neuroimaging markers associated with suicide attempt including smaller volumes of the left and right thalamus and the right pallidum and lower surface area of the left inferior parietal lobe. CONCLUSIONS: This study addresses the lack of replicability and consistency in several previously published neuroimaging studies of suicide attempt and further demonstrates the need for well-powered samples and collaborative efforts. Our results highlight the potential involvement of the thalamus, a structure viewed historically as a passive gateway in the brain, and the pallidum, a region linked to reward response and positive affect. Future functional and connectivity studies of suicidal behaviors may focus on understanding how these regions relate to the neurobiological mechanisms of suicide attempt risk.

Cross-Disorder Analysis of Brain Structural Abnormalities in Six Major Psychiatric Disorders: A Secondary Analysis of Mega- and Meta-analytical Findings From the ENIGMA Consortium.

BACKGROUND: Neuroimaging studies have consistently reported similar brain structural abnormalities across different psychiatric disorders. Yet, the extent and regional distribution of shared morphometric abnormalities between disorders remains unknown. METHODS: Here, we conducted a cross-disorder analysis of brain structural abnormalities in 6 psychiatric disorders based on effect size estimates for cortical thickness and subcortical volume differences between healthy control subjects and psychiatric patients from 11 mega- and meta-analyses from the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta Analysis) consortium. Correlational and exploratory factor analyses were used to quantify the relative overlap in brain structural effect sizes between disorders and to identify brain regions with disorder-specific abnormalities. RESULTS: Brain structural abnormalities in major depressive disorder, bipolar disorder, schizophrenia, and obsessive-compulsive disorder were highly correlated (r = .443 to r = .782), and one shared latent underlying factor explained between 42.3% and 88.7% of the brain structural variance of each disorder. The observed shared morphometric signature of these disorders showed little similarity with brain structural patterns related to physiological aging. In contrast, patterns of brain structural abnormalities independent of all other disorders were observed in both attention-deficit/hyperactivity disorder and autism spectrum disorder. Brain regions showing high proportions of independent variance were identified for each disorder to locate disorder-specific morphometric abnormalities. CONCLUSIONS: Taken together, these results offer novel insights into transdiagnostic as well as disorder-specific brain structural abnormalities across 6 major psychiatric disorders. Limitations comprise the uncertain contribution of risk factors, comorbidities, and medication effects to the observed pattern of results that should be clarified by future research.

Biological sex classification with structural MRI data shows increased misclassification in transgender women.

Transgender individuals (TIs) show brain-structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of N = 1753 cisgender (CG) healthy participants were used to train (N = 1402) and validate (20% holdout N = 351) a support-vector machine classifying the biological sex. As a second validation, we classified N = 1104 patients with depression. A third validation was performed using the matched CG sample of the transgender women (TW) application sample. Subsequently, the classifier was applied to N = 26 TW. Finally, we compared brain volumes of CG-men, women, and TW-pre/post treatment cross-sex hormone treatment (CHT) in a univariate analysis controlling for sexual orientation, age, and total brain volume. The application of our biological sex classifier to the transgender sample resulted in a significantly lower true positive rate (TPR-male = 56.0%). The TPR did not differ between CG-individuals with (TPR-male = 86.9%) and without depression (TPR-male = 88.5%). The univariate analysis of the transgender application-sample revealed that TW-pre/post treatment show brain-structural differences from CG-women and CG-men in the putamen and insula, as well as the whole-brain analysis. Our results support the hypothesis that brain structure in TW differs from brain structure of their biological sex (male) as well as their perceived gender (female). This finding substantiates evidence that TIs show specific brain-structural alterations leading to a different pattern of brain structure than CG-individuals.

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing.

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.

Lack of Association Between Shape and Volume of Subcortical Brain Structures and Restless Legs Syndrome.

OBJECTIVE: Previous studies on patients with restless legs syndrome (RLS) yielded inconclusive results in the magnetic resonance imaging (MRI)-based analyses of alterations of subcortical structures in the brain. The aim of this study was to compare volumes as well as shapes of subcortical structures and the hippocampus between RLS cases and controls. Additionally, the associations between the genetic risks for RLS and subcortical volumes were investigated. METHODS: We compared volumetric as well as shape differences assessed by 3 T MRI in the caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus in 39 RLS cases versus 117 controls, nested within a population-based sample. In a subsample, we explored associations between known genetic risk markers for RLS and the volumes of the subcortical structures and the hippocampus. RESULTS: No significant differences between RLS cases and controls in subcortical and hippocampal shapes and volumes were observed. Furthermore, the genetic risk for RLS was unrelated to any alterations of subcortical and hippocampal gray matter volume. INTERPRETATION: We conclude that neither RLS nor the genetic risk for the disease give rise to changes in hippocampal and subcortical shapes and gray matter volumes.

Reduced fractional anisotropy in patients with major depressive disorder and associations with vascular stiffness.

Previous studies revealed several alterations of the cerebral white matter in patients with major depressive disorder. However, it is unknown if these alterations are associated with vascular changes in the brain and other body parts. We compared diffusion tensor imaging derived fractional anisotropy in a well characterized sample of middle-aged patients with major depressive disorder (n = 290) and never-depressed controls (n = 346) by the method of tract-based spatial statistics. Subsequently, the potential role of pulse wave velocity as a mediator of depression- and age-related changes in extracted estimates of fractional anisotropy were analyzed. The results of the tract-based analysis revealed significantly reduced fractional anisotropy in the left posterior thalamic radiation associated with depression. Analyses of extracted data indicated additional reductions of fractional anisotropy bilaterally in the posterior thalamic radiation and in the left sagittal stratum. The analyses of indirect effects did not show any significant mediation of depression-related effects on fractional anisotropy via pulse wave velocity. However, age-related effects on fractional anisotropy were partially mediated by pulse wave velocity. In conclusion, major depressive disorder is associated with detrimental effects on cerebral white matter microstructure properties which are independent of vascular changes, as measured by pulse wave velocity. However, a portion of age-related detrimental effects on white matter is explained by vascular changes. Longitudinal studies are required for investigating changes in white matter and vascular parameters over time and their association with incident depression.