Publications by authors named "Nic J A van der Wee"

135 Publications

The clinical and cost-effectiveness of a self-management intervention for patients with persistent depressive disorder and their partners/caregivers: study protocol of a multicenter pragmatic randomized controlled trial.

Trials 2021 Oct 23;22(1):731. Epub 2021 Oct 23.

Department of Psychiatry, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.

Background: After regular treatment, patients with persistent depressive disorder (PDD) may remain in specialized psychiatric outpatient care without achieving remission. Lacking other options, these patients often receive long-term, non-protocolized care as usual (CAU) that does not involve the partner/caregiver of the patient. Although the revised depression treatment guidelines suggest focusing on psychiatric rehabilitation and self-management as the next treatment step for PDD, an evidence-based cost-effective self-management protocol for PDD is lacking. This study investigates the "Patient and Partner Education Program for All Chronic Illnesses" (PPEP4All) as a brief self-management protocol that could lead to lower costs, higher quality of life, and less disease burden in PDD patients and their partners/caregivers.

Methods: Presented is the rationale and methods of a multicenter pragmatic randomized controlled trial to evaluate the clinical efficacy and cost-effectiveness of PPEP4All for patients with PDD and their partners/caregivers. In accordance with current recommendations, a mixed methods research approach is used with both quantitative and qualitative data. A total of 178 eligible outpatients with PDD and their partners/caregivers are recruited and randomized to either PPEP4All or CAU. Those assigned to PPEP4All receive nine weekly self-management sessions with a trained PPEP4All therapist. Primary and secondary outcome measurements are at 0, 3, 6, and 12 months.

Discussion: This project will result in the implementation of a self-management intervention for patients with PDD, meeting an urgent need in mental healthcare. Using PPEP4All can optimize the quality and efficiency of care for both patients with PDD and their partners/caregivers.

Trial Registration: Netherlands Trial Register Identifier NTR5973 . Registered on 20 July 2016.
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http://dx.doi.org/10.1186/s13063-021-05666-yDOI Listing
October 2021

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.

Transl Psychiatry 2021 10 1;11(1):502. Epub 2021 Oct 1.

Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.
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http://dx.doi.org/10.1038/s41398-021-01622-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486763PMC
October 2021

Social dysfunction is transdiagnostically associated with default mode network dysconnectivity in schizophrenia and Alzheimer's disease.

World J Biol Psychiatry 2021 Sep 17:1-14. Epub 2021 Sep 17.

Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Amsterdam UMC, VU Medical Centre and GGZ inGeest, Amsterdam, The Netherlands.

Objectives: Social dysfunction is one of the most common signs of major neuropsychiatric disorders. The Default Mode Network (DMN) is crucially implicated in both psychopathology and social dysfunction, although the transdiagnostic properties of social dysfunction remains unknown. As part of the pan-European PRISM (Psychiatric Ratings using Intermediate Stratified Markers) project, we explored cross-disorder impact of social dysfunction on DMN connectivity.

Methods: We studied DMN intrinsic functional connectivity in relation to social dysfunction by applying Independent Component Analysis and Dual Regression on resting-state fMRI data, among schizophrenia (SZ; =48), Alzheimer disease (AD; =47) patients and healthy controls (HC; =55). Social dysfunction was operationalised via the Social Functioning Scale (SFS) and De Jong-Gierveld Loneliness Scale (LON).

Results: Both SFS and LON were independently associated with diminished DMN connectional integrity within rostromedial prefrontal DMN subterritories ( range=0.02-0.04). The combined effect of these indicators (Mean.SFS + LON) on diminished DMN connectivity was even more pronounced (both spatially and statistically), independent of diagnostic status, and not confounded by key clinical or sociodemographic effects, comprising large sections of rostromedial and dorsomedial prefrontal cortex (=0.01).

Conclusions: These findings pinpoint DMN connectional alterations as putative transdiagnostic endophenotypes for social dysfunction and could aid personalised care initiatives grounded in social behaviour.
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http://dx.doi.org/10.1080/15622975.2021.1966714DOI Listing
September 2021

Contributing factors to advanced brain aging in depression and anxiety disorders.

Transl Psychiatry 2021 07 21;11(1):402. Epub 2021 Jul 21.

Department of Psychiatry, Amsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam Neuroscience, Amsterdam, The Netherlands.

Depression and anxiety are common and often comorbid mental health disorders that represent risk factors for aging-related conditions. Brain aging has shown to be more advanced in patients with major depressive disorder (MDD). Here, we extend prior work by investigating multivariate brain aging in patients with MDD, anxiety disorders, or both, and examine which factors contribute to older-appearing brains. Adults aged 18-57 years from the Netherlands Study of Depression and Anxiety underwent structural MRI. A pretrained brain-age prediction model based on >2000 samples from the ENIGMA consortium was applied to obtain brain-predicted age differences (brain PAD, predicted brain age minus chronological age) in 65 controls and 220 patients with current MDD and/or anxiety. Brain-PAD estimates were associated with clinical, somatic, lifestyle, and biological factors. After correcting for antidepressant use, brain PAD was significantly higher in MDD (+2.78 years, Cohen's d = 0.25, 95% CI -0.10-0.60) and anxiety patients (+2.91 years, Cohen's d = 0.27, 95% CI -0.08-0.61), compared with controls. There were no significant associations with lifestyle or biological stress systems. A multivariable model indicated unique contributions of higher severity of somatic depression symptoms (b = 4.21 years per unit increase on average sum score) and antidepressant use (-2.53 years) to brain PAD. Advanced brain aging in patients with MDD and anxiety was most strongly associated with somatic depressive symptomatology. We also present clinically relevant evidence for a potential neuroprotective antidepressant effect on the brain-PAD metric that requires follow-up in future research.
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http://dx.doi.org/10.1038/s41398-021-01524-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295382PMC
July 2021

Dynamic time warp analysis of individual symptom trajectories in depressed patients treated with electroconvulsive therapy.

J Affect Disord 2021 10 2;293:435-443. Epub 2021 Jul 2.

Department of Psychiatry, Leiden University Medical Center (LUMC), the Netherlands. Electronic address:

Background: Although electroconvulsive therapy (ECT) effectively improves severity scores of depression, its effects on its individual symptoms has scarcely been studied. We aimed to study which depressive symptom trajectories dynamically cluster together in individuals as well as groups of patients during ECT using Dynamic Time Warp (DTW) analysis.

Methods: We analysed the standardized weekly scores on the 25-item abbreviated version of the Comprehensive Psychopathological Rating Scale (CPRS) in depressed patients before and during their first six weeks of ECT treatment. DTW analysis was used to analyse the (dis)similarity of time series of items scores at the patient level (300 'DTW distances' per patient) as well as on the group level. Hierarchical cluster, network, and Distatis analyses yielded symptom dimensions.

Results: We included 133 patients, 64.7% female, with an average age of 60.4 years (SD 15.1). Individual DTW distance matrices and networks revealed marked differences in hierarchical and network clusters among patients. Based on cluster analyses of the aggregated matrices, four symptom clusters emerged. In patients who reached remission, the average DTW distance between their symptoms was significantly smaller than non-remitters, reflecting denser symptom networks in remitters than non-remitters (p=0.04).

Limitations: The assessments were done only weekly during the first six weeks of ECT treatment. The use of individual items of the abbreviated CPRS may have led to measurement error as well as floor and ceiling effects.

Conclusion: DTW offers an efficient new approach to analyse symptom trajectories within individuals as well as groups of patients, aiding personalized medicine of psychopathology.
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http://dx.doi.org/10.1016/j.jad.2021.06.068DOI Listing
October 2021

Dynamic time warp analysis of individual symptom trajectories in depressed patients treated with electroconvulsive therapy.

J Affect Disord 2021 10 2;293:435-443. Epub 2021 Jul 2.

Department of Psychiatry, Leiden University Medical Center (LUMC), the Netherlands. Electronic address:

Background: Although electroconvulsive therapy (ECT) effectively improves severity scores of depression, its effects on its individual symptoms has scarcely been studied. We aimed to study which depressive symptom trajectories dynamically cluster together in individuals as well as groups of patients during ECT using Dynamic Time Warp (DTW) analysis.

Methods: We analysed the standardized weekly scores on the 25-item abbreviated version of the Comprehensive Psychopathological Rating Scale (CPRS) in depressed patients before and during their first six weeks of ECT treatment. DTW analysis was used to analyse the (dis)similarity of time series of items scores at the patient level (300 'DTW distances' per patient) as well as on the group level. Hierarchical cluster, network, and Distatis analyses yielded symptom dimensions.

Results: We included 133 patients, 64.7% female, with an average age of 60.4 years (SD 15.1). Individual DTW distance matrices and networks revealed marked differences in hierarchical and network clusters among patients. Based on cluster analyses of the aggregated matrices, four symptom clusters emerged. In patients who reached remission, the average DTW distance between their symptoms was significantly smaller than non-remitters, reflecting denser symptom networks in remitters than non-remitters (p=0.04).

Limitations: The assessments were done only weekly during the first six weeks of ECT treatment. The use of individual items of the abbreviated CPRS may have led to measurement error as well as floor and ceiling effects.

Conclusion: DTW offers an efficient new approach to analyse symptom trajectories within individuals as well as groups of patients, aiding personalized medicine of psychopathology.
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http://dx.doi.org/10.1016/j.jad.2021.06.068DOI Listing
October 2021

Intrinsic functional connectivity in families genetically enriched for social anxiety disorder - an endophenotype study.

EBioMedicine 2021 Jul 20;69:103445. Epub 2021 Jun 20.

Department of Psychiatry, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden, the Netherlands. Electronic address:

Background: Social anxiety disorder (SAD) is a serious psychiatric condition with a high prevalence, and a typical onset during childhood/adolescence. The condition runs in families, but it is largely unknown which neurobiological characteristics transfer this genetic vulnerability ('endophenotypes'). Using data from the Leiden Family Lab study on SAD, including two generations of families genetically enriched for SAD, we investigated whether social anxiety (SA) co-segregated with changes in intrinsic functional connectivity (iFC), and examined heritability.

Methods: Functional MRI data were acquired during resting-state in 109 individuals (56 males; mean age: 31·5, range 9·2-61·5 years). FSL's tool MELODIC was used to perform independent component analysis. Six networks of interest (default mode, dorsal attention, executive control, frontoparietal, limbic and salience) were identified at the group-level and used to generate subject-specific spatial maps. Voxel-wise regression models, with SA-level as predictor and voxel-wise iFC as candidate endophenotypes, were performed to investigate the association with SA, within masks of the networks of interest. Subsequently, heritability was estimated.

Findings: SA co-segregated with iFC within the dorsal attention network (positive association in left middle frontal gyrus and right postcentral gyrus) and frontoparietal network (positive association within left middle temporal gyrus) (cluster-forming-threshold z>2·3, cluster-corrected extent-threshold p<0·05). Furthermore, iFC of multiple voxels within these clusters was at least moderately heritable.

Interpretation: These findings provide initial evidence for increased iFC as candidate endophenotype of SAD, particularly within networks involved in attention. These changes might underlie attentional biases commonly present in SAD.

Funding: Leiden University Research Profile 'Health, Prevention and the Human Lifecycle'.
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http://dx.doi.org/10.1016/j.ebiom.2021.103445DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237289PMC
July 2021

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 17. Epub 2021 Feb 17.

Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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http://dx.doi.org/10.1002/hbm.25364DOI Listing
February 2021

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 11. Epub 2021 Feb 11.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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http://dx.doi.org/10.1002/hbm.25320DOI Listing
February 2021

Associations between depression, lifestyle and brain structure: A longitudinal MRI study.

Neuroimage 2021 05 4;231:117834. Epub 2021 Feb 4.

Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Vrije Universiteit Amsterdam, The Netherlands. Electronic address:

Background: Depression has been associated with decreased regional grey matter volume, which might partly be explained by an unhealthier lifestyle in depressed individuals which has been ignored by most earlier studies. Also, the longitudinal nature of depression, lifestyle and brain structure associations is largely unknown. This study investigates the relationship of depression and lifestyle with brain structure cross-sectionally and longitudinally over up to 9 years.

Methods: We used longitudinal structural MRI data of persons with depression and/or anxiety disorders and controls (N = 347, N = 609). Cortical thickness of medial orbitofrontal cortex (mOFC), rostral anterior cingulate cortex (rACC) and hippocampal volume were derived using FreeSurfer. Using Generalized Estimating Equations, we investigated associations of depression and lifestyle (Body mass index (BMI), smoking, alcohol consumption, physical activity and sleep duration) with brain structure and change in brain structure over 2 (n = 179) and 9 years (n = 82).

Results: Depression status (B = -.053, p = .002) and severity (B = -.002, p = .002) were negatively associated with rACC thickness. mOFC thickness was negatively associated with BMI (B = -.004, p < .001) and positively with moderate alcohol consumption (B = .030, p = .009). All associations were independent of each other. No associations were observed between (change in) depression, disease burden or lifestyle factors with brain change over time.

Conclusions: Depressive symptoms and diagnosis were independently associated with thinner rACC, BMI with thinner mOFC, and moderate alcohol consumption with thicker mOFC. No longitudinal associations were observed, suggesting that regional grey matter alterations are a long-term consequence or vulnerability indicator for depression but not dynamically or progressively related to depression course trajectory.
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http://dx.doi.org/10.1016/j.neuroimage.2021.117834DOI Listing
May 2021

Investigating microstructure of white matter tracts as candidate endophenotypes of Social Anxiety Disorder - Findings from the Leiden Family Lab study on Social Anxiety Disorder (LFLSAD).

Neuroimage Clin 2020 5;28:102493. Epub 2020 Nov 5.

Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands; Leiden Institute for Brain and Cognition, Leiden, The Netherlands. Electronic address:

Background: Social anxiety disorder (SAD) is a mental illness with a complex, partially genetic background. Differences in characteristics of white matter (WM) microstructure have been reported in patients with SAD compared to healthy controls. Also, WM characteristics are moderately to highly heritable. Endophenotypes are measurable characteristics on the road from genotype to phenotype, putatively reflective of genetically based disease mechanisms. In search of candidate endophenotypes of SAD we used a unique sample of SAD patients and their family members of two generations to explore microstructure of WM tracts as candidate endophenotypes. We focused on two endophenotype criteria: co-segregation with social anxiety within the families, and heritability.

Methods: Participants (n = 94 from 8 families genetically vulnerable for SAD) took part in the Leiden Family Lab Study on Social Anxiety Disorder (LFLSAD). We employed tract-based spatial statistics to examine structural WM characteristics, being fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD) and radial diffusivity (RD), in three a-priori defined tracts of interest: uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF). Associations with social anxiety symptoms and heritability were estimated.

Results: Increased FA in the left and right SLF co-segregated with symptoms of social anxiety. These findings were coupled with decreased RD and MD. All characteristics of WM microstructure were estimated to be at least moderately heritable.

Conclusion: These findings suggest that alterations in WM microstructure in the SLF could be candidate endophenotypes of SAD, as they co-segregated within families genetically vulnerable for SAD and are heritable. These findings further elucidate the genetic susceptibility to SAD and improve our understanding of the overall etiology.
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http://dx.doi.org/10.1016/j.nicl.2020.102493DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691726PMC
June 2021

Suspected Transverse Myelitis with Normal MRI and CSF Findings in a Patient with Lupus: What to Do? A Case Series and Systematic Review.

Neuropsychiatr Dis Treat 2020 22;16:3173-3186. Epub 2020 Dec 22.

Department of Rheumatology, Leiden University Medical Center (LUMC), Leiden, the Netherlands.

Purpose: To evaluate the use of immunosuppressive treatment, clinical outcome and diagnostic strategy in patients with systemic lupus erythematosus (SLE) presenting with clinical features of transverse myelitis (TM), but normal MRI of the spinal cord (sMRI) and normal cerebrospinal fluid (CSF) assessment, and to suggest a clinical guideline.

Patients And Methods: All patients with SLE and clinical features compatible with (sub)acute TM visiting the NPSLE clinic of the LUMC between 2007 and 2020 were included. Information on baseline characteristics, investigations, treatment and outcomes was collected from electronic medical records. In addition, a systematic review of individual participant data was performed up to April 2020 in PubMed, Embase and Web of Science, identifying all patients with TM, SLE and sMRI assessment. Data regarding sMRI, CSF analysis, treatment and outcome were extracted, and outcome was compared between patients with normal sMRI and CSF (sMRI-/CSF-) and patients with abnormalities.

Results: Twelve SLE patients with a clinical diagnosis of TM were identified: four sMRI-/CSF- and one sMRI- with CSF not available. All patients received immunosuppressive treatment, but outcome in sMRI-/CSF- patients was worse: no recovery (n=1) or partial recovery (n=3) compared to partial recovery (n=4) and (nearly) complete recovery (n=3) in MRI+ patients. The systematic literature review yielded 146 articles eligible for inclusion, 90% case reports. A total of 427 SLE patients with TM were identified, of which only four cases were sMRI-/CSF- (1%), showing no improvement (n=1), partial improvement (n=2) and complete recovery (n=1) after immunosuppressive treatment.

Conclusion: Outcome in SLE patients presenting with clinically suspected TM with normal sMRI and CSF is less favorable, despite treatment with immunosuppressive therapy. Taking a functional neurological disorder into consideration may be helpful in order to start other therapeutic strategies. We suggest prescribing immunosuppressive treatment for a restricted period of time to evaluate its effect in cases where a functional disorder initially is considered unlikely.
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http://dx.doi.org/10.2147/NDT.S267000DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7764958PMC
December 2020

Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis.

Mol Psychiatry 2020 Dec 7. Epub 2020 Dec 7.

Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA, USA.

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.
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http://dx.doi.org/10.1038/s41380-020-00967-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180531PMC
December 2020

Mortality in patients with systemic lupus erythematosus and neuropsychiatric involvement: A retrospective analysis from a tertiary referral center in the Netherlands.

Lupus 2020 Dec 20;29(14):1892-1901. Epub 2020 Oct 20.

Department of Rheumatology, Leiden University Medical Center, Leiden, the Netherlands.

Objective: We aimed to evaluate all-cause and cause-specific mortality in patients with systemic lupus erythematosus (SLE) and neuropsychiatric (NP) symptoms in the Netherlands between 2007-2018.

Methods: Patients visiting the tertiary referral NPSLE clinic of the Leiden University Medical Center were included. NP symptoms were attributed to SLE requiring treatment (major NPSLE) or to other and mild causes (minor/non-NPSLE). Municipal registries were checked for current status (alive/deceased). Standardized mortality ratios (SMRs) and 95% confidence intervals (CI) were calculated using data from the Dutch population. Rate ratio (RR) and 95% CI were calculated using direct standardization to compare mortality between major NPSLE and minor/non-NPSLE.

Results: 351 patients were included and 149 patients were classified as major NPSLE (42.5%). Compared with the general population, mortality was increased in major NPSLE (SMR 5.0 (95% CI: 2.6-8.5)) and minor/non-NPSLE patients (SMR 3.7 (95% CI: 2.2-6.0)). Compared with minor/non-NPSLE, mortality was similar in major NPSLE patients (RR: 1.0 (95% CI: 0.5-2.0)). Cause-specific mortality rates demonstrated an increased risk of death due to infections in both groups, whereas death due to cardiovascular disease was only increased in minor/non-NPSLE patients.

Conclusion: Mortality was increased in both major NPSLE and minor/non-NPSLE patients in comparison with the general population. There was no difference in mortality between major NPSLE and minor/non-NPSLE patients.
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http://dx.doi.org/10.1177/0961203320963815DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7684795PMC
December 2020

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.

JAMA Psychiatry 2021 Jan;78(1):47-63

Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht University, the Netherlands.

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.

Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.

Design, Setting, And Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.

Main Outcomes And Measures: Interregional profiles of group difference in cortical thickness between cases and controls.

Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.

Conclusions And Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.2694DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450410PMC
January 2021

Neural processing of socioemotional content in conduct-disordered juvenile offenders with limited prosocial emotions.

Prog Neuropsychopharmacol Biol Psychiatry 2021 03 29;105:110045. Epub 2020 Jul 29.

Leiden University Medical Center, Dept. of Child and Adolescent Psychiatry, Curium, the Netherlands; Leiden Institute for Brain and Cognition, the Netherlands; Örebro University, Dept. of Behavioral, Social, and Legal Sciences, Sweden; Ghent University, Dept. Special Needs Education, Belgium.

Background: Reflecting evidence on Callous-Unemotional (CU) traits (e.g., lack of empathy and guilt, shallow affect), the DSM-5 added a categorical CU-based specifier for Conduct Disorder (CD), labeled 'with Limited Prosocial Emotions' (LPE). Theory and prior work suggest that CD youths with and without LPE will likely differ in neural processing of negative socioemotional content. This proposition, however, is mainly derived from studies employing related, yet distinct, operationalizations of CU traits (e.g., dimensional measure/median split/top quartile), thus precluding direct examination of LPE-specific neurocognitive deficits.

Methods: Employing a DSM-5 informed LPE proxy, neural processing of recognizing and resonating negative socioemotional content (angry and fearful faces) was therefore examined here among CD offenders with LPE (CD/LPE+; N = 19), relative to CD offenders without LPE (CD/LPE-; N = 31) and healthy controls (HC; N = 31).

Results: Relative to HC and CD/LPE- youths and according to a linearly increasing trend (CD/LPE- < HC < CD/LPE+), CD/LPE+ youths exhibited hyperactivity within dorsolateral, dorsomedial, and ventromedial prefrontal regions during both emotion recognition and resonance. During emotion resonance, CD/LPE+ youths additionally showed increased activity within the posterior cingulate and precuneal cortices in comparison to HC and CD/LPE- youths, which again followed a linearly increasing trend (CD/LPE- < HC < CD/LPE+). These effects moreover seemed specific to the LPE specifier, when compared to a commonly employed method for CU-based grouping in CD (i.e., median split on CU scores).

Conclusions: These data cautiously suggest that CD/LPE+ youths may exhibit an over-reliance on cortical neurocognitive systems when explicitly processing negative socioemotional information, which could have adverse downstream effects on relevant socioemotional functions. The findings thus seem to provide novel, yet preliminary, clues on the neurocognitive profile of CD/LPE+, and additionally highlight the potential scientific utility of the LPE specifier.
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http://dx.doi.org/10.1016/j.pnpbp.2020.110045DOI Listing
March 2021

ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders.

Hum Brain Mapp 2020 Jul 3. Epub 2020 Jul 3.

Department of Psychiatry & Mental Health, University of Cape Town, Cape Town, South Africa.

Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.
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http://dx.doi.org/10.1002/hbm.25100DOI Listing
July 2020

A framework for assessing neuropsychiatric phenotypes by using smartphone-based location data.

Transl Psychiatry 2020 07 1;10(1):211. Epub 2020 Jul 1.

Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.

The use of smartphone-based location data to quantify behavior longitudinally and passively is rapidly gaining traction in neuropsychiatric research. However, a standardized and validated preprocessing framework for deriving behavioral phenotypes from smartphone-based location data is currently lacking. Here, we present a preprocessing framework consisting of methods that are validated in the context of geospatial data. This framework aims to generate context-enriched location data by identifying stationary, non-stationary, and recurrent stationary states in movement patterns. Subsequently, this context-enriched data is used to derive a series of behavioral phenotypes that are related to movement. By using smartphone-based location data collected from 245 subjects, including patients with schizophrenia, we show that the proposed framework is effective and accurate in generating context-enriched location data. This data was subsequently used to derive behavioral readouts that were sensitive in detecting behavioral nuances related to schizophrenia and aging, such as the time spent at home and the number of unique places visited. Overall, our results indicate that the proposed framework reliably preprocesses raw smartphone-based location data in such a manner that relevant behavioral phenotypes of interest can be derived.
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http://dx.doi.org/10.1038/s41398-020-00893-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329884PMC
July 2020

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

Hum Brain Mapp 2020 Jun 29. Epub 2020 Jun 29.

Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.
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http://dx.doi.org/10.1002/hbm.25096DOI Listing
June 2020

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

Transl Psychiatry 2020 05 29;10(1):172. Epub 2020 May 29.

Illinois Institute of Technology, Chicago, IL, USA.

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.
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http://dx.doi.org/10.1038/s41398-020-0842-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7260219PMC
May 2020

Stress resilience during the coronavirus pandemic.

Eur Neuropsychopharmacol 2020 06 11;35:12-16. Epub 2020 May 11.

Department of Pschiatry, Leiden University Medical Center, Leiden, the Netherlands, Leiden Institute for Brain and Cognition, Leiden, The Netherlands.

The epidemic of the 2019 novel coronavirus SARS-CoV-2, causing the coronavirus disease 2019 (COVID-19) is a global public health emergency with multifaceted severe consequences for people's lives and their mental health. In this article, as members of the European College of Neuropsychopharmacology (ECNP) Resilience, we will discuss the urgent need for a focus on resilience during the current coronavirus pandemic. Resilience is pivotal to cope with stress and vital to stay in balance. We will discuss the importance of resilience at the individual and societal level, but also the implication for patients with a psychiatric condition and health care workers. We not only advocate for an increased focus on mental health during the coronavirus pandemic but also highlight the urgent need of augmenting our focus on resilience and on strategies to enhance it.
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http://dx.doi.org/10.1016/j.euroneuro.2020.05.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211573PMC
June 2020

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

Mol Psychiatry 2020 May 18. Epub 2020 May 18.

Department of Psychiatry, University of Münster, Münster, Germany.

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.
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http://dx.doi.org/10.1038/s41380-020-0754-0DOI Listing
May 2020

Amygdala hyperreactivity to faces conditioned with a social-evaluative meaning- a multiplex, multigenerational fMRI study on social anxiety endophenotypes.

Neuroimage Clin 2020 16;26:102247. Epub 2020 Mar 16.

Institute of Psychology, Leiden University, Wassenaarseweg 52, 2333 AK Leiden, The Netherlands; Leiden Institute for Brain and Cognition, Leiden, The Netherlands. Electronic address:

Social anxiety disorder (SAD) runs in families, but the neurobiological pathways underlying the genetic susceptibility towards SAD are largely unknown. Here, we employed an endophenotype approach, and tested the hypothesis that amygdala hyperreactivity to faces conditioned with a social-evaluative meaning is a candidate SAD endophenotype. We used data from the multiplex, multigenerational Leiden Family Lab study on Social Anxiety Disorder (eight families, n = 105) and investigated amygdala activation during a social-evaluative conditioning paradigm with high ecological validity in the context of SAD. Three neutral faces were repeatedly presented in combination with socially negative, positive or neutral sentences. We focused on two endophenotype criteria: co-segregation of the candidate endophenotype with the disorder within families, and heritability. Analyses of the fMRI data were restricted to the amygdala as a region of interest, and association analyses revealed that bilateral amygdala hyperreactivity in response to the conditioned faces co-segregated with social anxiety (SA; continuous measure) within the families; we found, however, no relationship between SA and brain activation in response to more specific fMRI contrasts. Furthermore, brain activation in a small subset of voxels within these amygdala clusters was at least moderately heritable. Taken together, these findings show that amygdala engagement in response to conditioned faces with a social-evaluative meaning qualifies as a neurobiological candidate endophenotype of social anxiety. Thereby, these data shed light on the genetic vulnerability to develop SAD.
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http://dx.doi.org/10.1016/j.nicl.2020.102247DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125356PMC
February 2021

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Transl Psychiatry 2020 03 20;10(1):100. Epub 2020 Mar 20.

Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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http://dx.doi.org/10.1038/s41398-020-0705-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083923PMC
March 2020

Predicting individual clinical trajectories of depression with generative embedding.

Neuroimage Clin 2020 17;26:102213. Epub 2020 Feb 17.

Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich 8032, Switzerland; Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, United Kingdom; Max Planck Institute for Metabolism Research, Cologne, Germany.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy - generative embedding (GE) - which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of connections involved in emotional face processing might be associated with higher risk of developing a less favorable clinical course.
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http://dx.doi.org/10.1016/j.nicl.2020.102213DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082217PMC
March 2021

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Cortical Thickness in Dutch Police Officers: An Examination of Factors Associated with Resilience.

J Trauma Stress 2020 04 11;33(2):181-189. Epub 2020 Mar 11.

Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands.

Previous neuroimaging studies on resilience have generally compared resilience and psychopathology after stress exposure, which does not allow for conclusions regarding correlates specific to resilience. The aim of the present study was to investigate resilience-specific correlates in cortical thickness and/or cortical surface area and their correlations with psychometric measurements, using a three-group design that included a non-trauma-exposed control group in order to disentangle effects related to resilience from those related to psychopathology. Structural magnetic resonance imaging scans were acquired from 82 Dutch police officers. Participants were categorized into resilient (n = 31; trauma exposure, no psychopathology), vulnerable (n = 32; trauma exposure, psychopathology), and control groups (n = 19; no trauma exposure, no psychopathology). Specific regions of interest (ROIs) were identified based on previous studies that found the rostral and caudal anterior cingulate cortex (ACC) to be implicated in trauma-related psychopathology. Cortical thickness and surface area of the ROIs-the rostral and caudal ACC-and of the whole brain were examined. No significant differences in cortical thickness or surface area were found between the resilient group and other groups in the ROI and whole-brain analyses. Thus, the results of the present study provide no evidence of an association between resilience to traumatic stress and measures of thickness and surface area in cortical regions of the brain in a sample of Dutch police officers.
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http://dx.doi.org/10.1002/jts.22494DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216895PMC
April 2020

Default Mode Network Connectivity and Social Dysfunction in Major Depressive Disorder.

Sci Rep 2020 01 13;10(1):194. Epub 2020 Jan 13.

Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.

Though social functioning is often hampered in Major Depressive Disorder (MDD), we lack a complete and integrated understanding of the underlying neurobiology. Connectional disturbances in the brain's Default Mode Network (DMN) might be an associated factor, as they could relate to suboptimal social processing. DMN connectional integrity, however, has not been explicitly studied in relation to social dysfunctioning in MDD patients. Applying Independent Component Analysis and Dual Regression on resting-state fMRI data, we explored DMN intrinsic functional connectivity in relation to social dysfunctioning (i.e. composite of loneliness, social disability, small social network) among 74 MDD patients (66.2% female, Mean age = 36.9, SD = 11.9). Categorical analyses examined whether DMN connectivity differs between high and low social dysfunctioning MDD groups, dimensional analyses studied linear associations between social dysfunction and DMN connectivity across MDD patients. Threshold-free cluster enhancement (TFCE) with family-wise error (FWE) correction was used for statistical thresholding and multiple comparisons correction (P < 0.05). The analyses cautiously linked greater social dysfunctioning among MDD patients to diminished DMN connectivity, specifically within the rostromedial prefrontal cortex and posterior superior frontal gyrus. These preliminary findings pinpoint DMN connectional alterations as potentially germane to social dysfunction in MDD, and may as such improve our understanding of the underlying neurobiology.
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http://dx.doi.org/10.1038/s41598-019-57033-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6957534PMC
January 2020

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium.

Mol Psychiatry 2019 Dec 19. Epub 2019 Dec 19.

Department of Psychiatry, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.
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http://dx.doi.org/10.1038/s41380-019-0631-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302988PMC
December 2019

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019
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