Functional MRI correlates of emotion regulation in major depressive disorder related to depressive disease load measured over nine years

Major Depressive Disorder (MDD) often is a recurrent and chronic disorder. We investigated the neurocognitive underpinnings of the incremental risk for poor disease course by exploring relations between enduring depression and brain functioning during regulation of negative and positive emotions using cognitive reappraisal. We used fMRI-data from the longitudinal Netherlands Study of Depression and Anxiety acquired during an emotion regulation task in 77 individuals with MDD. Task-related brain activity was related to disease load, calculated from presence and severity of depression in the preceding nine years. Additionally, we explored task related brain-connectivity. Brain functioning in individuals with MDD was further compared to 35 controls to explore overlap between load-effects and general effects related to MDD history/presence. Disease load was not associated with changes in affect or with brain activity, but with connectivity between areas essential for processing, integrating and regulating emotional information during downregulation of negative emotions. Results did not overlap with general MDD-effects. Instead, MDD was generally associated with lower parietal activity during downregulation of negative emotions. During upregulation of positive emotions, disease load was related to connectivity between limbic regions (although driven by symptomatic state), and connectivity between frontal, insular and thalamic regions was lower in MDD (vs controls). Results suggest that previous depressive load relates to brain connectivity in relevant networks during downregulation of negative emotions. These abnormalities do not overlap with disease-general abnormalities and could foster an incremental vulnerability to recurrence or chronicity of MDD. Therefore, optimizing emotion regulation is a promising therapeutic target for improving long-term MDD course.

Elevated cognitive rumination and adverse life events are associated with lower cortical surface area and suicidal ideation in adolescents with major depressive disorder

INTRODUCTION

Suicide is the second most common cause of death among young people. Structural brain alterations, rumination, and recent stressful experiences contribute to suicidal thoughts and behaviors (STBs).

METHODS

Here, we employed structural equation modeling (SEM) to examine the unique and combined relationships of these risk factors with STBs in a sample of young people with major depressive disorder (MDD) from the Magnetic Resonance-Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT) study (N = 67, mean age = 15.90; standard deviation ± 1.32).

RESULTS

Whereas increased rumination and lower surface area of brain regions, that have been previously reported to be involved in both STBs and rumination, were associated with each other (Beta = -0.268, standard error (SE) = 0.114, Z = -2.346, p = 0.019), only increased rumination was related to greater severity of suicidal ideation (Beta = 0.281, SE = 0.132, Z = 2.134, p = 0.033). In addition, we observed that recent stress was associated with lower surface area in the suicidal ideation model without covariate only (Beta = -0.312, SE = 0.149, Z = -2.089, p = 0.037). For the attempt models, no associations were found between any of the risk factors and suicide attempts.

LIMITATIONS

We emphasize that these findings from this secondary analysis are hypothesis-forming and preliminary in nature given the small sample size for SEM analyses.

CONCLUSION

Our findings suggest that neither lower surface area nor recent stress are directly associated with youth suicidal ideation or attempt. However, lower surface area is related to recent stress and increased rumination, which predicted greater severity of suicidal ideation in young people with MDD.

Genomics-driven screening for causal determinants of suicide attempt

OBJECTIVE

Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt.

METHODS

We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology.

RESULTS

Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator.

CONCLUSIONS

Suicide attempt risk is likely explained by a combination of behavioural phenotypes and risk for both physical and psychiatric disorders. Our results also suggest that substance use behaviours and pain-related conditions are associated with an increased suicide attempt risk, elucidating important causal mechanisms that underpin this significant public health problem.

Brain grey and white matter structural associations with future suicidal ideation and behaviors in adolescent and young adult females with mood disorders

Background

To reduce suicide in females with mood disorders, it is critical to understand brain substrates underlying their vulnerability to future suicidal ideation and behaviors (SIBs) in adolescence and young adulthood. In an international collaboration, grey and white matter structure was investigated in adolescent and young adult females with future suicidal behaviors (fSB) and ideation (fSI), and without SIBs (fnonSIB).

Methods

Structural (n = 91) and diffusion-weighted (n = 88) magnetic resonance imaging scans at baseline and SIB measures at follow-up on average two years later (standard deviation, SD = 1 year) were assessed in 92 females [age(SD) = 16.1(2.6) years] with bipolar disorder (BD, 28.3%) or major depressive disorder (MDD, 71.7%). One-way analyses of covariance comparing baseline regional grey matter cortical surface area, thickness, subcortical grey volumes, or white matter tensor-based fractional anisotropy across fSB (n = 40, 43.5%), fSI (n = 33, 35.9%) and fnonSIB (n = 19, 20.6%) groups were followed by pairwise comparisons in significant regions (p < 0.05).

Results

Compared to fnonSIBs, fSIs and fSBs showed significant decreases in cortical thickness of right inferior frontal gyrus pars orbitalis and middle temporal gyrus, fSIs of left inferior frontal gyrus, pars orbitalis. FSIs and fSBs showed lower fractional anisotropy in left uncinate fasciculus and corona radiata, and fSBs in right uncinate and superior fronto-occipital fasciculi.

Conclusions

The study provides preliminary evidence of grey and white matter alterations in brain regions subserving emotional and behavioral regulation and perceptual processing in adolescent and young adult females with mood disorders with, versus without, future SIBs. Findings suggest potential targets to prevent SIBs in female adolescents and young adults.

Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium

Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

Risk Factors for Suicide Attempt During Outpatient Care in Adolescents With Severe and Complex Depression

Background: Young people receiving tertiary mental health care are at elevated risk for suicidal behavior, and understanding which individuals are at increased risk during care is important for treatment and suicide prevention. Aim: We aimed to retrospectively identify risk factors for attempted suicide during outpatient care and predict which young people did or did not attempt during care. Method: Penalized logistic regression analysis was performed in a small high-risk sample of 84 young people receiving care at Orygen's Youth Mood Clinic (age: 14-25 years, 51% female) to predict suicide attempt during care (N = 16). Results: Prediction of suicide attempt during care was only moderately accurate (Area Under the Receiver Operating Curve range 0.71; sensitivity 0.57) using a combination of sociodemographic, psychosocial, and clinical variables. The features that best discriminated both groups included suicidal ideation during care, history of suicide attempt prior to care, changes in appetite reported on the PHQ-9, history of parental separation, and parental mental illness. Limitation: Replication of findings in an independent validation sample is needed. Conclusion: While prediction of suicide attempt during care was only moderately successful, we were able to identify individual risk factors for suicidal behavior during care in a high-risk sample.

Classification of suicidal thoughts and behaviour in children: results from penalised logistic regression analyses in the Adolescent Brain Cognitive Development study

BACKGROUND

Despite efforts to predict suicide risk in children, the ability to reliably identify who will engage in suicide thoughts or behaviours has remained unsuccessful.

AIMS

We apply a novel machine-learning approach and examine whether children with suicide thoughts or behaviours could be differentiated from children without suicide thoughts or behaviours based on a combination of traditional (sociodemographic, physical health, social-environmental, clinical psychiatric) risk factors, but also more novel risk factors (cognitive, neuroimaging and genetic characteristics).

METHOD

The study included 5885 unrelated children (50% female, 67% White, 9-11 years of age) from the Adolescent Brain Cognitive Development (ABCD) study. We performed penalised logistic regression analysis to distinguish between: (a) children with current or past suicide thoughts or behaviours; (b) children with a mental illness but no suicide thoughts or behaviours (clinical controls); and (c) healthy control children (no suicide thoughts or behaviours and no history of mental illness). The model was subsequently validated with data from seven independent sites involved in the ABCD study (n = 1712).

RESULTS

Our results showed that we were able to distinguish the suicide thoughts or behaviours group from healthy controls (area under the receiver operating characteristics curve: 0.80 child-report, 0.81 for parent-report) and clinical controls (0.71 child-report and 0.76-0.77 parent-report). However, we could not distinguish children with suicidal ideation from those who attempted suicide (AUROC: 0.55-0.58 child-report; 0.49-0.53 parent-report). The factors that differentiated the suicide thoughts or behaviours group from the clinical control group included family conflict, prodromal psychosis symptoms, impulsivity, depression severity and history of mental health treatment.

CONCLUSIONS

This work highlights that mostly clinical psychiatric factors were able to distinguish children with suicide thoughts or behaviours from children without suicide thoughts or behaviours. Future research is needed to determine if these variables prospectively predict subsequent suicidal behaviour.

ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.

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

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.

Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.

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.

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

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.

The impact of depression and anxiety treatment on biological aging and metabolic stress: study protocol of the MOod treatment with antidepressants or running (MOTAR) study

BACKGROUND

Depressive and anxiety disorders have shown to be associated to premature or advanced biological aging and consequently to adversely impact somatic health. Treatments with antidepressant medication or running therapy are both found to be effective for many but not all patients with mood and anxiety disorders. These interventions may, however, work through different pathophysiological mechanisms and could differ in their impact on biological aging and somatic health. This study protocol describes the design of an unique intervention study that examines whether both treatments are similarly effective in reducing or reversing biological aging (primary outcome), psychiatric status, metabolic stress and neurobiological indicators (secondary outcomes).

METHODS

The MOod Treatment with Antidepressants or Running (MOTAR) study will recruit a total of 160 patients with a current major depressive and/or anxiety disorder in a mental health care setting. Patients will receive a 16-week treatment with either antidepressant medication or running therapy (3 times/week). Patients will undergo the treatment of their preference and a subsample will be randomized (1:1) to overcome preference bias. An additional no-disease-no-treatment group of 60 healthy controls without lifetime psychopathology, will be included as comparison group for primary and secondary outcomes at baseline. Assessments are done at week 0 for patients and controls, and at week 16 and week 52 for patients only, including written questionnaires, a psychiatric and medical examination, blood, urine and saliva collection and a cycle ergometer test, to gather information about biological aging (telomere length and telomerase activity), mental health (depression and anxiety disorder characteristics), general fitness, metabolic stress-related biomarkers (inflammation, metabolic syndrome, cortisol) and genetic determinants. In addition, neurobiological alterations in brain processes will be assessed using structural and functional Magnetic Resonance Imaging (MRI) in a subsample of at least 25 patients per treatment arm and in all controls.

DISCUSSION

This intervention study aims to provide a better understanding of the impact of antidepressant medication and running therapy on biological aging, metabolic stress and neurobiological indicators in patients with depressive and anxiety disorders in order to guide a more personalized medicine treatment.

TRIAL REGISTRATION

Trialregister.nl Number of identification: NTR3460, May 2012.

Neuroimaging predictors of onset and course of depression in childhood and adolescence: A systematic review of longitudinal studies

Major depressive disorder (MDD) often emerges during adolescence with detrimental effects on development as well as lifetime consequences. Identifying neurobiological markers that are associated with the onset or course of this disorder in childhood and adolescence is important for early recognition and intervention and, potentially, for the prevention of illness onset. In this systematic review, 68 longitudinal neuroimaging studies, from 34 unique samples, that examined the association of neuroimaging markers with onset or changes in paediatric depression published up to 1 February 2019 were examined. These studies employed different imaging modalities at baseline; structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI) or electroencephalography (EEG). Most consistent evidence across studies was found for blunted reward-related (striatal) activity (fMRI and EEG) as a potential biological marker for both MDD onset and course. With regard to structural brain measures, the results were highly inconsistent, likely caused by insufficient power to detect complex mediating effects of genetic and environmental factors in small sample sizes. Overall, there were a limited number of samples, and confounding factors such as sex and pubertal development were often not considered, whereas these factors are likely to be relevant especially in this age range.

White matter architecture in major depression with anxious distress symptoms

BACKGROUND

Comorbid anxious distress is common in Major Depressive Disorder (MDD), and associated with significantly worse clinical course and treatment response. While DSM-5 recently introduced the Anxious Distress (AD) specifier as a potentially useful symptom-based subtyping scheme for MDD, its neurobiological underpinnings remain unclear. The current study hence uniquely probed whether MDD with co-occurring AD (MDD/AD+) relates to distinct perturbations in frontolimbic white matter (WM) pathways tentatively theorized in MDD/AD+ pathophysiology.

METHODS

Tract-based spatial statistics (TBSS) was therefore used to analyze diffusion tensor imaging data on WM microstructure, in MDD/AD+ patients (N = 20) relative to MDD patients without AD (MDD/AD-; N = 29) and healthy controls (HC; N = 39). Using TBSS, we probed fractional anisotropy and axial/radial/mean diffusivity as proxies for WM integrity. Categorical (between-groups) and dimensional (within-patients) analyses subsequently assessed how Anxious Distress in MDD impacts frontolimbic WM connectivity. Receiver-Operating Characteristics additionally assessed classification capabilities of between-groups WM effects.

RESULTS

Compared to MDD/AD- and HC participants, MDD/AD+ patients exhibited diminished integrity within the anterior thalamic radiation (ATR). Higher AD specifier scores within MDD patients additionally related to diminished integrity of the uncinate fasciculus and cingulum pathways. These effects were not confounded by key clinical (e.g., comorbid anxiety disorder) and sociodemographic (e.g., age/sex) factors, with altered ATR integrity moreover successfully classifying MDD/AD+ patients from MDD/AD- and HC participants (90% sensitivity | 73% specificity | 77% accuracy).

CONCLUSIONS

These findings collectively link MDD/AD+ to distinct WM anomalies in frontolimbic tracts important to adaptive emotional functioning, and may as such provide relevant, yet preliminary, clues on MDD/AD+ pathophysiology.

Effect of childhood maltreatment and brain-derived neurotrophic factor on brain morphology

Childhood maltreatment (CM) has been associated with altered brain morphology, which may partly be due to a direct impact on neural growth, e.g. through the brain-derived neurotrophic factor (BDNF) pathway. Findings on CM, BDNF and brain volume are inconsistent and have never accounted for the entire BDNF pathway. We examined the effects of CM, BDNF (genotype, gene expression and protein level) and their interactions on hippocampus, amygdala and anterior cingulate cortex (ACC) morphology. Data were collected from patients with depression and/or an anxiety disorder and healthy subjects within the Netherlands Study of Depression and Anxiety (NESDA) (N = 289). CM was assessed using the Childhood Trauma Interview. BDNF Val66Met genotype, gene expression and serum protein levels were determined in blood and T1 MRI scans were acquired at 3T. Regional brain morphology was assessed using FreeSurfer. Covariate-adjusted linear regression analyses were performed. Amygdala volume was lower in maltreated individuals. This was more pronounced in maltreated met-allele carriers. The expected positive relationship between BDNF gene expression and volume of the amygdala is attenuated in maltreated subjects. Finally, decreased cortical thickness of the ACC was identified in maltreated subjects with the val/val genotype. CM was associated with altered brain morphology, partly in interaction with multiple levels of the BNDF pathway. Our results suggest that CM has different effects on brain morphology in met-carriers and val-homozygotes and that CM may disrupt the neuroprotective effect of BDNF.

Heritability and reliability of automatically segmented human hippocampal formation subregions

The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test-retest reliability and transplatform reliability (1.5T versus 3T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N=39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N=163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N=598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h(2)) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test-retest reliability was high for all twelve subregions in the 3T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70-0.97) and moderate-to-high in the 4T QTIM sample (ICC=0.5-0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC=0.66-0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5T and 3T field strengths (ICC=0.47-0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC=0.78-0.84; Dice Similarity Coefficient (DSC)=0.55-0.70), and poor for all other subregions (ICC=0.34-0.81; DSC=0.28-0.51). All hippocampal subregion volumes were highly heritable (h(2)=0.67-0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium.

Altered inhibition-related frontolimbic connectivity in obsessive-compulsive disorder

BACKGROUND

Recent studies have shown that response inhibition is impaired in patients with obsessive-compulsive disorder and their unaffected siblings, suggesting that these deficits may be considered a cognitive endophenotype of obsessive-compulsive disorder. Structural and functional neural correlates of altered response inhibition have been identified in patients and siblings. This study aims to examine the functional integrity of the response inhibition network in patients with obsessive-compulsive disorder and their unaffected siblings.

METHODS

Forty-one unmedicated patients with obsessive-compulsive disorder, 17 of their unaffected siblings and 37 healthy controls performed a stop signal task during functional magnetic resonance imaging. Psycho-physiological interaction analysis was used to examine functional connectivity between the following regions of interest: the bilateral inferior frontal gyri, presupplementary motor area, subthalamic nuclei, inferior parietal lobes, anterior cingulate cortex, and amygdala. We then used dynamic causal modeling to investigate the directionality of the networks involved.

RESULTS

Patients, and to a lesser extent also their unaffected siblings, show altered connectivity between the inferior frontal gyrus and the amygdala during response inhibition. The follow-up dynamic causal modeling suggests a bottom-up influence of the amygdala on the inferior frontal gyrus in healthy controls, whereas processing occurs top-down in patients with obsessive-compulsive, and in both directions in siblings.

CONCLUSIONS

Our findings suggest that amygdala activation in obsessive-compulsive disorder interferes differently with the task-related recruitment of the inhibition network, underscoring the role of limbic disturbances in cognitive dysfunctions in obsessive-compulsive disorder.

Response inhibition and interference control in obsessive-compulsive spectrum disorders

Over the past 20 years, motor response inhibition and interference control have received considerable scientific effort and attention, due to their important role in behavior and the development of neuropsychiatric disorders. Results of neuroimaging studies indicate that motor response inhibition and interference control are dependent on cortical–striatal–thalamic–cortical (CSTC) circuits. Structural and functional abnormalities within the CSTC circuits have been reported for many neuropsychiatric disorders, including obsessive–compulsive disorder (OCD) and related disorders, such as attention-deficit hyperactivity disorder, Tourette’s syndrome, and trichotillomania. These disorders also share impairments in motor response inhibition and interference control, which may underlie some of their behavioral and cognitive symptoms. Results of task-related neuroimaging studies on inhibitory functions in these disorders show that impaired task performance is related to altered recruitment of the CSTC circuits. Previous research has shown that inhibitory performance is dependent upon dopamine, noradrenaline, and serotonin signaling, neurotransmitters that have been implicated in the pathophysiology of these disorders. In this narrative review, we discuss the common and disorder-specific pathophysiological mechanisms of inhibition-related dysfunction in OCD and related disorders.