Genetic correlations between wellbeing, depression and anxiety symptoms and behavioral responses to the emotional faces task in healthy twins

Currently there is a very limited understanding of how mental wellbeing versus anxiety and depression symptoms are associated with emotion processing behaviour. For the first time, we examined these associations using a behavioural emotion task of positive and negative facial expressions in 1668 healthy adult twins. Linear mixed model results suggested faster reaction times to happy facial expressions was associated with higher wellbeing scores, and slower reaction times with higher depression and anxiety scores. Multivariate twin modelling identified a significant genetic correlation between depression and anxiety symptoms and reaction time to happy facial expressions, in the absence of any significant correlations with wellbeing. We also found a significant negative phenotypic relationship between depression and anxiety symptoms and accuracy for identifying neutral emotions, although the genetic or environment correlations were not significant in the multivariate model. Overall, the phenotypic relationships between speed of identifying happy facial expressions and wellbeing on the one hand, versus depression and anxiety symptoms on the other, were in opposing directions. Twin modelling revealed a small common genetic correlation between response to happy faces and depression and anxiety symptoms alone, suggesting that wellbeing and depression and anxiety symptoms show largely independent relationships with emotion processing at the behavioral level.

Sex, Sleep Deprivation, and the Anxious Brain

Insufficient sleep is a known trigger of anxiety. Nevertheless, not everyone experiences these effects to the same extent. One determining factor is sex, wherein women experience a greater anxiogenic impact in response to sleep loss than men. However, the underlying brain mechanism(s) governing this sleep-loss-induced anxiety increase, including the markedly different reaction in women and men, is unclear. Here, we tested the hypothesis that structural brain morphology in a discrete network of emotion-relevant regions represents one such explanatory factor. Healthy participants were assessed across sleep-rested and sleep-deprived conditions, with brain structure quantified using gray matter volume measures. Sleep loss triggered greater levels of anxiety in women compared with men. Reduced gray matter volume in the anterior insula and lateral orbitofrontal cortex predicted the anxiogenic impact of sleep loss in women, yet predicted resilience in men, and did so with high discrimination accuracy. In contrast, gray matter volume in ventromedial prefrontal cortex predicted the anxiogenic impact of sleep loss in both men and women. Structural human brain morphology therefore appears to represent one mechanistic pathway (and possible biomarker) determining anxiety vulnerability to sleep loss-a discovery that may help explain the higher prevalence of sleep disruption and anxiety in women.

Antidepressant Outcomes Predicted by Genetic Variation in Corticotropin-Releasing Hormone Binding Protein

OBJECTIVE

Genetic variation within the hypothalamic-pituitary-adrenal (HPA) axis has been linked to risk for depression and antidepressant response. However, these associations have yet to produce clinical gains that inform treatment decisions. The authors investigated whether variation within HPA axis genes predicts antidepressant outcomes within two large clinical trials.

METHOD

The test sample comprised 636 patients from the International Study to Predict Optimized Treatment in Depression (iSPOT-D) who completed baseline and 8-week follow-up visits and for whom complete genotyping data were available. The authors tested the relationship between genotype at 16 candidate HPA axis single-nucleotide polymorphisms (SNPs) and treatment outcomes for three commonly used antidepressants (escitalopram, sertraline, and extended-release venlafaxine), using multivariable linear and logistic regression with Bonferroni correction. Response and remission were defined using the Hamilton Depression Rating Scale. Findings were then validated using the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study of outcome predictors in treatment-naive patients with major depression.

RESULTS

The authors found that the rs28365143 variant within the corticotropin-releasing hormone binding protein (CRHBP) gene predicted antidepressant outcomes for remission, response, and symptom change. Patients homozygous for the G allele of rs28365143 had greater remission rates, response rates, and symptom reductions. These effects were specific to drug class. Patients homozygous for the G allele responded significantly better to the selective serotonin reuptake inhibitors escitalopram and sertraline than did A allele carriers. In contrast, rs28365143 genotype was not associated with treatment outcomes for the serotonin norepinephrine reuptake inhibitor venlafaxine. When patients were stratified by race, the overall effect of genotype on treatment response remained. In the validation sample, the GG genotype was again associated with favorable antidepressant outcomes, with comparable effect sizes.

CONCLUSIONS

These findings suggest that a specific CRHBP SNP, rs28365143, may have a role in predicting which patients will improve with antidepressants and which type of antidepressant may be most effective. The results add to the foundational knowledge needed to advance a precision approach to personalized antidepressant choices.

"Motoring in idle": The default mode and somatomotor networks are overactive in children and adolescents with functional neurological symptoms

Objective

Children and adolescents with functional neurological symptom disorder (FND) present with diverse neurological symptoms not explained by a disease process. Functional neurological symptoms have been conceptualized as somatoform dissociation, a disruption of the brain's intrinsic organization and reversion to a more primitive level of function. We used EEG to investigate neural function and functional brain organization in children/adolescents with FND.

Method

EEG was recorded in the resting eyes-open condition in 57 patients (aged 8.5-18 years) and 57 age- and sex-matched healthy controls. Using a topographical map, EEG power data were quantified for regions of interest that define the default mode network (DMN), salience network, and somatomotor network. Source localization was examined using low-resolution brain electromagnetic tomography (LORETA). The contributions of chronic pain and arousal as moderators of differences in EEG power were also examined.

Results

Children/adolescents with FND had excessive theta and delta power in electrode clusters corresponding to the DMN-both anteriorly (dorsomedial prefrontal cortex [dmFPC]) and posteriorly (posterior cingulate cortex [PCC], precuneus, and lateral parietal cortex)-and in the premotor/supplementary motor area (SMA) region. There was a trend toward increased theta and delta power in the salience network. LORETA showed activation across all three networks in all power bands and localized neural sources to the dorsal anterior cingulate cortex/dmPFC, mid cingulate cortex, PCC/precuneus, and SMA. Pain and arousal contributed to slow wave power increases in all three networks.

Conclusions

These findings suggest that children and adolescents with FND are characterized by overactivation of intrinsic resting brain networks involved in threat detection, energy regulation, and preparation for action.

Profiling risk for depressive disorder by circuit, behavior and self-report measures of emotion function

BACKGROUND

Major depressive disorder (MDD) is characterized by maladaptions in affective brain circuitry and in emotion regulation. It remains unknown whether these maladaptions characterize first-degree relatives of probands who are unaffected yet have a higher risk of developing MDD.

METHODS

Participants were 72 unaffected first-degree relatives of probands with MDD and 66 matched non-relative controls. We investigated brain circuit function and self-reported emotion regulation strategies for reappraisal and suppression. During functional magnetic resonance imaging, we probed circuitry relevant to both negative and positive valence systems using facial expressions signaling potential threat, sadness and happiness, presented under both conscious and subliminal viewing conditions. We compared groups using a statistically controlled region of interest (ROI) approach including the amygdala, insula, anterior cingulate cortex (ACC), ventromedial prefrontal cortex and dorsolateral prefrontal cortex. We also used a data-driven cluster analytic approach for characterizing the relatives by their brain function profiles.

RESULTS

As a group, relatives were distinguished by hyper-reactivity of the pregenual ACC during subliminal viewing of threat-related expressions but hypo-activation of the amygdala, insula and dorsal ACC during explicit viewing of the same threat-related expressions and sadness. When considered individually, this brain function profile characterized two-thirds of relatives, and these relatives were also less likely to use reappraisal to regulate negative emotion.

LIMITATIONS

The design was cross-sectional and therefore does not provide direct evidence as to the trait- (versus state-) like profile observed in relatives.

CONCLUSIONS

Familial risk for MDD may involve a disruption to the normal recruitment of neural circuits for appraising salient emotions, both implicit and explicit. Interventions targeting reappraisal strategies for regulating negative emotion may serve to buffer this risk.

Transdiagnostic Symptom Clusters and Associations With Brain, Behavior, and Daily Function in Mood, Anxiety, and Trauma Disorders

IMPORTANCE

The symptoms that define mood, anxiety, and trauma disorders are highly overlapping across disorders and heterogeneous within disorders. It is unknown whether coherent subtypes exist that span multiple diagnoses and are expressed functionally (in underlying cognition and brain function) and clinically (in daily function). The identification of cohesive subtypes would help disentangle the symptom overlap in our current diagnoses and serve as a tool for tailoring treatment choices.

OBJECTIVE

To propose and demonstrate 1 approach for identifying subtypes within a transdiagnostic sample.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed data from the Brain Research and Integrative Neuroscience Network Foundation Database that had been collected at the University of Sydney and University of Adelaide between 2006 and 2010 and replicated at Stanford University between 2013 and 2017. The study included 420 individuals with a primary diagnosis of major depressive disorder (n = 100), panic disorder (n = 53), posttraumatic stress disorder (n = 47), or no disorder (healthy control participants) (n = 220). Data were analyzed between October 2016 and October 2017.

MAIN OUTCOMES AND MEASURES

We followed a data-driven approach to achieve the primary study outcome of identifying transdiagnostic subtypes. First, machine learning with a hierarchical clustering algorithm was implemented to classify participants based on self-reported negative mood, anxiety, and stress symptoms. Second, the robustness and generalizability of the subtypes were tested in an independent sample. Third, we assessed whether symptom subtypes were expressed at behavioral and physiological levels of functioning. Fourth, we evaluated the clinically meaningful differences in functional capacity of the subtypes. Findings were interpreted relative to a complementary diagnostic frame of reference.

RESULTS

Four hundred twenty participants with a mean (SD) age of 39.8 (14.1) years were included in the final analysis; 256 (61.0%) were female. We identified 6 distinct subtypes characterized by tension (n=81; 19%), anxious arousal (n=55; 13%), general anxiety (n=38; 9%), anhedonia (n=29; 7%), melancholia (n=37; 9%), and normative mood (n=180; 43%), and these subtypes were replicated in an independent sample. Subtypes were expressed through differences in cognitive control (F5,383 = 5.13, P < .001, ηp2 = 0.063), working memory (F5,401 = 3.29, P = .006, ηp2 = 0.039), electroencephalography-recorded β power in a resting paradigm (F5,357 = 3.84, P = .002, ηp2 = 0.051), electroencephalography-recorded β power in an emotional paradigm (F5,365 = 3.56, P = .004, ηp2 = 0.047), social functional capacity (F5,414 = 21.33, P < .001, ηp2 = 0.205), and emotional resilience (F5,376 = 15.10, P < .001, ηp2 = 0.171).

CONCLUSIONS AND RELEVANCE

These findings offer a data-driven framework for identifying robust subtypes that signify specific, coherent, meaningful associations between symptoms, behavior, brain function, and observable real-world function, and that cut across DSM-IV-defined diagnoses of major depressive disorder, panic disorder, and posttraumatic stress disorder.

A Public Database of Immersive VR Videos with Corresponding Ratings of Arousal, Valence, and Correlations between Head Movements and Self Report Measures

Virtual reality (VR) has been proposed as a methodological tool to study the basic science of psychology and other fields. One key advantage of VR is that sharing of virtual content can lead to more robust replication and representative sampling. A database of standardized content will help fulfill this vision. There are two objectives to this study. First, we seek to establish and allow public access to a database of immersive VR video clips that can act as a potential resource for studies on emotion induction using virtual reality. Second, given the large sample size of participants needed to get reliable valence and arousal ratings for our video, we were able to explore the possible links between the head movements of the observer and the emotions he or she feels while viewing immersive VR. To accomplish our goals, we sourced for and tested 73 immersive VR clips which participants rated on valence and arousal dimensions using self-assessment manikins. We also tracked participants' rotational head movements as they watched the clips, allowing us to correlate head movements and affect. Based on past research, we predicted relationships between the standard deviation of head yaw and valence and arousal ratings. Results showed that the stimuli varied reasonably well along the dimensions of valence and arousal, with a slight underrepresentation of clips that are of negative valence and highly arousing. The standard deviation of yaw positively correlated with valence, while a significant positive relationship was found between head pitch and arousal. The immersive VR clips tested are available online as supplemental material.

Sex differences modulating serotonergic polymorphisms implicated in the mechanistic pathways of risk for depression and related disorders

Despite consistent observations of sex differences in depression and related emotional disorders, we do not yet know how these sex differences modulate the effects of genetic polymorphisms implicated in risk for these disorders. This Mini-Review focuses on genetic polymorphisms of the serotonergic system to illustrate how sex differences might modulate the neurobiological pathways involved in the development of depression. We consider the interacting role of environmental factors such as early-life stress. Given limited current knowledge about this topic, we highlight methodological considerations, challenges, and guidelines for future research. © 2016 Wiley Periodicals, Inc.

Is the Alzheimer's disease cortical thickness signature a biological marker for memory?

Recent work suggests that analysis of the cortical thickness in key brain regions can be used to identify individuals at greatest risk for development of Alzheimer's disease (AD). It is unclear to what extent this "signature" is a biological marker of normal memory function - the primary cognitive domain affected by AD. We examined the relationship between the AD signature biomarker and memory functioning in a group of neurologically healthy young and older adults. Cortical thickness measurements and neuropsychological evaluations were obtained in 110 adults (age range 21-78, mean = 46) drawn from the Brain Resource International Database. The cohort was divided into young adult (n = 64, age 21-50) and older adult (n = 46, age 51-78) groups. Cortical thickness analysis was performed with FreeSurfer, and the average cortical thickness extracted from the eight regions that comprise the AD signature. Mean AD-signature cortical thickness was positively associated with performance on the delayed free recall trial of a list learning task and this relationship did not differ between younger and older adults. Mean AD-signature cortical thickness was not associated with performance on a test of psychomotor speed, as a control task, in either group. The results suggest that the AD signature cortical thickness is a marker for memory functioning across the adult lifespan.

Cyprinid herpesvirus 3 as a potential biological control agent for carp (Cyprinus carpio) in Australia: susceptibility of non-target species

Carp (Cyprinus carpio L.) is a pest species in Australian waterways, and cyprinid herpesvirus 3 (CyHV-3) is being considered as a potential biological control (biocontrol) agent. An important consideration for any such agent is its target specificity. In this study, the susceptibility to CyHV-3 of a range of non-target species (NTS) was tested. The NTS were as follows: 13 native Australian, and one introduced, fish species; a lamprey species; a crustacean; two native amphibian species (tadpole and mature stages); two native reptilian species; chickens; and laboratory mice. Animals were exposed to 100-1000 times the approximate minimum amount of CyHV-3 required to cause disease in carp by intraperitoneal and/or bath challenge, and then examined clinically each day over the course of 28 days post-challenge. There were no clinical signs, mortalities or histological evidence consistent with a viral infection in a wide taxonomic range of NTS. Furthermore, there was no molecular evidence of infection with CyHV-3, and, in particular, all RT-PCRs for viral mRNA were negative. As a consequence, the results encourage further investigation of CyHV-3 as a potential biocontrol agent that is specific for carp.

Utilizing a transdiagnostic neuroscience-informed approach to differentiate the components of a complex clinical presentation: A case report

Background

Recent research recognizes considerable overlap in the clinical presentation of psychiatric disorders such as Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder and Social Anxiety Disorder. The diagnostic approach collects symptoms to reflect a single underlying psychopathological process. The Research Domain Criteria (RDoC) emphasizes psychopathology as arising from combinations of abnormalities in core underlying constructs that can be measured at many levels of analysis, from biological to behavioral. Patients who present with clinical heterogeneity may benefit from transdiagnostic case conceptualization that integrates detailed symptom information across multiple measurements spanning multiple domains of functioning based in the RDoC framework.

Case presentation

We report on one case that was included in a research study focused on advancing knowledge towards a transdiagnostic, brain-based model of anxiety and depression. The 20-year-old male patient presented at a community mental health clinic for inattention, low mood, sleep problems and anxious symptoms. The patient also presented with primary problems in negative valence systems (anxiety, avoidance, and bias towards negative information), cognitive systems (fluctuating cognitive ability over time, poor concentration and ability to focus), and social processing systems (deficits in social communication skills). Conceptualizing this case through a transdiagnostic lens augmented the patient's treatment plan by including a more integrative approach. Treatment included social skills training, progressive relaxation exercises, and basic psychoeducation in emotional expression and independent living skills.

Conclusion

This case illustrates the utility of a transdiagnostic approach, particularly when a traditional diagnostic model generates conflicting evidence and/or multiple comorbidities. RDoC provides a framework for integrating abnormalities across multiple dimensions. Furthermore, it lays the foundation for future integration of brain-behavior relationships into case conceptualization and personalized treatment approaches.

Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization. We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I (n = 16) or as ADHD-C (n = 18) and 28 matched typically developing controls, aged 8-17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry. Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in "nodal degree"). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization. Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be reflected in distinct aberrations in underlying brain organization.

Grey matter abnormalities in children and adolescents with functional neurological symptom disorder

Objective

Functional neurological symptom disorder refers to the presence of neurological symptoms not explained by neurological disease. Although this disorder is presumed to reflect abnormal function of the brain, recent studies in adults show neuroanatomical abnormalities in brain structure. These structural brain abnormalities have been presumed to reflect long-term adaptations to the disorder, and it is unknown whether child and adolescent patients, with illness that is typically of shorter duration, show similar deficits or have normal brain structure.

Method

High-resolution, three-dimensional T1-weighted magnetic resonance images (MRIs) were acquired in 25 patients (aged 10–18 years) and 24 healthy controls. Structure was quantified in terms of grey matter volume using voxel-based morphometry. Post hoc, we examined whether regions of structural difference related to a measure of motor readiness to emotional signals and to clinical measures of illness duration, illness severity, and anxiety/depression.

Results

Patients showed greater volumes in the left supplementary motor area (SMA) and right superior temporal gyrus (STG) and dorsomedial prefrontal cortex (DMPFC) (corrected p < 0.05). Previous studies of adult patients have also reported alterations of the SMA. Greater SMA volumes correlated with faster reaction times in identifying emotions but not with clinical measures.

Conclusions

The SMA, STG, and DMPFC are known to be involved in the perception of emotion and the modulation of motor responses. These larger volumes may reflect the early expression of an experience-dependent plasticity process associated with increased vigilance to others' emotional states and enhanced motor readiness to organize self-protectively in the context of the long-standing relational stress that is characteristic of this disorder.

•

We used high-resolution MRI to investigate brain structure in children presenting with acute functional neurological symptom disorder (FND).

•

Patients had multiple antecedent stressors, a long-standing history of relational stress and at-risk attachment strategies.

•

Patients had greater volumes in the SMA—where motor-, cognitive-, and emotion-processing signals interact to influence motor function.

•

FND may involve experience-dependent changes in brain structure alongside experience-dependent changes in brain function.

The new field of 'precision psychiatry'

BACKGROUND

Precision medicine is a new and important topic in psychiatry. Psychiatry has not yet benefited from the advanced diagnostic and therapeutic technologies that form an integral part of other clinical specialties. Thus, the vision of precision medicine as applied to psychiatry - 'precision psychiatry' - promises to be even more transformative than in other fields of medicine, which have already lessened the translational gap.

DISCUSSION

Herein, we describe 'precision psychiatry' and how its several implications promise to transform the psychiatric landscape. We pay particular attention to biomarkers and to how the development of new technologies now makes their discovery possible and timely. The adoption of the term 'precision psychiatry' will help propel the field, since the current term 'precision medicine', as applied to psychiatry, is impractical and does not appropriately distinguish the field. Naming the field 'precision psychiatry' will help establish a stronger, unique identity to what promises to be the most important area in psychiatry in years to come.

CONCLUSION

In summary, we provide a wide-angle lens overview of what this new field is, suggest how to propel the field forward, and provide a vision of the near future, with 'precision psychiatry' representing a paradigm shift that promises to change the landscape of how psychiatry is currently conceived.

Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: a theoretical review of the evidence and future directions for clinical translation

Complex emotional, cognitive and self-reflective functions rely on the activation and connectivity of large-scale neural circuits. These circuits offer a relevant scale of focus for conceptualizing a taxonomy for depression and anxiety based on specific profiles (or biotypes) of neural circuit dysfunction. Here, the theoretical review first outlines the current consensus as to what constitutes the organization of large-scale circuits in the human brain identified using parcellation and meta-analysis. The focus is on neural circuits implicated in resting reflection (default mode), detection of "salience," affective processing ("threat" and "reward"), "attention," and "cognitive control." Next, the current evidence regarding which type of dysfunctions in these circuits characterize depression and anxiety disorders is reviewed, with an emphasis on published meta-analyses and reviews of circuit dysfunctions that have been identified in at least two well-powered case:control studies. Grounded in the review of these topics, a conceptual framework is proposed for considering neural circuit-defined "biotypes." In this framework, biotypes are defined by profiles of extent of dysfunction on each large-scale circuit. The clinical implications of a biotype approach for guiding classification and treatment of depression and anxiety is considered. Future research directions will develop the validity and clinical utility of a neural circuit biotype model that spans diagnostic categories and helps to translate neuroscience into clinical practice in the real world.

Altered gray matter organization in children and adolescents with ADHD: a structural covariance connectome study

Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome.

Shared versus distinct genetic contributions of mental wellbeing with depression and anxiety symptoms in healthy twins

Mental wellbeing and mental illness symptoms are typically conceptualized as opposite ends of a continuum, despite only sharing about a quarter in common variance. We investigated the normative variation in measures of wellbeing and of depression and anxiety in 1486 twins who did not meet clinical criteria for an overt diagnosis. We quantified the shared versus distinct genetic and environmental variance between wellbeing and depression and anxiety symptoms. The majority of participants (93%) reported levels of depression and anxiety symptoms within the healthy range, yet only 23% reported a wellbeing score within the "flourishing" range: the remainder were within the ranges of "moderate" (67%) or "languishing" (10%). In twin models, measures of wellbeing and of depression and anxiety shared 50.09% of variance due to genetic factors and 18.27% due to environmental factors; the rest of the variance was due to unique variation impacting wellbeing or depression and anxiety symptoms. These findings suggest that an absence of clinically-significant symptoms of depression and anxiety does not necessarily indicate that an individual is flourishing. Both unique and shared genetic and environmental factors may determine why some individuals flourish in the absence of symptoms while others do not.

Cognitive control network anatomy correlates with neurocognitive behavior: A longitudinal study

Cognitive control is the process of employing executive functions, such as attention, planning or working memory, to guide appropriate behaviors in order to achieve a specific goal. Functional magnetic resonance imaging studies suggest a superordinate cognitive control network, comprising the dorsal regions of the lateral prefrontal cortex (DLPFC), anterior cingulate cortex (dACC) and parietal cortex (DPC). How gray matter structure changes across this network throughout neurodevelopment and how these changes impact cognitive control are not yet fully understood. Here we investigate changes in gray matter volume of the key nodes of the cognitive control network using structural MRI scans from 176 participants aged 8-38 years. One hundred and eleven of these also completed a longitudinal follow-up at two years. We compare these with performance on a cognitive battery also measured at these two time points. We found that volume decreases in the cognitive control network were associated with improved performance in executive function (in left DLPFC and bilateral DPC), information processing (in bilateral dACC and right DPC) and emotion identification tasks (left DLPFC). These results were significant after controlling for age. Furthermore, gray matter changes were coordinated across the network. These findings imply age-independent synaptic pruning in the cognitive control network may have a role in improving performance in cognitive domains. This study provides insight into the direct impact of structural changes on behavior within this network during neurodevelopment and provides a normative evidence base to better understand development of cognitive dysfunction in brain disorders. Hum Brain Mapp 38:631-643, 2017. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

A trans-diagnostic review of anxiety disorder comorbidity and the impact of multiple exclusion criteria on studying clinical outcomes in anxiety disorders

Anxiety disorders are highly comorbid with each other and with other serious mental disorders. As our field progresses, we have the opportunity to pursue treatment study designs that consider these comorbidities. In this perspective review, we first characterized the prevalence of multiple anxiety disorder comorbidity by reanalyzing national survey data, then conducted an English-language PubMed search of studies analyzing the impact of exclusion criteria on treatment outcome data. In the prevalence data, 60% of people with an anxiety disorder had one or more additional anxiety or depression diagnosis. Because our commonly applied exclusion criteria focus on a single diagnosis and do not consider a multiple comorbidity profile, the impact of the criteria may be to exclude up to 92% of anxiety disorder treatment seekers. Moreover, the findings do not suggest a consistent relationship between the number of exclusion criteria and the effect size of treatment outcomes. Thus, future studies might consider a more trans-diagnostic rationale for determining exclusion criteria, one that is generalizable to real-world settings in which multiple diagnoses commonly co-occur. The findings also encourage a more systematic reporting of rationales for the choice of-and the implications of-each exclusion criterion.