Gene expression networks regulated by human personality.

Genome-wide association studies of human personality have been carried out, but transcription of the whole genome has not been studied in relation to personality in humans. We collected genome-wide expression profiles of adults to characterize the regulation of expression and function in genes related to human personality. We devised an innovative multi-omic approach to network analysis to identify the key control elements and interactions in multi-modular networks. We identified sets of transcribed genes that were co-expressed in specific brain regions with genes known to be associated with personality. Then we identified the minimum networks for the co-localized genes using bioinformatic resources. Subjects were 459 adults from the Young Finns Study who completed the Temperament and Character Inventory and provided peripheral blood for genomic and transcriptomic analysis. We identified an extrinsic network of 45 regulatory genes from seed genes in brain regions involved in self-regulation of emotional reactivity to extracellular stimuli (e.g., self-regulation of anxiety) and an intrinsic network of 43 regulatory genes from seed genes in brain regions involved in self-regulation of interpretations of meaning (e.g., production of concepts and language). We discovered that interactions between the two networks were coordinated by a control hub of 3 miRNAs and 3 protein-coding genes shared by both. Interactions of the control hub with proteins and ncRNAs identified more than 100 genes that overlap directly with known personality-related genes and more than another 4000 genes that interact indirectly. We conclude that the six-gene hub is the crux of an integrative network that orchestrates information-transfer throughout a multi-modular system of over 4000 genes enriched in liquid-liquid-phase-separation (LLPS)-related RNAs, diverse transcription factors, and hominid-specific miRNAs and lncRNAs. Gene expression networks associated with human personality regulate neuronal plasticity, epigenesis, and adaptive functioning by the interactions of salience and meaning in self-awareness.

Examination of reward processing dysfunctions in the left dorsal striatum and other brain regions among psychiatric inpatients with substance use.

BACKGROUND: Substance misuse is a major public health issue and research has established attenuated reward responses to drug cues in those who misuse substances. Yet, little is known about whether the expectation of natural reinforcers engages distinct brain regions in substance misuse. METHODS: Using functional magnetic resonance imaging (fMRI), we delivered juice at expected and unexpected times to examine reward processing dysfunctions. We focused on the responses within the left dorsal striatum (DS) in individuals with high-risk substance use (HRU, n = 65), low-risk substance use (psychiatric controls, PC, n = 65), and healthy controls (HC, n = 65). Additionally, we investigated whether the dysfunction in reward processing within the left DS is correlated with other common psychiatric symptoms. Finally, we conducted a comprehensive analysis of the whole brain to investigate other non-hypothesized brain regions. RESULTS: Compared to HC, HRU displayed lower responses to juice delivery (i.e., reward) in the left DS (p <.05). The whole-brain analysis demonstrated that compared to HC, HRU displayed significantly lower responses to reward stimuli in various brain regions, including the bilateral caudate, temporal gyrus, left frontal gyrus, middle frontal gyrus, and right thalamus. LIMITATIONS: Participants were individuals with polysubstance use; therefore, we were not able to examine the effects of individual substances. CONCLUSIONS: Our findings suggest that HRU displays lower responses to reward stimuli within the left DS and other non-hypothesized brain regions. Our findings may help further elucidate reward processing dysfunctions related to substance misuse.

Resting-State Functional Connectivity of the Anterior Cingulate Cortex Among Persons With Mood Disorders and Suicidal Behaviors.

OBJECTIVE: To assess whether anterior cingulate cortex (ACC) abnormalities contribute to suicide risk in major depressive disorder and bipolar disorder, the investigators compared resting-state functional connectivity (rsFC) of ACC subdivisions between individuals with major depressive or bipolar disorder with and without a lifetime history of suicidal behavior. METHODS: Forty-two inpatients with and 26 inpatients without a history of suicidal behavior (SB+ and SB-, respectively) associated with major depressive or bipolar disorder and 40 healthy control (HC) participants underwent rsFC neuroimaging. RsFC of the subgenual, perigenual, rostral, dorsal, and caudal subdivisions of the ACC was calculated. Possible confounders, such as psychosis and severity of depression, were controlled for, seed-to-voxel and post hoc region of interest (ROI)-to-ROI analyses were performed, and the accuracy of rsFC in classifying suicidal behavior was studied. RESULTS: Compared with individuals in the SB- and HC groups, patients in the SB+ group had higher rsFC between the left rostral and right dorsal ACC seeds and visual cortex clusters. Conversely, rsFC between the left rostral and right dorsal ACC seeds and cingulate and frontal clusters was lower in the SB+ group than in the HC group. Left rostral ACC to left Brodmann's area 18 connectivity showed up to 75% discriminative accuracy in distinguishing SB+ from SB- patients. CONCLUSIONS: A history of suicidal behavior among individuals with major depressive disorder or bipolar disorder was associated with altered rsFC of the rostral and caudal ACC, regions involved in conflict detection and error monitoring. Replication of these findings is needed to further explore the involvement of the ACC in the neurobiology of suicidal behavior and suicidal ideation.

Framework for Accurate Classification of Self-Reported Stress From Multisession Functional MRI Data of Veterans With Posttraumatic Stress.

Background: Posttraumatic stress disorder (PTSD) is a significant burden among combat Veterans returning from the wars in Iraq and Afghanistan. While empirically supported treatments have demonstrated reductions in PTSD symptomatology, there remains a need to improve treatment effectiveness. Functional magnetic resonance imaging (fMRI) neurofeedback has emerged as a possible treatment to ameliorate PTSD symptom severity. Virtual reality (VR) approaches have also shown promise in increasing treatment compliance and outcomes. To facilitate fMRI neurofeedback-associated therapies, it would be advantageous to accurately classify internal brain stress levels while Veterans are exposed to trauma-associated VR imagery. Methods: Across 2 sessions, we used fMRI to collect neural responses to trauma-associated VR-like stimuli among male combat Veterans with PTSD symptoms (N = 8). Veterans reported their self-perceived stress level on a scale from 1 to 8 every 15 s throughout the fMRI sessions. In our proposed framework, we precisely sample the fMRI data on cortical gray matter, blurring the data along the gray-matter manifold to reduce noise and dimensionality while preserving maximum neural information. Then, we independently applied 3 machine learning (ML) algorithms to this fMRI data collected across 2 sessions, separately for each Veteran, to build individualized ML models that predicted their internal brain states (self-reported stress responses). Results: We accurately classified the 8-class self-reported stress responses with a mean (± standard error) root mean square error of 0.6 (± 0.1) across all Veterans using the best ML approach. Conclusions: The findings demonstrate the predictive ability of ML algorithms applied to whole-brain cortical fMRI data collected during individual Veteran sessions. The framework we have developed to preprocess whole-brain cortical fMRI data and train ML models across sessions would provide a valuable tool to enable individualized real-time fMRI neurofeedback during VR-like exposure therapy for PTSD.

miR-124-3p target genes identify globus pallidus role in suicide ideation recovery in borderline personality disorder.

Borderline personality disorder (BPD) is characterized by patterns of unstable affect, unstable interpersonal relationships, and chronic suicidal tendencies. Research on the genetics, epigenetics, and brain function of BPD is lacking. MicroRNA-124-3p (miR-124-3p) was recently identified in a Genome-Wide Association Study as likely associated with BPD. Here, we identified the anatomical brain expression of genes likely modulated by miR-124-3p and compared morphometry in those brain regions in BPD inpatients vs. controls matched for psychiatric comorbidities. We isolated lists of targets likely modulated by miR-124-3p from TargetScan (v 8.0) by their preferentially conserved targeting (Aggregate PCT > 0.99, see Supplementary Table 1). We applied Process Genes List (PGL) to identify regions of interest associated with the co-expression of miR-124-3p target genes. We compared the gray matter volume of the top region of interest co-expressing those genes between BPD inpatients (n = 111, 46% female) and psychiatric controls (n = 111, 54% female) at The Menninger Clinic in Houston, Texas. We then correlated personality measures, suicidal ideation intensity, and recovery from suicidal ideation with volumetrics. Gene targets of miR-124-3p were significantly co-expressed in the left Globus Pallidus (GP), which was smaller in BPD than in psychiatric controls. Smaller GP volume was negatively correlated with agreeableness and with recovery from suicidal ideation post-treatment. In BPD, GP volume may be reduced through miR-124-3p regulation and suppression of its target genes. Importantly, we identified that a reduction of the GP in BPD could serve as a potential biomarker for recovery from suicidal ideation.

Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder.

Introduction: Suicide is one of the leading causes of death across different age groups. The persistence of suicidal ideation and the progression of suicidal ideations to action could be related to impulsivity, the tendency to act on urges with low temporal latency, and little forethought. Quantifying impulsivity could thus help suicidality estimation and risk assessments in ideation-to-action suicidality frameworks. Methods: To model suicidality with impulsivity quantification, we obtained questionnaires, behavioral tests, heart rate variability (HRV), and resting state functional magnetic resonance imaging measurements from 34 participants with mood disorders. The participants were categorized into three suicidality groups based on their Mini-International Neuropsychiatric Interview: none, low, and moderate to severe. Results: Questionnaire and HRV-based impulsivity measures were significantly different between the suicidality groups with higher subscales of impulsivity associated with higher suicidality. A multimodal system to characterize impulsivity objectively resulted in a classification accuracy of 96.77% in the three-class suicidality group prediction task. Conclusions: This study elucidates the relative sensitivity of various impulsivity measures in differentiating participants with suicidality and demonstrates suicidality prediction with high accuracy using a multimodal objective impulsivity characterization in participants with mood disorders.

Pilot clinical trial of macimorelin to assess safety and efficacy in patients with cancer cachexia.

BACKGROUND: Cancer cachexia is associated with reduced body weight, appetite and quality of life (QOL) with no approved treatments. Growth hormone secretagogues like macimorelin have potential to mitigate these effects. METHODS: This pilot study assessed the safety and efficacy of macimorelin for 1 week. Efficacy was defined a priori as 1-week change in body weight (≥0.8 kg), plasma insulin-like growth factor (IGF)-1 (≥50 ng/mL) or QOL (≥15%). Secondary outcomes included food intake, appetite, functional performance, energy expenditure and safety laboratory parameters. Patients with cancer cachexia were randomized to 0.5 or 1.0 mg/kg macimorelin or placebo; outcomes were assessed non-parametrically. RESULTS: Participants receiving at least one of either macimorelin dose were combined (N = 10; 100% male; median age = 65.50 ± 2.12) and compared with placebo (N = 5; 80% male; median age = 68.00 ± 6.19). Efficacy criteria achieved: body weight (macimorelin N = 2; placebo N = 0; P = 0.92); IGF-1 (macimorelin N = 0; placebo N = 0); QOL by Anderson Symptom Assessment Scale (macimorelin N = 4; placebo N = 1; P = 1.00) or Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F; macimorelin N = 3; placebo N = 0; P = 0.50). No related serious or non-serious adverse events were reported. In macimorelin recipients, change in FACIT-F was directly associated with change in body weight (r = 0.92, P = 0.001), IGF-1 (r = 0.80, P = 0.01), and caloric intake (r = 0.83, P = 0.005), and inversely associated with change in energy expenditure (r = -0.67, P = 0.05). CONCLUSIONS: Daily oral macimorelin for 1 week was safe and numerically improved body weight and QOL in patients with cancer cachexia compared with placebo. Longer term administration should be evaluated for mitigation of cancer-induced reductions in body weight, appetite and QOL in larger studies.

Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group.

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE < 0.001; right: d = -0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.

Iron deficiency and internalizing symptom severity in unmedicated adolescents: a pilot study.

BACKGROUND: Iron plays a key role in a broad set of metabolic processes. Iron deficiency is the most common nutritional deficiency in the world, but its neuropsychiatric implications in adolescents have not been examined. METHODS: Twelve- to 17-year-old unmedicated females with major depressive or anxiety disorders or with no psychopathology underwent a comprehensive psychiatric assessment for this pilot study. A T1-weighted magnetic resonance imaging scan was obtained, segmented using Freesurfer. Serum ferritin concentration (sF) was measured. Correlational analyses examined the association between body iron stores, psychiatric symptom severity, and basal ganglia volumes, accounting for confounding variables. RESULTS: Forty females were enrolled, 73% having a major depressive and/or anxiety disorder, 35% with sF < 15 ng/mL, and 50% with sF < 20 ng/mL. Serum ferritin was inversely correlated with both anxiety and depressive symptom severity (r = -0.34, p < 0.04 and r = -0.30, p < 0.06, respectively). Participants with sF < 15 ng/mL exhibited more severe depressive and anxiety symptoms as did those with sF < 20 ng/mL. Moreover, after adjusting for age and total intracranial volume, sF was inversely associated with left caudate (Spearman's r = -0.46, p < 0.04), left putamen (r = -0.58, p < 0.005), and right putamen (r = -0.53, p < 0.01) volume. CONCLUSIONS: Brain iron may become depleted at a sF concentration higher than the established threshold to diagnose iron deficiency (i.e. 15 ng/mL), potentially disrupting brain maturation and contributing to the emergence of internalizing disorders in adolescents.

Reward Processing in Psychiatric Inpatients With Depression.

BACKGROUND: Previous neuroimaging studies have investigated reward-processing dysfunction in major depressive disorder and have led to the common finding that major depressive disorder is associated with reduced reward responses within the reward circuit. Yet it is unclear whether such reward-processing dysfunction is specifically associated with the severity of depressive symptoms in major depressive disorder or is associated with common comorbidities. METHODS: We investigated reward-processing differences using a classic juice-delivery functional magnetic resonance imaging experiment to compare psychiatric patients with severe depressive symptoms (DEPs) to both psychiatric control subjects (PCs) and healthy control subjects. In this study, the DEPs (n = 108) were matched to healthy control subjects (n = 62) for demographic characteristics and to the PCs (n = 108) for demographics and comorbid psychiatric diagnoses. An a priori region of interest, the left putamen, was selected using previous studies. An exploratory whole-brain analysis was performed to explore for nonhypothesized regions. RESULTS: Relative to the PCs and healthy control subjects, the DEP group showed smaller responses to reward stimulus in the left putamen. Whole-brain exploratory analysis revealed that DEPs had significantly lower responses to reward stimulus in the bilateral dorsal striatum (putamen and caudate), middle frontal gyrus, left precentral gyrus, and middle cingulate cortex than PCs. CONCLUSIONS: Our findings suggest that DEPs may have a lesser ability to modulate behavior as a function of reward, especially in those individuals who experience the most severe depressive symptoms. In both DEPs and PCs, the severity of depressive symptoms was related to reduced reward responses in the left putamen.

Turning data into better mental health: Past, present, and future.

In this mini-review, we discuss the fundamentals of using technology in mental health diagnosis and tracking. We highlight those principles using two clinical concepts: (1) cravings and relapse in the context of addictive disorders and (2) anhedonia in the context of depression. This manuscript is useful for both clinicians wanting to understand the scope of technology use in psychiatry and for computer scientists and engineers wishing to assess psychiatric frameworks useful for diagnosis and treatment. The increase in smartphone ownership and internet connectivity, as well as the accelerated development of wearable devices, have made the observation and analysis of human behavior patterns possible. This has, in turn, paved the way to understand mental health conditions better. These technologies have immense potential in facilitating the diagnosis and tracking of mental health conditions; they also allow the implementation of existing behavioral treatments in new contexts (e.g., remotely, online, and in rural/underserved areas), and the possibility to develop new treatments based on new understanding of behavior patterns. The path to understand how to best use technology in mental health includes the need to match interdisciplinary frameworks from engineering/computer sciences and psychiatry. Thus, we start our review by introducing bio-behavioral sensing, the types of information available, and what behavioral patterns they may reflect and be related to in psychiatric diagnostic frameworks. This information is linked to the use of functional imaging, highlighting how imaging modalities can be considered "ground truth" for mental health/psychiatric dimensions, given the heterogeneity of clinical presentations, and the difficulty of determining what symptom corresponds to what disease. We then discuss how mental health/psychiatric dimensions overlap, yet differ from, psychiatric diagnoses. Using two clinical examples, we highlight the potential agreement areas in assessment/management of anhedonia and cravings. These two dimensions were chosen because of their link to two very prevalent diseases worldwide: depression and addiction. Anhedonia is a core symptom of depression, which is one of the leading causes of disability worldwide. Cravings, the urge to use a substance or perform an action (e.g., shopping, internet), is the leading step before relapse. Lastly, through the manuscript, we discuss potential mental health dimensions.

Clotting factor genes are associated with preeclampsia in high-altitude pregnant women in the Peruvian Andes.

Preeclampsia is a multi-organ complication of pregnancy characterized by sudden hypertension and proteinuria that is among the leading causes of preterm delivery and maternal morbidity and mortality worldwide. The heterogeneity of preeclampsia poses a challenge for understanding its etiology and molecular basis. Intriguingly, risk for the condition increases in high-altitude regions such as the Peruvian Andes. To investigate the genetic basis of preeclampsia in a population living at high altitude, we characterized genome-wide variation in a cohort of preeclamptic and healthy Andean families (n = 883) from Puno, Peru, a city located above 3,800 meters of altitude. Our study collected genomic DNA and medical records from case-control trios and duos in local hospital settings. We generated genotype data for 439,314 SNPs, determined global ancestry patterns, and mapped associations between genetic variants and preeclampsia phenotypes. A transmission disequilibrium test (TDT) revealed variants near genes of biological importance for placental and blood vessel function. The top candidate region was found on chromosome 13 of the fetal genome and contains clotting factor genes PROZ, F7, and F10. These findings provide supporting evidence that common genetic variants within coagulation genes play an important role in preeclampsia. A selection scan revealed a potential adaptive signal around the ADAM12 locus on chromosome 10, implicated in pregnancy disorders. Our discovery of an association in a functional pathway relevant to pregnancy physiology in an understudied population of Native American origin demonstrates the increased power of family-based study design and underscores the importance of conducting genetic research in diverse populations.

A Novel Approach to Link Genetics and Human MRI Identifies AKAP7-Dependent Subicular/Prefrontal Functional Connectivity as Altered in Suicidality.

Background: Brain imaging and genetics are fields acquiring data at increasing speed, but more information does not always result in a better understanding of the underlying biology. We developed the ProcessGeneLists (PGL) approach to use genetics and mRNA gene expression data to generate regions of interest for imaging studies. Methods: We applied PGL to past suicide attempt (ATT): We averaged the mRNA expression levels of genes (n = 130) possibly associated with ATT (p ≤ 10-3 in a published genome-wide association study, GWAS) in each brain region studied in the Human Allen Brain Atlas (6 ex-vivo brains, 158 to 946 regions/brain have mRNA expression data) and compared that to the averaged mRNA expression levels of all other genes in each region in each brain in the atlas. Results: PGL revealed 8 regions where "attempt-related genes" were differentially expressed (Wilcoxon test with Bonferroni correction 8.88-11 =

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

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.

Effects of Smoking Status and State on Intrinsic Connectivity.

BACKGROUND: Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity. METHODS: Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution. RESULTS: Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent. CONCLUSIONS: These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.

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

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.

Smoking status links habenular volume to glycated hemoglobin: Findings from the Human Connectome Project-Young Adult.

BACKGROUND: The habenula-pancreas axis regulates the stimulatory effects of nicotine on blood glucose levels and may participate in the emergence of type 2 diabetes in human tobacco smokers. This secondary analysis of young adults from the Human Connectome Project (HCP-YA) evaluated whether smoking status links the relationship between habenular volume and glycated hemoglobin (HbA1c), a marker of long-term glycemic control. METHODS: Habenula segmentation was performed using a fully-automated myelin content-based approach in HCP-YA participants and the results were inspected visually (n = 693; aged 22-37 years). A linear regression analysis was used with habenular volume as the dependent variable, the smoking-by-HbA1c interaction as the independent variable of interest, and age, gender, race, ethnicity, education, income, employment status, body mass index, and total gray matter volume as covariates. RESULTS: Habenula volume and HbA1c were similar in smokers and nonsmokers. There was a significant interaction effect (F(1, 673)= 5.03, p = 0.025) indicating that habenular volume was related to HbA1c in a manner that depended on smoking status. Among participants who were smokers (n = 120), higher HbA1c was associated with apparently larger habenular volume (ß = 6.74, standard error=2.36, p = 0.005). No such association between habenular volume and HbA1c was noted among participants who were nonsmokers (n = 573). DISCUSSION: Blood glucose levels over an extended time period, reflected by HbA1c, were correlated with habenular volume in smokers, consistent with a relationship between the habenula and blood glucose homeostasis in smokers. Future studies are needed to evaluate how habenular function relates to glycemic control in smokers and nonsmokers.

Impact of the KCNQ2/3 Channel Opener Ezogabine on Reward Circuit Activity and Clinical Symptoms in Depression: Results From a Randomized Controlled Trial.

OBJECTIVE: Preclinical studies point to the KCNQ2/3 potassium channel as a novel target for the treatment of depression and anhedonia, a reduced ability to experience pleasure. The authors conducted the first randomized placebo-controlled trial testing the effect of the KCNQ2/3 positive modulator ezogabine on reward circuit activity and clinical outcomes in patients with depression. METHODS: Depressed individuals (N=45) with elevated levels of anhedonia were assigned to a 5-week treatment period with ezogabine (900 mg/day; N=21) or placebo (N=24). Participants underwent functional MRI during a reward flanker task at baseline and following treatment. Clinical measures of depression and anhedonia were collected at weekly visits. The primary endpoint was the change from baseline to week 5 in ventral striatum activation during reward anticipation. Secondary endpoints included depression and anhedonia severity as measured using the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Snaith-Hamilton Pleasure Scale (SHAPS), respectively. RESULTS: The study did not meet its primary neuroimaging endpoint. Participants in the ezogabine group showed a numerical increase in ventral striatum response to reward anticipation following treatment compared with participants in the placebo group from baseline to week 5. Compared with placebo, ezogabine was associated with a significantly larger improvement in MADRS and SHAPS scores and other clinical endpoints. Ezogabine was well tolerated, and no serious adverse events occurred. CONCLUSIONS: The study did not meet its primary neuroimaging endpoint, although the effect of treatment was significant on several secondary clinical endpoints. In aggregate, the findings may suggest that future studies of the KCNQ2/3 channel as a novel treatment target for depression and anhedonia are warranted.

Evidence of Altered Habenular Intrinsic Functional Connectivity in Pediatric ADHD.

Objective: The habenula is a small region in the epithalamus that contributes to the regulation of midbrain dopaminergic circuits implicated in attention-deficit hyperactivity disorder (ADHD). This investigation aims to evaluate the intrinsic functional connectivity (iFC) of the habenula in children with ADHD. Method: A total of 112 children (5-9 years; 75 ADHD, 37 healthy comparisons) completed anatomical and resting-state functional magnetic resonance imaging (MRI) scans. Habenula regions of interest (ROIs) were identified individually on normalized T1-weighted anatomical images. Seed-based iFC analyses and group comparisons were conducted for habenula ROIs, as well as thalamic ROIs to test the specificity of habenula findings. Results: Children with ADHD exhibited reduced habenula-putamen iFC compared with healthy comparisons. Group differences in thalamic iFC showed no overlap with habenular findings. Conclusion: These preliminary findings suggest that habenula-putamen iFC may be disrupted in children with ADHD. Further work is needed to confirm and elucidate the role of this circuit in ADHD pathophysiology.