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Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response.The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response.Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups.Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.

Background: Epilepsy is the most common neurological disease in the world, affecting 50 million people, with the majority living in low- and middle-income countries (LMICs). A major focus of epilepsy treatment in LMICs has been task-sharing the identification and care for epilepsy by community health workers (CHWs). The present study aimed to assess the knowledge, attitudes, and practices (KAPs) of CHWs towards epilepsy in Mozambique. Methods: One hundred and thirty-five CHWs completed a questionnaire that included socio-demographic characteristics and 44-items divided into six subscales pertaining to KAPs towards epilepsy (QKAP-EPI) across nine districts of Sofala, Mozambique. The internal consistency was examined to evaluate the reliability of the instrument (QKAP-EPI). The association between sociodemographic variables and QKAP-EPI subscales was examined using linear regression models. Results: The internal consistency was moderate for two subscales (causes of epilepsy, α = 0.65; medical treatment, α = 0.694), acceptable for cultural treatment (α = 0.797) and excellent for 2 subscales (safety and risks, α = 0.926; negative attitudes, α = 0.904). Overall, CHWs demonstrated accurate epilepsy knowledge (medical treatment: mean = 1.63, SD = 0.28; safety/risks: mean = 1.62, SD = 0.59). However, CHWs reported inaccurate epilepsy knowledge of the causes, negative attitudes, as well as culturally specific treatments for epilepsy, such as: “if a person with epilepsy burns when set on fire they cannot be treated”. Knowledge about how to manage epileptic seizures varied across the different emergency care practices, from the accurate belief that it is not advisable to place objects in the individual’s mouth during an epileptic seizure, to the wrong perception of the need to hold the person in seizures to control seizures. Heterogeneity in the level of epilepsy knowledge was observed among CHWs, when considering epilepsy according to the local names as treatable (“Dzumba”) and other forms as untreatable (“Nzwiti”). Conclusion: CHWs knowledge of medical treatment and epilepsy safety/risks were adequate. However, information on the causes of epilepsy, stigmatizing attitudes, cultural treatment, and some knowledge of epileptic seizure management were low. These areas of poor knowledge should be the focus of educating CHWs in increasing their ability to provide quality care for patients with epilepsy in Mozambique.

Preclinical studies have implicated kappa opioid receptors (KORs) in stress responses and depression-related behaviors, but evidence from human studies is limited. Here we present results of a secondary analysis of data acquired using positron emission tomography (PET) with the KOR radiotracer [11C]GR103545 in 10 unmedicated, currently depressed individuals with major depressive disorder (MDD; 32.6 ± 6.5 years, 5 women) and 13 healthy volunteers (34.8 ± 10 years, 6 women). Independent component analysis was performed to identify spatial patterns of coherent variance in KOR binding (tracer volume of distribution, VT) across all subjects. Expression of each component was compared between groups and relationships to symptoms were explored using the 17-item Hamilton Depression Rating Scale (HDRS). Three components of variation in KOR availability across ROIs were identified, spatially characterized by [11C]GR103545 VT in (1) bilateral frontal lobe; (2) occipital and parietal cortices, right hippocampus, and putamen; and (3) right anterior cingulate, right superior frontal gyrus and insula, coupled to negative loading in left middle cingulate. In MDD patients, component 3 was negatively associated with symptom severity on the HDRS (r = −0.85, p = 0.0021). There were no group-wise differences in expression of any component between patients and controls. These preliminary findings suggest that KOR signaling in cortical regions relevant to depression, particularly right anterior cingulate, could reflect MDD pathophysiology.

Serotonin transporter (5-HTT) binding deficits are reported in major depressive disorder (MDD). However, most studies have not considered serotonin system anatomy when parcellating brain regions of interest (ROIs). We now investigate 5-HTT binding in MDD in two novel ways: (1) use of a 5-HTT tract-based analysis examining binding along serotonergic axons; and (2) using the Copenhagen University Hospital Neurobiology Research Unit (NRU) 5-HT Atlas, based on brain-wide binding patterns of multiple serotonin receptor types. [11C]DASB 5-HTT PET scans were obtained in 59 unmedicated participants with MDD in a current depressive episode and 32 healthy volunteers (HVs). Binding potential (BPP) was quantified with empirical Bayesian estimation in graphical analysis (EBEGA). Within the [11C]DASB tract, MDD showed significantly lower BPP compared with HVs (p=0.02). The BPP diagnosis difference varied by tract location at a trend-level (p=0.08), with MDD binding deficit strongest most proximal to brainstem raphe nuclei. NRU 5-HT Atlas ROIs showed trend-level lower BPPin MDD relative to HVs (p=0.06) and BPP diagnosis difference that varied by region (p=0.001). BPP was lower in MDD in 4/10 regions (p-values

Two-thirds of health professionals facing the clinical demands of responding to the Covid-19 pandemic experience psychiatric symptoms, including post-traumatic stress, anxiety, substance use, depression, insomnia, and suicide.

Background Our lab has previously found that structural integrity in tracts from the raphe nucleus (RN) to the amygdala, measured by fractional anisotropy (FA), predicts remission to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder (MDD). This could potentially serve as a biomarker for remission that can guide clinical decision-making. To enhance repeatability and reproducibility, we replicated our study in a larger, more representative multi-site sample. Methods 64 direction DTI was collected in 144 medication-free patients with MDD from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) study. We performed probabilistic tractography between the RN and bilateral amygdala and hippocampus and calculated weighted FA in these tracts. Patients were treated with either sertraline or placebo, and their change in Hamilton Depression Rating Scale (HDRS) score reported. Pretreatment weighted FA was compared between remitters and nonremitters, and correlation between FA and percent change in HDRS score was assessed. Exploratory moderator and voxel analyses were also performed. Results Contrary to our hypotheses, FA was greater in nonremitters than in remitters in RN-left and right amygdala tracts (p = 0.02 and 0.01, respectively). Pretreatment FA between the raphe and left amygdala correlated with greater, not reduced, HDRS (r = 0.18, p = 0.04). This finding was found to be greater in the placebo group. Moderator and voxel analyses yielded no significant findings. Conclusions We found greater FA in nonremitters between the RN and amygdala than in remitters, and a correlation between FA and symptom worsening, particularly with placebo. These findings may help reveal more about the nature of MDD, as well as guide research methods involving placebo response.

Major depressive disorder (MDD) is a serious, heterogeneous disorder accompanied by brain-related changes, many of which are still to be discovered or refined. Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood flow (CBF; perfusion) to understand brain function and detect differences among groups. CBF differences have been detected in MDD, and may reveal biosignatures of disease-state. The current work aimed to discover and replicate differences in CBF between MDD participants and healthy controls (HC) as part of the EMBARC study. Participants underwent neuroimaging at baseline, prior to starting study medication, to investigate biosignatures in MDD. Relative CBF (rCBF) was calculated and compared between 106 MDD and 36 HC EMBARC participants (whole-brain Discovery); and 58 MDD EMBARC participants and 58 HC from the DLBS study (region-of-interest Replication). Both analyses revealed reduced rCBF in the right parahippocampus, thalamus, fusiform and middle temporal gyri, as well as the left and right insula, for those with MDD relative to HC. Both samples also revealed increased rCBF in MDD relative to HC in both the left and right inferior parietal lobule, including the supramarginal and angular gyri. Cingulate and prefrontal regions did not fully replicate. Lastly, significant associations were detected between rCBF in replicated regions and clinical measures of MDD chronicity. These results (1) provide reliable evidence for ASL in detecting differences in perfusion for multiple brain regions thought to be important in MDD, and (2) highlight the potential role of using perfusion as a biosignature of MDD.

Objective: To estimate the prevalence of major depressive episode (MDE) in patients with presumptive pulmonary tuberculosis (pre-PTB, defined by cough lasting ≥ 3 weeks) and compare it between patients with pulmonary tuberculosis (PTB) and without PTB. Methods: Patients with pre-PTB (n=260) were screened for depression using the Patient Health Questionnaire (PHQ-9). Those individuals with scores ≥ 10 were subsequently assessed with the depression module of the Mini International Neuropsychiatric Interview (MINI-Plus) to confirm diagnosis. Associations of categorical variables with PTB and MDE were calculated using the chi-square test and OR. Results: PTB was confirmed in 98 patients (37.7%). A high proportion of both groups (active PTB and no PTB) screened positive for depression (60.2 vs. 62.1%, respectively). Among 159 patients who screened positive for depression, a subset of 97 (61.0%) were further evaluated with the MINI-Plus; current MDE was confirmed in 54.6% (53/97). On univariate and multivariate analysis, female sex was the only factor associated with the diagnosis of current MDE (p = 0.04). Conclusion: The prevalence of MDE was high among individuals with prolonged respiratory symptoms, independent of PTB diagnosis. This is consistent with other studies of depression in primary care in Brazil.

Medications to treat major depressive disorder (MDD) are not equally effective across patients. Given that neural response to rewards is altered in MDD and given that reward-related circuitry is modulated by dopamine and serotonin, we examined, for the first time, whether reward-related neural activity moderated response to sertraline, an antidepressant medication that targets these neurotransmitters. 222 unmedicated adults with MDD randomized to receive sertraline (n=110) or placebo (n=112) in the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study completed demographic and clinical assessments, and pre-treatment functional magnetic resonance imaging while performing a reward task. We tested whether an index of reward system function in the ventral striatum (VS), a key reward circuitry region, moderated differential response to sertraline versus placebo, assessed with the Hamilton Rating Scale for Depression over 8 weeks. We observed a significant moderation effect of the reward index, reflecting the temporal dynamics of VS activity, on Week-8 depression levels (Fs≥9.67,ps≤0.002). Specifically, VS responses that were abnormal with respect to predictions from reinforcement learning theory were associated with lower Week-8 depression symptoms in the sertraline versus placebo arms. Thus, a more abnormal pattern of pre-treatment VS dynamic response to reward expectancy (expected outcome value) and prediction error (difference between expected and actual outcome), likely reflecting serotonergic and dopaminergic deficits, was associated with better response to sertraline than placebo. Pre-treatment measures of reward-related VS activity may serve as objective neural markers to advance efforts to personalize interventions by guiding individual-level choice of antidepressant treatment. Trial Registration: NCT01407094; http://clinicaltrials.gov/show/NCT01407094

Background Baseline rostral anterior cingulate cortex (rACC) activity is a well-replicated nonspecific predictor of depression improvement. The rACC is a key hub of the default mode network, which prior studies indicate is hyperactive in major depressive disorder. Because default mode network downregulation is reliant on input from the salience network and frontoparietal network, an important question is whether rACC connectivity with these systems contributes to depression improvement. Methods Our study evaluated this hypothesis in outpatients (N = 238; 151 female) enrolled in the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) 8-week randomized clinical trial of sertraline versus placebo for major depressive disorder. Depression severity was measured using the Hamilton Rating Scale for Depression, and electroencephalography was recorded at baseline and week 1. Exact low-resolution electromagnetic tomography was used to compute activity from the rACC, and key regions within the default mode network (posterior cingulate cortex), frontoparietal network (left dorsolateral prefrontal cortex), and salience network (right anterior insula [rAI]). Connectivity in the theta band (4.5–7 Hz) and beta band (12.5–21 Hz) was computed using lagged phase synchronization. Results Stronger baseline theta-band rACC–rAI (salience network hub) connectivity predicted greater depression improvement across 8 weeks of treatment for both treatment arms (B = −0.57, 95% confidence interval = −1.07, −0.08, p = .03). Early increases in theta-band rACC–rAI connectivity predicted greater likelihood of achieving remission at week 8 (odds ratio = 2.90, p = .03). Conclusions Among patients undergoing treatment, theta-band rACC–rAI connectivity is a prognostic, albeit treatment-nonspecific, indicator of depression improvement, and early connectivity changes may predict clinically meaningful outcomes.

Background Abnormalities in the hypothalamic-pituitary-adrenal axis, serotonergic system, and stress response have been linked to the pathogenesis of major depressive disorder. State-dependent hyper-reactivity of the hypothalamic-pituitary-adrenal axis is seen in major depressive disorder, and higher binding to the serotonin 1A receptor is observed as a trait in both currently depressed and remitted untreated major depressive disorder. Here, we sought to examine whether a relationship exists between cortisol secretion in response to a stressor and serotonin 1A receptor binding throughout the brain, both in healthy controls and participants with major depressive disorder. Methods Research participants included 42 medication-free, depressed subjects and 31 healthy volunteers. Participants were exposed to either an acute, physical stressor (radial artery catheter insertion) or a psychological stressor (Trier Social Stress Test). Levels of serotonin 1A receptor binding on positron emission tomography with [11C]WAY-100635 were also obtained from all participants. The relationship between [11C]WAY-100635 binding and cortisol was examined using mixed linear effects models with group (major depressive disorder vs control), cortisol, brain region, and their interactions as fixed effects and subject as a random effect. Results We found a positive correlation between post-stress cortisol measures and serotonin 1A receptor ligand binding levels across multiple cortical and subcortical regions, independent of diagnosis and with both types of stress. The relationship between [11C]WAY-100635 binding and cortisol was homogenous across all a priori brain regions. In contrast, resting cortisol levels were negatively correlated with serotonin 1A receptor ligand binding levels independently of diagnosis, except in the RN. There was no significant difference in cortisol between major depressive disorder participants and healthy volunteers with either stressor. Similarly, there was no correlation between cortisol and depression severity in either stressor group. Conclusions This study suggests that there may be a common underlying mechanism that links abnormalities in the serotonin system and hypothalamic-pituitary-adrenal axis hyper-reactivity to stress. Future studies need to determine how hypothalamic-pituitary-adrenal axis dysfunction affects mood to increase the risk of suicide in major depression.

BackgroundAlthough there are extensive data on clinical psychopathology in youth with suicidal ideation, data are lacking regarding their neurocognitive function.AimsTo characterise the cognitive profile of youth with suicidal ideation in a community sample and evaluate gender differences and pubertal status effects.MethodParticipants (N = 6151, age 11–21 years, 54.9% females) from the Philadelphia Neurodevelopmental Cohort, a non-help-seeking community sample, underwent detailed clinical evaluation. Cognitive phenotyping included executive functioning, episodic memory, complex reasoning and social cognitive functioning. We compared participants with suicidal ideation (N = 672) and without suicidal ideation (N = 5479). Regression models were employed to evaluate differences in cognitive performance and functional level, with gender and pubertal status as independent variables. Models controlled for lifetime depression or general psychopathology, and for covariates including age and socioeconomic status.ResultsYouth with suicidal ideation showed greater psychopathology, poorer level of function but better overall neurocognitive performance. Greater functional impairment was observed in females with suicidal ideation (suicidal ideation × gender interaction, t = 3.091, P = 0.002). Greater neurocognition was associated with suicidal ideation post-puberty (suicidal ideation × puberty interaction, t = 3.057, P = 0.002). Exploratory analyses of specific neurocognitive domains showed that suicidal ideation-associated cognitive superiority was more prominent in post-pubertal males compared with females (Cohen's d = 0.32 and d = 0.11, respectively) across all cognitive domains.ConclusionsSuicidal ideation was associated with poorer functioning yet better cognitive performance, especially in post-pubertal males, as measured by a comprehensive cognitive battery. Findings point to gender and pubertal-status specificity in the relationship between suicidal ideation, cognition and function in youth.Declaration of interestR.B. serves on the scientific board and reports stock ownership in ‘Taliaz Health’, with no conflict of interest relevant to this work. M.A.O. receives royalties for the commercial use of the Columbia-Suicide Severity Rating Scale from the Research Foundation for Mental Hygiene. Her family owns stock in Bristol-Myers Squibb. All other authors declare no potential conflict of interest.

Background Identifying brain activity patterns that are associated with suicidal ideation (SI) may help to elucidate its pathogenesis and etiology. Suicide poses a significant public health problem, and SI is a risk factor for suicidal behavior. Methods Forty-one unmedicated adult participants in a major depressive episode (MDE), 26 with SI on the Beck Scale for Suicidal Ideation and 15 without SI, underwent resting-state functional magnetic resonance imaging scanning. Twenty-one healthy volunteers (HVs) were scanned for secondary analyses. Whole brain analysis of both amplitude of low-frequency fluctuations (ALFFs) and fractional ALFF was performed in MDE subjects to identify regions where activity was associated with SI. Results Subjects with SI had greater ALFF than those without SI in two clusters: one in the right hippocampus and one in the thalamus and caudate, bilaterally. Multi-voxel pattern analysis distinguished between those with and without SI. Post hoc analysis of the mean ALFF in the hippocampus cluster found it to be associated with a delayed recall on the Buschke memory task. Mean ALFF from the significant clusters was not associated with depression severity and did not differ between MDE and HV groups. Discussion These results indicate that SI is associated with altered resting-state brain activity. The pattern of elevated activity in the hippocampus may be related to how memories are processed.

BackgroundCognitive behavioral therapy (CBT) is an effective treatment for many patients suffering from major depressive disorder (MDD), but predictors of treatment outcome are lacking, and little is known about its neural mechanisms. We recently identified longitudinal changes in neural correlates of conscious emotion regulation that scaled with clinical responses to CBT for MDD, using a negative autobiographical memory-based task.MethodsWe now examine the neural correlates of emotional reactivity and emotion regulation during viewing of emotionally salient images as predictors of treatment outcome with CBT for MDD, and the relationship between longitudinal change in functional magnetic resonance imaging (fMRI) responses and clinical outcomes. Thirty-two participants with current MDD underwent baseline MRI scanning followed by 14 sessions of CBT. The fMRI task measured emotional reactivity and emotion regulation on separate trials using standardized images from the International Affective Pictures System. Twenty-one participants completed post-treatment scanning. Last observation carried forward was used to estimate clinical outcome for non-completers.ResultsPre-treatment emotional reactivity Blood Oxygen Level-Dependent (BOLD) signal within hippocampus including CA1 predicted worse treatment outcome. In contrast, better treatment outcome was associated with increased down-regulation of BOLD activity during emotion regulation from time 1 to time 2 in precuneus, occipital cortex, and middle frontal gyrus.ConclusionsCBT may modulate the neural circuitry of emotion regulation. The neural correlates of emotional reactivity may be more strongly predictive of CBT outcome. The finding that treatment outcome was predicted by BOLD signal in CA1 may suggest overgeneralized memory as a negative prognostic factor in CBT outcome.

Background Findings regarding brain circuitry abnormalities in suicide attempters (SAs) converge across bipolar disorder (BD) and major depressive disorder (MDD), the most common disorders observed in suicides. These abnormalities appear to be present during adolescence/young adulthood when suicide rates increase steeply, and suicide is a leading cause of death in this age group. Identification of brain circuitry common to adolescent/young adult SAs with BD and MDD is important for generating widely effective early prevention strategies. We examined brain circuitry in SAs in adolescents/young adults across these two disorders. Methods Eighty-three participants (ages 14–25 years), 46 with BD (21 SAs) and 37 with MDD (19 SAs), underwent structural and diffusion-weighted magnetic resonance scanning. Whole-brain analyses compared gray matter (GM) volume and white matter (WM) fractional anisotropy (FA) between SAs and non-suicide attempters (NSAs) across and within BD and MDD (p Results Across and within BD and MDD, SAs showed differences compared to NSAs in ventral prefrontal cortex (PFC) GM volume and fronto-limbic (including uncinate fasciculus (UF)) WM FA. Exploratory analyses showed additional within-disorder differences for BD SAs in dorsolateral PFC (dlPFC) and hippocampus GM volume and UF FA, and for MDD SAs dorsomedial and dlPFC GM and dorsal frontal WM. However, there was no significant interaction between suicide attempt status and diagnosis. Limitations Modest sample size. Conclusions Common fronto-limbic gray and white matter alterations in adolescent/young adult SAs are potential targets for suicide prevention strategies across mood disorders. Preliminary findings of disorder-specific regional findings could suggest diagnostic-specific optimal targets may exist.

BACKGROUND: Mood disorders are major risk factors for suicidal behavior. While cross-sectional studies implicate frontal systems, data to aid prediction of suicide-related behavior in mood disorders are limited. Longitudinal research on neuroanatomical mechanisms underlying suicide risk may assist in developing targeted interventions. Therefore, we conducted a preliminary study investigating baseline gray and white matter structure and longitudinal structural changes associated with future suicide attempts. METHODS: High-resolution structural magnetic resonance imaging, diffusion tensor imaging, and suicide-related behavioral assessment data for 46 adolescents and young adults with mood disorders [baseline age(mean)=18 years; 61% female] were collected at baseline and at follow-up (interval(mean)=3 years). Differences in baseline and longitudinal changes in gray matter volume and white matter fractional anisotropy in frontal systems that distinguished the participants who made future attempts from those who did not were investigated. RESULTS: Seventeen (37%) of participants attempted suicide within the follow-up period. Future attempters (those attempting suicide between their baseline and follow-up assessment), compared to those who did not, showed lower baseline ventral and rostral prefrontal gray matter volume and dorsomedial frontal, anterior limb of the internal capsule, and dorsal cingulum fractional anisotropy, as well as greater decreases over time in ventral and dorsal frontal fractional anisotropy (p

Background/aims: While substantial prior research has evaluated the psychometric properties of the 12-item Concise Health Risk Tracking-Self Report (CHRT-SR12), a measure of suicide propensity and suicidal thoughts, no prior research has investigated its factor structure, sensitivity to change over time, and other psychometric properties in a placebo-controlled trial of antidepressant medication, nor determined whether symptoms change throughout treatment. Methods: Participants in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study ( n=278) provided data to evaluate the factor structure and sensitivity to change over time of the CHRT-SR12 through eight weeks of a clinical trial in which participants received either placebo or antidepressant medication (sertraline). Results/Outcomes: Factor analysis confirmed two factors: propensity (comprised of first-order factors including pessimism, helplessness, social support, and despair) and suicidal thoughts. Internal consistency (α’s ranged from 0.69–0.92) and external validity were both acceptable, with the total score and propensity factor scores significantly correlated with total scores and single-item suicidal-thoughts scores on the self-report Quick Inventory of Depressive Symptoms and the clinician-rated 17-item Hamilton Rating Scale for Depression. Through analyzing CHRT-SR12 changes over eight treatment weeks, the total score and both the factors decreased regardless of baseline suicidal thoughts. Change in clinician-rated suicidal thoughts was reflected by change in both the total score and propensity factor score. Conclusions/interpretation: These results confirm the reliability, validity, and applicability of the CHRT-SR12 to a placebo-controlled clinical trial of depressed outpatients receiving antidepressant medication.

Memory deficits are reported in major depressive disorder (MDD). Prefrontal cortical and mesiotemporal cortical (MTC)/subcortical regions are involved in the Buschke Selective Reminding Task (SRT), a verbal list-learning task. To determine whether depression-related changes in resting brain metabolism explain (in part) the deficits in SRT performance found in MDD, statistical correlation maps were calculated between SRT total recall score (TR) and relative regional cerebral metabolic rate for glucose (rCMRglu), measured by [18F]-flourodeoxyglucose (FDG) positron emission tomography (PET), in unmedicated, depressed MDD patients (N = 29). Subsequently, to explore hypothesized loss of top-down control in MDD, we compared the correlations between rCMRglu of SRT-relevant regions of the dorsolateral prefrontal cortex (dlPFC) and amygdala in a larger cohort of MDD (N = 60; 29 inclusive) versus healthy controls (HC) (N = 43). SRT performance of patients is on average 0.5 standard deviation below published normative mean. TR and rCMRglu positively correlate in bilateral dorsomedial PFC, dlPFC, dorsal anterior cingulate; negatively correlate in bilateral MTC/subcortical regions, and cerebellum. rCMRglu in dlPFC correlates negatively with that in amygdala in HC but not in MDD. Depression-related changes present in FDG-PET measured resting brain activity may be in part responsible for memory deficit found in MDD.

Globally, suicide is the second leading cause of death for youth ages 10-24 years, and more than 75% of all deaths by suicide occur in low- and middle-income countries (LMIC).

Background Neurocognitive deficits are common in depression, but most prior studies have not found strong associations between standard measures of symptom severity and the extent of these neurocognitive deficits. Diagnostic heterogeneity, or the lack of specific questions about neurocognition in these measures, may be undermining these associations. Method Neuropsychological performance was assessed via 10 tasks in a sample of 262 unmedicated patients with Major Depressive Disorder (MDD) and compared to that in healthy volunteers (n = 140), then correlated with (1) standard measures of depression severity including the Hamilton Depression Rating Scale and Beck Depression Inventory, (2) previously established, factor-analytically derived symptom factors that characterize the heterogeneity of these scales, and (3) a separate measure of cognitive complaint (Cognitive Failures Questionnaire) that was included to address the absence of specific questions about cognition in standard rating scales. Results Neurocognitive performance in these unmedicated MDD patients was not significantly associated with either total scores on the depression severity measures, any of their derived symptom factors, or the degree of subjective cognitive complaint – which itself was most strongly associated with mood disturbance. Limitations Depressed patients with the most prominent neurovegetative symptoms may be underrepresented in this sample. Conclusions Neurocognitive deficits were only weakly associated with standard depression symptom ratings, and not captured by self-report ratings of cognitive complaint. Neurocognitive deficits appear to be a separate symptom dimension that cannot be inferred from overall depression severity and require their own assessment, given that they have prognostic value for functional outcomes, suicide risk, and differential therapeutics.

Growing evidence suggests that the glutamatergic modulator ketamine has rapid antidepressant effects in treatment-resistant depressed subjects. The anticholinergic agent scopolamine has also shown promise as a rapid-acting antidepressant. This study applied genome-wide markers to investigate the role of genetic variants in predicting acute antidepressant response to both agents. The ketamine-treated sample included 157 unrelated European subjects with major depressive disorder (MDD) or bipolar disorder (BD). The scopolamine-treated sample comprised 37 unrelated European subjects diagnosed with either MDD or BD who had a current Major Depressive Episode (MDE), and had failed at least two adequate treatment trials for depression. Change in Montgomery–Asberg Depression Rating Scale (MADRS) or the 17-item Hamilton Depression Rating Scale (HAM-D) scale scores at day 1 (24 h post-treatment) was considered the primary outcome. Here, we conduct pilot genome-wide association study (GWAS) analyses to identify potential markers of ketamine response and dissociative side effects. Polygenic risk score analysis of SNPs ranked by the strength of their association with ketamine response was then calculated in order to assess whether common genetic markers from the ketamine study could predict response to scopolamine. Findings require replication in larger samples in light of low power of analyses of these small samples. Neverthless, these data provide a promising illustration of our future potential to identify genetic variants underlying rapid treatment response in mood disorders and may ultimately guide individual patient treatment selection in the future.

The current study examined the contribution of baseline neuropsychological functioning to the prediction of antidepressant outcome with cognitive behavioral therapy (CBT) for Major Depressive Disorder (MDD). We hypothesized that depressed participants who were more neurocognitively intact and had less rigid, negative thinking would respond better to CBT. Thirty-one MDD patients completed a comprehensive neuropsychological battery before initiation of CBT. A subgroup also completed a probabilistic reversal learning task. Depression severity was assessed with the Beck Depression Inventory (BDI); rigid, negative thinking was assessed with the Dysfunctional Attitudes Scale (DAS) and the Automatic Thoughts Questionnaire (ATQ) throughout treatment. Remitters were compared to non-remitters. Paradoxically, eventual remitters performed generally worse across the neuropsychological battery considered as a whole. Univariate testing showed a significant difference on only a single measure, the Continuous Performance Test d', when corrected for multiple comparisons. Baseline rigid, negative thinking did not predict treatment outcome. Results suggest that the structure of CBT may particularly benefit individuals with mild depression-related neurocognitive difficulties during a depressive episode. Further research is needed to examine these patient characteristics and their potential contribution to the mechanisms of CBT efficacy.

BackgroundPatients with bipolar disorder have a high lifetime risk of suicide. Predicting, preventing and managing suicidal behavior are major goals in clinical practice. Changes in suicidal thoughts and behavior are common in the course of treatment of bipolar disorder.MethodsUsing a dataset from a randomized clinical trial of bipolar disorder treatment (N=98), we tested predictors of future suicidal behavior identified through a review of literature and applied marginal variable selection and machine learning methods. The performance of the models was assessed using the optimism-adjusted C statistic.ResultsNumber of prior hospitalizations, number of prior suicide attempts, current employment status and Hamilton Depression Scale were identified as predictors and a simple logistic regression model was constructed. This model was compared with a model incorporating interactions with treatment group assignment, and more complex variable selection methods (LASSO and Survival Trees). The best performing models had average optimism-adjusted C-statistics of 0.67 (main effects only) and 0.69 (Survival Trees). Incorporating medication group did not improve prediction performance of the models.ConclusionsThese results suggest that models with a few predictors may yield a clinically meaningful way to stratify risk of emerging suicide events in patients who are undergoing pharmacologic treatment for bipolar disorder.Significance StatementThis study aims to find out whether suicide events that occur during the pharmacological treatment of bipolar disorder, a severe psychiatric disorder that is highly associated with suicide behavior, can be predicted. Using existing methods, we developed and compared several predictive models. We showed that these models performed similarly to predictive models of other outcomes, such as treatment efficacy, in unipolar and bipolar depression. This suggests that suicide events during bipolar disorder may be a feasible target for individualized interventions in the future.

Despite substantial suicide prevention efforts, US suicide rates continue to climb, currently reaching about 14 per 100,000 individuals. Suicidal behavior has been linked to neurobiological, neurocognitive and behavioral factors; however, integrative, multi-modal studies are rare. Furthermore, prospective studies, crucial to understanding future risk factors, have focused on a single predictor and a single outcome, implying that suicidal behavior is homogeneous. But recent research shows suicidal behavior is complex and heterogeneous, with the possible existence of subtypes. The present report describes a project testing a model that posits two putative subtypes, using a prospective, multi-model design. The subtypes differ in regard to the patterns of suicidal ideation and underlying mechanisms. One hundred subjects diagnosed with a Major Depressive episode, half of whom have attempted suicide in the past, are enrolled and followed for two years, notably the highest risk period for suicidal behavior. Baseline assessments include a clinical assessment, neurocognitive and behavioral tasks, Ecological Momentary Assessments (EMA), PET imaging, and a cognitive emotion regulation task in the MRI scanner. The follow-up assessment includes a clinical assessment and EMA. The study findings have the potential to pave the way for a clearer understanding of suicidal ideation and behaviors and to improve our ability to treat those at risk for suicide by developing tailored approaches that will allow for more accurate pharmacological and psychosocial interventions.

The association of aggression and impulsivity with suicidal behavior (SB) in depression may vary across countries. This study aimed (i) to compare aggression and impulsivity levels, measured with the Brown-Goodwin Scale (BGS) and the Barratt Impulsivity Scale (BIS), respectively, between New York City (NYC) (US), Madrid (Spain) and Florence (Italy) (ANOVA); and (ii) to investigate between-site differences in the association of aggression and impulsivity with previous SB (binary logistic regression). Aggression scores were higher in NYC, followed by Florence and Madrid. Impulsivity levels were higher in Florence than in Madrid or NYC. Aggression and impulsivity scores were higher in suicide attempters than in non-attempters in NYC and in Madrid. SB was associated with aggression in NYC (OR 1.12, 95% CI 1.07–1.16; p < 0.001) and in Florence (OR 1.11, 95% CI 1.01–1.22; p = 0.032). Impulsivity was linked with SB in NYC (OR 1.01, 95% CI 1.00–1.02; p < 0.001) and in Madrid (OR 1.03, 95% CI 1.02–1.05; p < 0.001). The higher suicide rates in NYC, compared to Madrid or Florence, may be, in part, explained by these cross-cultural differences in the contribution of aggression-impulsivity to SB, which should be considered by future research on SB prevention.

International audience; Background: It remains unclear whether the dopaminergic and noradrenergic systems may be implied in suicide attempt risk. In addition, although the serotonergic system has been extensively studied, no formal meta-analysis has been performed to examine its association with suicide attempt.Methods: Using PRISMA methodology, we performed a systematic literature review and random-effects meta-analyses of the differences in cerebrospinal fluid (CSF) levels of 5-HIAA, HVA and MHPG between suicide attempters and individuals who never attempted suicide.Results: We identified 30 studies including 937 suicide attempters and 1128 non-attempters; 29 of them measured CSF levels of 5-HIAA, 22 measured CSF levels of HVA and 14 measured CSF levels of MHPG. CSF levels of 5-HIAA and HVA were significantly lower in suicide attempters than in non-attempters [SMD = -0.43 (95% CI: -0.71 to -0.15; p < 0.01) and SMD = -0.45 (95% CI: -0.72 to -0.19; p < 0.01), respectively]. We did not find a significant association between CSF MHPG levels and suicide attempt.Limitations: Our analyses relied on a limited number of studies of good quality and most studies included small sample sizes.Conclusion: Both serotonin and dopamine systems may play a role in suicide attempt risk. Our findings suggest that a silo approach to biomarkers should be phased out in favor of the study of multiple systems in parallel and in the same populations to progress in the identification of the biological components independently associated with suicide risk, with the goal of identifying new treatment targets and improving suicide risk prediction.

To understand suicidal behaviour and how to prevent it we must appreciate its neurobiological substrates. Neuroimaging provides an in vivo structural, functional, and molecular snapshot of the suicidal brain. Over the past decade, the use of neuroimaging techniques in studying suicidal behaviour has gained momentum, with a notable expansion in structural approaches as well as molecular and functional techniques. Findings from these studies point towards structural and functional changes in the fronto-temporo-limbic circuitry of suicide attempters that affect areas associated with decision-making, cognitive control, and emotion processing. Although these results show promise, direct comparison between studies is often challenging due to methodological inconsistencies between studies. A focus on more uniform, goal-directed methodology with a prospective component can aid future comparisons, and further our understanding of the neural underpinnings of suicidal behaviour.

PURPOSE We developed and implemented a new model of collaborative care that includes a triage and referral management system. We present initial implementation metrics using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework. METHODS Primary care clinicians in 8 practices referred patients with any unmet mental health needs to the Penn Integrated Care program. Assessments were conducted using validated measures. Patients were primarily triaged to collaborative care (26%) or specialty mental health care with active referral management (70%). We conducted 50 qualitative interviews to understand the implementation process and inform program refinement. Our primary outcomes were reach and implementation metrics, including referral and encounter rates derived from the electronic health record. RESULTS In 12 months, 6,124 unique patients were referred. Assessed patients reported symptoms consistent with a range of conditions from mild to moderate depression and anxiety to serious mental illnesses including psychosis and acute suicidal ideation. Among patients enrolled in collaborative care, treatment entailed a mean of 7.2 (SD 5.1) encounters over 78.1 (SD 51.3) days. Remission of symptoms was achieved by 32.6% of patients with depression and 39.5% of patients with anxiety. Stakeholders viewed the program favorably and had concrete suggestions to ensure sustainability. CONCLUSIONS The Penn Integrated Care program demonstrated broad reach. Implementation was consistent with collaborative care as delivered in seminal studies of the model. Our results provide insight into a model for launching and implementing collaborative care to meet the needs of a diverse group of patients with the full range of mental health conditions seen in primary care.

Objective This study explored perspectives of researchers working with the National Institute of Mental Health (NIMH) Scale-Up Hubs, consisting of research partnerships for scaling up mental health interventions in low- and middle-income countries (LMICs), to: 1) identify common barriers to conducting impactful research on the implementation of evidence-based mental health services; and 2) provide recommendations to overcome these implementation challenges. Methods A sequential qualitative approach was employed. First, an open-ended survey was distributed to the 10 Scale-Up Hubs and NIMH program staff asking informants to identify challenges in conducting mental health implementation research in LMICs. Second, survey findings guided an in-person workshop to generate implementation recommendations to inform the field. Results In total, 46 respondents completed surveys, and 101 researchers attended the workshop. The workshop produced implementation recommendations for low-resource settings: 1) identifying impact of research on policy and practice; 2) sustaining careers of early researchers in global mental health; 3) engaging policymakers and donors to value mental health research; 4) supporting the workforce for delivering evidence-based treatments for mental disorders; and 5) promoting sustainability of programs. Conclusions These findings can strengthen collaboration between researchers and key stakeholders, and highlight important targets for improving mental health implementation research in LMICs.

Efforts in research, prevention, and treatment of suicidal behavior have produced mixed results. One of the main barriers to combating suicidal behavior lies in the very conceptualization of suicide, a phenomenon that is at once sociological, psychiatric, and even philosophical, and one that has not always been included in the field of health care. There are also many barriers at the social level, ranging from stigma against people with suicidal behavior to stigma towards psychiatric care, as well as the controversial role of the media. The media plays an important role in society and depending on its attitude it can be either beneficial or harmful in our fight against suicidal behavior. Differences between countries - in the provision of resources, in the way of understanding the phenomenon or in the manner of providing official figures - pose an additional challenge to suicide prevention on a global level. In the field of research, predicting suicidal behavior by identifying effective risk markers is severely hampered by the low occurrence of suicide in the population, which limits the statistical power of studies. The authors recommend combining various risk factors to build predictive models. This, in addition to employing increasingly precise machine learning techniques, is a step in the right direction, although there is still a long way to go before the expected results can be obtained. Finally, adequate training of health professionals, both specialized and non-specialized, as well as gatekeeper training, is crucial for implementing suicide prevention strategies in the population.

Background Smartphone monitoring could contribute to the elucidation of the correlates of suicidal thoughts and behaviors (STB). In this study, we employ smartphone monitoring and machine learning techniques to explore the association of wish to die (passive suicidal ideation) with disturbed sleep, altered appetite and negative feelings. Methods This is a prospective cohort study carried out among adult psychiatric outpatients with a history of STB. A daily questionnaire was administered through the MEmind smartphone application. Participants were followed-up for a median of 89.8 days, resulting in 9,878 person-days. Data analysis employed a machine learning technique called Indian Buffet Process. Results 165 patients were recruited, 139 had the MEmind mobile application installed on their smartphone, and 110 answered questions regularly enough to be included in the final analysis. We found that the combination of wish to die and sleep problems was one of the most relevant latent features found across the sample, showing that these variables tend to be present during the same time frame (96 hours). Conclusions Disturbed sleep emerges as a potential clinical marker for passive suicidal ideation. Our findings stress the importance of evaluating sleep as part of the screening for suicidal behavior. Compared to previous smartphone monitoring studies on suicidal behavior, this study includes a long follow-up period and a large sample.

Environment (E) is pivotal in explaining variability in brain and behavior development, including suicidal ideation (SI) and behavior. It is therefore critical to systematically study relationships among environmental exposures (i.e., exposome) and suicidal phenotypes. Here, we evaluated the role of individual-level adversity and neighborhood environment and their interaction (E x E) in association with youth SI. Sample included youth (N = 7,054, ages 11–21) from the Philadelphia Neurodevelopmental Cohort, which investigated clinical phenotypes in a diverse US community population. We examined cross-sectional associations of environmental exposures with lifetime history of SI (n = 671), focusing on interactions between individual-level exposures to assaultive trauma (n = 917) and neighborhood-level socioeconomic status (SES) quantified using geocoded Census data. Models included potential confounds and overall psychopathology. Results showed that assaultive trauma was strongly associated with SI (OR = 3.3, 95%CI 2.7–4, p, Graphical abstract Image 1, Highlights • Environment (E) is key in shaping development of suicidal ideation (SI). • We integrated individual-level trauma exposure and neighborhood-level data on socioeconomic status (SES) in N=7,054 youths. • Trauma was robustly associated with youth SI in our cohort, while SES had no association with SI. • Only in youth with history of assaultive trauma, low SES was associated with lower SI rates (trauma by SES interaction). • Results suggest a stress inoculation effect that was shown in animal models, but has not been shown in human suicide research.

Background: Epilepsy is the most common neurological disease in the world, affecting 50 million people, with the majority living in low- and middle-income countries (LMICs). A major focus of epilepsy treatment in LMICs has focused on task-sharing identification and epilepsy care by community health workers (CHWs). The present study aimed to assess the KAPs of CHWs towards epilepsy in Sofala province, Mozambique. Methods: One hundred and thirty five CHWs completed a questionnaire that included socio-demographic characteristics and 44-items divided in six subscales pertaining to KAPs towards epilepsy (QKAP-EPI) in nine districts of Sofala Province, Mozambique. The internal consistency and factor structure were examined to evaluate the reliability and construct validity of the QKAP-EPI, respectively. To examine correlates of KAPs toward epilepsy we evaluated the association between sociodemographic variables and QKAP-EPI subscales using linear regression models. Results: CHWs demonstrated adequate knowledge regarding epilepsy for medical treatment details (Mean=1.63, SD=0.28) and epilepsy safety/risks (Mean=1.62, SD=0.59). However, CHWs reported low levels of knowledge related to the causes of epilepsy, espousing stigmatizing attitudes, as well as cultural treatment, which is the perception in different cultures of how epilepsy should be treated. Knowledge about how to manage epilepsy during crisis varied across the different types of emergency care practices. Heterogeneity in the level of knowledge regarding epilepsy was observed among CHWs in the different districts of Sofala Province and when using different local names of epilepsy (Dzumba, Nzwiti).Conclusion: CHWs knowledge of medical treatment and epilepsy safety/risks were adequate. However, information on the causes of epilepsy, stigmatizing attitudes, cultural treatment, and some aspects of epileptic crisis response were low. These areas of poor knowledge should be the focus of educating CHWs in increasing their ability to provide quality care for patients with epilepsy in LMICs.

Abnormalities in brain structural measures, such as cortical thickness and subcortical volumes, are observed in patients with major depressive disorder (MDD) who also often show heterogeneous clinical features. This study seeks to identify the multivariate associations between structural phenotypes and specific clinical symptoms, a novel area of investigation. T1-weighted magnetic resonance imaging measures were obtained using 3 T scanners for 178 unmedicated depressed patients at four academic medical centres. Cortical thickness and subcortical volumes were determined for the depressed patients and patients' clinical presentation was characterized by 213 item-level clinical measures, which were grouped into several large, homogeneous categories by K-means clustering. The multivariate correlations between structural and cluster-level clinical-feature measures were examined using canonical correlation analysis (CCA) and confirmed with both 5-fold and leave-one-site-out cross-validation. Four broad types of clinical measures were detected based on clustering: an anxious misery composite (composed of item-level depression, anxiety, anhedonia, neuroticism and suicidality scores); positive personality traits (extraversion, openness, agreeableness and conscientiousness); reported history of physical/emotional trauma; and a reported history of sexual abuse. Responses on the item-level anxious misery measures were negatively associated with cortical thickness/subcortical volumes in the limbic system and frontal lobe; reported childhood history of physical/emotional trauma and sexual abuse measures were negatively correlated with entorhinal thickness and left hippocampal volume, respectively. In contrast, the positive traits measures were positively associated with hippocampal and amygdala volumes and cortical thickness of the highly-connected precuneus and cingulate cortex. Our findings suggest that structural brain measures may reflect neurobiological mechanisms underlying MDD features.

International audience; To analyze the relationship between suicide in men and stratified measures of religiosity.Methods: We studied 192 suicides and 81 controls (nonsuicide, sudden, or accidental death). We employed the psychological autopsy method to compile diagnoses based on DSM-IV criteria. Overall, religiosity and participation in religious associations were determined using a Likert-type scale. Given the limited participation of women in the religious associations of southern Spain, only male subjects were included.Results: Religious participants had decreased risk of suicide compared to nonparticipants (OR = 0.148, 95% CI = 0.049-0.447). This lower risk was further associated with the degree of involvement in religious activity. Suicides accounted for 73.47% of subjects with no religious participation, 61.17% of those with some participation, and 56.52% of frequent participants (linear trend test Z = -2.0329, p = .042). Membership in a religious association was also associated with a lower rate of suicide compared to nonmembers (OR = 0.356, 95% CI = 0.172-0.736). This effect was similarly associated with the degree of involvement in the association. Suicides accounted for 74.67% of subjects who never participated in the activities of a religious association, 69.23% of those who sometimes participated, and 42.86% of frequent participants (linear trend test Z = -3.4082, p < .001).Conclusions: Religiosity, either as general participation or through a religious association, was associated with protection against suicide proportional to the degree of involvement in religious activities.

Objective To examine factors differentiating individuals whose first suicide attempt was during childhood (ages 5–12 yrs) from those who first attempted suicide during adolescence (13–19 yrs) and during adulthood (≥20 yrs). Method A sample of 418 participants (ages 18–64 yrs) with a mood disorder and ≥1 lifetime suicide attempt was divided into three groups according to age of first suicide attempt (childhood: N = 43, adolescent: N = 149, adulthood: N = 226) and compared on demographics, childhood adversity, parental psychopathology, comorbid lifetime axis I diagnoses, self-harm and characteristics of first attempt. Results Participants in the Childhood Attempt group were more likely to report childhood adversity, parental alcohol use disorder and subsequent suicide attempts than the two other groups. They were also more likely to have a depressed mother, non-suicidal self-injury (NSSI) during childhood and adolescence, lifetime PTSD and aggressive behavior than the Adulthood Attempt group. The Adolescent Attempt group had more childhood adversity, parental suicidal behavior, lifetime PTSD and NSSI during adolescence than the Adulthood Attempt group. The groups differed on methods of first attempt, and its lethality was related to age of attempt. Conclusions Early adversity and parental psychopathology are particularly prominent in those who make childhood suicide attempts, suggesting that this group may represent a suicidal behavior subtype.

Objective The cognitive theory of suicide postulates that hopelessness is an essential precondition for suicidal ideation in patients with depressive disorder . However, the explanatory power and predictive value of hopelessness for suicidal ideation remain uncertain. Methods From 1997 to 2007, patients with depressive disorder who were cohorts from the Vantaa Depression Studies (n = 406) completed the Scale for Suicide Ideation (SSI), Beck Hopelessness Scale (BHS), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Perceived Social Support Scale-Revised (PSSS-R), and Eysenck Personality Inventory-Q (EPI-Q) at baseline, 6 and 18 months, and 5 years. We conducted a mixed-effects generalized linear regression and clustered receiver-operating characteristics analysis to test how well BDI and BHS predict severe suicidal ideation within and between patients. Results BHS predicted clinically significant suicidal ideation (odds ratio [OR] = 2.8), explaining 13.1% of between-patient and and 3.5% of within-patient variance of SSI. Adjusting for the fixed effect of BDI removed a substantial part of the effect of BHS on SSI (adjusted OR = 1.38, P = .018). BAI moderated the effect of BHS on SSI, whereas EPI-Q and PSSS-R did not. BDI detected suicidal ideation more accurately (area under the receiver-operating characteristics curve [AUC] = 0.846) than BHS (AUC = 0.754). Conclusions In patients with depressive disorder, hopelessness explains suicidal ideation, but largely because it covaries with depressive symptoms. The role of hopelessness as a central determinant of suicidal ideation in depression may have been overestimated. Symptoms of anxiety moderate the association between hopelessness and suicidal ideation. Severity of depressive symptoms may predict suicidal ideation more accurately than hopelessness.

Background. Aberrant activity of the subcallosal cingulate (SCC) is a common theme across pharmacologic treatment efficacy prediction studies. The functioning of the SCC in psychotherapeutic interventions is relatively understudied, as are functional differences among SCC subdivisions. We conducted functional connectivity analyses (rsFC) on resting-state functional magnetic resonance imaging (fMRI) data, collected before and after a course of cognitive behavioral therapy (CBT) in patients with major depressive disorder (MDD), using seeds from three SCC subdivisions. Methods. Resting-state data were collected from unmedicated patients with current MDD (Hamilton Depression Rating Scale-17 > 16) before and after 14-sessions of CBT monotherapy. Treatment outcome was assessed using the Beck Depression Inventory (BDI). Rostral anterior cingulate (rACC), anterior subcallosal cingulate (aSCC), and Brodmann’s area 25 (BA25) masks were used as seeds in connectivity analyses that assessed baseline rsFC and symptom severity, changes in connectivity related to symptom improvement after CBT, and prediction of treatment outcomes using whole-brain baseline connectivity. Results. Pretreatment BDI negatively correlated with pretreatment rACC ~ dorsolateral prefrontal cortex and aSCC ~ lateral prefrontal cortex rsFC. In a region-of-interest longitudinal analysis, rsFC between these regions increased post-treatment (p FDR). In whole-brain analyses, BA25 ~ paracentral lobule and rACC ~ paracentral lobule connectivities decreased post-treatment. Whole-brain baseline rsFC with SCC did not predict clinical improvement. Conclusions. rsFC features of rACC and aSCC, but not BA25, correlated inversely with baseline depression severity, and increased following CBT. Subdivisions of SCC involved in top-down emotion regulation may be more involved in cognitive interventions, while BA25 may be more informative for interventions targeting bottom-up processing. Results emphasize the importance of subdividing the SCC in connectivity analyses.

Efforts in research, prevention, and treatment of suicidal behavior have produced mixed results. One of the main barriers to combating suicidal behavior lies in the very conceptualization of suicide, a phenomenon that is at once sociological, psychiatric, and even philosophical, and one that has not always been included in the field of health care. There are also many barriers at the social level, ranging from stigma against people with suicidal behavior to stigma towards psychiatric care, as well as the controversial role of the media. The media plays an important role in society and depending on its attitude it can be either beneficial or harmful in our fight against suicidal behavior. Differences between countries - in the provision of resources, in the way of understanding the phenomenon or in the manner of providing official figures - pose an additional challenge to suicide prevention on a global level. In the field of research, predicting suicidal behavior by identifying effective risk markers is severely hampered by the low occurrence of suicide in the population, which limits the statistical power of studies. The authors recommend combining various risk factors to build predictive models. This, in addition to employing increasingly precise machine learning techniques, is a step in the right direction, although there is still a long way to go before the expected results can be obtained. Finally, adequate training of health professionals, both specialized and non-specialized, as well as gatekeeper training, is crucial for implementing suicide prevention strategies in the population.

It is unclear whether anxiety increases or decreases suicidal risk. This may contribute to the lack of guidance on which antidepressant medications are best for suicidal depressed patients who present with high anxiety. This study explored whether anxiety predicts suicidal ideation in depressed individuals treated with paroxetine or bupropion. An 8-week double-blind trial comparing controlled-release paroxetine (N=36) versus extended-release bupropion (N=38) for effect on suicidal ideation and behavior in depressed patients with suicidal ideation, past attempt, or both found an advantage for paroxetine, but anxiety effects were not investigated. This secondary analysis explored the relationship, measured at baseline and weekly, of anxiety with suicidal ideation. Anxiety severity measured weekly correlated with suicidal ideation severity irrespective of treatment (P=0.012). Patients with high baseline anxiety showed a trend toward faster reduction of suicidal ideation with paroxetine compared with bupropion treatment (standard P=0.047; bootstrap P=0.077). The latter finding, if confirmed in larger samples, could enhance choice of antidepressant medication for suicidal, depressed patients presenting with high levels of anxiety.

Prior research suggests that sleep disturbances are associated with increased risk of suicide. However, sleep disturbances are associated with a wide range of psychiatric disorders, and it is unknown whether this association is independent of psychopathology. In a large nationally representative prospective survey, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), we used structural equation modeling to examine the shared and specific effects of three sleep complaints (i.e., trouble falling asleep, early morning awakening, and hypersomnia) on the 3-year occurrence of attempting suicide. Because psychiatric disorders increase the risk of suicide attempt almost exclusively through a general psychopathology factor representing their shared effect, covariates included that factor, prior history of suicide attempt, and a wide range of sociodemographic and clinical characteristics. The 3-year prevalence rate of suicide attempt was 0.6% (n = 241). Compared with participants who did not attempt suicide between the two waves, those who did reported significantly more frequently having trouble falling asleep (44.6% vs. 16.6%), early morning awakening (38.9% vs. 12.7%), and hypersomnia (35.0% vs. 10.7%). Following adjustments, effects of sleep complaints on this risk were significant and exerted almost exclusively through a general sleep complaints factor representing the shared effect across all sleep complaints. There were no residual associations of any individual sleep complaint with attempting suicide above that association. Sleep complaints are associated with an increased risk of attempting suicide independently of psychopathology, and should be included in suicide risk assessments as these symptoms may provide targets for reducing the risks of suicidal behaviors.

A better understanding of suicide phenomena is needed, and precision medicine is a promising approach toward this aim. In this manuscript, we review recent advances in the field, with particular focus on the role of digital health. Technological advances such as smartphone-based ecological momentary assessment and passive collection of information from sensors provide a detailed description of suicidal behavior and thoughts. Further, we review more traditional approaches in the field of genetics. We first highlight the need for precision medicine in suicidology. Then, in light of recent and promising research, we examine the role of smartphone-based information collection using explicit (active) and implicit (passive) means to construct a digital phenotype, which should be integrated with genetic and epigenetic data to develop tailored therapeutic and preventive approaches for suicide.

BackgroundMajor depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.MethodsWithin an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.ResultsFive pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).ConclusionsA subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

To date, there are no biomarkers for major depressive disorder (MDD) treatment response in clinical use. Such biomarkers could allow for individualized treatment selection, reducing time spent on ineffective treatments and the burden of MDD. In search of such a biomarker, multisite pretreatment and early-treatment (1 week into treatment) structural magnetic resonance (MR) images were acquired from 184 patients with MDD randomized to an 8-week trial of the selective serotonin reuptake inhibitor (SSRI) sertraline or placebo. This study represents a large, multisite, placebo-controlled effort to examine the association between pretreatment differences or early-treatment changes in cortical thickness and treatment-specific outcomes. For standardization, a novel, robust site harmonization procedure was applied to structural measures in a priori regions (rostral and caudal anterior cingulate, lateral orbitofrontal, rostral middle frontal, and hippocampus), chosen based on previously published reports. Pretreatment cortical thickness or volume did not significantly associate with SSRI response. Thickening of the rostral anterior cingulate cortex in the first week of treatment was associated with better 8-week responses to SSRI (p = 0.010). These findings indicate that frontal lobe structural alterations in the first week of treatment may be associated with long-term treatment efficacy. While these associational findings may help to elucidate the specific neural targets of SSRIs, the predictive accuracy of pretreatment or early-treatment structural alterations in classifying treatment remitters from nonremitters was limited to 63.9%. Therefore, in this large sample of adults with MDD, structural MR imaging measures were not found to be clinically translatable biomarkers of treatment response to SSRI or placebo.

Objective Neurocognitive dysfunction in patients with residual or emergent symptoms after treatment for Lyme Disease is often attributed to comorbid depression. In this study, patients with Post-Treatment Lyme Disease Syndrome (PTLDS) were compared to patients with Major Depressive Disorder (MDD), as well as healthy comparison subjects (HC), on neurocognitive measures administered through the same laboratory, to determine if patterns of performance were similar. Methods Two analyses were conducted. First, performance on the Wechsler Adult Intelligence Scale (WAIS-III) and on subtests from the Wechsler Memory Scale (WMS-III) was compared among the groups. Second, comparable subgroups of PTLDS and MDD patients with at least one low WMS-III score were compared on an additional set of measures assessing motor function, psychomotor performance, attention, memory, working memory, and language fluency, to determine if the overall profile of performance was similar in the two subgroups. Results In the first analysis, PTLDS patients performed more poorly than both MDD and HC on tasks assessing verbal abilities, working memory, and paragraph learning. Processing speed in the two patient groups, however, was equally reduced. In the second analysis, MDD patients with low WMS-III exhibited concomitantly greater difficulties in psychomotor speed and attention, while low-WMS-III PTLDS patients exhibited greater difficulties in language fluency. Conclusions MDD and PTLDS can be confused neuropsychologically because both exhibit similar levels of psychomotor slowing. However, problems on memory-related tasks, though mild, are more pronounced in PTLDS. PTLDS patients with poorer memory also exhibit poorer language fluency, and less deficit in processing speed and attention compared to MDD.