Cognitive Behavioural Therapy for insomnia decreases the discrepancy between objective and subjective measures of sleep.

INTRODUCTION: Individuals with insomnia disorder often exhibit differences between reported experiences of sleep and objectively measured sleep parameters; however, the implications of this subjective-objective sleep discrepancy during treatment remains unclear. OBJECTIVE: The aim of this study was to investigate the impact of cognitive behavioural therapy for insomnia (CBT-I) on the discrepancy between objective and subjective measures of sleep, and to assess whether changes in clinical variables such as depression, anxiety, fatigue, and beliefs about sleep, were related to changes in discrepancy. METHODS: Twenty-five participants with insomnia disorder were enrolled in group CBT-I. Sleep measures were continually sampled from baseline until 2 weeks post-treatment with both objective (i.e., actigraphy) and subjective (i.e., sleep diary) methods. RESULTS: The subjective-objective discrepancy significantly decreased from baseline early on in treatment (following the second session) and were maintained at post-treatment for sleep onset latency, wake after sleep onset (WASO) and sleep efficiency (SE). Total sleep time (TST) discrepancy and misperception decreased from baseline to post-treatment. Improvement in depression symptoms, fatigue symptoms, and negative beliefs about sleep were significantly correlated with the decrease in the discrepancy for WASO and SE. CONCLUSION: These findings suggest that CBT-I resolves the mismatch between objective and subjective sleep parameters early in treatment for adults with insomnia. Sleep misperception improved from underestimating to accurately estimating TST. Improvement of psychological symptoms were related to decrease in sleep discrepancies across treatment. Future research is needed to explore how feedback on objective and subjective sleep discrepancy may impact sleep perception across treatment with CBT-I.

Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo.

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (ß = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

Large Individual Differences in Functional Connectivity in the Context of Major Depression and Antidepressant Pharmacotherapy.

Clinical studies of major depression (MD) generally focus on group effects, yet interindividual differences in brain function are increasingly recognized as important and may even impact effect sizes related to group effects. Here, we examine the magnitude of individual differences in relation to group differences that are commonly investigated (e.g., related to MD diagnosis and treatment response). Functional MRI data from 107 participants (63 female, 44 male) were collected at baseline, 2, and 8 weeks during which patients received pharmacotherapy (escitalopram, N = 68) and controls (N = 39) received no intervention. The unique contributions of different sources of variation were examined by calculating how much variance in functional connectivity was shared across all participants and sessions, within/across groups (patients vs controls, responders vs nonresponders, female vs male participants), recording sessions, and individuals. Individual differences and common connectivity across groups, sessions, and participants contributed most to the explained variance (>95% across analyses). Group differences related to MD diagnosis, treatment response, and biological sex made significant but small contributions (0.3-1.2%). High individual variation was present in cognitive control and attention areas, while low individual variation characterized primary sensorimotor regions. Group differences were much smaller than individual differences in the context of MD and its treatment. These results could be linked to the variable findings and difficulty translating research on MD to clinical practice. Future research should examine brain features with low and high individual variation in relation to psychiatric symptoms and treatment trajectories to explore the clinical relevance of the individual differences identified here.

Depression-Anxiety Coupling Strength as a predictor of relapse in major depressive disorder: A CAN-BIND wellness monitoring study report.

BACKGROUND: A critical challenge in the study and management of major depressive disorder (MDD) is predicting relapse. We examined the temporal correlation/coupling between depression and anxiety (called Depression-Anxiety Coupling Strength, DACS) as a predictor of relapse in patients with MDD. METHODS: We followed 97 patients with remitted MDD for an average of 394 days. Patients completed weekly self-ratings of depression and anxiety symptoms using the Quick Inventory of Depressive Symptoms (QIDS-SR) and the Generalized Anxiety Disorder 7-item scale (GAD-7). Using these longitudinal ratings we computed DACS as random slopes in a linear mixed effects model reflecting individual-specific degree of correlation between depression and anxiety across time points. We then tested DACS as an independent variable in a Cox proportional hazards model to predict relapse. RESULTS: A total of 28 patients (29 %) relapsed during the follow-up period. DACS significantly predicted confirmed relapse (hazard ratio [HR] 1.5, 95 % CI [1.01, 2.22], p = 0.043; Concordance 0.79 [SE 0.04]). This effect was independent of baseline depressive or anxiety symptoms or their average levels over the follow-up period, and was identifiable more than one month before relapse onset. LIMITATIONS: Small sample size, in a single study. Narrow phenotype and comorbidity profiles. CONCLUSIONS: DACS may offer opportunities for developing novel strategies for personalized monitoring, early detection, and intervention. Future studies should replicate our findings in larger, diverse patient populations, develop individual patient prediction models, and explore the underlying mechanisms that govern the relationship of DACS and relapse.

Integrative Genetic Variation, DNA Methylation, and Gene Expression Analysis of Escitalopram and Aripiprazole Treatment Outcomes in Depression: A CAN-BIND-1 Study.

INTRODUCTION: Little is known about the interplay between genetics and epigenetics on antidepressant treatment (1) response and remission, (2) side effects, and (3) serum levels. This study explored the relationship among single nucleotide polymorphisms (SNPs), DNA methylation (DNAm), and mRNA levels of four pharmacokinetic genes, CYP2C19, CYP2D6, CYP3A4, and ABCB1, and its effect on these outcomes. METHODS: The Canadian Biomarker Integration Network for Depression-1 dataset consisted of 177 individuals with major depressive disorder treated for 8 weeks with escitalopram (ESC) followed by 8 weeks with ESC monotherapy or augmentation with aripiprazole. DNAm quantitative trait loci (mQTL), identified by SNP-CpG associations between 20 SNPs and 60 CpG sites in whole blood, were tested for associations with our outcomes, followed by causal inference tests (CITs) to identify methylation-mediated genetic effects. RESULTS: Eleven cis-SNP-CpG pairs (q<0.05) constituting four unique SNPs were identified. Although no significant associations were observed between mQTLs and response/remission, CYP2C19 rs4244285 was associated with treatment-related weight gain (q=0.027) and serum concentrations of ESCadj (q<0.001). Between weeks 2-4, 6.7% and 14.9% of those with *1/*1 (normal metabolizers) and *1/*2 (intermediate metabolizers) genotypes, respectively, reported ≥2 lbs of weight gain. In contrast, the *2/*2 genotype (poor metabolizers) did not report weight gain during this period and demonstrated the highest ESCadj concentrations. CITs did not indicate that these effects were epigenetically mediated. DISCUSSION: These results elucidate functional mechanisms underlying the established associations between CYP2C19 rs4244285 and ESC pharmacokinetics. This mQTL SNP as a marker for antidepressant-related weight gain needs to be further explored.

The association of blood biomarkers with cerebral white matter and myelin content in bipolar disorder: a systematic review.

OBJECTIVES: Evidence from diffusion tensor imaging (DTI) and postmortem studies has demonstrated white-matter (WM) deficits in bipolar disorder (BD). Changes in peripheral blood biomarkers have also been observed; however, studies evaluating the potential relationship between brain alterations and the periphery are scarce. The objective of this systematic review is to investigate the relationship between blood-based biomarkers and WM in BD. METHODS: PubMed, Embase, and PsycINFO were used to conduct literature searches. Cross-sectional or longitudinal studies reporting original data which investigated both a blood-based biomarker and WM (by neuroimaging) in BD were included. RESULTS: Of 3,750 studies retrieved, 23 were included. Several classes of biomarkers were found to have a significant relationship with WM in BD. These included cytokines and growth factors (interleukin-8 [IL-8], tumor necrosis factor alpha [TNF-a], and insulin-like growth factor binding protein 3 [IGFBP-3]), innate immune system (natural killer cells [NK]), metabolic markers (lipid hydroperoxidase, cholesterol, triglycerides), the kynurenine (Kyn) pathway (5-hydroxyindoleacetic acid, kynurenic acid [Kyna]), and various gene polymorphisms (serotonin-transporter-linked promoter region). CONCLUSION: This systematic review revealed that blood-based biomarkers are associated with markers of WM deficits observed in BD. Longitudinal studies investigating the potential clinical utility of these specific biomarkers are encouraged.

Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023 Update on Clinical Guidelines for Management of Major Depressive Disorder in Adults: Réseau canadien pour les traitements de l'humeur et de l'anxiété (CANMAT) 2023 : Mise à jour des lignes directrices cliniques pour la prise en charge du trouble dépressif majeur chez les adultes.

BACKGROUND: The Canadian Network for Mood and Anxiety Treatments (CANMAT) last published clinical guidelines for the management of major depressive disorder (MDD) in 2016. Owing to advances in the field, an update was needed to incorporate new evidence and provide new and revised recommendations for the assessment and management of MDD in adults. METHODS: CANMAT convened a guidelines editorial group comprised of academic clinicians and patient partners. A systematic literature review was conducted, focusing on systematic reviews and meta-analyses published since the 2016 guidelines. Recommendations were organized by lines of treatment, which were informed by CANMAT-defined levels of evidence and supplemented by clinical support (consisting of expert consensus on safety, tolerability, and feasibility). Drafts were revised based on review by patient partners, expert peer review, and a defined expert consensus process. RESULTS: The updated guidelines comprise eight primary topics, in a question-and-answer format, that map a patient care journey from assessment to selection of evidence-based treatments, prevention of recurrence, and strategies for inadequate response. The guidelines adopt a personalized care approach that emphasizes shared decision-making that reflects the values, preferences, and treatment history of the patient with MDD. Tables provide new and updated recommendations for psychological, pharmacological, lifestyle, complementary and alternative medicine, digital health, and neuromodulation treatments. Caveats and limitations of the evidence are highlighted. CONCLUSIONS: The CANMAT 2023 updated guidelines provide evidence-informed recommendations for the management of MDD, in a clinician-friendly format. These updated guidelines emphasize a collaborative, personalized, and systematic management approach that will help optimize outcomes for adults with MDD.

Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder.

BACKGROUND: Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories. METHODS: A total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response. RESULTS: Brain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles. CONCLUSIONS: Consistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function.

Greater within- and between-day instability is associated with worse anxiety and depression symptoms.

BACKGROUND: Depression and anxiety affect hundreds of millions of people worldwide, and their prevalence increased during the COVID-19 pandemic as social schedules were disrupted. This study explores the associations between anxiety and depression and within- and between-day instability of affective, somatic, and cognitive symptoms during the early pandemic stages. METHODS: Participants (n = 153, ages 18-77, 72 % female) reported daily levels of affective (anxiety/sadness), somatic (appetite/sleepiness), and cognitive (concentration/energy) symptoms for 14-44 days at five timepoints: 0, 3, 6, 9, and 12 h after awakening. At the end of the study, participants completed validated scales for anxiety (GAD-7) and depression (PHQ-9). Symptom instability was assessed using the Absolute Real Variability (ARV) index. Regression models examined within-day instability (WD-I) and between-day instability (BD-I) with GAD-7 and PHQ-9 scores as outcomes. RESULTS: Greater instability (both WD-I and BD-I) of affective symptoms correlated with elevated GAD-7 and PHQ-9 scores. For somatic and cognitive symptoms, greater BD-I was associated with higher scores. LIMITATIONS: The study used retrospective daily data, which could benefit from real-time assessments for improved accuracy. CONCLUSIONS: This study provides empirical evidence of a connection between greater anxiety and depression severity and increased instability in daily mood and physiological symptoms. The findings underscore the importance of consistent symptom monitoring to understand overall mental health trajectories. Additionally, it highlights the role of daily routines in stabilizing the circadian system, potentially regulating physiological and psychological processes and reducing symptom instability.

Factors associated with suicide risk in young women with premenstrual dysphoric disorder: A population-based study.

PURPOSE: Women with premenstrual dysphoric disorder (PMDD) are more likely to report suicide ideation and behavior when compared to women without PMDD. However, there is a lack of studies investigating the risk factors for suicide risk in women with PMDD. Thus, the aim of this study is to assess the factors associated with suicide risk in young women with PMDD. METHODS: This is a cross-sectional study including 128 young women with PMDD who were recruited from the community. PMDD and suicide risk were assessed by trained psychologists using the Mini International Neuropsychiatric Interview (MINI-PLUS). Suicide risk evaluation includes six questions that assess suicidal intention, planning and previous attempts. Subjects who answer yes to any of the six questions are classified as having current suicide risk. RESULTS: The prevalence of current suicide risk in women with PMDD was 28.1%. The factors associated with suicide risk in this population were: presenting current panic disorder (OR: 18.71 [95% CI: 1.02 - 343.27], p=0.048), a non-white skin color (OR: 4.18 [CI 95%: 1.28 - 13.61], p=0.018), greater severity of depressive symptoms (OR: 1.22 [95% CI: 1.12 - 1.32], < 0.001), and history of childhood trauma (OR: 1.04 [95% CI: 1.01 - 1.08], 0.010). CONCLUSION: Our findings indicate that there are key sociodemographic and clinical factors associated with suicide risk in young women with PMDD, enabling clinicians to identify at-risk individuals who could benefit from further screening and interventions.

Routine regularity during a global pandemic: Impact on mental health outcomes and influence of chronotype.

Among the public health recommendations for supporting mental health during the COVID-19 pandemic, many strategies had an impact on biological rhythms, like sleep hygiene, physical exercise and healthy eating habits. Considering the known relationship between circadian organization and mental health, our aim was to test the association between behavioral regularity and mental health, and its interaction with chronotype, in a large sample surveyed in Brazil. We collected longitudinal data using online questionnaires that assessed sociodemographic characteristics, behavioral routines, mental health (PHQ-9, GAD-7, WHO-5 scales), and chronotype estimation based on midpoint of sleep on free days - MSF (µMCTQ), in a sample of 1390 participants (81% females). We computed a Routine Regularity Score (RRS) that reflects regularity across four behaviors: sleep, eating, working, exercising. There was a strong negative association between RRS and the severity of anxiety and depressive symptoms (GAD-7 and PHQ-9 scores), which was weaker among participants with late MSF, and a strong positive association with well-being (WHO-5 scores). RRS was a mediator of the MSF-mental health association and a predictor of mental health states. This study provides empirical evidence that maintaining behavioral routines during times of hardship may serve as tools to alleviate the negative impact on mental health.

Functional neuroimaging biomarkers of anhedonia response to escitalopram plus adjunct aripiprazole treatment for major depressive disorder.

BACKGROUND: Identifying neuroimaging biomarkers of antidepressant response may help guide treatment decisions and advance precision medicine. AIMS: To examine the relationship between anhedonia and functional neurocircuitry in key reward processing brain regions in people with major depressive disorder receiving aripiprazole adjunct therapy with escitalopram. METHOD: Data were collected as part of the CAN-BIND-1 study. Participants experiencing a current major depressive episode received escitalopram for 8 weeks; escitalopram non-responders received adjunct aripiprazole for an additional 8 weeks. Functional magnetic resonance imaging (on weeks 0 and 8) and clinical assessment of anhedonia (on weeks 0, 8 and 16) were completed. Seed-based correlational analysis was employed to examine the relationship between baseline resting-state functional connectivity (rsFC), using the nucleus accumbens (NAc) and anterior cingulate cortex (ACC) as key regions of interest, and change in anhedonia severity after adjunct aripiprazole. RESULTS: Anhedonia severity significantly improved after treatment with adjunct aripiprazole.There was a positive correlation between anhedonia improvement and rsFC between the ACC and posterior cingulate cortex, ACC and posterior praecuneus, and NAc and posterior praecuneus. There was a negative correlation between anhedonia improvement and rsFC between the ACC and anterior praecuneus and NAc and anterior praecuneus. CONCLUSIONS: Eight weeks of aripiprazole, adjunct to escitalopram, was associated with improved anhedonia symptoms. Changes in functional connectivity between key reward regions were associated with anhedonia improvement, suggesting aripiprazole may be an effective treatment for individuals experiencing reward-related deficits. Future studies are required to replicate our findings and explore their generalisability, using other agents with partial dopamine (D2) agonism and/or serotonin (5-HT2A) antagonism.

An empirical analysis of structural neuroimaging profiles in a staging model of depression.

We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions. Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses. Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group. We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.

Assessing remission in major depressive disorder using a functional-structural data fusion pipeline: A CAN-BIND-1 study.

Neural network-level changes underlying symptom remission in major depressive disorder (MDD) are often studied from a single perspective. Multimodal approaches to assess neuropsychiatric disorders are evolving, as they offer richer information about brain networks. A FATCAT-awFC pipeline was developed to integrate a computationally intense data fusion method with a toolbox, to produce a faster and more intuitive pipeline for combining functional connectivity with structural connectivity (denoted as anatomically weighted functional connectivity (awFC)). Ninety-three participants from the Canadian Biomarker Integration Network for Depression study (CAN-BIND-1) were included. Patients with MDD were treated with 8 weeks of escitalopram and adjunctive aripiprazole for another 8 weeks. Between-group connectivity (SC, FC, awFC) comparisons contrasted remitters (REM) with non-remitters (NREM) at baseline and 8 weeks. Additionally, a longitudinal study analysis was performed to compare connectivity changes across time for REM, from baseline to week-8. Association between cognitive variables and connectivity were also assessed. REM were distinguished from NREM by lower awFC within the default mode, frontoparietal, and ventral attention networks. Compared to REM at baseline, REM at week-8 revealed increased awFC within the dorsal attention network and decreased awFC within the frontoparietal network. A medium effect size was observed for most results. AwFC in the frontoparietal network was associated with neurocognitive index and cognitive flexibility for the NREM group at week-8. In conclusion, the FATCAT-awFC pipeline has the benefit of providing insight on the 'full picture' of connectivity changes for REMs and NREMs while making for an easy intuitive approach.

Influence of CYP2C19, CYP2D6, and ABCB1 Gene Variants and Serum Levels of Escitalopram and Aripiprazole on Treatment-Emergent Sexual Dysfunction: A Canadian Biomarker Integration Network in Depression 1 (CAN-BIND 1) Study.

OBJECTIVES: Treatment-emergent sexual dysfunction is frequently reported by individuals with major depressive disorder (MDD) on antidepressants, which negatively impacts treatment adherence and efficacy. We investigated the association of polymorphisms in pharmacokinetic genes encoding cytochrome-P450 drug-metabolizing enzymes, CYP2C19 and CYP2D6, and the transmembrane efflux pump, P-glycoprotein (i.e., ABCB1), on treatment-emergent changes in sexual function (SF) and sexual satisfaction (SS) in the Canadian Biomarker Integration Network in Depression 1 (CAN-BIND-1) sample. METHODS: A total of 178 adults with MDD received treatment with escitalopram (ESC) from weeks 0-8 (Phase I). At week 8, nonresponders were augmented with aripiprazole (ARI) (i.e., ESC + ARI, n = 91), while responders continued ESC (i.e., ESC-Only, n = 80) from weeks 8-16 (Phase II). SF and SS were evaluated using the sex effects (SexFX) scale at weeks 0, 8, and 16. We assessed the primary outcomes, SF and SS change for weeks 0-8 and 8-16, using repeated measures mixed-effects models. RESULTS: In ESC-Only, CYP2C19 intermediate metabolizer (IM) + poor metabolizers (PMs) showed treatment-related improvements in sexual arousal, a subdomain of SF, from weeks 8-16, relative to CYP2C19 normal metabolizers (NMs) who showed a decline, F(2,54) = 8.00, p < 0.001, q = 0.048. Specifically, CYP2C19 IM + PMs reported less difficulty with having and sustaining vaginal lubrication in females and erection in males, compared to NMs. Furthermore, ESC-Only females with higher concentrations of ESC metabolite, S-desmethylcitalopram (S-DCT), and S-DCT/ESC ratio in serum demonstrated more decline in SF (r = -0.42, p = 0.004, q = 0.034) and SS (r = -0.43, p = 0.003, q = 0.034), respectively, which was not observed in males. ESC-Only females also demonstrated a trend for a correlation between S-DCT and sexual arousal change in the same direction (r = -0.39, p = 0.009, q = 0.052). CONCLUSIONS: CYP2C19 metabolizer phenotypes may be influencing changes in sexual arousal related to ESC monotherapy. Thus, preemptive genotyping of CYP2C19 may help to guide selection of treatment that circumvents selective serotonin reuptake inhibitor-related sexual dysfunction thereby improving outcomes for patients. Additionally, further research is warranted to clarify the role of S-DCT in the mechanisms underlying ESC-related changes in SF and SS. This CAN-BIND-1 study was registered on clinicaltrials.gov (Identifier: NCT01655706) on 27 July 2012.

Relation of hippocampal volume and SGK1 gene expression to treatment remission in major depression is moderated by childhood maltreatment: A CAN-BIND-1 report.

Preclinical research implicates stress-induced upregulation of the enzyme, serum- and glucocorticoid-regulated kinase 1 (SGK1), in reduced hippocampal volume. In the current study, we tested the hypothesis that greater SGK1 mRNA expression in humans would be associated with lower hippocampal volume, but only among those with a history of prolonged stress exposure, operationalized as childhood maltreatment (physical, sexual, and/or emotional abuse). Further, we examined whether baseline levels of SGK1 and hippocampal volume, or changes in these markers over the course of antidepressant treatment, would predict treatment outcomes in adults with major depression [MDD]. We assessed SGK1 mRNA expression from peripheral blood, and left and right hippocampal volume at baseline, as well as change in these markers over the first 8 weeks of a 16-week open-label trial of escitalopram as part of the Canadian Biomarker Integration Network in Depression program (MDD [n = 161] and healthy comparison participants [n = 91]). Childhood maltreatment was assessed via contextual interview with standardized ratings. In the full sample at baseline, greater SGK1 expression was associated with lower hippocampal volume, but only among those with more severe childhood maltreatment. In individuals with MDD, decreases in SGK1 expression predicted lower remission rates at week 16, again only among those with more severe maltreatment. Decreases in hippocampal volume predicted lower week 16 remission for those with low childhood maltreatment. These results suggest that both glucocorticoid-related neurobiological mechanisms of the stress response and history of childhood stress exposure may be critical to understanding differential treatment outcomes in MDD. ClinicalTrials.gov: NCT01655706 Canadian Biomarker Integration Network for Depression Study.

The association of blood biomarkers with cerebral white matter and myelin content in bipolar disorder: a systematic review

Objectives: Evidence from diffusion tensor imaging (DTI) and postmortem studies has demonstrated white-matter (WM) deficits in bipolar disorder (BD). Changes in peripheral blood biomarkers have also been observed; however, studies evaluating the potential relationship between brain alterations and the periphery are scarce. The objective of this systematic review is to investigate the relationship between blood-based biomarkers and WM in BD. Methods: PubMed, Embase, and PsycINFO were used to conduct literature searches. Cross-sectional or longitudinal studies reporting original data which investigated both a blood-based biomarker and WM (by neuroimaging) in BD were included. Results: Of 3,750 studies retrieved, 23 were included. Several classes of biomarkers were found to have a significant relationship with WM in BD. These included cytokines and growth factors (interleukin-8 [IL-8], tumor necrosis factor alpha [TNF-α], and insulin-like growth factor binding protein 3 [IGFBP-3]), innate immune system (natural killer cells [NK]), metabolic markers (lipid hydroperoxidase, cholesterol, triglycerides), the kynurenine (Kyn) pathway (5-hydroxyindoleacetic acid, kynurenic acid [Kyna]), and various gene polymorphisms (serotonin-transporter-linked promoter region). Conclusion: This systematic review revealed that blood-based biomarkers are associated with markers of WM deficits observed in BD. Longitudinal studies investigating the potential clinical utility of these specific biomarkers are encouraged. Systematic review registration: PROSPERO CRD42021279246.

A tale of two targets: examining the differential effects of posterior cingulate cortex- and amygdala-targeted fMRI-neurofeedback in a PTSD pilot study.

Introduction: Real-time fMRI-based neurofeedback (rt-fMRI-NFB) is a non-invasive technology that enables individuals to self-regulate brain activity linked to neuropsychiatric symptoms, including those associated with post-traumatic stress disorder (PTSD). Selecting the target brain region for neurofeedback-mediated regulation is primarily informed by the neurobiological characteristics of the participant population. There is a strong link between PTSD symptoms and multiple functional disruptions in the brain, including hyperactivity within both the amygdala and posterior cingulate cortex (PCC) during trauma-related processing. As such, previous rt-fMRI-NFB studies have focused on these two target regions when training individuals with PTSD to regulate neural activity. However, the differential effects of neurofeedback target selection on PTSD-related neural activity and clinical outcomes have not previously been investigated. Methods: Here, we compared whole-brain activation and changes in PTSD symptoms between PTSD participants (n = 28) that trained to downregulate activity within either the amygdala (n = 14) or the PCC (n = 14) while viewing personalized trauma words. Results: For the PCC as compared to the amygdala group, we observed decreased neural activity in several regions implicated in PTSD psychopathology - namely, the bilateral cuneus/precuneus/primary visual cortex, the left superior parietal lobule, the left occipital pole, and the right superior temporal gyrus/temporoparietal junction (TPJ) - during target region downregulation using rt-fMRI-NFB. Conversely, for the amygdala as compared to the PCC group, there were no unique (i.e., over and above that of the PCC group) decreases in neural activity. Importantly, amygdala downregulation was not associated with significantly improved PTSD symptoms, whereas PCC downregulation was associated with reduced reliving and distress symptoms over the course of this single training session. In this pilot analysis, we did not detect significant between-group differences in state PTSD symptoms during neurofeedback. As a critical control, the PCC and amygdala groups did not differ in their ability to downregulate activity within their respective target brain regions. This indicates that subsequent whole-brain neural activation results can be attributed to the effects of the neurofeedback target region selection in terms of neurophysiological function, rather than as a result of group differences in regulatory success. Conclusion: In this study, neurofeedback-mediated downregulation of the PCC was differentially associated with reduced state PTSD symptoms and simultaneous decreases in PTSD-associated brain activity during a single training session. This novel analysis may guide researchers in choosing a neurofeedback target region in future rt-fMRI-NFB studies and help to establish the clinical efficacy of specific neurofeedback targets for PTSD. A future multi-session clinical trial of rt-fMRI-NFB that directly compares between PCC and amygdala target regions is warranted.

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report.

Background: Quality of life (QoL) is an important patient-centric outcome to evaluate in treatment of major depressive disorder (MDD). This work sought to investigate the performance of several machine learning methods to predict a return to normative QoL in patients with MDD after antidepressant treatment.Methods: Several binary classification algorithms were trained on data from the first 2 weeks of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (n = 651, conducted from 2001 to 2006) to predict week 9 normative QoL (score ≥ 67, based on a community normative sample, on the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form [Q-LES-Q-SF]) after treatment with citalopram. Internal validation was performed using a STAR*D holdout dataset, and external validation was performed using the Canadian Biomarker Integration Network in Depression-1 (CAN-BIND-1) dataset (n = 175, study conducted from 2012 to 2017) after treatment with escitalopram. Feature importance was calculated using SHapley Additive exPlanations (SHAP).Results: Random Forest performed most consistently on internal and external validation, with balanced accuracy (area under the receiver operator curve) of 71% (0.81) on the STAR*D dataset and 69% (0.75) on the CAN-BIND-1 dataset. Random Forest Classifiers trained on Q-LES-Q-SF and Quick Inventory of Depressive Symptomatology-Self-Rated variables had similar performance on both internal and external validation. Important predictive variables came from psychological, physical, and socioeconomic domains.Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.

Delphi consensus study to develop guidelines for the management of adults with borderline personality disorder in the emergency department: a protocol.

INTRODUCTION: Clinicians caring for adults with borderline personality disorder (BPD) in acute settings such as the emergency department (ED) have little evidence/guidance to base decisions on. Specific/detailed guidance for managing BPD in the ED is needed given the morbidity and mortality risks, high service utilisation, unique challenges and risk of iatrogenic interventions. The primary objective of this study is to use a consensus method to develop a guideline for managing adults with BPD in the ED. This protocol and the key questions for the guideline were developed with the advice of people with BPD and their family members/support persons. METHODS AND ANALYSIS: We will perform a four-phase Delphi study of an expert panel of clinicians, researchers, adults with BPD and their family members/support persons. Various disciplines (psychiatry, psychology, emergency medicine, nursing, social work) and treatment approaches will be included in the expert panel. An online questionnaire will be developed from systematic reviews, qualitative assessments of pivotal literature, and opinions suggested by the panel (phase 1). The panel will rate their agreement on opinions for each key question covering areas of emergency care of adults with BPD using two rounds of this questionnaire (phases 2 and 3). Opinions meeting predefined thresholds for consensus will be brought to consensus meetings moderated by an independent chair (phase 4). The purpose of these meetings is to finalise the set and phrasing of the opinions for each area of emergency care. These final opinions will be the recommendations in the guideline. If there are significant differences of opinion, the guideline will present both recommendations alongside one another. ETHICS AND DISSEMINATION: This study has received ethics approval by the Hamilton Integrated Research Ethics Board in Hamilton, Ontario, Canada. The results of this study will be disseminated through peer-reviewed publications, conferences and national professional and patient/family/support associations.