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.

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.

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.

Prediction of depression treatment outcome from multimodal data: a CAN-BIND-1 report.

BACKGROUND: Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers. METHODS: In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively. RESULTS: A combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction. CONCLUSIONS: A combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.

Identification of Endocannabinoid Predictors of Treatment Outcomes in Major Depressive Disorder: A Secondary Analysis of the First Canadian Biomarker Integration Network in Depression (CAN-BIND 1) Study.

INTRODUCTION: An increasing number of studies are examining the link between the endocannabinoidome and major depressive disorder (MDD). We conducted an exploratory analysis of this system to identify potential markers of treatment outcomes. METHODS: The dataset of the Canadian Biomarker Integration Network in Depression-1 study, consisting of 180 patients with MDD treated for eight weeks with escitalopram followed by eight weeks with escitalopram alone or augmented with aripiprazole was analyzed. Association between response Montgomery-Asberg Depression Rating Scale (MADRS; score reduction≥50%) or remission (MADRS score≤10) at weeks 8 and 16 and single nucleotide polymorphisms (SNPs), methylation, and mRNA levels of 33 endocannabinoid markers were examined. A standard genome-wide association studies protocol was used for identifying SNPs, and logistic regression was used to assess methylation and mRNA levels. RESULTS: Lower methylation of CpG islands of the diacylglycerol lipase alpha gene (DAGLA) was associated with non-remission at week 16 (DAGLA; OR=0.337, p<0.003, q=0.050). Methylation of DAGLA was correlated with improvement in Clinical Global Impression (p=0.026), Quick Inventory of Depressive Symptomatology (p=0.010), and Snaith-Hamilton Pleasure scales (p=0.028). We did not find any association between SNPs or mRNA levels and treatment outcomes. DISCUSSION: Methylation of DAGLA is a promising candidate as a marker of treatment outcomes for MDD and needs to be explored further.

"One Degree of Separation": A Mixed-Methods Evaluation of Canadian Mental Health Care User and Provider Experiences With Remote Care During COVID-19.

OBJECTIVES: The COVID-19 pandemic has contributed to a shift from in-person to remote mental health care. While remote care methods have long existed, their widespread use is unprecedented. There is little research about mental health care user and provider experiences with this transition, and no published studies to date have compared satisfaction between these groups. METHODS: Canadian mental health care users (n = 332) and providers (n = 107) completed an online self-report survey from October 2020 to February 2021 hosted by the Canadian Biomarker Integration Network in Depression. Using a mixed-methods approach, participants were asked about their use of remote care, including satisfaction, barriers to use, helpful and unhelpful factors, and suggestions for improvement. RESULTS: Overall, 59% to 63% of health care users and 59% of health care providers were satisfied with remote care. Users reported the greatest satisfaction with the convenience of remote care, while providers were most satisfied with the speed of provision of care; all groups were least satisfied with therapeutic rapport. Health care providers were less satisfied with the user-friendliness of remote care (P < 0.001) than users, while health care users were less satisfied than providers with continuity of care (P < 0.001). The use of a video-based platform was associated with remote care satisfaction among health care users (P < 0.02), and qualitative responses support the importance of visual cues in maintaining therapeutic rapport remotely. The majority of users (55%) and providers (87%) reported a likelihood of using remote care after the pandemic. CONCLUSIONS: Remote mental health care is generally accepted by both users and providers, and the majority would consider using remote care following the pandemic. Suggestions for improvement include greater use of video, increased attention to body language and eye contact, consistency with in-person care, as well as increased provider training and administrative support.

Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis.

BACKGROUND: Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a given person. We aim to examine the performance of machine learning methods in delivering replicable predictions of treatment outcomes. METHODS: Of 7732 non-duplicate records identified through literature search, we retained 59 eligible reports and extracted data on sample, treatment, predictors, machine learning method, and treatment outcome prediction. A minimum sample size of 100 and an adequate validation method were used to identify adequate-quality studies. The effects of study features on prediction accuracy were tested with mixed-effects models. Fifty-four of the studies provided accuracy estimates or other estimates that allowed calculation of balanced accuracy of predicting outcomes of treatment. RESULTS: Eight adequate-quality studies reported a mean accuracy of 0.63 [95% confidence interval (CI) 0.56-0.71], which was significantly lower than a mean accuracy of 0.75 (95% CI 0.72-0.78) in the other 46 studies. Among the adequate-quality studies, accuracies were higher when predicting treatment resistance (0.69) and lower when predicting remission (0.60) or response (0.56). The choice of machine learning method, feature selection, and the ratio of features to individuals were not associated with reported accuracy. CONCLUSIONS: The negative relationship between study quality and prediction accuracy, combined with a lack of independent replication, invites caution when evaluating the potential of machine learning applications for personalizing the treatment of depression.

Guideline No. 422c: Menopause: Mood, Sleep, and Cognition.

OBJECTIVE: Provide strategies for improving the care of perimenopausal and postmenopausal women based on the most recent published evidence. TARGET POPULATION: Perimenopausal and postmenopausal women. BENEFITS, HARMS, AND COSTS: Target population will benefit from the most recent published scientific evidence provided via the information from their health care provider. No harms or costs are involved with this information since women will have the opportunity to choose among the different therapeutic options for the management of the symptoms and morbidities associated with menopause, including the option to choose no treatment. EVIDENCE: Databases consulted were PubMed, MEDLINE, and the Cochrane Library for the years 2002-2020, and MeSH search terms were specific for each topic developed through the 7 chapters. VALIDATION METHODS: The authors rated the quality of evidence and strength of recommendations using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. See online Appendix A (Tables A1 for definitions and A2 for interpretations of strong and weak recommendations). INTENDED AUDIENCE: physicians, including gynaecologists, obstetricians, family physicians, internists, emergency medicine specialists; nurses, including registered nurses and nurse practitioners; pharmacists; medical trainees, including medical students, residents, fellows; and other providers of health care for the target population. SUMMARY STATEMENTS: RECOMMENDATIONS.

Directive clinique n° 422c : Ménopause : Humeur, sommeil et cognition.

OBJECTIF: Proposer des stratégies fondées sur les plus récentes données publiées pour améliorer les soins aux femmes ménopausées ou en périménopause. POPULATION CIBLE: Les femmes ménopausées ou en périménopause. BéNéFICES, RISQUES ET COûTS: La population cible bénéficiera des plus récentes données scientifiques publiées communiquées par leurs fournisseurs de soins de santé. Aucun coût ni préjudice ne sont associés à cette information, car les femmes seront libres de choisir parmi les différentes options thérapeutiques, y compris le statu quo, pour la prise en charge des symptômes et morbidités associés à la ménopause. DONNéES PROBANTES: Les auteurs ont interrogé les bases de données PubMed, MEDLINE et Cochrane Library pour extraire des articles publiés entre 2002 et 2020 en utilisant des termes MeSH spécifiques à chacun des sujets abordés dans les 7 chapitres. MéTHODES DE VALIDATION: Les auteurs ont évalué la qualité des données probantes et la force des recommandations en utilisant l'approche d'évaluation, de développement et d'évaluation (GRADE). Voir l'annexe A en ligne (tableau A1 pour les définitions et tableau A2 pour l'interprétation des recommandations fortes et conditionnelles [faibles]). PROFESSIONNELS CONCERNéS: gynécologues, obstétriciens, médecins de famille, internistes, urgentologues, infirmières (autorisées et praticiennes), pharmaciens, stagiaires (étudiants en médecine, résidents, moniteurs cliniques) et autres fournisseurs de soins de santé pour la population cible. DÉCLARATIONS SOMMAIRES: RECOMMANDATIONS.

The Effects of Probiotics on Symptoms of Depression: Protocol for a Double-Blind Randomized Placebo-Controlled Trial.

BACKGROUND: A growing body of evidence has linked mental health outcomes to the gut microbiome. This has led to the investigation of the GI tract as a target for novel treatments and interventions for depression, including probiotic supplementation. Our recent pilot study provided the first evidence of probiotics improving symptoms of depression in treatment-naive depressed patients. To further support and expand upon this evidence, data from the pilot study were used to plan a 16-week, double-blind, randomized, placebo-controlled trial to assess the effects of probiotics on depression. Here, we report the protocol for this trial. METHODS: Participants diagnosed with depression will orally consume a probiotic supplement containing Lactobacillus helveticus and Bifidobacterium longum or placebo once daily. Participants will undergo assessments measuring clinical outcomes using a battery of validated clinical scales and questionnaires. Sleep architecture and quality will be measured using polysomnography. Neuroimaging data will be collected using magnetic resonance imaging to examine functional and structural neurophysiological changes. Molecular data will be collected from blood, stool, and urine samples to examine cytokine levels and explore potential genes and proteins that may predict outcomes in depression. RESULTS: We expect results to replicate and expand on our pilot data demonstrating that probiotics may be effective in alleviating symptoms of depression, and to find biomarkers that will predict these outcomes. CONCLUSIONS: The findings from this study will add to the growing body of research in this emerging field, which eventually may provide evidence for probiotics having a role in alleviating symptoms of depression.

Predictors of functional response and remission with desvenlafaxine 50 mg and 100 mg: a pooled analysis of randomized, placebo-controlled studies in patients with major depressive disorder.

OBJECTIVE: The value of early functional improvement at week 2 for predicting subsequent functional outcomes at week 8 was assessed in a pooled analysis of patients with major depressive disorder (MDD) treated with desvenlafaxine (50 or 100 mg/d) or placebo. METHODS: Data were pooled from eight double-blind, placebo-controlled studies of desvenlafaxine 50 mg/d or 100 mg/d for the treatment of MDD. Optimal week-2 improvement thresholds in Sheehan Disability Scale (SDS) score, which best predicted week-8 treatment success, were determined using receiver operating characteristic (ROC) analysis. Four definitions of treatment success were established: (1) functional response, (2) functional/depression response, (3) functional remission, and (4) functional/depression remission. Odds ratios (ORs) of early improvement for prediction (based on thresholds determined in the ROC analysis) of week-8 treatment success were computed using logistic regression models. RESULTS: Functional early improvement thresholds of 17%-32% were predictive of week-8 treatment success across treatment groups and definitions of treatment success. Optimal thresholds were higher for more stringent definitions. Negative predictive value exceeded positive predictive value, indicating that failure to achieve early functional improvement was more informative about later treatment success than was the achievement of early functional improvement. Early change in SDS was a highly significant predictor of functional response/remission (ORs, 4.981-8.737; all p < 0.0001); the interaction between treatment and early functional improvement was not significant. CONCLUSION: Early improvement in SDS total score was predictive of functional outcomes for patients treated with desvenlafaxine 50 mg, desvenlafaxine 100 mg, or placebo.

The Canadian Biomarker Integration Network in Depression (CAN-BIND): magnetic resonance imaging protocols

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging ­ alone or in combination with other variables ­ can predict the outcomes of various treatment modalities.

Categorical improvement in functional impairment in depressed patients treated with desvenlafaxine.

OBJECTIVE: This post-hoc pooled analysis evaluated categorical change in functional impairment in patients with major depressive disorder (MDD) treated with desvenlafaxine versus placebo and examined whether early improvement in functioning predicted functional outcomes at study endpoint. METHODS: Data were pooled from eight randomized, double-blind, placebo-controlled studies of desvenlafaxine for the treatment of MDD, including adults who were randomly assigned to receive desvenlafaxine 50 or 100 mg/d or placebo (N=3,384). Shift tables were generated for categorical changes in functional impairment from baseline based on Sheehan Disability Scale (SDS) subscale scores. The categories were none/mild (0-3), moderate (4-6), and marked/extreme (7-10). Treatment comparisons for prespecified shifts of interest and predictive value of week 2 or 4 improvement in SDS subscale scores for functional outcome at week 8 were assessed using logistic regression. RESULTS: Greater proportions of patients receiving desvenlafaxine 50 and 100 mg achieved improvement from baseline to week 8 for each prespecified shift endpoint versus placebo (all p ≤ 0.02). Early improvement in SDS subscale scores was a statistically significant predictor of functional outcome at week 8, both overall and for each treatment group (all p<0.0001). CONCLUSIONS: Treatment with desvenlafaxine 50 or 100 mg/d led to significantly greater categorical improvement in functional impairment versus placebo, and improvement in SDS subscale scores significantly predicted functional outcome. Monitoring patient progress early in the course of antidepressant treatment using a functional assessment such as the SDS may help clinicians determine whether or not treatment adjustments are needed.

Association of functioning and quality of life with objective and subjective measures of sleep and biological rhythms in major depressive and bipolar disorder.

OBJECTIVE: Disruptions in biological rhythms and sleep are a core aspect of mood disorders, with sleep and rhythm changes frequently occurring prior to and during mood episodes. Wrist-worn actigraphs are increasingly utilized to measure ambulatory activity rhythm and sleep patterns. METHODS: A comprehensive study using subjective and objective measures of sleep and biological rhythms was conducted in 111 participants (40 healthy volunteers [HC], 38 with major depressive disorder [MDD] and 33 with bipolar disorder [BD]). Participants completed 15-day actigraphy and first-morning urine samples to measure 6-sulfatoxymelatonin levels. Sleep and biological rhythm questionnaires were administered: Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN), Munich Chronotype Questionnaire (MCTQ), Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). Actigraph data were analyzed for sleep and daily activity rhythms, light exposure and likelihood of transitioning between rest and activity states. RESULTS: Mood groups had worse subjective sleep quality (PSQI) and biological rhythm disruption (BRIAN) and higher objective mean nighttime activity than controls. Participants with BD had longer total sleep time, higher circadian quotient and lower 6-sulfatoxymelatonin levels than HC group. The MDD group had longer sleep onset latency and higher daytime probability of transitioning from rest to activity than HCs. Mood groups displayed later mean timing of light exposure. Multiple linear regression analysis with BRIAN scores, circadian quotient, mean nighttime activity during rest and daytime probability of transitioning from activity to rest explained 43% of variance in quality-of-life scores. BRIAN scores, total sleep time and probability of transitioning from activity to rest explained 52% of variance in functioning (all p < 0.05). CONCLUSIONS: Disruption in biological rhythms is associated with poorer functioning and quality of life in bipolar and MDD. Investigating biological rhythms and sleep using actigraphy variables, urinary 6-sulfatoxymelatonin and subjective measures provide evidence of widespread sleep and circadian system disruptions in mood disorders.

A longitudinal study of neurotrophic, oxidative, and inflammatory markers in first-onset depression in midlife women.

Prospective studies have shown during the years preceding and following menopause, also known as "menopause transition", that midlife women are at higher risk for developing first-onset major depressive disorder (MDD). The biological factors associated with risk and resilience in this population are, however, largely unknown. Considering the growing body of evidence suggesting that inflammation, oxidative stress, and brain-derived neurotrophic factor (BDNF) are associated with the pathophysiology of MDD, we investigated serum levels of protein carbonyl, lipid peroxidation (thiobarbituric acid reactive substances-TBARS), thiol group content, BDNF, 3-nitrotyrosine, and heat shock protein 70 (HSP70) in a longitudinal cohort of first-onset MDD. One hundred and forty-eight women from the Harvard Study of Moods and Cycles, a prospective study of midlife women monitored throughout the transition to menopause, were studied. Within- and between-groups analyses of these peripheral markers were conducted in 37 women who developed and 111 women that did not develop MDD during the 3-year follow-up period. In women who developed MDD, HSP70 and 3-nitrotyrosine were elevated at baseline, whereas TBARS were elevated 6 months prior to development of MDD, as compared to those who did not develop MDD. Within-group analyses showed that HSP70, 3-nitrotyrosine, and BDNF decreased over time, whereas protein carbonyl was elevated only at 12 months prior to development of MDD. In women who did not develop MDD, HSP70 and thiol decreased over time. The development of MDD in midlife women may be associated with a systemic cascade of pro-oxidative and pro-inflammatory events including increased HSP70, 3-nitrotyrosine, protein carbonyl, and lipid peroxidation and decreased BDNF.

Premenstrual Dysphoric Disorder: Contemporary Diagnosis and Management.

Most ovulatory women experience premenstrual symptoms (premenstrual syndrome, molimina) which indicate impending menstruation and are of little clinical relevance because they do not affect quality of life. A few women, however, experience significant physical and/or psychological symptoms before menstruation that, if left untreated, would result in deterioration in functioning and relationships. The precise etiology remains elusive, although new theories are gaining support in pre-clinical and early clinical trials. Refined diagnostic criteria allow better discrimination of this condition from other psychiatric diagnoses and the selection of symptom appropriate therapies that afford relief for most women. Pharmacotherapies (particularly selective serotonin reuptake inhibitors and SNRIs) represent the first-line treatment for premenstrual dysphoric disorder and severe, mood-related premenstrual syndrome. Continuous combined oral contraceptives have limited evidence for usefulness in premenstrual dysphoric disorder, whereas medical ovarian suppression is often recommended for patients who fail to respond or cannot tolerate first-line treatments (e.g., selective serotonin reuptake inhibitors). The use of cognitive behavioural therapies is promising, but it remains limited by sparse data and restricted access to trained professionals. A proper diagnosis (particularly the distinction from other underlying psychiatric conditions) is crucial for the implementation of effective therapy and alleviation of this impairing condition.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

BACKGROUND: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. METHODS: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. DISCUSSION: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.

Working memory in pregnant women: Relation to estrogen and antepartum depression.

This article is part of a Special Issue "Estradiol and cognition". Subjective changes in concentration and memory are commonly reported by women during the second or third trimesters of pregnancy, but the nature of the problem is poorly understood. We hypothesized that these self-reports might reflect difficulties in working memory (WM). It was further hypothesized that antepartum depression (depression arising during pregnancy) may play an etiological role, either on its own or due to secondary changes in endocrine function or sleep. Using WM tasks that emphasized executive control processes mediated by the prefrontal cortex (PFC) we compared pregnant women tested at 34-36 weeks of gestation (n = 28) with age- and education-matched non-pregnant controls (n = 26). All pregnant women were screened for depression. Evidence of a WM disturbance was found, and was evident only among pregnant women showing depressive symptoms. In contrast, pregnant women who were not depressed showed WM performance that equalled, or even significantly exceeded, non-pregnant controls. No significant differences were observed on control tests of other cognitive functions. Multiple regression revealed that serum estradiol concentrations, along with severity of depressive affect but not sleep disruption, significantly predicted variation in the WM scores. In agreement with studies of estradiol and WM in other contexts, higher estradiol was associated with better WM, while higher levels of depressive symptoms predicted poorer WM. We conclude that memory disturbance during gestation might not be as widespread as commonly believed, but can be seen among women experiencing antepartum depression. The high level of WM performance found in healthy, non-depressed, pregnant women is discussed from an adaptationist perspective.