Early clinical predictors and correlates of long-term morbidity in bipolar disorder

OBJECTIVES: Identifying factors predictive of long-term morbidity should improve clinical planning limiting disability and mortality associated with bipolar disorder (BD). METHODS: We analyzed factors associated with total, depressive and mania-related long-term morbidity and their ratio D/M, as %-time ill between a first-lifetime major affective episode and last follow-up of 207 BD subjects. Bivariate comparisons were followed by multivariable linear regression modeling. RESULTS: Total % of months ill during follow-up was greater in 96 BD-II (40.2%) than 111 BD-I subjects (28.4%; P=0.001). Time in depression averaged 26.1% in BD-II and 14.3% in BD-I, whereas mania-related morbidity was similar in both, averaging 13.9%. Their ratio D/M was 3.7-fold greater in BD-II than BD-I (5.74 vs. 1.96; P<0.0001). Predictive factors independently associated with total %-time ill were: [a] BD-II diagnosis, [b] longer prodrome from antecedents to first affective episode, and [c] any psychiatric comorbidity. Associated with %-time depressed were: [a] BD-II diagnosis, [b] any antecedent psychiatric syndrome, [c] psychiatric comorbidity, and [d] agitated/psychotic depressive first affective episode. Associated with %-time in mania-like illness were: [a] fewer years ill and [b] (hypo)manic first affective episode. The long-term D/M morbidity ratio was associated with: [a] anxious temperament, [b] depressive first episode, and [c] BD-II diagnosis. CONCLUSIONS: Long-term depressive greatly exceeded mania-like morbidity in BD patients. BD-II subjects spent 42% more time ill overall, with a 3.7-times greater D/M morbidity ratio, than BD-I. More time depressed was predicted by agitated/psychotic initial depressive episodes, psychiatric comorbidity, and BD-II diagnosis. Longer prodrome and any antecedent psychiatric syndrome were respectively associated with total and depressive morbidity

Inter and intra-hemispheric structural imaging markers predict depression relapse after electroconvulsive therapy: a multisite study.

Relapse of depression following treatment is high. Biomarkers predictive of an individual's relapse risk could provide earlier opportunities for prevention. Since electroconvulsive therapy (ECT) elicits robust and rapidly acting antidepressant effects, but has a &gt;50% relapse rate, ECT presents a valuable model for determining predictors of relapse-risk. Although previous studies have associated ECT-induced changes in brain morphometry with clinical response, longer-term outcomes have not been addressed. Using structural imaging data from 42 ECT-responsive patients obtained prior to and directly following an ECT treatment index series at two independent sites (UCLA: n = 17, age = 45.41±12.34 years; UNM: n = 25; age = 65.00±8.44), here we test relapse prediction within 6-months post-ECT. Random forests were used to predict subsequent relapse using singular and ratios of intra and inter-hemispheric structural imaging measures and clinical variables from pre-, post-, and pre-to-post ECT. Relapse risk was determined as a function of feature variation. Relapse was well-predicted both within site and when cohorts were pooled where top-performing models yielded balanced accuracies of 71-78%. Top predictors included cingulate isthmus asymmetry, pallidal asymmetry, the ratio of the paracentral to precentral cortical thickness and the ratio of lateral occipital to pericalcarine cortical thickness. Pooling cohorts and predicting relapse from post-treatment measures provided the best classification performances. However, classifiers trained on each age-disparate cohort were less informative for prediction in the held-out cohort. Post-treatment structural neuroimaging measures and the ratios of connected regions commonly implicated in depression pathophysiology are informative of relapse risk. Structural imaging measures may have utility for devising more personalized preventative medicine approaches

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies

Can a One-Item Mood Scale Do the Trick? Predicting Relapse over 5.5-Years in Recurrent Depression

To examine whether a simple Visual Analogue Mood Scale (VAMS) is able to predict time to relapse over 5.5-years.187 remitted recurrently depressed out-patients were interviewed using the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) and the 17-item Hamilton Depression rating scale (HAM-D) to verify remission status (HAM-D <10). All patients rated their current mood with the help of a Visual Analogue Mood Scale (VAMS) at baseline and at a follow-up assessment three months later. Relapse over 5.5-years was assessed by the SCID-I. Cox regression revealed that both the VAMS at baseline and three months later significantly predicted time to relapse over 5.5-years. Baseline VAMS even predicted time to relapse when the number of previous depressive episodes and HAM-D scores were controlled for. The baseline VAMS explained 6.3% of variance in time to relapse, comparable to the HAM-D interview.Sad mood after remission appears to play a pivotal role in the course of depression. Since a simple VAMS predicted time to relapse, the VAMS might be an easy and time-effective way to monitor mood and risk of early relapse, and offers possibilities for daily monitoring using e-mail and SMS.International Standard Randomized Controlled Trial Register Identifier: ISRCTN68246470

Physical activity in depressed patients: a self-determination approach

The aim of this Thesis was threefold: (i) to contribute to the clarification of the issue of causality between physical exercise and depressionamelioration in adult patients with major depressive disorder (18-65years), (ii) to investigate if self-determination theory (SDT) could revealpredictive properties towards depression relief and physical activity participation in adult outpatients (18-65years) with major depressive disorder, and (iii) to examine whether objectively measured habitual physical activity is associated with predictive effects on the improvement of depression in adult outpatients (18-65years) with major depressive disorder. The first study wasa critical review provided extensive interpretation of the literature referred to exercise for adult patients with major depressive disorder. Based on this study, physical exercise was associated with an improvement in depression, butdepressed patients participating in exercise on prescription schemes documented the highest dropout rates among all patients. Relevant recommendations based on SDT were provided in order to increase treatment effectiveness and to decrease dropout rates. In light of the inconclusive views seen in literature concerning the causal antidepressant effects of exercise, a systematic review was conducted to examineif exercise brings about clinically signficant antidepressant effects on adult patients with major depressive disorder. Based on normative comparisons, exercise led to an improvement in depression that was equivalent to general population. The most effective dose-response relationship was moderate intensity exercise ofthree times per week for both short- or longer-term (3, 8, or 9 weeks). A subsequent systematic review employed practical significance comparisons (meta-analytic techniques) toexploreif the aerobic modality of exercise in particular, compares favourably to routine practice treatment conditions. This meta-analysisfavoured the antidepressant effects of aerobic exerciseattributable to the large and significant overall effect-size and thelow heterogeneity levels. Also, no publication bias was recorded. Coding on participant, intervention, comparison, outcome and design characteristics did not change the result. The most-effective dose-response relationship referred to aerobic exercise of three times per week at moderate intensity for a short- (up to six weeks) or longer period (eight to twelve weeks). Following the supportive evidence for the causal antidepressant effects of exercise, the fourth study of this Thesis investigated the predictive contribution of SDT to depression relief and to physical activity participationin order to provide a robust rationale that could tackle the sedentary lifestyle of depressed patients and the disappointing dropout rates from exercise on prescription schemes. Based on a sample of 206 patients, this study revealed that need satisfaction (competence, autonomy and relatedness) is capable of predicting depression relief and physical activity participationincluding the corresponding metabolic equivalents by its own right as it overcome and neutralised the positive mediating effects of autonomous- (internal/identified)behavioural regulators(e.g., exercise for pleasure or for personal importance). Depression, however, illustrated an adverse toxic effect on need satisfaction. Controlling forms-(external/introjected)of behavioural regulators(e.g., exercise for external rewards or self-blame) typically comprising the iatrogenic physical activity/exerciseon prescription or promotion model showed no mediating effect.Finally, given that the selfadministrative health behavioural pattern of habitual physical activity may represent the frontline treatment tool against depression, the fifth study of this Thesisrecruited 19 depressed patients to explore whether objective habitual physical activity levels measured by means of a 7-day use of triaxial accelerometer devices are associated withantidepressant predictive properties. The study recordedan average of 32 minutes of moderate to vigorous habitual physical activity per day. This amount of habitual physical activitypredicted depression ameliorationand explained 23% of the variance of depression. It should be noted that only 40 seconds of the 32 minutes represented the vigorous component.Collectively, this Thesis has found that physical exercise shows causal antidepressant effects. Also, satisfying the SDT dendrites of psychological needs for exercise may lead to depression relief as well as to participation in physical activity. Finally, the objectively measured level of moderate to vigorous habitual physical activity for 32 minutes per day is related with depression amelioration.Studies 4 and 5 need to be replicated with a longitutinal design in order to draw causal conclusions.Also, the implementation of pragmatic randomized controlled trials is essential in order to translate into real life settings the clinical evidence referred to the antidepresiveness of physical activity/exercise and the predictive power of SDT towards physical activity participation

Chemokines in depression in health and in inflammatory illness: a systematic review and meta-analysis

Inflammatory illness is associated with depression. Preclinical work has shown that chemokines are linked with peripheral–central crosstalk and may be important in mediating depressive behaviours. We sought to establish what evidence exists that differences in blood or cerebrospinal fluid chemokine concentration discriminate between individuals with depression and those without. Following PRISMA guidelines, we systematically searched Embase, PsycINFO and Medline databases. We included participants with physical illness for subgroup analysis, and excluded participants with comorbid psychiatric diagnoses. Seventy-three studies met the inclusion criteria for the meta-analysis. Individuals with depression had higher levels of blood CXCL4 and CXCL7 and lower levels of blood CCL4. Sensitivity analysis of studies with only physically healthy participants identified higher blood levels of CCL2, CCL3, CCL11, CXCL7 and CXCL8 and lower blood levels of CCL4. All other chemokines examined did not reveal significant differences (blood CCL5, CCL7, CXCL9, CXCL10 and cerebrospinal fluid CXCL8 and CXCL10). Analysis of the clinical utility of the effect size of plasma CXCL8 in healthy individuals found a negative predictive value 93.5%, given the population prevalence of depression of 10%. Overall, our meta-analysis finds evidence linking abnormalities of blood chemokines with depression in humans. Furthermore, we have demonstrated the possibility of classifying individuals with depression based on their inflammatory biomarker profile. Future research should explore putative mechanisms underlying this association, attempt to replicate existing findings in larger populations and aim to develop new diagnostic and therapeutic strategies

Interaction between the MTHFR C677T polymorphism and traumatic childhood events predicts depression

Childhood trauma is associated with the onset and recurrence of major depressive disorder (MDD). The thermolabile T variant of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism (rs1801133) is associated with a limited (oxidative) stress defense. Therefore, C677T MTHFR could be a potential predictor for depressive symptomatology and MDD recurrence in the context of traumatic stress during early life. We investigated the interaction between the C677T MTHFR variant and exposure to traumatic childhood events (TCEs) on MDD recurrence during a 5.5-year follow-up in a discovery sample of 124 patients with recurrent MDD and, in an independent replication sample, on depressive syniptomatology in 665 healthy individuals from the general population. In the discovery sample, Cox regression analysis revealed a significant interaction between MTHFR genotype and TCEs on MOD recurrence (P = 0.017). Over the 5.5-year follow-up period, median time to recurrence was 191 days for T-allele carrying patients who experienced TCEs (T + and TCE +); 461 days for T - and TCE + patients; 773 days for T + and TCE - patients and 866 days for T - and TCE - patients. In the replication sample, a significant interaction was present between the MTHFR genotype and TCEs on depressive symptomatology (P = 0.002). Our results show that the effects of TCEs on the prospectively assessed recurrence of MOD and self-reported depressive symptoms in the general population depend on the MTHFR genotype. In conclusion, T-allele carriers may be at an increased risk for depressive symptoms or MOD recurrence after exposure to childhood trauma

Hidden scars in depression? Implicit and explicit self-associations following recurrent depressive episodes

To help explain the recurrent nature of major depressive disorder, we tested the hypothesis that depressive episodes and/or the duration of depressive symptoms may give rise to persistent dysfunctional implicit and/or more explicit self-associations, which in turn may place people at risk for the recurrence of symptoms. We therefore examined, in the context of the Netherlands Study of Depression and Anxiety, whether the strength of self-depressed associations at baseline was related to the number of past episodes (retrospective analysis; n = 666), and whether the duration of symptoms between baseline and follow-up predicted self-depressed associations at 2-year follow-up (prospective analysis; n = 726). The lifetime Composite International Diagnostic Interviews and Life Chart Interview were used to index the number of depressive episodes; the Implicit Association Test and its explicit equivalent were used to index self-associations. Consistent with the hypothesis that self-depressed associations strengthen following prolonged activation of negative self-associations during depressive episodes, individuals' implicit and explicit self-depressed associations correlated positively both with the number of prior depressive episodes at baseline and with the duration of depressive symptoms between baseline and 2-year follow-up. There was evidence that these relationships held, particularly in the prospective study, even when controlling for neuroticism and current depressive symptoms, whereas the retrospective relationship between number of episodes and implicit self-associations fell just short of significance