Lifetime use of MDMA/ecstasy and psilocybin is associated with reduced odds of major depressive episodes

Background: Depression is a major mental health issue worldwide, with high rates of chronicity and non-recovery associated with the condition. Existing treatments such as antidepressant medication and psychological treatments have modest effectiveness, suggesting the need for alternative interventions. Aim: The aim of this study was to examine the relationships between MDMA (3,4-methylenedioxymethamphetamine)/ecstasy and psilocybin use and major depressive episodes (MDEs). Methods: This observational study used data from a large ( N = 213,437) nationally representative sample of US adults to test the association of lifetime use of MDMA/ecstasy, psilocybin and other classic psychedelics (lysergic acid diethylamide (LSD), peyote, mescaline), other illegal substances (e.g. cocaine, phencyclidine (PCP)), and legal/medicinal substances of misuse (e.g. pain relievers, tranquilizers) with lifetime, past year, and past year severe MDEs. Results: Results revealed that lifetime MDMA/ecstasy use was associated with significantly lowered odds of a lifetime MDE (adjusted odds ratio (aOR) = 0.84; p < 0.001), past year MDE (aOR = 0.84; p < 0.001), and past year severe MDE (aOR = 0.82; p < 0.001). Psilocybin was associated with significantly lowered odds of a past year MDE (aOR = 0.90; p < 0.05) and past year severe MDE (aOR = 0.87; p < 0.05). All other substances either shared no relationship with a MDE or conferred increased odds of an MDE. Conclusions: These results suggest that MDMA/ecstasy and psilocybin use is associated with lower risk of depression. Experimental studies are needed to test whether there is a causal association between use of these compounds and the alleviation of depressive symptoms.

Prediction of suicide attempts in a prospective cohort study with a nationally representative sample of the US population

Psychological Medicine ◽

10.1017/s0033291720004997 ◽

2021 ◽

pp. 1-12

Author(s):

Cristiane dos Santos Machado ◽

Pedro L. Ballester ◽

Bo Cao ◽

Benson Mwangi ◽

Marco Antonio Caldieraro ◽

...

Keyword(s):

Borderline Personality Disorder ◽

Personality Disorder ◽

Suicide Attempt ◽

Representative Sample ◽

Borderline Personality ◽

Predictor Variables ◽

Major Depressive ◽

Nationally Representative ◽

Abstract Background There is still little knowledge of objective suicide risk stratification. Methods This study aims to develop models using machine-learning approaches to predict suicide attempt (1) among survey participants in a nationally representative sample and (2) among participants with lifetime major depressive episodes. We used a cohort called the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) that was conducted in two waves and included a nationally representative sample of the adult population in the United States. Wave 1 involved 43 093 respondents and wave 2 involved 34 653 completed face-to-face reinterviews with wave 1 participants. Predictor variables included clinical, stressful life events, and sociodemographic variables from wave 1; outcome included suicide attempt between wave 1 and wave 2. Results The model built with elastic net regularization distinguished individuals who had attempted suicide from those who had not with an area under the ROC curve (AUC) of 0.89, balanced accuracy 81.86%, specificity 89.22%, and sensitivity 74.51% for the general population. For participants with lifetime major depressive episodes, AUC was 0.89, balanced accuracy 81.64%, specificity 85.86%, and sensitivity 77.42%. The most important predictor variables were a diagnosis of borderline personality disorder, post-traumatic stress disorder, and being of Asian descent for the model in all participants; and previous suicide attempt, borderline personality disorder, and overnight stay in hospital because of depressive symptoms for the model in participants with lifetime major depressive episodes. Random forest and artificial neural networks had similar performance. Conclusions Risk for suicide attempt can be estimated with high accuracy.

Major Depressive Episodes and Employment Earnings Trajectories over the Following Decade among Working-aged Canadian Men and Women

Journal of Affective Disorders ◽

10.1016/j.jad.2021.02.019 ◽

2021 ◽

Vol 285 ◽

pp. 37-46

Author(s):

Kathleen G. Dobson ◽

Simone N. Vigod ◽

Cameron Mustard ◽

Peter M. Smith

Keyword(s):

Major Depressive ◽

Men And Women ◽

Diagnosing and Treating Major Depressive Episodes that Lie Along the Mood Disorders Spectrum: Focus on Depression with Mixed Features

CNS Spectrums ◽

10.1017/s1092852921000262 ◽

2021 ◽

pp. 1-25

Author(s):

Susan L. McElroy ◽

Anna I. Guerdjikova ◽

Francisco Romo-Nava

Keyword(s):

Mood Disorders ◽

Major Depressive ◽

Mixed Features ◽

Efficacy and tolerability of reboxetine compared with imipramine in a double-blind study in patients suffering from major depressive episodes

European Neuropsychopharmacology ◽

10.1016/s0924-977x(97)00418-5 ◽

1997 ◽

Vol 7 (1) ◽

pp. S37-S47 ◽

Cited By ~ 72

Author(s):

H. Berzewski ◽

M. Van Moffaert ◽

C.A. Gagiano

Keyword(s):

Blind Study ◽

Double Blind Study ◽

Major Depressive ◽

Double Blind ◽

What is the role of conventional antidepressants in the treatment of major depressive episodes with Mixed Features Specifier?

CNS Spectrums ◽

10.1017/s1092852916000493 ◽

2016 ◽

Vol 22 (2) ◽

pp. 120-125 ◽

Cited By ~ 7

Author(s):

Gianni L. Faedda ◽

Ciro Marangoni

Keyword(s):

Clinical Trials ◽

Unipolar Depression ◽

Preliminary Evidence ◽

Major Depressive ◽

Pharmacological Management ◽

Diagnostic And Statistical Manual ◽

Mixed Features ◽

Effective Use ◽

The newly introduced Mixed Features Specifier of Major Depressive Episode and Disorder (MDE/MDD) is especially challenging in terms of pharmacological management. Prior to the publication of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, the symptoms of the mixed features specifier were intradepressive hypomanic symptoms, always and only associated with bipolar disorder (BD).Intradepressive hypomanic symptoms, mostly referred to as depressive mixed states (DMX), have been poorly characterized, and their treatment offers significant challenges. To understand the diagnostic context of DMX, we trace the nosological changes and collocation of intradepressive hypomanic symptoms, and examine diagnostic and prognostic implications of such mixed features.One of the reasons so little is known about the treatment of DMX is that depressed patients with rapid cycling, substance abuse disorder, and suicidal ideation/attempts are routinely excluded from clinical trials of antidepressants. The exclusion of DMX patients from clinical trials has prevented an assessment of the safety and tolerability of short- and long-term use of antidepressants. Therefore, the generalization of data obtained in clinical trials for unipolar depression to patients with intradepressive hypomanic features is inappropriate and methodologically flawed.A selective review of the literature shows that antidepressants alone have limited efficacy in DMX, but they have the potential to induce, maintain, or worsen mixed features during depressive episodes in BD. On the other hand, preliminary evidence supports the effective use of some atypical antipsychotics in the treatment of DMX.