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The Critical Relationship Between Anxiety and Depression

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Treatment for Anxiety and Comorbid Depressive Disorders: Transdiagnostic Cognitive-Behavioral Strategies

Affiliations.

1 Department of Psychiatry, Massachusetts General Hospital.
2 Harvard Medical School.
3 Department of Psychology, Harvard University.
PMID: 34433988
PMCID: PMC8382208
DOI: 10.3928/00485713-20210414-01

Anxiety and depressive disorders are common psychiatric conditions with high rates of co-occurrence. Although traditional cognitive-behavioral therapy (CBT) protocols targeting individual anxiety and depressive disorder diagnoses have been shown to be effective, such "single-diagnosis" approaches pose challenges for providers who treat patients with multiple comorbidities and for large-scale dissemination of and training in evidence-based psychological treatments. To help meet this need, newer "transdiagnostic" CBT interventions targeting shared underlying features across anxiety, depressive, and related disorders have been developed in recent years. Here we provide a rationale for and description of the transdiagnostic CBT model, followed by an overview of key therapeutic strategies included in transdiagnostic CBT protocols for patients with anxiety disorders and comorbid depression. We conclude with a brief review of the empirical evidence in support of transdiagnostic CBT for individuals with anxiety and depressive disorders and identify directions for future research.

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DOI: 10.1186/s12888-024-05961-3
Corpus ID: 271941343

Impact of moderate-to-high-suicide-intent in major depressive disorder: a retrospective cohort study on patient characteristics and healthcare resource utilisation in England

Tom Denee , Cicely Kerr , +4 authors Fintan Larkin
Published in BMC Psychiatry 23 August 2024
Medicine, Psychology

23 References

Current treatments used in clinical practice for major depressive disorder and treatment resistant depression in england: a retrospective database study..

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Prevalence of suicidal ideation and planning in patients with major depressive disorder: A meta-analysis of observation studies.

Suicide rates among people with serious mental illness: a systematic review and meta-analysis, cost of depression in europe., global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the covid-19 pandemic, the economic burden of adults with major depressive disorder in the united states (2010 and 2018), prevalence and variability of current depressive disorder in 27 european countries: a population-based study, patient-reported outcomes in major depressive disorder with suicidal ideation: a real-world data analysis using patientslikeme platform, related papers.

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Introduction
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Article Information

a After completing the prescreening questionnaire, people were deemed ineligible if they were currently using antidepressant medication (n = 157); lived outside reasonable commuting distance (n = 161); did not meet criteria for the magnetic resonance imaging scans (n = 99); had a first- or second-degree relative with a diagnosis of schizophrenia spectrum, bipolar I or II, or other psychotic disorder ( = 77); had a recent history of substance use disorder (n = 50); opted out of in-person screening (n = 38); were not in a current depressive episode (n = 37); were more than 25% beyond the upper or lower range of recommended body weight (n = 32); had a medically significant suicide attempt (n = 30); had lifetime hallucinogen use that exceeded the exclusion threshold (n = 30); if major depressive disorder (MDD) was not primary psychiatric diagnosis (n = 18); if they had a medical exclusion (n = 11); had exclusionary use of nonserotonergic psychoactive medication (n = 11); or failed to respond to electroconvulsive therapy during current depressive episode (n = 4). Forty-five people were ineligible for other reasons.

b People were deemed ineligible during in-person screening if they had a psychiatric condition judged to be incompatible with establishment of rapport or safe exposure to psilocybin (n = 17); did not have confirmed DSM-5 diagnosis of MDD (n = 7); had a recent history of moderate to severe substance use disorder (n = 5); were at high risk for suicidality (n = 3); disagreed with study procedures (n = 3); had a baseline GRID Hamilton Depression Rating Scale score lower than the eligibility threshold of 17 (n = 2); had cardiovascular conditions (n = 2); had lifetime hallucinogen use that exceeded the exclusion threshold (n = 2); were currently taking serotonergic medication (n = 1); or were more than 25% beyond the upper and lower range of recommended body weight (n = 1).

c Dropped out of the study due to anticipatory anxiety about the upcoming first psilocybin session.

d Dropped out of study due to sleep difficulties. Sleep difficulties were also reported at screening, and it was not clear whether sleep difficulties were exacerbated by the intervention.

e Participant showed a marked reduction in depression symptoms immediately following the first psilocybin session and chose not to proceed with the intervention.

GRID-HAMD indicates GRID Hamilton Depression Rating Scale.

Data points are presented as mean (SD). In the immediate treatment group (n = 13), weeks 5 and 8 correspond to weeks 1 and 4 after the psilocybin session 2. In the delayed treatment group (n = 11), weeks 5 and 8 are prepsilocybin assessments obtained during the delay period. Effect sizes (Cohen d with 95% CI) and P values reflect the results of a 2-sample t test between the 2 groups at week 5 (Cohen d = 2.5; 95% CI, 1.4-3.5; P < .001) and week 8 (Cohen d = 2.6; 95% CI, 1.5-3.7; P < .001).

The mean (SD) GRID-HAMD score was 22.8 (3.9) at baseline, 8.7 (7.6) at week 1, and 8.9 (7.4) at week 4. Effect sizes (Cohen d with 95% CI) and P values reflect the results of a paired sample t test that compared scores between baseline and week 1 (Cohen d = 2.3; 95% CI, 1.5-3.1; P < .001) and week 4 postsession-2 follow-up (Cohen d = 2.3; 95% CI, 1.5-3.1; P < .001).

Trial protocol

eTable 1. Repeated Measures ANOVAs Comparing Depression, Anxiety, and Suicidal Ideation Outcomes at Each Timepoint by Treatment Condition

eTable 2. t Tests Comparing Depression, Anxiety, and Suicidal Ideation Outcomes at Each Timepoint by Condition

eTable 3. Repeated Measures ANOVAs and Effect Sizes for Depression, Anxiety, and Suicidal Ideation Outcomes Across Overall Sample

eTable 4. Ratings of Personal Meaning, Spiritual Significance, Psychological Challenge, and Psychological Insight During Each of Two Psilocybin Sessions

eTable 5. Mean Proportion (and Standard Deviation) of Total Possible Score on the Mystical and Challenging Experiences Questionnaires During Each of Two Psilocybin Sessions; Proportion of Participants Who Had a Complete Mystical Experience in Each Session

eTable 6. Monitor Ratings of Peak Psilocybin Effects During Each of Two Psilocybin Sessions

eTable 7. Mean of the Peak Heart Rate and Blood Pressure Across Participants During Each of Two Psilocybin Sessions. Data Regarding Number of Participants Requiring Increased Rate of Monitoring

eTable 8. Adverse Emotional and Physical Effects During Psilocybin Sessions

eTable 9. Adverse Effects Reported the Day After Sessions 1 and 2 That Were Rated by Staff as Possibly or Probably Related to Psilocybin

eTable 10. Initiation of Antidepressant Medication, Psychotherapy, or Psilocybin Reported 4 weeks After Session 2

eFigure 1. Decrease in Depression Scores on the Quick Inventory of Depression Symptoms (QIDS-SR) from Baseline to 1-day Post Psilocybin Session 1 and Through the 4-week Follow-up

eFigure 2. Comparison of Depression Scores on the Quick Inventory of Depression Symptoms (QIDS-SR) by Treatment Condition

eFigure 3. Comparison of Depression Scores on the Beck Depression Inventory – II (BDI-II) by Treatment Condition

eFigure 4. Comparison of Depression Scores on the Patient Health Questionnaire – 9 Item (PHQ-9) by Treatment Condition

eFigure 5. Comparison of Anxiety Scores on the Hamilton Anxiety Scale (HAM-A) by Treatment Condition (Immediate vs Delayed). Effect Size Calculation Using Cohen’s d Statistic

eFigure 6. Comparison of Anxiety Scores on the State-Trait Anxiety Inventory – State Subscale (STAI-State) by Treatment Condition

eFigure 7. Comparison of Anxiety Scores on the State-Trait Anxiety Inventory – Trait Subscale (STAI-Trait) by Treatment Condition

eFigure 8. Comparison of Anxiety Scores on the State-Trait Anxiety Inventory – Total Scale (STAI-Total) by Treatment Condition

eFigure 9. Comparison of Suicidal Ideation Scores on the Columbia Suicide Severity Rating Scale (CSSRS) by Treatment Condition

Data sharing statement

JAMA Network Journals’ Articles of the Year 2021 JAMA Medical News & Perspectives December 28, 2021 This Medical News article is our fifth-annual roundup of the top-viewed articles from each of the JAMA Network Journals. Jennifer Abbasi
Psilocybin-Assisted Supportive Psychotherapy in the Treatment of Major Depression—Quo Vadis? JAMA Psychiatry Editorial May 1, 2021 Charles F. Reynolds III, MD
Errors in a Response Rate and in Effect Sizes in Study of Psilocybin-Assisted Therapy for Major Depressive Disorder JAMA Psychiatry Comment & Response May 1, 2021 Alan K. Davis, PhD; Roland R. Griffiths, PhD
Errors in Response Rate, Effect Sizes, and Confidence Intervals JAMA Psychiatry Correction May 1, 2021

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Davis AK , Barrett FS , May DG, et al. Effects of Psilocybin-Assisted Therapy on Major Depressive Disorder : A Randomized Clinical Trial . JAMA Psychiatry. 2021;78(5):481–489. doi:10.1001/jamapsychiatry.2020.3285

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Effects of Psilocybin-Assisted Therapy on Major Depressive Disorder : A Randomized Clinical Trial

1 Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
2 College of Social Work, The Ohio State University, Columbus
3 Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, Maryland
Editorial Psilocybin-Assisted Supportive Psychotherapy in the Treatment of Major Depression—Quo Vadis? Charles F. Reynolds III, MD JAMA Psychiatry
Medical News & Perspectives JAMA Network Journals’ Articles of the Year 2021 Jennifer Abbasi JAMA
Comment & Response Errors in a Response Rate and in Effect Sizes in Study of Psilocybin-Assisted Therapy for Major Depressive Disorder Alan K. Davis, PhD; Roland R. Griffiths, PhD JAMA Psychiatry
Correction Errors in Response Rate, Effect Sizes, and Confidence Intervals JAMA Psychiatry

Question Is psilocybin-assisted therapy efficacious among patients with major depressive disorder?

Findings In this randomized clinical trial of 24 participants with major depressive disorder, participants who received immediate psilocybin-assisted therapy compared with delayed treatment showed improvement in blinded clinician rater–assessed depression severity and in self-reported secondary outcomes through the 1-month follow-up.

Meaning This randomized clinical trial found that psilocybin-assisted therapy was efficacious in producing large, rapid, and sustained antidepressant effects in patients with major depressive disorder.

Importance Major depressive disorder (MDD) is a substantial public health burden, but current treatments have limited effectiveness and adherence. Recent evidence suggests that 1 or 2 administrations of psilocybin with psychological support produces antidepressant effects in patients with cancer and in those with treatment-resistant depression.

Objective To investigate the effect of psilocybin therapy in patients with MDD.

Design, Setting, and Participants This randomized, waiting list–controlled clinical trial was conducted at the Center for Psychedelic and Consciousness Research at Johns Hopkins Bayview Medical Center in Baltimore, Maryland. Adults aged 21 to 75 years with an MDD diagnosis, not currently using antidepressant medications, and without histories of psychotic disorder, serious suicide attempt, or hospitalization were eligible to participate. Enrollment occurred between August 2017 and April 2019, and the 4-week primary outcome assessments were completed in July 2019. A total of 27 participants were randomized to an immediate treatment condition group (n = 15) or delayed treatment condition group (waiting list control condition; n = 12). Data analysis was conducted from July 1, 2019, to July 31, 2020, and included participants who completed the intervention (evaluable population).

Interventions Two psilocybin sessions (session 1: 20 mg/70 kg; session 2: 30 mg/70 kg) were given (administered in opaque gelatin capsules with approximately 100 mL of water) in the context of supportive psychotherapy (approximately 11 hours). Participants were randomized to begin treatment immediately or after an 8-week delay.

Main Outcomes and Measures The primary outcome, depression severity was assessed with the GRID-Hamilton Depression Rating Scale (GRID-HAMD) scores at baseline (score of ≥17 required for enrollment) and weeks 5 and 8 after enrollment for the delayed treatment group, which corresponded to weeks 1 and 4 after the intervention for the immediate treatment group. Secondary outcomes included the Quick Inventory of Depressive Symptomatology-Self Rated (QIDS-SR).

Results Of the randomized participants, 24 of 27 (89%) completed the intervention and the week 1 and week 4 postsession assessments. This population had a mean (SD) age of 39.8 (12.2) years, was composed of 16 women (67%), and had a mean (SD) baseline GRID-HAMD score of 22.8 (3.9). The mean (SD) GRID-HAMD scores at weeks 1 and 4 (8.0 [7.1] and 8.5 [5.7]) in the immediate treatment group were statistically significantly lower than the scores at the comparable time points of weeks 5 and 8 (23.8 [5.4] and 23.5 [6.0]) in the delayed treatment group. The effect sizes were large at week 5 (Cohen d = 2.5; 95% CI, 1.4-3.5; P < .001) and week 8 (Cohen d = 2.6; 95% CI, 1.5-3.7; P < .001). The QIDS-SR documented a rapid decrease in mean (SD) depression score from baseline to day 1 after session 1 (16.7 [3.5] vs 6.3 [4.4]; Cohen d = 2.6; 95% CI, 1.8-3.5; P < .001), which remained statistically significantly reduced through the week 4 follow-up (6.0 [5.7]; Cohen d = 2.3; 95% CI, 1.5-3.0; P < .001). In the overall sample, 17 participants (71%) at week 1 and 17 (71%) at week 4 had a clinically significant response to the intervention (≥50% reduction in GRID-HAMD score), and 14 participants (58%) at week 1 and 13 participants (54%) at week 4 were in remission (≤7 GRID-HAMD score).

Conclusions and Relevance Findings suggest that psilocybin with therapy is efficacious in treating MDD, thus extending the results of previous studies of this intervention in patients with cancer and depression and of a nonrandomized study in patients with treatment-resistant depression.

Trial Registration ClinicalTrials.gov Identifier: NCT03181529

Major depressive disorder (MDD) is a substantial public health concern, affecting more than 300 million individuals worldwide. Depression is the number one cause of disability, 1 and the relative risk of all-cause mortality for those with depression is 1.7 times greater than the risk for the general public. 2 In the United States, approximately 10% of the adult population has been diagnosed with MDD in the past 12 months, 3 and the yearly economic burden of MDD is estimated to be $210 billion. 4

Although effective pharmacotherapies for depression are available, these drugs have limited efficacy, produce adverse effects, and are associated with patient adherence problems. 5 Although many patients with depression showed reduced or remitted symptoms after treatment with existing pharmacotherapies, 6 approximately 30% to 50% of patients did not respond fully and as many as 10% to 30% of patients were considered treatment-resistant, resulting in average effects that were only modestly larger than the effects of placebo. 7 , 8

Most of the current pharmacotherapies for MDD, including the widely used selective serotonin reuptake inhibitors, increase levels of brain monoamine neurotransmitters such as serotonin and norepinephrine (typically by blocking reuptake). 6 A growing body of evidence suggests that newer ketamine-like medications exert therapeutic efficacy in MDD through effects on glutamate neurotransmission. 9 , 10 Ketamine hydrochloride, a nonselective N -methyl- d -aspartate receptor antagonist, is the most well-researched of these newer medications. Several studies have demonstrated the efficacy of a single ketamine infusion in rapidly (within hours) reducing depression symptoms and, when effective, lasting from a few days to about 2 weeks. 10 , 11 However, ketamine has high abuse liability, and its administration involves moderate physiological risk that requires medical monitoring. 12

Quiz Ref ID The combined serotonergic and glutamatergic action of psilocybin 13 - 15 (a classic hallucinogen) and the preliminary evidence of the antidepressant effects of psilocybin-assisted therapy (among patients with life-threatening cancer or patients with treatment-resistant depression) 16 - 18 indicate the potential of psilocybin-assisted therapy as a novel antidepressant intervention. 19 Moreover, psilocybin has lower addiction liability and toxic effects compared with ketamine 20 - 22 and is generally not associated with long-term perceptual, cognitive, or neurological dysfunction. 23

The substantial negative public health impact of MDD underscores the importance of conducting more research into drugs with rapid and sustained antidepressant effects. Current pharmacotherapies for depression have variable efficacy and unwanted adverse effects. Novel antidepressants with rapid and sustained effects on mood and cognition could represent a breakthrough in the treatment of depression and may potentially improve or save lives. Therefore, the primary objective of this randomized clinical trial was to investigate the effect of psilocybin therapy in patients with MDD.

This randomized, waiting list–controlled clinical trial was conducted at the Center for Psychedelic and Consciousness Research in Baltimore, Maryland. The Johns Hopkins Medicine Institutional Review Board approved this trial (the protocol is included in Supplement 1 ). Written informed consent was obtained from all participants.

This trial of psilocybin therapy included participants with moderate or severe MDD episodes, as assessed with the Structured Clinical Interview for DSM-5 (SCID-5) 24 and the GRID-Hamilton Depression Rating Scale (GRID-HAMD; a score of ≥17 was required for enrollment). 25 , 26 Eligible candidates were aged 21 to 75 years who self-reported no current pharmacotherapy for depression at trial screening. To avoid the confounding effects and potential interactions of concurrent antidepressant use, candidates were required to refrain from using antidepressants (eg, selective serotonin reuptake inhibitors) for at least 5 half-lives before the screening and up to 4 months after enrollment (through the completion of the primary outcome assessment). However, the decision to taper off and/or continuing not to take their medications during the study was made by the individuals and their prescribing physicians and not by study personnel. Additional eligibility requirements included being medically stable with no uncontrolled cardiovascular conditions; having no personal or family history (first or second degree) of psychotic or bipolar disorders; and, for women, being nonpregnant, being non-nursing, and agreeing to use contraception. Individuals with a moderate or severe alcohol or other drug use disorder (including nicotine) in the past year, as defined by Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) ( DSM-5 ) criteria, were excluded, as were individuals with substantial lifetime use (>10 total) or recent use (past 6 months) of ketamine or classic hallucinogens, such as psilocybin-containing mushrooms or lysergic acid diethylamide (eMethods in Supplement 2 ).

Participants were enrolled between August 2017 and April 2019, and the 4-week primary outcome assessments were completed in July 2019. Recruitment was carried out through flyers, print advertisements, internet forums, social media, and the study website. Of the 870 individuals screened by telephone or electronic screening survey, 70 went on to undergo in-person medical and psychological screening, 43 were disqualified, and 27 qualified and were enrolled in the study. After screening, baseline assessments, and enrollment, 27 participants were randomized to either the immediate treatment group or the delayed treatment group (ie, the waiting list control condition). The use of a delayed treatment control was chosen to differentiate the psilocybin intervention from spontaneous symptom improvement. The delay interval was 8 weeks, after which participants in the delayed treatment group underwent all study assessments and entered the study intervention period. Randomization to the immediate treatment and delayed treatment groups occurred after screening and baseline assessments ( Figure 1 ). Participants were randomized using urn randomization, 27 balancing for sex, age, depression severity at screening (assessed using the GRID-HAMD), and level of treatment resistance (assessed using the Maudsley Staging Method). 28 One of us (F.S.B.), who was not involved in participant screening or enrollment, performed urn randomization using the randPack library, version 1.32.0, 29 in the R Statistical Software package (R Foundation for Statistical Computing). 30

Participants received no monetary compensation for undergoing the intervention. However, participants received a total of $200 for completing 2 magnetic resonance imaging sessions.

Quiz Ref ID The intervention period was 8 weeks and involved at least 18 in-person visits, including 2 daylong psilocybin administration sessions ( Figure 2 ). Consistent with previous studies using psilocybin, 16 , 31 the visit schedule included preparatory meetings (8 hours in total) with 2 session facilitators before the first psilocybin session as well as follow-up meetings after psilocybin sessions (2-3 hours in total) (eMethods in Supplement 2 ). Session facilitators were study staff with varying educational levels (ie, bachelor’s, master’s, doctorate, and medical degrees) and professional disciplines (eg, social work, psychology, and psychiatry). After the preparation meetings, 2 psilocybin administration sessions were conducted a mean of 1.6 weeks apart (no statistically significant differences were found between conditions; eResults in Supplement 2 ). The psilocybin dose was moderately high (20 mg/70 kg) in session 1 and was high (30 mg/70 kg) in session 2. Procedures for psilocybin administration and the conduct of the sessions were similar to procedures used in previous and ongoing studies with psilocybin (eMethods in Supplement 2 ) at the Center for Psychedelic and Consciousness Research. 16 , 32 , 33

Psilocybin was administered in opaque gelatin capsules with approximately 100 mL water. Both facilitators were present in the room and available to respond to participants’ physical and emotional needs during the day-long session, with the exception of short breaks taken by 1 facilitator at a time. During the session, participants were instructed to lie on a couch in a living room–like environment, and facilitators encouraged participants to focus their attention inward and stay with any experience that arose. To enhance inward reflection, music was played (the playlist is provided in the eMethods in Supplement 2 ), and participants were instructed to wear eyeshades and headphones.

For safety during the 8-week delay period of the delayed treatment group, participants were monitored weekly by in-person assessment or brief telephone calls. In weeks 5 and 8, participants attended an in-person visit and underwent the GRID-HAMD assessment and other study measures. In other weeks of the delay period, participants received telephone calls that included a brief check-in and assessment for self-reported suicidal ideation or behavior and depression symptoms. All assessments during the delay period were administered by study staff who were not lead facilitators. At the end of the delay period, all participants in the delayed treatment group completed the same intervention as the participants in the immediate treatment group.

Screening evaluation included a preliminary questionnaire administered via telephone or an online survey as well as an in-person medical history and physical examination, electrocardiogram, routine medical blood and urinalysis laboratory tests, and structured assessments (eg, SCID-5, SCID-5 Screening Personality Questionnaire, SCID-5 Personality Disorders, and Personality Assessment Inventory). 24 , 34 - 36

Quiz Ref ID The primary outcome measure was the GRID-HAMD, 37 a version of the 17-item Hamilton Depression Rating Scale that has high reliability and validity. 26 The GRID-HAMD was administered by blinded clinician raters via telephone at baseline and at postrandomization weeks 5 and 8 for participants in the delayed treatment group and at the weeks 1 and 4 follow-up visits after the second psilocybin session for participants in both the immediate treatment and delayed treatment groups. The primary between-group end point comparison was at weeks 5 and 8 between the immediate treatment and delayed treatment groups ( Figure 2 ). The primary within-group end point comparison was between baseline and weeks 1 and 4 postsession 2 follow-up visits in both groups.

Severity of depression was assessed using the total GRID-HAMD score (0-7: no depression; 8-16: mild depression; 17-23: moderate depression; ≥24: severe depression). 38 A clinically significant response was defined as 50% or greater decrease from baseline; symptom remission was defined as a score of 7 or lower. The GRID-HAMD assessment was audiorecorded to examine interrater reliability (eMethods in Supplement 2 ). Interrater reliability for all depression assessments (through postsession week 4) was 85%. Rapid and sustained antidepressant effects were examined at baseline; at day 1 and week 1 of postsession-1 follow-up; and at day 1, week 1, and week 4 postsession-2 follow-up using the Quick Inventory of Depressive Symptomatology–Self-Report (QIDS-SR; score range: 0-27, with higher scores indicating very severe depression). 39

Descriptions of secondary outcome measures and timing of assessment are provided in the eMethods in Supplement 2 . Secondary outcome measures for depressive symptoms were the Beck Depression Inventory II (score range: 0-63, with higher scores indicating severe depression) 40 and the 9-item Patient Health Questionnaire (score range: 0-27, with higher scores indicating severe depression). 41 The Columbia-Suicide Severity Rating Scale (severity of ideation subscale score range: 0-5, with higher scores indicating presence of ideation with at least some intent to die) 42 , 43 was completed at every visit to assess for potentially worsening suicidal ideation throughout the trial. Anxiety symptoms were measured using the clinician-administered Hamilton Anxiety Rating Scale (score range: 0-56, with higher scores indicating severe anxiety) 44 and the State-Trait Anxiety Index (score range: 0-80, with higher scores indicating greater anxiety). 45 Blood pressure and heart rate were examined before and during the psilocybin sessions.

Data analysis was conducted on participants who completed the intervention (evaluable population). A previous study of psilocybin 16 found a large effect of a high psilocybin dose (compared with a low dose) on reducing GRID-HAMD scores (Cohen d = 1.30). Assuming a similar large effect size with 24 participants, nearly 100% power was calculated to detect a statistically significant effect of psilocybin on change in depressive symptoms.

No primary outcome data were missing. Descriptive statistics for demographic and background characteristics for all study variables were calculated and compared between study conditions using a 2-sample t test for continuous variables and a χ 2 test for all remaining variables. A repeated-measures analysis of variance with time (baseline, week 5, and week 8) and condition (immediate treatment and delayed treatment) as factors was used to examine changes in the primary depression outcome (GRID-HAMD score).

Follow-up planned comparisons included independent samples t tests to compare week 1 with week 4 GRID-HAMD scores in the immediate treatment condition group (corresponding to the week 5 and week 8 time points in the delayed treatment condition group). Within-participant (n = 24) treatment effect was examined using t tests comparing GRID-HAMD scores at baseline with scores at week 1 and week 4 postsession-2 follow-up. Rapid and sustained antidepressant effects were examined using t tests comparing QIDS-SR scores between baseline and day 1 postsession-1 and between baseline and week 4 postsession-2 follow-up. Effect sizes for the independent samples t tests were calculated using the Cohen d statistic, and effect sizes for the repeated-measures analysis of variance were calculated using the partial eta squared (η p 2 ) statistic. Further primary outcomes included a descriptive analysis of the percentage of participants who met the criterion for clinically significant response and remission in the sample.

All statistical tests used a P < .05 to determine statistical significance. Data analysis was conducted from July 1, 2019, to July 31, 2020, using SPSS, version 25 (IBM). 46 Data analysis plans for secondary outcomes are reported in the eMethods in Supplement 2 .

A total of 27 participants were randomized, of whom 24 (89%) completed the intervention as well as the postsession assessments at weeks 1 and 4; specifically, 13 were randomized to the immediate treatment group and 11 to the delayed treatment group ( Figure 1 ). The Table shows the demographic characteristics for the 24 participants, among whom were 16 women (67%) and 8 men (33%), with a mean (SD) age of 39.8 (12.2) years and a mean (SD) baseline GRID-HAMD score of 22.8 (3.9). An examination of the differences in stratification variables as a function of the treatment condition indicated no statistically significant differences between conditions (mean [SD] months in current major depressive episode: immediate treatment, 25.9 [22.4]; delayed treatment, 22.6 [22.5]; P = .39) ( Table ).

A statistically significant time by condition interaction effect on GRID-HAMD was found (η p 2 = 0.57; 90% CI, 0.38-0.66; P < .001) ( Figure 3 ).

Follow-up independent samples t tests revealed significantly lower depression scores in the immediate treatment condition at weeks 1 and 4 postsession-2 follow-up compared with the corresponding time points (weeks 5 and 8) in the delayed treatment condition before psilocybin treatment. In the immediate treatment group, the mean (SD) GRID-HAMD scores were 22.9 (3.6) at baseline, 8.0 (7.1) at week 5, and 8.5 (5.7) at week 8. In the delayed treatment group, the mean (SD) GRID-HAMD scores were 22.5 (4.4) at baseline, 23.8 (5.4) at week 5, and 23.5 (6.0) at week 8. The effect sizes were large at week 5 (Cohen d = 2.5; 95% CI, 1.4-3.5; P < .001) and at week 8 (Cohen d = 2.6; 95% CI, 1.5-3.7; P < .001) (eTables 1-3 and eResults in Supplement 2 ).

Quiz Ref ID After the psilocybin session, 17 participants (71%) at week 1 and 17 participants (71%) at week 4 had a clinically significant response to the intervention (≥50% reduction in GRID-HAMD score), and 14 participants (58%) at week 1 and 13 participants (54%) at week 4 met the criteria for remission of depression (≤7 GRID-HAMD score). Within-participant t tests showed statistically significant decreases in GRID-HAMD scores among participants from baseline to week 1 (Cohen d = 2.3; 95% CI, 1.5-3.1; P < .001) and week 4 (Cohen d = 2.3; 95% CI, 1.5-3.1; P < .001) ( Figure 4 ). The QIDS-SR measure of depression, which was assessed more frequently, showed a rapid, large decrease in mean (SD) depression score among participants from baseline to day 1 after psilocybin session 1 (16.7 [3.5] vs 6.3 [4.4]; Cohen d = 2.6; 95% CI, 1.8-3.5; P < .001). This substantial decrease remained through week 4 after session 2 (6.0 [5.7]; Cohen d = 2.3; 95% CI, 1.5-3.0; P < .001) (eFigure 1 in Supplement 2 ).

All secondary depression and anxiety outcomes showed a similar pattern of results as the primary depression outcomes, with statistically significant differences between conditions and across both conditions after entry into the active intervention period (eTables 1 to 3 and eFigures 1 to 8 in Supplement 2 ). For example, statistically significant treatment condition effects were found on self-reported depression (Beck Depression Inventory II and Patient Health Questionnaire–9) and clinician-administered anxiety (Hamilton Anxiety Rating Scale) measures. Overall, suicidal ideation was low and trended lower after enrollment in both groups (eFigure 9 in Supplement 2 ).

Participant and facilitator rated intensity of acute psilocybin effects are provided in eTables 4-6 in Supplement 2 . There were no serious adverse events in this trial. A transient increase in blood pressure that exceeded the protocol criteria for more frequent assessment (ie, diastolic blood pressure >100 mm Hg) occurred during 1 session, but no medical intervention was needed, and the blood pressure level remained within predetermined safety parameters and resolved spontaneously during the session (eTable 7 in Supplement 2 ). Other nonserious adverse effects, which occurred during the psilocybin administration, that were reported by participants after completing at least one-half of the psilocybin sessions included challenging emotional (eg, fear and sadness) and physical (eg, feeling body shake or tremble) experiences (eTable 8 in Supplement 2 ). Mild to moderate transient headache was reported during 16 of 48 sessions (33%) and after the subjective psilocybin effects had subsided after 14 of 48 sessions (29%). Other adverse events are reported in eTables 8 and 9 in Supplement 2 , and initiation of antidepressants or psychotherapy is reported in eTable 10 in Supplement 2 .

This randomized clinical trial documented the substantial rapid and enduring antidepressant effects of psilocybin-assisted therapy among patients with MDD. Although the rapid antidepressant effects of psilocybin are similar to those reported with ketamine, 10 , 11 the therapeutic effects are different: ketamine effects typically last for a few days to 2 weeks, whereas the current study showed that clinically significant antidepressant response to psilocybin therapy persisted for at least 4 weeks, with 71% of the participants continuing to show a clinically significant response (≥50% reduction in GRID-HAMD score) at week 4 of follow-up. Furthermore, psilocybin was found to have low potential for addiction 22 and a minimal adverse event profile, 22 , 23 suggesting therapeutic advantages with less risk for associated problems than ketamine. 12 The present findings in patients with MDD are consistent with results of studies that reported on the effectiveness of psilocybin-assisted therapy in producing antidepressant effects among patients with cancer who had psychological distress 16 , 17 , 47 and a small open-label study of patients with treatment-resistant depression. 18

The mounting evidence of the use of psilocybin as an adjunct to treatment of a variety of psychiatric conditions (eg, depression, 16 - 18 tobacco use disorder, 48 and alcohol use disorder 49 ) suggests a transdiagnostic mechanism of action. In several studies in patients 16 - 18 , 49 - 51 and in healthy volunteers, 32 , 52 the intensity of mystical-type experiences reported after psilocybin sessions was associated with favorable outcomes. Furthermore, cross-sectional studies have suggested that mystical-type and psychologically insightful experiences during a psychedelic session predict positive therapeutic effects. 53 - 55 Consistent with these previous studies, the current trial showed that psilocybin-occasioned mystical-type, personally meaningful, and insightful experiences were associated with decreases in depression at 4 weeks (eResults in Supplement 2 ). Furthermore, a recent report suggested that psilocybin may decrease negative affect and the neural correlates of negative affect, 56 which may be a mechanism underlying transdiagnostic efficacy. Taken together, these findings suggest that further studies into psychological and neural mechanisms across different psychiatric conditions are warranted.

The present trial showed that psilocybin administered in the context of supportive psychotherapy (approximately 11 hours) produced large, rapid, and sustained antidepressant effects. The effect sizes reported in this study were approximately 2.5 times greater than the effect sizes found in psychotherapy 57 and more than 4 times greater than the effect sizes found in psychopharmacological depression treatment studies. 58 These findings are consistent with literature that showed that combined pharmacotherapy and psychotherapy were more efficacious in the treatment of MDD than either intervention alone. 59 - 61 Furthermore, given that psilocybin was associated with nonserious adverse effects that were frequently reported as mild-to-moderate headache and challenging emotions that were limited to the time of sessions (eTables 8 and 9 in Supplement 2 ), this intervention may be more acceptable to patients than widely prescribed antidepressant medications that confer substantially more problematic effects (eg, suicidal ideation, decrease in sexual drive, and weight gain). The effectiveness of psilocybin therapy after a single or only a few administrations represents another substantial advantage over commonly used antidepressants that require daily administration.

This study has some strengths. It had a randomized design and used GRID-HAMD as the primary outcome measure that was assessed by blinded clinician raters. The delayed treatment condition controlled for the possible effects of having been accepted into the trial and for the passage of time between screening and initial follow-up assessments. However, the delayed treatment condition did not control for other aspects of psilocybin administration, such as preparation and rapport building, postsession integration meetings, or expectancy effects. Although placebo and active treatment controlled designs are widely used in therapeutic trials, 62 they too have limitations owing to the highly discriminable effects of psilocybin.

Quiz Ref ID This study has some other limitations. It had a short-term follow-up, a small sample that was predominantly composed of White non-Hispanic participants, and included participants with low risk of suicide and moderately severe depression. Further research with larger and more diverse samples, longer-term follow-up, and a placebo control is needed to better ascertain the safety (eg, abuse potential of psilocybin, suicide risk, and emergence of psychosis) and efficacy of this intervention among patients with MDD. Another limitation is the psychotherapy approach 31 that involved session facilitators from a variety of professional disciplines (eg, social work, psychology, psychiatry) and session facilitators without formal clinical training (eg, research assistants and clinical trainees). The type of psychotherapy offered and the characteristics of therapists should be explored in future studies.

Results of this randomized clinical trial demonstrated the efficacy of psilocybin-assisted therapy in producing large, rapid, and sustained antidepressant effects among patients with MDD. These data expand the findings of previous studies involving patients with cancer and depression as well as patients with treatment-resistant depression by suggesting that psilocybin may be effective in the much larger population of MDD. Further studies are needed with active treatment or placebo controls and in larger and more diverse populations.

Accepted for Publication: July 31, 2020.

Published Online: November 4, 2020. doi:10.1001/jamapsychiatry.2020.3285

Correction: This article was corrected on February 10, 2021, to fix errors in the Abstract Results and Results section.

Corresponding Authors: Alan K. Davis, PhD ( [email protected] ), and Roland R. Griffiths, PhD ( [email protected] ), Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 5510 Nathan Shock Drive, Baltimore, MD 21224.

Author Contributions: Drs Davis and Griffiths had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Davis, Barrett, May, Cosimano, Johnson, Griffiths.

Acquisition, analysis, or interpretation of data: Davis, Barrett, May, Sepeda, Johnson, Finan, Griffiths.

Drafting of the manuscript: Davis, Barrett, May, Cosimano, Sepeda, Griffiths.

Critical revision of the manuscript for important intellectual content: Davis, Barrett, May, Sepeda, Johnson, Finan, Griffiths.

Statistical analysis: Davis, Griffiths.

Obtained funding: Barrett, Griffiths.

Administrative, technical, or material support: Davis, Barrett, May, Cosimano, Sepeda, Finan, Griffiths.

Supervision: Davis, Barrett, May, Cosimano, Johnson, Griffiths.

Conflict of Interest Disclosures: Dr Davis reported being a board member at Source Research Foundation. Dr Johnson reported receiving grants from Heffter Research Institute outside the submitted work and personal fees as a consultant and/or advisory board member from Beckley Psychedelics Ltd, Entheogen Biomedical Corp, Field Trip Psychedelics Inc, Mind Medicine Inc, and Otsuka Pharmaceutical Development & Commercialization Inc. Dr Griffiths reported being a board member at Heffter Research Institute and receiving grants from Heffter Research Institute outside the submitted work. No other disclosures were reported.

Funding/Support: This study was funded in part by a crowd-sourced funding campaign organized by Tim Ferriss; a grant from the Riverstyx Foundation; and grants from Tim Ferriss, Matt Mullenweg, Craig Nerenberg, Blake Mycoskie, and the Steven and Alexandra Cohen Foundation. Drs Davis and May were supported by postdoctoral training grant T32DA07209 from NIDA. Dr Finan was supported by grant K23DA035915 from NIDA. Drs Griffiths and Johnson were partially supported by grant R01DA03889 from NIDA. The Center for Psychedelic and Consciousness Research is funded by the Steven and Alexandra Cohen Foundation and has received support from Tim Ferriss, Matt Mullenweg, Craig Nerenberg, and Blake Mycoskie.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Annie Umbricht, MD, and Eric Strain, MD, provided medical oversight during the study sessions. Jessiy Salwen, PhD, and Mary Bailes, LCPC, served as blinded clinician raters. Natalie Gukasyan, MD; Laura Doyle, BA; John Clifton, BS; Kasey Cox, MS; and Rhiannon Mayhugh, PhD, facilitated the intervention sessions. These individuals, from Johns Hopkins University, received no additional compensation, outside of their usual salary, for their contributions.

Data Sharing Statement: See Supplement 3 .

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Major Depressive Disorder: Advances in Neuroscience Research and Translational Applications

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Published: 13 February 2021
Volume 37 , pages 863–880, ( 2021 )

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Zezhi Li 1 , 2 ,
Meihua Ruan 3 ,
Jun Chen 1 , 5 &
Yiru Fang ORCID: orcid.org/0000-0002-8748-9085 1 , 4 , 5

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A Correction to this article was published on 17 May 2021

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Major depressive disorder (MDD), also referred to as depression, is one of the most common psychiatric disorders with a high economic burden. The etiology of depression is still not clear, but it is generally believed that MDD is a multifactorial disease caused by the interaction of social, psychological, and biological aspects. Therefore, there is no exact pathological theory that can independently explain its pathogenesis, involving genetics, neurobiology, and neuroimaging. At present, there are many treatment measures for patients with depression, including drug therapy, psychotherapy, and neuromodulation technology. In recent years, great progress has been made in the development of new antidepressants, some of which have been applied in the clinic. This article mainly reviews the research progress, pathogenesis, and treatment of MDD.

Introduction

Neuroimaging advance in depressive disorder.

The cellular and molecular basis of major depressive disorder: towards a unified model for understanding clinical depression

Avoid common mistakes on your manuscript.

Major depressive disorder (MDD) also referred to as depression, is one of the most severe and common psychiatric disorders across the world. It is characterized by persistent sadness, loss of interest or pleasure, low energy, worse appetite and sleep, and even suicide, disrupting daily activities and psychosocial functions. Depression has an extreme global economic burden and has been listed as the third largest cause of disease burden by the World Health Organization since 2008, and is expected to rank the first by 2030 [ 1 , 2 ]. In 2016, the Global Burden of Diseases, Injuries, and Risk Factors Study demonstrated that depression caused 34.1 million of the total years lived with disability (YLDs), ranking as the fifth largest cause of YLD [ 3 ]. Therefore, the research progress and the clinical application of new discoveries or new technologies are imminent. In this review, we mainly discuss the current situation of research, developments in pathogenesis, and the management of depression.

Current Situation of Research on Depression

Analysis of published papers.

In the past decade, the total number of papers on depression published worldwide has increased year by year as shown in Fig. 1 A. Searching the Web of Science database, we found a total of 43,863 papers published in the field of depression from 2009 to 2019 (search strategy: TI = (depression$) or ts = ("major depressive disorder$")) and py = (2009 – 2019), Articles). The top 10 countries that published papers on the topic of depression are shown in Fig. 1 B. Among them, researchers in the USA published the most papers, followed by China. Compared with the USA, the gap in the total number of papers published in China is gradually narrowing (Fig. 1 C), but the quality gap reflected by the index (the total number of citations and the number of citations per paper) is still large, and is lower than the global average (Fig. 1 D). As shown in Fig. 1 E, the hot research topics in depression are as follows: depression management in primary care, interventions to prevent depression, the pathogenesis of depression, comorbidity of depression and other diseases, the risks of depression, neuroimaging studies of depression, and antidepressant treatment.

Analysis of published papers around the world from 2009 to 2019 in depressive disorder. A The total number of papers [from a search of the Web of Science database (search strategy: TI = (depression$) or ts = ("major depressive disorder$")) and py = (2009 – 2019), Articles)]. B The top 10 countries publishing on the topic. C Comparison of papers in China and the USA. D Citations for the top 10 countries and comparison with the global average. E Hot topics.

Analysis of Patented Technology Application

There were 16,228 patent applications in the field of depression between 2009 and 2019, according to the Derwent Innovation Patent database. The annual number and trend of these patents are shown in Fig. 2 A. The top 10 countries applying for patents related to depression are shown in Fig. 2 B. The USA ranks first in the number of depression-related patent applications, followed by China. The largest number of patents related to depression is the development of antidepressants, and drugs for neurodegenerative diseases such as dementia comorbid with depression. The top 10 technological areas of patents related to depression are shown in Fig. 2 C, and the trend in these areas have been stable over the past decade (Fig. 2 D).

Analysis of patented technology applications from 2009 to 2019 in the field of depressive disorder. A Annual numbers and trends of patents (the Derwent Innovation patent database). B The top 10 countries/regions applying for patents. C The top 10 technological areas of patents. D The trend of patent assignees. E Global hot topic areas of patents.

Analysis of technical hotspots based on keyword clustering was conducted from the Derwent Innovation database using the "ThemeScape" tool. This demonstrated that the hot topic areas are as follows (Fig. 2 E): (1) improvement for formulation and the efficiency of hydrobromide, as well as optimization of the dosage; intervention for depression comorbid with AD, diabetes, and others; (3) development of alkyl drugs; (4) development of pharmaceutical acceptable salts as antidepressants; (5) innovation of the preparation of antidepressants; (6) development of novel antidepressants based on neurotransmitters; (7) development of compositions based on nicotinic acetylcholine receptors; and (8) intervention for depression with traditional Chinese medicine.

Analysis of Clinical Trial

There are 6,516 clinical trials in the field of depression in the ClinicalTrials.gov database, and among them, 1,737 valid trials include the ongoing recruitment of subjects, upcoming recruitment of subjects, and ongoing clinical trials. These clinical trials are mainly distributed in the USA (802 trials), Canada (155), China (114), France (93), Germany (66), UK (62), Spain (58), Denmark (41), Sweden (39), and Switzerland (23). The indications for clinical trials include various types of depression, such as minor depression, depression, severe depression, perinatal depression, postpartum depression, and depression comorbid with other psychiatric disorders or physical diseases, such as schizophrenia, epilepsy, stroke, cancer, diabetes, cardiovascular disease, and Parkinson's disease.

Based on the database of the Chinese Clinical Trial Registry website, a total of 143 clinical trials for depression have been carried out in China. According to the type of research, they are mainly interventional and observational studies, as well as a small number of related factor studies, epidemiological studies, and diagnostic trials. The research content involves postpartum, perinatal, senile, and other age groups with clinical diagnosis (imaging diagnosis) and intervention studies (drugs, acupuncture, electrical stimulation, transcranial magnetic stimulation). It also includes intervention studies on depression comorbid with coronary heart disease, diabetes, and heart failure.

New Medicine Development

According to the Cortellis database, 828 antidepressants were under development by the end of 2019, but only 292 of these are effective and active (Fig. 3 A). Large number of them have been discontinued or made no progress, indicating that the development of new drugs in the field of depression is extremely urgent.

New medicine development from 2009 to 2019 in depressive disorder. A Development status of new candidate drugs. B Top target-based actions.

From the perspective of target-based actions, the most common new drugs are NMDA receptor antagonists, followed by 5-HT targets, as well as dopamine receptor agonists, opioid receptor antagonists and agonists, AMPA receptor modulators, glucocorticoid receptor antagonists, NK1 receptor antagonists, and serotonin transporter inhibitors (Fig. 3 B).

Epidemiology of Depression

The prevalence of depression varies greatly across cultures and countries. Previous surveys have demonstrated that the 12-month prevalence of depression was 0.3% in the Czech Republic, 10% in the USA, 4.5% in Mexico, and 5.2% in West Germany, and the lifetime prevalence of depression was 1.0% in the Czech Republic, 16.9% in the USA, 8.3% in Canada, and 9.0% in Chile [ 4 , 5 ]. A recent meta-analysis including 30 Countries showed that lifetime and 12-month prevalence depression were 10.8% and 7.2%, respectively [ 6 ]. In China, the lifetime prevalence of depression ranged from 1.6% to 5.5% [ 7 , 8 , 9 ]. An epidemiological study demonstrated that depression was the most common mood disorder with a life prevalence of 3.4% and a 12-month prevalence of 2.1% in China [ 10 ].

Some studies have also reported the prevalence in specific populations. The National Comorbidity Survey-Adolescent Supplement (NCS-A) survey in the USA showed that the lifetime and 12-month prevalence of depression in adolescents aged 13 to 18 were 11.0% and 7.5%, respectively [ 11 ]. A recent meta-analysis demonstrated that lifetime prevalence and 12-month prevalence were 2.8% and 2.3%, respectively, among the elderly population in China [ 12 ].

Neurobiological Pathogenesis of Depressive Disorder

The early hypothesis of monoamines in the pathophysiology of depression has been accepted by the scientific community. The evidence that monoamine oxidase inhibitors and tricyclic antidepressants promote monoamine neurotransmission supports this theory of depression [ 13 ]. So far, selective serotonin reuptake inhibitors and norepinephrine reuptake inhibitors are still the first-line antidepressants. However, there remain 1/3 to 2/3 of depressed patients who do not respond satisfactorily to initial antidepressant treatment, and even as many as 15%–40% do not respond to several pharmacological medicines [ 14 , 15 ]. Therefore, the underlying pathogenesis of depression is far beyond the simple monoamine mechanism.

Other hypotheses of depression have gradually received increasing attention because of biomarkers for depression and the effects pharmacological treatments, such as the stress-responsive hypothalamic pituitary adrenal (HPA) axis, neuroendocrine systems, the neurotrophic family of growth factors, and neuroinflammation.

Stress-Responsive HPA Axis

Stress is causative or a contributing factor to depression. Particularly, long-term or chronic stress can lead to dysfunction of the HPA axis and promote the secretion of hormones, including cortisol, adrenocorticotropic hormone, corticotropin-releasing hormone, arginine vasopressin, and vasopressin. About 40%–60% of patients with depression display a disturbed HPA axis, including hypercortisolemia, decreased rhythmicity, and elevated cortisol levels [ 16 , 17 ]. Mounting evidence has shown that stress-induced abnormality of the HPA axis is associated with depression and cognitive impairment, which is due to the increased secretion of cortisol and the insufficient inhibition of glucocorticoid receptor regulatory feedback [ 18 , 19 ]. In addition, it has been reported that the increase in cortisol levels is related to the severity of depression, especially in melancholic depression [ 20 , 21 ]. Further, patients with depression whose HPA axis was not normalized after treatment had a worse clinical response and prognosis [ 22 , 23 ]. Despite the above promising insights, unfortunately previous studies have shown that treatments regulating the HPA axis, such as glucocorticoid receptor antagonists, do not attenuate the symptoms of depressed patients [ 24 , 25 ].

Glutamate Signaling Pathway

Glutamate is the main excitatory neurotransmitter released by synapses in the brain; it is involved in synaptic plasticity, cognitive processes, and reward and emotional processes. Stress can induce presynaptic glutamate secretion by neurons and glutamate strongly binds to ionotropic glutamate receptors (iGluRs) including N-methyl-D-aspartate receptors (NMDARs) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptors (AMPARs) [ 26 ] on the postsynaptic membrane to activate downstream signal pathways [ 27 ]. Accumulating evidence has suggested that the glutamate system is associated with the incidence of depression. Early studies have shown increased levels of glutamate in the peripheral blood, cerebrospinal fluid, and brain of depressed patients [ 28 , 29 ], as well as NMDAR subunit disturbance in the brain [ 30 , 31 ]. Blocking the function of NMDARs has an antidepressant effect and protects hippocampal neurons from morphological abnormalities induced by stress, while antidepressants reduce glutamate secretion and NMDARs [ 32 ]. Most importantly, NMDAR antagonists such as ketamine have been reported to have profound and rapid antidepressant effects on both animal models and the core symptoms of depressive patients [ 33 ]. On the other hand, ketamine can also increase the AMPAR pathway in hippocampal neurons by up-regulating the AMPA glutamate receptor 1 subunit [ 34 ]. Further, the AMPAR pathway may be involved in the mechanism of antidepressant effects. For example, preclinical studies have indicated that AMPAR antagonists might attenuate lithium-induced depressive behavior by increasing the levels of glutamate receptors 1 and 2 in the mouse hippocampus [ 35 ].

Gamma-Aminobutyric Acid (GABA)

Contrary to glutamate, GABA is the main inhibitory neurotransmitter. Although GABA neurons account for only a small proportion compared to glutamate, inhibitory neurotransmission is essential for brain function by balancing excitatory transmission [ 36 ]. Number of studies have shown that patients with depression have neurotransmission or functional defects of GABA [ 37 , 38 ]. Schür et al ., conducted a meta-analysis of magnetic resonance spectroscopy studies, which showed that the brain GABA level in depressive patients was lower than that in healthy controls, but no difference was found in depressive patients in remission [ 39 ]. Several postmortem studies have shown decreased levels of the GABA synthase glutamic acid decarboxylase in the prefrontal cortex of patients with depression [ 40 , 41 ]. It has been suggested that a functional imbalance of the GABA and glutamate systems contributes to the pathophysiology of depression, and activation of the GABA system might induce antidepressant activity, by which GABA A receptor mediators α2/α3 are considered potential antidepressant candidates [ 42 , 43 ]. Genetic mouse models, such as the GABA A receptor mutant mouse and conditional the Gad1-knockout mouse (GABA in hippocampus and cerebral cortex decreased by 50%) and optogenetic methods have verified that depression-like behavior is induced by changing the level of GABA [ 44 , 45 ].

Neurotrophin Family

The neurotrophin family plays a key role in neuroplasticity and neurogenesis. The neurotrophic hypothesis of depression postulates that a deficit of neurotrophic support leads to neuronal atrophy, the reduction of neurogenesis, and the destruction of glia support, while antidepressants attenuate or reverse these pathophysiological processes [ 46 ]. Among them, the most widely accepted hypothesis involves brain-derived neurotrophic factor (BDNF). This was initially triggered by evidence that stress reduces the BDNF levels in the animal brain, while antidepressants rescue or attenuate this reduction [ 47 , 48 ], and agents involved in the BDNF system have been reported to exert antidepressant-like effects [ 49 , 50 ]. In addition, mounting studies have reported that the BDNF level is decreased in the peripheral blood and at post-mortem in depressive patients, and some have reported that antidepressant treatment normalizes it [ 51 , 52 ]. Furthermore, some evidence also showed that the interaction of BDNF and its receptor gene is associated with treatment-resistant depression [ 15 ].

Recent studies reported that depressed patients have a lower level of the pro-domain of BDNF (BDNF pro-peptide) than controls. This is located presynaptically and promotes long-term depression in the hippocampus, suggesting that it is a promising synaptic regulator [ 53 ].

Neuroinflammation

The immune-inflammation hypothesis has attracted much attention, suggesting that the interactions between inflammatory pathways and neural circuits and neurotransmitters are involved in the pathogenesis and pathophysiological processes of depression. Early evidence found that patients with autoimmune or infectious diseases are more likely to develop depression than the general population [ 54 ]. In addition, individuals without depression may display depressive symptoms after treatment with cytokines or cytokine inducers, while antidepressants relieve these symptoms [ 55 , 56 ]. There is a complex interaction between the peripheral and central immune systems. Previous evidence suggested that peripheral inflammation/infection may spread to the central nervous system in some way and cause a neuroimmune response [ 55 , 57 ]: (1) Some cytokines produced in the peripheral immune response, such as IL-6 and IL-1 β, can leak into the brain through the blood-brain barrier (BBB). (2) Cytokines entering the central nervous system act directly on astrocytes, small stromal cells, and neurons. (3) Some peripheral immune cells can cross the BBB through specific transporters, such as monocytes. (4) Cytokines and chemokines in the circulation activate the central nervous system by regulating the surface receptors of astrocytes and endothelial cells at the BBB. (5) As an intermediary pathway, the immune inflammatory response transmits peripheral danger signals to the center, amplifies the signals, and shows the external phenotype of depressive behavior associated with stress/trauma/infection. (6) Cytokines and chemokines may act directly on neurons, change their plasticity and promote depression-like behavior.

Patients with depression show the core feature of the immune-inflammatory response, that is, increased concentrations of pro-inflammatory cytokines and their receptors, chemokines, and soluble adhesion molecules in peripheral blood and cerebrospinal fluid [ 58 , 59 , 60 ]. Peripheral immune-inflammatory response markers not only change the immune activation state in the brain that affects explicit behavior, but also can be used as an evaluation index or biological index of antidepressant therapy [ 61 , 62 ]. Li et al . showed that the level of TNF-α in patients with depression prior to treatment was higher than that in healthy controls. After treatment with venlafaxine, the level of TNF-α in patients with depression decreased significantly, and the level of TNF-α in the effective group decreased more [ 63 ]. A recent meta-analysis of 1,517 patients found that antidepressants significantly reduced peripheral IL-6, TNF-α, IL-10, and CCL-2, suggesting that antidepressants reduce markers of peripheral inflammatory factors [ 64 ]. Recently, Syed et al . also confirmed that untreated patients with depression had higher levels of inflammatory markers and increased levels of anti-inflammatory cytokines after antidepressant treatment, while increased levels of pro-inflammatory cytokines were found in non-responders [ 62 ]. Clinical studies have also found that anti-inflammatory cytokines, such as monoclonal antibodies and other cytokine inhibitors, may play an antidepressant role by blocking cytokines. The imbalance of pro-inflammatory and anti-inflammatory cytokines may be involved in the pathophysiological process of depression.

In addition, a recent study showed that microglia contribute to neuronal plasticity and neuroimmune interaction that are involved in the pathophysiology of depression [ 65 ]. When activated microglia promote inflammation, especially the excessive production of pro-inflammatory factors and cytotoxins in the central nervous system, depression-like behavior can gradually develop [ 65 , 66 ]. However, microglia change polarization as two types under different inflammatory states, regulating the balance of pro- and anti-inflammatory factors. These two types are M1 and M2 microglia; the former produces large number of pro-inflammatory cytokines after activation, and the latter produces anti-inflammatory cytokines. An imbalance of M1/M2 polarization of microglia may contribute to the pathophysiology of depression [ 67 ].

Microbiome-Gut-Brain Axis

The microbiota-gut-brain axis has recently gained more attention because of its ability to regulate brain activity. Many studies have shown that the microbiota-gut-brain axis plays an important role in regulating mood, behavior, and neuronal transmission in the brain [ 68 , 69 ]. It is well established that comorbidity of depression and gastrointestinal diseases is common [ 70 , 71 ]. Some antidepressants can attenuate the symptoms of patients with irritable bowel syndrome and eating disorders [ 72 ]. It has been reported that gut microbiome alterations are associated with depressive-like behaviors [ 73 , 74 ], and brain function [ 75 ]. Early animal studies have shown that stress can lead to long-term changes in the diversity and composition of intestinal microflora, and is accompanied by depressive behavior [ 76 , 77 ]. Interestingly, some evidence indicates that rodents exhibit depressive behavior after fecal transplants from patients with depression [ 74 ]. On the other hand, some probiotics attenuated depressive-like behavior in animal studies, [ 78 ] and had antidepressant effects on patients with depression in several double-blind, placebo-controlled clinical trials [ 79 , 80 ].

The potential mechanism may be that gut microbiota can interact with the brain through a variety of pathways or systems, including the HPA axis, and the neuroendocrine, autonomic, and neuroimmune systems [ 81 ]. For example, recent evidence demonstrated that gut microbiota can affect the levels of neurotransmitters in the gut and brain, including serotonin, dopamine, noradrenalin, glutamate, and GABA [ 82 ]. In addition, recent studies showed that changes in gut microbiota can also impair the gut barrier and promote higher levels of peripheral inflammatory cytokines [ 83 , 84 ]. Although recent research in this area has made significant progress, more clinical trials are needed to determine whether probiotics have any effect on the treatment of depression and what the potential underlying mechanisms are.

Other Systems and Pathways

There is no doubt that several other systems or pathways are also involved in the pathophysiology of depression, such as oxidant-antioxidant imbalance [ 85 ], mitochondrial dysfunction [ 86 , 87 ], and circadian rhythm-related genes [ 88 ], especially their critical interactions ( e.g. interaction between the HPA and mitochondrial metabolism [ 89 , 90 ], and the reciprocal interaction between oxidative stress and inflammation [ 2 , 85 ]). The pathogenesis of depression is complex and all the hypotheses should be integrated to consider the many interactions between various systems and pathways.

Advances in Various Kinds of Research on Depressive Disorder

Genetic, molecular, and neuroimaging studies continue to increase our understanding of the neurobiological basis of depression. However, it is still not clear to what extent the results of neurobiological studies can help improve the clinical and functional prognosis of patients. Therefore, over the past 10 years, the neurobiological study of depression has become an important measure to understand the pathophysiological mechanism and guide the treatment of depression.

Genetic Studies

Previous twin and adoption studies have indicated that depression has relatively low rate of heritability at 37% [ 91 ]. In addition, environmental factors such as stressful events are also involved in the pathogenesis of depression. Furthermore, complex psychiatric disorders, especially depression, are considered to be polygenic effects that interact with environmental factors [ 13 ]. Therefore, reliable identification of single causative genes for depression has proved to be challenging. The first genome-wide association studies (GWAS) for depression was published in 2009, and included 1,738 patients and 1,802 controls [ 92 , 93 ]. Although many subsequent GWASs have determined susceptible genes in the past decade, the impact of individual genes is so small that few results can be replicated [ 94 , 95 ]. So far, it is widely accepted that specific single genetic mutations may play minor and marginal roles in complex polygenic depression. Another major recognition in GWASs over the past decade is that prevalent candidate genes are usually not associated with depression. Further, the inconsistent results may also be due to the heterogeneity and polygenic nature of genetic and non-genetic risk factors for depression as well as the heterogeneity of depression subtypes [ 95 , 96 ]. Therefore, to date, the quality of research has been improved in two aspects: (1) the sample size has been maximized by combining the data of different evaluation models; and (2) more homogenous subtypes of depression have been selected to reduce phenotypic heterogeneity [ 97 ]. Levinson et al . pointed out that more than 75,000 to 100,000 cases should be considered to detect multiple depression associations [ 95 ]. Subsequently, several recent GWASs with larger sample sizes have been conducted. For example, Okbay et al . identified two loci associated with depression and replicated them in separate depression samples [ 98 ]. Wray et al . also found 44 risk loci associated with depression based on 135,458 cases and 344,901 controls [ 99 ]. A recent GWAS of 807,553 individuals with depression reported that 102 independent variants were associated with depression; these were involved in synaptic structure and neural transmission, and were verified in a further 1,507,153 individuals [ 100 ]. However, even with enough samples, GWASs still face severe challenges. A GWAS only marks the region of the genome and is not directly related to the potential biological function. In addition, a genetic association with the indicative phenotype of depression may only be part of many pathogenic pathways, or due to the indirect influence of intermediate traits in the causal pathway on the final result [ 101 ].

Given the diversity of findings, epigenetic factors are now being investigated. Recent studies indicated that epigenetic mechanisms may be the potential causes of "loss of heritability" in GWASs of depression. Over the past decade, a promising discovery has been that the effects of genetic information can be directly influenced by environment factors, and several specific genes are activated by environmental aspects. This process is described as interactions between genes and the environment, which is identified by the epigenetic mechanism. Environmental stressors cause alterations in gene expression in the brain, which may cause abnormal neuronal plasticity in areas related to the pathogenesis of the disease. Epigenetic events alter the structure of chromatin, thereby regulating gene expression involved in neuronal plasticity, stress behavior, depressive behavior, and antidepressant responses, including DNA methylation, histone acetylation, and the role of non-coding RNA. These new mechanisms of trans-generational transmission of epigenetic markers are considered a supplement to orthodox genetic heredity, providing the possibility for the discovery of new treatments for depression [ 102 , 103 ]. Recent studies imply that life experiences, including stress and enrichment, may affect cellular and molecular signaling pathways in sperm and influence the behavioral and physiological phenotypes of offspring in gender-specific patterns, which may also play an important role in the development of depression [ 103 ].

Brain Imaging and Neuroimaging Studies

Neuroimaging, including magnetic resonance imaging (MRI) and molecular imaging, provides a non-invasive technique for determining the underlying etiology and individualized treatment for depression. MRI can provide important data on brain structure, function, networks, and metabolism in patients with depression; it includes structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging, and magnetic resonance spectroscopy.

Previous sMRI studies have found damaged gray matter in depression-associated brain areas, including the frontal lobe, anterior cingulate gyrus, hippocampus, putamen, thalamus, and amygdala. sMRI focuses on the thickness of gray matter and brain morphology [ 104 , 105 ]. A recent meta-analysis of 2,702 elderly patients with depression and 11,165 controls demonstrated that the volumes of the whole brain and hippocampus of patients with depression were lower than those of the control group [ 106 ]. Some evidence also showed that the hippocampal volume in depressive patients was lower than that of controls, and increased after treatment with antidepressants [ 107 ] and electroconvulsive therapy (ECT) [ 108 ], suggesting that the hippocampal volume plays a critical role in the development, treatment response, and clinical prognosis of depression. A recent study also reported that ECT increased the volume of the right hippocampus, amygdala, and putamen in patients with treatment-resistant depression [ 109 ]. In addition, postmortem research supported the MRI study showing that dentate gyrus volume was decreased in drug-naive patients with depression compared to healthy controls, and was potentially reversed by treatment with antidepressants [ 110 ].

Diffusion tensor imaging detects the microstructure of the white matter, which has been reported impaired in patients with depression [ 111 ]. A recent meta-analysis that included first-episode and drug-naïve depressive patients showed that the decrease in fractional anisotropy was negatively associated with illness duration and clinical severity [ 112 ].

fMRI, including resting-state and task-based fMRI, can divide the brain into self-related regions, such as the anterior cingulate cortex, posterior cingulate cortex, medial prefrontal cortex, precuneus, and dorsomedial thalamus. Many previous studies have shown the disturbance of several brain areas and intrinsic neural networks in patients with depression which could be rescued by antidepressants [ 113 , 114 , 115 , 116 ]. Further, some evidence also showed an association between brain network dysfunction and the clinical correlates of patients with depression, including clinical symptoms [ 117 ] and the response to antidepressants [ 118 , 119 ], ECT [ 120 , 121 ], and repetitive transcranial magnetic stimulation [ 122 ].

It is worth noting that brain imaging provides new insights into the large-scale brain circuits that underlie the pathophysiology of depressive disorder. In such studies, large-scale circuits are often referred to as “networks”. There is evidence that a variety of circuits are involved in the mechanisms of depressive disorder, including disruption of the default mode, salience, affective, reward, attention, and cognitive control circuits [ 123 ]. Over the past decade, the study of intra-circuit and inter-circuit connectivity dysfunctions in depression has escalated, in part due to advances in precision imaging and analysis techniques [ 124 ]. Circuit dysfunction is a potential biomarker to guide psychopharmacological treatment. For example, Williams et al . found that hyper-activation of the amygdala is associated with a negative phenotype that can predict the response to antidepressants [ 125 ]. Hou et al . showed that the baseline characteristics of the reward circuit predict early antidepressant responses [ 126 ].

Molecular imaging studies, including single photon emission computed tomography and positron emission tomography, focus on metabolic aspects such as amino-acids, neurotransmitters, glucose, and lipids at the cellular level in patients with depression. A recent meta-analysis examined glucose metabolism and found that glucose uptake dysfunction in different brain regions predicts the treatment response [ 127 ].

The most important and promising studies were conducted by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, which investigated the human brain across 43 countries. The ENIGMA-MDD Working Group was launched in 2012 to detect the structural and functional changes associated with MDD reliably and replicate them in various samples around the world [ 128 ]. So far, the ENIGMA-MDD Working Group has collected data from 4,372 MDD patients and 9,788 healthy controls across 14 countries, including 45 cohorts [ 128 ]. Their findings to date are shown in Table 1 [ 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 ].

Objective Index for Diagnosis of MDD

To date, the clinical diagnosis of depression is subjectively based on interviews according to diagnostic criteria ( e.g. International Classification of Diseases and Diagnostic and Statistical Manual diagnostic systems) and the severity of clinical symptoms are assessed by questionnaires, although patients may experience considerable differences in symptoms and subtypes [ 138 ]. Meanwhile, biomarkers including genetics, epigenetics, peripheral gene and protein expression, and neuroimaging markers may provide a promising supplement for the development of the objective diagnosis of MDD, [ 139 , 140 , 141 ]. However, the development of reliable diagnosis for MDD using biomarkers is still difficult and elusive, and all methods based on a single marker are insufficiently specific and sensitive for clinical use [ 142 ]. Papakostas et al . showed that a multi-assay, serum-based test including nine peripheral biomarkers (soluble tumor necrosis factor alpha receptor type II, resistin, prolactin, myeloperoxidase, epidermal growth factor, BDNF, alpha1 antitrypsin, apolipoprotein CIII, brain-derived neurotrophic factor, and cortisol) yielded a specificity of 81.3% and a sensitivity of 91.7% [ 142 ]. However, the sample size was relatively small and no other studies have yet validated their results. Therefore, further studies are needed to identify biomarker models that integrate all biological variables and clinical features to improve the specificity and sensitivity of diagnosis for MDD.

Management of Depression

The treatment strategies for depression consist of pharmacological treatment and non-pharmacological treatments including psychotherapy, ECT [ 98 ], and transcranial magnetic stimulation. As psychotherapy has been shown to have effects on depression including attenuating depressive symptoms and improving the quality of life [ 143 , 144 ]; several practice guidelines are increasingly recommending psychotherapy as a monotherapy or in combination with antidepressants [ 145 , 146 ].

Current Antidepressant Treatment

Antidepressants approved by the US Food and Drug Administration (FDA) are shown in Table 2 . Due to the relatively limited understanding of the etiology and pathophysiology of depression, almost all the previous antidepressants were discovered by accident a few decades ago. Although most antidepressants are usually safe and effective, there are still some limitations, including delayed efficacy (usually 2 weeks) and side-effects that affect the treatment compliance [ 147 ]. In addition, <50% of all patients with depression show complete remission through optimized treatment, including trials of multiple drugs with and without simultaneous psychotherapy. In the past few decades, most antidepressant discoveries focused on finding faster, safer, and more selective serotonin or norepinephrine receptor targets. In addition, there is an urgent need to develop new approaches to obtain more effective, safer, and faster antidepressants. In 2019, the FDA approved two new antidepressants: Esketamine for refractory depression and Bresanolone for postpartum depression. Esmolamine, a derivative of the anesthetic drug ketamine, was approved by the FDA for the treatment of refractory depression, based on a large number of preliminary clinical studies [ 148 ]. For example, several randomized controlled trials and meta-analysis studies showed the efficacy and safety of Esketamine in depression or treatment-resistant depression [ 26 , 149 , 150 ]. Although both are groundbreaking new interventions for these debilitating diseases and both are approved for use only under medical supervision, there are still concerns about potential misuse and problems in the evaluation of mental disorders [ 151 ].

To date, although several potential drugs have not yet been approved by the FDA, they are key milestones in the development of antidepressants that may be modified and used clinically in the future, such as compounds containing dextromethorphan (a non-selective NMDAR antago–nist), sarcosine (N-methylglycine, a glycine reuptake inhibitor), AMPAR modulators, and mGluR modulators [ 152 ].

Neuromodulation Therapy

Neuromodulation therapy acts through magnetic pulse, micro-current, or neural feedback technology within the treatment dose, acting on the central or peripheral nervous system to regulate the excitatory/inhibitory activity to reduce or attenuate the symptoms of the disease.

ECT is one of most effective treatments for depression, with the implementation of safer equipment and advancement of techniques such as modified ECT [ 153 ]. Mounting evidence from randomized controlled trial (RCT) and meta-analysis studies has shown that rTMS can treat depressive patients with safety [ 154 ]. Other promising treatments for depression have emerged, such as transcranial direct current stimulation (tDCS) [ 155 ], transcranial alternating current stimulation (tACS)[ 156 ], vagal nerve stimulation [ 157 ], deep brain stimulation [ 158 ] , and light therapy [ 159 ], but some of them are still experimental to some extent and have not been widely used. For example, compared to tDCS, tACS displays less sensory experience and adverse reactions with weak electrical current in a sine-wave pattern, but the evidence for the efficacy of tACS in the treatment of depression is still limited [ 160 ]. Alexander et al . recently demonstrated that there was no difference in efficacy among different treatments (sham, 10-Hz and 40-Hz tACS). However, only the 10-Hz tACS group had more responders than the sham and 40-Hz tACS groups at week 2 [ 156 ]. Further RCT studies are needed to verify the efficacy of tACS. In addition, the mechanism of the effect of neuromodulation therapy on depression needs to be further investigated.

Precision Medicine for Depression

Optimizing the treatment strategy is an effective way to improve the therapeutic effect on depression. However, each individual with depression may react very differently to different treatments. Therefore, this raises the question of personalized treatment, that is, which patients are suitable for which treatment. Over the past decade, psychiatrists and psychologists have focused on individual biomarkers and clinical characteristics to predict the efficiency of antidepressants and psychotherapies, including genetics, peripheral protein expression, electrophysiology, neuroimaging, neurocognitive performance, developmental trauma, and personality [ 161 ]. For example, Bradley et al . recently conducted a 12-week RCT, which demonstrated that the response rate and remission rates of the pharmacogenetic guidance group were significantly higher than those of the non-pharmacogenetic guidance group [ 162 ].

Subsequently, Greden et al . conducted an 8-week RCT of Genomics Used to Improve Depression Decisions (GUIDED) on 1,167 MDD patients and demonstrated that although there was no difference in symptom improvement between the pharmacogenomics-guided and non- pharmacogenomics-guided groups, the response rate and remission rate of the pharmacogenomics-guided group increased significantly [ 163 ].

A recent meta-analysis has shown that the baseline default mode network connectivity in patients with depression can predict the clinical responses to treatments including cognitive behavioral therapy, pharmacotherapy, ECT, rTMS, and transcutaneous vagus nerve stimulation [ 164 ]. However, so far, the biomarkers that predict treatment response at the individual level have not been well applied in the clinic, and there is still a lot of work to be conducted in the future.

Future Perspectives

Although considerable progress has been made in the study of depression during a past decade, the heterogeneity of the disease, the effectiveness of treatment, and the gap in translational medicine are critical challenges. The main dilemma is that our understanding of the etiology and pathophysiology of depression is inadequate, so our understanding of depression is not deep enough to develop more effective treatment. Animal models still cannot fully simulate this heterogeneous and complex mental disorder. Therefore, how to effectively match the indicators measured in animals with those measured in genetic research or the development of new antidepressants is another important challenge.

Change history

17 may 2021.

A Correction to this paper has been published: https://doi.org/10.1007/s12264-021-00694-9

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Acknowledgments

This review was supported by the National Basic Research Development Program of China (2016YFC1307100), the National Natural Science Foundation of China (81930033 and 81771465; 81401127), Shanghai Key Project of Science & Technology (2018SHZDZX05), Shanghai Jiao Tong University Medical Engineering Foundation (YG2016MS48), Shanghai Jiao Tong University School of Medicine (19XJ11006), the Sanming Project of Medicine in Shenzhen Municipality (SZSM201612006), the National Key Technologies R&D Program of China (2012BAI01B04), and the Innovative Research Team of High-level Local Universities in Shanghai.

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Zezhi Li, Jun Chen & Yiru Fang

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Meihua Ruan

Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai, 200031, China

Shanghai Key Laboratory of Psychotic Disorders, Shanghai, 201108, China

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Li, Z., Ruan, M., Chen, J. et al. Major Depressive Disorder: Advances in Neuroscience Research and Translational Applications. Neurosci. Bull. 37 , 863–880 (2021). https://doi.org/10.1007/s12264-021-00638-3

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DOI : https://doi.org/10.1007/s12264-021-00638-3

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Depression: The Latest Research

If you’re one of more than 17 million adults or 3.2 million teens in the United States with major depression, you may know that treatment often falls short. The latest research on this common mental health disorder, also called clinical depression , aims to help you feel better faster, and with fewer side effects.

Right now, doctors don’t have a precise way to tell which medication is best for you. That’s part of the reason that many people with depression have to try more than one drug before they feel better.

Most antidepressants , the type of drug doctors often use to treat depression, take weeks to months to work. That means a lot of time can pass before you know if the treatment helps your symptoms. And, about 30% of people don’t feel better even after trying several medications. Doctors call this treatment-resistant depression.

Because this trial-and-error process takes time -- and sometimes doesn’t work -- depression can continue to affect your ability to live your life.

Recent numbers from the National Institute of Mental Health show that depression causes major distress and life disruption for more 63% of adults and more than 70% of teens with the disorder. Depression can also lead you to think more about or to attempt suicide.

Here’s a look at what researchers are studying now and how their work may help you if you have depression.

Fast-Acting Antidepressants

Fast-acting antidepressants can work in hours to help you feel better if you have depression or suicidal thoughts . The FDA in 2019 approved the first, a nasal spray called esketamine for treatment-resistant depression. A year later the FDA approved it for depression that includes suicidal thinking.

Esketamine, which you might take with a traditional antidepressant, is made from an older medication called ketamine. Doctors first used ketamine years ago as an anesthetic, a drug used to put people to sleep.

Ketamine can also rapidly improve depression but can cause serious side effects. These include out-of-body experiences and hallucinations . Some people abuse ketamine.

Esketamine can cause similar side effects and abuse problems. However, a 2021 review of studies published in Frontiers in Neuroscience reported that its effects are usually mild to moderate and don’t last long.

Scientists think esketamine improves depression by raising levels of glutamate, a chemical that helps brain cells communicate. Researchers are studying a number of newer agents that work on glutamate or on GABA, another of your brain’s chemical messengers. Scientists hope they may have fewer side effects than current options.

The FDA has given breakthrough therapy status to several experimental fast-acting antidepressants. The agency gives this status to speed development of drugs that may be able to outperform available treatments for serious conditions like depression.

More Exact Antidepressant Selection

Right now, doctors rely mostly on guesswork to choose your antidepressant. The latest research may give them tools that can help them pick the best treatment for individuals. Tests and tools that may cut down on trial and error in antidepressant treatment include:

Blood tests. Recent studies show blood tests that measure levels of certain proteins can predict whether particular antidepressants are likely to relieve your symptoms.

Gene tests. Tests for certain genes and how they affect your body’s response to specific drugs may help guide your doctor to the best treatment for you. In one recent study, people who took a 10-gene test to help direct treatment choice got better more often than those whose treatment was chosen without the test.

Brain imaging. Researchers are testing SPECT (single positron emission computed tomography ) and PET (positron emission tomography) to see if these imaging tools can help doctors choose the right drug for you. They show activity in different areas of your brain.

A recent review of studies found that using PET to look at how the brain uses glucose, or sugar, could help predict whether an antidepressant would improve a person’s depression.

Artificial intelligence (AI) that reads brain scans. Some scientists hope to treat depression with AI programs that can find patterns in EEG ( electroencephalogram ) scans. These scans measure your brain’s electrical activity. A 2020 Nature Biotechnology study found that an AI program could use a person’s EEG data to predict whether the most common type of antidepressant would work for them.

Causes of Depression

New knowledge about the causes of depression could open the door to new treatments. These biological processes may play a role:

Inflammation. Inflammation is your body’s natural defense against infections and injury. But when it happens when it shouldn’t or gets out of control it can lead to or worsen many different diseases. Depression is one of them, according to the latest research.

In the largest-ever study of depression and inflammation, published in 2021 in the American Journal of Psychiatry , scientists confirmed the link between the two. They found people with depression had more inflammation than those without the mental health disorder. This was true even after scientists accounted for other factors involved in depression.

This means that medications that lower inflammation may be helpful add-ons to antidepressant treatment. Lifestyle changes that can reduce inflammation, such as exercise and a healthy diet, may also help improve symptoms of depression .

The gut-brain connection . You’ve got trillions of bacteria and microorganisms, or microbes, in your gut. Some are helpful and some can be harmful. When the balance isn’t right, it can add to health problems, including depression and inflammation.

Some of the latest research has found that probiotics, which can give you a better balance of gut microbes, may also ease symptoms of depression. Probiotics are living bacteria found in fermented foods like yogurt or in supplements . They have few side effects.

Scientists need to learn more about how probiotics work in people with depression. Some studies find they work best when you use them along with antidepressant drugs. Research also suggests different strains, or types, of probiotics may help with different symptoms of depression.

In the meantime, it’s probably safe to try a probiotic for a month to see if it improves your mood. Just don’t stop any of your prescribed medications without the OK from your doctor.

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Understanding the Complex of Suicide in Depression: from Research to Clinics

Laura orsolini.

1 Psychopharmacology, Drug Misuse and Novel Psychoactive Substances Research Unit, School of Life and Medical Sciences, University of Hertfordshire, Hatfield, UK

2 Neomesia Mental Health, Villa Jolanda Hospital, Jesi, Italy

3 Polyedra, Teramo, Italy

Roberto Latini

Maurizio pompili.

4 Department of Neurosciences, Mental Health and Sensory Organs, Suicide Prevention Center, S. Andrea Hospital, Sapienza University, Rome, Italy

Gianluca Serafini

5 Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, IRCCS Ospedale Policlinico San Martino, Genoa, Italy

Umberto Volpe

6 Department of Clinical Neurosciences/DIMSC, School of Medicine, Section of Psychiatry, Polytechnic University of Marche, Ancona, Italy

Federica Vellante

7 Department of Neuroscience, Imaging and Clinical Science, Chair of Psychiatry, University of “G. D’Annunzio”, Chieti, Italy

Michele Fornaro

8 Department of Psychiatry, Federico II University, Naples, Italy

Alessandro Valchera

9 Villa S. Giuseppe Hospital, Hermanas Hospitalarias, Ascoli Piceno, Italy

Carmine Tomasetti

10 Department of Mental Health, National Health Service, Psychiatric Service of Diagnosis and Treatment, Hospital “SS. Annunziata” ASL 4, Giulianova, Italy

Silvia Fraticelli

Marco alessandrini, raffaella la rovere.

11 Department of Mental Health, National Health Service, Azienda Sanitaria Locale, Pescara, Italy

Sabatino Trotta

Giovanni martinotti, massimo di giannantonio, domenico de berardis.

12 Department of Mental Health, National Health Service, Psychiatric Service of Diagnosis and Treatment, Hospital “G. Mazzini”, ASL 4, Teramo, Italy

Amongst psychiatric disorders, major depressive disorder (MDD) is the most prevalent, by affecting approximately 15–17% of the population and showing a high suicide risk rate equivalent to around 15%. The present comprehensive overview aims at evaluating main research studies in the field of MDD at suicide risk, by proposing as well as a schematic suicide risk stratification and useful flow-chart for planning suicide preventive and therapeutic interventions for clinicians.

A broad and comprehensive overview has been here conducted by using PubMed/Medline, combining the search strategy of free text terms and exploded MESH headings for the topics of ‘Major Depressive Disorder’ and ‘Suicide’ as following: (( suicide [Title/Abstract]) AND ( major depressive disorder [Title/Abstract])). All articles published in English through May 31, 2019 were summarized in a comprehensive way.

Despite possible pathophysiological factors which may explain the complexity of suicide in MDD, scientific evidence supposed the synergic role of genetics, exogenous and endogenous stressors (i.e., interpersonal, professional, financial, as well as psychiatric disorders), epigenetic, the hypothalamic-pituitary-adrenal stress-response system, the involvement of the monoaminergic neurotransmitter systems, particularly the serotonergic ones, the lipid profile, neuro-immunological biomarkers, the Brain-derived neurotrophic factor and other neuromodulators.

The present overview reported that suicide is a highly complex and multifaceted phenomenon in which a large plethora of mechanisms could be variable implicated, particularly amongst MDD subjects. Beyond these consideration, modern psychiatry needs a better interpretation of suicide risk with a more careful assessment of suicide risk stratification and planning of clinical and treatment interventions.

INTRODUCTION

Suicide is a leading public health problem, being a leading cause of injury and death at a worldwide level, with approximately one million people who die by suicide per year and an estimate of around one suicide death occurring every 40 seconds [ 1 - 3 ]. Suicide is ranked as the 2th leading cause of death among people aged 10 to 34 and the tenth among all age groups [ 3 , 4 ]. Notably, suicidal behaviour has been implicated as a co-morbidity of several neuropsychiatric disorders, including borderline personality disorder, schizophrenia, bipolar disorder and major depressive disorder (MDD), being considered one of the leading causes of preventable death amongst people affected with mental disorders [ 5 ]. MDD is a common psychiatric disorder which is associated with significant personal suffering, physical and mental disability, with a global point prevalence being around 4.7% and a lifetime prevalence ranging from 3% in Japan to 16.9% in USA, whilst in other Western countries the figures varied between 8% and 17% [ 6 - 8 ]. The association between MDD and suicide attempts (SA) and/or ideation (SI) has been well documented, being SI and suicidal behaviour frequently reported during depressive episodes, with a suicide risk rate equivalent to around 15% [ 3 , 9 - 11 ]. Furthermore, epidemiological studies reported as well that MDD subjects with comorbid anxiety disorders were among the main predictors of SA amongst depressed suicide subjects [ 12 ]. However, the role of comorbid anxiety disorders, in increasing suicidal risk is still a matter of debate although it has been well recognized that the association between MDD and anxiety disorders appear to have more a synergic role in increasing suicidal risk [ 13 ]. Despite possible pathophysiological factors which may determine/ explain the correlation between depression and suicidal risk are not yet fully understood, it has been supposed the synergic role of genetics, exogenous and endogenous stressors (i.e., interpersonal, professional, financial, as well as psychiatric disorders), the hypothalamic-pituitary-adrenal (HPA)-stressresponse system, epigenetics, the involvement of the monoaminergic neurotransmitter systems, particularly the serotonergic ones, the role of specific neurotrophins, such as the Brain-derived neurotrophic factor (BDNF), etc [ 14 - 16 ]. Overall, suicide is a complex phenomenon and, according to the World Health Organization [ 3 ], suicidal behaviour may be defined as “a range of behaviours that include thinking about suicide (suicidal ideation, SI), suicide threat (ST), planning for suicide (SP), attempting suicide (SA) and suicide itself (CS)” ( Table 1 ). The complex phenomenon is not due to a simple etiology but rather is the result of a complex interaction of genetic vulnerability, stress factors, underlying psychopathology and social aspects, even though the precise pathophysiological mechanisms underlining the suicide behaviour is not yet fully understood and probably not completely investigated. Being literature published so far on suicide risk within patients affected with MDD extremely varied and broad, the present paper aimed at overviewing only a selected range of suicide risk predictors in MDD subjects, by analysing both research and clinical evidence, as primary objective, to try identifying a pathophysiological as well as clinical perspective, able to answer to questions regarding performing preventive tools (if any), easy to measure and useful for clinical practice. Furthermore, as secondary objective, a schematic suicide risk stratification proposal together with a useful flow-chart for planning suicide preventive and therapeutic interventions has been here proposed for clinicians working in the field of Mental Health, particularly with those subjects affected with mood disorders at higher suicidal risk.

Definitions and suicide risk formulation

Suicidal ideation (SI)	Thoughts, fantasies and wishes about ending one’s own life	If a patient states that SI is present, the clinician is obligated to explore SI furtherly by posing the following questions:
			• Content (active thoughts of suicide vs. passive wishes for death)
			• Content (planning or not?)
			• Duration of SI
			• Frequency of SI
			• Intensity of SI
			• Controllability or not?
			• Expectations about death (i.e., thoughts of reuniting with lost significant others; thoughts of evoking punishment of others; the need to escape a painful physical or psychological situation; thoughts of harming others first before harming him or herself)
Suicide threat (ST)	Thoughts of engaging in self-injurious behavior that are verbalized and intended to lead others to think that one wants to die, despite no intention of dying (e.g., ‘if you leave me, I will kill myself ’)	If patient manifests a ST, clinicians should furtherly investigate the followings:
Suicide threat (ST)			• Are there non-suicidal self-injurious thoughts? e.g., are there any thoughts of engaging in self-injurious behavior characterized by the deliberate destruction of body tissue in the absence of any intent to die or not?
Suicide plan (SP)	Having plans on how to end one’s own life	If a patient has a SI, clinicians should carefully investigate the presence and characteristics of SP as following:
			• Has a specific plan been formulated or implemented, including a specific method, place and time?
			• What is the anticipated outcome of the plan?
			• Are the means of committing suicide available or readily accessible?
			• Does the patient know how to use these means?
			• What is the lethality of the plan? (patient’s conception of lethality vs objective lethality?)
			• What is the likehood of rescue?
			• Have any preparations been performed (e.g., changing wills, suicide notes, etc.) or how close has the patient come to completing the plan?
			• Has the patient practiced the suicidal act or has an actual attempt already been made?
			• Is there a history of impulsive behaviours or SUD that might increase impulsivity?
			• What is the patient’s ability to control impulsivity?
Suicide attempt (SA)	Self-destructive act with intent to end one’s own life, even though is not fatal	If patient did a SA, clinicians should furtherly investigate the followings:
			• Is a self-injurious behaviour accompanied by any intent to die or not? If yes, it is a real SA
			• Is a non-suicidal self-injurious behaviour? i.e., a deliberate destruction of body tissue in the absence of any intent to die?
			• Investigate if patient had a previous SA and/or a family history of a SA or CS
			• Managing patient as follows:
			Medical stabilization
			Inpatient hospitalization
Completed suicide (CS)	Self-injurious behaviour with intent to end one’s own life and is fatal	Clinicians should apply post-suicide interventions, i.e., helping family, friends and coworkers understand why suicide victims killed themselves and decreasing the assumption of inappropriate guilt for the death
			• Identify ‘survivors’ at risk of suicide
			• Prevent PTSD, complicated grief, depressive symptoms

SUD: substance use disorder, PTSD: posttraumatic stress disorder

MATERIAL AND METHODS

Search sources and strategies.

A broad overview has been here conducted with literature searches performed by using PubMed/Medline. We combined the search strategy of free text terms and exploded MESH headings for the topics of ‘Major Depressive Disorder’ and ‘Suicide’ as following: (( suicide [Title/Abstract]) AND ( major depressive disorder [Title/Abstract])). All articles published in English have been properly selected and screened. Studies published through May 31, 2019 were here considered. In addition, secondary searches were performed using the reference listing of all eligible as well as relevant articles and consultation with experts in the field and or manual search.

Study selection, data extraction and management

We considered studies evaluating the Suicide in MDD, by excluding other mental disorders in comorbidity, including anxiety disorders and/or bipolar disorder and/or psychotic disorders. We examined all titles and abstracts, and obtained full texts of potentially relevant papers. After this first screening, we followed a two-step process: 1) in a first phase, we specifically selected all papers containing relevant data on suicide risk factors in MDD subjects (with the aim to identify which suicide risk factors better investigate in the next step, with the aim to address those aspects useful for preventive strategies); 2) in the second phase, we specifically selected a range of macro-categories to be better deepened, as follows: 1) The role of genetic vulnerability and epigenetic modulation in determining suicide risk in MDD subjects; 2) the role of HPA axis in suicide risk in MDD subjects; 3) the role of serotoninergic system in suicide risk in MDD subjects; 4) the role of neurotrophins and neuroplasticity in suicide risk in MDD subjects; 5) the role of neuro-immunological mediators/ biomarkers in suicide risk in MDD subjects; 6) the role of metabolic factors (i.e., lipid profile) in suicide risk in MDD subjects; 7) the role of cognitive domains and neuropsychological dimensions in suicide risk in MDD subjects; 8) the role of personality traits in suicide risk in MDD subjects; 9) evidences coming from neuroimaging studies in suicide risk in MDD subjects. Working independently and in duplicate, two reviewers (LO and DDB) read the papers and determined whether they met inclusion criteria. LO and DDB, independently extracted the data on the above subcategories and selected relevant data useful for the present overview. Disagreements were resolved by discussion and consensus with a third member of the team (FV). All English-language articles identified by the data sources, reporting data on suicide in MDD, both from a preclinical and clinical perspective, have been considered for the present overview. Data collected were then summarized according to the abovementioned categories.

Risk factors

Although the aetiology of suicide and MDD is certainly complex, some suicide risks factors are thought to contribute to the risk of suicidal behaviour, including biological/individual, psychological social, clinical/symptomatological and environmental factors ( Table 2 ) [ 3 , 14 , 17 , 18 ].

Suicide risk and protective factors in MDD

	Risk factors		Protective factors
Factors affecting threshold for suicidal behaviour
	Demographic and individual risk factors		Demographic and individual risk factors
		• Male gender		• No personal history of attempted suicide
		• Younger and/or older age		• No family history of suicide and/or attempted suicide
		• Personal history of attempted suicide		• No personal and/or family history for psychotic symptoms and/or disorders
		• Positive family history of suicide		• No personal and/or family history for SUD and/or AUD
		• Marital isolation		• Religious or moral constraints
		• Chronic physical illness		• Concern about social disapproval
		• Parental loss through death before age 11		• Better coping skills
		• Child history of physical or sexual abuse		• Feelings of responsibility towards family
		• Corporal punishment in adolescence		• Living with children under age 18
	Symptom risk profile risks			• Supportive relationships
		• Presence of hopelessness		• Positive and valid therapeutic alliance
		• Presence of low self-esteem		• Better impulsivity control
		• Feelings of whortlessness		• Better emotional regulation
		• Feelings of helplessness
		• Feelings of entrapment
		• Anhedonia
		• Cognitive rigidity
		• Impaired problem solving and/or decision making
		• Impulsive aggressive personality trait
		• Early onset of MDD
		• First episode of MDD
		• Comorbid SUD and/or AUD
		• Comorbid BPD
Suicide risk factors as triggers
	Demographic and individual risk factors		Symptom protective risks
		• Social, financial or family crisis or loss		• Good self-esteem
		• Contagion or recent exposure to suicide		• Self-efficacy
		• Social support lacking		• Good problem-solving skills
	Symptom risk profile risks			• Willingness to seek help
		• Comorbid anxiety symptoms		• Positive coping skills
		• Comorbid panic disorder		• Emotional stability
		• Acute alcohol and/or substance intoxication		• Responsibility to family
		• Presence of psychotic symptoms		• Developed self-identity
		• Severity of depressive episode of MDD		• Healthy lifestyle choices
		• Post-partum
	Circumstantial risk profile risks		Circumstantial risk profile risks
		• Reduced or absent desire to live		• Absence of SI, SP, SB or SHB
		• Active SI		• No feelings of hopelessness, desire to die
		• Presence of a SP		• Good connectedness
		• Presence of SB or SHB		• Good therapeutic adherence
		• Acute alcohol and/or substance intoxication		• Positive therapeutic relationship and alliance
		• Unresolvable problems		• Good future planning
		• Presence of auditory imperative hallucinations (order to suicide oneself)		• Solving of previous critical problems
				• Positive social support
				• Moral objections towards SB
				• Fear of social disapproval towards SB

MDD: major depressive disorder, SUD: substance use disorder, AUD: alcohol use disorder, BPD: borderline personality disorder, SI: suicidal ideation, SP: suicide planning, SB: suicidal behaviour, SHB: self-harm behaviour

Genetic vulnerability and epigenetic modulation

Family studies suggest that SA and fulfilled suicide show familial accumulation [ 19 ], with heritability estimates of suicidal behavior between 30% and 55% and an increased risk of at least two-fold [ 20 - 23 ]. Inherited genetic differences have a relevant role in suicidality, as demonstrated by twin studies, particularly that monozygotic twins’ concordance for the CS is notably higher than in dizygotic twin pairs, being respectively 24.1% and 2.8% [ 23 - 25 ]. A genome-wide association study (GWAS) of suicidal thoughts and behaviour in MDD, indicated a polygenetic architecture with multiple genes implicated even though with small effects [ 26 ]. However, although several GWAS studies have been conducted on SA examining individuals with MDD, comparing suicide attempters with non-attempters and testing for genetic variants that might contribute independently to SA [ 27 - 31 ], epidemiological evidence suggests that the inheritance of suicidality is likely to be independent of the underlying MDD, by supporting a distinct genetic contribution to suicidality [ 32 ]. Polygenic risk scores for SA have shown modest predictive capability in independent samples, and small but significant single-nucleotide polymorphism (SNP) heritability estimates for SA have been reported [ 28 , 33 , 34 ]. A significant association between two SNPs (rs12415800 and rs4746720 in 3’UTR) and CS amongst MDD women aged more than 50 years compared to healthy controls [ 35 ]. The FKBP5 gene which encodes the FK506 binding protein 51 (FKBP51) and participates as regulator of the glucocorticoid receptor (GR) activity, has received an increasing attention as well, in relation to the suicidal behaviour [ 36 , 37 ]. FKBP51 is an important modulator of stress response [ 38 ]. FKBP5 SNPs have been associated with an increased risk of MDD and SA [ 39 - 43 ]. Amongst the serotonin system candidate genes for SB, many genetic association studies have focused on the SLC6A4 (Solute Carrier Family 6, Member 4) gene [ 44 , 45 ], located on chromosome 17 (17q11.2) which encodes for the serotonin transporter, a transmembrane presynaptic protein involved in the reuptake of the released serotonin from the synaptic cleft [ 46 ]. Moreover, the transcriptional activity of SLC6A4 gene is modulated by a 44 base-pair insertion/ deletion polymorphism, commonly known as 5-HTTLPR (serotonin transporter linked polymorphic region polymorphism-rs4795541), located upstream of the transcription start site. Genetic studies demonstrated that depressed suicide victims had a smaller amount of serotonin transporters in the PFC, hypothalamus and brainstem compared to not suicide MDD subjects [ 47 ]. Moreover, a recent GWAS study identified GWS SNPs in proximity to genes involved in the regulation of circadian clock rhythms (ARNTL2), anaerobic energy production (LDHB) and catecholamine catabolism (FAH), amongst MDD patients with SA [ 48 ]. Therefore, further studies should better evaluate which is common (if any) genetic load in MDD subjects at risk for SA and/or SC and the correlation (if any) is dependent or independent.

Furthermore, distal (predisposing) factors interact with proximal (precipitating) factors in determining suicidal event, i.e., genetic predisposition/vulnerability, early adversities and associated epigenetic modifications, and together may modulate suicidal behaviour and personality traits associated to suicide in MDD [ 49 ]. Early life adversity is considered one of the strongest risk factor for SA, i.e., exposure to maltreatment during the early phases of a person’s development increases the risk of SB thought the lifespan within 2- to 5-fold times [ 50 ]. In fact, these events may epigenetically regulate key emotional and behavioural systems which in turns may contribute to the development of MDD and suicide behaviour, mainly by inducing a DNA methylation [ 51 - 54 ]. A study investigated whether epigenetic modifications of stress-related genes play a role in suicidal behaviour and whether these modifications are common to or independent of MDD, by reporting a significant increase I DNA methylation of stressrelated genes including BDNF, NR3C1, FKBP5, and CRHBP amongst MDD subjects (with and without SI) compared to healthy controls, together with a concomitant decrease in expression of BDNF, NR3C1, and FKBP5 transcript variant 1, 2 and 3 (but not 4) amongst MDD-suicide subjects compared to healthy controls [ 54 ].

The hypothalamic-pituitary-adrenal axis

The HPA axis is the major neuroendocrine system involved in the regulation of the body’s response to stress [1. The stressrelated theory of MDD states that chronic stress may lead to long-term activation of the HPA axis, which may result in reductions in the volume or impaired function of the hippocampus [ 55 ]. The corticotrophin-releasing hormone (CRH) and vasopressin are hormones released from neurosecretory nerve terminals and act synergistically to stimulate the secretion of stored adrenocorticotrophic hormone (ACTH) from corticotrophin cells, which in turns stimulates biosynthesis of corticosteroids [ 14 ]. Prospective biological studies suggest that dysfunctions in the HPA axis have some predictive power for suicide in MDD [ 14 ]. Subjects affected with MDD who manifest a suicidal behaviour show an increased level of CRH in the cerebrospinal fluid compared to not suicide MDD subjects [ 56 ]. Several studies reported that cortisol non-suppression in response to the dexamethasone challenge test represents a strong predictor of suicidal behaviour in MDD [ 14 , 57 - 60 ].

Serotonergic system

The serotonin system has been widely investigated in studies of both MDD subjects and suicidal behaviour. Postmortem studies of the suicidal brains have shown evidence of serotonin dysfunction amongst MDD subjects [ 61 - 63 ]. Serotonin transporters have been reported to be reduced in the prefrontal cortices, hypothalamic, occipital cortices, and brainstems of subjects affected with MDD who have committed suicide [ 45 ]. Studies demonstrated a lower concentration of the serotonin metabolite 5-hydryndolacetic acid (5-HIAA) in the cerebrospinal fluid of depressed patients prone to develop suicidal behaviour [ 64 ] as well as lower levels of serotonin (5-HT) and 5-HIAA in the brainstem of suicide victims [ 65 - 67 ], compared to non-suicide MDD subjects. The serotonin transporter (5-HTT) is the major determinant of 5-HT inactivation following 5-HT release at synapses, a decrease in 5-HTT has been observed in suicide victims with MDD [ 68 ]. Some postmortem studies have reported increased 5-HT2A receptor binding in the prefrontal cortex of suicidal individuals with MDD [ 69 , 70 ]. A meta-analysis of prospective biological studies estimated the odds ratio for the prediction of suicide completion to be 4.5-fold greater for MDD subjects with low levels of 5-HIAA in the cerebrospinal fluid compared to subjects with high levels of 5-HIAA [ 71 ]. The serotonin transporter gene is located on chromosome 17q11.1-q12 and two polymorphisms have been reported [ 72 ]. Electroencephalographic (EEG) changes and various polysomnographic findings can reflect the central serotonin activity and demonstrate that high suicidality score has been associated with shorter REM (rapid eye movement) latency [ 73 ]. An increase of REM time and activity in MDD subjects with SA has been associated with reduced serotonin activity or 5-HIAA levels in cerebrospinal fluid [ 74 ].

Neuroplasticity, brain-derived neurotrophic factor and nerve growth factor

Several theories have been proposed to explain the biological substrates of suicide behaviour, including the role of specific neurotrophins, such as the brain-derived neurotrophic factor (BDNF) and the nerve growth factor (NGF) [ 75 - 80 ]. The “neurotrophic hypothesis” of MDD seeks to understand depression through regulatory proteins (e.g., BDNF) which promote neuroplasticity, adult neurogenesis and neurotransmission [ 81 - 83 ]. Changes in brain structures and function, such as reduced neuronal cell numbers, density and size, as well as decreased cortical thickness and changes in synaptic circuits, may be associated with MDD, stress and suicidal behaviour [ 84 , 85 ]. In fact, both MDD and suicidal behaviour involve altered neural plasticity, resulting in an abnormal central nervous system response to stressors and environmental outcomes [ 79 ]. The neurotrophic factors activate the neuroendocrine cells and the neuronal responses, by regulating the growth and proliferation of glial cells, modulating the activity of endogenous opioid peptides, activating the HPA axis, exerting effects on corticotrophin releasing hormone-producing neurons, and acting on the endothelial cells of the cerebral vasculature or on the glial cells in the circumventricular organs [ 86 ]. Furthermore, the neurotrophic factors may influence as well as the metabolism of the noradrenergic, serotonergic and dopaminergic systems [ 87 ]. It has been as well supposed that low BDNF levels relate to suicidality rather than to MDD specifically [ 88 ], even though low BDNF levels have been reported in MDD subjects who attempted suicide when compared to non-suicidal MDD and healthy controls [ 77 , 80 , 89 ]. A recent study found that serum BDNF levels were significantly lower in MDD with SI compared to MDD without SI but were not significantly correlated with MDD severity [ 90 ]. CREB1 (cyclic adenosine monophosphate response element binding protein) is a transcription factor that controls the transcription of numerous neuronally expressed genes such as BDNF [ 91 - 95 ]. There is evidence for CREB1 playing an important role in the neurobiology of suicidal behaviour [ 96 - 99 ]. Nerve growth factor (NGF) is a neurotrophin, produced in the cortex, hippocampus and hypothalamus as well as in the peripheral nervous system and immune system [ 100 ]. Neurotrophins generally are implicated in neuronal survival, differentiation, connectivity and plasticity during development and adulthood [ 101 ]. Clinical studies have detected reduced levels of NGF in patients with MDD and suicide victims, particularly in the prefrontal cortex and the hippocampus [ 101 - 104 ], areas implicated in the cognition and mood regulation as well as in the pathophysiology of affective disorders and suicide [ 102 ]. Furthermore, the hippocampus is an area affected by early stress, which in turns is implicated in the suicidal behaviour [ 101 ]. However, studies specifically investigating NGF, MDD and suicide risk are scarce and extremely heterogeneous from a methodological point of view, hence, further studies should be carried out in order to better clarify the potential role of NGF in increasing suicide risk amongst MDD subjects.

Neuro-immunological markers

Inflammatory mediators and oxidative stress leading to excitotoxicity may play a critical role in the pathophysiology of MDD and suicide, including an imbalance between proinflammatory cytokines (i.e., interleukin IL-1b, IL-2, IL-6, interferon-gamma INF-γ) and tumor necrosis factor-alpha (TNF-α) versus anti-inflammatory cytokines (i.e., IL-4 and IL-10); or increased levels of pro-inflammatory cytokines and level of severity of MDD [ 105 ]. Therefore, a dysregulation of immune response could be a contributing factor to MDD at risk of suicide, including the vascular endothelial growth factor (VEGF) and kynurenine levels [ 105 , 106 ]. Moreover, several findings suggest that suicidal MDD patients display a distinct peripheral blood cytokine profile compared to non-suicidal patients with MDD, being specific changes in inflammatory cytokines levels most frequently associated with MDD and suicidality [ 105 ]. In particularly, lower IL-8 levels linked to a reduced neuroprotection and higher IL-13 levels have been found in MDD patients with SI compared to those MDD subjects without [ 105 ]; whilst increased levels of interferon-gamma (INF-γ) and IL-6 appeared to be more robustly associated with SA in MDD [ 107 ], even though previous studies evaluating suicidal MDD patients reported decreased levels of INF-γ and IL-6, compared with non-suicidal MDD patients [ 108 , 109 ]. Indeed, other studies are quite conflicting in findings, for instance, high IL-4 levels have been found in MDD women with CS, suicidal MDD patients and both suicidal and nonsuicidal MDD subjects [ 105 ]. Suicidal MDD subjects, particularly those who were violent SA, were are likely to own higher IL-6 and lower IL-2 levels compared to non-suicidal MDD subjects and healthy controls [ 105 ]. Furthermore, higher TNF-α levels have been reported as well in suicidal MDD subjects compared to non-suicidal MDD and healthy controls, even though some evidence appear to be contrasting [ 105 ]. A key biological pathway which may link inflammation and MDD is the activation of the HPA axis by cytokines, mainly due to psychosocial stressors, resulting in increased cortisol levels and release of monoamines which may initially enhance inflammatory signaling pathways and active immune system. However, not all studies demonstrated a positive correlation between inflammatory cytokines and suicidal behaviour in MDD subjects, hence, further studies should better investigate this correlation (if any). For a more complete overview, see Marini et al [ 110 ].

Metabolic pattern

Large randomized clinical trials of cholesterol-lowering drugs and meta-analytic studies reported an increase in violence-related deaths, including suicide, amongst individuals taking serum cholesterol-lowering medications [ 111 , 112 ]. Suicidal MDD patients tend to have dysregulated lipid levels compared with non-suicidal patients [ 113 - 115 ]. Clinical studies carried out on psychiatric subjects, including MDD subjects, revealed a relationship between lower total cholesterol levels and suicidal behaviour [ 116 - 120 ]. Lower levels of total cholesterol in MDD patients with SI, compared to non-suicide MDD subjects, have been reported in a recent meta-analysis [ 121 ]. Low triglycerides, low levels of low-density lipoprotein (LDL) and low levels of high-density lipoprotein (HDL) are significantly related to suicidality in MDD patients [ 122 , 123 ]. A proposed hypothesis suggested that reduced cholesterol levels may reduce serotonin precursors and modify the functions and viscosity of serotonin receptors and transporters, by increasing one’s tendencies towards impulsive, aggressive, and suicidal behaviour. Low serum triglycerides concentrations may also alter serotonin metabolism, leading to poor control of aggressive impulses in MDD subjects, by resulting in an increased suicidality risk [ 124 ]. Another hypothesis state that low peripheral and central cholesterol can reduce lipid viscosity of neuronal cell membranes, which may decrease exposures of pre-synaptic serotonin transporter or post-synaptic serotonin receptors [ 125 ]. Similarly, further studies should better investigate the role of metabolic (including lipid) profile in determining an increased suicide risk amongst MDD patients, and evaluate how anti-cholesterol and anti-dyslipidemia drugs may reduce suicidality in MDD patients.

Neuropsychological and neurocognitive factors

Patients with MDD show cognitive deficits in neuropsychological domains, such as visual and verbal memory, working memory, attention, executive function and processing speed [ 126 ], being the executive functioning impairment the most prominent [ 127 - 130 ]. More specifically, impairments in cognitive control (i.e., the ability to regulate one’s own thoughts and actions in order to achieve internal goals and allows flexible adaptation of behaviour to changing environments), has been strongly associated with MDD-related pathology [ 131 - 133 ]. Impaired cognitive control abilities have been correlated as well with high suicide rate amongst MDD subjects [ 128 , 132 - 137 ]. In fact, neurocognitive deficits are presumed to increase suicide risk as they may determine an incorrect appraisal of one’s life situation and an impaired decision-making [ 133 , 136 ]. One of the neuropsychological domains strongly impaired in MDD regards the executive function, a set of self-regulatory cognitive processes essential for adaptive behaviour [ 137 - 143 ].

Temperament, character and personality traits

The suicide risk factors implicated in MDD subjects may include distal factors (i.e., those risk factors not strictly related to current episode), such as family history of suicide, early onset of mood disorders, alcohol/substance abuse, adverse early life events, and specific personality traits; as well as proximal factors (i.e., related to current or past mood episode), including hopelessness levels, impulsiveness, SI, severity of current episode within MDD, and recent life events ( Table 2 ). Overall, personality refers to individual features in characteristic patterns of thinking, feeling and consequently behaviours and belong to the stress-diathesis model for suicidal behaviour, being significant influencing factors able to discriminate if a suicidal behaviour emerges within a recrudescence of a psychiatric condition or whether is a situation-oriented process [ 144 ]. In fact, specific personality traits, temperaments and characters may predispose a subject with MDD to develop a SI and/or SA or SC. According to the Cloninger’s psychobiological model of temperament and character [ 145 ], MDD subjects who had recent SA during a depressive episode exerted different personality profile compared to non-suicidal control group [ 144 ]. In fact, MDD subjects suicide attempters, showed significantly higher scores on harm avoidance (HA) (i.e., a tendency to respond intensely to signals or aversive stimuli) and significantly lower scores in self-directedness (SD), cooperativeness (CO) and persistence (PS) when compared to the non-suicidal group [ 144 ]. HA is highly heritable temperament dimension linked to the serotonergic system which is in turns altered in suicidal behavior, as abovementioned. SD encompasses personality features like responsibility, self-acceptance, effectiveness; hence, low SD levels have been associated with immaturity, poor self-integration, ineffectiveness and destructiveness which are related to suicidality [ 145 ]. Similarly, the alexithymia construct applied to MDD subjects, seemed to demonstrate a correlation between alexithymia traits, MDD severity and increased risk of SI and more severe SA [ 146 , 147 ].

Neuroimaging studies

Neuroimaging studies show changes in several brain areas associated with an increased vulnerability to suicidality [ 148 ]. It has been documented that brain dysfunctions located in temporal, parietal and frontal (specifically dorsolateral and orbitofrontal areas) cortices are described in the suicidal brain [ 148 - 154 ]. Moreover, three structural areas, e.g., the left superior temporal gyrus, rectal gyrus, caudate nucleus; and three functional areas, e.g., right cingulate gyrus, the anterior cingulate and posterior cingulate have been identified as implicated in an increased suicidal vulnerability [ 151 , 155 - 157 ]. A smaller volume of the orbitofrontal cortex (right and left), lower left ventrolateral prefrontal cortex (VLPFC), frontal and temporal lobe volumes were observed amongst MDD patients with SA [ 158 - 160 ]. Reduced grey matter volumes in the frontal, parietal, temporal, insula cortices, left angular gyrus, lentiform nucleus, midbrain, nucleus accumbens, cerebellum have been reported amongst MDD subjects with SA and have been correlated with higher hopelessness levels and lower social support seeking [ 161 - 163 ]. Right amygdala volumes and lower hippocampal volumes are reported amongst MDD subjects with SA compared to non-suicide attempters [ 158 , 160 , 164 ]. Studies carried out on a sample of MDD subjects by using functional magnetic resonance (fMRI) reported a greater resting state functional connectivity in the amygdala, a greater amplitude of low-frequency fluctuation (ALFF) in the right superior temporal gyrus, left middle temporal gyrus and left middle occipital gyrus, whilst a lower ALFF in the left superior frontal gyrus, right ventral medial frontal gyrus and left middle frontal gyrus, amongst MDD subject with SA compared to MDD without SA [ 165 - 167 ]. Further fMRI studies described a reduced left lateral orbitofrontal cortex (OFC) and occipital cortex activation during risky choices, a higher activation on the left hippocampal and left middle temporal gyrus, amongst MDD with SA [ 168 - 170 ]. Moreover, a dysfunctional emotion processing neural circuitry has been documented amongst MDD subjects with SA [ 171 ]. In addition, PET studies reported a lower 5-HTT binding in the midbrain, but not in the ventral PFC or the anterior cingulate network, reduced SERT binding potential in the midbrain/pons and putamen, amongst MDD with SA [ 172 , 173 ]. A SPECT study found reduced SERT binding in the OFC, temporal areas, midbrain, thalamus, basal ganglia and cerebellum of MDD subjects with SA, which in turns are correlated with an increased impulsivity [ 174 ].

DISCUSSION AND CONCLUSION

Suicide behaviour is highly prevalent amongst patients with MDD [ 11 , 175 ], however, depression per se is not a useful tool for a proper understanding of the complexity of suicide, and SI is not a proxy for the diagnosis of MDD [ 176 ]. The uniqueness of each patient determines the variability of the threshold for sustaining mental pain, a condition dependent on personal experiences, emotional states and intimate situation experienced from childhood [ 175 , 176 ]. Hence, someone could argue that human sadness, most as a reaction to a loss, grief, somewhat crisis, etc., could share features with MDD even in the absence of a validated psychiatric diagnosis [ 177 , 178 ]. In line with this, the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) states, “Diagnosis of a mental disorder should have clinical utility” but “the diagnosis of a mental disorder is not equivalent to a need for treatment. Need for treatment is a complex clinical decision that takes into consideration symptom severity, symptom salience (e.g., the presence of suicidal ideation), the patient’s distress (mental pain)” and “Clinicians may thus encounter individuals whose symptoms do not meet full criteria for a mental disorder but who demonstrate a clear need for treatment or care. The fact that some individuals do not show all symptoms indicative of a diagnosis should not be used to justify limiting their access to appropriate care [ 176 , 179 ]."

The present comprehensive review aimed at investigating only a selection of the myriad of suicide risk factors supposed to be implicated in the suicidality amongst MDD subjects. Overall, suicidality is indeed a highly complex and multifaceted phenomenon in which a large plethora of mechanisms and processes could be variable implicated, including the dysregulation of HPA activity, genetic load, epigenetics, cholesterol and triglyceride profile, specific neurocognitive and neuropsychological impaired domains, some personality traits and characters, sometimes state-dependent, and so on [ 8 , 23 , 41 , 43 , 65 , 78 , 110 , 112 , 114 , 128 , 130 , 144 , 145 , 148 , 150 , 175 , 176 ]. However, somewhat contrasting and sometimes inconclusive findings have been so far published, by enlarging the plethora of research fields yet to be furtherly deepened and investigated in the field of suicide risk amongst MDD subjects. As abovementioned, great deal of research has focused on dysfunction of the HPA axis and on alterations of main neurotransmitter system as well as a set of neuro-inflammatory modulators, even though concluding findings are still unclear [ 14 , 55 - 60 ]. Indeed, the recently investigated and interesting role of glutamatergic involvement may play a significant role, given recent antisuicidal findings with NMDA antagonist esketamine [ 180 , 181 ]. Further evidences appear to emerge at the genetic and epigenetic level, with a series of supposed proximal and distal suicide risk factors associated with various endophenotypes implicated in suicidality amongst MDD subjects [ 19 - 54 ]. Therefore, assessing suicidality amongst MDD subjects requires a multidimensional approach, which takes into account suicidality factors at every level, preclinical, neurobiological, neurochemical, clinical and psychopathological. Overall, key suicide and protective risk factors amongst patients with MDD have been clearly recognized and analyzed ( Table 2 ). However, one could argue that SA would be indeed different with CS, regarding a suicide risk stratification as it reflects a different underpinning biological mechanism. Indeed, the most significant predictors of CS appeared to be represented by the presence of a history of previous SA, reaching an odds ratio (OR) of around 4.84 [ 182 ]. Therefore, the identification of a range of suicide risk factors, particularly regarding a previous (family and personal) history of SA is clinically relevant for clinicians and should be always considered for preventing CS amongst MDD patients. Beyond these consideration, modern psychiatry needs a better interpretation of suicide risk with a more careful assessment of suicide risk stratification and planning of clinical and treatment interventions, particularly amongst special population [ 183 , 184 ]. Therefore, authors here propose a stratification model of suicide risk accompanied with a list of suggested recommendations regarding interventions and treatments to be planned, useful for clinical practice, particularly for those working in Mental Health ( Table 3 ).

Proposal for suicide risk stratification and recommended interventions

‘White code’–no suicide risk
	• Absence of SI	• Clinical observation
	• Negative personal and/or family history of suicide, previous SA	• Periodic suicide risk evaluation (including the occurrence of new situations, e.g., the presence of suicide risks before not present)
	• Symptomatological stability
	• Absence of specific suicide risk (Table 1)
‘Green code’–low suicide risk
	• Presence of SI (occasional, inconstant, fleeting, reported to clinician with scarce credence/conviction (e.g., with the aim at requesting attention and help; e.g., present but criticized by the patent in a credible manner)	• Careful and periodic clinical observation by clinicians and all components of the multi-disciplinary team (i.e., physicians, nurses, psychiatric rehabilitators, auxiliary staff, psychologists, etc.) of the patient, especially if he/she is almost silent (and/or he/she does not ask for help/support)
	• Acute depressive episode in MDD, mild severity (not stable, not remitted, without comorbid anxiety and/or mixed symptoms)	• Actively listen to or support even only with our presence, by ensuring a peaceful atmosphere and inviting the patient to call and ask for help in the case he/she may experience negative thoughts
	• Positive family history of suicide and/or SA in MDD	• Developing a good therapeutic alliance and relationship
	• Positive personal history of SHB and/or ST (single and/or recurrent, with low lethality)	• Encouraging the expression of thoughts and/or feelings (also negative)
	• Negative personal history for SA	• Providing information and support to patient and his/her family members regarding the management of a potential emotional crisis and/or instability and about the alternative coping strategies useful for managing and solving critical problem(s)
		• Carefully observing family, personal and group dynamics and identifying specific potential trigger factors
		• Monitoring and alerting about the occurrence of potential symptoms and/or behaviours at risk (e.g., anxiety, agitation, irritability, hypervigilance and/or mood instability)
		• If possible, do not leave the patient alone (e.g., choose a room with a mate)
		• Carefully evaluating the correct intake of medications (do not leave the medications to patient without checking its assumption)
		• Carefully monitoring about personal potentially risky duties
‘Yellow code’–moderate suicide risk
	• Presence of SI (constant, with low intensity)	• As for ‘green code’ plus
	• Presence of SI (partially criticized by the patent in a credible manner)	• Informing and involving family members
	• Positive and recent personal history of SA without current SI	• Providing a personalized supervision and vigilance
	• Acute depressive episode in MDD, moderate severity (not stable, not remitted, with comorbid anxiety and/or mixed symptoms, without psychotic symptomatology)	• Evaluating the safety of personal duties (assisting the patient during the use of potential risky objects)
		• Eventually, if any, evaluating if changing the room, the position of the bed, in order to increase the visibility for clinical observation
		• Encouraging the patient to objectively evaluate the positive aspects of the current situation, by analyzing the success experiences (self-motivating statement)
		• Correcting his/her sensorial and/or situation/circumstantial wrong perceptions, without belittle his/her fears and without showing disapproval of his/her convictions
		• Limiting frustrating situations if patient is not currently able to express the anger feeling in a constructed and balanced manner
		• Facilitating the expression of anger feelings in a more functional manner (e.g., sports)
		• Stimulating the patient in identifying values of life, the meaning of life, by doing open-questions, e.g., what do you think it should be your tasks in your life? Which are your dreams’ life? etc.
		• Encouraging the patient that ‘changing is possible’
		• Involving the patient in some positive activity, by facilitating the social interaction
		• Encouraging the patient in communicating SI and/or self-harm thoughts to clinicians
		• Identifying potential initial agitation and/or anxiety and/or irritability and/or impulsivity
‘Red code’–severe suicide risk
	• Positive and recent personal history of SA with active, current and intensive SI	• As for ‘green’ and ‘yellow’ code plus
	• Presence of SI (constant, with high intensity but not criticized by the patent in a credible manner)	• Providing a more careful and intense clinical supervision and vigilance (eventually, providing a continuous, 24h monitoring of patient)
	• Acute depressive episode in MDD, severe severity (not stable, not remitted, with and/or without psychotic symptomatology, e.g., guilt or ruin delusion, with an intense psychomotor agitation, impulsivity, with mixed symptoms, higher introversion levels, with auditory imperative hallucinations of self-harm)	• Evaluating hospitalization

SI: suicide ideation, SA: suicide attempt, ST: suicide threat, SHB: self-harm behaviour, MDD: major depressive disorder

Acknowledgments

The authors have no potential conflicts of interest to disclose.

Author Contributions

All authors have contributed to the present reviwe with equal efforts.

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Published: 21 August 2024

Accelerometer-derived ‘weekend warrior’ physical activity pattern and brain health

Jiahao Min 1 na1 ,
Zhi Cao 2 na1 ,
Tingshan Duan 1 ,
Yaogang Wang ORCID: orcid.org/0000-0003-2493-6471 3 , 4 , 5 na2 &
Chenjie Xu ORCID: orcid.org/0000-0002-8997-9299 1 na2

Nature Aging ( 2024 ) Cite this article

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Neurological disorders
Psychiatric disorders

Extensive evidence shows the beneficial effect of adhering to a regular physical activity (PA) pattern on brain health. However, whether the ‘weekend warrior’ pattern, characterized by concentrated moderate-to-vigorous PA (MVPA) over 1–2 days, is associated with brain health is unclear. Here, we perform a prospective cohort study including 75,629 participants from the UK Biobank with validated accelerometry data. Individuals were classified into three PA patterns using current guideline thresholds: inactive (<150 min week −1 of MVPA), weekend warrior (≥150 min week −1 with ≥50% of total MVPA occurring within 1–2 days) and regularly active (≥150 min week −1 but not meeting weekend warrior criteria). We find that the weekend warrior pattern is associated with similarly lower risks of dementia, stroke, Parkinson’s disease, depressive disorders and anxiety compared to a regularly active pattern. Our findings highlight the weekend warrior pattern as a potential alternative in preventive intervention strategies, particularly for those unable to maintain daily activity routines.

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Accelerometer-derived physical activity and mortality in individuals with type 2 diabetes

Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality

Associations of timing of physical activity with all-cause and cause-specific mortality in a prospective cohort study

Data availability.

The main data used in this study were accessed from the publicly available UK Biobank Resource ( https://www.ukbiobank.ac.uk ) under application no. 79095, which cannot be shared with other investigators because of data privacy laws. The UK Biobank data can be accessed by researchers on the application. Source data are provided with this paper.

Code availability

Scripts used to perform the analyses are available at https://github.com/Chen-jie-Xu/UKB_weekend_warrior_brain_health.git .

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Acknowledgements

This study was conducted using the UK Biobank resource (application no. 79095). We want to express our sincere thanks to the participants of the UK Biobank and the members of the survey, development and management teams of this project. This work was supported by the National Natural Science Foundation of China (grant no. 72204071 to C.X. and no. 72342017 to Y.W.); Zhejiang Provincial Natural Science Foundation of China (grant no. LY23G030005 to C.X.); Major Science and Technology Project of Public Health in Tianjin (grant no. 21ZXGWSY00090 to Y.W.); and Scientific Research Foundation for Scholars of HZNU (grant no. 4265C50221204119 to C.X.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The person icons in the left panel of Supplementary Fig. 1 were designed by Chagu from Iconfont ( https://www.iconfont.cn ). The icons for dementia and depressive disorder in Supplementary Fig. 1 were created by Ziyuejunkui and Lisefei from Iconfont. The PD icon in Supplementary Fig. 1 was designed by Freepik from Flaticon ( https://www.flaticon.com ). We sincerely thank the designers at Iconfont and Flaticon.

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These authors contributed equally: Jiahao Min, Zhi Cao.

These authors jointly supervised this work: Yaogang Wang, Chenjie Xu.

Authors and Affiliations

School of Public Health, Hangzhou Normal University, Hangzhou, China

Jiahao Min, Tingshan Duan & Chenjie Xu

School of Public Health, Zhejiang University School of Medicine, Hangzhou, China

School of Public Health, Tianjin Medical University, Tianjin, China

Yaogang Wang

School of Integrative Medicine, Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China

National Institute of Health Data Science at Peking University, Peking University, Beijing, China

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Contributions

J.M., Z.C., Y.W. and C.X. contributed to the conception, study design and ideas. J.M. and Z.C. collected, assembled the data and performed the statistical analysis. J.M., Z.C., T.D, Y.W. and C.X. conducted results interpretation. J.M. and Z.C. wrote the first and successive drafts of the manuscript. T.D, Y.W. and C.X. revised the manuscript for important intellectual content. C.X. and Y.W. obtained fundings. C.X. and Y.W. provided administrative, technical and logistic support. All authors reviewed the manuscript and approved the final version.

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Correspondence to Yaogang Wang or Chenjie Xu .

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Min, J., Cao, Z., Duan, T. et al. Accelerometer-derived ‘weekend warrior’ physical activity pattern and brain health. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00688-y

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The Critical Relationship Between Anxiety and Depression

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Treatment for Anxiety and Comorbid Depressive Disorders: Transdiagnostic Cognitive-Behavioral Strategies

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Impact of moderate-to-high-suicide-intent in major depressive disorder: a retrospective cohort study on patient characteristics and healthcare resource utilisation in England

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Prevalence of suicidal ideation and planning in patients with major depressive disorder: A meta-analysis of observation studies.

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Introduction

The cellular and molecular basis of major depressive disorder: towards a unified model for understanding clinical depression

Current Situation of Research on Depression

Analysis of Patented Technology Application

Analysis of Clinical Trial

New Medicine Development

Epidemiology of Depression

Neurobiological Pathogenesis of Depressive Disorder

Stress-Responsive HPA Axis

Glutamate Signaling Pathway

Gamma-Aminobutyric Acid (GABA)

Neurotrophin Family

Neuroinflammation

Microbiome-Gut-Brain Axis

Other Systems and Pathways

Advances in Various Kinds of Research on Depressive Disorder

Genetic Studies

Brain Imaging and Neuroimaging Studies

Objective Index for Diagnosis of MDD

Management of Depression

Current Antidepressant Treatment

Neuromodulation Therapy

Precision Medicine for Depression

Future Perspectives

Change history

Acknowledgments

Author information

Corresponding author

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Depression: The Latest Research

Fast-Acting Antidepressants

More Exact Antidepressant Selection

Causes of Depression

Top doctors in ,

Understanding the Complex of Suicide in Depression: from Research to Clinics

Roberto Latini

Gianluca Serafini

Umberto Volpe

Federica Vellante

Michele Fornaro

Alessandro Valchera

Carmine Tomasetti

Silvia Fraticelli

Sabatino Trotta

INTRODUCTION

MATERIAL AND METHODS

Study selection, data extraction and management

Risk factors

Genetic vulnerability and epigenetic modulation

The hypothalamic-pituitary-adrenal axis

Serotonergic system

Neuroplasticity, brain-derived neurotrophic factor and nerve growth factor

Neuro-immunological markers