Major Mood Disorders Research Articles

Novel youth mental health services in Australia: What differences are being reported about the clinical needs of those who attend and the outcomes achieved?

Globally, youth mental health services are evolving, with Australia's headspace services presented as a leading exemplar. headspace services were designed as enhanced primary care-based entities and were expected to collaborate with local acute, and specialist clinical and psychosocial services. The lack of large-scale health services trials necessitates understanding their impact through systematic monitoring and evaluation. This paper compares data from differing sources that describe the demographic and clinical features, and functional outcomes, of young people presenting to various headspace services. headspace National reports that care is provided largely to youth with transient distress, minimal clinical disorders, suicidality or comorbidities and limited functional impairment. Almost 50% of clients are reported to have no significant psychological symptoms or risk factors, and less than 30% to have a clinical disorder. Consequently, 36% receive only a single session of care and the median number of clinical sessions provided is three. By contrast, empirically derived estimates, utilising data from an academic centre and its affiliated centres, other independent agencies and more refined analyses of headspace national data variously portray 50-60% of youth as presenting with at least moderate clinical complexity (including at least 20% with high complexity), and with another 27% requiring active clinical intervention. Together, these data suggest approximately 75% of attendees require substantive clinical care. Clinical outcomes data from all sources indicate limited impacts on functional outcomes, with less than a third achieving significant improvement. These data support the original intent of headspace services to focus on equitable access to multidimensional and clinical assessment, evidence-based early interventions for early stages of major anxiety, mood or psychotic disorders. As demand for youth services continues to rise, there is an urgent need to reconfigure our national youth service networks to address the unmet clinical and psychosocial needs of youth presenting in the early stages of major mental disorders.

Victimisation in other- and self-directed violence as a function of ethnicity and primary diagnosis among inpatients with serious mental illness.

Among individuals with serious mental illness (SMI), victimisation has been found to increase the risk of engaging in other- and self-directed violence. However, rates of victimisation within this population have been found to vary by ethnic group and primary diagnosis. This study primarily aimed to examine the relationship between victimisation and other- and self-directed violence among a sample of inpatients with SMI during the first 3 months of admission. The role of ethnicity and primary diagnosis were also explored. This cross-sectional study utilised data from South London and Maudsley's (SLaM) anonymised database. Participants (n = 7,265) were aged over 18 upon admission, of White British, Black African, Black Caribbean or Asian ethnicity and had a primary diagnosis of major mood disorder, mania or psychosis. Among a sample of inpatients with SMI, victimisation increased the risk of other-directed violence but not self-directed violence. While Black African ethnicity was associated with an increased risk of other-directed violence, all minority ethnic groups had a decreased risk of self-directed violence compared to White British ethnicity. Those with a primary diagnosis of mania or psychosis were observed to be at increased risk of other-directed violence and decreased risk of self-directed violence compared to those with a major mood disorder. Inpatients with SMI who have experienced victimisation are at an increased risk of engaging in other-directed violence during the first 3 months of admission.

In silico analysis of hub genes and regulatory networks implicates the putamen in non-motor Parkinson’s disease disorders

BackgroundParkinson’s disease (PD) is a neurodegenerative condition marked by the gradual degeneration of dopaminergic neurons in the substantia nigra, leading to depletion of the dopaminergic neurons in the substantia nigra as well as degeneration as and decreased activity in the putamen. This study aims to identify the role of putamen in non-motor PD symptoms as well as potential therapeutic target in the putamen of PD.MethodsTranscriptome profiles of PD (dataset number: GSE205450, obtained from postmortem putamen and caudate samples from forty controls and thirty-five PD patients) were retrieved from the Gene Expression Omnibus (GEO) database. Specifically, we focused on putamen data for controls and PD patients. Differential gene expression analysis was carried out using with Limma, filtering for genes with |logFC|> 1 (fold change) and p < 0.05 (p-value). Protein–Protein Interaction networks were constructed using stringDB (combined score > 0.7) and analyzed in Cytoscape to identify hub genes based on various topological measures (EPC, MCC, MNC, Degree, and EcCentricity). Enrichment analysis of target genes was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Also, we constructed transcription factor (TF)-hub gene expression networks, miRNA-hub gene expression networks, and disease hub gene association networks using the JASPAR database, Tarbase database, and DisGeNET via NetworkAnalyst platform, respectively.ResultsSeven genes, namely SST, NPY, IL6, PVALB, ALB, NTS, and TH were identified as hub genes in PD putamen. Notable miRNAs included hsa-mir-34a-5p, hsa-mir-15a-5p, hsa-mir-424-5p, and hsa-mir-19b-3p, while key transcription factors include GATA2, CREB1, FOXC1, FOXL1, TID1, NFKB1, YY1, SPIB, GATA3, and STAT3.ConclusionsOur findings revealed close associations between the hub genes of PD putamen and non-motor symptoms of PD such as major depressive disorder, mood disorders and schizophrenia. These findings may provide a new direction for developing therapy for non-motor symptoms of PD and wet lab research is encouraged.

Incidence and antecedents of emergent suicidal ideation and behavior among Veterans with serious mental illness receiving intensive case management.

Veterans with serious mental illness (SMI; i.e., schizophrenia-spectrum disorders, major mood disorders, post-traumatic stress disorder) are a high-risk group for suicide and little is known about those with emergent suicidal ideation and/or behavior. The primary study aim was to examine the six-month incidence and baseline antecedents of emergent suicidal ideation and/or behavior (suicidal ideation and/or behavior at six-month follow-up but not at enrollment) in Veterans with SMI enrolled in the Veterans Health Administration's (VHA) community-based treatment program (i.e., Intensive Community Mental Health Recovery [ICMHR]). A second, exploratory aim was to examine six-month follow-up ICMHR service use (e.g., frequency of contact with Veteran, type of services provided) in those with emergent suicidal ideation and/or behavior. National ICMHR program evaluation data from 2000 to 2013 were analyzed for Veterans with enrollment and six-month follow-up assessments (n=9921). Analyses examined differences in baseline characteristics and ICMHR service use in those with emergent suicidal ideation and/or behavior compared to those with other suicidal ideation and/or behavior patterns (i.e., none [at either timepoint], improved [present at enrollment but not at follow-up], persistent [present at both timepoints]). Results showed that 1.7% (n=167) of the sample had emergent suicidal ideation and/or behavior. Some suicidal ideation and/or behavior groups differed significantly from the emergent suicidal ideation and/or behavior group on odds of: lifetime hospitalizations, baseline subjective distress, affective disorder diagnosis, and baseline quality of life. Overall, historical and current clinical factors and quality of life should be assessed in this population given their association with emergent suicidal ideation and/or behavior.

Pineal gland volume in children with intellectual disability.

Pineal gland volume (PGV), which is associated with sleep and circadian rhythm, is known to be changed in some psychiatric disorders such as major depression, mood disorders and schizophrenia. This study aimed to compare the PGV of children with mild and moderate intellectual disability (ID) and healthy children. This multicentre retrospective study included 40 children with ID (patient group), aged 6-12 years and 40 age- and sex-matched healthy children (control group). The children were examined for their sociodemographic characteristics and for PGV using magnetic resonance imaging. The PGV of the patient group was significantly larger than that of the controls (p = 0.023). There was no statistically significant difference in PGV between mild and moderate ID. A moderate and positive correlation was found between Weschler Intelligence Scale for Children-revised (WISC-R) performance score and PGV (p = 0.049, r = 0.313) only in the patient group. In the receiver operating characteristic analysis, the area under the curve was 0.648, and the sensitivity was 70.0%, and the specificity was 60.0%. In conclusion, this study demonstrated that the increased PGV levels were associated with autism spectrum disorder (ASD) and PGV could be a risk factor in the aetiology of ID. Further research with larger sample sizes is needed to clarify this issue.

Functional Principal Component Analysis for Continuous Non-Gaussian, Truncated, and Discrete Functional Data.

Mobile health studies often collect multiple within-day self-reported assessments of participants' behavior and well-being on different scales such as physical activity (continuous scale), pain levels (truncated scale), mood states (ordinal scale), and the occurrence of daily life events (binary scale). These assessments, when indexed by time of day, can be treated and analyzed as functional data corresponding to their respective types: continuous, truncated, ordinal, and binary. Motivated by these examples, we develop a functional principal component analysis that deals with all four types of functional data in a unified manner. It employs a semiparametric Gaussian copula model, assuming a generalized latent non-paranormal process as the underlying generating mechanism for these four types of functional data. We specify latent temporal dependence using a covariance estimated through Kendall's bridging method, incorporating smoothness in the bridging process. The approach is then extended with methods for handling both dense and sparse sampling designs, calculating subject-specific latent representations of observed data, latent principal components and principal component scores. Simulation studies demonstrate the method's competitive performance under both dense and sparse sampling designs. The method is applied to data from 497 participants in the National Institute of Mental Health Family Study of Mood Spectrum Disorders to characterize differences in within-day temporal patterns of mood in individuals with the major mood disorder subtypes, including Major Depressive Disorder and Type 1 and 2 Bipolar Disorder. Software implementation of the proposed method is provided in an R-package.

Daily Self-Monitoring and Feedback of Circadian Rhythm Measures in Major Depression and Bipolar Disorder Using Wearable Devices and Smartphones-The Circadian Rhythm for Mood (CRM®) Trial Protocol: A Randomized Sham Controlled Double-Blind Trial.

The circadian rhythm for mood (CRM) is a digital therapeutic, which aims to prevent mood episode and improve clinical course in patients with major mood disorders. Developed on the circadian rhythm hypothesis of mood disorder, CRM predicts the impending risk of mood episode with its built-in algorithm, utilizing wearable devices data and daily self-reports, and provides personalized feedback. In a pilot study of the CRM, the users experienced less frequent and shorter duration of mood episodes than the non-users. To investigate the efficacy of the upgraded CRM, a double-blind, randomized, sham-controlled, parallel-group trial is designed. Patients aged between 19 and 70, diagnosed with bipolar I disorder, bipolar II disorder, or major depressive disorder, in a euthymic state for more than two months, can participate. During this 12-month trial, participants are assessed for episode recurrence every three months, and the efficacy of the CRM as a potential digital therapeutic is evaluated. Trial registration: ClinicalTrials.gov Identifier: NCT05400785.

How to Solve Clinical Challenges in Mood Disorders; Machine Learning Approaches Using Electrophysiological Markers.

Differentiating between the diagnoses of mood disorders and other psychiatric disorders, and predicting treatment response in depression has long been a concern for clinicians. Machine learning (ML) is one part of artificial intelligence that focuses on instructing computers to mimic the cognitive abilities of the human brain through training. This study will review the research on the use of ML techniques to differentiate diagnoses and predict treatment responses in mood disorders based on electroencephalography (EEG) data. There have been several attempts to differentiate between the diagnoses of bipolar disorder and major depressive disorder , mood disorders, and other psychiatric disorders using ML techniques found on EEG markers. Previous studies have shown that accuracy varies depending on which EEG markers are used, the sample size, and the ML technique. Also, precise and improved ML approaches can be developed by adapting the various feature selection and validation methods that reflect each disease's characteristics. Although ML faces some limitations and challenges in solving for consistent and improved accuracy in the diagnosis and treatment of mood disorders, it has a great potential to understand mood disorders better and provide valuable tools to personalize both identification and treatment.

Identifying predictive factors for mood recurrence in early-onset major mood disorders: A 4-year, multicenter, prospective cohort study

We investigate the predictive factors of the mood recurrence in patients with early-onset major mood disorders from a prospective observational cohort study from July 2015 to December 2019. A total of 495 patients were classified into three groups according to recurrence during the cohort observation period: recurrence group with (hypo)manic or mixed features (MMR), recurrence group with only depressive features (ODR), and no recurrence group (NR). As a result, the baseline diagnosis of bipolar disorder type 1 (BDI) and bipolar disorder type 2 (BDII), along with a familial history of BD, are strong predictors of the MMR. The discrepancies in wake-up times between weekdays and weekends, along with disrupted circadian rhythms, are identified as a notable predictor of ODR. Our findings confirm that we need to be aware of different predictors for each form of mood recurrences in patients with early-onset mood disorders. In clinical practice, we expect that information obtained from the initial assessment of patients with mood disorders, such as mood disorder type, family history of BD, regularity of wake-up time, and disruption of circadian rhythms, can help predict the risk of recurrence for each patient, allowing for early detection and timely intervention.

Mixed Features Specifier in Mood Disorder: The Prevalence and Associated Factors

Introduction: Malaysia’s unique cultural landscape may influence the manifestation of mixed features differently than in global studies. We’ve conducted the first study on the prevalence of the Mixed Feature Specifier (MFS) in mood disorders in Malaysia, addresses crucial research gaps to potentially inform culturally sensitive treatment approaches in Malaysia. Methods: This cross-sectional prevalence study was conducted at a psychiatric hospital in Malaysia, using a researcher administered questionnaire, consisted of five parts which includes sociodemographic factors, clinical characteristics, MADRS score, YMRS score and QoL score. Data was analyzed using SPSS version 24.0. Results: 148 patients were recruited into this study. Overall prevalence of MFS among Major Mood Disorder was 29.8%. There were significant associations between ethnicity (X2=9.063; p=0.028), marital status (X2=18.738; p&lt;0.001) and average monthly income (X2=31.534; p=&lt;0.001) with MFS. In terms of clinical characteristics, there were significant associations between number of hospitalizations (X2=41.026; p&lt;0.001), trials of medications (X2=29.540; p&lt;0.001), total number of medications on (X2=42.338; p&lt;0.001), history of ECT (X2=10.590; p=0.001), family history of mood disorder (X2=20.944; p&lt;0.001), suicidal attempts (X2=26.570; p&lt;0.001), history substance use (X2=19.249; p&lt;0.001), compliance to treatment (X2=4.310; p=0.038), YMRS score (X2=16.799; p=0.001) and MADRS score (X2=43.525; p&lt;0.001) with MFS. Conclusion: We identified predictors associated with MFS, such as amount of income, substance use and number of hospitalizations. Sociodemographic and clinical characteristics are significantly associated with MFS, with significant differences between the QoL of MFS and non-MFS patients. This could foster early detection of cases, hence addressing the psychological needs of both MFS and non-MFS patients.

Serum autoantibodies against α7-nicotinic receptors in subgroups of patients with bipolar disorder or schizophrenia: clinical features and link with peripheral inflammation

There is growing evidence that autoantibodies (AAbs) against proteins expressed in the brain are playing an important role in neurological and psychiatric disorders. Here, we explore the presence and the role of peripheral AAbs to the α7-nicotinic acetylcholine receptor (nAChR) in inflammatory subgroups of psychiatric patients with bipolar disorder (BD) or schizophrenia (SCZ) and healthy controls. We have identified a continuum of AAb levels in serum when employing a novel ELISA technique, with a significant elevation in patients compared to controls. Using unsupervised two-step clustering to stratify all the subjects according to their immuno-inflammatory background, we delineate one subgroup consisting solely of psychiatric patients with severe symptoms, high inflammatory profile, and significantly increased levels of anti-nAChR AAbs. In this context, we have used monoclonal mouse anti-human α7-nAChR antibodies (α7-nAChR-mAbs) and shown that TNF-α release was enhanced upon LPS stimulation in macrophages pre-incubated with α7-nAChR-mAbs compared to the use of an isotype control. These findings provide a basis for further study of circulating nicotinic AAbs, and the inflammatory profile observed in patients with major mood and psychotic disorders.

A Hybrid Type 1 trial of a multi-component mHealth intervention to improve post-hospital transitions of care for patients with serious mental illness: Study protocol

BackgroundThe transition from acute (e.g., psychiatric hospitalization) to outpatient care is associated with increased risk for rehospitalization, treatment disengagement, and suicide among people with serious mental illness (SMI). Mobile interventions (i.e., mHealth) have the potential to increase monitoring and improve coping post-acute care for this population. This protocol paper describes a Hybrid Type 1 effectiveness-implementation study, in which a randomized controlled trial will be conducted to determine the effectiveness of a multi-component mHealth intervention (tFOCUS) for improving outcomes for adults with SMI transitioning from acute to outpatient care. MethodsAdults meeting criteria for schizophrenia-spectrum or major mood disorders (n = 180) will be recruited from a psychiatric hospital and randomized to treatment-as-usual (TAU) plus standard discharge planning and aftercare (CHECK-IN) or TAU plus tFOCUS. tFOCUS is a 12-week intervention, consisting of: (a) a patient-facing mHealth smartphone app with daily self-assessment prompts and targeted coping strategies; (b) a clinician-facing web dashboard; and, (c) mHealth aftercare advisors, who will conduct brief post-hospital clinical calls with patients (e.g., safety concerns, treatment engagement) and encourage app use. Follow-ups will be conducted at 6-, 12-, and 24-weeks post-discharge to assess primary and secondary outcomes, as well as target mechanisms. We also will assess barriers and facilitators to future implementation of tFOCUS via qualitative interviews of stakeholders and input from a Community Advisory Board throughout the project. ConclusionsInformation gathered during this project, in combination with successful study outcomes, will inform a potential tFOCUS intervention scale-up across a range of psychiatric hospitals and healthcare systems.Clinicaltrials.govregistration: NCT05703412

PCDH17 restricts dendritic spine morphogenesis by regulating ROCK2-dependent control of the actin cytoskeleton, modulating emotional behavior.

Proper regulation of synapse formation and elimination is critical for establishing mature neuronal circuits and maintaining brain function. Synaptic abnormalities, such as defects in the density and morphology of postsynaptic dendritic spines, underlie the pathology of various neuropsychiatric disorders. Protocadherin 17 (PCDH17) is associated with major mood disorders, including bipolar disorder and depression. However, the molecular mechanisms by which PCDH17 regulates spine number, morphology, and behavior remain elusive. In this study, we found that PCDH17 functions at postsynaptic sites, restricting the number and size of dendritic spines in excitatory neurons. Selective overexpression of PCDH17 in the ventral hippocampal CA1 results in spine loss and anxiety- and depression-like behaviors in mice. Mechanistically, PCDH17 interacts with actin-relevant proteins and regulates actin filament (F-actin) organization. Specifically, PCDH17 binds to ROCK2, increasing its expression and subsequently enhancing the activity of downstream targets such as LIMK1 and the phosphorylation of cofilin serine-3 (Ser3). Inhibition of ROCK2 activity with belumosudil (KD025) ameliorates the defective F-actin organization and spine structure induced by PCDH17 overexpression, suggesting that ROCK2 mediates the effects of PCDH17 on F-actin content and spine development. Hence, these findings reveal a novel mechanism by which PCDH17 regulates synapse development and behavior, providing pathological insights into the neurobiological basis of mood disorders.

Longitudinal trajectories of metabolic and inflammatory markers in youth with emerging mood disorders

Abstract Metabolic and inflammatory dysfunction is prevalent in middle-aged people with major mood disorders, but less is known about young people. We investigated the trajectories of sensitive metabolic (Homeostatic Model Assessment for Insulin Resistance [HOMA2-IR]) and inflammatory markers (C-reactive protein [CRP]) in 155 young people (26.9 ± 5.6 years) accessing mental health services. We examined demographic and clinical correlates, longitudinal trajectories and relationships with specific illness subtypes. Additionally, we compared the HOMA2-IR with fasting blood glucose (FBG) for sensitivity. We observed a significant increase in HOMA2-IR and CRP over time with higher baseline levels predicting greater increases, although the rate of increase diminished in those with higher baseline levels. Body mass index predicted increases in HOMA2-IR (p &lt; 0.001), but not CRP (p = 0.135). Multinomial logistic regression revealed that higher HOMA2-IR levels were associated with 2.3-fold increased odds of the “circadian-bipolar spectrum” subtype (p = 0.033), while higher CRP levels were associated with a reduced risk of the “neurodevelopmental psychosis” subtype (p = 0.033). Standard FBG measures were insensitive in detecting early metabolic dysregulation in young people with depression. The study supports the use of more sensitive markers of metabolic dysfunction to address the longitudinal relationships between immune-metabolic dysregulation and mood disorders in young people.

Knowledge and Behavior of Primary Care Physicians Regarding Utilization of Standardized Tools in Screening and Assessment of Anxiety, Depression, and Mood Disorders at a Large Integrated Health System.

Standardized screening, objective evaluation, and management of behavioral health conditions are major challenges in primary care. The Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), and Mood Disorder Questionnaire (MDQ) provide standardized screening and symptom management tools for generalized anxiety disorder (GAD), major depressive disorder (MDD), and Mood Disorders (MD), respectively. This study explores family physicians' knowledge, attitudes, and practices regarding the utilization of GAD-7, PHQ-9, and MDQ in outpatient primary care offices. The study method was a cross-sectional electronic and paper survey utilizing a self-administered questionnaire that assessed primary care physicians' demographics, knowledge, attitudes, and practices in rural and urban outpatient clinical settings regarding GAD-7, PHQ-9, and MDQ. Statistical software SAS 9.4 was used for descriptive and Chi-Square statistics. Out of 320 total participants,145 responded (45.3%). Responding family physicians demonstrated a high level of familiarity with the GAD-7 (97.9%), PHQ-9 (97.9%), and MDQ (81.3%) assessment tools. However, the reported utilization rates were relatively lower than knowledge, with 62.7%, 73.1%, and 31.9% extremely likely or likely to utilize the GAD-7, PHQ-9, and MDQ as screening and monitoring tools, respectively. Less than a quarter of the total respondents use the objective score for the future management of GAD, with significantly more residents utilizing the score for GAD-7 compared to attendings (P < .05). There was no statistical significance difference between residents and attendings for the objective evaluation of Major Depressive Disorder (P = .26) and Mood Disorders (P = .05). Despite being knowledgeable of the utility of GAD-7, PHQ-9, and MDQ, the primary care physicians in a large integrated health system in Central Pennsylvania and Northern Maryland report inconsistent utilization in their practice. Further studies are needed to determine the underlying factors contributing to the suboptimal usage of these screening tools and ways to increase it.

What is the place of universal, selective, and indicated prevention strategies for depression and other mood disorders?

Given the global prevalence of depression and other major mood disorders, the evidence of increasing rates among younger cohorts, the limited capacity of most treatment systems to respond to increasing demands for care, and the reality that services do not connect with a large proportion of those living with depressive disorders, a greater emphasis is being placed on our capacity to prevent the onset, recurrence, or persistence of these disabling conditions (Herrman et al., 2022).

Developmental Trajectory of Body Weight in Youths at Risk for Major Mood Disorders

Mood disorders are associated with increased body weight, especially in females, but it remains unknown when the weight increase starts. To examine sex-specific weight trajectories associated with familial mood disorder risk and determine the age at which youth at familial risk for mood disorders begin to diverge in weight from controls. This community-based, single-center, acceleration cohort study of youth at familial risk for mood disorders and controls with yearly follow-ups (mean [SD], 5 [2.1] years) from January 1, 2014, to December 31, 2022, assessed 394 unaffected female and male offspring (aged 3 to 20 years) of parents with or without a mood disorder. Parents with mood (depressive or bipolar) disorders were recruited through adult mental health services. Parents of control participants were matched on age and socioeconomic factors and recruited through acquaintance referrals or schools. The youth in the familial mood risk group had at least 1 parent with a major mood disorder, whereas control youth did not have a parent with a mood disorder. Body mass indexes (BMIs) were calculated as weight in kilograms divided by height in meters squared from measured weight and height at annual assessments and then converted to age- and sex-adjusted z scores (zBMIs). Repeated-measure regressions examined the association between zBMI and age in youth at familial risk of mood disorders and controls while accounting for sex. Sensitivity analyses accounted for socioeconomic status, prematurity, and birth weight. Of 394 participants (mean [SD] age, 11.5 [3.6] years; 203 [51.5%] female), youths at familial risk for mood disorders showed overall no difference in body weight (β = 0.12; 95% CI, 0.01-0.24) from controls. A sex-specific difference was detected, with females at familial risk showing a rapid peripubertal increase in body weight, leading to significantly increased zBMIs at 12 years and older compared with controls (β = 0.57; 95% CI, 0.31-0.82) independent of socioeconomic status, prematurity, or birth weight. Males did not differ from controls at any age. In this cohort study, females with a family history of mood disorders were prone to weight gain starting around puberty and predating mood disorder onset. Early interventions aiming to prevent adverse mental and physical outcomes in this vulnerable group need to start in childhood.

Early sexual or physical abuse in female and male mood disorder patients

Early abuse has been associated with psychiatric morbidity but comparisons of bipolar (BD) and major depressive (MDD) disorder subjects with versus without early sexual or physical abuse are rare. Patients (n = 684) diagnosed with a DSM-5-TR major mood disorder were evaluated and followed for several years at mood disorder centers to compare details of history and clinical status in participants with versus without early sexual or physical abuse. Early history of sexual (16.2%) or physical abuse (11.9%) was prevalent; 5.15% reported both. Both types of abuse were much more prevalent with BD than MDD. Sexual abuse was associated with younger illness-onset and somewhat younger menarche in females; both abuse-types were associated with familial mood disorders, especially BD. Prospective, long-term illness episode-frequency, depressions or [hypo]manias/year and %-time [hypo]manic all were greater following sexual abuse but morbidity measures did not differ following physical abuse. Prevalence of suicidal behavior ranked: double (48.5%) > physical (32.1%) > sexual (30.3%) abuse, and with BD > MDD (OR = 2.31). Recall bias and not using psychometric instruments to define abuse severity or type may limit interpretation of findings. Early sexual (more than physical) abuse, led to greater morbidity and both abuses were strongly associated with familial mood disorders and greater suicidal risk, especially with double-abuse and BD diagnosis. We support a bilateral relationship between abuse and diagnosis of BD: abuse may facilitate early appearance of BD but also may result from the actions of abusive BD family members.

To what extent are depressive or other mood disorders a consequence of earlier traumatic experiences?

The potential relationships between traumatic experiences and the onset and course of major mood disorders have always been controversial. Some experiences, most notably physical or sexual abuse, as well as substantive bullying in childhood, are clearly recognised as major risk factors for a range of mental disorders, as well as a range of linked phenomena including self-harm and suicidal behaviours (McKay et al., 2021; Zatti et al., 2017). There is considerable interest and ongoing research into how these adverse experiences come to be ‘encoded’ via neurobiological or genetic mechanisms that then transmit those effects into later-onset major mental disorders, substance misuse or other self-harming behaviours (Maddox et al., 2019).

Are depressive and other mood disorders best conceptualized as disorders of energy, and related motor activity, rather than mood?

The most basic distinction between depressive (and other mood) disorders and other major mental disorders is the notion that they are primarily mood or affective disorders and not fundamentally perturbations of other cognitive, perceptual, motor, communication, impulse, sleep−wake, fear-response, arousal, developmental or personality functions. The primacy of mood or affective state is captured in the ‘core’ criteria for major depression (depressed mood or loss of pleasure) and the other major mood disorders (e.g., for dysthymia – prolonged depressed mood) (American Psychiatric Association, 2013). For bipolar disorder, while the presence of manic features (with increased motor activity) (Scott et al., 2017) is the core element, the depressive phase is described in similar terms, with the emphasis on the same shared features of major depression (i.e., depressed mood or loss of pleasure).