Admixture analysis of age at onset in major depressive disorder

Differences in the prevalence and clinical correlates of comorbid suicide attempts in patients with early- and late-onset major depressive disorder

Objective

There are many studies on differences in the onset age of major depressive disorder (MDD) patients. However, study on differences in clinical correlates of suicide attempts between early- and late-onset MDD patients is limited. The aim of this study was to investigate the differences in the prevalence and clinical correlates of suicide attempts in patients with early- and late-onset MDD in China.

Methods

A total of 1718 adult outpatients with MDD were recruited. Demographic and clinical data were collected. The 17-item Hamilton Rating Scale for Depression (HAMD-17), Hamilton Anxiety Rating Scale (HAMA), Positive and Negative Syndrome Scale (PANSS) positive subscale, and Clinical Global Impression-Severity (CGI-S) Scales were used to assess their depressive, anxiety, psychotic symptoms, and the severity of the clinical symptoms, respectively.

Results

The prevalence of suicide attempts was higher in late-onset MDD patients (291/1369, 21.3%) than in early-onset MDD patients (55/349, 15.8%) (p = 0.023). However after Bonferroni correction no significant difference was found in the prevalence of suicide attempts in late-onset and late-onset MDD patients (p > 0.05). In both early- and late-onset groups, univariate analysis showed that the following characteristics were significantly associated with suicide attempts: HAMA, HAMD and PANSS positive subscale scores, thyroid stimulating hormone (TSH) levels, blood glucose levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). In both the early- and late-onset groups, the prevalence rates of severe anxiety disorder and psychotic symptoms were significantly higher in the suicide attempt group than in the non-suicide attempt group. In regression analysis, disease duration, TSH levels and HAMA score were independently associated with suicide attempts in the early-onset group, while TSH levels, HAMA and HAMD score were independently associated with suicide attempts in the late-onset group.

Conclusion

This study suggests that suicide attempts are not frequent in early-onset outpatients with MDD compared with late-onset, and some clinical correlates are associated with suicide attempt in early- and late-onset MDD.

A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures

BACKGROUND

Major Depressive Disorder (MDD) is a psychiatric disorder characterized by functional brain deficits, as documented by resting-state functional magnetic resonance imaging (rs-fMRI) studies.

AIMS

In recent years, some studies used machine learning (ML) approaches, based on rs-fMRI features, for classifying MDD from healthy controls (HC). In this context, this review aims to provide a comprehensive overview of the results of these studies.

DESIGN

The studies research was performed on 3 online databases, examining English-written articles published before August 5, 2022, that performed a two-class ML classification using rs-fMRI features. The search resulted in 20 eligible studies.

RESULTS

The reviewed studies showed good performance metrics, with better performance achieved when the dataset was restricted to a more homogeneous group in terms of disease severity. Regions within the default mode network, salience network, and central executive network were reported as the most important features in the classification algorithms.

LIMITATIONS

The small sample size together with the methodological and clinical heterogeneity limited the generalizability of the findings.

CONCLUSIONS

In conclusion, ML applied to rs-fMRI features can be a valid approach to classify MDD and HC subjects and to discover features that can be used for additional investigation of the pathophysiology of the disease.

Clinical and psychopathological correlates of duration of untreated illness (DUI) in affective spectrum disorders

Affective disorders represent psychopathological entities lying on a continuum, characterized by high prevalence and functional impairment. A delay in treatment initiation might increase the burden associated with affective spectrum disorders. The present study was aimed at analyzing the correlates of a long duration of untreated illness (DUI) in these conditions. We recruited subjects diagnosed with affective disorders, both in- and outpatients, and collected information concerning socio-demographic, clinical, and psychopathological characteristics. Long DUI was defined according to previous research criteria as >2 years for Bipolar Disorders or >1 year for Depressive Disorders. Bivariate analyses were performed to compare subjects with a long and short DUI (p<0.05). A logistic regression was operated to evaluate the correlates of long DUI. In the present sample (n=135), 34.1% (n=46) subjects showed a long DUI. This subgroup presented with more physical comorbidities (p=0.003), higher body mass index (BMI) (p<0.001), more frequent anxiety onset (p=0.018), younger onset age (p=0.042), and more severe depressive symptoms (Hamilton Depression Rating Scale item 1-depressed mood (p=0.032) and item 2-guilt feelings (p=0.018)). At the logistic regression, higher severity of depressed mood (OR 1.568), higher BMI (OR 1.264), and younger age at onset (OR 0.935) were associated with long DUI. The present study confirmed a possible role of DUI as a construct underpinning higher clinical severity in affective spectrum disorders, possibly linked to worse illness course and unfavorable outcomes. Intervention strategies targeting physical comorbidities and depressive symptoms severity may decrease disease burden in subjects with a long DUI.

Does virtual reality increase the efficacy of psychotherapy for young adults with mild-to-moderate depression? A study protocol for a multicenter randomized clinical trial

BACKGROUND

The improvement of psychological treatments for depression in young adults is a pressing issue highlighted in the literature. Its relevance is determined not only because young adults are underrepresented in research, but also to prevent chronic severe mental health disorders later in life. Engagement is considered a key factor for a good therapeutic outcome, especially among young patients. In this sense, virtual reality could be particularly suited to engage young adults in the therapy process. This project aims to improve the psychological treatment of mild-to-moderate depression in young adults by testing out the efficacy of virtual reality-enhanced personal construct therapy (PCT-VR), as compared to personal construct therapy alone (PCT) and to the reference standard cognitive behavioral therapy (CBT). In contrast to CBT, PCT neither educates patients about depression nor gives them directions on the changes to be made in their dysfunctional behaviors or cognitions. Rather, PCT explores the coherence (or conflicts) of thoughts and behaviors with respect to the person's sense of identity and focuses on meaning-making processes.

METHODS

The efficacy of this innovative intervention (PCT-VR) will be compared to PCT and to CBT in a randomized clinical trial. The study includes an appraisal of therapists' adherence and independent assessments to preserve internal validity. The Beck Depression Inventory-II is the primary outcome measure for calculating both statistical and clinical significance, but other outcomes will also be assessed (e.g., functioning, well-being, anxiety, stress) at pre- and post-therapy and at 6-month follow-up. The trial will be conducted in a naturalistic context, mostly at the usual health care center of each patient. A sample of 225 participants is targeted to reach enough statistical power to accomplish the goals of the study.

DISCUSSION

We expect that providing evidence for PCT-VR will widen the repertoire of evidence-based technology-based psychotherapeutic interventions for young adults and contribute to the prevention of deteriorating courses of the disorder.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04321525 . Registered on 18 February 2020.

Prevalence of attention-deficit/hyperactivity disorder in people with mood disorders: A systematic review and meta-analysis

OBJECTIVE

Attention-deficit/hyperactivity disorder (ADHD) in mood disorders is associated with unfavorable outcomes, including more frequent mood episodes, and increased risk of suicide. The reported prevalence of ADHD in individuals with mood disorders varies widely.

METHODS

We searched PsycInfo and PubMed for articles published before September 21^st , 2020, using search terms for ADHD and mood disorders. We included original data on the prevalence of ADHD in individuals with bipolar disorder (BD) or major depressive disorder (MDD). We estimated the prevalence of ADHD, by developmental period and disorder using random-effects meta-analyses. We also compared the rate of ADHD in people with MDD and BD, and with and without mood disorders.

RESULTS

Based on 92 studies including 17089 individuals, prevalence of ADHD in BD is 73% (95% CI 66-79) in childhood, 43% (95% CI 35-50) in adolescence, and 17% (95% CI 14-20) in adulthood. Data from 52 studies with 16897 individuals indicated that prevalence of ADHD in MDD is 28% (95% CI 19-39) in childhood, 17% (95% CI 12-24) in adolescence, and 7% (95% CI 4-11) in adulthood. ADHD was three times more common in people with mood disorders compared to those without and 1.7 times more common in BD compared to MDD.

CONCLUSION

People with mood disorders are at a significant risk for ADHD. ADHD should be assessed and treated in individuals with BD and MDD. Comprehensive assessment strategies are needed to address challenges of diagnosing ADHD alongside mood disorders.

Developmental trajectories in psychiatric disorders: does substance/alcohol use moderate the effects of affective temperaments as moderators of age at onset? A study in post-acute, hospitalized patients with psychotic or DSM-5 bipolar or major depressive disorders

BACKGROUND

Age-at-onset (AAO) affects psychiatric disorder outcome; substance (SUDs) or alcohol use disorders (AUDs) may influence their onset. Affective temperaments may affect early AAO and drug-use proneness. Objectives: To investigate whether SUD/AUD moderated temperamental effects in determining AAO of mental disorders. Methods: We included 300 post-acute inpatients with schizophrenia-spectrum and other psychotic (SSOPDs), major depressive (MDD) or bipolar (BD) disorders (168 men; mean age, 40.63 years ± 11.82 men, 43.21 years ± 12.69 women) with (N = 110) or without (N = 190) SUD/AUD. Patients completed cross-sectionally TEMPS-A. We carried moderation analysis with each regression-significant TEMPS temperament as independent variable, SUD/AUD presence/absence as dichotomous moderator, and AAO as dependent variable. Significance was set at p < 0.05. Results: AAO was lower in patients with SUD/AUD diagnosis than in patients without (23.74 ± 10.09 vs. 27.73 ± 10.35, respectively, p = 0.001, η2 = 0.034). SUD/AUD patients scored higher on the hyperthymic (10.22 ± 4.08, p < 0.001, η2 = 0.069) and irritable (8.26 ± 4.69, p < 0.01, η2 = 0.026) temperaments than nonSUD/AUD patients. Moderation analysis showed only direct effects of irritable (β = -0.55, p < 0.005) and hyperthymic (β = -0.95, p < 0.001) temperaments on AAO and no significant SUD/AUD and interaction effects. Limitations. Cross-sectional design. Conclusions: When irritable and hyperthymic traits prevail over other temperaments, AAO is earlier in SSOPDs, MDD, and BD. SUD/AUD presence/absence does not moderate the relationship between temperament and AAO.

Does early and late life depression differ in residual symptoms, functioning and quality of life among the first-episode major depressive patients

AIMS & OBJECTIVES

Age differences exist in many aspects in patients with major depressive disorder (MDD). The present study aims to examine the effect of age on treatment outcomes in first-episode MDD.

METHODOLOGY

A total of 982 first-episode major depressive patients, who were above 18 years old and admitted in both psychiatric hospitals and units of general hospitals were recruited for the present study. These patients were newly treated and responded to 8-12 weeks of antidepressant treatment. Depressive symptoms, psychosocial functioning and quality of life were measured using standardized instruments. The study population was divided into three age groups: early adult (18-44 years old), middle adult (45-59 years old), and late adult (60-85 years old).

RESULTS

Earlier age was associated with greater symptom severity, severer depressive symptoms in hypersomnia, concentration/decision making, negative view of the self, suicide ideation and restlessness, more impaired function, poorer satisfaction in social relationship and economic status, when compared to late adults with MDD (all P < 0.05). In the multivariable analyses, among the other variables, early age remained as an independent correlation of residual depressive severity (middle age vs. early age: OR = 0.631, 95%CI[0.462, 0.862]; old age vs. early age: OR = 0.521, 95%CI[0.348, 0.780]) and functional impairment. Comorbidity of physical illness had a negative contribution to all treatment outcomes.

CONCLUSION

In first major depressive episode, early age was strongly associated with depressive severity and functional impairment after responding to antidepressant treatment. Early-life depression may be an indicator of MDD for poor clinical outcomes and high clinical burden.

Age at onset of first suicide attempt: Exploring the utility of a potential candidate variable to subgroup attempters

PURPOSE

Our objective was to explore the utility of age at first suicide attempt in identifying subgroups of suicide attempters.

METHODS

In a retrospective study design, we collected information from the clinical charts of 895 patients assessed over a seven-year period. Admixture analysis was used to determine the best fitting theoretical model for distribution of age at first attempt that divided the sample. Subsequently, multivariate analysis was performed to identify variables that distinguished the subgroups identified.

RESULTS

The theoretical solution that best explained the observed distribution of age at first suicide attempt was a mixture of two Gaussian distributions with a cut-off of 31 years for the two subgroups. In logistic regression analysis, male gender (Odds ratios [OR] 3.047, 95% Confidence Interval (CI) 1.818-5.106), fewer years of formal schooling (OR 3.384, 95% CI 1.701-6.734) and being married (OR 23.36, 95% CI 10.753-50.000), were more commonly associated with the late onset subgroup (age at first attempt >31 years). Further, the late onset subgroup had poorer global functioning (OR 0.980, 95% CI 0.962 to 0.998).

CONCLUSION

Age at onset of first suicide attempt is a useful candidate marker to delineate an early and late onset subgroup among suicide attempters. These results are likely to inform customization of suicide prevention strategies.

Possible predictors of age at illness onset and illness duration in a cohort study comparing younger adults and older major affective patients

BACKGROUND

Major affective conditions are associated with significant disability and psychosocial impairment. Whether specific socio-demographic and clinical characteristics may distinguish subgroups of patients in terms of prognosis and illness trajectories is a matter of debate.

METHODS

The sample of this naturalistic cohort study included 675 currently euthymic patients with major affective disorders of which 428 (63.4%) were diagnosed with unipolar and 247 (36.6%) with bipolar disorders.

RESULTS

Younger adults with a longer duration of untreated illness and residual inter-episodic symptoms were more likely to be single or divorced, students, with an earlier age of first treatment/hospitalization, longer duration of substance abuse and duration of illness than older patients who were, conversely, more likely to be widowed and retired. Multivariate analyses showed a significant positive contribution to age at illness onset by marital status, nonpsychiatric medications, substance abuse, psychiatric diagnosis (bipolar vs. unipolar), age at first treatment/hospitalization, duration of illness, and current age. According to a further analysis, we also found a significant positive contribution to duration of illness by marital status, educational level, positive history of psychiatric conditions in family, substance abuse, psychiatric diagnosis (bipolar vs. unipolar), age at illness onset, age at first treatment, and certain cardiovascular disorders.

CONCLUSIONS

There are substantial socio-demographic and clinical differences that may help to distinguish specific subgroups of patients; however, additional studies are requested to replicate these results and further investigate the main factors underlying our findings.

Age-at-onset subsets of bipolar I disorders: A critical insight into admixture analyses

Gaussian mixture analysis is frequently used to model the age-at-onset (AAO) in bipolar I disorder and identify homogeneous subsets of patients. This study aimed to examine whether, using admixture analysis of AAO, cross-sectional designs (which cause right truncation), unreliable diagnosis for individuals younger than 10 years old (which causes left truncation) and the selection criterion used for admixture analysis impact the number of identified subsets. A simulation study was performed. Different criteria - the likelihood ratio test (LRT), the Akaike information criterion (AIC), and the Bayesian information criterion (BIC) - were compared using no, left and/or right truncation simulated data. The error rate of each criterion (percentage of erroneous number of detected subsets) was estimated. An application to two real databases, including 2,876 and 1,393 patients, is provided. Without data truncation and regardless of the distribution of AAO, the LRT and the AIC had much higher error rates (12% and 33%, respectively) than the BIC (1%). For a homogeneous population, the error rate increased with the introduction of left truncation. This study shows that the number of subsets identified using admixture analysis may depend on the sample size, the selection criterion, and the study design.

A cluster analysis of early onset in common anxiety disorders

Early onset is regarded as an important characteristic of anxiety disorders, associated with higher severity. However, previous findings diverge, as definitions of early onset vary and are often unsubstantiated. We objectively defined early onset in social phobia, panic disorder, agoraphobia, and generalised anxiety disorder, using cluster analysis with data gathered in the general population. Resulting cut-off ages for early onset were ≤22 (social phobia), ≤31 (panic disorder), ≤21 (agoraphobia), and ≤27 (generalised anxiety disorder). Comparison of psychiatric comorbidity and general wellbeing between subjects with early and late onset in the general population and an outpatient cohort, demonstrated that among outpatients anxiety comorbidity was more common in early onset agoraphobia, but also that anxiety- as well as mood comorbidity were more common in late onset social phobia. A major limitation was the retrospective assessment of onset. Our results encourage future studies into correlates of early onset of psychiatric disorders.

Early onset mood disorders and first alcohol use in the general population

BACKGROUND

Mood disorders and alcohol use are common in the general population and often occur together. This study explored how early onset mood disorders relate to age of first alcohol use in the Australian general population.

METHODS

Discrete time survival analysis modelled the odds of first alcohol use among those with, versus without, an early onset DSM-IV mood disorders (major depression, dysthymia or bipolar disorder). Data came from the 2007 Australian National Survey of Mental Health and Wellbeing (N=8841).

RESULTS

Early onset mood disorders as an overall class were not significantly related to the odds of first alcohol use in any given year. On examining the different types of mood disorders individually early onset bipolar disorder was a significant predictor of first alcohol use. The analysis then looked at interactions with time and found that after the age of 14 years the presence of an early onset mood disorder significantly increased the odds of first alcohol use by 32%.

LIMITATIONS

Retrospective recall was used to determine age of onset data which is subject to known biases and replication is recommended in some subgroup analysis due to smaller sample sizes.

CONCLUSIONS

Mood disorders, particularly bipolar disorder, act as unique risk factors for first alcohol use in the general population and show significant interactions with developmental timing. The findings point to the potential utility of prevention programs that target alcohol use and mood disorders together from early adolescence.

Potential Relationship between Season of Birth and Clinical Characteristics in Major Depressive Disorder in Koreans: Results from the CRESCEND Study

We aimed to examine the potential relationship between season of birth (SOB) and clinical characteristics in Korean patients with unipolar non-psychotic major depressive disorder (MDD). Using data from the Clinical Research Center for Depression (CRESCEND) study in South Korea, 891 MDD patients were divided into two groups, those born in spring/summer (n=457) and those born in autumn/winter (n=434). Measurement tools comprising the Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Brief Psychiatric Rating Scale, Scale for Suicidal Ideation, Clinical Global Impression of severity, Social and Occupation Functional Assessment Scale, WHO Quality of Life assessment instrument-abbreviated version, Alcohol Use Disorder Identification Test, and Temperament and Character Inventory were used to evaluate depression, anxiety, overall symptoms, suicidal ideation, global severity, social function, quality of life, drinking, and temperament and character, respectively. Using independent t-tests for continuous variables and χ² tests for discrete variables, the clinical characteristics of the two groups were compared. MDD patients born in spring/summer were on average younger at onset of first depressive episode (t=2.084, p=0.038), had greater loss of concentration (χ²=4.589, p=0.032), and were more self-directed (t=2.256, p=0.025) than those born in autumn/winter. Clinically, there was a trend for the MDD patients born in spring/summer to display the contradictory characteristics of more severe clinical course and less illness burden; this may have been partly due to a paradoxical effect of the 5-HT system.

Admixture analysis of age at symptom onset and age at disorder onset in a large sample of patients with obsessive-compulsive disorder

BACKGROUND

A number of studies tested for the presence of different homogeneous subgroups of obsessive-compulsive disorder (OCD) patients depending on the age at onset (AAO). However, none of the various thresholds of AAO have been validated. No study examined whether age at symptoms onset (ASO) and age at disorder onset (ADO) each define specific and diverse OCD subgroups.

METHODS

We used normal distribution mixture analysis in a sample of 483 OCD patients to test whether we could identify subgroups of patients according to the AAO. We tested whether ASO and ADO had different distributions and identified different subgroups of OCD patients, and whether clinical correlates had similar patterns of associations with patients subgroups identified with ASO or ADO.

RESULTS

The mixture analysis showed a trimodal distribution for ASO (mean ASO: 6.9 years for the early onset, 14.99 years for the intermediate onset, and 27.7 years for the late onset component), and confirmed a bimodal distribution for ADO (mean ADO: 18.0 and 29.5 years). Significant differences in the clinical profile of the subgroups emerged, particularly when identified using ASO.

LIMITATIONS

Limitations of our study are the retrospective investigation of AAO, and the fact that our sample may not represent the OCD population, as we enrolled patients referring to a tertiary center specialized in the treatment of OCD. Our findings need to be confirmed in community samples. Another limitation is the lack of information on medication status at enrollment.

CONCLUSIONS

Age at symptom onset and ADO showed distinct patterns of distributions. Similarly, phenotypic delineation was specific for ASO and ADO identified subgroups. Accurate clinical and biological profiling of ADO and ASO subgroups might show distinct genetic liabilities, ultimately leading to better nosological models and possibly to improved treatment decision making of OCD patients.

Does age at onset of first major depressive episode indicate the subtype of major depressive disorder?: the clinical research center for depression study

PURPOSE

The purpose of this study was to evaluate the effects of age at onset of the first major depressive episode on the clinical features of individuals with major depressive disorder (MDD) in a large cohort of Korean depressed patients.

MATERIALS AND METHODS

We recruited 419 MDD patients of age over 18 years from the Clinical Research Center for Depression study in South Korea. At the start of the study, the onset age of the first major depressive episode was self-reported by the subjects. The subjects were divided into four age-at-onset subgroups: childhood and adolescent onset (ages <18), early adult onset (ages 18-44), middle adult onset (ages 45-59), and late onset (ages 60+). Using analysis of covariance (ANCOVA) and ordinal logistic regression analysis with adjusting the effect of age, the relationships between clinical features and age at onset of MDD were evaluated.

RESULTS

There was an apparent, but inconsistent correlation between clinical features and age at onset. Earlier onset MDD was significantly associated with higher proportion of female gender [adjusted odds ratio (AOR)=0.570, p=0.022], more previous suicide attempts (AOR=0.635, p=0.038), greater number of previous depressive episodes (F=3.475, p=0.016) and higher scores on the brief psychiatric rating scale (F=3.254, p=0.022), its negative symptom subscale (F=6.082, p<0.0001), and the alcohol use disorder identification test (F=7.061, p<0.0001).

CONCLUSION

Early age at onset may increase the likelihood of distinguishable MDD subtype, and age at onset of the first major depressive episode is a promising clinical indicator for the clinical presentation, course, and outcome of MDD.