Diagnostic consistency of major depression with psychosis across 10 years

Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression signatures in six different populations using six public and two domestic cohorts (n = 1942) conducting mega-analysis and meta-analysis of the individual studies. We evaluated 12 machine learning and deep learning strategies for depression classification both in cross-validation (CV) and in hold-out tests using merged data from 8 separate batches, constructing models with both biased and unbiased feature selection. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level, and the associated genes were nominally related to axon guidance and immune pathways based on enrichment analysis and eQTM data. Random forest classifiers achieved the highest performance (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data. In contrast, the methylation showed low predictive power (all AUCs < 0.57) for all classifiers in CV and no predictive power in hold-out tests when used with harmonized data. All models achieved significantly better performance (>14% gain in AUCs) with pre-selected features (selection bias), with some of the models (joint autoencoder-classifier) reaching AUCs of up to 0.91 in the final testing regardless of data preparation. Different algorithmic feature selection approaches may outperform limma, however, random forest models perform well regardless of the strategy. The results provide an overview over potential future biomarkers for depression and highlight many important methodological aspects for DNA methylation-based depression profiling including the use of machine learning strategies.

Long-term diagnostic stability, predictors of diagnostic change, and time until diagnostic change of first-episode psychosis: a 21-year follow-up study

BACKGROUND

Although diagnostic instability in first-episode psychosis (FEP) is of major concern, little is known about its determinants. This very long-term follow-up study aimed to examine the diagnostic stability of FEP diagnoses, the baseline predictors of diagnostic change and the timing of diagnostic change.

METHODS

This was a longitudinal and naturalistic study of 243 subjects with FEP who were assessed at baseline and reassessed after a mean follow-up of 21 years. The diagnostic stability of DSM-5 psychotic disorders was examined using prospective and retrospective consistencies, logistic regression was used to establish the predictors of diagnostic change, and survival analysis was used to compare time to diagnostic change across diagnostic categories.

RESULTS

The overall diagnostic stability was 47.7%. Schizophrenia and bipolar disorder were the most stable diagnoses, with other categories having low stability. Predictors of diagnostic change to schizophrenia included a family history of schizophrenia, obstetric complications, developmental delay, poor premorbid functioning in several domains, long duration of untreated continuous psychosis, spontaneous dyskinesia, lack of psychosocial stressors, longer duration of index admission, and poor early treatment response. Most of these variables also predicted diagnostic change to bipolar disorder but in the opposite direction and with lesser effect sizes. There were no significant differences between specific diagnoses regarding time to diagnostic change. At 10-year follow-up, around 80% of the diagnoses had changed.

CONCLUSIONS

FEP diagnoses other than schizophrenia or bipolar disorder should be considered as provisional. Considering baseline predictors of diagnostic change may help to enhance diagnostic accuracy and guide therapeutic interventions.

Mortality in psychotic depression: 18-year follow-up study

BACKGROUND

Evidence on the role of co-occurring psychiatric disorders in mortality associated with psychotic depression is limited.

AIMS

To estimate the risk of cause-specific mortality in psychotic depression compared with severe non-psychotic depression while controlling for comorbid psychiatric disorders.

METHOD

This cohort study used routine data from nationwide health registers in Finland. Eligible participants had their first diagnosis for psychotic depression or for severe non-psychotic depression between the years 2000 and 2018, had no pre-existing diagnoses for schizophrenia spectrum disorders or bipolar disorder, and were aged 18-65 years at the index diagnosis. Causes of death were defined by ICD-10 codes. The follow-up time was up to 18 years.

RESULTS

We included 19 064 individuals with incident psychotic depression and 90 877 individuals with incident non-psychotic depression. Half (1199/2188) of the deaths in those with psychotic depression occurred within 5 years from the index diagnosis and the highest relative risk was during the first year after the diagnosis. Compared with individuals with non-psychotic depression, those with psychotic depression had a higher risk of all-cause mortality (adjusted hazard ratio, aHR = 1.59, 95% CI 1.48-1.70), suicides (aHR = 2.36, 95% CI 2.11-2.64) and fatal accidents (aHR 1.63, 95% CI 1.26-2.10) during the subsequent 5-year period after the index diagnosis.

CONCLUSIONS

Psychotic symptoms markedly added to the mortality risk associated with severe depression after controlling for psychiatric comorbidity. Prompt treatment and enhanced monitoring for psychotic symptoms is warranted in all patients with severe depression to prevent deaths because of suicides and other external causes.

Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder

BACKGROUND

Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).

METHODS

This study enrolled 2470 hospitalized patients with BD (n = 1333) or MDD (n = 1137) at reproductive age from 2009 to 2018 in China. We extracted 8 parameters, uric acid (UA), direct bilirubin (DBIL), indirect bilirubin (IDBIL), lactic dehydrogenase (LDH), free triiodothyronine (FT3), thyroid-stimulating hormone (TSH), high-density lipoprotein (HDL) and prealbumin of male, patients and 12 parameters, UA, DBIL, IBIL, LDH, FT3, TSH, glutamic-pyruvic transaminase (GPT), white blood cell (WBC), alkaline phosphatase (ALP), fasting blood glucose (FBG), triglyceride and low-density lipoprotein (LDL) of female patients. Backward stepwise multivariate regression analysis and the Chi-Square Automatic Interaction Detection (CHAID) segmentation analysis via SPSS Decision Tree were implemented to define the discrimination of BD and MDD.

RESULTS

DBIL was extracted as the first splitting variable, with LDH and IBIL as the second, TSH and prealbumin as the third in the model of male patients (p-value < .05). For the model of female patients, DBIL was also extracted as the first splitting variable, with UA, LDH, and IBIL as the second, triglyceride and FT3 as the third (p-value < .05). The predictive accuracies of the Decision Tree and multiple logistic regression models were similar (74.9% vs 76.9% in males; 74.4% vs 79.5% in females).

CONCLUSIONS

This study suggests the value of the Decision Tree models, which employ biochemical parameters as diagnostic predictors for BD and MDD. The CHAID Decision Tree identified that patients with concomitantly increased LDH, IBIL, and decreased DBIL could be in the group that showed the highest risk of being diagnosed as BD.

Differences in psychosocial functioning between psychotic disorders in the Finnish SUPER study

BACKGROUND

Psychotic disorders differ in their impact on psychosocial functioning. However, few studies have directly compared psychosocial functioning and its determinants between schizophrenia, schizoaffective disorder (SAD), bipolar disorder (BD), and major depressive disorder with psychotic features (psychotic MDD).

OBJECTIVE

We compared rates of independent living, employment, marriage, and having children between these diagnostic groups in a large national sample of participants with psychotic disorders in Finland.

METHODS

A cross-sectional substudy of participants (N = 9148) aged 18 to 65 years in the Finnish SUPER study, recruited nationwide from health- and social care settings and with advertisements. Psychosis diagnoses, age of onset, and hospitalizations were collected from healthcare registers. Participants were interviewed for psychosocial functioning. Associations of age of onset, hospitalizations, gender, and education with psychosocial functioning were analyzed using logistic regression models.

RESULTS

Of participants, 13.8% were employed or studying, 72.0% living independently and 32.5% had children. Overall, BD was associated with best, SAD and psychotic MDD with intermediate, and schizophrenia with worst level of psychosocial functioning. Greatest differences were found in independent living (OR 4.06 for BD vs. schizophrenia). In multivariate models, gender and number of hospitalizations predicted employment, marriage, and independent living in all diagnostic categories, and age of onset in some diagnostic categories.

CONCLUSIONS

Level of functioning and psychosocial outcomes differed markedly between psychotic disorders, particularly in independent living. Outcomes were worst for schizophrenia and best for BD. Across all psychotic disorders, female gender and lifetime number of hospitalizations had strong independent associations with marriage, employment, and independent living.

Biochemical and Endocrine Parameters for the Discrimination and Calibration of Bipolar Disorder or Major Depressive Disorder

OBJECTIVES

Conventional biochemical indexes may have predictive values in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).

METHODS

This study included 2,470 (BD/MDD = 1,333/1,137) hospitalized patients in Shanghai as training sets and 2,143 (BD/MDD = 955/1,188) in Hangzhou as test sets. A total of 35 clinical biochemical indexes were tested, including blood cells, immuno-inflammatory factors, liver enzymes, glycemic and lipid parameters, and thyroid and gonadal hormones. A stepwise analysis of a multivariable logistic regression was performed to build a predictive model to identify BD and MDD.

RESULTS

Most of these biochemical indexes showed significant differences between BD and MDD groups, such as white blood cell (WBC) in the hematopoietic system, uric acid (UA) in immuno-inflammatory factors, direct bilirubin (DBIL) in liver function, lactic dehydrogenase (LDH) in enzymes, and fasting blood glucose (FBG) and low-density lipoprotein (LDL) in glucolipid metabolism (p-values < 0.05). With these predictors for discrimination, we observed the area under the curve (AUC) of the predictive model to distinguish between BD and MDD to be 0.772 among men and 0.793 among women, with the largest AUC of 0.848 in the luteal phase of women. The χ² values of internal and external validation for male and female datasets were 2.651/10.264 and 10.873/6.822 (p-values < 0.05), respectively. The AUCs of the test sets were 0.696 for males and 0.707 for females.

CONCLUSION

Discrimination and calibration were satisfactory, with fair-to-good diagnostic accuracy and external calibration capability in the final prediction models. Female patients may have a higher differentiability with a conventional biochemical index than male patients.

TRIAL REGISTRATION

ICTRP NCT03949218. Registered on 20 November 2018. Retrospectively registered. https://www.clinicaltrials.gov/ct2/show/NCT03949218?id=NCT03949218&rank=1.

Mismatch negativity amplitude in first-degree relatives of individuals with psychotic disorders: Links with cognition and schizotypy

Mismatch negativity (MMN) amplitude is reliably reduced in psychotic disorders. While several studies have examined this effect in first-degree relatives of individuals with schizophrenia, few have sought to quantify deficits in relatives of individuals with other psychotic disorders. While some conclude that, compared to healthy subjects, first-degree relatives of schizophrenia show reduced MMN, others contradict this finding. Furthermore, though MMN is often shown to be associated with cognitive impairments and clinical symptoms in psychotic disorders, to our knowledge no studies have sought to fully examine these relationships in studies of first-degree relatives. The present study sought to clarify the extent of MMN amplitude reductions in a large sample of siblings of individuals with diverse psychotic disorders (n = 67), compared to probands with psychosis (n = 221) and never psychotic comparison subjects (n = 251). We further examined associations of MMN amplitude with cognition and schizotypal symptoms across these groups. We found that MMN amplitude was intact in siblings compared to probands. MMN amplitude was associated with cognition and schizotypal symptoms dimensionally across levels of familial risk. The present results imply that MMN reductions do not reflect genetic risk for psychotic disorders per se, and instead emerge as a result of, or in conjunction with, clinical features associated with psychosis. Such findings carry important implications for the utility of MMN amplitude as an indicator of inherited risk, and suggest that this component may be best conceptualized as an endophenotype for clinical symptoms and cognitive impairments, rather than risk for psychosis per se.

Clinical characteristics and sociodemographic features of psychotic major depression

BACKGROUND

Psychotic major depression (PMD) is a subtype of depression with a poor prognosis. Previous studies have failed to find many differences between patients with PMD and those with non-psychotic major depression (NMD) or schizophrenia (SZ). We compared sociodemographic factors (including season of conception) and clinical characteristics between patients with PMD, NMD, and schizophrenia. Our aim was to provide data to help inform clinical diagnoses and future etiology research.

METHODS

This study used data of all patients admitted to Shandong Mental Health Center from June 1, 2016 to December 31, 2017. We analyzed cases who had experienced an episode of PMD (International Classification of Diseases, Tenth Revision codes F32.3, F33.3), NMD (F32.0-2/9, F33.0-2/9), and SZ (F20-20.9). Data on sex, main discharge diagnosis, date of birth, ethnicity, family history of psychiatric diseases, marital status, age at first onset, education, allergy history, and presence of trigger events were collected. Odds ratios (OR) were calculated using logistic regression analyses. Missing values were filled using the k-nearest neighbor method.

RESULTS

PMD patients were more likely to have a family history of psychiatric diseases in their first-, second-, and third-degree relatives ([OR] 1.701, 95% confidence interval [CI] 1.019-2.804) and to have obtained a higher level of education (OR 1.451, 95% CI 1.168-1.808) compared with depression patients without psychotic features. Compared to PMD patients, schizophrenia patients had lower education (OR 0.604, 95% CI 0.492-0.741), were more often divorced (OR 3.087, 95% CI 1.168-10.096), had a younger age of onset (OR 0.934, 95% CI 0.914-0.954), less likely to have a history of allergies (OR 0.604, 95% CI 0.492-0.741), and less likely to have experienced a trigger event 1 year before first onset (OR 0.420, 95% CI 0.267-0.661). Season of conception, ethnicity, and sex did not differ significantly between PMD and NMD or schizophrenia and PMD.

CONCLUSIONS

PMD patients have more similarities with NMD patients than SZ patients in terms of demographic and clinical characteristics. The differences found between PMD and SZ, and PMD and NMD correlated with specificity of the diseases. Furthermore, allergy history should be considered in future epidemiological studies of psychotic disorders.

Relationships Among History of Psychosis, Cognition and Functioning in Later-Life Remitted Major Depression

OBJECTIVE

This study tested the hypotheses that, in older adults with remitted major depression, a history of psychotic features and poorer neuropsychological performance would be independently associated with poorer everyday functioning, but that neuropsychological performance would explain more of the variance in functioning than history of psychotic features.

METHODS

This cross-sectional study included 73 patients aged 50 years or older with remitted psychotic major depression or nonpsychotic major depression. The dependent variables were subjective and objective measures of function. The independent variables were history of psychotic features during one or more major depressive episodes in the previous 10 years and neuropsychological performance. Linear regression models examined the association of independent variables with function, controlling for pertinent covariates. Effect sizes were calculated for the magnitude of difference in function between the patient participants and an age- and gender-matched nonpsychiatric group, and distribution of functioning scores were compared between groups.

RESULTS

In separate models, history of psychotic features and poorer processing speed, executive function, and verbal learning were independently associated with poorer participant-reported functioning and performance-based functioning. However, the association of psychotic features with functioning was no longer statistically significant when tested in the same models as neuropsychological measures. Effect sizes of the difference in functioning between patients and the nonpsychiatric group were significantly larger for the remitted psychotic than the remitted nonpsychotic depression group; functioning scores were more heterogeneous in the remitted psychotic depression group.

CONCLUSION

Patients with remitted psychotic depression exhibit greater, and clinically important, impairment in everyday functioning than those with remitted nonpsychotic depression. Neuropsychological impairment appears to contribute to this relationship.

Prevalence and related factors of suicide attempts in first-episode and untreated Chinese Han outpatients with psychotic major depression

BACKGROUND

Major depressive depression (MDD) is often accompanied by suicidal behavior. Increasing evidence shows that MDD patients display psychotic symptoms. However, the relationship between psychotic symptoms and suicide attempt in MDD has not been reported. Therefore, this study was to identify the prevalence and associated factors of suicide attempts in first-episode and untreated Chinese Han outpatients comorbid with psychotic major depression (PMD).

METHODS

1718 first-episode and untreated MDD outpatients were assessed with Positive Symptom Scale of Positive and Negative Syndrome Scale (PANSS), the 17-item Hamilton Depression Scale, Hamilton Anxiety Scale, and clinical global impression of severity scale (CGI-S). Some glycolipid metabolism and thyroid hormone parameters were measured.

RESULTS

In MDD patients, the percentage of PMD was 10.0%. The incidence of attempted suicide in PMD patients was 51.5%, which was more than 3 times higher than that in non-PMD patients (16.7%). In PMD patients, compared to non-attempters, suicide attempters were older, had a longer course of disease, scored higher on all scales, as well as had higher levels of thyroid stimulating hormone (TSH), thyroid peroxidases antibody, anti-thyroglobulin and blood glucose. PANSS positive symptom, CGI, diastolic blood pressure and TSH were independently associated with suicide attempts of PMD.

CONCLUSIONS

PMD patients have a higher prevalence of suicide attempt than non-PMD patients. Some demographic and clinical parameters are relevant factors for suicide attempt in PMD patients.

Prevalence and clinical correlates of psychotic depression in first-episode and drug-naïve outpatients with major depressive disorder in a Chinese Han population

BACKGROUND

Few systemic studies of psychotic depression (PD) have been conducted in first-episode and drug-naïve (FEDN) patients. This study was to examine the prevalence of PD and its clinical correlates in a large sample of FEDN outpatients with major depressive disorder (MDD) in a Chinese Han population, which to our best knowledge has not been studied.

METHODS

In this cross-sectional study, a total of 1718 FEDN MDD outpatients were recruited. All patients were rated on the positive symptom subscale of the Positive and Negative Syndrome Scale (PANSS) for psychotic symptoms, the 17-item Hamilton Depression Rating Scale (HAMD-17) for depression and Hamilton Anxiety Rating Scale (HAMA) for anxiety.

RESULTS

The prevalence of PD was 10.0% (171/1718) in MDD patients. Compared to the non-PD patients, PD patients had significantly older age, lower educational levels, higher anxiety symptom score and were more likely to attempt suicide. Further logistic regression analysis indicated that PD was associated with older age, suicide attempt and comorbid anxiety (all p < 0.05). Multiple regression analyses showed that both HAMD and HAMA total scores were significantly associated with PANSS positive symptom subscale score.

LIMITATIONS

Our cross-sectional study design does not show a direct causal relationship between psychiatric symptoms and related factors in patients with MDD.

CONCLUSIONS

Our results suggest a high prevalence of PD in MDD patients in the acute early stage in a Chinese Han population, which is associated with demographic variables and clinical symptoms.

Affective Disorders with Psychosis in Youth: An Update

Mood disorders, including major depression and mania, can present with psychotic features. In youth psychotic-like phenomena such as "seeing faces in the dark" or "hearing noises" are fairly common. Rates of lifetime psychotic symptoms are much higher than rates of psychosis during a "current" episode of mania or depression in youth. Psychotic phenomena can be mood congruent or incongruent. A detailed mental status examination and clinical history include questioning to ensure the informants understand the questions being asked. There are interviews that structure how questions are asked, and rating scales that help anchor severity and quality of the mood episode.

Impact, Diagnosis, Phenomenology, and Biology

This section provides summaries of the epidemiology, phenomenology, nosology, and the suspected biological substrates of the depressive disorders. It particularly emphasizes the historical evolution of the pertinent diagnostic constructs and the prognostic import both of the various diagnostic groupings and of the individual symptoms and symptom clusters.

Epidemiology of psychotic depression - systematic review and meta-analysis

Large amount of data have been published on non-psychotic depression (NPD), schizophrenia (SZ), and bipolar disorder, while psychotic depression (PD) as an own entity has received much smaller attention. We performed a systematic review and meta-analyses on epidemiology, especially incidence and prevalence, risk factors, and outcomes of PD. A systematic search to identify potentially relevant studies was conducted using four electronic databases and a manual search. The search identified 1764 unique potentially relevant articles, the final study included 99 articles. We found that the lifetime prevalence of PD varies between 0.35% and 1%, with higher rates in older age. Onset age of PD was earlier than that of NPD in younger samples, but later in older samples. There were no differences in gender distribution in PD v. NPD, but higher proportion of females was found in PD than in SZ or in psychotic bipolar disorder (PBD). Risk factors have rarely been studied, the main finding being that family history of psychosis and bipolar disorder increases the risk of PD. Outcomes of PD were mostly worse when compared with NPD, but better compared with SZ and schizoaffective disorder. The outcome compared with PBD was relatively similar, and somewhat varied depending on the measure of the outcome. Based on this review, the amount of research on PD is far from that of NPD, SZ, and bipolar disorder. Based on our findings, PD seems distinguishable from related disorders and needs more scientific attention.

Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future.

Psychotic (delusional) depression and suicidal attempts: a systematic review and meta-analysis

OBJECTIVE

It still remains unclear whether psychotic features increase the risk of suicidal attempts in major depressive disorder. Thus, we attempted, through a systematic review coupled with a meta-analysis, to elucidate further whether unipolar psychotic depression (PMD) compared to non-PMD presents higher levels of suicidal attempts.

METHOD

A systematic search was conducted in PubMed, EMBASE, PsycINFO as well as in various databases of the so-called gray literature for all studies providing data on suicidal attempts in PMD compared to non-PMD, and the results were then subjected to meta-analysis.

RESULTS

Twenty studies met our inclusion criteria, including in total 1,275 PMD patients and 5,761 non-PMD patients. An elevated risk for suicide attempt for PMD compared to non-PMD patients was found: The total (lifetime) fixed-effects pooled OR was 2.11 (95% CI: 1.81-2.47), and the fixed-effects pooled OR of the five studies of the acute phase of the disorder was 1.93 (95% CI: 1.33-2.80). This elevated risk of suicidal attempt for PMD patients remained stable across all age groups of adult patients.

CONCLUSION

Despite data inconsistency and clinical heterogeneity, this systematic review and meta-analysis showed that patients with PMD are at a two-fold higher risk, both during lifetime and in acute phase, of committing a suicidal attempt than patients with non-PMD.

Psychotic (delusional) depression and completed suicide: a systematic review and meta-analysis

BACKGROUND

It remains unclear whether psychotic features increase the risk of completed suicides in unipolar depression. The present systematic review coupled with a meta-analysis attempts to elucidate whether unipolar psychotic major depression (PMD) compared to non-PMD presents higher rates of suicides.

METHODS

A systematic search was conducted in Scopus, PubMed, and "gray literature" for all studies providing data on completed suicides in PMD compared to non-PMD, and the findings were then subjected to meta-analysis. All articles were independently extracted by two authors using predefined data fields.

RESULTS

Nine studies with 33,873 patients, among them 828 suicides, met our inclusion criteria. PMD compared to non-PMD presented a higher lifetime risk of completed suicides with fixed-effect pooled OR 1.21 (95% CI 1.04-1.40). In a sub-analysis excluding a very large study (weight = 86.62%), and comparing 681 PMD to 2106 non-PMD patients, an even higher pooled OR was found [fixed-effect OR 1.69 (95% CI 1.16-2.45)]. Our meta-analysis may provide evidence that the presence of psychosis increases the risk of suicide in patients suffering from severe depression. The data are inconclusive on the contribution of age, mood congruence, comorbidity, and suicide method on PMD's suicide risk. The lack of accurate diagnosis at the time of suicide, PMD's diagnostic instability, and the use of ICD-10 criteria constitute the main study limitations.

CONCLUSIONS

The presence of psychosis in major depression should alert clinicians for the increased risk of completed suicide. Thus, the implementation of an effective treatment both for psychotic depression and patients' suicidality constitutes a supreme priority.

Rate and predictors of conversion from unipolar to bipolar disorder: A systematic review and meta-analysis

OBJECTIVES

For the first time to present a systematic review and meta-analysis of the conversion rate and predictors of conversion from unipolar disorder to bipolar disorder.

METHODS

A systematic literature search up to October 2016 was performed. For the meta-analysis, we only included studies that used survival analysis to estimate the conversion rate.

RESULTS

A total of 31 studies were identified, among which 11 used survival analyses, including two register-based studies. The yearly rate of conversion to bipolar disorder decreased with time from 3.9% in the first year after study entry with a diagnosis of unipolar disorder to 3.1% in years 1-2, 1.0% in years 2-5 and 0.8% in years 5-10. A total of eight risk factors were evaluated comprising gender, age at onset of unipolar disorder, number of depressive episodes, treatment resistance to antidepressants, family history of bipolar disorder, the prevalence of psychotic depression, the prevalence of chronic depression, and severity of depression. It was not possible to identify risk factors that were consistently or mainly confirmed to predict conversion across studies.

CONCLUSIONS

The conversion rate from unipolar to bipolar disorder decreases with time. It was not possible to identify predictors of conversion that were consistently or mainly confirmed across studies, which may be due to variations in methodology across studies.

Can lncRNAs be indicators for the diagnosis of early onset or acute schizophrenia and distinguish major depressive disorder and generalized anxiety disorder?-A cross validation analysis

Depression and anxiety are apparent symptoms in the early onset or acute phase of schizophrenia (SZ), which complicate timely diagnosis and treatment. It is imperative to seek an indicator to distinguish schizophrenia from depressive and anxiety disorders. Using lncRNA microarray profiling and RT-PCR, three up-regulated lncRNAs in SZ, six down-regulated lncRNAs in major depressive disorder (MDD), and three up-regulated lncRNAs in generalized anxiety disorder (GAD) had been identified as potential biomarkers. All the lncRNAs were, then, cross-validated in 40 SZ patients, 40 MDD patients, 40 GAD patients, and 40 normal controls. Compared with controls, three up-regulated SZ lncRNAs had a significantly down-regulated expression in GAD, and no remarkable differences existed between MDD and the controls. Additionally, the six down-regulated MDD lncRNAs were expressed in an opposite fashion in SZ, and the expression of the three up-regulated GAD lncRNAs were significantly different between SZ and GAD. These results indicate that the expression patterns of the three up-regulated SZ lncRNAs could not be completely replicated in MDD and GAD, and vice versa. Thus, these three SZ lncRNAs seem to be established as potential indicators for diagnosis of schizophrenia and distinguishing it from MDD and GAD. © 2017 Wiley Periodicals, Inc.

A systematic review and meta-analysis of prospective transition from major depression to bipolar disorder

OBJECTIVE

Some people with major depressive disorder (MDD) may be at a pre-onset stage for bipolar disorder (BD), where early identification or prevention efforts may be feasible. We aimed to identify rates and characteristics predictive of transition to BD in prospective follow-up studies of people with MDD.

METHODS

Using a systematic search strategy, we identified studies with a diagnostic ascertainment of MDD and BD of an adequate standard, and where the minimum length of follow-up was 6 months. We examined the incidence and point prevalence of BD and the pooled odds ratios (OR) for baseline predictors.

RESULTS

From 5554 unique publications, 56 were included. Nearly a quarter of adults (22.5%) and adolescents with MDD followed up for a mean length of 12-18 years developed BD, with the greatest risk of transition being in the first 5 years. The meta-analysis identified that transition from MDD to BD was predicted by family history of BD (OR = 2.89, 95% CI: 2.01-4.14, N = 7), earlier age of onset of depression (g = -0.33, SE = 0.05, N = 6) and presence of psychotic symptoms (OR = 4.76, 95% CI: 1.79-12.66, N = 5).

CONCLUSIONS

Participants with the identified risk factors merit closer observation and may benefit from prevention efforts, especially if outcomes broader than BD are considered.

What do childhood attention deficit/hyperactivity symptoms in depressed adults tell us about the bipolar spectrum?

BACKGROUND

This study aims to establish if adult patients with major depressive disorder (MDD) and childhood Attention Deficit/Hyperactivity disorder (ADHD) symptoms would be more frequently within the bipolar spectrum than depressed patients without childhood ADHD.

METHODS

This study was carried out in outpatients recruited by psychiatrists in private practice, with 3963 participants being included in the final sample. Clinicians filled out questionnaires about current depressive symptoms in their patients, lifetime bipolar symptoms, global assessment of functioning and parental history of both major depression and bipolar disorder. Patients assessed current level of anxiety and depressive symptoms and antecedents of childhood ADHD symptoms.

RESULTS

Depressed adults with significant childhood ADHD symptoms had a specific pattern of their major depressive episode compared to depressed patients without such symptoms. Subjects with childhood ADHD symptoms were more likely to report lifetime symptoms of mania/hypomania and to have a parent with type I or II bipolar disorder. The developmental trajectories of familial risk for lifetime bipolar symptoms showed that parental bipolar disorder influenced lifetime bipolar symptoms both through a direct pathway and an indirect pathway involving childhood ADHD symptoms. Childhood ADHD and number of depressive symptoms both made direct contributions to lifetime bipolar symptoms.

Gene expression-based biological test for major depressive disorder: an advanced study

PURPOSE

Recently, we could distinguished patients with major depressive disorder (MDD) from nonpsychiatric controls with high accuracy using a panel of five gene expression markers (ARHGAP24, HDAC5, PDGFC, PRNP, and SLC6A4) in leukocyte. In the present study, we examined whether this biological test is able to discriminate patients with MDD from those without MDD, including those with schizophrenia and bipolar disorder.

PATIENTS AND METHODS

We measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR), and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD.

RESULTS

This expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively.

CONCLUSION

Further research to identify MDD-specific markers is needed to improve the performance of this biological test.

Control-related frontal-striatal function is associated with past suicidal ideation and behavior in patients with recent-onset psychotic major mood disorders

OBJECTIVE

Suicide is highly-prevalent in major mood disorders, yet it remains unclear how suicidal ideation and suicidal behavior relate to brain functions, especially those that support control processes. We evaluated how prefrontal cortex (PFC) activity during goal-representation (an important component of cognitive control) relates to past suicidal ideation and behavior in patients with psychotic major mood disorders.

METHOD

30 patients with recent-onset of either DSM-IV-TR-defined bipolar disorder type I (n=21) or major depressive disorder (n=9) with psychotic features, but neither in a major mood episode nor acutely psychotic at study, were evaluated for past suicidal ideation and behavior (Columbia Suicide Severity Rating Scale) and functional MRI during cognitive control task performance. Group-level regression models of brain activation accounted for current depression, psychosis and trait impulsivity.

RESULTS

Intensity of past suicidal ideation was associated with higher control-related activation in right-hemisphere regions including the ventrolateral PFC (VLPFC) and orbitofrontal cortex, rostral insula, and dorsal striatum. Among those with past suicidal ideation (n=16), past suicidal behavior (n=8) was associated with higher control-related activation in right-hemisphere regions including VLPFC, rostrolateral PFC, and frontal operculum/rostral insula; and relatively lower activity in midline parietal regions, including cuneus and precuneus.

LIMITATIONS

The sample size of subjects with past suicidal behavior was modest, and all subjects were taking psychotropic medication.

CONCLUSIONS

This study provides unique evidence that in early-course psychotic major mood disorders, suicidal ideation and behavior histories directly relate to PFC-based circuit function in support of cognitive control.

Validation of electronic health record phenotyping of bipolar disorder cases and controls

OBJECTIVE

The study was designed to validate use of electronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects.

METHOD

EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype diagnoses was calculated against diagnoses from direct semistructured interviews of 190 patients by trained clinicians blind to EHR diagnosis.

RESULTS

The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR-classified control subject received a diagnosis of bipolar disorder on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based classifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses.

CONCLUSIONS

Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

Toward a comprehensive clinical staging model for bipolar disorder: integrating the evidence

OBJECTIVES

To describe key findings relating to the natural history and heterogeneity of bipolar disorder (BD) relevant to the development of a unitary clinical staging model. Currently proposed staging models are briefly discussed, highlighting complementary findings, and a comprehensive staging model of BD is proposed integrating the relevant evidence.

METHOD

A selective review of key published findings addressing the natural history, heterogeneity, and clinical staging models of BD are discussed.

RESULTS

The concept of BD has broadened, resulting in an increased spectrum of disorders subsumed under this diagnostic category. Different staging models for BD have been proposed based on the early psychosis literature, studies of patients with established BD, and prospective studies of the offspring of parents with BD. The overarching finding is that there are identifiable sequential clinical phases in the development of BD that differ in important ways between classical episodic and psychotic spectrum subtypes. In addition, in the context of familial risk, early risk syndromes add important predictive value and inform the staging model for BD.

CONCLUSIONS

A comprehensive clinical staging model of BD can be derived from the available evidence and should consider the natural history of BD and the heterogeneity of subtypes. This model will advance both early intervention efforts and neurobiological research.

Psychotic major depression in older people: a systematic review

OBJECTIVE

This study aimed to systematically review available evidence relevant to the following issues: (1) whether psychotic major depression (PMD) in older people differs in overall severity from non-PMD, besides the presence of psychotic symptoms; (2) whether it constitutes a distinct clinical entity from non-PMD; and (3) whether it differs from PMD in younger adults.

DESIGN

A computerized MEDLINE, PsycINFO and the entire Cochrane Library search has been performed in June 2013 for prospective controlled studies investigating PMD features in older people.

RESULTS

Thirty-five relevant studies were identified. PMD in older people compared with non-PMD has been shown to present with overall more severe depressive symptomatology, more psychomotor disturbance, more guilt feelings, more depressive episodes with psychosis, worse prognosis, more severe executive dysfunction associated with frontal lobe atrophy, and lower serum dopamine β-hydroxylase activity. No differences in the efficacy of an antidepressant plus antipsychotic combination versus antidepressant monotherapy in the acute treatment as well as in the maintenance treatment were found. PMD in older patients is characterized by more somatic complaints and delusions of hypochondriacaland impending disaster content and by a lower comorbidity with anxiety disorders compared with PMD in younger adults.

CONCLUSIONS

Psychotic major depression in older people is associated with higher severity in most clinically important key features than in non-PMD. However, available evidence is still insufficient for the conclusive elucidation of its nosological status. Finally, the differences between PMD in older and younger patients can be attributed to biological and psychosocial changes of old age.

Diagnostic trajectory, interplay and convergence/divergence across all 12 DSM-IV psychotic diagnoses: 6-year follow-up of the Cavan-Monaghan First Episode Psychosis Study (CAMFEPS)

BACKGROUND

The boundaries of psychotic illness and the extent to which operational diagnostic categories are distinct in the long term remain poorly understood. Clarification of these issues requires prospective evaluation of diagnostic trajectory, interplay and convergence/divergence across psychotic illness, without a priori diagnostic or other restrictions.

METHOD

The Cavan-Monaghan First Episode Psychosis Study (CAMFEPS), conducted using methods to attain the closest approximation to epidemiological completeness, incepts all 12 DSM-IV psychotic diagnoses. In this study we applied methodologies to achieve diagnostic reassessments on follow-up, at a mean of 6.4 years after first presentation, for 196 (97%) of the first 202 cases, with quantification of prospective and retrospective consistency.

RESULTS

Over 6 years, the 12 initial psychotic diagnoses were characterized by numerous transitions but only limited convergence towards a smaller number of more stable diagnostic nodes. In particular, for initial brief psychotic disorder (BrP), in 85% of cases this was the harbinger of long-term evolution to serious psychotic illness of diagnostic diversity; for initial major depressive disorder with psychotic features (MDDP), in 18% of cases this was associated with mortality of diverse causality; and for initial psychotic disorder not otherwise specified (PNOS), 31% of cases continued to defy DSM-IV criteria.

CONCLUSIONS

CAMFEPS methodology revealed, on an individual case basis, a diversity of stabilities in, and transitions between, all 12 DSM-IV psychotic diagnoses over 6 years; thus, psychotic illness showed longitudinal disrespect to current nosology and may be better accommodated by a dimensional model. In particular, a first episode of BrP or MDDP may benefit from more vigorous, sustained interventions.

Disorders and borders: psychiatric genetics and nosology

Over the past century, the definition and classification of psychiatric disorders has evolved through a combination of historical trends, clinical observations, and empirical research. The current nosology, instantiated in the DSM-5 and ICD-10, rests on descriptive criteria agreed upon by a consensus of experts. While the development of explicit criteria has enhanced the reliability of diagnosis, the validity of the current diagnostic categories has been the subject of debate and controversy. Genetic studies have long been regarded as a key resource for validating the boundaries among diagnostic categories. Genetic epidemiologic studies have documented the familiality and heritability of clinically defined psychiatric disorders and molecular genetic studies have begun to identify specific susceptibility variants. At the same time, there is growing evidence from family, twin and genomic studies that genetic influences on psychiatric disorders transcend clinical boundaries. Here I review this evidence for cross-disorder genetic effects and discuss the implications of these findings for psychiatric nosology. Psychiatric genetic research can inform a bottom-up reappraisal of psychopathology that may help the field move beyond a purely descriptive classification and toward an etiology-based nosology.

Diagnosis and evaluation of hallucinations and other psychotic symptoms in children and adolescents

Recognizing positive psychotic symptoms and their diagnostic context in youth is challenging. A large minority say they "hear things others do not hear," though they seldom present with complaints of hallucinations or delusions. Few have schizophrenia spectrum disorder, but many have other psychiatric disorders. Frequently, they have psychotic symptoms for an extended period before diagnosis. Clinicians should understand psychotic symptoms and their differential diagnoses. This article reviews the epidemiology, associated diagnoses, and prognosis of hallucinations and delusions in youth. Strategies for optimizing the clinical diagnostic interview, appropriate laboratory tests, indications for psychological testing, and rating scales are reviewed.

Affective disorders and psychosis in youth

The significance of psychosis has yet to be fully understood and research is complicated because psychosis is often a state rather than trait occurrence. In youth, psychoticlike phenomena are common. Rates of lifetime psychotic symptoms are higher than rates of psychosis during a current episode of mania or depression, at least in youth. Rates vary widely between studies. Hallucinations are also more common than delusions in youth. Psychotic phenomena can be mood congruent or incongruent. A good mental status examination requires close questioning. There are several interviews that structure how questions are asked, and rating scales that help anchor severity.

Structural and functional neuroimaging studies in major depressive disorder with psychotic features: a critical review

The relationship between major depressive disorder with psychotic (MDDP) features and schizophrenia has long been recognized, and the neurobiological boundaries between these disorders can nowadays be investigated using neuroimaging techniques. This article provides a critical review of such studies, addressing how they support a dimensional approach to the nosology and pathophysiology of psychotic disorders. A proportion of neuroimaging studies carried out to date indicate that MDDP subjects display structural and functional abnormalities in some brain regions specifically implicated in the pathophysiology of mood disorders, such as the subgenual cingulate cortex. This reinforces the validity of the classification of MDDP in proximity to major depression without psychosis. There is some neuroimaging evidence that MDDP may be associated with additional brain abnormalities relative to nonpsychotic major depression although less prominently in comparison with findings from the neuroimaging literature on schizophrenia. Brain regions seen as critical both to emotional processing and to models of psychotic symptoms, such as the hippocampus, insula, and lateral prefrontal cortex, have been implicated in separate neuroimaging investigations of either schizophrenia or major depression, as well as in some studies that directly compared depressed patients with and without psychotic features. These brain regions are key targets for future studies designed to validate imaging phenotypes more firmly associated with MDDP, as well as to investigate the relationship between these phenotypes and possible etiological influences for MDDP.