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Predicting change in diagnosis from major depression to bipolar disorder after antidepressant initiation.

ABSTRACT: We aimed to develop and validate classification models able to identify individuals at high risk for transition from a diagnosis of depressive disorder to one of bipolar disorder. This retrospective health records cohort study applied outpatient clinical data from psychiatry and nonpsychiatry practice networks affiliated with two large academic medical centers between March 2008 and December 2017. Participants included 67,807 individuals with a diagnosis of major depressive disorder or depressive disorder not otherwise specified and no prior diagnosis of bipolar disorder, who received at least one of the nine antidepressant medications. The main outcome was at least one diagnostic code reflective of a bipolar disorder diagnosis within 3 months of index antidepressant prescription. Logistic regression and random forests using diagnostic and procedure codes as well as sociodemographic features were used to predict this outcome, with discrimination and calibration assessed in a held-out test set and then a second academic medical center. Among 67,807 individuals who received at least one antidepressant medication, 925 (1.36%) subsequently received a diagnosis of bipolar disorder within 3 months. Models incorporating coded diagnoses and procedures yielded a mean area under the receiver operating characteristic curve of 0.76 (ranging from 0.73 to 0.80). Standard supervised machine learning methods enabled development of discriminative and transferable models to predict transition to bipolar disorder. With further validation, these scores may enable physicians to more precisely calibrate follow-up intensity for high-risk patients after antidepressant initiation.

SUBMITTER: Pradier MF

PROVIDER: S-EPMC7852537 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Pharmacogenomic overlap between antidepressant treatment response in major depression & antidepressant associated treatment emergent mania in bipolar disorder.

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| S-EPMC7006450 | biostudies-literature

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Subthreshold hypomanic symptoms in progression from unipolar major depression to bipolar disorder.

Project description:The authors assessed whether subthreshold hypomanic symptoms in patients with major depression predicted new-onset mania or hypomania.The authors identified 550 individuals followed for at least 1 year in the National Institute of Mental Health Collaborative Depression Study with a diagnosis of major depression at intake. All participants were screened at baseline for five manic symptoms: elevated mood, decreased need for sleep, unusually high energy, increased goal-directed activity, and grandiosity. Participants were followed prospectively for a mean of 17.5 years and up to 31 years. The Longitudinal Interval Follow-up Examination was used to monitor course of illness and to identify any hypomania or mania. The association of subthreshold hypomanic symptoms at baseline with subsequent hypomania or mania was determined in survival analyses using Cox proportional hazards regression.With a cumulative probability of one in four on survival analysis, 19.6% (N=108) of the sample experienced hypomania or mania, resulting in revision of diagnoses for 12.2% to bipolar II disorder and 7.5% to bipolar I disorder. Number of subthreshold hypomanic symptoms, presence of psychosis, and age at illness onset predicted progression to bipolar disorder. Decreased need for sleep, unusually high energy, and increased goal-directed activity were specifically implicated.Symptoms of hypomania, even when of low intensity, were frequently associated with subsequent progression to bipolar disorder, although the majority of patients who converted did not have any symptoms of hypomania at baseline. These results suggest that continued monitoring for the possibility of progression to bipolar disorder is necessary over the long-term course of major depressive disorder.

| S-EPMC3042431 | biostudies-literature

Identifying genetic differences between bipolar disorder and major depression through multiple GWAS.

Project description:BackgroundAccurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD).AimsHere, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis.MethodsBased on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses.ResultsWhile our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD.ConclusionsWe find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.

| S-EPMC10896417 | biostudies-literature

Affect Regulation-Related Emergent Brain Network Properties Differentiate Depressed Bipolar Disorder From Major Depression and Track Risk for Bipolar Disorder.

Project description:BackgroundIndividuals with or at risk for bipolar disorder (BD) often present initially for the treatment of depressive symptoms. Unfortunately, pharmacological treatments for major depressive disorder (MDD) can be iatrogenic, precipitating mania that may not have otherwise occurred. Current diagnostic procedures rely solely on self-reported/observable symptoms, and thus alternative data sources, such as brain network properties, are needed to supplement current self-report/observation-based indices of risk for mania.MethodsBrain connectivity during affect maintenance/regulation was examined in a large (N = 249), medication-free sample of currently depressed patients with BD (n = 50) and MDD (n = 116) and healthy control subjects (n = 83). BD risk was categorized in a subset of patients with MDD. We used graph theory to identify emergent network properties that differentiated between patients with BD and MDD and between patients with MDD at high and low risk for BD.ResultsBD and MDD differed in the extent to which the rostral anterior cingulate cortex was embedded in the local network, amount of influence the hippocampus exerted over global network communication, and clarity of orbitofrontal cortex communication. Patients with MDD at high risk for BD showed a pattern of local network clustering around the right amygdala that was similar to the pattern observed in healthy control subjects, whereas patients with MDD at low risk for BD deviated from this pattern.ConclusionsBD and MDD differed in emergent network mechanisms subserving affect regulation, and amygdala properties tracked BD risk in patients with MDD. If replicated, our findings may be combined with other markers to assess the presence of BD and/or BD risk in individuals presenting with depressive symptoms to prevent the use of iatrogenic treatments.

| S-EPMC8993939 | biostudies-literature

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