Cluster analysis with MOODS-SR illustrates a potential bipolar disorder risk phenotype in young adults with remitted major depressive disorder.

OBJECTIVES: Delays in the diagnosis and detection of bipolar disorder can lead to adverse consequences, including improper treatment and increased suicide risk. The Mood Spectrum Self-Report Measure (MOODS-SR) was designed to capture the full spectrum of lifetime mood symptomology with factor scores for depression and mania symptom constellations. The utility of the MOODS-SR as a tool to investigate homogeneous subgroups was examined, with particular focus on a possible bipolar risk subgroup. Moreover, potential patterns of differences in MOODS-SR subtypes were probed using cognitive vulnerabilities, neuropsychological functioning, and ventral striatum connectivity. METHODS: K-mean cluster analysis based on factor scores of MOODS-SR was used to determine homogeneous subgroupings within a healthy and remitted depressed young adult sample (N = 86). Between-group comparisons (based on cluster subgroupings) were conducted on measures of cognitive vulnerabilities, neuropsychological functioning, and ventral striatum rs-fMRI connectivity. RESULTS: Three groups of participants were identified: one with minimal symptomology, one with moderate primarily depressive symptomology, and one with more severe manic and depressive symptomology. Differences in impulsivity, neuroticism, conscientiousness, facial perception accuracy, and rs-fMRI connectivity exist between moderate and severe groups. CONCLUSIONS: Within a sample of people with and without depression histories, a severe subgroup was identified with potentially increased risk of developing bipolar disorder through use of the MOODS-SR. This small subgroup had higher levels of lifetime depression and mania symptoms. Additionally, differences in traits, affective processing, and connectivity exist between those with a more prototypic unipolar subgrouping and those with potential risk for developing bipolar disorder.