Functional outcomes across development in offspring of parents with bipolar disorder

Objective: Whereas the risk and course of psychopathology in offspring of parents with bipolar disorder (BD) have been the primary focus of high-risk offspring studies to date, functional outcomes have not been given much attention. We present a systematic review of functional outcomes and quality of life (QoL) across development in offspring of parents with BD and aim to explore the role of offspring psychopathology in these outcomes. Method: We searched Embase, MEDLINE, PsycINFO, Web of Science, Cochrane Central, and Google Scholar from inception to June 24, 2022, for studies referring to functional outcomes (global, social, academic or occupational) or QoL in offspring of parents with BD. Results: From the 6470 records identified, 39 studies were retained (global = 17; social = 17; school = 16; occupational = 3; QoL = 5), including 13 studies that examined multiple domains. For all domains, high heterogeneity was found in study methods and quality. Only 56 % of studies adjusted for offspring psychopathology, impeding interpretation. Global and social functioning generally seemed to be impaired among older offspring (&gt;16 years). Academic performance appeared to be unaffected. School behavior, occupational functioning, and QoL showed mixed results. Offspring psychopathology is associated with social functioning, but the relationship of offspring psychopathology with other domains is less clear. Conclusion: Studies on functional outcome in offspring of parents with BD show predominantly mixed results. Inconsistent adjustment of psychopathology and age limits conclusive interpretation. Functional outcomes should be prioritized as research topics in high-risk studies and the potential associations between familial risk status, offspring psychopathology, and age may inform prevention strategies.</p

Using genetic algorithms to uncover individual differences in how humans represent facial emotion

Emotional facial expressions critically impact social interactions and cognition. However, emotion research to date has generally relied on the assumption that people represent categorical emotions in the same way, using standardized stimulus sets and overlooking important individual differences. To resolve this problem, we developed and tested a task using genetic algorithms to derive assumption-free, participant-generated emotional expressions. One hundred and five participants generated a subjective representation of happy, angry, fearful and sad faces. Population-level consistency was observed for happy faces, but fearful and sad faces showed a high degree of variability. High test-retest reliability was observed across all emotions. A separate group of 108 individuals accurately identified happy and angry faces from the first study, while fearful and sad faces were commonly misidentified. These findings are an important first step towards understanding individual differences in emotion representation, with the potential to reconceptualize the way we study atypical emotion processing in future research