A latent class analysis of parental bipolar disorder: examining associations with offspring psychopathology

Bipolar disorder (BD) is highly heterogeneous, and course variations are associated with patient outcomes. This diagnostic complexity challenges identification of patients in greatest need of intervention. Additionally, course variations have implications for offspring risk. First, latent class analysis (LCA) categorized parents with BD based on salient illness characteristics: BD type, onset age, polarity of index episode, pole of majority of episodes, rapid cycling, psychosis, anxiety comorbidity, and substance dependence. Fit indices favored three parental classes with some substantively meaningful patterns. Two classes, labeled “Earlier-Onset Bipolar-I” (EO-I) and “Earlier-Onset Bipolar-II” (EO-II), comprised parents who had a mean onset age in mid-adolescence, with EO-I primarily BD-I parents and EO-II entirely BD-II parents. The third class, labeled “Later-Onset BD” (LO) had an average onset age in adulthood. Classes also varied on probability of anxiety comorbidity, substance dependence, psychosis, rapid cycling, and pole of majority of episodes. Second, we examined rates of disorders in offspring (ages 4–33, Mage=13.46) based on parental latent class membership. Differences emerged for offspring anxiety disorders only such that offspring of EO-I and EO-II parents had higher rates, compared to offspring of LO parents, particularly for daughters. Findings may enhance understanding of BD and its nosologyThis study was funded by two Brain & Behavior Research Foundation (formerly NARSAD) Independent Investigator Awards (PI: Nierenberg), a Brain & Behavior Research Foundation Young Investigator Award (PI: Henin) generously supported in part by the SHINE Initiative, and an MGH Claflin Award (PI: Henin). We thank David A. Langer, Ph.D., Thomas M. Olino, Ph.D., and Meredith Lotz Wallace, Ph.D. for their consultation. (Brain & Behavior Research Foundation; Brain & Behavior Research Foundation Young Investigator Award; SHINE Initiative; MGH Claflin Award)Accepted manuscrip

Discriminant and Concurrent Validity of a Simplified DSM-Based Structured Diagnostic Instrument for the Assessment of Autism Spectrum Disorders in Youth and Young Adults

Background: To evaluate the concurrent and discriminant validity of a brief DSM-based structured diagnostic interview for referred individuals with autism spectrum disorders (ASDs). Methods: To test concurrent validity, we assessed the structured interview's agreement in 123 youth with the expert clinician assessment and the Social Responsiveness Scale (SRS). Discriminant validity was examined using 1563 clinic-referred youth. Results: The structured diagnostic interview and SRS were highly sensitive indicators of the expert clinician assessment. Equally strong was the agreement between the structured interview and SRS. We found evidence for high specificity for the structured interview. Conclusions: A simplified DSM-based ASD structured diagnostic interview could serve as a useful diagnostic aid in the assessment of subjects with ASDs in clinical and research settings

Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and dif-ferences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA)

Differentiating Anxious and Depressive Self-Statements: Combined Factor Structure of the Anxious Self-Statements Questionnaire and the Automatic Thoughts Questionnaire-Revised

Cognitive models of negative emotion suggest that depression and anxiety are associated with different cognitive features. However, distinguishing anxious from depressive self-talk is difficult because of the overlap between anxiety and depression. The Automatic Thoughts Questionnaire-Revised was developed to assess self-statements related to depression and the Anxious Self-Statement Questionnaire to assess self-statements related to anxiety. However, confirmatory factor analyses of the pooled items from both measures suggested that this implicit two-factor model did not fit the data. Instead, an exploratory common factor analysis yielded four orthogonal factors: self-statements reflecting depression/hopelessness, self-statements reflecting one's inability to cope, self-statements reflecting anxiety/uncertainty about the future, and positive affect self-statements. In an exploratory hierarchical factor analysis, the first three factors loaded onto a single higher order factor, while positive affect self-statements did not. Attempts to predict depression and trait anxiety on the basis of these factor scores produced complex results, at least potentially due to the relative impurity of the criterion measures. These results provide evidence for the differentiation of anxious and depressive self-talk as well as for the common ground shared by these aspects of internal dialogue. They also support the future study of the factors from the ATQ-R and ASSQ in relation to more construct-pure measures of anxiety and depression

Differentiating Anxious and Depressive Self-statements in Youth: Factor Structure of the Negative Affect Self-statement Questionnaire Among Youth Referred to an Anxiety Disorders Clinic

Conducted a factor analysis on the items from the Negative Affect Self-Statement Questionnaire (NASSQ; Ronan, Kendall, & Rowe, 1994). This analysis yielded 4 factors (Depressive Self-Statements, Anxiety/Somatic Self-Statements, Negative Affect Self-Statements, and Positive Affect Self-Statements) broadly consistent with both the content-specificity hypothesis (Beck & Clark, 1988) and L. A. Clark and Watson's (1991b) tripartite model of anxiety and depression. The association between children's self-talk and measures of trait anxiety and depression was also examined. Self-statements with content theoretically specific to depression were the best predictors of self-reported depressive symptoms, but the results were less clear for trait anxiety. Overall, these results provide evidence for the discriminability of anxious and depressive self-talk in youth and for the utility of the NASSQ as a cognitive assessment instrument

Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and dif-ferences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA)

Discriminant and concurrent validity of a simplified DSM-based structured diagnostic instrument for the assessment of autism spectrum disorders in youth and young adults

Abstract Background To evaluate the concurrent and discriminant validity of a brief DSM-based structured diagnostic interview for referred individuals with autism spectrum disorders (ASDs). Methods To test concurrent validity, we assessed the structured interview's agreement in 123 youth with the expert clinician assessment and the Social Responsiveness Scale (SRS). Discriminant validity was examined using 1563 clinic-referred youth. Results The structured diagnostic interview and SRS were highly sensitive indicators of the expert clinician assessment. Equally strong was the agreement between the structured interview and SRS. We found evidence for high specificity for the structured interview. Conclusions A simplified DSM-based ASD structured diagnostic interview could serve as a useful diagnostic aid in the assessment of subjects with ASDs in clinical and research settings.</p