Family Study of Affective and Anxiety Spectrum Disorders

National Institute Of Mental Health

Investigators

Linked publications, trials & patents

Abstract

To date, over 600 probands and nearly 1200 of their relatives have completed the study, including 200 children between the ages of 7-17 years. Approximately 600 individuals have also been evaluated at the NIH Clinical Center. Probands represent not only a large range of psychiatric disorders including mood and anxiety spectrum, but also substantial medical comorbidity related to sleep, migraine, pain, and cardiovascular conditions, as well as controls with minimal to no pathology. We are focusing on remotely collecting measures including mobile assessments and saliva for extracting genetics data, recontacting relatives for updated information, and expanding on our findings in new research tools and studies. During the past year, we have devoted substantial effort to validating and modernizing research operations. To streamline data collection, management and analyses, and to facilitate research collaboration, we updated our primary mental health interview to meet the latest diagnostic criteria (DSM-V) for integration into a sophisticated data capture system entitled the Diagnostic Assessment for Spectrum of Health (DASH). This system will utilize the power of modularized data capture combined with automated reporting features. We continue to work with experts to further develop new data science methods and tools, including efficient platforms to visualize multilevel data in R, a platform that combines data acquisition with data management and analysis, and computer programs to exploit the item-level data from diagnostic interviews and related measures, including algorithms for subthreshold syndromes, clinical phenomena, and self-report measures. This collaboration with developers and external researchers has led to the development of a new long-term data acquisition platform for health research (MindLogger), which will be used for cognitive testing, electronic diary applications, and tracking of mobile assessments in our studies (Klein et al, 2021). We have continued to devote research effort to collect follow-up data from families to maximize our ability to study causes, correlates, and consequences of these interrelated conditions. This involved repeating diagnostic interviews and self-report clinical and psychosocial measures, in order to test the stability of these measures over time and track their relationship with emerging mental and medical disorders in families. We developed and obtained scientific approval (by the NIMH Science Review Committee) for a new research protocol that will replicate and interrogate findings from our family study. This protocol employs an intensive longitudinal design with combined ecological and inpatient and outpatient laboratory assessments in the NIH Clinical Center to extensively characterize the associations between motor activity and mood states by expanding the assessments of individual, physiologic, cognitive, and environmental correlates. Recent publications over the last year focused on analyzing existing data from our family study to examine aggregation of mood and anxiety disorders in probands and first-degree relatives. We examined the familial aggregation/coaggregation of cannabis use disorder (CUD) and its association with mood disorder subtypes. Findings confirm the familial aggregation of CUD and show an increased risk of CUD among relatives of probands with bipolar 2 disorder (BP2), thereby suggesting that CUD shares a common underlying diathesis with BP2 (Quick et al, 2022). We also investigated the comorbidity, familial aggregation, and cross-aggregation of back/neck pain with mood disorder subtypes. Findings identified common familial risk factors underlying back/neck pain with major depressive disorder (MDD), as well as extensive within-individual comorbidity of bipolar disorder (BD) with back/neck pain (Stapp et al, 2022). Additionally, our group contributed to a publication proposing to establish large, global longitudinal cohorts of BD studied consistently in a multidimensional and multidisciplinary manner to determine etiology and help improve treatment (McInnis et al, 2022). The article discussed the collection of a broad range of data reflecting heterogenic phenotypic manifestations of BD that include dimensional and categorical measures of mood, neurocognitive, personality, behavior, sleep and circadian, life-story, and outcomes domains, in combination with genetic and biological information, to enhance ongoing and future studies of BD. These publications highlight the need for future studies that identify common factors that can inform prevention and interventions across mental and physical health. We continue to devote major effort toward methods development and dissemination and analyses of dynamic phenotypes derived from actigraphy and electronic diaries, which permit investigation of fluctuations in core domains of mood disorders in the context of daily life. This work has been conducted in conjunction with collaborators across multiple sites including Lausanne, Switzerland; Sydney, Australia; Amsterdam, Netherlands; and Hong Kong, China. With collaborators at Johns Hopkins University, we focused on educating researchers about the knowledge that can be gained by conducting analyses that respect time of day rather than averaging across days and weeks. Such methodological collaborations highlight opportunities for discovery in psychiatric research afforded by mobile technologies. We previously studied mood dynamics and reactivity and differential patterns of reactivity for those with bipolar 1 disorder (BP1) compared to those with BP2, MDD, and anxiety disorders, providing phenomenological support for distinguishing BP1 from other affective disorders. In contrast, groups did not differ in their degree of mood variability or instability compared to controls. These findings contribute to our understanding of the underlying bases of mood and anxiety disorders, consistent with the overall objectives of our research program. Finally, expanding upon these findings as well as our prior findings on the role of activity in mood regulation, we have established a workgroup which will conduct follow-up analyses to examine the influence of other factors such as substance use/disorders, exercise, and eating in these relationships. Public Health Impact: Integration of the clinical, neuropsychological, and psychophysiological measures within families will render an in-depth analysis of the mechanisms crucial to mood and anxiety disorders and their underlying diatheses. This will not only lead to a better fundamental, etiologic understanding of these conditions, but also may inform the development of novel treatment options, possible strategies for early intervention, and potential prevention in those with elevated risk for these conditions. Future Plans: During the next year, we plan to shift our efforts to center on the causes, correlates, and consequences of mood spectrum disorders, guided by our growing body of findings related to energy, motor activity, and other biorhythms linked to homeostasis; mental-medical comorbidity and the mechanistic association thereof; and psychiatric endophenotypes and risk processes associated with BD ranging from anxiety disorders to substance use disorders to suicide. Our analyses and new data collection will further discern subgroups for more intensive follow-up and examination of key clinical and biological questions.