Family Study of Affective and Anxiety Spectrum Disorders

National Institute Of Mental Health

Investigators

Linked publications, trials & patents

Abstract

The Rhythm and Blues Study (R&B) is employing a comprehensive set of clinical, psychophysiological and neuropsychological measures that extend initial Family Study measures, but novel approaches are also being employed to address the key study aims including: 1) clinical information from a semi-structured diagnostic interview for mood and anxiety disorders; structured diagnostic interviews for major headache syndromes and sleep disorders; family history information on psychiatric disorders, sleep disorders and headache syndromes; a series of self-reported measures of symptoms, sleep patterns and personality; medical history, family structure, history and function, and major life/family events; 2) mobile activity assessments, including the multidomain ecological toolkit to capture accelerometry, light, and daily diary data, and 3) in person evaluations at the NIH Clinical Center (NIH CC), including physical and neurological examination; laboratory measures of metabolic, cardiovascular, and immunologic function; structural magnetic resonance imaging; DXA and exercise tests; computerized cognitive assessments; and olfactory function testing. Over 600 probands and nearly 1200 of their relatives have completed the Family Study, including 200 children between 7-17 years old. Approximately 600 have also been evaluated at the NIH CC under this protocol. 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. Over the past year, we continued to focus on analyzing our data from the Family Study and expanding our findings in new research tools and studies, including the R&B protocol. Through R&B, we ascertained participants from the community in addition to previous Family Study participants. By recruiting participants from the community as well as the Family Study, we employ intensive longitudinal design with combined ecological and laboratory assessments in the NIH CC to extensively characterize the associations among motor activity, circadian rhythms, and mood states by expanding the assessments of individual, physiologic, cognitive, and environmental correlates. To date, over 100 participants have been enrolled and are completing interviews and study procedures. Additionally, this year we expanded our recruitment for the inpatient and outpatient phases of R&B, where over 50 participants have completed clinical and laboratory measures, including physical and neurological exams, biological samples, cognitive assessments, and sensory testing. Furthermore, participants began 2-week mobile activity tasks and over 90 participants have completed at least 1 study epoch including ecological momentary assessments (EMA), actigraphy, and light sensory tasks. During the past year, we continued to validate and modernize research operations. For streamlined data collection, management and analyses, and to facilitate research collaboration, we updated primary study instruments to meet the latest diagnostic and headache criteria (DSM-V, ICHD-3) for integration into a sophisticated data capture system entitled the Diagnostic Assessment for Spectrum of Health (DASH). This system utilizes the power of modularized data capture combined with automated reporting features. We updated our screening and physical health instruments to incorporate as self-administered modules into the DASH. The DASH platform will represent a comprehensive assessment tool measuring multiple domains of mental and physical health and will have a user-friendly dashboard where specific modules assessing mental and physical health can be easily selected and administered. In addition to the DASH, we continued to work with experts to 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. Our collaboration with developers and external researchers has led to more developments in a new long-term data acquisition platform for health research (Curious/formerly MindLogger), to capture clinical and ambulatory testing and mobile assessments in our studies. We continue to devote major effort towards methods development and analyses of data from the Family Study sample to study the aggregation of mood disorders subtypes and behaviors in families and dynamic phenotypes derived from mobile health measures. In a study of N=807 participants, lifetime smoking and mood disorders were assessed through a study of semi-structured diagnostic interviews and family histories (Conway et al, 2025). It was found that while all smoking behaviors were familial, subtypes of major depression and bipolar disorder were risk factors for smoking, while anxiety typically preceded smoking onset. These results suggested smoking prevention and treatment may reduce smoking risk and interventions may be useful in preventing or further reducing behaviors that lead to future health risks. In another study of N=497 Family Study participants, data was used to review multiple within-day self-reported behavioral data by creating a real-time functional principal component analysis (Dey et al, 2024). The development and use of this model allows for the successful analysis of multiple data types (physical health: continuous, pain: truncated, mood state: ordinal, and daily life events: binary) to study differences in health patterns based on time of day. 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: We plan to continue 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 bipolar disorder 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 especially within the context of the R&B. Findings from both studies will have implications for interventions in both the general community and clinical samples of people with mood disorders.