Family Study of Affective and Anxiety Spectrum Disorders

National Institute Of Mental Health

Investigators

Linked publications & trials

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. Over the past year, we focused on remotely collecting saliva and pooling existing samples for extracting genetics data, recontacting relatives for updated information, and expanding on our findings in new research tools and studies, including a newly approved research protocol under 000754-M, NCT05669703. 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 continued to update 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 also began a comprehensive review to update our demographic, medical history, headache, sleep and family history instruments to incorporate as modules into the DASH. As a result, the DASH represents a comprehensive assessment tool measuring multiple domains of mental and physical health. Further, the DASH 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 platform, we continued 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. Our collaboration with developers and external researchers has led to more developments in a new long-term data acquisition platform for health research (MindLogger), which we plan to use for cognitive testing, electronic diary applications, and tracking of mobile assessments in our studies. 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 administering 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 approvals by the NIMH Science Review Committee and the Institutional Review Board for a new research protocol (NIMH Rhythms and Blues Study) that will more deeply interrogate findings from our family study. By recruiting participants from the community as well as the NIMH Family Study, this new 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 among motor activity, circadian rhythms, and mood states by expanding the assessments of individual, physiologic, cognitive, and environmental correlates. For this new protocol, we have begun to pilot our updated diagnostic instruments, self-report surveys, and ecological measures, and tested a new computerized screener. 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. We are also continuing our work to examine mood disorder subtypes from childhood to adulthood, in collaboration with researchers in our parallel family study in Lausanne, Switzerland. In our most recent publication, we examined the occurrence of psychotic features within mood episodes in patients with bipolar 1 disorder (BD-1), and the associations with mood-congruent (MC) and mood-incongruent (MI) features. In a sample of thoroughly characterized patients with bipolar disorder (BD), our research suggests that patients with psychotic symptoms, particularly those with MI features, have more clinical severity in terms of a higher likelihood of reporting hallucinations, suicidal attempts, and comorbid cannabis dependence. These findings provide additional evidence supporting the distinction between BD-1 with and without psychotic features as well as the distinction between MI and MC psychotic features, highlighting the need for more thorough psychopathological evaluations to assess the presence of these symptoms in patients (Elowe et al, 2022). 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 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 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 especially within the context of the NIMH Rhythms and Blues Study.