Motor Activity Research Consortium for Health (mMarch)

National Institute Of Mental Health

Investigators

Linked publications, trials & patents

Abstract

There is growing interest in studying the environmental, biologic, and genetic correlates of the components of motor activity as well as the relationships between motor activity with sleep, exercise, mood, and cognitive functioning. Aggregation of the findings across studies is challenged by the substantial differences in both the study goals, procedures, and statistical methods. Therefore, mMARCH seeks greater coordination across studies in the procedures and analytic methods of functional data associated with mood and other disorders. In the past year at NIMH, we have been expanding on intensive multimodal studies of youth and within families, following up samples to examine stability, and expanding on domains of assessment. Across the initiative, we have developed a new processing platform (GGIR, an R package to analyze accelerometer data); processed and analyzed actigraphy data from 6 sites; applied novel statistical methods including functional data analysis and Joint Individual Variance Explained (JIVE) to actigraphy cross-site data; collected and analyzed concomitant ecological momentary assessment (EMA) data from 2 sites; examined cross device features; and expanded to new sites including Yale, Toronto (CAMH), and the Healthy Brain Network, NY. Additionally, over the last year we collaborated to publish several key papers related to motor activity and daily rhythms monitoring. With researchers in Australia, we outlined evidence for a new clinical phenotype- circadian depression. We hypothesized this phenotype as cross-cutting, accounting for some cases with diagnoses currently conceptualized as depressive, bipolar disorder (BD), anxious, psychotic, and/or somatic physical syndromes such as chronic fatigue and fibromyalgia. We proposed that the key clinical features of circadian depression included disrupted 24-hour sleep wake cycles, reduced motor activity, low subjective energy, and weight gain. Further investigation is needed to evaluate the utility of the proposed phenotype and to guide the optimal use of circadian-targeted interventions (Carpenter et al, 2021). We continued to join forces with collaborators from the Netherlands Study of Depression and Anxiety (NESDA) to employ the processing and statistical methods that we have developed to pursue study specific hypotheses, and we published a study on the association between daily motor activity patterns assessed via actigraphy and 1) sociodemographic, health and lifestyle and sampling factors, and 2) psychiatric clinical characteristics in the NESDA site (Difrancesco et al, 2021). Results demonstrated that the presence and severity of depression/anxiety disorders were associated with a lower overall activity pattern but not with the time of activity, while age, work/school days and season were strongly associated with patterns and time of activity. It is recommended that future studies on motor activity in depression/anxiety take these patterns into account. Additionally, in a commentary related to a recent publication in Bipolar Disorders, we advocated for the inclusion of digital technologies as additional choices for the treatment and prevention of the high risk of suicide of BD (Panchal et al, 2021). Two ongoing collaborator studies of treatment of youth at risk for mood disorders (Strauss, Battaglia et al, CAMH) and suicide (Blumberg et al, Yale) are now employing the procedures that we have developed for real-time assessments of mood and related domains. We have also been involved in reviewing the aggregate evidence and establishing procedures and analytic methods for the use of combined passive (wrist-worn actigraphy) and active (EMA) mobile technologies to gain insight into the role of the circadian system and patterns of sleep and motor activity in people with BD (Dunster et al, 2020). The strong associations across the domains tapped by real-time monitoring suggest that future research should shift focus on sleep, physical/motor activity, or circadian patterns to identify common biologic pathways that influence their interrelations. Public Health Impact: The formation and continuation of the mMARCH initiative will enable groups to efficiently share and combine data to learn more about how activity affects different disorders and diseases across many populations, including mood disorders, sleep patterns, circadian rhythms, genetic studies, emotion, eating, and other disorders that impact public health. This work will also define targets for prevention and intervention studies. Future Plans: Plans for the next year include expanding the network using the common procedures of actigraphy and EMA to include more sites that can conduct common data analyses, continued development of analytic models including multi-level dynamic models of intensive repeated measures data, and machine learning approaches that classify the structure of inter-relationships among the regulatory domains under investigation. We will also report the findings of our analyses of several projects that investigate the heritability of actigraphy phenotypes and their associations with clinical and health measures in the NIMH and CoLaus family studies, and genetic association studies of these phenotypes in the CoLaus cohort. We will focus on five major activities: 1) joint analysis of the mMARCH core group data including the CoLaus/PsyCoLaus study of comorbidity of depression and cardiovascular disease, the NESDA study in the Netherlands, the Australian studies of twin and youth with emerging mood disorders, and the Hong Kong circadian rhythms study; 2) follow-up of the NIMH Family Study and CoLaus/PsyCoLaus samples to investigate the stability of the findings from the first wave of participation; 3) addition of several sites with actigraphy data in both adults and youth with BD; 4) initiation of new studies of youth in seven sites (miniMARCH collaboration); and 5) development of translational studies to identify the regulatory systems underlying motor activity and sleep across species. We also plan to examine the cross-domain inter-relationships and their directional influences using real-time tracking and experimental paradigms in the NIH Rhythms and Blues Program.