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 these studies is complicated by the substantial differences in both the study goals, procedures and statistical methods. There is a need for greater coordination across studies in the procedures and analytic methods that can take into account advances in analysis of functional data. We have begun to present our preliminary data at scientific meetings and thus have received an increasing number of requests from multiple investigators collecting actigraphy data to join the mMARCH initiative. Although the study was originally centralized by the use of the GENEActiv device, subsequent work suggests that estimates from different devices can be adjusted for common analyses. We are currently comparing several devices and are developing empirical algorithms for calibrating measures across devices. Therefore, we have extended our collaboration to include more than 15 additional sites that are using alternative actigraphy devices, or are studying topics other than mood disorders (e.g., insomnia, ADHD, substance abuse, and cardiovascular disease). We are also including prospective studies of population samples of adults and children in the U.S., Switzerland and Australia that will use these devices to track activity over time. This expansion has led us to establish thematic subgroups that will focus on developing procedures, ancillary data collection and analyses of a range of relevant physical and mental health topics. A subgroup that focuses on genetics was also recently established. Public Health Impact: The formation 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, etc. This work will also define targets for prevention and intervention studies. Future Plans: We propose to devote substantial effort to implement the goals and progress begun in the mMARCH initiative to address the aims described above. This administrative effort is balanced by the scientific opportunity to sample more than 5,000 people with actigraphy data and up to 1,000 with BPD without greater burden than those associated with our original collaborative network on actigraphy and mood disorders at 5 core sites. Establishing a larger network will also increase our ability to examine clinical and biologic subgroups of people with BPD, examine developmental patterns cross-sectionally across diverse age groups, and prospectively track patterns of activity and clinical correlates over time. The most important goal of the next year will be to develop standard measures of core domains assessed across the sites to facilitate common analyses of the data. We plan to have future publications of mega-analyses and to form topical work groups for mood disorders, sleep patterns, circadian rhythms, developmental trajectories, and genetic studies. One of the most important activities of the mMARCH initiative will be the development of an international team of biostatisticians and mathematicians directed by Drs. Vadim Zipunnikov and Haochang Shou who will identify and develop methods for analyses of the complex data from actigraphy. The joint application of actigraphy and EMA provides powerful measures that track multiple systems simultaneously, but the analytic issues of these multilevel data are quite complex. Therefore, the Analytic Work Group of mMARCH will develop methods that address diverse research questions in the network by reviewing available analytic approaches. This comprehensive approach will simultaneously characterize multiple landmarks in circadian rhythms and will model inter- and intra-day interactions and dynamics in rest/activity and sleep patterns, thereby augmenting the available information and will empower the analytical framework uniformly applied across mMARCH sites.

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1
Fiscal Year
2016
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U.S. National Institute of Mental Health
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