Motor Activity Research Consortium for Health (mMarch)

运动健康研究联盟 (mMarch)

• 批准号: 10929839
• 负责人: kathleen r merikangas
• 金额: $ 143.69万
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10929839
• 关键词: Academic Medical Centers; Accelerometer; Address; Adolescent; Adult; Affect; Affective; Anxiety; Applet; Attention deficit hyperactivity disorder; Australia; Behavior; Biological; Biometry; Bipolar Disorder; Bipolar I; Body mass index; Brain; Callithrix; Cardiovascular Diseases; Chinese; Circadian Rhythms; Classification; Clinic; Clinical; Cohort Studies; Collaborations; Data; Data Analyses; Data Collection; Databases; Development; Devices; Disease; Disease remission; Distributional Activity; Doctor of Philosophy; Early Intervention; Eating; Ecological momentary assessment; Electronics; Emotions; Evaluation; Exercise; Exhibits; Exposure to; Family; Family Study; Future; General Population; Genetic; Genetic study; Goals; Graph; Health; Health Policy; Heritability; Hong Kong; Hour; Human; Hunger; Individual; Intervention Studies; Investigation; Joints; Learning; Light; Location; Machine Learning; Major Depressive Disorder; Measures; Mediating; Memory; Mental Depression; Mental Health; Mental disorders; Metabolic syndrome; Methodology; Methods; Mind; Modeling; Monitor; Monkeys; Mood Disorders; Moods; Motor; Motor Activity; National Institute of Mental Health; Netherlands; Paper; Participant; Patients; Pattern; Pennsylvania; Perception; Persons; Phenotype; Physical Examination; Physical activity; Population; Population Research; Prevention; Procedures; Process; Protocols documentation; Public Health; Public Health Schools; Publications; Publishing; Queensland; Reporting; Reproducibility; Research; Research Activity; Research Institute; Research Methodology; Research Personnel; Role; Sampling; Sampling Studies; Schizophrenia; Site; Sleep; Standardization; Statistical Methods; Structure; Subgroup; Switzerland; Symptoms; System; Technology; Temperament; Temperature; Testing; Time; Twin Multiple Birth; Twin Studies; United States National Institutes of Health; Universities; Vulnerable Populations; Work; Youth; actigraphy; analytical method; anxiety spectrum disorders; assessment application; cardiovascular risk factor; circadian; climate change; climate impact; cognitive function; cognitive testing; cohort; comorbid depression; comorbidity; data management; design; diaries; disorder subtype; executive function; follow-up; genetic association; genetic risk factor; high risk; improved; indicated prevention; individual variation; insight; interest; mobile application; multimodality; nonhuman primate; novel; open source; personalized medicine; physical conditioning; programs; psychologic; psychological outcomes; response; sedentary lifestyle; sleep behavior; sleep pattern; smartphone based assessment; substance use; translational study; treatment choice

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. 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; examined cross device features; expanded to new sites including Yale, Toronto (CAMH), and the Healthy Brain Network, NY; and supported the development of sophisticated applets in the MindLogger platform to enhance longitudinal data collection for cognitive testing, electronic diary applications, and tracking of mobile assessments in population-based research. Over the last year we collaborated to publish several key papers related to motor activity and daily rhythms monitoring. With researchers from Australia, we examined evidence that suggested a role of circadian dysrhythmia in the switch between activation states in bipolar 1 disorder (BD-1) (Hickie et al, 2023). We found that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states. This work has implications for indicated prevention, early intervention, and personalized treatment choices, suggesting prioritization in BD research. In collaboration with investigators in Switzerland, we published 3 studies using follow-up data from the CoLaus/PsyColaus study. We investigated the associations of major depressive disorder (MDD) and its subtypes with actigraphy-derived measures of sleep, physical activity and circadian rhythms and tested the potentially mediating role of sleep, physical activity and circadian rhythms in the well-established associations of the atypical MDD subtype with body mass index (BMI) and the metabolic syndrome (MeS) (Glaus et al, 2023). The sample included data from participants who used actigraphy measures as part of their physical evaluation. Results confirmed associations of MDD and its atypical subtype with sleep and physical activity, which are likely to partially mediate the associations of atypical MDD with BMI and MeS, although most of these associations are not explained by sleep and activity variables. Findings highlight the need to consider atypical MDD, sleep and sedentary behavior as cardiovascular risk factors. In a second publication, we investigated associations between ambient temperatures and bad daily mood and identified variables affecting the strength of these associations in the CoLaus/PsyCoLaus population (Bundo et al, 2023). Daily mood was collected using EMA as part of the physical examination. We found that rising temperatures may positively affect mood in the general population, but individuals with psychiatric disorders (such as anxiety, depression, and schizophrenia) may exhibit alternated responses to heat. This research suggests that tailored public health policies may help protect this vulnerable population. Lastly, we published a report on the associations between hunger and psychological outcomes (de Rivaz et al, 2022) using data from participants who completed EMA for one week in CoLaus/PsyCoLaus. Findings showed that positive psychological states and hunger can influence each other, while no association was found between hunger and negative psychological states. We continued to collaborate with investigators from the Netherlands, Norwegian and US (Yale) affiliated mMarch sites on several papers on motor activity. First, we investigated patterns of motor activity with comorbid attention-deficit/hyperactivity disorder (ADHD) and temperamental factors that may influence the clinical course and symptoms, including cyclothymic temperament (CT) (Syrstad et al, 2022). From the Netherlands site data, we reported findings from examining the bidirectional associations between accelerometry-derived physical activity level (PAL) and EMA-rated affect in a 3-hour time frame and evaluated whether associations differed between people with and without current or remitted depression or anxiety (Difrancesco et al, 2022). We found that higher PAL may improve affect, especially in patients with depression or anxiety. This study supports and extends previous findings on the bidirectional relationship between physical activity and mood. We collaborated on statistical and methodologic research on accelerometry data and its demographic and clinical correlates. With researchers from the University of Pennsylvania Biometrics team, we published a paper proposing nonparametric, graph-based two-sample tests for object data with the same structure of repeated measures (Zhang et al, 2022). The proposed tests were demonstrated to provide additional insights on the location, inter- and intra-individual variability of the daily physical activity distributions in a sample of studies for mood disorders. Additionally, our NIMH statistical group developed an open-source publicly available pipeline for loading and cleaning raw accelerometry that facilitates harmonization and enhances reproducibility of accelerometry data (Guo et al, 2022). 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: We plan to expand 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 six 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, the Hong Kong circadian rhythms study and a cohort study of Brazilian youth; 2) establishment of a new protocol "Rhythms and Blues: Multidomain Dynamics of Motor Activity and Mood" to test mechanisms for findings on the mechanisms underlying BD from NIMH Family Study; 3) addition of several sites with actigraphy and EMA data in both adults and youth with mood disorders; 4) initiation of new studies of youth in seven sites (miniMARCH collaboration); 5) development of translational studies to identify the regulatory systems underlying motor activity and sleep across species, where 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; and 6) establishment of methodologic workgroups to address challenges in analysis of multidomain, multilevel intensive repeated measures data from mobile assessments, and another designed to build aggregate environmental data bases on light and temperature to address the impact of climate change on mental health and underlying domains.

我们一直在扩大对青少年和家庭内部的深入多模式研究，跟踪样本以检查稳定性，并扩大评估领域。我们开发了一个新的处理平台（GGIR，一个用于分析加速度计数据的R包）；处理和分析来自 6 个站点的体动记录数据；将新的统计方法应用于体动记录仪跨站点数据，包括功能数据分析和联合个体方差解释（JIVE）；收集并分析伴随的生态瞬时评估（EMA）数据；检查跨设备功能；扩展到新地点，包括多伦多耶鲁大学 (CAMH) 和纽约州健康大脑网络；支持 MindLogger 平台中复杂小程序的开发，以增强认知测试、电子日记应用程序以及基于人群的研究中移动评估跟踪的纵向数据收集。 去年，我们合作发表了几篇与运动活动和日常节律监测相关的重要论文。我们与澳大利亚的研究人员一起检查了证据，表明昼夜节律失常在双相情感障碍 1 型障碍 (BD-1) 激活状态之间的切换中发挥着作用 (Hickie et al, 2023)。我们发现昼夜节律失常是向高激活状态和低激活状态转变的合理驱动因素。这项工作对指示性预防、早期干预和个性化治疗选择具有重要意义，表明双相情感障碍研究的优先顺序。 我们与瑞士的研究人员合作，利用 CoLaus/PsyColaus 研究的后续数据发表了 3 项研究。我们研究了重度抑郁症 (MDD) 及其亚型与体动记录仪测量的睡眠、体力活动和昼夜节律之间的关系，并测试了睡眠、体力活动和昼夜节律在非典型 MDD 亚型与体重指数 (BMI) 和代谢综合征 (MeS) 之间已确立的关联中的潜在中介作用 (Glaus 等人) 等人，2023）。该样本包括来自使用体动记录仪测量作为身体评估一部分的参与者的数据。结果证实了 MDD 及其非典型亚型与睡眠和体力活动的关联，这可能部分介导了非典型 MDD 与 BMI 和 MeS 的关联，尽管大多数这些关联不能用睡眠和活动变量来解释。研究结果强调需要将非典型MDD、睡眠和久坐行为视为心血管危险因素。在第二篇出版物中，我们研究了环境温度与不良日常情绪之间的关联，并确定了影响 CoLaus/PsyCoLaus 人群中这些关联强度的变量（Bundo 等人，2023）。作为体检的一部分，使用 EMA 收集每日情绪。我们发现，气温升高可能会对普通人群的情绪产生积极影响，但患有精神疾病（例如焦虑、抑郁和精神分裂症）的个体可能会对热表现出交替的反应。这项研究表明，量身定制的公共卫生政策可能有助于保护这一弱势群体。最后，我们利用在 CoLaus/PsyCoLaus 完成一周 EMA 的参与者的数据，发表了一份关于饥饿与心理结果之间关联的报告 (de Rivaz et al, 2022)。研究结果表明，积极的心理状态和饥饿可以相互影响，而饥饿和消极的心理状态之间没有发现任何关联。 我们继续与荷兰、挪威和美国（耶鲁大学）附属 mMarch 网站的研究人员合作，撰写了几篇有关运动活动的论文。 首先，我们研究了共病注意力缺陷/多动障碍 (ADHD) 的运动活动模式以及可能影响临床病程和症状的气质因素，包括循环气质 (CT) (Syrstad 等人，2022)。根据荷兰网站的数据，我们报告了在 3 小时时间范围内检查加速度计衍生的体力活动水平 (PAL) 与 EMA 评级影响之间的双向关联的结果，并评估了当前或未缓解抑郁或焦虑的人和没有抑郁或焦虑的人之间的关联是否存在差异（Difrancesco 等人，2022）。我们发现较高的 PAL 可能会改善情感，尤其是对于患有抑郁或焦虑的患者。这项研究支持并扩展了之前关于身体活动和情绪之间双向关系的发现。 我们合作对加速度数据及其人口统计和临床相关性进行统计和方法学研究。我们与宾夕法尼亚大学生物识别团队的研究人员一起发表了一篇论文，提出对具有相同重复测量结构的对象数据进行非参数、基于图形的双样本测试（Zhang 等人，2022）。事实证明，所提出的测试可以为情绪障碍研究样本中日常身体活动分布的位置、个体间和个体内变异性提供更多见解。此外，我们的 NIMH 统计小组开发了一个开源的公开管道，用于加载和清理原始加速度测量，以促进协调并提高加速度测量数据的可重复性（Guo 等人，2022）。 公共卫生影响： mMARCH 计划的形成和持续将使各团体能够有效地共享和整合数据，以更多地了解活动如何影响许多人群的不同疾病和疾病，包括情绪障碍、睡眠模式、昼夜节律、基因研究、情绪、饮食和其他影响公共健康的疾病。这项工作还将确定预防和干预研究的目标。 未来计划： 我们计划使用体动记录仪和 EMA 的通用程序来扩展网络，以包括更多可以进行通用数据分析的站点，继续开发分析模型，包括密集重复测量数据的多级动态模型，以及对所调查的监管领域之间的相互关系结构进行分类的机器学习方法。我们还将报告我们对几个项目的分析结果，这些项目调查了 NIMH 和 CoLaus 家族研究中体动记录表型的遗传性及其与临床和健康措施的关联，以及 CoLaus 队列中这些表型的遗传关联研究。我们将重点开展六项主要活动：1）联合分析mMARCH核心组数据，包括CoLaus/PsyCoLaus抑郁症和心血管疾病共病研究、荷兰NESDA研究、澳大利亚针对出现情绪障碍的双胞胎和青少年的研究、香港昼夜节律研究和巴西青少年队列研究； 2) 建立一个新的协议“节奏和布鲁斯：运动活动和情绪的多域动力学”，以测试 NIMH 家庭研究中 BD 潜在机制的发现； 3) 添加了几个具有情绪障碍成人和青少年体动记录仪和 EMA 数据的站点； 4) 在七个地点启动新的青年研究（miniMARCH 合作）； 5) 开展转化研究，以确定跨物种运动活动和睡眠的调节系统，我们还计划使用 NIH 节奏和布鲁斯计划中的实时跟踪和实验范例来检查跨域相互关系及其方向影响； 6) 建立方法工作组，以应对分析来自移动评估的多领域、多层次密集重复测量数据的挑战，另一个旨在建立基于光和温度的综合环境数据库，以解决气候变化对心理健康和基础领域的影响。

项目成果

Objectively assessed sleep and physical activity in depression subtypes and its mediating role in their association with cardiovascular risk factors.

客观评估抑郁亚型的睡眠和体力活动及其在与心血管危险因素关联中的中介作用。

• DOI: 10.1016/j.jpsychires.2023.05.042
• 发表时间: 2023
• 期刊: Journal of psychiatric research
• 影响因子: 4.8
• 作者: Glaus,Jennifer;Kang,SunJung;Guo,Wei;Lamers,Femke;Strippoli,Marie-PierreF;Leroux,Andrew;Dey,Debangan;Plessen,KerstinJ;Vaucher,Julien;Vollenweider,Peter;Zipunnikov,Vadim;Merikangas,KathleenR;Preisig,Martin
• 通讯作者: Preisig,Martin

Dim light melatonin patterns in unaffected offspring of parents with bipolar disorder: A case-control high-risk study.

患有双相情感障碍的父母未受影响的后代的弱光褪黑激素模式：一项病例对照高风险研究。

• DOI: 10.1016/j.jad.2022.07.029
• 发表时间: 2022
• 期刊: Journal of affective disorders
• 影响因子: 6.6
• 作者: Feng,Hongliang;Ho,AmyWing-Yin;Lei,Binbin;Chan,JoeyWingYan;Wang,Jing;Liu,Yaping;Tsang,JessieChiChing;Chan,NganYin;Lam,SiuPing;Merikangas,KathleenRies;Ho,ChungShun;Zhang,Jihui;Wing,YunKwok
• 通讯作者: Wing,YunKwok

Within-day bidirectional associations between physical activity and affect: A real-time ambulatory study in persons with and without depressive and anxiety disorders.

• DOI: 10.1002/da.23298
• 发表时间: 2022-12
• 期刊: DEPRESSION AND ANXIETY
• 影响因子: 7.4
• 作者: Difrancesco, Sonia;Penninx, Brenda W. J. H.;Merikangas, Kathleen R.;van Hemert, Albert M.;Riese, Harriette;Lamers, Femke
• 通讯作者: Lamers, Femke

Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: A scoping review.

用于监测儿童和青少年抑郁症状的移动和可穿戴技术：范围界定审查。

• DOI: 10.1016/j.jad.2019.11.156
• 发表时间: 2020
• 期刊: Journal of affective disorders
• 影响因子: 6.6
• 作者: Sequeira,Lydia;Perrotta,Steve;LaGrassa,Jennifer;Merikangas,Kathleen;Kreindler,David;Kundur,Deepa;Courtney,Darren;Szatmari,Peter;Battaglia,Marco;Strauss,John
• 通讯作者: Strauss,John

Objective assessment of motor activity in a clinical sample of adults with attention-deficit/hyperactivity disorder and/or cyclothymic temperament.

• DOI: 10.1186/s12888-022-04242-1
• 发表时间: 2022-09-14
• 期刊: BMC psychiatry
• 影响因子: 4.4