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ENIGMA Parkinson’s Initiative: A Global Initiative for Parkinson’s Disease

ENIGMA 帕金森病倡议：针对帕金森病的全球倡议

基本信息

批准号：
10703214
负责人：
Kathleen Lombard Poston
金额：
$ 62.26万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10703214
关键词：
Affect Africa Age of Onset Amygdaloid structure Anatomy Anterior Area Asia Atrophic Attenuated Austria Basal Ganglia Belgium Biological Markers Bipolar Disorder Bradykinesia Brain Brain Diseases Brain imaging Brazil China Clinical Clinical Trials Cognitive Cognitive deficits Collaborations Corpus Callosum Corpus striatum structure Corticospinal Tracts Country Data Data Pooling Data Set Data Sources Development Diagnosis Diffusion Diffusion Magnetic Resonance Imaging Dimensions Disease Disease Progression Environmental Risk Factor Epilepsy Europe Foundations Functional Magnetic Resonance Imaging Future Gait Genetic Genetic Predisposition to Disease Genetic Risk Genomics Head Image Impaired cognition Impulsivity Individual International Intervention Investigation Italy Japan Learning Least-Squares Analysis Letters Machine Learning Major Depressive Disorder Measures Mental Depression Modeling Motor Motor Cortex Movement Movement Disorder Society Unified Parkinson&apos s Disease Rating Scale Multimodal Imaging Nerve Degeneration Netherlands Neurodegenerative Disorders New Zealand North America Oceania Parkinson Disease Pathway interactions Patient-Focused Outcomes Patients Pattern Persons Pharmaceutical Preparations Phenotype Posture Predictive Factor Protocols documentation Publishing Reproducibility Research Rest Risk Risk Factors Russia Sample Size Scanning Schizophrenia Severities Severity of illness Source South Africa South America Structure Structure of inferior temporal gyrus Susceptibility Gene Switzerland Symptoms Taiwan Testing Thalamic structure Thick Treatment Efficacy Tremor United States National Institutes of Health autism spectrum disorder biobank biological sex biotypes burden of illness cholinergic cognitive impairment in Parkinson&apos s cohort design disease diagnosis disorder risk disorder subtype diverse data economic cost empowerment functional decline genetic risk factor imaging biomarker imaging genetics imaging study improved indexing magnetic resonance imaging biomarker multimodal data multimodality neural neuroimaging neuropsychiatry personalized medicine polygenic risk score predict clinical outcome predictive modeling putamen rate of change response risk variant shape analysis simulation thalamocortical tract translational goal treatment response uptake white matter

项目摘要

ABSTRACT Parkinson’s disease (PD) is a devastating, progressive neurodegenerative brain disease, with no known cure. The disease afflicts 10 million people worldwide - ~1.5 million in the U.S. alone, and ~50k-60k new cases are diagnosed annually. Risk factors or interventions are extremely hard to evaluate as we lack objective metrics of how PD affects the brain. The vast global availability of brain imaging has led to several promising metrics to gauge PD progression in the brain - structural changes in the basal ganglia and motor cortex, abnormalities in neural connectivity seen with diffusion MRI (dMRI), and disruptions of the brain’s functional synchrony across regions, seen with resting state functional MRI (fMRI). Despite these findings, factors that affect disease severity are difficult to discover, as most imaging studies of PD scan <100 patients. Most PD research is conducted in isolated cohorts from the US and Europe, limiting worldwide generalizability. Factors that affect PD progression are hard to verify, leading to a crisis of reproducibility. Responding to NIH’s call for more reproducible studies, here we launch ENIGMA’s Worldwide Parkinson’s Initiative. ENIGMA recently published the largest neuroimaging studies of schizophrenia, bipolar disorder, major depression, epilepsy, and autism spectrum disorder. With ENIGMA’s globally coordinated, highly powered consortium approach, we plan to overcome the crisis of small studies with poor power and reproducibility. Pooling anatomic, diffusion and resting state functional MRI metrics from 21 deeply assessed international cohorts - from the US, Brazil, Taiwan, New Zealand, the Netherlands, Italy, Switzerland, South Africa, China, and Russia - we ask: How does the illness affect the brain's structure, neural connectivity, and functional synchrony? What imaging biomarkers track disease progression and consistently predict clinical outcomes? Do genetic risk loci for PD help predict brain decline? What PD subtypes, or clusters, can imaging identify? Combining multimodal data from 2,307 patients and 1,264 controls, we will thoroughly evaluate predictors and brain biomarkers in PD. Our aims are to: (1) Evaluate and rank structural, diffusion, and resting state functional MRI biomarkers of PD worldwide; (2) Evaluate the added value of polygenic risk scores (PRS) in predicting PD brain biomarkers; (3) Predict future functional decline in PD with machine learning, multi-modal imaging and genomics. We will use genetic data and baseline clinical variables from PD patients and healthy controls across our cohorts to construct an ensemble of models to predict the annual rate of change in combined scores from the Movement Disorder Society—Unified Parkinson's Disease Rating Scale parts II and III. We will rank the best predictors of decline, and assess how robust they are internationally. By better modeling variance in patient outcomes, our multimodal predictive model will empower PD clinical trials by ranking biomarkers of disease burden and determining the contexts where they are reliable, accurate, and feasible to use.

摘要

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Comparison of Anatomical and Diffusion MRI for detecting Parkinson's Disease using Deep Convolutional Neural Network.

使用深度卷积神经网络检测帕金森病的解剖和扩散 MRI 的比较。

DOI：
10.1109/embc40787.2023.10340792
发表时间：
2023
期刊：
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子：
0
作者：
Chattopadhyay,Tamoghna;Singh,Amit;Laltoo,Emily;Boyle,ChristinaP;Owens-Walton,Conor;Chen,Yao-Liang;Cook,Philip;McMillan,Corey;Tsai,Chih-Chien;Wang,J-J;Wu,Yih-Ru;vanderWerf,Ysbrand;Thompson,PaulM
通讯作者：
Thompson,PaulM