Predictive model of spread of Parkinson's pathology using network diffusion

使用网络扩散预测帕金森病病理传播的模型

• 批准号: 9913596
• 负责人: Ajay Gupta
• 金额: $ 58.77万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-15 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9913596
• 关键词: Age; Algorithms; Alzheimer' s Disease; Anatomy; Atlases; Atrophic; Biological Markers; Bradykinesia; Brain; Brain Stem; Cells; Clinical; Clinical Data; Cognitive; Computer Assisted; Computer software; Corpus striatum structure; Coupled; Custom; Data; Data Set; Databases; Degenerative Disorder; Dementia; Development; Diagnostic; Diagnostic Imaging; Diffuse; Diffusion; Disease; Disease Progression; Disease model; Etiology; Exercise; Exhibits; Fiber; Future; Genetic; Goals; Image; Individual; Inflammatory; Joints; Lewy Bodies; Longitudinal Studies; Magnetic Resonance Imaging; Maps; Modeling; Motor; Neocortex; Neurocognitive; Neurodegenerative Disorders; Neurologist; Parkinson Disease; Pathologic; Pathology; Patients; Pattern; Positron-Emission Tomography; Process; Proteins; Regression Analysis; Reporting; Research; Resolution; Risk; Role; Severities; Severity of illness; Software Tools; Speed; Substantia nigra structure; Symptoms; Techniques; Technology; Testing; Travel; Tremor; Validation; age related; alpha synuclein; base; biophysical model; cerebral atrophy; clinical application; clinical care; clinical heterogeneity; cohort; connectome; diffusion weighted; disease transmission; disorder subtype; follow-up; human data; imaging biomarker; imaging study; in vivo; individual patient; insight; kinetic model; macrophage; mathematical model; misfolded protein; network models; neuroimaging; neuron loss; outcome forecast; pars compacta; posture instability; predictive modeling; predictive tools; prion-like; prognostic; prognostic tool; progression marker; radiotracer; raphe nuclei; regional atrophy; spatiotemporal; synuclein; synucleinopathy; technique development; tool; transmission process; uptake

PROJECT SUMMARY / ABSTRACT Project Summary Parkinson’s disease (PD) is a debilitating neurodegenerative disease characterized by progressive bradykinesia, rigidity, tremor and postural instability. The etiology, mechanism and progression of pathology and its relationship to clinical manifestations is not fully understood. These factors, coupled with its insidious onset, clinical heterogeneity, overlap with dementias, and the variability in speed and pattern of symptom progression, make a rigorous characterization and prognosis of PD difficult. Recent bench research on the trans-neuronal “prion-like” transmission of misfolded proteins is at last filling the gaps in the pathological context of PD, whereby misfolded alpha-synuclein protein can trigger misfolding in adjacent cells. If this spread mechanisms could be quantitatively modeled, it could enable accurate prediction of PD progression. This is the aim of our proposal. We will turn hitherto qualitative neuropathological insights into a rigorous “network-diffusion” model of disease spread. The model will be fed baseline in vivo MRI of PD patients, and will produce a deterministic and testable prediction for PD progression and conversion to dementia. By explicitly incorporating the brain’s connectivity network, our model will quantify the role of the brain’s anatomic connectivity network in disease transmission. We are targeting various applications, including diagnostic imaging biomarker, prognostic tool for assessing likely future patterns of disease and future neurocognitive status including likelihood of conversion to dementia. Relevance Parkinson’s Disease is a debilitating and common age-related degenerative disorder. The proposed network model will yield a validated deterministic and predictive model for PD progression, with applications in prediction of a patient’s future atrophy patterns, neurocognitive and motor scores.

项目摘要/摘要

项目成果

Origins of atrophy in Parkinson linked to early onset and local transcription patterns.

帕金森萎缩的起源与早期发病和局部转录模式有关。

• DOI: 10.1093/braincomms/fcaa065
• 发表时间: 2020
• 期刊: Brain communications
• 影响因子: 4.8
• 作者: Maia,PedroD;Pandya,Sneha;Freeze,Benjamin;Torok,Justin;Gupta,Ajay;Zeighami,Yashar;Raj,Ashish
• 通讯作者: Raj,Ashish

Combined Model of Aggregation and Network Diffusion Recapitulates Alzheimer's Regional Tau-Positron Emission Tomography.

聚集和网络扩散的组合模型概括了阿尔茨海默病的区域 Tau 正电子发射断层扫描。

• DOI: 10.1089/brain.2020.0841
• 发表时间: 2021
• 期刊: Brain connectivity
• 影响因子: 3.4
• 作者: Raj,Ashish;Tora,Veronica;Gao,Xiao;Cho,Hanna;Choi,JaeYong;Ryu,YoungHoon;Lyoo,ChulHyoung;Franchi,Bruno
• 通讯作者: Franchi,Bruno

Regional expression of genes mediating trans-synaptic alpha-synuclein transfer predicts regional atrophy in Parkinson disease.

• DOI: 10.1016/j.nicl.2018.01.009
• 发表时间: 2018
• 期刊: NeuroImage. Clinical
• 作者: Freeze B;Acosta D;Pandya S;Zhao Y;Raj A
• 通讯作者: Raj A

Preserved Structural Network Organization Mediates Pathology Spread in Alzheimer's Disease Spectrum Despite Loss of White Matter Tract Integrity.

• DOI: 10.3233/jad-170798
• 发表时间: 2018
• 期刊: Journal of Alzheimer's disease : JAD
• 作者: Powell F;Tosun D;Sadeghi R;Weiner M;Raj A;Alzheimer’s Disease Neuroimaging Initiative
• 通讯作者: Alzheimer’s Disease Neuroimaging Initiative

Computational Models in Electroencephalography.

• DOI: 10.1007/s10548-021-00828-2
• 发表时间: 2022-01
• 期刊: Brain topography
• 影响因子: 2.7
• 作者: Glomb K;Cabral J;Cattani A;Mazzoni A;Raj A;Franceschiello B
• 通讯作者: Franceschiello B