Metabolic Alteration in Presymptomatic and Symptomatic ALS Study (MAPS ALS Study)

症状前和症状性 ALS 研究中的代谢改变（MAPS ALS 研究）

• 批准号: 10644489
• 负责人: Ikjae Lee
• 金额: $ 22.96万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10644489
• 关键词: ALS patients; Adult; Affect; Amyotrophic Lateral Sclerosis; Area; Biological Markers; Biometry; Blood; Body Composition; Body Weight; Body mass index; C9ORF72; Cessation of life; Classification; Clinic; Clinical; Clinical Course of Disease; Cohort Studies; Control Groups; Data; Data Set; Deglutition Disorders; Development; Diagnosis; Diagnostic; Differential Diagnosis; Disease; Disease Progression; Early Diagnosis; Early Intervention; Early identification; Early treatment; Energy Intake; Energy Metabolism; Epidemiology; Family; Fatty acid glycerol esters; Foundations; Genetic Predisposition to Disease; Genetic Risk; Goals; Height; Individual; Knowledge; Learning; Lipids; Longitudinal cohort study; Machine Learning; Measures; Mentored Patient-Oriented Research Career Development Award; Metabolic; Metabolic Marker; Metabolism; Motor Neuron Disease; Motor Neurons; Muscle Weakness; Natural History; Nerve Degeneration; Neurodegenerative Disorders; Neuronal Dysfunction; Newly Diagnosed; Oxidative Stress; Participant; Pathogenesis; Pathogenicity; Pattern; Plasma; Population; Positioning Attribute; Primary Lateral Sclerosis; Probability; Production; Prospective, cohort study; Public Health; Reporting; Research; Research Personnel; Research Training; Respiratory Failure; Rest; Sampling; Signs and Symptoms; Stress; Symptoms; Techniques; United States; Universities; Validation; Variant; Weight; algorithm training; biobank; biomarker development; clinical application; cohort; comparison control; diagnostic biomarker; drug development; early detection biomarkers; effective therapy; familial amyotrophic lateral sclerosis; fatty acid oxidation; indexing; insight; lipid mediator; lipid metabolism; lipidome; lipidomics; longitudinal, prospective study; machine learning algorithm; metabolic profile; mitochondrial dysfunction; mutation carrier; novel; novel diagnostics; phenotypic biomarker; predictive marker; predictive tools; prevent; skills; sporadic amyotrophic lateral sclerosis; supervised learning; therapeutic target; total energy expenditure

Project Summary/Abstract Amyotrophic lateral sclerosis (ALS) is a devastating disease with upper and lower motor neuron dysfunction and degeneration leading to progressive weakness and death due to dysphagia and respiratory failure. There is an urgent need to develop effective treatment to stop or reverse the progression. However, this has proven to be challenging due to an incomplete understanding of the pathogenesis and delay in the diagnosis of ALS. There are data supporting biomarkers of mitochondrial dysfunction, energy expenditure (EE) and body weight/composition as early indices of incident clinical disease. Identification of these markers could facilitate earlier intervention to prevent or delay disease progression as well as provide information on therapeutic targets in individuals at genetic risk for ALS. I hypothesize that 1) the plasma lipid mediators (lipidome) can accurately differentiate ALS, and primary lateral sclerosis (PLS) subjects from controls 2) body weight/composition and EE differ between C9orf72+ ALS, presymptomatic C9orf72 mutation carriers (C9orf72+ Pre-ALS) participants and controls 3) certain metabolic profiles will predict symptom onset in C9orf72+ Pre-ALS participants. In this proposed study, I will 1) investigate the plasma lipidome profile of ALS and PLS subjects to identify lipid mediators as diagnostic biomarkers in motor neuron disease, 2) evaluate body weight/composition and EE in C9orf72+ ALS and Pre-ALS to measure changes in energy metabolism in advance of and through the course of disease, and 3) follow a cohort of C9orf72+ Pre-ALS participants annually to track the emergence of ALS symptoms and signs to determine if certain metabolic profiles predict symptom onset in this genetically predisposed population. Successful completion of this project would provide key data to 1) establish the lipidome profile as a diagnostic biomarker for ALS and PLS, and 2) provide the foundation for a prospective cohort study of C9orf72+ Pre-ALS individuals to determine if the lipidome profile and metabolic markers (body composition, EE) could serve as a premonitory marker for the phenotypic conversion from asymptomatic to symptomatic ALS. This K23 award will provide the support needed to complete the proposed research and to further develop my expertise in three major scientific areas, 1) expertise in lipidome data production and analysis, 2) expertise in metabolism and EE, and 3) mastery of advanced statistical techniques for clinical applications. I will leverage the research training I receive in the K23 to lead a longitudinal cohort study of pre-ALS participants to determine the relationship between metabolic changes and clinical manifestations of ALS. My overarching goal is to identify early diagnostic biomarkers and therapeutic targets for the development of an effective treatment to prevent or delay the progression of ALS.

项目总结/文摘