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Predicting neurodegeneration in living patients by IR imaging of skin fibroblasts

通过皮肤成纤维细胞的红外成像预测活体患者的神经退行性变

基本信息

批准号：
10433612
负责人：
Cynthia Therese McMurray
金额：
$ 54.13万
依托单位：
UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10433612
关键词：
Address Age Alzheimer&apos s Disease Alzheimer&apos s disease patient Amides Astrocytes Autopsy Behavioral Benchmarking Biological Biological Markers Biology Brain Calcium Fluoride Cell Nucleus Cells Characteristics Chemicals Classification Clinical Trials Collecting Cell Cytoplasm Diagnosis Discrimination Disease Exposure to Fibroblasts Fingerprint Fourier Transform Gender Genes Genotype Human Huntington Disease Huntington protein Image Length Life Light Methods Mus Nerve Degeneration Neurodegenerative Disorders Onset of illness Pathology Patients Phenotype Physiological Principal Component Analysis Process Property Proteins Publishing Severities Skin Spectroscopy, Fourier Transform Infrared Statistical Data Interpretation Stretching Symptoms Technology Testing Tissues analysis pipeline base brain cell cellular imaging cohort design diagnostic signature disease classification disease phenotype disorder subtype experimental study familial Alzheimer disease improved outcome infrared spectroscopy insight lymphoblast mouse model mutant nervous system disorder nonalzheimer dementia spectrograph statistics therapeutically effective tool vibration

项目摘要

ABSTRACT Although neurodegenerative diseases most often can be identified by late onset behavioral characteristics or by post-mortem pathology, we often lack reliable methods to predict disease status early in life. It remains extraordinarily difficult in many cases to make clear distinctions among neurodegenerative disease subtypes before the onset of symptoms, or to determine when disease onset will occur. New biomarkers are needed. We have developed a Fourier transform infrared (FTIR) spectromicroscopy approach to predict disease status from cell images based on chemical endpoints. Cells are exposed to IR light and spectral phenotyping ofthe cell images produces an absorbance signature as a rapid physiological indicator of disease state. We will test whether the method can accurately classify disease status in the absence of behavioral or tissue abnormalities and benchmark the predictions in mice with known disease features. In human cells, we will test whether the FTIR biomarker can accurately predict neurodegenerative disease class using human patient fibroblasts and lymphoblasts as surrogate cells. The FTIR spectrum will be tested to distinguish among neurodegenerative subtypes that are often confused with each other, e.g., Alzheimer’s disease (AD) and non-AD dementias. These proof of principle experiments are designed to establish whether the FTIR method can generate a reliable early disease biomarker and whether the signature has the power to discriminate among distinct disease subtypes. 1

摘要虽然神经退行性疾病通常可以通过迟发性行为特征或通过尸检病理学，我们往往缺乏可靠的方法来预测生命早期的疾病状态。它仍然是在许多情况下，很难在神经退行性疾病亚型之间做出明确的区分在症状发作之前，或确定疾病何时发作。需要新的生物标志物。我们开发了一种傅里叶变换红外（FTIR）光谱显微镜方法来预测疾病状态从细胞图像上得到的结果。将细胞暴露于IR光并对细胞进行光谱表型分析图像产生作为疾病状态的快速生理指标的吸收特征。我们将测试在没有行为或组织异常的情况下，该方法是否可以准确地分类疾病状态，在具有已知疾病特征的小鼠中进行基准预测。在人体细胞中，我们将测试FTIR是否生物标志物可以使用人类患者成纤维细胞准确地预测神经变性疾病类别，淋巴母细胞作为替代细胞。将测试FTIR光谱，以区分神经退行性变经常相互混淆的亚型，例如，阿尔茨海默病（AD）和非AD痴呆。这些原理实验的证明被设计为确定FTIR方法是否可以产生可靠的早期疾病生物标志物以及该特征是否具有区分不同疾病的能力。疾病亚型。 1