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

抽象的尽管神经退行性疾病通常可以通过迟发的行为特征或通过尸检病理学，我们常常缺乏可靠的方法来预测生命早期的疾病状态。在许多情况下，明确区分神经退行性疾病亚型非常困难在症状出现之前，或确定疾病何时发生，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根据基于化学终点的细胞图像将细胞暴露于红外光和细胞的光谱表型。图像产生吸光度特征作为疾病状态的快速生理指标，我们将进行测试。该方法是否可以在没有行为或组织异常的情况下准确地对疾病状态进行分类，以及在人类细胞中，我们将测试 FTIR 是否能够对具有已知疾病特征的小鼠的预测进行基准测试。生物标志物可以使用人类患者成纤维细胞准确预测神经退行性疾病类别将测试 FTIR 光谱以区分神经退行性细胞。经常相互混淆的亚型，例如阿尔茨海默病 (AD) 和非 AD 痴呆。这些原理验证实验旨在确定 FTIR 方法是否可以生成可靠的早期疾病生物标志物以及签名是否具有区分不同特征的能力疾病亚型。 1