Predicting neurodegeneration in living patients by IR imaging of skin fibroblasts

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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