Unbiased Proteomics And Multivariable Regularized Regression Techniques Identify Smoc1, Nog, Apcs, And Ntn1 In An Alzheimer’s Disease Brain Proteomic Signature

This study used a machine learning approach to identify a set of four proteins (SMOC1, APCS, NOG, and NTN1) that could accurately distinguish between Alzheimer’s Disease (AD) and control individuals in two independent cohorts of brain tissue samples. The same four proteins were found to differ between AD and control individuals in both brain regions, and serum concentrations of APCS and NTN1 additionally differed between AD and control individuals in the ROS cohort at the time of AD diagnosis. Additionally, strong positive correlations were found between the four proteins and AD pathology scores in both ROS and BLSA cohorts.