NEW YORK – An international team has tracked the protein changes that occur in cerebrospinal fluid (CSF) during disease progression in individuals with autosomal dominant forms of Alzheimer's disease.
"[O]ur results lay the groundwork for creating predictive models and identifying potential therapeutic targets, enhancing our understanding of ADAD and fostering the development of more effective future treatments," senior and corresponding author Carlos Cruchaga, a psychiatry, neurology, and neurogenomics and informatics researcher at Washington University in St. Louis (WUSTL), and his coauthors wrote in Cell on Thursday.
As part of the "Dominantly Inherited Alzheimer Network" (DIAN), Cruchaga and colleagues at centers in the US, Spain, Germany, Argentina, and China turned to the SomaLogic SomaScan assay to measure levels of nearly 6,200 proteins in 463 CSF samples. They also profiled levels of 6,022 proteins in 538 blood plasma samples from the DIAN participants, who included 286 individuals carrying ADAD-linked genetic alterations and 177 non-mutation carriers.
The primary goal of the study was to identify proteins in CSF and plasma that present early changes in ADAD mutation carriers compared with noncarriers, the authors explained, noting that they relied on a unique approach that leverages estimated age at symptom onset to assess pseudo-trajectories.
In particular, the team's analyses revealed 137 proteins with significant ties to the early, middle, or late stages of the presymptomatic period of ADAD development, while uncovering 227 protein patterns coinciding with the presence or absence of ADAD mutations overall.
"The detection of numerous dysregulated proteins through a robust approach, exhibiting altered patterns early in the disease and maintaining statistical significance even after rigorous multiple test correlations, highlights profound changes in the CSF proteome in ADAD," the authors wrote.
When the investigators set the findings against CSF proteomic profiles for 1,763 individuals with sporadic forms of Alzheimer's disease, they found that the 137 CSF proteins implicated in ADAD disease development also shared significant ties to sporadic AD. A handful of the ADAD mutation status-linked proteins had higher effect sizes in ADAD than in sporadic Alzheimer's, while seven ADAD mutation-associated showed opposite directional ties to sporadic Alzheimer's.
After further validating the results using data for participants profiled with Olink proteomic panels or Alamar Biosciences assays in several published studies, the team used the ADAD-associated CSF protein profiles to come up with predictive models for ADAD risk with the help of machine learning — an approach that led to half a dozen protein markers that had significant associations with ADAD mutation status and disease-related cognitive features.
Even so, the authors cautioned that to "translate this model from the bench to the bedside, specific multiplex panels that include all six proteins will need to be developed to further validate the model and to determine the specific weights and cutoffs for the new platform."