Proteomic Clusters Underlie Heterogeneity in Preclinical AD Progression

Background: Heterogeneity in progression to AD poses challenges for both clinical prognosis and clinical trial implementation. In the absence of a well-defined understanding of future disease trajectory, participants may receive unnecessary treatment or true effects of pharmacological intervention may be obscured. We identified early differences in preclinical Alzheimer Disease (AD) biomarkers, assessed patterns for developing preclinical AD across the Amyloid-Tau-(Neurodegeneration) (AT(N)) framework, and considered potential sources of difference by analyzing the CSF proteome.Methods: 108 participants enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center (ADRC) who completed four or more lumbar punctures and were cognitively normal at baseline were included. Cerebrospinal fluid (CSF) measures of Aβ42, pTau181, and Neurofilament Light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including positron emission tomography (PET) amyloid and tau and structural magnetic resonance imaging (MRI) were repeatedly obtained when available. This allowed for staging individuals according to the AT(N) framework.Results and Conclusion: Growth mixture modeling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and CSF Aβ42. Two groups (AD Biomarker Positive and AD Biomarker Intermediate) had distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were successfully re-classified using only proteomic profiles (AUCAD Biomarker Positive vs AD Biomarker Negatives = 0.970, AUCAD Biomarker Positive vs. Intermediate AD Biomarkers = 0.750, AUCIntermediate AD Biomarkers vs. AD Biomarker Negative = 0.698). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified individuals who became AD Biomarker Positive before age 50. A second group, AD Biomarker Intermediate, developed elevated CSF ptau181 in their mid-60’s before becoming amyloid positive in their mid-70’s. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing vs. other agents) in clinical trials. CSF proteome analysis highlighted additional potential opportunities for non-AT(N) focused therapies, including blood brain barrier-, liver-, and neuroinflammatory-related targets.