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CSF protein changes in autosomal dominant Alzheimer's disease show inflammatory markers follow amyloid and tau abnormalities

CSF protein changes in autosomal dominant Alzheimer's disease show inflammatory markers follow amylo…
Photo by Google DeepMind / Unsplash
Key Takeaway
Interpret CSF inflammatory markers in autosomal dominant AD as following amyloid/tau changes; clinical relevance for sporadic AD is not established.

This observational study analyzed 972 cerebrospinal fluid (CSF) samples from 484 participants with pathogenic PSEN1, PSEN2, and APP mutations enrolled in the Dominantly Inherited Alzheimer Disease Network (DIAN). The research examined the chronological emergence of protein changes in relation to estimated years to symptom onset (EYO), aiming to identify proteins differentially abundant by mutation status and symptomatology, and to assess whether specific protein measures improved EYO prediction.

The analysis found that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses. A multi-protein composite approach for predicting EYO outperformed single biomarker values. Exact effect sizes, absolute numbers, p-values, and confidence intervals for these findings were not reported in the provided data.

No safety or tolerability data were reported for this biomarker analysis study. The study was funded by multiple national and international government and non-profit agencies, including the National Institute on Aging and the Alzheimer's Association. As an observational study, it demonstrates association, not causation. The findings are based on analysis of biomarker changes in a specific genetic population, and their generalizability to sporadic Alzheimer's disease and the clinical utility of biomarker panels should not be overstated. Practice relevance was not reported.

Study Details

Sample sizen = 484
EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
BACKGROUND: Increasing evidence suggests that accurate prediction of Alzheimer disease (AD) symptom onset requires more than amyloid- and tau-centric biomarkers such as cerebrospinal fluid (CSF) A{beta}42/40, total tau and p-tau181 and plasma p-tau217. Autosomal dominant AD (ADAD), caused by pathogenic PSEN1, PSEN2 and APP mutations with predictable age at symptom onset, presents a unique opportunity to characterize the chronological changes in proteins beyond amyloid and tau and clarify them as early biomarkers of disease onset or as biomarkers related to disease staging and progression monitoring. METHODS: We measured 972 CSF samples corresponding to 484 participants of the Dominantly Inherited Alzheimer Disease Network (DIAN) using the NULISASeq 120 CNS Disease Panel. We first benchmarked the technology against gold-standard measurements followed by the identification of proteins that were differentially abundant in relation to mutation status and symptomatology. Next, we determined the chronological emergence of protein changes in relation to the estimated years to onset (EYO). Finally, we assessed whether specific protein measures improved the prediction of EYO in the ADAD. FINDINGS: NULISA measurements were comparable to those previously published. We demonstrated that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses suggesting that clinical manifestation of AD happens before the inflammatory processes is fully developed. Finally, we found a multi-protein composite approach for predicting EYO that outperformed single biomarker values. INTERPRETATION: Our results suggest that the main CSF proteomic landscape changes in ADAD are due to the presence of a pathogenic mutation and occur prior to symptom onset. Improved performance of multi-protein composite to predict EYO compared to single biomarker values highlights the added value of multiplex proteomic signatures for biomarker panel development. FUNDING: National Institute on Aging, Alzheimers Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea, Spanish Institute of Health Carlos III.
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