Proteomic clusters underlie heterogeneity in preclinical Alzheimer’s disease progression

Author:

Wisch Julie K1ORCID,Butt Omar H1,Gordon Brian A234ORCID,Schindler Suzanne E14,Fagan Anne M14,Henson Rachel L1,Yang Chengran56ORCID,Boerwinkle Anna H1ORCID,Benzinger Tammie L S24,Holtzman David M134,Morris John C14ORCID,Cruchaga Carlos34ORCID,Ances Beau M1234

Affiliation:

1. Department of Neurology, Washington University in St. Louis , St. Louis, MO 63110 , USA

2. Department of Radiology, Washington University in St. Louis , St. Louis, MO 63110 , USA

3. Hope Center, Washington University in Saint Louis , St. Louis, MO 63110 , USA

4. Knight Alzheimer Disease Research Center, Washington University School of Medicine , St. Louis, MO 63110 , USA

5. Department of Psychiatry, Washington University School of Medicine , St. Louis, MO 63110 , USA

6. NeuroGenomics and Informatics Center, Washington University School of Medicine , St. Louis, MO 63110 , USA

Abstract

AbstractHeterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome.Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework.Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed 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 re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952).We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. 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 versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood–brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.

Funder

National Institutes of Health

Barnes-Jewish Hospital

Washington University Institute of Clinical and Translational Sciences Foundation

Hope Center for Neurological Disorders

the Paula and Rodger O. Riney Fund

the Daniel J Brennan MD Fund

Fred Simmons Olga Mohan Fund and the Chuck Zuckerberg Initiative

Publisher

Oxford University Press (OUP)

Subject

Neurology (clinical)

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