ArticleBrain : a journal of neurology2020
Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics.
Article in Brain : a journal of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers, 3 of them syntheses that pooled it.
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Who cites it
110 citing papers in PubMed, 3 syntheses or guidelines pooled it, 214 citations in OpenAlex.
- Linking genomic and proteomic signatures to brain amyloid burden: insights from GR@ACE/DEGESCO.Functional & integrative genomics · 2025Pooled it
- Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers.Acta neuropathologica · 2022Pooled it
- Bayes analysis supports null hypothesis of anti-amyloid beta therapy in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2021Pooled it
- Atypical Alzheimer disease: a multi-axis framework toward defining heterogeneity.Nature reviews. Neurology · 2026Review
- Cerebrospinal Fluid Over Plasma Links Analytes to Cognitive Decline in Older Adults at Risk for Alzheimer's Disease.Annals of clinical and translational neurology · 2026Article
- Schizophrenia Spectrum Biomarkers Consortium: Establishment of a Biorepository for the Discovery of Quantitative Fluid Biomarkers.Schizophrenia bulletin · 2026Article
- Nanoparticles that target nonamyloid and nontau pathways in Alzheimer's disease.Discover nano · 2026Review
- GPIHBP1 on oligodendrocytes binds lipoprotein lipase within the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
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- Reproducibility-driven discovery and systematic benchmarking reveal a robust cerebrospinal fluid proteomic signature in Alzheimer's disease.medRxiv : the preprint server for health sciences · 2026Article
- Transcriptomic analysis in autism spectrum disorder suggests three molecular subtypes with distinct phenotypic profiles and functional pathways.Communications biology · 2026Article
- Stratification of Alzheimer's disease patients using knowledge-guided unsupervised latent factor clustering with electronic health record data.Communications medicine · 2026Article
- Targeting Pain and Depression in Alzheimer's Disease: Translational Insights and Emerging Treatments.Pharmaceuticals (Basel, Switzerland) · 2026Review
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- Identifying Alzheimer's Disease Progression Subphenotypes Via a Graph-based Framework Using Electronic Health Records.Journal of healthcare informatics research · 2026Article
- Neuroplasticity and immune system are related to altered grey matter networks: a cohort study in sporadic Alzheimer's disease.Brain communications · 2026Article
- Distinct CSF lipidomic profiles are associated with five proteomic subtypes in patients with Alzheimer's disease.Molecular neurodegeneration advances · 2026Article
- CSF proteomic profiles related to cognitive decline in MCI A+ depend on tau levels.Brain : a journal of neurology · 2025Article
- Integrating imaging and omics for enhanced subtyping of mild cognitive impairment associated with Alzheimer's disease.Journal of translational medicine · 2025Article
50 more citing papers are in PubMed but not listed here.
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Authors and funding
28 authors at 14 institutions in 8 countries.
Funding
Abstract
Alzheimer's disease is biologically heterogeneous, and detailed understanding of the processes involved in patients is critical for development of treatments. CSF contains hundreds of proteins, with concentrations reflecting ongoing (patho)physiological processes. This provides the opportunity to study many biological processes at the same time in patients. We studied whether Alzheimer's disease biological subtypes can be detected in CSF proteomics using the dual clustering technique non-negative matrix factorization. In two independent cohorts (EMIF-AD MBD and ADNI) we found that 705 (77% of 911 tested) proteins differed between Alzheimer's disease (defined as having abnormal amyloid, n = 425) and controls (defined as having normal CSF amyloid and tau and normal cognition, n = 127). Using these proteins for data-driven clustering, we identified three robust pathophysiological Alzheimer's disease subtypes within each cohort showing (i) hyperplasticity and increased BACE1 levels; (ii) innate immune activation; and (iii) blood-brain barrier dysfunction with low BACE1 levels. In both cohorts, the majority of individuals were labelled as having subtype 1 (80, 36% in EMIF-AD MBD; 117, 59% in ADNI), 71 (32%) in EMIF-AD MBD and 41 (21%) in ADNI were labelled as subtype 2, and 72 (32%) in EMIF-AD MBD and 39 (20%) individuals in ADNI were labelled as subtype 3. Genetic analyses showed that all subtypes had an excess of genetic risk for Alzheimer's disease (all P > 0.01). Additional pathological comparisons that were available for a subset in ADNI suggested that subtypes showed similar severity of Alzheimer's disease pathology, and did not differ in the frequencies of co-pathologies, providing further support that found subtypes truly reflect Alzheimer's disease heterogeneity. Compared to controls, all non-demented Alzheimer's disease individuals had increased risk of showing clinical progression (all P < 0.01). Compared to subtype 1, subtype 2 showed faster clinical progression after correcting for age, sex, level of education and tau levels (hazard ratio = 2.5; 95% confidence interval = 1.2, 5.1; P = 0.01), and subtype 3 at trend level (hazard ratio = 2.1; 95% confidence interval = 1.0, 4.4; P = 0.06). Together, these results demonstrate the value of CSF proteomics in studying the biological heterogeneity in Alzheimer's disease patients, and suggest that subtypes may require tailored therapy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.