Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Clinical Neurology, Neurosciences, Neurosciences & Neurology, Alzheimer's disease, cerebrospinal fluid, proteomics, subtypes, MILD COGNITIVE IMPAIRMENT, C-I EXPRESSION, NATIONAL INSTITUTE, ASSOCIATION WORKGROUPS, DIAGNOSTIC GUIDELINES, APOLIPOPROTEIN-C, BIOMARKER SIGNATURE, CSF BIOMARKERS, A-BETA, TAU, Alzheimer’s disease, Aged, Aged, 80 and over, Alzheimer Disease, Amyloid Precursor Protein Secretases, Amyloid beta-Peptides, Aspartic Acid Endopeptidases, Blood-Brain Barrier, Cluster Analysis, Cognitive Dysfunction, Cohort Studies, Disease Progression, Female, Humans, Longitudinal Studies, Male, Mental Status and Dementia Tests, Middle Aged, Neuropsychological Tests, Peptide Fragments, Proteomics, tau Proteins, Alzheimer’s Disease Neuroimaging Initiative (ADNI), 11 Medical and Health Sciences, 17 Psychology and Cognitive Sciences, Neurology & Neurosurgery, 32 Biomedical and clinical sciences, 42 Health sciences, 52 Psychology

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.