Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics

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.

Keywords: Alzheimer’s disease; cerebrospinal fluid; proteomics; subtypes.

Figure 1

Cluster results. (A) Subject loadings on subtype scores (orange: subtype 1, hyperplasticity; blue: subtype 2, innate immune activation; green: subtype 3, blood–brain barrier dysfunction) for EMIF-AD MBD (left) and ADNI (right). Each dot shows how an individual matches all three proteomic subtypes at the same time, e.g. the right-most green dot is a subject who shows very high loading on the subtype 3 axis, and very low loadings on subtypes 1 and 2 axes. (B) Heat map of subtype average Z-scores (according to the mean and SD of controls). Labels not shown, see Supplementary Table 5 for list of proteins. (C) Proportion of cell type production for protein levels higher (positive proportions) or lower than control subjects (negative proportions). (D) Selected subset of GO pathways that show subtype-specific enrichment with log(pFDR) positive values for proteins with higher levels than controls, and negative values for proteins with lower levels than controls (see Supplementary Table 7 for complete list of enriched pathways).

Figure 2

Genetic factor comparisons between subtypes. (A) Proportion of APOE e4 carriers according to subtype. (B) Effect sizes (95% CI) of Alzheimer’s disease polygenic risk scores for increasing SNP inclusion P-value thresholds, comparing Alzheimer’s disease subtypes to the control group (normal cognition, normal CSF amyloid and tau levels). (C) Comparisons of Alzheimer’s disease subtypes in Alzheimer’s disease polygenic risk specific for GO innate immune response (left) and GO complement activation (right), for increasing SNP inclusion P-value thresholds. (B and C) The pooled sample, and the cohorts separately. The dotted vertical lines in B and C indicate mean scores for the control group. See Supplementary Tables 10 and 11 for test statistics of all comparisons.

Figure 3

Clinical stage, age, sex and other CSF markers comparisons between subtypes. (A) Proportions of disease stage (NC = normal cognition), and females according to Alzheimer’s disease subtypes and cohort. (B) Distributions of age, t-tau and p-tau levels according to Alzheimer’s disease subtypes and cohort. (C) Distributions of CSF markers not included in clustering according to subtype and cohort, including additional CSF biomarkers that were available in ADNI only for a subset of individuals. See Supplementary Table 10 for test statistics of all comparisons.

Figure 4

Cortical thickness and cognition comparisons between subtypes. (A) All brain areas where differences compared to controls were observed. (B) Brain areas with a significant main effect for subtype; all beta values reflect volumetric differences of subtypes compared to controls. (C) Comparisons of cognitive profiles between subtypes. (D) Changes over time on MMSE (left), and CDRsob (right) in ADNI only. (E) Cumulative progression to dementia curves for subtypes, in ADNI only. All cortical thickness and neuropsychological test values are standardized according to the mean and SD values of the control subjects. See Supplementary Tables 10 and 12–15 for test statistics of all comparisons.