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

Tijms, Betty M.; Gobom, Johan; Reus, Lianne M.; Jansen, Iris E.; Hong, Shengjun; Dobričić, Valerija; Kilpert, Fabian; Kate, Mara ten; Barkhof, Frederik; Tsolaki, Magda; Verhey, Frans R.J.; Popp, Julius; Martínez-Lage, Pablo; Vandenberghe, Rik; Lleó, Alberto; Molinuevo, José Luís; Engelborghs, Sebastiaan; Bertram, Lars; Lovestone, Simon; Streffer, Johannes; Vos, Stephanie J.B.; Bos, Isabelle; Blennow, Kaj; Scheltens, Philip; Teunissen, Charlotte E.; Zetterberg, Henrik; Visser, Pieter Jelle

doi:10.1093/brain/awaa325

Cited by 99 publications

(78 citation statements)

References 84 publications

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“…Higginbotham et al summarized the CSF DE proteins into synaptic, vascular, myelin, immunological, and metabolic panels, and applied the five biomarker panels to the classification of asymptomatic AD subjects into two subgroups [ 75 ]. In agreement with the heterogeneity of AD-related cases, three molecular subtypes are implicated by transcriptomics [ 200 ] and CSF proteomics [ 134 ].…”

Section: Proteomics-based Biomarker Discovery In Admentioning

confidence: 69%

Proteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery

Bai

Vanderwall

et al. 2021

Mol Neurodegeneration

105

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Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer’s disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in “amyloidome” (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

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Section: Proteomics-based Biomarker Discovery In Admentioning

confidence: 69%

Proteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery

Bai

Vanderwall

et al. 2021

Mol Neurodegeneration

105

View full text Add to dashboard Cite

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“…8 In line with this recognition, more recent findings suggest that cerebrospinal fluid proteomics may define subtypes of AD that are potentially relevant from a pathophysiological perspective. 9 The same may By contrasting the results of a traditional frequentist meta-analysis with the results from a Bayesian meta-analysis, and showing how an additional trial result would change the overall results of the latter meta-analysis, we illustrate that further pursuing AAB immunotherapy as treatment for AD as a rather homogeneous condition is likely futile.…”

Section: Discussionmentioning

confidence: 94%

Bayes analysis supports null hypothesis of anti‐amyloid beta therapy in Alzheimer's disease

Richard

Brok

Gool

2021

Alzheimer's & Dementia

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Numerous clinical trials of anti-amyloid beta (Aβ) immunotherapy in Alzheimer's disease have been performed. None of these have provided convincing evidence for beneficial effects. Using traditional frequentist meta-analysis, the conclusion is that there is absence of evidence for a therapeutic effect, with a point estimate effect size of 0.05 (95% confidence interval −0.00 to 0.10, P = .055). In addition, this non-significant effect equates to 0.4 points per year on the cognitive subscale of the Alzheimer's Disease Assessment Scale. This is well below the minimally clinically important difference.Bayesian meta-analysis of these trial data provides strong evidence of absence of a therapeutic effect, with a Bayes factor of 11.27 in favor of the null hypothesis, opposed to a Bayes factor of 0.09 in favor of a treatment effect. Bayesian analysis is particularly valuable in this context of repeatedly reported small, non-significant effect sizes in individual trials. Mechanisms other than removal of Aβ from the brain may be probed to slow progression of Alzheimer's disease.

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“…For ADNI biomarker abnormality was defined by Aβ42 levels <192 pg/mL and t-tau levels >93 pg/mL [18,23,24]. In EMIF-AD MBD cut-offs for p were study specific as previously reported [17,18,23,24]. Cluster analyses were performed on proteomic data performed using tandem mass tag (TMT) technique with 10 + 1 plexing in EMIF-AD MBD using high-pH reverse phase HPLC for peptide prefractionation [17,25,26].…”

Section: Cerebrospinal Fluid Datamentioning

confidence: 99%

“…In EMIF-AD MBD cut-offs for p were study specific as previously reported [17,18,23,24]. Cluster analyses were performed on proteomic data performed using tandem mass tag (TMT) technique with 10 + 1 plexing in EMIF-AD MBD using high-pH reverse phase HPLC for peptide prefractionation [17,25,26]. The EMIF-AD MBD mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [27] partner repository with the dataset identifier PXD019910 and 10.6019/PXD019910.…”

Section: Cerebrospinal Fluid Datamentioning

confidence: 99%

“…This suggests that CSF protein levels may indicate that AD pathophysiological processes have started before aggregated amyloid can be detected. In CSF it is also possible to tease out disease heterogeneity in AD, as we previously identified AD subtypes that show distinct CSF proteomic profiles [17]. One subtype showed hyperplasticity, increased BACE1 activity and high levels of tau, the second showed innate immune system activation and the third subtype showed blood-brain barrier dysfunction, mostly normal tau levels and hypoplasticity.…”

Section: Introductionmentioning

confidence: 97%

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CSF Proteomic Alzheimer’s Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals

et al. 2021

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We recently discovered three distinct pathophysiological subtypes in Alzheimer’s disease (AD) using cerebrospinal fluid (CSF) proteomics: one with neuronal hyperplasticity, a second with innate immune system activation, and a third subtype with blood–brain barrier dysfunction. It remains unclear whether AD proteomic subtype profiles are a consequence of amyloid aggregation, or might exist upstream from aggregated amyloid. We studied this question in 127 older individuals with intact cognition and normal AD biomarkers in two independent cohorts (EMIF-AD MBD and ADNI). We clustered 705 proteins measured in CSF that were previously related to AD. We identified in these cognitively intact individuals without AD pathology three subtypes: two subtypes were seen in both cohorts (n = 49 with neuronal hyperplasticity and n = 44 with blood–brain barrier dysfunction), and one only in ADNI (n = 12 with innate immune activation). The proteins specific for these subtypes strongly overlapped with AD subtype protein profiles (overlap coefficients 92%–71%). Longitudinal p181-tau and amyloid β 1–42 (Aβ42) CSF analysis showed that in the hyperplasticity subtype p181-tau increased (β = 2.6 pg/mL per year, p = 0.01) and Aβ42 decreased over time (β = −4.4 pg/mL per year, p = 0.03), in the innate immune activation subtype p181-tau increased (β = 3.1 pg/mL per year, p = 0.01) while in the blood–brain barrier dysfunction subtype Aβ42 decreased (β = −3.7 pg/mL per year, p = 0.009). These findings suggest that AD proteomic subtypes might already manifest in cognitively normal individuals and may predispose for AD before amyloid has reached abnormal levels.

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

Cited by 99 publications

References 84 publications

Proteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery

Proteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery

Bayes analysis supports null hypothesis of anti‐amyloid beta therapy in Alzheimer's disease

CSF Proteomic Alzheimer’s Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals

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