Literature DB >> 33439986

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

Betty M Tijms1, Johan Gobom2,3, Lianne Reus1, Iris Jansen1, Shengjun Hong4, Valerija Dobricic4, Fabian Kilpert4, Mara Ten Kate1, Frederik Barkhof5,6, Magda Tsolaki7, Frans R J Verhey8, Julius Popp9,10, Pablo Martinez-Lage11, Rik Vandenberghe12,13, Alberto Lleó14, José Luís Molinuevo15,16, Sebastiaan Engelborghs17,18, Lars Bertram4, Simon Lovestone19,20, Johannes Streffer17,21, Stephanie Vos8, Isabelle Bos1,8, Kaj Blennow2,3, Philip Scheltens1, Charlotte E Teunissen22, Henrik Zetterberg2,3,23,24, Pieter Jelle Visser1,8,25.   

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.
© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.

Entities:  

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

Year:  2020        PMID: 33439986     DOI: 10.1093/brain/awaa325

Source DB:  PubMed          Journal:  Brain        ISSN: 0006-8950            Impact factor:   13.501


  17 in total

1.  Temporal Subtyping of Alzheimer's Disease Using Medical Conditions Preceding Alzheimer's Disease Onset in Electronic Health Records.

Authors:  Zhe He; Shubo Tian; Arslan Erdengasileng; Neil Charness; Jiang Bian
Journal:  AMIA Annu Symp Proc       Date:  2022-05-23

2.  Increased CSF-decorin predicts brain pathological changes driven by Alzheimer's Aβ amyloidosis.

Authors:  Richeng Jiang; Una Smailovic; Hazal Haytural; Betty M Tijms; Hao Li; Robert Mihai Haret; Ganna Shevchenko; Gefei Chen; Axel Abelein; Johan Gobom; Susanne Frykman; Misaki Sekiguchi; Ryo Fujioka; Naoto Watamura; Hiroki Sasaguri; Sofie Nyström; Per Hammarström; Takaomi C Saido; Vesna Jelic; Stina Syvänen; Henrik Zetterberg; Bengt Winblad; Jonas Bergquist; Pieter Jelle Visser; Per Nilsson
Journal:  Acta Neuropathol Commun       Date:  2022-07-04       Impact factor: 7.578

3.  Signatures of glial activity can be detected in the CSF proteome.

Authors:  Timo Eninger; Stephan A Müller; Mehtap Bacioglu; Manuel Schweighauser; Marius Lambert; Luis F Maia; Jonas J Neher; Sarah M Hornfeck; Ulrike Obermüller; Gernot Kleinberger; Christian Haass; Philipp J Kahle; Matthias Staufenbiel; Lingyan Ping; Duc M Duong; Allan I Levey; Nicholas T Seyfried; Stefan F Lichtenthaler; Mathias Jucker; Stephan A Kaeser
Journal:  Proc Natl Acad Sci U S A       Date:  2022-06-06       Impact factor: 12.779

Review 4.  Microglia in Alzheimer's Disease: a Key Player in the Transition Between Homeostasis and Pathogenesis.

Authors:  Karen N McFarland; Paramita Chakrabarty
Journal:  Neurotherapeutics       Date:  2022-03-14       Impact factor: 6.088

Review 5.  Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease.

Authors:  Dallas P Veitch; Michael W Weiner; Paul S Aisen; Laurel A Beckett; Charles DeCarli; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Susan M Landau; John C Morris; Ozioma Okonkwo; Richard J Perrin; Ronald C Petersen; Monica Rivera-Mindt; Andrew J Saykin; Leslie M Shaw; Arthur W Toga; Duygu Tosun; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2021-09-28       Impact factor: 16.655

6.  Cerebrospinal fluid biomarker panel for synaptic dysfunction in Alzheimer's disease.

Authors:  Johanna Nilsson; Johan Gobom; Simon Sjödin; Gunnar Brinkmalm; Nicholas J Ashton; Johan Svensson; Per Johansson; Erik Portelius; Henrik Zetterberg; Kaj Blennow; Ann Brinkmalm
Journal:  Alzheimers Dement (Amst)       Date:  2021-05-01

Review 7.  Advances in Proteomic and Metabolomic Profiling of Neurodegenerative Diseases.

Authors:  Artur Schumacher-Schuh; Andrei Bieger; Wyllians V Borelli; Makayla K Portley; Paula Saffie Awad; Sara Bandres-Ciga
Journal:  Front Neurol       Date:  2022-01-31       Impact factor: 4.003

8.  Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer's disease.

Authors:  Pieter Jelle Visser; Lianne M Reus; Johan Gobom; Iris Jansen; Ellen Dicks; Sven J van der Lee; Magda Tsolaki; Frans R J Verhey; Julius Popp; Pablo Martinez-Lage; Rik Vandenberghe; Alberto Lleó; José Luís Molinuevo; Sebastiaan Engelborghs; Yvonne Freund-Levi; Lutz Froelich; Kristel Sleegers; Valerija Dobricic; Simon Lovestone; Johannes Streffer; Stephanie J B Vos; Isabelle Bos; August B Smit; Kaj Blennow; Philip Scheltens; Charlotte E Teunissen; Lars Bertram; Henrik Zetterberg; Betty M Tijms
Journal:  Mol Neurodegener       Date:  2022-03-28       Impact factor: 14.195

Review 9.  Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery.

Authors:  Bing Bai; David Vanderwall; Yuxin Li; Xusheng Wang; Suresh Poudel; Hong Wang; Kaushik Kumar Dey; Ping-Chung Chen; Ka Yang; Junmin Peng
Journal:  Mol Neurodegener       Date:  2021-08-12       Impact factor: 14.195

10.  Dense core vesicle markers in CSF and cortical tissues of patients with Alzheimer's disease.

Authors:  Neus Barranco; Virginia Plá; Daniel Alcolea; Irene Sánchez-Domínguez; Reiner Fischer-Colbrie; Isidro Ferrer; Alberto Lleó; Fernando Aguado
Journal:  Transl Neurodegener       Date:  2021-09-26       Impact factor: 8.014

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