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Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities
,
Francesca Eroli,
Vilma Alanko,
Julen Goikolea,
Maria Latorre-Leal,
Patricia Rodriguez-Rodriguez ,
William Griffiths ,
Yuqin Wang ,
Manuela Pacciarini,
Ann Brinkmalm,
Henrik Zetterberg ,
Kaj Blennow,
Anna Rosenberg,
Nenad Bogdanovic,
Bengt Winblad,
Miia Kivipelto,
Delphine Ibghi,
Angel Cedazo-Minguez,
Silvia Maioli,
Anna Matton
Brain Communications, Volume: 5, Issue: 5
Swansea University Authors:
William Griffiths , Yuqin Wang , Manuela Pacciarini
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© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. Distributed under the terms of a Creative Commons Attribution 4.0 License (CC BY 4.0).
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DOI (Published version): 10.1093/braincomms/fcad228
Abstract
Alzheimer’s disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolemia and diabetes are known contributors to the disease progression. However, less is known on their mechanistic contribution to Alzheimer’s pathology and neurodegeneration....
| Published in: | Brain Communications |
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| ISSN: | 2632-1297 |
| Published: |
Oxford University Press (OUP)
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63624 |
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| Abstract: |
Alzheimer’s disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolemia and diabetes are known contributors to the disease progression. However, less is known on their mechanistic contribution to Alzheimer’s pathology and neurodegeneration. The aim of this study was to investigate the relationship of several biomarkers related to risk mechanisms in Alzheimer’s disease with the well-established Alzheimer’s disease markers in a memory clinic population without common comorbidities. We investigated 13 molecular markers representing key mechanisms underlying Alzheimer’s disease pathogenesis in CSF from memory clinic patients without diagnosed hypertension, hypercholesterolemia, or diabetes nor other neurodegenerative disorder. Analysis of 21 covariance (ANCOVA) was used to compare biomarker levels between clinical groups. Associations were analyzed by linear regression. Two-step cluster analysis was used to determine patient clusters. Two key markers were analyzed by immunofluorescence staining in hippocampus from non-demented control and Alzheimer’s disease individuals. CSF samples from a total of 90 participants were enrolled included in this study; 30 with from patients with subjective cognitive decline (age 62.4 4.38, female 60%) 30 with mild cognitive impairment (age 65.6 7.48, female 50%), and 30 with Alzheimer’s disease (age 68.2 7.86, female 50%). Angiotensinogen, thioredoxin-1, and interleukin-15 had the most prominent associations with Alzheimer’s disease pathology, synaptic and axonal damage markers. Synaptosomal-associated protein 25 kDa (SNAP-25) and neurofilament light chain (NFL) were increased in mild cognitive impairment and Alzheimer’s disease cases. Grouping biomarkers by biological function, showed that inflammatory and survival components were associated with Alzheimer’s disease pathology, synaptic dysfunction and axonal damage. Moreover, a vascular/metabolic component was associated with synaptic dysfunction. In the data-driven analysis, two patient clusters were identified; cluster 1 had increased CSF markers of oxidative stress, vascular pathology and neuroinflammation and was characterized by elevated synaptic and axonal damage, compared to cluster 2. Clinical groups were evenly distributed between the clusters. Analysis of post-mortem hippocampal tissue, showed that, compared to non-demented controls, angiotensinogen staining was higher in Alzheimer’s disease and co-localized with phosphorylated-tau. The identification of biomarker-driven endophenotypes in cognitive disorder patients, further highlights the biological heterogeneity of Alzheimer’s disease and the importance of tailored prevention and treatment strategies. |
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| Keywords: |
Alzheimer’s disease, biomarkers, metabolic disorders, clustering, cerebrospinal fluid |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
BBSRC |
| Issue: |
5 |