See the published version of this preprint at Alzheimer's Research and Therapy.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Julius Popp
Centre Hospitalier Universitaire Vaudois
Corresponding Author
ORCiD: https://orcid.org/0000-0002-0068-0312
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Multiple pathophysiological processes have been described in Alzheimer’s disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood, however. We tested the hypothesis that cerebrospinal fluid (CSF) integrative multi-omics analysis highlights novel interacting pathway alterations in AD.
Methods: We performed multi-level CSF omics in a well-characterized cohort of older adults including subjects with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analysed applying Elastic-net regression and Multi-Omics Factor Analysis followed by pathway enrichment. Multivariate analysis was used to select best predictive models of AD pathology and cognitive decline.
Results: Multi-omics integration identified five major dimensions of heterogenicity explaining the variance within the cohort and differentially associated with AD . Further analysis exposed multiple interactions between single ‘omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response and extracellular matrix signalling pathways in association with AD. Further, combinations of four selected molecules significantly improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1).
Conclusions: Applying an integrative multi-omics approach we confirmed previously reported associations with AD pathology and report new molecular and pathways alterations. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.
Keywords
Alzheimer’s disease, CSF, MOFA, multi-omics, biomarkers
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
- AdditionalFile1Clark.docx
Supplementary methods used in this study, including additional details on omics techniques used for quantification, validation of the MOFA model and association with clinical measurements.
- AdditionalFile2Clark.docx
Additional Figures, including a correlation matrix analysis of latent factors (Figure S1) and prediction of CSF AD biomarkers using the trained MOFA model (Figure S2)
- AdditionalFile3Clark.docx
Additional Tables, including coarse-grain categories used for pathway enrichment (Table S1), Analytes associated with individual CSF AD biomarkers (Table S2), CSF proteins presenting an association with cognitive impairment (Table S3), and correlations between selected proteins and lipids with CDR-SoB and MMSE scores (Tables S4)
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Alzheimer's Research and Therapy.
Version 1
Posted 21 Dec, 2020
No community comments so far
Editorial decision: Major Revision
On 09 Jan, 2021
Review #2 received
Received 07 Jan, 2021
Review #3 received
Received 05 Jan, 2021
Review #1 received
Received 03 Jan, 2021
Reviewer #3 agreed
On 18 Dec, 2020
Reviewer #2 agreed
On 15 Dec, 2020
Reviewers invited
Invitations sent on 12 Dec, 2020
Reviewer #1 agreed
On 12 Dec, 2020
First submitted
On 29 Nov, 2020
Editor assigned
On 29 Nov, 2020
Submission checks complete
On 29 Nov, 2020
Editor invited
On 29 Nov, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cognitive Neuroscience
Learn more about our company.
See the published version of this preprint at Alzheimer's Research and Therapy.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Julius Popp
Centre Hospitalier Universitaire Vaudois
Corresponding Author
ORCiD: https://orcid.org/0000-0002-0068-0312
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Alzheimer's Research and Therapy.
Version 1
Posted 21 Dec, 2020
No community comments so far
Editorial decision: Major Revision
On 09 Jan, 2021
Review #2 received
Received 07 Jan, 2021
Review #3 received
Received 05 Jan, 2021
Review #1 received
Received 03 Jan, 2021
Reviewer #3 agreed
On 18 Dec, 2020
Reviewer #2 agreed
On 15 Dec, 2020
Reviewers invited
Invitations sent on 12 Dec, 2020
Reviewer #1 agreed
On 12 Dec, 2020
First submitted
On 29 Nov, 2020
Editor assigned
On 29 Nov, 2020
Submission checks complete
On 29 Nov, 2020
Editor invited
On 29 Nov, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cognitive Neuroscience
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Alzheimer's Research and Therapy.
Background: Multiple pathophysiological processes have been described in Alzheimer’s disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood, however. We tested the hypothesis that cerebrospinal fluid (CSF) integrative multi-omics analysis highlights novel interacting pathway alterations in AD.
Methods: We performed multi-level CSF omics in a well-characterized cohort of older adults including subjects with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analysed applying Elastic-net regression and Multi-Omics Factor Analysis followed by pathway enrichment. Multivariate analysis was used to select best predictive models of AD pathology and cognitive decline.
Results: Multi-omics integration identified five major dimensions of heterogenicity explaining the variance within the cohort and differentially associated with AD . Further analysis exposed multiple interactions between single ‘omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response and extracellular matrix signalling pathways in association with AD. Further, combinations of four selected molecules significantly improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1).
Conclusions: Applying an integrative multi-omics approach we confirmed previously reported associations with AD pathology and report new molecular and pathways alterations. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
- AdditionalFile1Clark.docx
Supplementary methods used in this study, including additional details on omics techniques used for quantification, validation of the MOFA model and association with clinical measurements.
- AdditionalFile2Clark.docx
Additional Figures, including a correlation matrix analysis of latent factors (Figure S1) and prediction of CSF AD biomarkers using the trained MOFA model (Figure S2)
- AdditionalFile3Clark.docx
Additional Tables, including coarse-grain categories used for pathway enrichment (Table S1), Analytes associated with individual CSF AD biomarkers (Table S2), CSF proteins presenting an association with cognitive impairment (Table S3), and correlations between selected proteins and lipids with CDR-SoB and MMSE scores (Tables S4)
Loading...