| Title: |
Network propagation unveils molecular mechanisms modulated in Alzheimer’s Disease patients treated by the complex plasma fraction GRF6019 |
| Authors: |
File, Balint; Nanasi, Tibor; Lohr, Scott; Braithwaite, Steven P; Lehallier, Benoit |
| Source: |
Alzheimer's & Dementia ; volume 19, issue S21 ; ISSN 1552-5260 1552-5279 |
| Publisher Information: |
Wiley |
| Publication Year: |
2023 |
| Collection: |
Wiley Online Library (Open Access Articles via Crossref) |
| Description: |
Background Our pre‐clinical work provided evidence of the interest of plasma fraction treatment to reverse age‐related cognitive decline. One of the most potent plasma fractions, GRF6019 was tested on patients with Alzheimer’s disease (AD). GRF6019 was safe and well tolerated, and patients experienced no cognitive decline and minimal functional decline. However, understanding these responses requires large‐scale mapping of the underlying molecular mechanisms. Recent affinity‐based approaches can measure levels of thousands of proteins in plasma but the increased signal‐to‐noise ratio and the large‐scale analysis of the proteomics changes require sophisticated bioinformatic techniques. To this end, we applied network propagation methods and combined protein‐protein interaction (PPI) networks, known AD‐associated proteins and GRF6019 induced protein changes to shed the light on the molecular mechanisms underlying patients’ responses to GRF6019 treatment. Method Phase 2 clinical trials with repeated infusions of the plasma fraction GRF6019 were conducted in patients with AD (GRF6019‐201 n = 40 and GRF6019‐202 n = 26). Proteomic measurements from 136 plasma samples across three timepoints were performed by SomaLogic and Olink platforms. GRF6019‐induced proteomics changes were expressed by a Modulation Score (MS) for each protein. This MS captures the amplitude of the proteomics changes and the consistency of these changes within and between trials. Network propagation modeled the spread of MS on the PPI network. The network propagation algorithm we applied was the fusion of Hierarchical HotNet (permutation part) and NetCore (coreness normalization part). The algorithm highlighted the perturbed proteins which are close in the PPI network topology to proteins with high MS. Result Highly perturbed proteins were more strongly associated with AD and other age‐related diseases (e.g.: AMD, Ischemic stroke) than proteins with high MS. Several pathways involved in AD were found to be associated to the perturbed ... |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1002/alz.079278 |
| Availability: |
https://doi.org/10.1002/alz.079278 |
| Rights: |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
| Accession Number: |
edsbas.6C61F0AC |
| Database: |
BASE |