Manara - Qatar Research Repository
Browse
1/1
3 files

Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia

journal contribution
submitted on 2024-07-02, 09:40 and posted on 2024-07-02, 09:40 authored by Hanan Ehtewish, Areej Mesleh, Georgios Ponirakis, Alberto De la Fuente, Aijaz Parray, Ilham Bensmail, Houari Abdesselem, Marwan Ramadan, Shafi Khan, Mani Chandran, Raheem Ayadathil, Ahmed Elsotouhy, Ahmed Own, Hanadi Al Hamad, Essam M. Abdelalim, Julie Decock, Nehad M. Alajez, Omar Albagha, Paul J. Thornalley, Abdelilah Arredouani, Rayaz A. Malik, Omar M. A. El-Agnaf

Dementia is a progressive and debilitating neurological disease that affects millions of people worldwide. Identifying the minimally invasive biomarkers associated with dementia that could provide insights into the disease pathogenesis, improve early diagnosis, and facilitate the development of effective treatments is pressing. Proteomic studies have emerged as a promising approach for identifying the protein biomarkers associated with dementia. This pilot study aimed to investigate the plasma proteome profile and identify a panel of various protein biomarkers for dementia. We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. There was also the dysregulation of 153 plasma proteins in individuals with dementia compared with those with MCI, and machine learning algorithms identified 8 biomarkers that classified dementia from MCI with an AUC of 0.87 ± 0.07. Moreover, multiple proteins selected in both diagnostic panels such as NEFL, IL17D, WNT9A, and PGF were negatively correlated with cognitive performance, with a correlation coefficient (r2) ≤ −0.47. Gene Ontology (GO) and pathway analysis of dementia-associated proteins implicated immune response, vascular injury, and extracellular matrix organization pathways in dementia pathogenesis. In conclusion, the combination of high-throughput proteomics and machine learning enabled us to identify a blood-based protein signature capable of potentially differentiating dementia from MCI and cognitively normal controls. Further research is required to validate these biomarkers and investigate the potential underlying mechanisms for the development of dementia.

Other Information

Published in: International Journal of Molecular Sciences
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.3390/ijms24098117

Additional institutions affiliated with: Hamad General Hospital - HMC, Cancer Research Center - QBRI.


Funding

Qatar National Research Fund (NPRP12S-0213-190080), Corneal Confocal Microscopy: A rapid diagnostic and prognostic imaging biomarker for neurodegeneration in dementia.

Hamad Bin Khalifa University, Qatar Biomedical Research Institute (IDRP-2018-002).

Hamad Medical Corporation (RP14494/14).

Weill Cornell Medicine-Qatar (15-00019).

History

Language

  • English

Publisher

MDPI

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Health and Life Sciences - HBKU
  • Qatar Biomedical Research Institute - HBKU
  • Neurological Disorders Research Center - QBRI
  • Diabetes Research Center - QBRI
  • Weill Cornell Medicine - Qatar
  • Hamad Medical Corporation
  • Academic Health System - HMC
  • Neuroscience Institute - HMC
  • Rumailah Hospital - HMC