Decorin is an early CSF biomarker of Alzheimer’s Aβ amyloidosis

Jiang, Richeng; Smailović, Una; Haytural, Hazal; Haret, Robert Mihai; Shevchenko, Ganna; Tijms, Betty M.; Gobom, Johan; Abelein, Axel; Bogdanović, Nenad; Zetterberg, Henrik; Winblad, Bengt; Frykman, Susanne; Jelić, Vesna; Bergquist, Jonas; Visser, Pieter Jelle; Nilsson, Per

doi:10.21203/rs.3.rs-275229/v1

Cited by 2 publications

(1 citation statement)

References 53 publications

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“…Recent researches have shown that it also plays a critical role in autoimmune and inflammatory diseases (Dong et al, 2022), antifibrotic (Järvinen and Ruoslahti, 2019), antioxidant, and antiangiogenic properties (Sofeu Feugaing et al, 2013;Järveläinen et al, 2015). DCN was found significantly increased in both AD mouse models and CSF of AD patients, predicting well innate immune activation and potential choroid plexus dysfunction (Jiang et al, 2022). Other studies also demonstrated that endothelial-activated DCNpositive astrocytes contributed to vascular amyloid deposits but not parenchymal amyloid plaques in AD mouse models and AD/CAA patients (Taylor et al, 2022).…”

Section: Discussionmentioning

confidence: 94%

Identification of biomarkers differentiating Alzheimer’s disease from other neurodegenerative diseases by integrated bioinformatic analysis and machine-learning strategies

Jin

Fei

Sang³

et al. 2023

Front. Mol. Neurosci.

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BackgroundAlzheimer’s disease (AD) is the most common neurodegenerative disease, imposing huge mental and economic burdens on patients and society. The specific molecular pathway(s) and biomarker(s) that distinguish AD from other neurodegenerative diseases and reflect the disease progression are still not well studied.MethodsFour frontal cortical datasets of AD were integrated to conduct differentially expressed genes (DEGs) and functional gene enrichment analyses. The transcriptional changes after the integrated frontal cortical datasets subtracting the cerebellar dataset of AD were further compared with frontal cortical datasets of frontotemporal dementia and Huntingdon’s disease to identify AD-frontal-associated gene expression. Integrated bioinformatic analysis and machine-learning strategies were applied for screening and determining diagnostic biomarkers, which were further validated in another two frontal cortical datasets of AD by receiver operating characteristic (ROC) curves.ResultsSix hundred and twenty-six DEGs were identified as AD frontal associated, including 580 downregulated genes and 46 upregulated genes. The functional enrichment analysis revealed that immune response and oxidative stress were enriched in AD patients. Decorin (DCN) and regulator of G protein signaling 1 (RGS1) were screened as diagnostic biomarkers in distinguishing AD from frontotemporal dementia and Huntingdon’s disease of AD. The diagnostic effects of DCN and RGS1 for AD were further validated in another two datasets of AD: the areas under the curve (AUCs) reached 0.8148 and 0.8262 in GSE33000, and 0.8595 and 0.8675 in GSE44770. There was a better value for AD diagnosis when combining performances of DCN and RGS1 with the AUCs of 0.863 and 0.869. Further, DCN mRNA level was correlated to CDR (Clinical Dementia Rating scale) score (r = 0.5066, p = 0.0058) and Braak staging (r = 0.3348, p = 0.0549).ConclusionDCN and RGS1 associated with the immune response may be useful biomarkers for diagnosing AD and distinguishing the disease from frontotemporal dementia and Huntingdon’s disease. DCN mRNA level reflects the development of the disease.

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Section: Discussionmentioning

confidence: 94%

Identification of biomarkers differentiating Alzheimer’s disease from other neurodegenerative diseases by integrated bioinformatic analysis and machine-learning strategies

Jin

Fei

Sang³

et al. 2023

Front. Mol. Neurosci.

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Gal-9 and DCN Serum Expression Reflect Accelerated Brain Aging and Are Attenuated by the Green-Mediterranean Diet: The 18-month DIRECT PLUS Proteomics-Brain MRI Trial

Pachter,

Yaskolka Meir,

Kaplan

et al. 2024

Preprint

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Background: We recently reported that a green-Mediterranean (green-MED), high-polyphenol diet is potentially neuroprotective for age-related brain atrophy. Here, we explored the interplay between dietary intervention, proteomics profile, and accelerated brain age. Methods: In the 18-month DIRECT PLUS trial, 294 participants (adherence rate=89%) were randomized to one of three arms: 1) Healthy dietary guidelines (HDG); 2) MED diet; or 3) green-MED diet. Both MED diets included 28g/day of walnuts. Additionally, the low red/processed meat green-MED group received daily supplements of polyphenol-rich green-tea and green Mankai aquatic plant. In this secondary analysis, we measured 87 serum proteins (Olink-CVDII) and conducted Magnetic Resonance Imaging (MRI) to obtain brain 3D-T1-weighted for brain age calculation based on brain convolutional neural network to identify protein markers reflecting the brain age gap (BAG: residual deviation of MRI-assessed brain age from chronological age). Results: We analyzed eligible brain MRIs (216 at baseline and 18-month) for BAG calculation. At baseline (age=51.3yrs, 90% men), lower weight, waist circumference, diastolic blood pressure, and HbA1c parameters were associated with younger brain age than expected (p<0.05 for all). At baseline, higher levels of two specific proteins: Galectin-9 (Gal-9) and Decorin (DCN), were associated with larger BAG (accelerated brain aging; FDR<0.05). A proteomics principal component analysis (PCA) revealed a significant difference between the 18-month time points among participants who completed the trial with accelerated brain aging (p=0.02). Between baseline and 18 months, Gal-9 significantly decreased (p<0.05) among individuals who completed the intervention with attenuated brain age, and DCN significantly increased (p<0.05) among those who completed the trial with accelerated brain age. A significant interaction was observed between the green-MED diet and proteomics PCA change compared to the HDG (β=-1.7; p-interaction=0.05). Participants in the green-MED diet significantly decreased Gal-9 compared to the HDG diet (p=0.015) and from baseline (p=0.003). DCN levels, however, marginally increased in the HDG diet from baseline (p=0.053). Conclusion: Higher serum levels of Gal-9 and DCN may indicate an acceleration of brain aging and might be reduced by the green-MED/high-polyphenol diet rich in Mankai and green-tea and low in red/processed meat.

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Decorin is an early CSF biomarker of Alzheimer’s Aβ amyloidosis

Cited by 2 publications

References 53 publications

Identification of biomarkers differentiating Alzheimer’s disease from other neurodegenerative diseases by integrated bioinformatic analysis and machine-learning strategies

Identification of biomarkers differentiating Alzheimer’s disease from other neurodegenerative diseases by integrated bioinformatic analysis and machine-learning strategies

Gal-9 and DCN Serum Expression Reflect Accelerated Brain Aging and Are Attenuated by the Green-Mediterranean Diet: The 18-month DIRECT PLUS Proteomics-Brain MRI Trial

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