首页|Karolinska Institute Reports Findings in Alzheimer Disease (CSF protein ratios with enhanced potential to reflect Alzheimer’s disease pathology and neurodegeneration)
Karolinska Institute Reports Findings in Alzheimer Disease (CSF protein ratios with enhanced potential to reflect Alzheimer’s disease pathology and neurodegeneration)
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Springer Nature
New research on Neurodegenerative Diseases and Conditions - Alzheimer Disease is the subject of a report. According to news reporting from Stockholm, Sweden, by NewsRx journalists, research stated, “Amyloid and tau aggregates are considered to cause neurodegeneration and consequently cognitive decline in individuals with Alzheimer’s disease (AD). Here, we explore the potential of cerebrospinal fluid (CSF) proteins to reflect AD pathology and cognitive decline, aiming to identify potential biomarkers for monitoring outcomes of disease-modifying therapies targeting these aggregates.” Financial supporters for this research include H2020 Marie Sklodowska-Curie Actions, Royal Institute of Technology. The news correspondents obtained a quote from the research from Karolinska Institute, “We used a multiplex antibody-based suspension bead array to measure the levels of 49 proteins in CSF from the Swedish GEDOC memory clinic cohort at the Karolinska University Hospital. The cohort comprised 148 amyloid- and tau-negative individuals (A-T-) and 65 amyloid- and tau-positive individuals (A+T+). An independent sample set of 26 A-T- and 26 A+T+ individuals from the Amsterdam Dementia Cohort was used for validation. The measured proteins were clustered based on their correlation to CSF amyloid beta peptides, tau and NfL levels. Further, we used support vector machine modelling to identify protein pairs, matched based on their cluster origin, that reflect AD pathology and cognitive decline with improved performance compared to single proteins. The protein-clustering revealed 11 proteins strongly correlated to t-tau and p-tau (tau-associated group), including mainly synaptic proteins previously found elevated in AD such as NRGN, GAP43 and SNCB. Another 16 proteins showed predominant correlation with Ab42 (amyloid-associated group), including PTPRN2, NCAN and CHL1. Support vector machine modelling revealed that proteins from the two groups combined in pairs discriminated A-T- from A+T+ individuals with higher accuracy compared to single proteins, as well as compared to protein pairs composed of proteins originating from the same group. Moreover, combining the proteins from different groups in ratios (tauassociated protein/amyloid-associated protein) significantly increased their correlation to cognitive decline measured with cognitive scores. The results were validated in an independent cohort. Combining brainderived proteins in pairs largely enhanced their capacity to discriminate between AD pathology-affected and unaffected individuals and increased their correlation to cognitive decline, potentially due to adjustment of inter-individual variability.”
StockholmSwedenEuropeAlzheimer DiseaseAmyloidBrain Diseases and ConditionsCentral Nervous System Diseases and ConditionsDementiaEmerging TechnologiesHealth and MedicineMachine LearningNeurodegenerationNeurodegenerative Diseases and ConditionsNeurologyPathologyPeptidesPeptides and ProteinsProteinsSupport Vector MachinesTauopathiesVector Machines
NETL
NSTL
Springer Nature
