Researchers at Fudan University recently decided to examine proteins in the cerebrospinal fluid (CSF) of individuals with and without Alzheimer’s disease (AD). The results of their analyses and experiments, outlined in an article published in Nature Human Behaviorhave revealed specific CSF proteins that could serve as biomarkers of the disease.
CSF-Specific Oroteins Are Biomarkers of Alzheimer’s Disease
“Our recent paper was born out of the urgent need to improve early diagnosis and prediction of AD,” Jintai Yu and Yu Guo, co-authors of the paper, told Medical Xpress. “This study was inspired by the growing understanding that Alzheimer’s disease has a complex and multifaceted pathophysiology that current diagnostic methods fail to comprehensively capture.”
The primary goal of the recent study by Yu, Guo, and colleagues was to identify specific biomarkers in human CSF that could help accurately detect AD and predict its progression. To achieve this goal, the researchers analyzed CSF samples from patients diagnosed with AD who were at different stages of the disease, as well as samples from cognitively normal individuals.
“We used multiplex proteomics, a sophisticated method that allows the simultaneous measurement of multiple proteins within a sample,” Yu and Guo said. “This technique involved mass spectrometry, which is highly sensitive and can detect even small changes in protein levels.”
Analyses conducted by Yu, Guo, and their colleagues uncovered proteins that are linked to the core pathology of Alzheimer’s, while also identifying proteins that may indicate inflammation, neuronal damage, and other disruptions in human physiological processes. By comparing the proteomic profiles of patients diagnosed with AD to those of controls, they discovered new biomarkers that could help diagnose and estimate the progression of AD.
“The most notable finding of this study is the identification of the novel biomarker CSF YWHAG,” Yu and Guo said. “Among 6,361 proteins, CSF YWHAG performed the best in diagnosing both biologically (AUC=0.969) and clinically (AUC=0.857) defined AD. Four (YWHAG, SMOC1, PIGR, and TMOD2) and five (ACHE, YWHAG, PCSK1, MMP10, and IRF1) protein panels significantly improved the accuracy, to 0.987 and 0.975, respectively.”
To evaluate the efficacy of the identified biomarkers, the researchers conducted an additional follow-up study on an independent and external patient cohort. The results of this study validated the strength of the biomarkers.
Furthermore, using autopsy data, the authors demonstrated that the biomarkers they identified could help distinguish between samples from deceased individuals with Alzheimer’s disease and those from others who had never been diagnosed with AD, outperforming existing biomarkers used to diagnose the disease.
“The discovered biomarkers also effectively predicted clinical progression to AD dementia and were strongly associated with core AD biomarkers and cognitive decline,” Yu and Guo said. “A better understanding of the different molecular subtypes of Alzheimer’s disease could lead to refined treatment approaches that target specific disease processes in individual patients.”
Using sophisticated proteome analysis techniques, researchers were able to reveal molecular changes associated with Alzheimer’s, which proved to be a highly promising diagnostic target. In the future, this study could inform the development of high-precision tools for the accurate diagnosis of AD, as well as early targeted therapeutic interventions.
In their next studies, Yu, Guo, and their colleagues plan to replicate their study in external cohorts drawn from a broader range of diverse individuals. They also hope to refine the biomarkers they identified and develop standardized diagnostic tests for these markers that could be performed in clinical settings.
“In our future research, we will also explore the biological mechanisms underlying the identified proteomic changes to better understand the relationship between these biomarkers and disease progression,” added Yu and Guo.
“Longitudinal studies will also be conducted to determine how early these biomarkers can predict Alzheimer’s disease and how they correlate with clinical outcomes. The ultimate goal is to integrate these biomarkers into routine clinical practice, facilitating early diagnosis and personalized treatment strategies.”
48 Cerebrospinal Fluid Proteins Complement Existing Alzheimer’s Biomarkers
A panel of 48 proteins in cerebrospinal fluid (CSF 48 panel) complements existing CSF biomarkers for Alzheimer’s disease (AD), according to a study published in Science Translational Medicine.
Rafi Haque, M.D., Ph.D., of Emory University School of Medicine in Atlanta, and colleagues developed a robust, high-throughput mass spectrometry-selected reaction monitoring assay that targets 48 key proteins altered in CSF, as identified in previous work. The protein panel’s diagnostic utility was examined in CSF collected during baseline visits from 706 participants recruited from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
The researchers found that the CSF 48 panel performed at least as well as existing CSF Alzheimer’s biomarkers (amyloid β 42, tTau, and pTau 181) for predicting clinical diagnosis, fluorodeoxyglucose (FDG), positron emission tomography (PET), hippocampal volume, and measures of cognitive and dementia severity.
The CSF 48 panel plus existing CSF Alzheimer biomarkers significantly improved diagnostic performance for each of these outcomes. Compared with either measure alone, the CSF 48 panel plus existing CSF AD biomarkers significantly improved predictions for changes in FDG PET, hippocampal volume, and measures of cognitive decline and dementia severity.
“CSF 48 panel improves AT(N) biomarkers [ placche amiloidi , grovigli neurofibrillari e neurodegenerazione] “These new approaches will help predict many pathophysiological mechanisms linked to AD and AD-related brain dementia; distinguish pathophysiological mechanisms based on their proteomic signature; and improve prediction of disease progression and future changes in cognition, dementia severity, and hippocampal volume,” the authors write.
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