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Related Concept Videos

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
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Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers01:19

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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Muhammad Ali1,2, Ying Xu1,2, Gyujin Heo1

  • 1Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

This study identifies unique protein signatures in cerebrospinal fluid and plasma to differentiate neurodegenerative diseases (NDs) like Alzheimer's and Parkinson's, aiding in targeted therapies.

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Area of Science:

  • Neuroproteomics
  • Biomarker Discovery
  • Neurodegenerative Diseases

Background:

  • Neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB) present overlapping clinical features, complicating diagnosis.
  • Accurate differentiation is crucial for effective treatment and understanding disease mechanisms.
  • Proteomics offers a powerful tool for identifying disease-specific molecular signatures and biomarkers.

Purpose of the Study:

  • To identify disease-specific proteomic signatures in cerebrospinal fluid (CSF) and plasma for differentiating NDs.
  • To develop accurate diagnostic and classification models for AD, PD, FTD, and DLB.
  • To elucidate shared and unique molecular pathways underlying different NDs.

Main Methods:

  • SomaScan proteomic analysis of 2,705 CSF and 3,009 plasma samples across AD, PD, FTD, DLB, and controls.
  • Identification and validation of disease-associated proteins (FDR < 0.05).
  • Development of prediction models and pathway-enrichment analyses.

Main Results:

  • Disease-specific proteins were identified in both CSF and plasma, with CSF showing a higher number of associated proteins.
  • CSF demonstrated stronger tissue-specific similarity between DLB and FTD (r²=0.89), and between AD and DLB across tissues (r²=0.59/0.77).
  • Accurate prediction models were developed for AD, PD, FTD, and DLB in both CSF (AUC 0.81-0.95) and plasma (AUC 0.8-0.89).
  • Pathway analyses revealed common neuroinflammatory pathways and unique pathways for each disease, including synaptic impairment in AD, ER stress in PD, microglial activation in DLB, and interferon signaling in FTD.

Conclusions:

  • Shared and unique molecular pathways across NDs were delineated, highlighting common neurodegenerative processes driven by distinct molecular factors.
  • Unique molecular signatures and converging pathways like neuroinflammation and synaptic plasticity were identified.
  • These findings support targeted therapeutic strategies and advance precision medicine for neurodegeneration.