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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
Published on: January 28, 2014
Biomarkers
Mei Cui1,2, Zishuo Jin2, Yingzhe Wang2
1MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
Insights
Phospho-tau 217 (pTau217) in blood shows promise for predicting post-stroke cognitive impairment (PSCI). This biomarker, combined with infarct characteristics, improves prediction accuracy, suggesting a link between Alzheimer's pathology and stroke-related cognitive decline.
Area of Science:
- Neurology
- Biomarker Discovery
- Neurodegenerative Diseases
Background:
- China faces a high burden of stroke, with a significant proportion of patients developing post-stroke cognitive impairment (PSCI).
- Understanding the interplay between cerebrovascular and Alzheimer's disease (AD) pathologies is critical for addressing stroke-related dementia, the most prevalent form in China.
Purpose of the Study:
- To investigate the association between peripheral blood biomarkers and the development of PSCI.
- To explore the predictive value of biomarkers, particularly pTau217, in identifying patients at risk for PSCI.
- To examine the relationship between pTau217 levels, infarct characteristics, and underlying amyloid pathology.
Main Methods:
- 350 ischemic stroke patients were enrolled within 14 days of stroke onset, with 274 completing a six-month follow-up for cognitive assessment.
- Diffusion-weighted imaging (DWI) quantified infarct lesions, while peripheral blood biomarkers (including pTau217, GFAP, NFL, IL-6) were measured.
- Machine learning and ROC curve analysis were used to assess biomarker associations and predictive performance for PSCI.
Main Results:
- Machine learning identified pTau217, GFAP, NFL, and IL-6 as strongly associated with PSCI, reflecting neurodegeneration, inflammation, and neuronal injury.
- pTau217 remained significantly associated with PSCI after adjusting for infarct volume and NIHSS score.
- The combination of pTau217 and infarct characteristics achieved an AUC of 0.86 for PSCI prediction, with pTau217 showing better prediction for smaller infarcts. Elevated pTau217 correlated with amyloid pathology.
Conclusions:
- Pre-existing Alzheimer's disease pathology may contribute to the development of PSCI.
- pTau217 is a promising blood biomarker for detecting underlying amyloid pathology.
- pTau217 holds significant potential for predicting PSCI, especially when combined with infarct imaging data.
Background:
The Global Burden of Disease Study 2019 reports that China has the highest number of stroke patients globally, with one-third developing post-stroke cognitive impairment (PSCI), making stroke-related dementia the most prevalent form in China. Understanding the overlap between cerebrovascular pathology and Alzheimer's disease (AD) pathology is crucial in comprehending their joint contribution to cognitive decline post-stroke.
Method:
This study, conducted within the Vascular, Imaging, and Cognition Association of China (VICA), included 350 patients enrolled within 14 days of ischemic infarction/TIA. Baseline blood samples were collected, and patients were followed up for six months for cognitive assessments. Of these, 274 patients completed the follow-up and were divided into PSCI and PSNCI groups. Infarct lesions were quantitatively analyzed using diffusion-weighted imaging (DWI), and several peripheral blood biomarkers were measured using a single-molecule immunoarray, including, Aβ, pTau217, neurofilament light (NFL), glial fibrillary acidic protein (GFAP), monocyte chemoattractant protein-1 (MCP-1), matrix metalloproteinases (MMPs), interleukin-6 (IL-6), brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), and placental growth factor (PLGF).
Result:
Machine learning identified pTau217, GFAP, NFL, and IL-6 most strongly associated with the occurrence of PSCI, which reflect neurodegeneration, inflammatory responses, and neuronal injury. After adjusting for factors such as infarct volume and NIHSS score, only pTau217 remained significantly associated with PSCI. In predicting the occurrence of PSCI, the area under the ROC curve (AUC) for pTau217 was 0.70, which was comparable to the AUC of 0.71 for infarct characteristics (including volume and location). However, the combination of pTau217 and infarct characteristics improved the prediction, achieving an AUC of 0.86. Notably, pTau217 demonstrated superior predictive performance for PSCI caused by smaller infarcts (lesion volume < 5 cm3). To further explore whether pTau217 reflects neurodegenerative pathology, we conducted amyloid PET imaging in a subset of patients with elevated pTau217 levels. The results confirmed that elevated pTau217 levels are associated with amyloid pathology.
Conclusion:
Pre-stroke AD pathology may contribute to the development of PSCI. pTau217 serves as a valuable biomarker for detecting underlying amyloid pathology and holds promise in predicting PSCI.
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