Evaluating vascular cognitive impairment and dementia due to small‐vessel disease using plasma levels of PLGF and VEGF‐A: Biomarkers (non‐neuroimaging)/Plasma/Serum/Urine biomarkers. (7th December 2020) - Winder, Zachary; Lee, Tiffany; Fardo, David W; Cheng, Qiang; Goldstein, Larry; Nelson, Peter T.; Schmitt, Frederick A.; Jicha, Gregory A.; Wilcock, Donna M.
Abstract: Background: Vascular Cognitive Impairment and Dementia (VCID) refers to cerebrovascular disease‐associated cognitive disorders. VCID may manifest clinically with mild cognitive impairment (MCI) or dementia. Depending on diagnostic criteria, dementia may be attributed to VCID in about 20% of cases. Arteriolosclerosis, microinfarctions, and microhemorrhages characterize a major subgroup of VCID pathologies, collectively referred to as small‐vessel disease (SVD). In this study, we evaluated the association of SVD with plasma levels of PLGF and VEGF‐A. We hypothesize that up‐regulation of these molecules in blood are part of the mechanism and/or reaction of the brain to SVD due to their roles in blood‐brain‐barrier breakdown and aberrant angiogenesis. Method: Plasma samples from participants in the University of Kentucky Alzheimer's Disease Center's prospective cohort study were collected and analyzed using Meso Scale Discovery and Quanterix Simoa digitized immunoassay techniques to measure angiogenic and inflammatory biomarker levels. Unsupervised clustering analysis was used to identify unique subsets within the MCI patient population based on their plasma biomarker profile. Paired t‐tests were used to compare plasma levels of PLGF and VEGF‐A in patients diagnosed with VCID‐SVD and age‐matched controls. Supervised machine learning was then used to classify patients into groups based on the severity of their chronic vascular pathology using plasma angiogenic and inflammatory biomarkers. Result: Clustering analysis identified a subset of MCI participants with elevated levels of VEGF‐A (p < 0.001), MMP1 (p < 0.001), and IL8 (p < 0.001). Whereas participants with VCID‐SVD had significantly elevated levels of PLGF compared to age‐matched controls (p < 0.01), a non‐significant increase in VEGF‐A was also found. Additionally, supervised classification analysis yielded a model with 52.4% accuracy in assigning patients to one of three groups of chronic vascular grading on cross validation. Conclusion: These experiments provide evidence for the utility of using plasma biomarkers such as PLGF and VEGF‐A in assessing SVD in patients with varied stages of VCID, ranging from MCI to dementia. In the future, analyzing plasma PLGF and VEGF‐A levels alongside imaging biomarkers may improve the accuracy of the diagnosis of VCID, monitoring of disease progression, and potentially provide a biomarker to assess therapeutic response.