Hierarchical Clustering Analyses of Plasma Proteins in Subjects With Cardiovascular Risk Factors Identify Informative Subsets Based on Differential Levels of Angiogenic and Inflammatory Biomarkers

Zachary Winder, Tiffany L. Sudduth, David Fardo, Qiang Cheng, Larry B. Goldstein, Peter T. Nelson, Frederick A. Schmitt, Gregory A. Jicha, Donna M. Wilcock

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Agglomerative hierarchical clustering analysis (HCA) is a commonly used unsupervised machine learning approach for identifying informative natural clusters of observations. HCA is performed by calculating a pairwise dissimilarity matrix and then clustering similar observations until all observations are grouped within a cluster. Verifying the empirical clusters produced by HCA is complex and not well studied in biomedical applications. Here, we demonstrate the comparability of a novel HCA technique with one that was used in previous biomedical applications while applying both techniques to plasma angiogenic (FGF, FLT, PIGF, Tie-2, VEGF, VEGF-D) and inflammatory (MMP1, MMP3, MMP9, IL8, TNFα) protein data to identify informative subsets of individuals. Study subjects were diagnosed with mild cognitive impairment due to cerebrovascular disease (MCI-CVD). Through comparison of the two HCA techniques, we were able to identify subsets of individuals, based on differences in VEGF (p < 0.001), MMP1 (p < 0.001), and IL8 (p < 0.001) levels. These profiles provide novel insights into angiogenic and inflammatory pathologies that may contribute to VCID.

Original languageEnglish
Article number84
JournalFrontiers in Neuroscience
Volume14
DOIs
StatePublished - Feb 6 2020

Bibliographical note

Funding Information:
The authors gratefully acknowledge the Sanders-Brown Center on Aging Clinic team for their support in participant recruitment and evaluations, Dr. Erin Abner for her assistance in study design, the NIH [NINR: 4R01NR014189-05 (GJ), NIA: 5UH2NS100606-02 (DW and GJ), NCATS: UL1TR001998, NIA: 5P30AG028383], and the participants of this study for their time and commitment.

Publisher Copyright:
© Copyright © 2020 Winder, Sudduth, Fardo, Cheng, Goldstein, Nelson, Schmitt, Jicha and Wilcock.

Keywords

  • IL8
  • MMP1
  • VEGF
  • hierarchical clustering analysis
  • mild cognitive impairment
  • vascular cognitive impairment and dementia

ASJC Scopus subject areas

  • Neuroscience (all)

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