A metabolomics approach to understanding recurrent stroke risk in African Americans

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Kelsey J Spragley (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Stroke is a significant health burden , as the fifth leading cause of death and the number one cause of serious , long term disability in the United States. Each year 795 , 000 individuals suffer a stroke; of which 185 , 000 will be a recurrent stroke. Recurrent strokes are more deadly and disabling than an initial stroke. Ethnic and geographical disparities in stroke recurrence are well documented. African Americans are twice as likely to suffer a stroke , 60 % more likely to experience a recurrent event , and are more likely to die from a stroke at a younger age when compared to their European American counterparts. African Americans also experience poorer outcomes or are more likely to experience disability and difficulties with daily living following a stroke event. To date , no biomarker studies have been performed to address disparities for stroke recurrence. The goal of this research is to use novel metabolomics approaches to identify potential plasma biomarkers that might predict one's risk of experiencing a recurrent event or formulate therapeutic targets to reduce one's risk of suffering a recurrent event. Global metabolomic data for over 900 metabolites were generated from 50 African American stroke patients (28 with a recurrent stroke and 22 without a stroke recurrence) from the Vitamin Intervention from Stroke Prevention (VISP) clinical trial. Individual and integrative -omics analyses combining metabolomic , DNA methylation , genotypic , and phenotypic data were performed. For metabolomics only analyses , univariate group comparisons , using Welch's t tests , identified 20 significant associations , including several tobacco related metabolites for baseline smoking and N-delta-acetylornithine , a metabolite implicated in chronic kidney disease , for recurrent stroke comparisons (males only) (p=1.97E-05). Weighted Gene Coexpression Network Analysis identified six associations between metabolite clusters , or modules , and stroke related clinical traits , with 5 of 6 associations related to lipid pathways and the most significant correlation between body mass index and the green module (p=0.002). Sphingolipids were a major component of many of the significant metabolite modules identified. Integrative metabolite-epigenetic and metabolite-genetic analyses identified significant associations with smoking related metabolites and xenobiotics such as metformin and salicylurate. These findings suggest a role of DNA methylation in drug metabolism and that VISP recurrent and nonrecurrent individuals may metabolize drugs differently. Stratifying by genotype for three single nucleotide polymorphisms (SNPs) associated with stroke recurrence yielded similar results. Metabolites of importance for genetic-metabolite analyses were exogenous metabolites such as salicylate and acetaminophen and their derivatives (p< 0.0001). While the moderate sample size of 50 individuals places limits on statistical power , findings from this study provide insight into associations between metabolomics , epigenetics , genetics and recurrent stroke. Our study is the first of its kind to explore biomarkers for recurrent stroke , particularly in African Americans.. Through this project potential biomarkers for stroke recurrence have been identified and include gamma-glutamyl amino acids and lipid pathway metabolites. Expanding this study to include the full 2 , 100 VISP participants will therefore provide the statistical power needed in order to definitively identify the relationship between the mutli-omic based approaches in this research and the recurrent stroke phenotype.

Additional Information

Publication

Thesis

Language: English

Date: 2019

Keywords

recurrent stroke, disparities, sphingolipids, biomarker, metabolomics, genetics, disease

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