Identification of Blood Biomarkers in Ischemic Stroke by Integrated Analysis of Metabolomics and Proteomics

We aimed to uncover the pathological
mechanism of ischemic
stroke
(IS) using a combined analysis of untargeted metabolomics and proteomics.
The serum samples from a discovery set of 44 IS patients and 44 matched
controls were analyzed using a specific detection method. The same
method was then used to validate metabolites and proteins in the two
validation sets: one with 30 IS patients and 30 matched controls,
and the other with 50 IS patients and 50 matched controls. A total
of 105 and 221 differentially expressed metabolites or proteins were
identified, and the association between the two omics was determined
in the discovery set. Enrichment analysis of the top 25 metabolites
and 25 proteins in the two-way orthogonal partial least-squares with
discriminant analysis, which was employed to identify highly correlated
biomarkers, highlighted 15 pathways relevant to the pathological process.
One metabolite and seven proteins exhibited differences between groups
in the validation set. The binary logistic regression model, which
included metabolite 2-hydroxyhippuric acid and proteins APOM_O95445,
MASP2_O00187, and PRTN3_D6CHE9, achieved an area under the curve of
0.985 (95% CI: 0.966–1) in the discovery set. This study elucidated
alterations and potential coregulatory influences of metabolites and
proteins in the blood of IS patients.