Circulating tRNA Fragments as a Novel Biomarker Class to Distinguish Acute Stroke Subtypes

Early blood biomarkers to diagnose acute stroke could drastically reduce treatment delays. We investigated whether circulating small non-coding RNAs can serve as biomarkers to distinguish between acute ischemic stroke (IS), intracerebral hemorrhage (ICH) and stroke mimics (SM). In an ongoing observa...

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Published inInternational journal of molecular sciences Vol. 22; no. 1; p. 135
Main Authors Nguyen, T Truc My, van der Bent, M Leontien, Wermer, Marieke J H, van den Wijngaard, Ido R, van Zwet, Erik W, de Groot, Bas, Quax, Paul H A, Kruyt, Nyika D, Nossent, Anne Yaël
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 24.12.2020
MDPI
Subjects
Accuracy
acute stroke
Biomarkers
Clinical medicine
Communication
Datasets
diagnostic accuracy
Diagnostic systems
Emergency medical care
Emergency medical services
Fragments
Gene expression
Hemorrhage
Hypertension
Ischemia
Medical imaging
MicroRNAs
miRNA
Non-coding RNA
Patients
Plasma
small non-coding RNA
Stroke
stroke codes
tRNA
tRNA fragment
diagnostic accuracy
small non-coding RNA
stroke codes
acute stroke
tRNA fragment
biomarkers
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Summary:Early blood biomarkers to diagnose acute stroke could drastically reduce treatment delays. We investigated whether circulating small non-coding RNAs can serve as biomarkers to distinguish between acute ischemic stroke (IS), intracerebral hemorrhage (ICH) and stroke mimics (SM). In an ongoing observational cohort study, we performed small RNA-sequencing in plasma obtained from a discovery cohort of 26 patients (9 IS, 8 ICH and 9 SM) presented to the emergency department within 6 h of symptom onset. We validated our results in an independent dataset of 20 IS patients and 20 healthy controls. ICH plasma had the highest abundance of ribosomal and tRNA-derived fragments, while microRNAs were most abundant in plasma of IS patients. Combinations of four to five tRNAs yielded diagnostic accuracies (areas under the receiver operating characteristics curve) up to 0.986 (ICH vs. IS and SM) in the discovery cohort. Validation of the IS and SM models in the independent dataset yielded diagnostic accuracies of 0.870 and 0.885 to distinguish IS from healthy controls. Thus, we identified tRNA-derived fragments as a promising novel class of biomarkers to distinguish between acute IS, ICH and SM, as well as healthy controls.
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These authors contributed equally to this work.
ISSN:1422-0067
1661-6596
1422-0067
DOI:10.3390/ijms22010135