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Usage Information

Elevation of plasma tRNA fragments precedes seizures in human epilepsy
Marion C. Hogg, Rana Raoof, Hany El Naggar, Naser Monsefi, Norman Delanty, Donncha F. O’Brien, Sebastian Bauer, Felix Rosenow, David C. Henshall, Jochen H.M. Prehn
Marion C. Hogg, Rana Raoof, Hany El Naggar, Naser Monsefi, Norman Delanty, Donncha F. O’Brien, Sebastian Bauer, Felix Rosenow, David C. Henshall, Jochen H.M. Prehn
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Concise Communication Neuroscience

Elevation of plasma tRNA fragments precedes seizures in human epilepsy

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Abstract

Transfer RNAs (tRNAs) are a major class of noncoding RNA. Stress-induced cleavage of tRNA is highly conserved and results in tRNA fragments. Here, we found that specific tRNA fragments in plasma are associated with epilepsy. Small RNA-Seq of plasma samples collected during video EEG monitoring of patients with focal epilepsy identified significant differences in 3 tRNA fragments (5′GlyGCC, 5′AlaTGC, and 5′GluCTC) compared with samples from healthy controls. The levels of these tRNA fragments were higher in pre-seizure than in post-seizure samples, suggesting that they may serve as biomarkers of seizure risk in patients with epilepsy. In vitro studies confirmed that production and extracellular release of tRNA fragments were lower after epileptiform-like activity in hippocampal neurons. We designed PCR-based assays to quantify tRNA fragments in a cohort of pre- and post-seizure plasma samples from patients with focal epilepsy and from healthy controls. Receiver operating characteristic analysis indicated that tRNA fragments potently distinguished pre- from post-seizure patients. Elevated levels of tRNA fragments were not detected in patients with psychogenic nonepileptic seizures and did not result from medication tapering. This study potentially identifies a new class of epilepsy biomarker and reveals the possible existence of prodromal molecular patterns in blood that could be used to predict seizure risk.

Authors

Marion C. Hogg, Rana Raoof, Hany El Naggar, Naser Monsefi, Norman Delanty, Donncha F. O’Brien, Sebastian Bauer, Felix Rosenow, David C. Henshall, Jochen H.M. Prehn

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Usage data is cumulative from November 2025 through November 2026.

Usage JCI PMC
Text version 1,294 131
PDF 415 35
Figure 603 2
Table 214 0
Supplemental data 275 33
Citation downloads 325 0
Totals 3,126 201
Total Views 3,327
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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