Omics · study · 2026
Circulating Transfer RNA Related Fragment (tRF) Abundance After Experimental Endometriosis Induction in Baboons
Listed in NCBI GEO
Endometriosis is a chronic systemic disease affecting approximately 10–15% of women of reproductive age, often resulting in chronic pelvic pain and infertility.
Description
Despite its high prevalence, diagnosis is frequently delayed. Transfer RNA-derived fragments (tRFs) are an emerging class of small non-coding RNAs that have been implicated in gene regulation and various pathological processes but remain understudied in endometriosis.
This study aimed to characterize temporal changes in circulating tRF abundance after experimentally induced endometriosis in a baboon model, with the goal of identifying non-invasive biomarkers for early disease detection. Endometriosis was induced in eight female baboons, and peripheral blood samples were collected at five time points: pre-inoculation and at 3-, 6-, 9-, and 15-months post-inoculation. RNA was extracted from serum samples and sequenced to profile tRF abundance.
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Differential expression analysis was performed using a linear modeling approach. Significant changes in tRFs were observed as early as three months after induction. Both upregulated and downregulated tRFs were identified at each time point.
A ranking based on log fold change and adjusted p-values revealed the ten most significantly altered tRFs, none of which had been previously described in the context of endometriosis. These tRFs demonstrated consistent differential abundance throughout all time points. This is the first study to investigate circulating tRFs in endometriosis.
There is a rapid induction of tRFs after the onset of endometriosis in the non-human primate model. Our longitudinal findings suggest that tRFs may serve as promising early biomarkers for endometriosis.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE327nnn/GSE327533 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE327533 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1451158 ncbi.nlm.nih.gov/bioproject/PRJNA1451158 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing
- From keywords
- Life Sciences
- Inferred from text
- Disease 75% · Longitudinal study 65%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE327533 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[method].local:method:longitudinal-study | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |