Evidence map›Paper›PMID 39272131›Full record

ArticleJournal of ovarian research2024

Long non-coding ribonucleic acid SNHG18 induced human granulosa cell apoptosis via disruption of glycolysis in ovarian aging.

Xuehan Zhao, Feiyan Zhao, Long Yan, Jiaqi Wu, Ying Fang, Cong Wang, Zhimin Xin, Xiaokui Yang

Abstract read
In one paragraph

Article in Journal of ovarian research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. [SF3B3 overexpression promotes proliferation of gastric cancer cells and correlates with poor patient prognosis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xuehan Zhao *Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China.
Feiyan Zhao *Department of Obstetrics and Gynecology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
Long YanKey Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
Jiaqi WuDepartment of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China.
Ying FangDepartment of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China.
Cong WangDepartment of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China.
Zhimin XinDepartment of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China. xinzhimin@ccmu.edu.cn.
Xiaokui YangDepartment of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China. yangxiaokui@ccmu.edu.cn.

Funding

Beijing Hospitals Authority' Ascent Plan DFL20191401Beijing Natural Science Foundation Z230013National Key Research and Development Program 2019YFA0110900National Natural Science Foundation of China 82271660
6 · The paper itself

Abstract

backgroundIn-depth understanding of dynamic expression profiles of human granulosa cells (GCs) during follicular development will contribute to the diagnostic and targeted interventions for female infertility. However, genome-scale analysis of long non-coding ribonucleic acid (lncRNA) in GCs across diverse developmental stages is challenging. Meanwhile, further research is needed to determine how aberrant lncRNA expression participates in ovarian diseases.

methodsGranulosa cell-related lncRNAs data spanning five follicular development stages were retrieved and filtered from the NCBI dataset (GSE107746). Stage-specific lncRNA expression patterns and mRNA-lncRNA co-expression networks were identified with bioinformatic approaches. Subsequently, the expression pattern of SNHG18 was detected in GCs during ovarian aging. And SNHG18 siRNA or overexpression plasmids were transfected to SVOG cells in examining the regulatory roles of SNHG18 in GC proliferation and apoptosis. Moreover, whether PKCɛ/SNHG18 signaling take part in GC glycolysis via ENO1 were verified in SVOG cells.

resultsWe demonstrated that GC-related lncRNAs were specifically expressed across different developmental stages, and coordinated crucial biological functions like mitotic cell cycle and metabolic processes in the folliculogenesis. Thereafter, we noticed a strong correlation of PRKCE and SNHG18 expression in our analysis. With downregulated SNHG18 of GCs identified in the context of ovarian aging, SNHG18 knockdown could further induce cell apoptosis, retard cell proliferation and exacerbate DNA damage in SVOG cell. Moreover, downregulated PKCɛ/SNHG18 pathway interrupted the SVOG cell glycolysis by lowering the ENO1 expression.

conclusionsAltogether, our results revealed that folliculogenesis-related lncRNA SNHG18 participated in the pathogenesis of ovarian aging, which may provide novel biomarkers for ovarian function and new insights for the infertility treatment.

Indexed as

ApoptosisGlycolysisGranulosa CellsRNA, Long NoncodingAgingFemaleHumansOvarylong non-coding RNA SNHG18, humanRNA, Long NoncodingFollicular developmentGlycolysisGranulosa celllncRNAOvarian agingSNHG18Transcriptomics

Identifiers

PMID39272131
PMCPMC11395969

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.