Evidence map›Paper›PMID 39398336›Full record

ArticleFrontiers in endocrinology2024

Shared diagnostic genes and potential mechanisms between polycystic ovary syndrome and recurrent miscarriage revealed by integrated transcriptomics analysis and machine learning.

Juanjuan He, Ahui Liu, Haofei Shen, Yanbiao Jiang, Min Gao, Liulin Yu, Wenjing Du, Xuehong Zhang, Fen Fu

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Article
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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

9 authors.

Juanjuan He *The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Ahui Liu *The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Haofei ShenThe First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Yanbiao JiangThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Min GaoThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Liulin YuThe First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Wenjing DuThe First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Xuehong ZhangThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Fen FuThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA), but the specific mechanism is not yet clear. Methods: Based on the GEO database, we downloaded the PCOS (GSE10946, GSE6798 and GSE137684) and RSA (GSE165004, GSE26787 and GSE22490) datasets and performed differential analysis, weighted gene co-expression network (WGCNA), functional enrichment, and machine learning, respectively, on the datasets of the two diseases, Nomogram and integrated bioinformatics analysis such as immune infiltration analysis. Finally, the reliability of the diagnostic gene was verified by external verification and collection of human specimens. Results: In this study, PCOS and RSA datasets were obtained from Gene Expression Omnibus (GEO) database, and a total of 23 shared genes were obtained by differential analysis and WGCNA analysis. GO results showed that the shared genes were mainly enriched in the functions of lipid catabolism and cell cycle transition (G1/S). DO enrichment revealed that shared genes are mainly involved in ovarian diseases, lipid metabolism disorders and psychological disorders. KEGG analysis showed significant enrichment of Regulation of lipolysis in adipocytes, Prolactin signaling pathway, FoxO signaling pathway, Hippo signaling pathway and other pathways. A diagnostic gene FAM166 B was obtained by machine learning and Nomogram screening, which mainly played an important role in Cellular component. GSEA analysis revealed that FAM166B may be involved in the development of PCOS and RSA by regulating the cell cycle, amino acid metabolism, lipid metabolism, and carbohydrate metabolism. CIBERSORT analysis showed that the high expression of FAM166 B was closely related to the imbalance of multiple immune cells. Further verification by qPCR suggested that FAM166 B could be used as a common marker of PCOS and RSA. Conclusions: In summary, this study identified FAM166B as a common biomarker for PCOS and RSA, and conducted in-depth research and analysis of this gene, providing new data for basic experimental research and early prognosis, diagnosis and treatment of clinical diseases.

Indexed as

Abortion, HabitualGene Expression ProfilingMachine LearningPolycystic Ovary SyndromeComputational BiologyDatabases, GeneticFemaleGene Regulatory NetworksHumansPregnancyTranscriptomebioinformatics analysisco-diagnostic genesimmune infiltrationmechanism researchPCOSRSA

Identifiers

PMID39398336
PMCPMC11466764

What Socratic holds

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Registered trials

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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 Socratic graph.