Evidence map›Paper›PMID 37608136›Full record

ArticleClinical rheumatology2024

Role of lipid metabolism gene KLF4 in osteoarthritis.

Kaibo Hu, Yuan Shu, Zuxi Feng, Mi Zou, Jiazhe Luo, Ziyue Wei, Jie Peng, Liang Hao

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical rheumatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
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 at 1 institution in 1 country.

Kaibo HuDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
Yuan ShuDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
Zuxi FengDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
Mi ZouDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
Jiazhe LuoDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
Ziyue WeiDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China.
Jie PengDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China. Jie_Peng0459@163.com.
Liang HaoDepartments of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China. ndefy07018@ncu.edu.cn.ORCID http://orcid.org/0000-0001-5658-9975
Nanchang University · CN

Funding

the Science and Technology Project of the Education Department of Jiangxi Province GJJ190014
6 · The paper itself

Abstract

introductionOsteoarthritis (OA) is a common degenerative disease of joints, which can appear in almost any joint of the body. Therefore, the widespread occurrence of this disease has a huge impact on the lives of patients around the world. As an important part of metabolism, lipid metabolism is closely related to the occurrence and development of osteoarthritis.

methodWe screened UGCG and KLF4 based on weighted co-expression network analysis (WGCNA) and SVM-REF analysis. The data from Gene Expression Omnibus (GEO) and single-cell data verified the expression of these two genes. We analyzed KLF4-related genes and established a diagnosis model of OA related to lipid metabolism through the least absolute shrinkage and selection operator (LASSO) analysis. RT-PCR was used to verify the expression of KLF4 in osteoarthritis.

resultsTen important lipid metabolism related genes (LMRGs) in OA were obtained. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that they are involve in the formation of immune microenvironment in osteoarthritis. CIBERSORT analysis revealed that there were significant differences in the immune microenvironment between osteoarthritis patients and normal controls. RT-PCR results showed that the expression of KLF4 in OA samples was lower than that in normal samples. The diagnostic model can be used to diagnose OA patients well.

conclusionsOverall, we demonstrated the potential relationship between the abnormal lipid metabolism and the pathological process of OA. Finally, we identified KLF4 as our significant LMRG and constructed a KLF4-related scoring model to accurately diagnose OA. In conclusion, therapy strategies targeting on regulating lipid metabolism may become a key factor in treating OA. Key Points (a) We identified the significant LMRG KLF4 and constructed a novel KLF4-related scoring model for the accuracy diagnosis of OA. (b) The potential relationship between lipid metabolism and the immune microenvironment in OA was demonstrated in our research. (c) The relationship of lipid metabolism and OA has been further improved in our research and provided novel insight for the diagnosis and therapy for OA patients.

Indexed as

Lipid MetabolismOsteoarthritisHumansKruppel-Like Factor 4KLF4 protein, humanKruppel-Like Factor 4Bioinformatics analysisImmuneKLF4Lipid metabolismOsteoarthritis

Identifiers

PMID37608136
OpenAlexW4386084686

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.