Evidence map›Paper›PMID 39328516›Full record

ArticleHeliyon2024

Integrated single-cell and bulk RNA sequencing analysis reveal immune-related biomarkers in postmenopausal osteoporosis.

Shenyun Fang, Haonan Ni, Qianghua Zhang, Jilin Dai, Shouyu He, Jikang Min, Weili Zhang, Haidong Li

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Emerging applications of feature selection in osteoporosis research: from biomarker discovery to clinical decision support.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2025
    Review
  5. Article
  6. 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.

Shenyun FangDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Haonan NiDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Qianghua ZhangDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Jilin DaiDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Shouyu HeDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Jikang MinDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Weili ZhangDepartment of Ophthalmology, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.
Haidong LiDepartment of Orthopedic Surgery, First People's Hospital of Huzhou, The First affiliated Hospital of Huzhou University, Huzhou, 313000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postmenopausal osteoporosis (PMOP) represents as a significant health concern, particularly as the population ages. Currently, there is a paucity of comprehensive descriptions regarding the immunoregulatory mechanisms and early diagnostic biomarkers associated with PMOP. This study aims to examine immune-related differentially expressed genes (IR-DEGs) in the peripheral blood mononuclear cells of PMOP patients to identify immunological patterns and diagnostic biomarkers. Methods: The GSE56815 dataset from the Gene Expression Omnibus (GEO) database was used as the training group, while the GSE2208 dataset served as the validation group. Initially, differential expression analysis was conducted after data integration to identify IR-DEGs in the peripheral blood mononuclear cells of PMOP. Subsequently, feature selection of these IR-DEGs was performed using RF, SVM-RFE, and LASSO regression models. Additionally, the expression of IR-DEGs in distinct bone marrow cell subtypes was analyzed using single-cell RNA sequencing (scRNA-seq) datasets, allowing the identification of cellular communication patterns within various cell subgroups. Finally, molecular subtypes and diagnostic models for PMOP were constructed based on these selected IR-DEGs. Furthermore, the expression levels of characteristic IR-DEGs were examined in rat osteoporosis (OP) models. Results: Using machine learning, six IR-DEGs (JUN, HMOX1, CYSLTR2, TNFSF8, IL1R2, and SSTR5) were identified. Subsequently, two molecular subtypes of PMOP (subtype 1 and subtype 2) were established, with subtype 1 exhibiting a higher proportion of M1 macrophage infiltration. Analysis of the scRNA-seq dataset revealed 11 distinct cell clusters. It was noted that JUN was significantly overexpressed in M1 macrophages, while HMOX1 showed a marked elevation in endothelial cells and M2 macrophages. Cell communication results suggested that the PMOP microenvironment features increased interactions among M2 macrophages, CD8 Conclusion: JUN, HMOX1, CYSLTR2, TNFSF8, IL1R2, and SSTR5 may serve as promising molecular targets for diagnosing and subtyping patients with PMOP. These results offer novel perspectives on the early diagnosis of PMOP and the advancement of personalized immune-based therapies.

Indexed as

BiomarkersDiagnosisImmuneMolecular subtypePostmenopausal osteoporosis

Identifiers

PMID39328516
PMCPMC11425179

What Socratic holds

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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.