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Identification of potential key genes related to efferocytosis in rheumatoid arthritis using machine learning.

Identification of potential key genes related to efferocytosis in rheumatoid arthritis using machine learning.

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600129534
Enrollment
Unknown
Registered
2026-08-06
Start date
2026-04-24
Completion date
Unknown
Last updated
2026-08-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Rheumatoid arthritis

Interventions

RA patient group:None
Healthy volunteer group:None

Sponsors

Taicang Loujiang New City Hospital (Ruijin Hospital, Taicang)
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Bioinformatics analysis datasets 1. Synovial tissue samples from patients with a definite diagnosis of rheumatoid arthritis; 2. Datasets containing complete gene expression profiling data; 3. Datasets with clear grouping information for RA group and normal control group. Clinical samples 1. RA patients meeting the 2010 ACR/EULAR classification criteria; 2. Healthy volunteers with no history of autoimmune diseases; 3. All subjects have signed informed consent forms.

Exclusion criteria

Exclusion criteria: 1.Bioinformatics analysis datasets (1) Samples with unqualified data quality; (2) Samples lacking clear grouping information. 2.Clinical samples (1) Comorbid with other autoimmune diseases; (2) Recent use of immunosuppressive therapy.

Design outcomes

Primary

MeasureTime frame
Expression levels of hub genes (PTPN6, CASP1, CD47) and their ability to discriminate RA from control samples (based on area under the receiver operating characteristic curve, AUC);

Secondary

MeasureTime frame
Differentially Expressed Endothelial-Related Genes (DE-ERGs) screening results;Immune cell infiltration score;Prediction of miRNAs and transcription factors (TFs);qRT-PCR validation results;Phagocytic clearance-related indicators (CFSE-positive proportion, p-MerTK, Calreticulin, IL-1ß);

Countries

China

Contacts

Public ContactLiu Zhenlu

Taicang Loujiang New City Hospital (Ruijin Hospital, Taicang)

944749410@qq.com+86 512 56561907

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Aug 25, 2026