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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Immunoglobulin A nephropathy (IgAN) is currently the most prevalent primary glomerular disease worldwide, with a particularly high incidence in the Asian population. Clinical studies have demonstrated that approximately 20%–40% of IgAN patients may progress to end-stage renal disease (ESRD). Therefore, in-depth investigations into the risk assessment of IgAN, its early diagnosis and prognostic prediction, the elucidation of its pathogenesis, and the optimization of therapeutic strategies—all aimed at improving patients' long-term prognosis—hold significant clinical value and scientific significance.
Objective
1. To investigate the causal relationship between risk factors and IgAN utilizing the Mendelian randomization (MR) approach.
2. To construct a non-invasive diagnostic model for IgAN via Bayesian network (BN), followed by evaluating the model’s diagnostic efficacy, thereby providing a novel tool for clinical IgAN diagnosis.
3. To assess the therapeutic efficacy and safety profile of telitacicept in combination with immunosuppressive regimens for the treatment of IgAN.
1. Analyses univariate and multivariate MR analyses were conducted using publicly accessible summary-level Genome-wide Association Study (GWAS) datasets to assess the causal effects of 33 candidate risk factors on the development of IgAN.
2. Clinical data were collected from patients who received a first-time diagnosis of primary glomerular disease via renal biopsy at the Second Hospital of Jilin University between January 2018 and December 2023. Subsequent data analysis and BN model establishment were performed using R software (Version 4.1.3).
3. Combined Therapy Patients with a confirmed diagnosis of primary IgAN (via renal needle biopsy as described above) were screened. Eligible participants were those with a 24-hour urine protein quantification (24h-UPRO) ≥ 0.5 g/d 3 months of optimized supportive care. Enrolled patients were assigned to two groups:
Experimental Group: Subcutaneous injection of telitacicept (160 mg) combined with methylprednisolone (MPS; 0.3–0.5 mg/kg) and/or mycophenolate mofetil (MMF; ≤ 1.0 g/d); Control Group: MPS (0.5–0.8 mg/kg) and/or MMF (≤ 1.0 g/d). The primary outcome was the change in 24 h-UPRO at week 24, while the secondary outcome was the change in estimated glomerular filtration rate (eGFR).
1. In the univariate and multivariate MR models, a causal relationship was identified between alcohol consumption frequency, BMI and education time and IgAN.
2. A range of significant differences were identified between the two groups in terms of age, haemoglobin, albumin, blood uric acid, serum creatinine, eGFR, LDL-C, total cholesterol, 24-hour urine protein, IgG, IgA, IgM, C3, and C4. The BN model was established with an accuracy rate of 85.8%, a recall rate of 75.0%, and an F1 score of 0.761, indicating its satisfactory clinical efficacy.
3. Following the implementation of the propensity score matching (PSM) test, the control and test groups were observed to undergo a 24-week period of observation. At the conclusion of this period, a 58.02% decrease in 24h-UPRO levels in the experimental group was recorded, with a P-value of less than 0.001. This decline was accompanied by a relatively stable test eGFR level. The hormone dosage was 61.7% of the hormone dosage in the control group, and the adverse events in the two groups were similar, not statistically significant, and there were no major adverse events, and there was a good safety during the treatment of IgAN.
In the present study, risk factors for IgAN were first identified from public databases. Subsequently, a non-invasive diagnostic prediction model was established using BN in a real-world setting, followed by an evaluation of the efficacy and safety of biological agents in the treatment of IgAN. This study provides robust evidence for the prevention, diagnosis, and treatment of IgAN, and holds important reference value for the development of IgAN-specific prevention and control strategies, diagnostic protocols, and therapeutic regimens. Furthermore, it carries great significance in reducing the incidence of IgAN, delaying the progression of IgAN to ESRD, and improving the prognosis of patients with IgAN.
