HLA GENOTYPES IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS IN RUSSIAN FEDERATION
Notice bibliographique
Résumé
PV111 / #471 Poster Topic: AS12 - Genetics, Epigenetics, Transcriptomics Background/Purpose Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by multiorgan damage mediated by immune complexes and the autoantibodies production. Human leukocyte antigen (HLA) gene polymorphisms play an important role in the pathogenesis of SLE, however, the observed susceptibility alleles vary across ethnic groups and geographic regions.[1] The current study aims to describe the spectrum of HLA class I and HLA class II alleles in Russian patients with SLE. Methods The study was approved by the local ethics committee and included 130 patients (110 women/20 men), average age was 34.0 [26.0; 42.0] years and 235 healthy controls. All enrolled patients were diagnosed with SLE according to the 2012 SLICC classification criteria. All patients signed informed consents to be included in the study. The duration of the disease was 7.0 [4.0; 13.0] years. Eighteen (14%) patients had secondary APS. SLEDAI-2K was 6.0 [4.0; 10.0]. Clinical and laboratory characteristics are presented in Table 1. HLA-typing of HLA-A, B, C, DRB1 and DQB1 alleles from whole genome sequencing data was conducted using the HLA-HD tool with a reference panel from the IPD-IMGT/HLA database.[2] All statistical analyses were performed using Python module statsmodels. Chi-square tests were performed to evaluate the differences in HLA allele frequencies between SLE patients and healthy controls. Alpha level was set at 0.05; p -values were corrected for multiple comparisons using Benjamini-Hochberg procedure. Table 1. Clinical and laboratory characteristics of the SLE patients. Results A total of 37 HLA-A, 58 HLA-B, 37 HLA-C, 34 HLA-DRB1 and 19 HLA-DQB1 4-digit allelic groups were detected in the patients with SLE. We found 2 alleles associated with increased risk for developing SLE in the Russian population: 1) HLA-DRB1*03:01 (OR = 2.31, 95% CI = 1.47-3.62, p-value = 0.03) 2) HLA-DQB1*02:02 (OR = 15.8, 95% CI = 4.72-53.1, p-value = 0.002) According to literary data HLA-DRB1:03:01allele is a major risk factor for SLE in Europeans, in addition, it was shown that the short epitope encoded by this allele activates SLE-characteristic cellular aberrations.[3] We also noted the overrepresentation of HLA-B*13:02, HLA-DRB1*15:01, HLA-DQB1*06:02 alleles in SLE patients (Figure 1). Figure 1. Cluster analysis of patients with SLE and healthy controls Conclusions Combinations of alleles identified as a result of cluster analysis were also considered. We observed that frequency of 5-loci haplotype HLA-A*01:01 ~ HLA-B*08:01~ HLA-C*07:01 ~ HLA-DQB1*02:01~ HLA-DRB1*03:01 was significantly increased in SLE patients when compared to controls. References: [1.] Lewis MJ. Rheumatology (Oxford) 2017;56(suppl_1):i67-77. [2.] Kawaguchi S. Hum Mutat 2017;38(7): 788-97. [3.] Miglioranza Scavuzzi B. Commun Biol 2022;5(1):751.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».