GENETIC ASSOCIATIONS WITH SYSTEMIC LUPUS ERYTHEMATOSUS IN SUDANESE POPULATION
Notice bibliographique
Résumé
PV101 / #418 Poster Topic: AS12 - Genetics, Epigenetics, Transcriptomics Background/Purpose Previous genome-wide studies have revealed >130 loci linked to systemic lupus erythematosus (SLE), primarily in European populations.[1] Research on East Asian groups has shown different genetic associations related to SLE. This study contributes to understanding genetic risk factors for SLE across various ancestries, focusing on the Sudanese population. This study aimed to assess genetic associations with SLE in a cohort of Sudanese individuals. We sought to determine if the HLA alleles found in this cohort align with those identified in other studies. Methods The study involved 483 Sudanese participants, 96 of whom were diagnosed with SLE based on the revised 1982 ACR criteria and 387 age- and sex-matched healthy controls. Genotyping was performed using the Infinium® Expanded Multi-Ethnic Genotyping Array (MEGAEX). HLA alleles and amino acids were imputed using a modified 1000G African panel in SNP2HLA.[2] Genetic markers with a minor allele frequency (MAF) below 1%, genomic missingness over 5%, or imputation quality under 75% were excluded. After quality control, 453 unrelated samples and 1,183,339 variants were analyzed statistically. Genetic associations were examined using logistic regression models adjusted for age, sex, and the first 5 principal components with PLINK 2.0.[3] Significant associations were defined using Bonferroni correction for HLA alleles and amino acids, while a conventional genome-wide significance threshold was applied to other genetic associations. Results The strongest association within the MHC region was found with the HLA-DRB1*03 allele (frequency = 12%), which was linked to an increased SLE risk (OR = 1.95, 95% CI = 1.19–3.16; p = 0.007). More specifically the HLA-DRB1*0301 allele was associated with a 2-fold risk increase (OR = 2.00; 95% CI = 1.22–3.29; p = 0.006). Additionally, a novel association was identified with the rs12953472 marker located within the intronic region of the ZNF236-DT gene, associated with a significant increase in SLE risk (OR = 5.6, 95% CI = 2.86–10.9; p = 4.5 × 10 -07 ; Figure 1). Intriguingly, there are no prominent association signals from the MHC compared to other studies. Figure 1. Manhattan plot showing genetic associations with lupus. X and y-axes display chromosomal positions and log-transformed p-values, respectively. Genome-wide significance threshold is shown as a red dashed line. Conclusions This study represents the first GWAS focused on genetic factors influencing SLE in the Sudanese population. It confirms the association of HLA-DRB1*03 with SLE and reveals a novel suggestive signal within the ZNF236-DT gene that significantly increases SLE risk. These associations need to be validated in independent studies. Future research will also focus on genetic associations to clinical manifestations of SLE in individuals of African ancestry. References: [1.] Khunsriraksakul C. Nat Commun 2023;14:668. [2.] Jia X. PLoS One 2013;8:e64683. [3.] Chang CC. Gigascience 2015;4:7.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».