GENETIC ASSOCIATIONS WITH SYSTEMIC LUPUS ERYTHEMATOSUS IN SUDANESE POPULATION
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".