The HLA-B*57:01 allele corresponds to a very large MHC haploblock likely explaining its massive effect for HIV-1 elite control
Bibliographic record
Abstract
Introduction We have reanalyzed the genomic data of the International Collaboration for the Genomics of HIV (ICGH), centering on HIV-1 Elite Controllers. Methods We performed a genome-wide Association Study comparing 543 HIV Elite Controllers with 3,272 uninfected controls of European descent. Using the latest database for imputation, we analyzed 35,552 Single Nucleotide Polymorphisms (SNPs) within the Major Histocompatibility Complex (MHC) region. Results Our analysis identified 2,626 SNPs significantly associated (p<5. 10-8) with elite control of HIV-1 infection, including well-established MHC signals such as the rs2395029-G allele which tags HLA-B*57:01. A thorough investigation of SNPs in linkage disequilibrium with rs2395029 revealed an extensive haploblock spanning 1.9 megabases in the MHC region tagging HLA-B*57:01, comprising 379 SNP alleles impacting 72 genes. This haploblock contains damaging variations in proteins like NOTCH4 and DXO and is also associated with a strong differential pattern of expression of multiple MHC genes such as HLA-B, MICB, and ZBTB12. The study was expanded to include two cohorts of seropositive African-American individuals, where a haploblock tagging the HLA-B*57:03 allele was similarly associated with control of viral load. The mRNA expression profile of this haploblock in African Americans closely mirrored that in the European cohort. Discussion These findings suggest that additional molecular mechanisms beyond the conventional antigen-presenting role of class I HLA molecules may contribute to the observed influence of HLA-B*57:01/B*57:03 alleles on HIV-1 elite control. Overall, this study has uncovered a large haploblock associated with HLA-B*57 alleles, providing novel insights into their massive effect on HIV-1 elite control.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".