Novel HLA class I associations with HIV-1 control in a unique genetically admixed population
Bibliographic record
Abstract
Abstract Associations between HLA class I alleles and HIV progression in populations exhibiting Amerindian and Caucasian genetic admixture remain understudied. Using univariable and multivariable analyses we evaluated HLA associations with five HIV clinical parameters in 3,213 HIV clade B-infected, ART-naïve individuals from Mexico and Central America (MEX/CAM cohort). A Canadian cohort (HOMER, n = 1622) was used for comparison. As expected, HLA allele frequencies in MEX/CAM and HOMER differed markedly. In MEX/CAM, 13 HLA - A , 24 HLA - B , and 14 HLA - C alleles were significantly associated with at least one clinical parameter. These included previously described protective ( e . g . B*27 : 05 , B*57 : 01 / 02 / 03 and B*58 : 01 ) and risk ( e . g . B*35 : 02 ) alleles, as well as novel ones ( e . g . A*03 : 01 , B*15 : 39 and B*39 : 02 identified as protective, and A*68 : 03 / 05 , B*15 : 30 , B*35 : 12 / 14 , B*39 : 01 / 06 , B*39 : 05~C*07 : 02 , and B*40 : 01~C*03 : 04 identified as risk). Interestingly, both protective (e.g. B*39 : 02 ) and risk (e.g. B*39 : 01 / 05 / 06 ) subtypes were identified within the common and genetically diverse HLA - B*39 allele group, characteristic to Amerindian populations. While HLA-HIV associations identified in MEX and CAM separately were similar overall (Spearman's rho = 0.33, p = 0.03), region-specific associations were also noted. The identification of both canonical and novel HLA/HIV associations provides a first step towards improved understanding of HIV immune control among unique and understudied Mestizo populations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".