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Killer immunoglobulin-like receptor (KIR) genes are associated with the risk of episodes of high-level and detectable viremia among HIV controllers

2021· preprint· en· W3178596007 on OpenAlexaff
Nathalia Beatriz Ramos de Sá, Karina dos S. Silva, Marcelo Ribeiro‐Alves, Diogo Gama Caetano, Fernanda Heloise Côrtes, Suwellen Sardinha Dias de Azevedo, Brenda Hoagland, Beatriz Grinsztejn, Valdiléa G. Veloso, Mariza Gonçalves Morgado, Sylvia Lopes Maia Teixeira

Bibliographic record

VenueF1000Research · 2021
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcGill University Health Centre
FundersFundação Oswaldo CruzFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsBiologyViremiaAlleleSingle-nucleotide polymorphismGenotypeVirologyHuman leukocyte antigenImmunologyGeneticsViral loadGeneAntigenAntibodyVirus

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background:</ns4:bold> HIV controllers (HICs) constitute a heterogeneous group of HIV-1 individuals able to suppress plasma viremia to low or undetectable levels in the absence of antiretroviral therapy. Host genetic factors may be involved in the sustained control of viral replication observed. We investigated the distribution and the potential impact of human leukocyte antigens (HLA)-B and -C alleles, killer immunoglobulin-like receptor (KIR) genes, single nucleotide polymorphisms (SNPs) of the NLRP3, CARD8 and IL-1β inflammasome genes, and CCR5Δ32 mutation on the viral control among HICs. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> In total, 28 HICs were categorized as persistent elite controllers (PECs, n = 7), ebbing elite controllers (EECs, n = 7), and viremic controllers (VCs, n = 14) according to the level of natural suppression of viremia. HLA alleles were assigned by sequencing-based typing, KIR alleles by polymerase chain reaction (PCR) sequence-specific amplification, SNPs by real-time PCR, and the CCR5Δ32 mutation by PCR. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> Significant differences were observed in the pairwise comparisons of protective HLA-B alleles, KIR Bx genotype, KIR2DL3 + C1 pair, KIR2DL5, and KIR2DS5 allelic carrier frequencies among the HIC groups. Multivariate models showed that HICs without the KIR2DL3 allele or without KIR2DL3 + C1/C2 pair, with the HLA-C*08 allele or with the NLRP3 rs10754558-G SNP had a higher mean hazard of a viral load above 2,000 copies/mL, while a lower mean hazard of this event was observed for HICs with KIR2DL5, KIR2DS1, KIR2DS5, and KIR3DS1 alleles. Moreover, HICs with the KIR2DS5 allele had less risk of undergoing viral load (VL) blips within the same normalized period than those participants without this allele, while HICs without the KIR2DL3 allele had a mean higher risk of experiencing VL blips. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> These results indicate that innate immune mechanisms may play an essential role in modulating the sustained control of viral replication in HICs. </ns4:p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.019
GPT teacher head0.241
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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