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Record W4376637640 · doi:10.1101/2023.05.12.23289896

Temporary increase in circulating replication-competent latent HIV-infected resting CD4+ T cells after switch to an integrase inhibitor based antiretroviral regimen

2023· preprint· en· W4376637640 on OpenAlexaff
Roux-Cil Ferreira, Steven J. Reynolds, Adam A. Capoferri, Owen R. Baker, Erin Brown, Ethan Klock, Jernelle Miller, Jun Lai, Sharada Saraf, Charles Kirby, Briana Lynch, Jada Hackman, Sarah N. Gowanlock, Stephen Tomusange, Samiri Jamiru, Aggrey Anok, Taddeo Kityamuweesi, Paul Buule, Daniel Bruno, Craig Martens, Rebecca Rose, Susanna L. Lamers, Ronald M. Galiwango, Art F. Y. Poon, Thomas C. Quinn, Jessica L. Prodger, Andrew D. Redd

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsWestern University
FundersNational Institute of Allergy and Infectious DiseasesJohns Hopkins University
KeywordsReplication (statistics)RegimenVirologyHuman immunodeficiency virus (HIV)Integrase inhibitorIntegraseAntiretroviral therapyViral replicationViral loadMedicineVirusBiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract The principal barrier to an HIV cure is the presence of a latent viral reservoir (LVR) made up primarily of latently infected resting CD4+ (rCD4) T-cells. Studies in the United States have shown that the LVR decays slowly (half-life=3.8 years), but this rate in African populations has been understudied. This study examined longitudinal changes in the inducible replication competent LVR (RC-LVR) of ART-suppressed Ugandans living with HIV (n=88) from 2015-2020 using the quantitative viral outgrowth assay, which measures infectious units per million (IUPM) rCD4 T-cells. In addition, outgrowth viruses were examined with site-directed next-generation sequencing to assess for possible ongoing viral evolution. During the study period (2018-19), Uganda instituted a nationwide rollout of first-line ART consisting of Dolutegravir (DTG) with two NRTI, which replaced the previous regimen that consisted of one NNRTI and the same two NRTI. Changes in the RC-LVR were analyzed using two versions of a novel Bayesian model that estimated the decay rate over time on ART as a single, linear rate (model A) or allowing for an inflection at time of DTG initiation (model B). Model A estimated the population-level slope of RC-LVR change as a non-significant positive increase. This positive slope was due to a temporary increase in the RC-LVR that occurred 0-12 months post-DTG initiation (p<0.0001). This was confirmed with model B, which estimated a significant decay pre-DTG initiation with a half-life of 7.7 years, but a significant positive slope post-DTG initiation leading to a transient estimated doubling-time of 8.1 years. There was no evidence of viral failure in the cohort, or consistent evolution in the outgrowth sequences associated with DTG initiation. These data suggest that either the initiation of DTG, or cessation of NNRTI use, is associated with a significant temporary increase in the circulating RC-LVR. Author Summary HIV is a largely incurable infection despite the use of highly successful antiretroviral drugs (ARV) due to the presence of a population of long-living resting CD4+ T cells, which can harbor a complete copy of the virus integrated into the host cell ’ s DNA. We examined changes in the levels of these cells, referred to as the latent viral reservoir, in a group of ARV-treated Ugandans living with HIV. During this examination, Uganda authorities switched the backbone drug used in ARV regimens to a different class of drug that blocks the ability of the virus to integrate into the cell ’ s DNA. We found that for approximately a year after this switch to the new drug, there was a temporary spike in the size of the latent viral reservoir despite the new drug continuing to completely suppress viral replication with no apparent adverse clinical effects.

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

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.032
GPT teacher head0.287
Teacher spread0.255 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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