Characterizing HIV-1 reservoir dynamics in subtypes B and C to advance treatment and cure strategies
Notice bibliographique
Résumé
Human immunodeficiency virus type 1 (HIV-1) is the cause of acquired immunodeficiency syndrome (AIDS), a disease that has claimed over 40 million lives. The development of antiretroviral therapy (ART) transformed HIV-1 infection from a fatal disease into a chronic condition. However, challenges remain: ART is inaccessible to many globally, and those with access may experience HIV-related health issues. Although ART prevents HIV-1 replication, the viral DNA integrated into human DNA remains hidden in immune cells in a dormant state, forming what is known as the viral reservoir. ART cannot eliminate this viral DNA, allowing the virus to reactivate if ART is stopped, thus necessitating lifelong treatment. Proviral DNA can be either intact, meaning it can infect new cells, or defective, due to mutations or missing DNA fragments, which render it unable to replicate. Accurate quantification of both forms is essential for assessing treatment effectiveness and potential cure strategies. The Intact Proviral DNA Assay (IPDA) is a PCR test developed to quantify both forms. Initially optimized for HIV-1 subtype B, which is common in high-income countries, this assay was not applicable to subtype C, which accounts for approximately 47% of global infections, primarily in Sub-Saharan Africa. To address this gap, we developed an optimized version of the IPDA capable of quantifying both subtypes B and C. Using this assay in a study of 82 people living with HIV subtype C, we found that prior to treatment, the amount of defective HIV-1 DNA was closely linked to viral load, viral activity, and immune response. Notably, after 96 weeks of ART, the intact viral reservoir declined more than the defective DNA. These findings suggest that defective HIV-1 DNA is not merely passive but may be associated with an increased risk of HIV-related conditions, underscoring the importance of eliminating this DNA to halt disease progression. Additionally, in a study involving 30 individuals with low-level viremia, about half suppressed their viremia after switching to the high genetic barrier drug Darunavir, while the other half did not respond. In the non-responding group, we observed correlations between the defective viral DNA and viral activity. This indicates that defective proviruses may contribute to ongoing viral production, potentially leading to adverse health effects due to an increased immune response. One of the strategies to eliminate viral reservoirs is the "induce and reduce" approach, which involves two steps: first, "inducing" the virus out of hiding using latency reversal agents (LRAs), and second, allowing the immune system to recognize and eliminate the now-active infected cells. We investigated whether combining different classes of LRAs could enhance the reactivation of latent HIV-1. Our in vitro and ex vivo results indicated that combinations involving panobinostat were most effective at reactivating dormant HIV-1 without significantly harming healthy cells. Future research should focus more on finding LRA combinations that effectively reverse latency while employing strategies that can eliminate the induced reservoir. Moreover, we emphasize the importance of including anatomical reservoirs, especially the central nervous system, in cure strategies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».