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Enregistrement W2332453515 · doi:10.1097/00002030-200201250-00019

The T cell receptor Vβ repertoire shows little change during treatment interruption-related viral rebound in chronic HIV infection

2002· article· en· W2332453515 sur OpenAlexaffabout
Michael D. Grant, I. U. Pardoe, Mark Whaley, Julio Montaner, P. Richard Harrigan

Notice bibliographique

RevueAIDS · 2002
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueHIV Research and Treatment
Établissements canadiensAIDS VancouverMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésT-cell receptorRepertoireBiologyImmunologyImmune systemViral replicationViral loadVirusVirologyT cell

Résumé

récupéré en direct d'OpenAlex

In this study, changes in plasma virus load, peripheral blood CD4 T cell counts and the T cell repertoire were assessed in eight chronically HIV-infected individuals suspending antiretroviral therapy. Despite rapid increases in virus load and substantial CD4 T cell losses during treatment interruption, no marked changes in the T cell receptor β chain repertoire were observed. The magnitude of associated T cell repertoire perturbation thus contrasts with that observed during primary HIV infection. During primary HIV infection, the activation and expansion of HIV-specific T cells globally affects the T cell receptor (TCR) repertoire at the level of relative representation of individual TCRβ variable (V) chain gene families [1,2]. The extent of TCR repertoire perturbation signifies the strength of the anti-HIV T cell response; however, moderate perturbations within multiple TCRβV gene families predict a more benign subsequent disease course than do severe perturbations within fewer TCRβV families [2]. This general association suggests that a more diverse anti-HIV T cell response provides for a more effective and lasting immune suppression of HIV replication. The residual significance of this relationship between the immune response and disease course, now that effective suppression of HIV replication is often mediated by highly active antiretroviral therapy, is largely unknown. In this study, our objectives were to determine whether TCR repertoire perturbations were detectable at the level of relative TCRβV gene family representation during treatment interruption, and if so, whether, as in primary HIV infection, the pattern of TCR repertoire perturbation relates to the nature of the subsequent changes in virus load or CD4 T cell counts. Serial blood samples in the days after treatment interruption were collected from eight chronically HIV-infected individuals electing to suspend antiretroviral treatment for various reasons. Plasma HIV RNA was measured by Roche HIV-1 Amplicor Ultra direct assay (Roche Molecular Systems, Laval, Quebec, Canada) and peripheral blood CD4 T cell counts were measured at the time of treatment suspension and at regular intervals thereafter. Relative TCRβV gene family representation was assessed as previously described by semi-quantitative reverse transcriptase–polymerase chain reaction of RNA extracted from peripheral blood mononuclear cells (PBMC) collected at the time of treatment suspension and at least one timepoint approximately 1 month later [3]. Briefly, RNA was extracted from PBMC using Trizol (Gibco BRL, Burlington, Ontario, Canada) and complementary DNA was synthesized using a first-strand cDNA kit (Pharmacia Biotech Inc., Baie d'Urfe, Quebec, Canada). The equivalent of 1 μg RNA was split into 24 PCR mixtures, each incorporating one of 24 TCRβV gene family-specific primers, a common Cβ primer and a pair of Cα primers for an internal positive control (primers as in Choi et al. [4]). Reactions were run in 50 μl for 30 cycles under standard conditions, and products were separated on 2% agarose gels. Digital image analysis, using [email protected] software, was used to quantitate TCRβV band intensities, and these were expressed as a fraction of the internal control Cα band intensity to compare relative expression levels of individual TCRβV families before and after treatment interruption. The eight individuals electing to suspend antiretroviral therapy displayed highly variable patterns of changing plasma virus load and CD4 T cell counts once treatment stopped (Fig. 1). In three cases (subjects 2, 12 and 15), there was a steady increase in plasma virus load after stopping therapy, although this was associated with a sharp, sustained fall in CD4 T cell counts in only one case (subject 12) within this short time frame (Fig. 1b). In another three cases (subjects 3, 4 and 7), plasma virus load peaked and then fell, in a pattern similar to that associated with the development of anti-HIV immunity in primary infection. In the other two cases (subjects 11 and 17), plasma virus load fluctuated within a fairly moderate range after treatment interruption (Fig. 1a). None of these three patterns of viral rebound was associated with a distinct pattern of changes in the TCR repertoire. In fact, none of the eight cases of treatment interruption produced marked changes in the peripheral blood TCR repertoire. The most substantive changes we observed during treatment interruption were reductions in the level of several TCRβV families. In the PBMC of subject 3, TCRβV2 decreased from 9 to 5.7% over 15 days of treatment interruption, whereas in the PBMC of subject 12, TCRβV2 and TCRβV13 decreased from 13 to 8.5% and from 11.3 to 6.1%, respectively, over 29 days of treatment interruption (Fig. 2). The largest expansion we observed was an increase in TCRβV6 in the PBMC of subject 15 from 4.5 to 8% over 63 days of treatment interruption (Fig. 2). In contrast, individual TCRβV families expanded to constitute as much as 40% of the peripheral blood T cell repertoire in six cases of acute symptomatic HIV infection, and a more comprehensive study revealed at least twofold expansions of one or more TCRβV families in 16 out of 21 individuals with symptomatic primary HIV infection [1,2]. The sum of such expansions within particular TCRβV families indicated that 16–38% of peripheral blood T cells were potentially involved in the primary immune response to HIV infection [2].Fig. 1.: (a) Changes in plasma virus load and (b) number of CD4 T lymphocytes/μl peripheral blood for eight HIV-infected individuals after treatment interruption at day 0. The T cell receptor (TCR) β variable (V) repertoire was analysed at day 0 and at timepoints indicated with an arrow (b). The TCRβV repertoire was analysed at day 0 and day 22 after treatment interruption for subject 7, at which time CD4 T cell counts were not available. (a) ––□–– 2 Viral loads (VL); uu.uu.uu.uu.⋄uu.uu.uu.uu. 3 VL; – ○ – 4 VL; - - - ▪ - - - 11 VL; -uu.-uu.-♦-uu.-uu.- 12 VL; ––•–– 15 VL; - - ▴ - - 17 VL. (b) ––□–– 2 CD4 cell counts; uu.uu.uu.uu.⋄uu.uu.uu.uu. 3 CD4 cell counts; - - - ○ - - - 4 CD4 cell counts; - - - ▵ - - - 7 CD4 cell counts; - - -▪- - - 11 CD4 cell counts; -uu.-uu.-♦-uu.-uu.- 12 CD4 cell counts; - - -•- - - 15 CD4 cell counts; - - ▴ - - 17 CD4 cell counts.Fig. 2.: Changes in the levels of 24 T cell receptor β variable families are shown for eight HIV-infected individuals, numbered 2, 3, 4, 7, 11, 12, 15 and 17, who opted to stop antiretroviral therapy. Levels of the T cell receptor β variable families are shown for each individual immediately before treatment interruption (open bars) and approximately 1 month later (solid bars).The absence of marked changes in the T cell repertoire during viral rebound, as assessed using our methodology, does not mean that no meaningful anti-HIV T cell response occurred. In cases of an early rise and subsequent fall in plasma virus load, the fall was most likely mediated by the reactivation of anti-HIV immune effector cells. However, there are several plausible reasons why the immune response during viral rebound would be weaker than the immune response during primary infection. Recent studies of seroconverters [5,6] suggested that without antiretroviral therapy during primary infection, T cell clones activated by HIV often undergo clonal deletion and thus are unavailable for secondary activation during viral rebound. Similarly, HIV-specific T cells may fail to enter the long-term memory compartment and quickly disappear once effective antiretroviral treatment reduces antigenic stimulation below the threshold required for the ongoing recruitment and activation of effector cells [7]. Assuming a hierarchy among responding T cells based on precursor frequency or replicative fitness, new responses occurring during viral rebound would be weaker than those made during primary infection if the original responding cells had been eliminated. It is also possible that the cumulative immunological defects caused by HIV infection, including effects on T cells, antigen presenting cells and the cytokine milieu, preclude strong secondary or de-novo immune responses during viral rebound. A fourth possible reason for the absence of marked changes in individual TCRβV families during treatment interruption is that the diversification of the T cell response against HIV after primary infection spreads the T cell response sufficiently over different TCRβV families that it becomes inapparent by global TCR repertoire analysis. Indeed, more sensitive functional and clonotype-based studies [8,9] demonstrated HIV-specific T cell responses in association with viral rebound during treatment interruption. Michael Granta Ingrid Pardoea Mark Whaleyb Julio S. G. Montanerb P. Richard Harriganb

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,612
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,005

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.

Tête enseignante Opus0,033
Tête enseignante GPT0,267
Écart entre enseignants0,234 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2002
Routes d'admission2
Résumé présentoui

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