Following the elite: Targeting immunometabolism to limit HIV pathogenesis
Notice bibliographique
Résumé
Few people living with HIV (PLWH) have undetectable plasma viral load, preserved CD4+ T cell counts, low HIV reservoir and limited immune activation/inflammation in the absence of antiretroviral therapy (ART). These individuals are called elite controllers (ECs) and represent a heterogeneous minority amongst PLWH. However, overtime, some of them lose HIV control. ECs who maintain viral control are called persistent controllers (PCs) while those who lose viral control are called transient controllers (TCs). As the underlying causes remain poorly understood, identifying factors associated with spontaneous loss of control will benefit HIV cure research [[1]Dagenais-Lussier X. Mouna A. Routy J.P. Tremblay C. Sekaly R.P. El-Far M. et al.Current topics in HIV-1 pathogenesis: the emergence of deregulated immuno-metabolism in HIV-infected subjects.Cytokine Growth Factor Rev. 2015; 26: 603-613https://doi.org/10.1016/j.cytogfr.2015.09.001Crossref PubMed Scopus (34) Google Scholar,[2]El-Far M. Kouassi P. Sylla M. Zhang Y. Fouda A. Fabre T. et al.Proinflammatory isoforms of IL-32 as novel and robust biomarkers for control failure in HIV-infected slow progressors.Sci Rep. 2016; 622902https://doi.org/10.1038/srep22902Crossref Scopus (33) Google Scholar]. Immunometabolism is rising to fame as the underlying mechanisms between metabolic reprogramming and immune response, thus providing a novel perspective of immunity in health and disease. In this issue of EBioMedicine, Tarancón-Diez et al. investigated the metabolic pathways linked with the spontaneous loss of control in HIV ECs [[3]Tarancón-Diez L. Rodríguez-Gallego E. Rull A. Peraire J. Viladés C. Portilla I. et al.Immunometabolism is a key factor for the persistent spontaneous elite control of HIV-1 infection.EBioMedicine. 2019; https://doi.org/10.1016/j.ebiom.2019.03.004Summary Full Text Full Text PDF Scopus (40) Google Scholar]. Using metabolomics, investigators from the Spanish AIDS Research Network compared plasma metabolites and lipids in persistent and transient controllers. Before losing control, TCs showed an increase in aerobic glycolysis, dysregulated mitochondrial activity, oxidative stress and immunological activation. Plasma levels of valine were found to differentiate TCs from PCs. Valine and related catabolic intermediates that could enter the tricarboxylic acid (TCA) Krebs cycle were elevated due to a switch from oxidative phosphorylation to glycolysis. In addition, lipid profiles characterized loss of viral control. Metabolites and lipid variations were associated with reduced HIV specific immune response demonstrated by a lower proportion of polyfunctional anti-HIV-Gag CD8+ T-cells in TCs compared to PCs. An immune response requires a massive amount of energy to allow cell proliferation, maturation, and production of effector molecules. Upon activation, both CD4+ and CD8+ T cells switch from a “resting state” of oxidative phosphorylation to glycolysis, allowing for a faster albeit more “costly” means to produce energy. In the same line, Valle-Casuso et al. found that metabolically active CD4+ T cells are susceptible to HIV infection, regardless of their activation status [[4]Valle-Casuso J.C. Angin M. Volant S. Passaes C. Monceaux V. Mikhailova A. et al.Cellular metabolism is a major determinant of HIV-1 reservoir seeding in CD4(+) T cells and offers an opportunity to tackle infection.Cell Metab. 2018; https://doi.org/10.1016/j.cmet.2018.11.015Summary Full Text Full Text PDF Scopus (88) Google Scholar]. Interestingly, targeting glycolysis and glutamine metabolism prevented HIV acquisition and viral production in CD4+ T cells in vitro. Furthermore, investigators showed that inhibiting glycolysis induced higher levels of cell death in HIV-infected cells compared to uninfected cells. These converging findings pave the way for novel therapeutic strategies targeting immunometabolism to prevent HIV infection and reduce HIV reservoir size [[4]Valle-Casuso J.C. Angin M. Volant S. Passaes C. Monceaux V. Mikhailova A. et al.Cellular metabolism is a major determinant of HIV-1 reservoir seeding in CD4(+) T cells and offers an opportunity to tackle infection.Cell Metab. 2018; https://doi.org/10.1016/j.cmet.2018.11.015Summary Full Text Full Text PDF Scopus (88) Google Scholar]. Importantly, an increase in glycolysis during HIV infection is not only restricted to T cell activation as monocytes, macrophages and dendritic cells also increase their ability to catabolize glucose upon detection of microbial products [[5]Palmer C.S. Anzinger J.J. Zhou J. Gouillou M. Landay A. Jaworowski A. et al.Glucose transporter 1-expressing proinflammatory monocytes are elevated in combination antiretroviral therapy-treated and untreated HIV+ subjects.J Immunol. 2014; 193: 5595-5603https://doi.org/10.4049/jimmunol.1303092Crossref PubMed Scopus (62) Google Scholar]. Hocini et al. recently found on a large number of patients strong HIV-specific immune responses and low inflammation in ECs compared to ART-treated patients, especially in CD4 and CD8 T cells [[6]Hocini H. Bonnabau H. Lacabaratz C. Lefebvre C. Tisserand P. Foucat E. et al.HIV controllers have low inflammation associated with a strong HIV-specific immune response in blood.J Virol. 2019; https://doi.org/10.1128/JVI.01690-18Crossref Scopus (21) Google Scholar]. This work also confirmed higher polyfunctionality of CD8+ T cells in ECs [[7]Almeida J.R. Price D.A. Papagno L. Arkoub Z.A. Sauce D. Bornstein E. et al.Superior control of HIV-1 replication by CD8+ T cells is reflected by their avidity, polyfunctionality, and clonal turnover.J Exp Med. 2007; 204: 2473-2485https://doi.org/10.1084/jem.20070784Crossref PubMed Scopus (577) Google Scholar]. Moreover, Chowdbury et al. described a distinct program of signaling pathways in CD8+ T cells from ECs with higher activation of pathways regulated by mammalian target of rapamycin (mTOR), phosphoinositide 3 kinase/Protein kinase B (PI3K/AKT) and eukaryotic initiation factor 2 (eIF2) [[8]Chowdhury F.Z. Ouyang Z. Buzon M. Walker B.D. Lichterfeld M. Yu X.G. Metabolic pathway activation distinguishes transcriptional signatures of CD8+ T cells from HIV-1 elite controllers.AIDS. 2018; 32: 2669-2677https://doi.org/10.1097/QAD.0000000000002007Crossref PubMed Scopus (23) Google Scholar]. These pathways are particularly implicated in the regulation of proliferation and cellular metabolism. Increased aerobic glycolysis is a hallmark of cellular proliferation and thus an underlying feature of cancer. However, modulating immunometabolism has proven difficult for cancer therapies. For instance, after promising results in mice models, recent trials showed no effect of indoleamine-2,3-deoxygenase (IDO) inhibitors in people with cancer [[9]O'Sullivan D. Sanin D.E. Pearce E.J. Pearce E.L. Metabolic interventions in the immune response to cancer.Nat Rev Immunol. 2019; https://doi.org/10.1038/s41577-019-0140-9Crossref Scopus (141) Google Scholar]. The role of immunometabolic pathways in the pathogenesis of HIV infection is flourishing as technical advances are allowing for more precise measurements of metabolic activities in immune cells. Metabolic targeted therapies aiming at decreasing inflammation and HIV reservoir size in ART-treated PLWH are currently being tested in clinical trials with the immunosuppressive drug sirolimus/rapamycin (ClinialTrials.gov NCT02440789) and the anti-diabetic medication Metformin (NCT02659306) [[10]Routy J.-P. Isnard S. Mehraj V. Ostrowski M.A. Chomont N. Ancuta P. et al.The effect of metformin on the size of the HIV reservoir in non-diabetic ART-treated individuals: the lilac pilot study protocol.BMJ Open. 2019; (in press)https://doi.org/10.1136/bmjopen-2018-028444Crossref Scopus (33) Google Scholar]. Overall, Tarancón-diez et al. [[3]Tarancón-Diez L. Rodríguez-Gallego E. Rull A. Peraire J. Viladés C. Portilla I. et al.Immunometabolism is a key factor for the persistent spontaneous elite control of HIV-1 infection.EBioMedicine. 2019; https://doi.org/10.1016/j.ebiom.2019.03.004Summary Full Text Full Text PDF Scopus (40) Google Scholar] demonstrated the relevance of immunometabolism in HIV-infection and highlighted it as a potential therapeutic tool to enhance immune response with the hope to clear HIV from reservoirs. The authors have no conflict of interest to disclaim. Immunometabolism is a key factor for the persistent spontaneous elite control of HIV-1 infectionAll these metabolomic differences should be considered not only as potential biomarkers but also as therapeutic targets in HIV infection. Full-Text PDF Open Access
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,015 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».