Vedolizumab and ART in recent HIV-1 infection unveil the role of α4β7 in reservoir size

Vedolizumab and ART in recent HIV-1 infection unveil the role of α4β7 in reservoir size Maria Reyes Jimenez-Leon, … , Luis F. Lopez-Cortes, Ezequiel Ruiz-Mateos JCI Insight. 2024;9(16):e182312. https://doi.org/10.1172/jci.insight.182312. We evaluated the safety and viral rebound, after analytical treatment interruption (ATI), of vedolizumab and ART in recent HIV-1 infection. We used this model to analyze the effect of α4β7 on the HIV-1 reservoir size. Participants started ART with monthly vedolizumab infusions, and ATI was performed at week 24. Biopsies were obtained from ileum and cecum at baseline and week 24. Vedolizumab levels, HIV-1 reservoir, flow cytometry, and cell-sorting and antibody competition experiments were assayed. Vedolizumab was safe and well tolerated. No participant achieved undetectable viremia off ART 24 weeks after ATI. Only a modest effect on the time to achieve more than 1,000 HIV-1 RNA copies/mL and the proportion of participants off ART was observed, being higher in the vedolizumab group compared with historical controls. Just before ATI, α4β7 expression was associated with HIV-1 DNA and RNA in peripheral blood and with PD1 and TIGIT levels. Importantly, a complete blocking of α4β7 was observed on peripheral CD4+ T cells but not in gut (ileum and cecum), where α4β7 blockade and vedolizumab levels were inversely associated with HIV-1 DNA. Our findings support α4β7 as an important determinant in HIV-1 […] Clinical Medicine AIDS/HIV Immunology Find the latest version: https://jci.me/182312/pdf 1 CLINICAL MEDICINE Authorship note: MRJL and CGC contributed equally to this work and are co–first authors. Conflict of interest: The authors have declared that no conflict of interest exists. Copyright: © 2024, Jimenez-Leon et al. This is an open access article published under the terms of the Creative Commons Attribution 4.0 International License. Submitted: April 23, 2024 Accepted: July 3, 2024 Published: August 22, 2024 Reference information: JCI Insight. 2024;9(16):e182312. https://doi.org/10.1172/jci. insight.182312. Vedolizumab and ART in recent HIV-1 infection unveil the role of α4β7 in reservoir size Maria Reyes Jimenez-Leon,1 Carmen Gasca-Capote,1 Cristina Roca-Oporto,1 Nuria Espinosa,1 Salvador Sobrino,2 Maria Fontillon-Alberdi,3 Ce Gao,4,5 Isabelle Roseto,4,5 Gregory Gladkov,4,5 Inmaculada Rivas-Jeremias,1 Karin Neukam,1 Jose German Sanchez-Hernandez,6 Raul Rigo-Bonnin,7 Antonio J. Cervera-Barajas,8 Rosario Mesones,8 Federico García,9 Ana Isabel Alvarez-Rios,10 Sara Bachiller,1 Joana Vitalle,1 Alberto Perez-Gomez,1 María Inés Camacho-Sojo,1 Isabel Gallego,1 Christian Brander,11 Ian McGowan,11 Beatriz Mothe,12,13 Pompeyo Viciana,1 Xu Yu,4,5 Mathias Lichterfeld,4,5 Luis F. Lopez-Cortes,1 and Ezequiel Ruiz-Mateos1 1Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Consejo Superior de Investigaciones Científicas, University of Seville, Clinical Unit of Infectious Diseases, Microbiology and Parasitology, Seville, Spain. 2Digestive Service and 3Service of Pathological Anatomy, Virgen del Rocío University Hospital, Seville, Spain. 4Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA. 5Infectious Disease Division, Brigham and Women’s Hospital, Boston, Massachusetts, USA. 6Pharmacy service, University Hospital of Salamanca-Institute for Biomedical Research of Salamanca, Salamanca, Spain. 7Department of Clinical Laboratory, Hospital Universitari de Bellvitge, Instituto de Investigación Biomédica de Bellvitge, Universitat de Barcelona, Barcelona, Spain. 8Clinical Trials Units, Virgen del Rocío University Hospital, Seville, Spain. 9Departament of Microbiology, San Cecilio University Hospital, Instituto de Investigación Ibs, Granada, Ciber de Enfermedades Infecciosas, Centro de Investigación Biomédica en Red de Enfermedades Infecciosas, Granada, Spain. 10Biochemistry Service, Virgen del Rocío University Hospital, Seville, Spain. 11AELIX Therapeutics S.L., Barcelona, Spain. 12Infectious Diseases Department and IrsiCaixa AIDS Research Institute, Hospital Germans Trias I Pujol, Badalona, Spain. 13Centro de Investigación Biomédica en Red de Enfermedades Infecciosas, Spain. BACKGROUND. We evaluated the safety and viral rebound, after analytical treatment interruption (ATI), of vedolizumab and ART in recent HIV-1 infection. We used this model to analyze the effect of α4β7 on the HIV-1 reservoir size. METHODS. Participants started ART with monthly vedolizumab infusions, and ATI was performed at week 24. Biopsies were obtained from ileum and cecum at baseline and week 24. Vedolizumab levels, HIV-1 reservoir, flow cytometry, and cell-sorting and antibody competition experiments were assayed. RESULTS. Vedolizumab was safe and well tolerated. No participant achieved undetectable viremia off ART 24 weeks after ATI. Only a modest effect on the time to achieve more than 1,000 HIV-1 RNA copies/mL and the proportion of participants off ART was observed, being higher in the vedolizumab group compared with historical controls. Just before ATI, α4β7 expression was associated with HIV-1 DNA and RNA in peripheral blood and with PD1 and TIGIT levels. Importantly, a complete blocking of α4β7 was observed on peripheral CD4+ T cells but not in gut (ileum and cecum), where α4β7 blockade and vedolizumab levels were inversely associated with HIV-1 DNA. CONCLUSION. Our findings support α4β7 as an important determinant in HIV-1 reservoir size, suggesting the complete α4β7 blockade in tissue as a promising tool for HIV-cure combination strategies. TRIAL REGISTRATION. ClinicalTrials.gov NCT03577782. FUNDING. This work was supported by the Instituto de Salud Carlos III (Fondo Europeo de Desarrollo Regional, “a way to make Europe,” research contracts FI17/00186 and FI19/00083 and research projects PI18/01532, PI19/01127, PI22/01796), Conserjería de Economía, Conocimiento, Empresas y Universidad, Junta de Andalucía (research projects P20/00906), the Red Temática de Investigación Cooperativa en SIDA (RD16/0025/0020), and the Spanish National Research Council. 2 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 Introduction Antiretroviral therapy (ART) suppresses HIV-1 replication to undetectable plasma levels but fails to eradicate the virus (1). HIV-1 remains transcriptionally active, primarily from defective HIV proviruses (2), or latent in anatomical and cellular reservoirs (3, 4). However, HIV rebounds after ART interruption in most people living with HIV (PLWH) (5, 6). Therapeutic strategies are being explored to achieve HIV eradication or permanent viral remission in the absence of ART, as occurs in persistent HIV-1 controllers (7). HIV-1 preferentially infects activated memory CD4+ T cells, which are enriched in gastrointestinal tissues (GITs) (8, 9). One of the pathways used by CD4+ T cells for trafficking into GITs is the interaction between α4β7 integrin, expressed on CD4+ T cells, and the mucosal vascular addressin cell adhesion molecule 1 (MAdCAM-1), expressed primarily on high endothelial venules within GITs (10). Additionally, α4β7 integrin is also incorporated in HIV-1 virions (11). HIV-1 gp120 can bind to α4β7 integrin, expressed on CD4+ T cells, leading to a rapid activation of lymphocyte function-associated antigen 1 (LFA-1), the integrin involved in the establishment of virological “synapses” and promoting cell-to-cell transmission of infection (12). These are key aspects in HIV-1 immunopathogenesis that need to be tackled to achieve a sustained virological remission since a high number of the target cells for HIV-1 infection are in the GITs. In this sense, CD4+α4β7+ T cells were found to harbor 3 times more SIV DNA than α4β7– T cell subsets (13). Besides, it has been shown that high levels of CD4+α4β7+ T cells increased the susceptibility to HIV-1 infection in nonhuman primates and heterosexual women (14–16). In addition, treatment with α4β7 blocking molecules significantly reduced SIVDNA levels in the gut (13, 17–19). However, the effect of blocking α4β7 expression on the HIV-1 reservoir landscape in peripheral blood and tissue in humans remains uncertain. These findings led to the hypothesis that α4β7 could be targeted to achieve a permanent virological remission off ART in humans. Vedolizumab is a humanized monoclonal antibody against α4β7 that is licensed for the treatment of inflammatory bowel disease (20–22). The therapeutic role of an α4β7 monoclonal antibody in HIV cure research remains unclear. In a recent clinical trial, no sustained viral remission was found after ART and vedolizumab treatment in ART-suppressed participants with chronic HIV infection (23), and the seminal efficacy data generated in a nonhuman primate model (19) could not be reproduced (24–26). In the present study, we evaluated the safety and efficacy in viral rebound, after analytical treatment interruption (ATI), of vedolizumab combined with ART on recently infected PLWH. None of the participants achieved undetectable viremia off ART at the end of the follow-up. However, importantly, α4β7 expression was associated with DNA and RNA HIV-1 levels in peripheral blood and in 2 gut locations (ileum and cecum). In addition, α4β7 levels were associated with PD1 and TIGIT protein levels, immune checkpoints molecules previously associated with the HIV-1 reservoir (27). Finally, just before ATI, despite the complete α4β7 blockade on peripheral CD4+ T cells, α4β7 was not entirely blocked in the gut, where the percentage of α4β7 blockade and vedolizumab levels were inversely associated with HIV-1 DNA levels. Therefore, using this model we describe key insights into the role of α4β7 in vivo in the human HIV-1 reservoir. Results Participants’ characteristics and safety of vedolizumab and ART in PLWH. Ten PLWH naive for ART (9 cisgender male participants and 1 cisgender female participant) were enrolled between September 2018 and June 2019 (Figure 1); all participants completed the study follow-up period. A total of 7 monthly vedolizumab infusions were administrated, in addition to ART, to each participant for 24 weeks. No adverse effects were observed during the infusions or postinfusion periods (Supplemental Table 1; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.182312DS1). Furthermore, no participant had detectable anti-vedolizumab antibodies at baseline (BL) or throughout follow-up (data not shown). Date of HIV-1 infection was estimated as the average between a HIV-1– and HIV-1+ serologic test (maximum time frame of 6 months) and/or 15 days before onset of symptoms compatible with acute retroviral syndrome. The median time from HIV-1 infection to study initiation was 75 days (IQR 40–82 days). Demographic, immunological, and virological characteristics of the study participants (vedolizumab group) are summarized in Table 1. In summary, vedolizumab was safe and well tolerated in people that started ART and vedolizumab after recent HIV infection diagnosis. Efficacy after the ATI. ART and vedolizumab were interrupted at week 24, and participants were followed every 4 weeks during the ATI period for up to 24 weeks. The plasma viral load (pVL) kinetics before ATI is shown in Supplemental Figure 1A. ART was restarted when pVL was more than 100,000 HIV-1 RNA copies/mL in 2 consecutive measurements 1 month apart. All participants had detectable viremia 3 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 during the ATI, and none achieved undetectable viremia (<20 HIV-1 RNA copies/mL) after 24 weeks of follow-up in the absence of treatment (Figure 2A). Four participants resumed ART due to the virological criteria, and the other 6 participants completed the follow-up with pVL of 1,590 HIV-1 RNA copies/mL (participant 1 [P1]); 6,250 HIV-1 RNA copies/mL (P4); 4,670 HIV-1 RNA copies/mL (P6); 10,000 HIV-1 RNA copies/mL (P8); 36,450 HIV-1 RNA copies/mL (P9); and 4,300 HIV-1 RNA copies/mL (P10) at week 48, respectively (Figure 2A). Participant number 7 restarted treatment at week 36 (12 weeks after ATI) and showed new viral recrudesce at week 40, compatible with self-reported intermittent low adherence to the treatment during the whole clinical trial. For that reason, P7 was removed from HIV-1 reservoir analysis. No ART resistance mutations were detected at BL, week 24, and week 48 in this participant (data not shown). Overall, there were no decreases in CD4+ T cell counts at week 24, 28, and 48 compared with the BL; in fact, we observed a significant increase in CD4+ T cell counts at week 24 and 28 (Supplemental Figure 1B). We did not observe a significant decrease from ATI to week 48 (Supplemental Figure 1B). Therefore, in this study we did not observe sustained viral remission during ATI after 24 weeks of ART and vedolizumab treatment in recently infected PLWH. Subsequently, in a post hoc analysis, we compared the pVL kinetics during the ATI from the vedolizumab group with historical controls from the placebo arm of the AELIX-002 study (NCT03204617), which also included a 24-week ATI (28). Both groups were matched by estimated time since HIV-1 acquisition at the moment of starting ART, sex, and age (Table 1). At the moment of ATI, CD4+ T cell counts and the CD4/CD8 ratio were higher in the historical controls, as these participants had been ART suppressed for 1 year more than the vedolizumab group (Table 1). For the purpose of this post hoc comparison, time off ART was analyzed with the same virological ART resumption criteria as the vedolizumab group. We did not observe significant differences in the proportion of participants remaining off ART between the 2 studies (Figure 2B). However, longer time to first pVL of more than 1,000 HIV-1 RNA copies/mL was observed in the vedolizumab group (P = 0.034) (Figure 2C). Time off ART was 24 weeks (IQR, 8–24 weeks) and 8 weeks (IQR, 5–20 weeks) in our study and the historical control cohort, respectively (P = 0.06; Supplemental Table 2). A nonsignificant increase in the time to reach more than 2,000 HIV-1 RNA copies/ mL (P = 0.074) was observed in the vedolizumab group, and no differences were observed in the time to first pVL of more than 10,000 or 20,000 HIV-1 RNA copies/mL (P = 0.333 and P = 0.303, respectively) (Supplemental Figure 1, C–E) and other parameters (Supplemental Table 2). HLA protective alleles have been associated with the spontaneous control of HIV viremia (29, 30). Individuals with these alleles may bias viral rebound kinetics after ATI. Considering only participants without protective HLA alleles (P36, P16, and P17 from the historical control cohort and P4 from our study were excluded), with the aim of avoiding confusing factors that could favor the viremia control, the differences between pVL kinetics increased between groups. There was a higher but not significant (P = 0.051) proportion of participants remaining off ART in the vedolizumab group (Figure 2D). Interestingly, the time off ART (median [IQR], 24 weeks [8–24 weeks] vs. 7 weeks [4–10 weeks]) and to peak pVL (median [IQR], 8 weeks [4–14 weeks] vs. 4 weeks [4–7 weeks]) were higher in the vedolizumab group compared with the historical controls (P = 0.027 and P = 0.047), respectively, the same as the time to first pVL of more than 1,000 HIV-1 RNA copies/mL (P = 0.044) (Figure 2E). A nonsignificant increase was observed in the time to reach more than 2,000 HIV-1 RNA copies/mL (P = 0.094) in the vedolizumab group, and no differences were observed in the time to first pVL of more than 10,000 or 20,000 HIV-1 RNA copies/mL (P = 0.263 and P = 0.285, respectively). It is important to note, that pVL before ART, in Figure 1. Clinical trial design. Ten individuals with HIV-1 diagnosis in acute/recent infection phase were enrolled. Participants started ART together with vedolizumab infusions (300 mg) at week 0, 4, 8, 12, 16, 20, and 24. At week 24, ART and vedolizumab treatments were interrupted. Biopsies were obtained from ileum and cecum at week 0 and 24. GALT, gut-associated lymphoid tissue; ART, antiretroviral therapy; ATI, analytic treatment interruption. 4 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 these participants without protective HLA alleles, was higher in the vedolizumab group compared with the historical control group (median [IQR], 6.09 HIV-1 RNA copies/mL [5.12–6.90 HIV-1 RNA copies/ mL] vs. 4.95 HIV-1 RNA copies/mL [4.43–5.73 HIV-1 RNA copies/mL], P = 0.030). Combined therapy resulted in decreased HIV-1 reservoir levels. Next, although no sustained viral remission was found, we took advantage of the study design to explore the relationship between immunological factors in the intervention cohort, focusing on α4β7+ expression, and HIV-1 reservoir levels in peripheral blood and GIT. Regarding HIV reservoir levels, a decrease in total HIV-1 DNA was observed in PBMCs at weeks 24 and 28. (Figure 3A, left). A similar pattern was observed in cell-associated HIV-1 RNA except for week 28 (Figure 3A, right). This may be due to the fact that all participants at week 28 were without ART but with detectable pVL (Figure 2A). Interestingly, in all of the studied time points, participants who restarted ART showed higher levels of total HIV-1 DNA in PBMCs than participants who reached study week 48 of follow-up without ART (Supplemental Figure 2A, left). The same kinetic was observed for cell-associated HIV-1 RNA but only for BL and week 28 (Supplemental Figure 2A, right). HIV-1 reservoir was also assayed in ileum and cecum cells (Figure 3B). A significant decrease was observed in both locations in total HIV-1 DNA and cell-associated HIV-1 RNA at week 24 respect to BL (Figure 3B, left and right, respectively). We did not observe differences in HIV-1 reservoir levels (DNA or RNA) between ileum and cecum, neither at BL nor week 24. Participants who restarted ART presented similar levels of HIV-1 reservoir in GIT (DNA or RNA) as those who did not restart ART, with no significant differences at BL and week 24 in ileum or cecum (Supplemental Figure 2B, left and right panel, respectively). There was a strong positive correlation between total HIV-1 DNA reservoir in ileum and cecum and the pVL at BL (Figure 3C, left). Interestingly, this correlation was not observed with the HIV-1 reservoir (DNA or RNA) in peripheral blood (Figure 3C, right). Effect of combined therapy on β7 integrin expression. The percentage of memory CD4+ T cells expressing β7 integrin was determined throughout the follow-up period. Quantification of α4β7+ levels was performed by gating CD4+CD45RO+β7+ as previously described (9, 14, 31, 32). We did not observe differences in either in the percentage (Figure 4A) or in the absolute numbers (Supplemental Figure 3A) of CD4+CD45RO+β7+ cells in PBMCs during follow-up. Nevertheless, PLWH who restarted ART had higher levels of CD4+C- D45RO+β7+ in PBMCs at week 24 compared with those participants who completed the ATI period (Supplemental Figure 4A). The same trend was observed for absolute CD4+CD45RO+β7+ cell counts but at Table 1. Characteristics of study participants Characteristic Vedolizumab group (n = 10) Historical control groupA (n = 15) P value Age (years) at study entry, median (IQR) 39.8 (27.0–42.6) 34.0 (30.0–42.0) 0.657 Male sex (%) 90 100 0.211 Female sex (%) 10 0 Time since HIV infection at study entry (days), median (IQR) 75 (40–82) 55 (30–108) 0.912 CD4+ T cell counts (cells/mm3) at study entry, median (IQR) 540 (401–735) 826 (608–950) 0.006 CD8+ T cell counts (cells/mm3) at study entry, median (IQR) 1,093 (603–1,287) 937 (468–1,101) 0.202 Ratio of CD4+/CD8+ T cells at study entry, median (IQR) 0.5 (0.4–0.9) 1.1 (0.7–1.6) 0.011 Pre-ART viral load (log10 HIV-1 RNA copies/mL), median (IQR) 5.7 (5.0–6.9) 4.9 (4.4–5.9) 0.101 Time on ART at ATIB start (years), median (IQR) 0.5 (0.5–0.5) 1.9 (1.6–3.2) <0.0001 Time with undetectable viral load at ATI start (years), median (IQR) 0.3 (0.3–0.4) 1.5 (1.3–2.9) <0.0001 INSTI-based ART, n (%) 10 (100) 15 (100) >0.999 Continuous variables were expressed as medians and IQRs, and categorical variables were expressed as numbers and percentages. The Mann-Whitney U and χ2 tests were used to analyze differences of continuous and categorical variables between groups, respectively. AHistorical participants in the placebo arm of a therapeutic vaccine trial (27). BAntiretroviral treatment interruption. INSTI, integrase strand transfer inhibitor. 5 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 not significant level (Supplemental Figure 5A). Interestingly, those participants who resume ART after ATI increased CD4+CD45RO+β7+ in PBMCs at week 24 or 28, and these increases were associated with nonsignificant higher pVL levels (P = 0.077), total cell-associated HIV-1 DNA (P = 0.034) and HIV-1 RNA levels (P = 0.034) in PBMCs (Supplemental Figure 4B) and higher HIV-1 RNA in ileum (P = 0.034) and HIV-1 DNA in cecum at BL (P = 0.077) (Supplemental Figure 4C). Likewise, at week 24, those participants who increased CD4+CD45RO+β7+ levels in PBMCs at week 24 or 28 had higher CD4+CD45RO+β7+, total and defective HIV-1 DNA and HIV-1 RNA levels in PBMCs at just before ATI (week 24) (Figure 4B and Supplemental Figure 4D). The same results were observed when analyzing absolute CD4+CD45RO+β7+ T cell counts (Supplemental Figure 3B and Supplemental Figure 5, B–D). In addition, cell-associated HIV-1 RNA, total and defective, but not intact HIV-1 DNA levels were also directly associated with CD4+C- D45RO+β7+ in PBMCs at week 24 (Figure 4C). Furthermore, PLWH who restarted ART presented higher levels of defective HIV-1 DNA levels (Supplemental Figure 4E). Unlike PBMCs (Figure 4A), the CD4+C- D45RO+β7+ subset was significant decreased in ileum and cecum at week 24 respect to BL (Figure 4D). There were no decreases in total CD4+ T cell levels in gastrointestinal (GI) tissue (Supplemental Figure 4F) and no differences were detected between PLWH who restarted ART and those who did not in GI tissue at BL and week 24 (Supplemental Figure 4G). Figure 2. Plasma viral load, proportion of participants off ART, and time to viral load rebound after ATI. (A) Longitudinal plasma viremia evolution after ATI. Four participants restarted ART (gray area) because of an increase of viral load (>105 HIV-1 RNA copies/ mL). The horizontal red line indicates the limit of detection (20 HIV-1 RNA copies/mL). (B) Kaplan-Meier analysis of the proportion of participants off ART after ATI compared with the historical control group. (C) Kaplan-Meier analysis between the vedolizumab and historical control groups of the time to first viral load of more than 1,000 HIV-1 RNA copies/mL. (D and E) Kaplan-Meier analysis considering only participants without protective alleles (HLA-B*27 and HLA-B*57). In this analysis, participants 36, 16, and 17 from the historical control cohort and participant 4 from the vedolizumab group were excluded. Wilcoxon’s test, log-rank, and Kaplan-Meier curves were used to assess differences during the follow-up period. BL, baseline; W, week; ATI, analytic treatment interruption. 6 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 To deeply analyze the importance of α4β7 integrin in the HIV reservoir levels, we also determined the HIV-1 reservoir in peripheral CD4+CD45RO+β7+ and β7– sorted cells (Figure 4E). CD4+CD45RO+β7+ cells presented higher levels of total HIV-1 DNA and cell-associated HIV-1 RNA at BL and week 24 than CD4+CD45RA+β7– cells. Although statistical differences were not observed at week 24 in HIV-1 RNA levels, 33.3% were positive for HIV-1 RNA levels in CD4+CD45RA+β7– cells compared with 66.6% in CD4+CD45RA+β7+ cells (Figure 4E). Interestingly, we only observed a decrease in HIV-1 DNA and RNA in CD4+CD45RO+β7+ cells at week 24 relative to BL (Figure 4E). Inefficient α4β7 blocking in GIT is associated with higher HIV-1 reservoir levels. Serum concentrations of vedolizumab were determined prior to each monthly infusion and at weeks 28 and 32 (Figure 5A). The concentrations were similar to those reported in clinical trials of inflammatory bowel disease (20, 21), but the median concentration was slightly lower compared with the clinical trial performed in chronic HIV-1 infection (23). This may occur because vedolizumab can also be bound to the α4β7 integrin present on free virus envelope from participants with high detectable viremia. Using the anti-α4β7 mAb clone ACT-1, with the same target epitope of vedolizumab, we observed that α4β7 integrin was completely blocked by vedolizumab on peripheral CD4+ T cells at week 24 (Figure 5B, left), while partial blocking was found in ileum and cecum in the same time point (Figure 5B, right). Indeed, there was a positive correlation between the fraction of CD4+CD45RO+α4β7+ cells not blocked by vedolizumab and HIV-1 DNA in ileum and cecum (Figure 5C, left). However, when we used the clone FIB504, which epitope is recognized independently of bounded vedolizumab, we did not observe this correlation (Figure 5C, right). Taking this into account, we calculated the percentage of blocked α4β7 with the combination of ACT-1 and FIB504 clones. There were Figure 3. Dynamics of HIV-1 reservoir. (A) Total cell-associated HIV-1 DNA and RNA in PBMCs during the follow-up period. (B) Cell-associated HIV-1 DNA and RNA in ileum and cecum cells at BL and week 24. (C) Associations between HIV-1 reservoir in GITs (cell-associated HIV-1 DNA) and PBMCs (cell-associ- ated HIV-1 DNA and RNA) and plasma viral load at BL. Horizontal red line indicates the limit of detection. Friedman’s test with Dunn’s multiple comparisons test correction was used to assess differences during the follow-up period and Mann-Whitney U test was used between GIT locations. P values are shown within the graphs. BL, baseline; W, week; ATI, analytic treatment interruption. 7 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 no differences in the percentage of CD4+CD45RO+α4β7+ cells blocked between ileum and cecum at week 24 neither between PLWH who restarted ART or those who not (Supplemental Figure 6A). Interestingly, we found an association between HIV-1 DNA reservoir and CD4+CD45RO+α4β7+ cells blocked in both ileum and cecum at the same time point (Figure 5D). Importantly, we also observed a negative correlation Figure 4. Analysis of the dynamic of β7 expression levels and association with the size of the HIV-1 reservoir at week 24. (A) Dynamic of α4β7 expression on CD4+ T cells during the follow-up period in PBMCs. (B) Correlation between dynamic patterns of peripheral CD4+α4β7+ T cell levels at week 24 or 28 and memory CD4+α4β7+ levels, total HIV-1 DNA assayed by FLIP-Seq, and HIV-RNA levels at week 24. (C) Correlation between peripheral CD4+α4β7+ T cells and total, intact, and defective HIV-1 DNA assayed by FLIP-Seq at week 24. CD4+α4β7+ levels were considered to decrease when there was more than 2.5-fold reduction at week 24 or 28 compared with BL. CD4+α4β7+ levels were considered to increase when there was more than 1.3-fold change at week 24 or 28 compared with BL. (D) Dynamic of α4β7 expression on CD4+ T cells in ileum and cecum at BL and week 24. (E) Total cell-associated HIV-1 DNA and RNA in peripheral CD4+ T α4β7+ and α4β7– sorted cells at BL and week 24. Horizontal red line indicates the limit of detection. P values were computed using Wilcoxon’s, Mann-Whitney U, and Spearman’s test. P values are shown within the graphs. BL, baseline; W, week; ATI, analytic treatment interruption. 8 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 between the HIV-1 RNA levels in ileum and vedolizumab concentration at week 20 (Figure 5E); this correlation was also observed for HIV-1 DNA levels on PBMCs (Supplemental Figure 6B). Immune checkpoint molecules are associated with α4β7 integrin and HIV-1 reservoir levels. Immune checkpoint molecules have been associated with HIV-1 reservoir levels (27). We quantified the expression of PD1, TIGIT, TIM3, and LAG3 in memory CD4+ T cells in PBMCs and GI tissue cells and analyzed its association with α4β7 integrin and HIV-1 reservoir levels. Following the same trend as overall α4β7 expression in peripheral blood (Figure 4A), we did not observe differences in either PD1 and TIGIT expression (Figure 6A) or LAG3 and TIM3 (Supplemental Figure 7A) during follow-up. We observed that PD1 memory CD4+ T cell levels positively correlated with peripheral total HIV-1 DNA, and a similar but nonsignificant (P = 0.125) correlation was observed for TIGIT memory CD4+ T cell levels (Figure 6B). In the same way, PD1 and TIGIT memory CD4+ T cell levels positively correlated with CD4+CD45RO+β7+ levels (Figure 6C). We calculated the “multiple immune checkpoint phenotype” in combination with β7 integrin (simultaneous expressions of 3 or more of the analyzed markers). The simultaneous expression index of these markers (β7+LAG3+PD1+TIM3+TIGIT+) positively correlated with CD4+CD45RO+β7+ and peripheral total HIV-1 DNA (Figure 6D), showing the highest levels in PLWH who restarted ART after ATI (Figure 6D and Supplemental Figure 7B). Furthermore, we analyzed whether these multiple immune checkpoints, α4β7+ expression, and HIV-1 reservoir were associated with inflammation. Inflammatory soluble markers, such as high-sensitivity C-reactive protein (hsCRP), the coagulation biomarker D-dimer (DD), and β2 microglobulin (B2M), were assayed (Figure 6E). B2M levels decreased during the follow-up period (Figure 6E, right) and at week 24 were associated with α4β7 and PD1 memory CD4+ T cell expression and with HIV-1 DNA levels, which in turn were also associated with DD levels (Figure 6F). Finally, we also analyzed these molecules in GIT. In this case, the HLA-DR, LAG3, TIM3 (Supplemental Figure 7C), and PD1 expression (Figure 6G) were significantly decreased in memory CD4+ T cells at week 24 with respect to BL in ileum and cecum, contrary to what occurred in peripheral blood (Figure 6A). Follicular CD4+ T (Tfh) cells express PD1 and are enriched in α4β7 integrin (33). Although Tfh cells levels did not change during follow-up (Figure 6H), at week 24, Tfh cells levels were positively associated with the fraction of CD4+α4β7+ not blocked by vedolizumab, and a nonsignificant positive correlation was found with total HIV-1 DNA in GIT (Figure 6I). Retinoic acid is associated with reservoir levels in GIT. The main GIT cell subsets associated with higher α4β7 integrin expression are Tfh cells, regulatory CD4+ T cells (Tregs), and IL-17–producing T helper (Th17) cells. However, we did not observe associations between Treg and Th17 cell levels and α4β7 expression, in contrast to Tfh cells (Figure 6I). Dendritic cells are the major producers of retinoic acid, which is required for inducing gut-tropic lymphocytes. Retinoic acid potentiates the induction of gut homing FoxP3+ Tregs and inhibits the development of Th17 cells. Th17 cell/Treg ratio and retinoic acid are involved in the maintenance of GIT homeostasis and damage (34). We found that Treg levels were significant increased, and consequently, the ratio Th17 cell/Treg decreased at week 24 in ileum (Figure 7A). Although we did not observe differences in retinoic acid plasma levels during follow-up (Supplemental Figure 8A), a negative correlation between total HIV-1 DNA levels in cecum and retinoic acid and a positive association between Tregs and myeloid dendritic cells in cecum with retinoic acid levels were observed at week 24 (Figure 7B). Finally, changes between peripheral HIV-1 DNA reservoir levels between BL and week 24 (Supplemental Figure 8B) and the Th17 cell/Treg ratio in ileum and cecum showed a positive nonsignificant and significant association, respectively(Figure 7C). Discussion In this clinical trial, we analyzed the safety and efficacy of vedolizumab combined with ART to achieve virological remission in treatment-naive recently infected PLWH after ATI. Our results show that vedolizumab was safe and well tolerated. Nevertheless, no sustained undetectable viremia was seen during the ATI period. However, using this model we unveiled important insights about the role of α4β7 expression in HIV-1 reservoir levels in peripheral blood and GIT in humans. A previous study performed in individuals with chronic HIV-1 infection (23), using a similar regimen of vedolizumab to the one used in our study, also showed that vedolizumab was well tolerated, confirming a safe spectrum profile in PLWH. In the same study, vedolizumab was also not able to induce virological remission after ART interruption (23), in accordance with previous findings in the SIV model (24–26). However, the criteria for ART reintroduction after ATI in our study allowed us to observe that 60% of participants 15 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 Laboratory). Retinoic acid plasma levels were determined by UHPLC-MS/MS according to previously described method (66–68). All the assays were performed following the manufacturers’ instructions. Plasma levels of vedolizumab and immunogenicity. Serum concentrations of vedolizumab and the presence of antidrug antibodies were determined in serum samples using the ELISA RIDASCREE VDZ Monitoring (r-biopharm). The assays were performed following the manufacturer’s instructions. Immunophenotyping and quantification of α4β7 cells. Cryopreserved PBMCs were thawed, washed (650g, 5 minutes, room temperature) with PBS, and incubated for 35 minutes at room temperature with LIVE/ DEAD Fixable Aqua Dead Cell Stain (Life Technologies) and extracellular anti-human antibodies anti- CD45RA (FITC); anti-TIGIT (PerCP-Cy5.5); anti-LAG3 (BV605); anti-PD1 (BV510); anti-integrin β7 (BV711); anti-CD27 (BV786); anti-CD38 (BV650); anti-CD3 (APCH7); anti-integrin α4β7 (APC); anti- TIM3 (PeCF594); anti-HLA-DR (BV570); anti-CD4 (AF 700); and anti-CD19, anti-CD14, and anti-CD56 (Pacific Blue) (See Supplemental Table 3). PBMCs were then washed with PBS and permeabilized with the Fixation/Permeabilization FoxP3 Kit (eBioscience) according to the manufacturer’s instructions. Cells were stained intracellularly at 4°C for 30 minutes with anti-Ki67 (PE) and then washed and fixed in PBS containing 4% paraformaldehyde. Samples were acquired using LSR-II Fortessa Cytometer (BD Immunocytometry Systems), and analyses were performed using FlowJo, version 9.2. Isolated GI cells were thawed, washed (650g, 5 minutes, room temperature) with PBS, and incubated for 35 minutes at room temperature with LIVE/DEAD fixable Violet Dead cell stain and extracellular anti-hu- man antibodies anti-CCR6 (AF 647); anti-CD45RA (FITC); anti-CD25 (PE-Cy7); anti-CXCR5 (BV421); anti-LAG3 (BV605); anti-CXCR3 (PerCP-Cy5.5); anti-PD1 (BV510); anti-CD127 (BUV737); anti-CD45 (BUV805); anti-CD8 (BUV615); anti-CD69 (BB700); anti-CD103 (BV480); anti-CCR7 (BUV563); anti- CD3 (APC-H7); anti-TIM3 (PE/DAZZLE 594); anti-integrin α4β7 (APC); anti-CD123 (Alexa Fluor700); anti-CD11c (BV650); anti-HLA-DR (BV570); anti-integrin β7 (BV711); anti-CD27 (BV786); and anti- CD19, anti-CD14, anti-CD20, and anti-CD56 (Pacific Blue) (See Supplemental Table 3). Cells were then washed and permeabilized using the Fixation/Permeabilization FoxP3 Kit (eBioscience) according to the manufacturer’s instructions. Cells were stained intracellularly at 4°C for 30 minutes with anti-FoxP3 (PE-Cy5) and anti-Ki67 (PerCP-eFluor 710) and then washed and fixed in PBS containing 4% paraformaldehyde. Samples were acquired using a Cytek Aurora Spectral Cytometer 4L (Cytek Biosciences), and analyses were performed using FlowJo, version 9.2. Anti-integrin α4β7 mAb (APC; clone: ACT-1) was provided by Danlan Wei and James Arthos (National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland, USA). Anti-integrin α4β7 mAb (APC; clone: ACT-1) and vedolizumab share the same epitope. Quantification of integrin α4β7 levels was performed using anti-α4β7 mAb (APC; clone: ACT-1) at BL and by gating CD4+CD45RO+β7+ during the follow-up period. Previous studies have demonstrated that CD4+CD45RO+β7+ cells in peripheral blood are more than 99% α4β7+ (9, 14, 31, 32); therefore, this gating strategy was used to quantify α4β7 expression on CD4+ T cells (Supplemental Figure 9). The percentage of α4β7 integrin blocked by vedolizumab was calculated through the combination of anti-α4β7 (APC; clone ACT-1) and anti-β7 (BV711; clone FIB504). Cell sorting. CD4+ memory T cells α4β7+ and α4β7– were sorted from PBMCs. Cryopreserved PBMCs were thawed, washed with PBS (650g, 5 minutes, room temperature), and incubated for 35 minutes at room temperature with LIVE/DEAD Fixable Violet Dead cell stain and extracellular anti-hu- man antibodies anti-CD45RA (FITC); anti-integrin β7 (BV711); anti-integrin α4β7 (APC); anti-CD27 (BV786); anti-CD3 (APC-H7); anti-CD4 (AF700); and anti-CD19, anti-CD14, and anti-CD56 (Pacific Blue) (See Supplemental Table 3). CD4+CD45RO+β7+ and CD4+CD45RO+β7– cells were sorted using a BD FACSAria Fusion Flow Cytometer (BD Immunocytometry Systems), and analysis was performed using FlowJo, version 9.2. Quantitation of cell-associated HIV-1 DNA and RNA. The procedures for quantitation of total cell-associat- ed HIV-1 DNA and RNA have been previously described in detail (69). Briefly, levels of total cell-associated HIV-1 DNA and RNA were quantified by droplet-digital PCR (ddPCR) from extracted DNA and RNA using the Bio-Rad QX200 Droplet Reader. Genomic DNA was extracted using the Blood DNA Mini Kit (Omega, Bio-Tek) for the bulk of PBMCs and QIAamp DNA Micro Kit (Qiagen) for CD4+CD45RO+ β7+ and β7– sorted cells following the manufacturer’s protocol. RNA was extracted using NucleoSpin RNA purification kit (Macherey-Nagel) for the bulk of PBMCs and RNeasy Micro Kit (Qiagen) for sorted cells following the manufacturer’s protocol. DNA and RNA concentrations were measured by the Qubit Assay (Thermo Fisher Scientific) and diluted to a concentration of 30 ng/μL. Bio-Rad QX200 ddPCR system 16 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 was run according to the manufacturer’s protocol, using an annealing temperature of 58°C, using 2 pairs of primers targeting LTR and Gag regions (69). Copy numbers were calculated using Bio-Rad QuantaSoft software v.1.7.4. RPP30 (to cell-associated HIV-1 DNA) and TBP genes (to cell-associated HIV-1 RNA) were the host cell genes used to normalize HIV-1 copies. Full-length individual proviral sequencing in PBMCs. Full-length individual proviral sequencing (FLIP-Seq) was assayed in PBMCs at week 24. Genomic DNA, previously extracted from PBMCs (DNeasy Blood & Tissue kit, QIAGEN), was diluted to single proviral genomes based on ddPCR results and Poisson distribution statistics, where 1 provirus was present in approximately 20%–30% of wells. Subsequently, DNA was subjected to HIV-1 near-full-genome amplification using a single-amplicon nested PCR approach. The reaction was composed of 1 unit of Invitrogen Platinum Taq (catalog 11302-029) per 20 μL of reaction, 1× reaction buffer, 2 mM MgSO4, 0.2 mM dNTP, and 0.4 μM of forward (first-round nested PCR: U5-623F, 5′-AAATCTCTAGCAGTGGCGCCCGAACAG-3′; second-round nested PCR: U5-638F, 5′-GCGC- CCGAACAGGGACYTGAAARCGAAAG-3′) and reverse primer (first-round nested PCR: U5-601R, 5′-TGAGGGATCTCTAGTTACCAGAGTC-3′; second-round nested PCR: U5-547R, 5′-GCACTCAAG- GCAAGCTTTATTGAGGCTTA-3′). The PCR was performed using the following thermocycler program: 2 minutes at 92°C, 10 cycles [10 seconds at 92°C, 30 seconds at 60°C, 10 minutes at 68°C], 20 cycles [10 seconds at 92°C, 30 seconds at 55°C, 10 minutes at 68°C], 10 minutes at 68°C, and 4°C infinite hold. PCR products were visualized by agarose gel electrophoresis. All near-full-length genomes were subjected to Illumina MiSeq sequencing at the MGH DNA Core facility. Large deleterious deletions (<8,000 bp of the amplicon aligned to HXB2), out-of-frame indels, premature/lethal stop codons, internal inversions, or packaging signal deletions (≥15 bp insertions and/or deletions relative to HXB2) were identified by an automated pipeline written in Python programming language (https://github.com/BWH-Lichterfeld- Lab/Intactness-Pipeline, commit ID 0c59371) (70), and the presence or absence of APOBEC-3G/3F-as- sociated hypermutations was determined using a Los Alamos National Laboratory HIV-1 Sequence Database Hypermut 2.0 program (71). Viral sequences without any of the mutations mentioned previously were classified as intact sequences. Phylogenetic distances between sequences were determined through maximum-likelihood trees in MEGA (https://www.megasoftware.net/) and visualized with Highlighter plots (https://www.hiv.lanl.gov/content/sequence/HIGHLIGHT/highlighter_top.html). Statistics. Continuous variables were expressed as medians and IQRs, and categorical variables were expressed as numbers and percentages. Friedman’s test with Dunn’s multiple comparisons test correction was used to assess differences during the follow-up period. Wilcoxon’s signed-rank test was used to analyze related samples and Mann-Whitney U and χ2 tests were used to analyze differences between groups. Correlations between variables were assessed using Spearman’s rank test. Log-rank test and Kaplan-Meier curves were used for time-to-event analysis regarding virological efficacy compared with the historical control group. All P values of less than 0.05 were considered significant. Statistical analysis was performed using Statistical Package for the Social Sciences software (SPSS 22.0). Multiple immune checkpoint phenotypes were constructed using Pestle version 1.6.2 and Spice version 6 (provided by M. Roederer, NIH) and quantified with the polyfunctionality index algorithm (Pindex) employing the 0.1.2 beta version of FunkyCells Boolean Dataminer software, provided by Martin Larson (INSERM U1135, Paris, France) as previously described (72). Study approval. All participants gave written informed consent prior to the study start, The clinical trial was approved by the Seville Provincial Ethics Committee of Research with Medicines (NCT03577782, please visit https://clinicaltrials.gov/ for protocol summary; internal code: FIS-VED-2017-01; study code: no. EudraCT: 2018-000497-30) and authorized by the Spanish Agency for Medicines and Medical Devices (AEMPS). Data availability. Data generated by this study are available in the Supporting Data Values file or upon request to the corresponding author. However, due to the sensitivity of the data and patient confidentiality, individual participant data will not be made available. Author contributions All authors reviewed and approved the submitted version of the manuscript. MRJL and CGC contributed equally to this work — we decided to list the PhD first and the PhD student second. LFLC, PV, NE, and CRO recruited the participants and provided PLWH blood samples. IRJ, AJCB, and RM supervised the clinical trial. SS and MFA performed the biopsies and provided PLWH GIT samples. ERM, MRJL, and CGC designed the experiments. MRJL, CGC, CG, IR, GG, JGSH, RRB, FG, MICS, IG, and AIAR performed the experiments. CB, IM, and BM provided data from the historical control group. MRJL, CGC, and ERM 17 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 analyzed and interpreted the data and wrote the manuscript. KN, CB, IM, BM, JV, SB, APG, XY, and ML reviewed and contributed to manuscript discussion. ERM conceived the idea, coordinated the project, and acquired funding for the study. Acknowledgments This study would not have been possible without the collaboration of all the participants, medical and nursing staff, and data managers who have taken part in this project. We are grateful to the Virgen del Rocío University Hospital and especially to the Phase I/II Clinical Trials Unit for assistance in the execution of this study. We also are grateful to Carmen Rodríguez and Jorge del Romero from Sandoval Center (Madrid, Spain) for their logistical support. This work was supported by the Instituto de Salud Carlos III (Fondo Europeo de Desarrollo Regional [FEDER], “a way to make Europe,” research contracts FI17/00186 to MRJL, FI19/00083 to CGC, and research projects PI18/01532, PI19/01127, and PI22/01796), Conserjería de Economía, Conocimiento, Empresas y Universidad, Junta de Andalucía (research projects P20/00906), Consejería de Salud y Familias, Junta de Andalucía/Programa Operativo Fondo Social Europeo de Andalucía 2014–2020, senior researcher contract (RH-0019-2021 to KN), and the Red Temática de Investigación Cooperativa en SIDA (RD16/0025/0020 to ERM), which is included in the Acción Estratégica en Salud, Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica, 2008–2011, and 2013–2016, Instituto de Salud Carlos III. ERM was supported by the Spanish National Research Council (CSIC). Address correspondence to: Ezequiel Ruiz-Mateos Carmona, Laboratory of Immunovirology (Lab 211), Institute of Biomedicine of Seville (IBIS), Virgen del Rocío University Hospital, Avda. Manuel Siurot s/n, PC 41013 Seville, Spain. Email: [email protected]. 1. Finzi D, et al. Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy. Science. 1997;278(5341):1295–1300. 2. Martin HA, et al. New assay reveals vast excess of defective over intact HIV-1 transcripts in antiretroviral therapy-suppressed individuals. J Virol. 2022;96(24):e0160522. 3. Richman DD, et al. The challenge of finding a cure for HIV infection. Science. 2009;323(5919):1304–1307. 4. Chun TW, et al. Presence of an inducible HIV-1 latent reservoir during highly active antiretroviral therapy. Proc Natl Acad Sci U S A. 1997;94(24):13193–13197. 5. Siliciano JD, et al. Long-term follow-up studies confirm the stability of the latent reservoir for HIV-1 in resting CD4+ T cells. Nat Med. 2003;9(6):727–728. 6. Montaner JSG, et al. Rebound of plasma HIV viral load following prolonged suppression with combination therapy. AIDS. 1998;12(11):1398–1399. 7. Pernas M, et al. Factors leading to the loss of natural elite control of HIV-1 infection. J Virol. 2018;92(5):e01805. 8. Mehandru S, Dandekar S. Role of the gastrointestinal tract in establishing infection in primates and humans. Curr Opin HIV AIDS. 2008;3(1):22–27. 9. Cicala C, et al. The integrin α4β7 forms a complex with cell-surface CD4 and defines a T-cell subset that is highly susceptible to infection by HIV-1. Proc Natl Acad Sci U S A. 2009;106(49):20877–20882. 10. Erle DJ, et al. Expression and function of the MAdCAM-1 receptor, integrin alpha 4 beta 7, on human leukocytes. J Immunol. 1994;153(2):517–528. 11. Guzzo C, et al. Virion incorporation of integrin α4β7 facilitates HIV-1 infection and intestinal homing. Sci Immunol. 2017;2(11):1. 12. Arthos J, et al. HIV-1 envelope protein binds to and signals through integrin α4β7, the gut mucosal homing receptor for peripheral T cells. Nat Immunol. 2008;9(3):301–309. 13. Kader M, et al. Alpha4(+)beta7(hi)CD4(+) memory T cells harbor most Th-17 cells and are preferentially infected during acute SIV infection. Mucosal Immunol. 2009;2(5):439–449. 14. Sivro A, et al. Integrin α4β7 expression on systemic CD4+ T cells predicts higher rates of HIV acquisition and disease progression. Sci Transl Med. 2018;10(425):eaam6354. 15. Martinelli E, et al. The frequency of α4β7(high) memory CD4+ T cells correlates with susceptibility to rectal simian immunodeficiency virus infection. J Acquir Immune Defic Syndr. 2013;64(4):325–331. 16. Byrareddy SN, et al. Species-specific differences in the expression and regulation of α4β7 integrin in various nonhuman primates. J Immunol. 2015;194(12):5968–5979. 17. Ansari AA, et al. Blocking of α4β7 gut-homing integrin during acute infection leads to decreased plasma and gastrointestinal tissue viral loads in simian immunodeficiency virus-infected rhesus macaques. J Immunol. 2011;186(2):1044–1059. 18. Byrareddy SN, et al. Targeting α4β7 integrin reduces mucosal transmission of simian immunodeficiency virus and protects gut-associated lymphoid tissue from infection. Nat Med. 2014;20(12):1397–1400. 19. Byrareddy SN, et al. Sustained virologic control in SIV+ macaques after antiretroviral and α4β7 antibody therapy. Science. 2016;354(6309):197–202. 18 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 20. Feagan BG, et al. Vedolizumab as induction and maintenance therapy for ulcerative colitis. N Engl J Med. 2013;369(8):699–710. 21. Sandborn WJ, et al. Vedolizumab as induction and maintenance therapy for Crohn’s disease. N Engl J Med. 2013;369(8):711–721. 22. Soler D, et al. The binding specificity and selective antagonism of vedolizumab, an anti-α4β7 integrin therapeutic antibody in development for inflammatory bowel diseases. J Pharmacol Exp Ther. 2009;330(3):864–875. 23. Sneller MC, et al. An open-label phase 1 clinical trial of the anti-α4β7 monoclonal antibody vedolizumab in HIV-infected individuals. Sci Transl Med. 2019;11(509):eaax3447. 24. Iwamoto N, et al. Blocking α4β7 integrin binding to SIV does not improve virologic control. Science. 2019;365(6457):1033–1036. 25. Di Mascio M, et al. Evaluation of an antibody to α4β7 in the control of SIVmac239-nef-stop infection. Science. 2019;365(6457):1025–1029. 26. Abbink P, et al. Lack of therapeutic efficacy of an antibody to α4β7 in SIVmac251-infected rhesus macaques. Science. 2019;365(6457):1029–1033. 27. Fromentin R, et al. CD4+ T Cells Expressing PD-1, TIGIT and LAG-3 Contribute to HIV Persistence during ART. PLoS Pathog. 2016;12(7):e1005761. 28. Bailón L, et al. Safety, immunogenicity and effect on viral rebound of HTI vaccines in early treated HIV-1 infection: a randomized, placebo-controlled phase 1 trial. Nat Med. 2022;28(12):2611–2621. 29. Fellay J, et al. A whole-genome association study of major determinants for host control of HIV-1. Science. 2007;317(5840):944–947. 30. Pereyra F. The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science. 2010;330(6010):1551–1557. 31. Martin AR, et al. The association of α4β7 expression with HIV acquisition and disease progression in people who inject drugs and men who have sex with men: Case control studies. EBioMedicine. 2020;62(1–7):103102. 32. Wang X, et al. Monitoring alpha4beta7 integrin expression on circulating CD4+ T cells as a surrogate marker for tracking intestinal CD4+ T-cell loss in SIV infection. Mucosal Immunol. 2009;2(6):518–526. 33. Cicala C, et al. Role of T-cell trafficking in the pathogenesis of HIV disease. Curr Opin HIV AIDS. 2019;14(2):115–120. 34. Sidell N, Kane MA. Actions of retinoic acid in the pathophysiology of HIV infection. Nutrients. 2022;14(8):1611. 35. Li JZ, et al. The size of the expressed HIV reservoir predicts timing of viral rebound after treatment interruption. AIDS. 2016;30(3):343–353. 36. Martin GE, et al. Post-treatment control or treated controllers? Viral remission in treated and untreated primary HIV infection. AIDS. 2017;31(4):477–484. 37. Massanella M, et al. Long-term effects of early antiretroviral initiation on HIV reservoir markers: a longitudinal analysis of the MERLIN clinical study. Lancet Microbe. 2021;2(5):e198–e209. 38. Besson GJ, et al. HIV-1 DNA decay dynamics in blood during more than a decade of suppressive antiretroviral therapy. Clin Infect Dis. 2014;59(9):1312–1321. 39. Viard JP, et al. Impact of 5 years of maximally successful highly active antiretroviral therapy on CD4 cell count and HIV-1 DNA level. AIDS. 2004;18(1):45–49. 40. Tincati C, et al. Early initiation of highly active antiretroviral therapy fails to reverse immunovirological abnormalities in gut-as- sociated lymphoid tissue induved by acute HIV infection. Antivir Ther. 2009;14(3):321–330. 41. Chintanaphol M, et al. Feasibility and safety of research sigmoid colon biopsy in a cohort of Thai men who have sex with men with acute HIV-1. J Virus Erad. 2020;6(1):7–10. 42. Honeycutt JB, et al. Macrophages sustain HIV replication in vivo independently of T cells. J Clin Invest. 2016;126(4):1353–1366. 43. Thornhill JP, et al. Simplified two-drug antiretroviral HIV treatment: novel data and expected impact. AIDS. 2019;33(14):2266–2268. 44. Fisher K, et al. Plasma-derived HIV-1 Virions contain considerable levels of defective genomes. J Virol. 2022;96(6):e0201121. 45. Joag VR, et al. Identification of preferential CD4+ T-cell targets for HIV infection in the cervix. Mucosal Immunol. 2016;9(1):1–12. 46. Cicala C, et al. HIV-1 envelope, integrins and co-receptor use in mucosal transmission of HIV. J Transl Med. 2011;9(suppl 1):S2. 47. Dufour C, et al. Phenotypic characterization of single CD4+ T cells harboring genetically intact and inducible HIV genomes. Nat Commun. 2023;14(1):1115. 48. Rindi LV, et al. Drug-induced progressive multifocal leukoencephalopathy (PML): a systematic review and meta-analysis. Drug Saf. 2024;47(4):333–354. 49. Loftus EV. Long-term safety of vedolizumab for inflammatory bowel disease. Aliment Pharmacol Ther. 2020;52(8):1353–1365. 50. Pereira LE, et al. Preliminary in vivo efficacy studies of a recombinant rhesus anti-alpha(4)beta(7) monoclonal antibody. Cell Immunol. 2009;259(2):165–176. 51. Frank I, et al. Blocking α4β7 integrin delays viral rebound in SHIVSF162P3-infected macaques treated with anti-HIV broadly neutralizing antibodies. Sci Transl Med. 2021;13(607):eabf7201. 52. Sun Y, Xue J. Expression profile and biological role of immune checkpoints in disease progression of HIV/SIV infection. Viruses. 2022;14(3):1. 53. Hurst J, et al. Immunological biomarkers predict HIV-1 viral rebound after treatment interruption. Nat Commun. 2015;6(1-9):8495. 54. Imamichia H, et al. Defective HIV-1 proviruses produce novel protein-coding RNA species in HIV-infected patients on combination antiretroviral therapy. Proc Natl Acad Sci U S A. 2016;113(31):8783–8788. 55. Goode D, et al. HSV-2-driven increase in the expression of α4β7 correlates with increased susceptibility to vaginal SHIV(S- F162P3) infection. PLoS Pathog. 2014;10(12):e1004567. 56. Perreau M, et al. Follicular helper T cells serve as the major CD4 T cell compartment for HIV-1 infection, replication, and production. J Exp Med. 2013;210(1):143–156. 57. Renault C, et al. Th17 CD4+ T-cell as a preferential target for HIV reservoirs. Front Immunol. 2022;13:822576. 58. Kanwar B, et al. Th17 and regulatory T cells: implications for AIDS pathogenesis. Curr Opin HIV AIDS. 2010;5(2):151–157. 59. Iwata M, et al. Retinoic acid imprints gut-homing specificity on T cells. Immunity. 2004;21(4):527–538. 19 CLINICAL MEDICINE JCI Insight 2024;9(16):e182312 https://doi.org/10.1172/jci.insight.182312 60. Ross AC. Vitamin A and retinoic acid in T cell-related immunity. Am J Clin Nutr. 2012;96(5):1166S–1172S. 61. Mora JR, et al. Vitamin effects on the immune system: vitamins A and D take centre stage. Nat Rev Immunol. 2008;8(9):685–698. 62. Nawaz F, et al. MAdCAM costimulation through Integrin-α4β7 promotes HIV replication. Mucosal Immunol. 2018;11(5):1342–1351. 63. Kaiser P, et al. Stimulating the RIG-I pathway to kill cells in the latent HIV reservoir following viral reactivation. Nat Med. 2016;22(7):807–811. 64. Uzzan M, et al. Anti-α4β7 therapy targets lymphoid aggregates in the gastrointestinal tract of HIV-1-infected individuals. Sci Transl Med. 2018;10(461):eaau4711. 65. Mowat A. The anatomical basis of intestinal immunity. Immunol Rev. 1997;156:145–166. 66. Gundersen TE, et al. Quantitative high-throughput determination of endogenous retinoids in human plasma using triple-stage liquid chromatography/tandem mass spectrometry. Rapid Commun Mass Spectrom. 2007;21(7):1176–1186. 67. Saha A, et al. High throughput LC-MS/MS method for simultaneous estimation of 9-cis-retinoic acid and its metabolite 4-Oxo-9-cis-retinoic acid in human plasma and its application to a bioequivalence study. J Anal Bioanal Tech. 2015;S13:001. 68. Arnold SLM, et al. A sensitive and specific method for measurement of multiple retinoids in human serum with UHPLC-MS/ MS. J Lipid Res. 2012;53(3):587–598. 69. de Pablo-Bernal RS, et al. Modulation of monocyte activation and function during direct antiviral agent treatment in patients coinfected with HIV and hepatitis C virus. Antimicrob Agents Chemother. 2020;64(9):1. 70. Lee GQ, et al. HIV-1 DNA sequence diversity and evolution during acute subtype C infection. Nat Commun. 2019;10(1):2737. 71. RosRose PP, Korber BT. Detecting hypermutations in viral sequences with an emphasis on G --> A hypermutation. Bioinformatics. 2000;16(4):400–401. 72. Dominguez-Molina B, et al. Immune correlates of natural HIV elite control and simultaneous HCV clearance-supercontrollers. Front Immunol. 2018;9:2897.