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Introduction: Few data are currently available on the nonnucleoside reverse transcriptase (RT) inhibitors (NNRTI) resistance mutations selected in persons living with HIV-1 (PLWH) who develop virological failure while receiving rilpivirine (RPV). Methods: We analyzed pooled HIV-1 RT genotypic data from 280 PLWH in the multicenter EuResist database and 115 PLWH in the Stanford HIV Drug Resistance Database (HIVDB) who received RPV as their only NNRTI. Results: Among the 395 PLWH receiving RPV, 180 (45.6%) had one or more NNRTI-associated DRMs. Overall, 44 NNRTI-associated DRMs were identified, including 26 that occurred in two or more PLWHs. Seven mutations had a prevalence ≥10% among the 180 PLWH with one or more NNRTI-associated DRM: E138K (32.2%), V90I (25.0%), K101E (17.8%), Y181C (17.2%), E138A (13.9%), H221Y (12.2%), and K103N (10.6%). Y181C was significantly more likely to co-occur with K101E, V179F, H221Y, and M230L. Ten novel non-polymorphic mutations at known NNRTI-associated mutation positions were also identified, usually in just one PLWH: L100F, V108A, T139I, P225S, M230V, Y232C, and T240A/I/M/S. Conclusions: Our analysis extends the spectrum of mutations emerging in PLWH receiving RPV. Additional phenotypic characterization of RPV-selected mutations is necessary to better understand their biological and possible clinical significance. [ABSTRACT FROM AUTHOR]

Post COVID-19 condition (PCC) is defined as ongoing symptoms at ≥1 month after acute COVID-19. We investigated the risk of PCC in an international cohort according to viral variants. We included 7699 hospitalized patients in six centers (January 2020–June 2023); a subset of participants with ≥1 visit over the year after clinical recovery were analyzed. Variants were observed or estimated using Global Data Science Initiative (GISAID) data. Because patients returning for a post COVID-19 visit may have a higher PCC risk, and because the variant could be associated with the probability of returning, we used weighted logistic regressions. We estimated the proportion of the effect of wild-type (WT) virus vs. Omicron on PCC, which was mediated by Intensive Care Unit (ICU) admission, through a mediation analysis. In total, 1317 patients returned for a post COVID visit at a median of 2.6 (IQR 1.84–3.97) months after clinical recovery. WT was present in 69.6% of participants, followed by the Alpha (14.4%), Delta (8.9%), Gamma (3.9%) and Omicron strains (3.3%). Among patients with PCC, the most common manifestations were fatigue (51.7%), brain fog (32.7%) and respiratory symptoms (37.2%). Omicron vs. WT was associated with a reduced risk of PCC and PCC clusters; conversely, we observed a higher risk with the Delta and Alpha variants vs. WT. In total, 42% of the WT effect vs. Omicron on PCC risk appeared to be mediated by ICU admission. A reduced PCC risk was observed after Omicron infection, suggesting a possible reduction in the PCC burden over time. A non-negligible proportion of the variant effect on PCC risk seems mediated by increased disease severity during the acute disease. [ABSTRACT FROM AUTHOR]

Motivation In predicting HIV therapy outcomes, a critical clinical question is whether using historical information can enhance predictive capabilities compared with current or latest available data analysis. This study analyses whether historical knowledge, which includes viral mutations detected in all genotypic tests before therapy, their temporal occurrence, and concomitant viral load measurements, can bring improvements. We introduce a method to weigh mutations, considering the previously enumerated factors and the reference mutation-drug Stanford resistance tables. We compare a model encompassing history (H) with one not using this information (NH). Results The H-model demonstrates superior discriminative ability, with a higher ROC-AUC score (76.34%) than the NH-model (74.98%). Wilcoxon test results confirm significant improvement of predictive accuracy for treatment outcomes through incorporating historical information. The increased performance of the H-model might be attributed to its consideration of latent HIV reservoirs, probably obtained when leveraging historical information. The findings emphasize the importance of temporal dynamics in acquiring mutations. However, our result also shows that prediction accuracy remains relatively high even when no historical information is available. Availability and implementation This analysis was conducted using the Euresist Integrated DataBase (EIDB). For further validation, we encourage reproducing this study with the latest release of the EIDB, which can be accessed upon request through the Euresist Network. [ABSTRACT FROM AUTHOR]

Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multidrug resistance, however, is a rare event in modern HIV treatment, but can be life‐threatening, particular in patients with very long therapy histories and in areas with limited access to novel drugs. To understand the evolution of multidrug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time. We hypothesize that the accumulation of resistance mutations is not acquired simultaneously and randomly across viral genotypes but rather tends to follow a predetermined order. The knowledge of this order might help to elucidate potential mechanisms of multidrug resistance. Our evolutionary model shows an almost monotonic increase of resistance with each acquired mutation, including less well‐known nucleoside reverse transcriptase (RT) inhibitor‐related mutations like K223Q, L228H, and Q242H. Mutations within the integrase (IN) (T97A, E138A/K G140S, Q148H, N155H) indicate high probability of multidrug resistance. Hence, these IN mutations also tend to be observed together with mutations in the protease (PR) and RT. We followed up with an analysis of the mutation‐specific error rates of our model given the data. We identified several mutations with unusual rates (PR: M41L, L33F, IN: G140S). This could imply the existence of previously unknown virus variants in the viral quasispecies. In conclusion, our bioinformatics model supports the analysis and understanding of multidrug resistance. [ABSTRACT FROM AUTHOR]

Objectives: To explore the effectiveness and durability of integrase strand transfer inhibitor (INSTI)‐based regimens in pre‐treated subjects. Methods: Treatment‐experienced individuals starting an INSTI‐based regimen during 2012–2019 were selected from the INTEGRATE collaborative study. The time to virological failure [VF: one measurement of viral load (VL) ≥ 1000 copies/mL or two ≥ 50 copies/ml or one VL measurement ≥ 50 copies/mL followed by treatment change] and to INSTI discontinuation were evaluated. Results: Of 13 560 treatments analysed, 4284 were from INSTI‐naïve, non‐viraemic (IN‐NV) individuals, 1465 were from INSTI‐naïve, viraemic (IN‐V) individuals, 6016 were from INSTI‐experienced, non‐viraemic (IE‐NV) individuals and 1795 were from INSTI‐experienced, viraemic (IE‐V) individuals. Major INSTI drug resistance mutations (DRMs) were previously detected in 4/519 (0.8%) IN‐NV, 3/394 (0.8%) IN‐V, 7/1510 (0.5%) IE‐NV and 25/935 (2.7%) IE‐V individuals. The 1‐year estimated probabilities of VF were 3.1% [95% confidence interval (CI): 2.5–3.8] in IN‐NV, 18.4% (95% CI: 15.8–21.2) in IN‐V, 4.2% (95% CI: 3.6–4.9) in IE‐NV and 23.9% (95% CI: 20.9–26.9) in IE‐V subjects. The 1‐year estimated probabilities of INSTI discontinuation were 12.1% (95% CI: 11.1–13.0) in IN‐NV, 19.6% (95% CI: 17.5–21.6) in IN‐V, 10.8% (95% CI: 10.0–11.6) in IE‐NV and 21.7% (95% CI: 19.7–23.5) in IE‐V subjects. Conclusions: Both VF and INSTI discontinuation occur at substantial rates in viraemic subjects. Detection of DRMs in a proportion of INSTI‐experienced individuals makes INSTI resistance testing mandatory after failure. [ABSTRACT FROM AUTHOR]

Aim of this study was to assess the predictors of virological failure (VF) among patients living with HIV (PLWHIV) switching from an effective first-line antiretroviral therapy (ART) regimen, and to evaluate the emergence of resistance-associated mutations. All adult patients enrolled in the Antiviral Response Cohort Analysis cohort who started ART after 2010, with at least 6 months of virological suppression (VS) before ART switch and with an available genotypic resistance test (GRT) at baseline were included. Thirty-two patients out of the 607 PLWHIV included (5.3%) experienced VF after a median of 11 months from ART switch. Younger age (adjusted Hazard Ratio [aHR] 0.96, 95% confidence interval [CI] 0.92–0.99, p = .023), being male who have sex with male (aHR 0.15, 95% CI 0.03–0.69, p = .014), and longer time from VS to ART switch (aHR 0.97, 95% CI 0.95–1.00, p = .021) resulted protective toward VF, while receiving a first-line regimen containing a backbone other than ABC/3TC or TXF/FTC (aHR 3.61, 95% CI 1.00–13.1, p = .050) and a boosted protease inhibitor as anchor drug (aHR 3.34, 95% CI 1.20–9.28, p = .021) were associated with higher risk of VF. GRT at the moment of VF was available only for 13 patients (40.6%). ART switch in patients with stable control of HIV infection is a safe practice, even if particular attention should be paid in certain cases of patients switching from regimens containing low-performance backbones or protease inhibitors. [ABSTRACT FROM AUTHOR]