Cohort Profile: A European Multidisciplinary Network for the Fight against HIV Drug Resistance (EuResist Network)

: The EuResist cohort was established in 2006 with the purpose of developing a clinical decision-support tool predicting the most effective antiretroviral therapy (ART) for persons living with HIV (PLWH), based on their clinical and virological data. Further to continuous extensive data collection from several European countries, the EuResist cohort later widened its activity to the more general area of antiretroviral treatment resistance with a focus on virus evolution. The EuResist cohort has retrospectively enrolled PLWH, both treatment-naïve and treatment-experienced, under clinical follow-up from 1998, in nine national cohorts across Europe and beyond, and this article is an overview of its achievement. A clinically oriented treatment-response prediction system was released and made available online in 2008. Clinical and virological data have been collected from more than one hundred thousand PLWH, allowing for a number of studies on the response to treatment, selection and spread of resistance-associated mutations and the circulation of viral subtypes. Drawing from its interdisciplinary vocation, EuResist will continue to investigate clinical response to antiretroviral treatment against HIV and monitor the development and circulation of HIV drug resistance in clinical settings, along with the development of novel drugs and the introduction of new treatment strategies. The support of artificial intelligence in these activities is essential

Only Slight Impact of Predicted Replicative Capacity for Therapy Response Prediction

BACKGROUND: Replication capacity (RC) of specific HIV isolates is occasionally blamed for unexpected treatment responses. However, the role of viral RC in response to antiretroviral therapy is not yet fully understood. MATERIALS AND METHODS: We developed a method for predicting RC from genotype using support vector machines (SVMs) trained on about 300 genotype-RC pairs. Next, we studied the impact of predicted viral RC (pRC) on the change of viral load (VL) and CD4(+) T-cell count (CD4) during the course of therapy on about 3,000 treatment change episodes (TCEs) extracted from the EuResist integrated database. Specifically, linear regression models using either treatment activity scores (TAS), the drug combination, or pRC or any combination of these covariates were trained to predict change in VL and CD4, respectively. RESULTS: The SVM models achieved a Spearman correlation (rho) of 0.54 between measured RC and pRC. The prediction of change in VL (CD4) was best at 180 (360) days, reaching a correlation of rho = 0.45 (rho = 0.27). In general, pRC was inversely correlated to drug resistance at treatment start (on average rho = -0.38). Inclusion of pRC in the linear regression models significantly improved prediction of virological response to treatment based either on the drug combination or on the TAS (t-test; p-values range from 0.0247 to 4 10(-6)) but not for the model using both TAS and drug combination. For predicting the change in CD4 the improvement derived from inclusion of pRC was not significant. CONCLUSION: Viral RC could be predicted from genotype with moderate accuracy and could slightly improve prediction of virological treatment response. However, the observed improvement could simply be a consequence of the significant correlation between pRC and drug resistance

A Comparison Between the Populations of Late Presenters and Non-late Presenters

Funding Information: We want to thank Frank Tang, Bin Lin, Mike Cohen and the rest of the Google speech team for their insightful discussions and inputs. Publisher Copyright: Copyright © 2022 Miranda, Pingarilho, Pimentel, Martins, Kaiser, Seguin-Devaux, Paredes, Zazzi, Incardona and Abecasis.Background: The increased use of antiretroviral therapy (ART) has decreased mortality and morbidity of HIV-1 infected people but increasing levels of HIV drug resistance threatens the success of ART regimens. Conversely, late presentation can impact treatment outcomes, health costs, and potential transmission of HIV. Objective: To describe the patterns of transmitted drug resistance (TDR) and acquired drug resistance (ADR) in HIV-1 infected patients followed in Europe, to compare its patterns in late presenters (LP) vs non-late presenters (NLP), and to analyze the most prevalent drug resistance mutations among HIV-1 subtypes. Methods: Our study included clinical, socio-demographic, and genotypic information from 26,973 HIV-1 infected patients from the EuResist Integrated Database (EIDB) between 1981 and 2019. Results: Among the 26,973 HIV-1 infected patients in the analysis, 11,581 (42.9%) were ART-naïve patients and 15,392 (57.1%) were ART-experienced. The median age was 37 (IQR: 27.0–45.0) years old and 72.6% were males. The main transmission route was through heterosexual contact (34.9%) and 81.7% of patients originated from Western Europe. 71.9% of patients were infected by subtype B and 54.8% of patients were classified as LP. The overall prevalence of TDR was 12.8% and presented an overall decreasing trend (p for trend < 0.001), the ADR prevalence was 68.5% also with a decreasing trend (p for trend < 0.001). For LP and NLP, the TDR prevalence was 12.3 and 12.6%, respectively, while for ADR, 69.9 and 68.2%, respectively. The most prevalent TDR drug resistance mutations, in both LP and NLP, were K103N/S, T215rev, T215FY, M184I/V, M41I/L, M46I/L, and L90M. Conclusion: Our study showed that the overall TDR (12.8%) and ADR (68.5%) presented decreasing trends during the study time period. For LP, the overall TDR was slightly lower than for NLP (12.3 vs 12.6%, respectively); while this pattern was opposite for ADR (LP slightly higher than NLP). We suggest that these differences, in the case of TDR, can be related to the dynamics of fixation of drug resistance mutations; and in the case of ADR with the more frequent therapeutic failure in LPs.publishersversionpublishe

EuCARE-POSTCOVID Study: a multicentre cohort study on long-term post-COVID-19 manifestations

BACKGROUND: Post-COVID-19 condition refers to persistent or new onset symptoms occurring three months after acute COVID-19, which are unrelated to alternative diagnoses. Symptoms include fatigue, breathlessness, palpitations, pain, concentration difficulties ("brain fog"), sleep disorders, and anxiety/depression. The prevalence of post-COVID-19 condition ranges widely across studies, affecting 10-20% of patients and reaching 50-60% in certain cohorts, while the associated risk factors remain poorly understood. METHODS: This multicentre cohort study, both retrospective and prospective, aims to assess the incidence and risk factors of post-COVID-19 condition in a cohort of recovered patients. Secondary objectives include evaluating the association between circulating SARS-CoV-2 variants and the risk of post-COVID-19 condition, as well as assessing long-term residual organ damage (lung, heart, central nervous system, peripheral nervous system) in relation to patient characteristics and virology (variant and viral load during the acute phase). Participants will include hospitalised and outpatient COVID-19 patients diagnosed between 01/03/2020 and 01/02/2025 from 8 participating centres. A control group will consist of hospitalised patients with respiratory infections other than COVID-19 during the same period. Patients will be followed up at the post-COVID-19 clinic of each centre at 2-3, 6-9, and 12-15 months after clinical recovery. Routine blood exams will be conducted, and patients will complete questionnaires to assess persisting symptoms, fatigue, dyspnoea, quality of life, disability, anxiety and depression, and post-traumatic stress disorders. DISCUSSION: This study aims to understand post-COVID-19 syndrome's incidence and predictors by comparing pandemic waves, utilising retrospective and prospective data. Gender association, especially the potential higher prevalence in females, will be investigated. Symptom tracking via questionnaires and scales will monitor duration and evolution. Questionnaires will also collect data on vaccination, reinfections, and new health issues. Biological samples will enable future studies on post-COVID-19 sequelae mechanisms, including inflammation, immune dysregulation, and viral reservoirs. TRIAL REGISTRATION: This study has been registered with ClinicalTrials.gov under the identifier NCT05531773

Drug resistance testing through remote genotyping and predicted treatment options in human immunodeficiency virus type 1 infected Tanzanian subjects failing first or second line antiretroviral therapy

Antiretroviral therapy (ART) has been successfully introduced in low-middle income countries. However an increasing rate of ART failure with resistant virus is reported. We therefore described the pattern of drug resistance mutations at antiretroviral treatment (ART) failure in a real-life Tanzanian setting using the remote genotyping procedure and thereafter predicted future treatment options using rule-based algorithm and the EuResist bioinformatics predictive engine. According to national guidelines, the default first-line regimen is tenofovir + lamivudine + efavirenz, but variations including nevirapine, stavudine or emtricitabine can be considered. If failure on first-line ART occurs, a combination of two nucleoside reverse transcriptase inhibitors (NRTIs) and boosted lopinavir or atazanavir is recommended

Determinants of HIV-1 Late Presentation in Patients Followed in Europe

To control the Human Immunodeficiency Virus (HIV) pandemic, the World Health Organization (WHO) set the 90-90-90 target to be reached by 2020. One major threat to those goals is late presentation, which is defined as an individual presenting a TCD4+ count lower than 350 cells/mm3 or an AIDS-defining event. The present study aims to identify determinants of late presentation in Europe based on the EuResist database with HIV-1 infected patients followed-up between 1981 and 2019. Our study includes clinical and socio-demographic information from 89,851 HIV-1 infected patients. Statistical analysis was performed using RStudio and SPSS and a Bayesian network was constructed with the WEKA software to analyze the association between all variables. Among 89851 HIV-1 infected patients included in the analysis, the median age was 33 (IQR: 27.0–41.0) years and 74.4% were males. Of those, 28,889 patients (50.4%) were late presenters. Older patients (>56), heterosexuals, patients originated from Africa and patients presenting with log VL >4.1 had a higher probability of being late presenters (p < 0.001). Bayesian networks indicated VL, mode of transmission, age and recentness of infection as variables that were directly associated with LP. This study highlights the major determinants associated with late presentation in Europe. This study helps to direct prevention measures for this population

Evaluation of HIV-1 integrase resistance emergence and evolution in patients treated with integrase inhibitors.

Abstract Objectives We evaluated the emergence of mutations associated to integrase strand transfer inhibitors (INSTI) resistance (INSTI-RMs) and the integrase evolution in HIV-1 infected patients treated with this drug class. Methods Emergence of INSTI-RMs and integrase evolution (estimated as genetic distance between integrase sequences under-INSTI and before-INSTI treatment) were evaluated in 107 INSTI-naive patients (19 drug-naive and 88 drug-experienced) with two plasma genotypic resistance tests available: one before and one under INSTI treatment. A logistic regression analysis was performed to evaluate factors associated with the integrase evolution under INSTI treatment. Results Patients were mainly infected by B subtype (72.0%). 87 patients were treated with raltegravir, 13 with dolutegravir and 7 with elvitegravir. Before INSTI treatment, one patient harboured the major INSTI-RM R263 K, and three patients the accessory INSTI-RMs T97A. Under INSTI treatment, the emergence of ≥1 INSTI-RM was found in 39 (36.4%) patients. The major INSTI-RMs which emerged more frequently were: N155H (17.8%), G140S (8.4%), Y143R (7.5%), Q148H (6.5%), Y143C (4.7%). Concerning integrase evolution, a higher genetic distance was found in patients with ≥1 INSTI-RM compared to those without emergence of resistance (0.024 [0.012-0.036] vs. 0.015 [0.009-0.024], p = 0.018). This higher integrase evolution was significantly associated with a longer duration of HIV-1 infection, a higher number of past regimens and non-B subtypes. Conclusions Our findings confirmed that in INSTI-naive patients, major INSTI-RMs occur very rarely. Under INSTI treatment, selection of drug-resistance follows the typical drug-resistance pathways; a higher evolution characterizes integrase sequences developing drug-resistance compared to those without any resistance

Early versus delayed antiretroviral therapy based on genotypic resistance test: Results from a large retrospective cohort study

Rapid start of antiretroviral therapy (ART) pending genotypic resistance test&nbsp;(GRT) has been recently proposed, but the effectiveness of this strategy is still debated.&nbsp;The rate of virological success (VS), defined as HIV-RNA\u2009&lt;\u200950 copies/ml, with and without GRT was compared in drug-na\uefve individuals enrolled in the Italian ARCA cohort who started ART between 2015 and 2018.&nbsp;521 individuals started ART: 397 without GRT (pre-GRT group) and 124 following GRT (post-GRT group). Overall, 398 (76%) were males and 30 (6%) were diagnosed with AIDS. In the pre-GRT group, baseline CD4+\u2009cell counts were lower (p\u2009&lt;\u20090.001), and viral load was higher (p\u2009&lt;\u20090.001) than in the post-GRT group. The estimated probability of VS in pre-GRT versus post-GRT group was 72.54% (CI95 : 67.78-76.60) versus 66.94% (CI95 : 57.53-74.26) at Week 24&nbsp;and 92.40% (CI95 : 89.26-94.62) versus 92.92% (CI95 : 86.35-96.33) at Week 48, respectively (p\u2009=\u20090.434). At Week 48, VS was less frequent among individuals with baseline CD4+\u2009cell counts &lt;200 versus &gt;500 (90.33% vs. 97.33%), log viral load &lt;5.00&nbsp;versus &gt;5.70 log10 cps/ml (97.17% vs 78.16%;&nbsp;p\u2009&lt;\u20090.001), and those treated with protease inhibitors or non-nucleoside reverse transcriptase inhibitors versus those treated with integrase strand transfer inhibitors (p\u2009&lt;\u20090.001).&nbsp;The rate of VS does not seem to be affected by an early ART initiation pending GRT results, but it could be influenced by the composition of the ART regimen, as well as immuno-virological parameters

Earlier initiation of antiretroviral treatment coincides with an initial control of the HIV-1 sub-subtype F1 outbreak among men-having-sex-with-men in Flanders, Belgium

Human immunodeficiency virus type 1 (HIV-1) non-B subtype infections occurred in Belgium since the 1980s, mainly amongst migrants and heterosexuals, whereas subtype B predominated in men-having-sex-with-men (MSM). In the last decade, the diagnosis of F1 sub-subtype in particular has increased substantially, which prompted us to perform a detailed reconstruction of its epidemiological history. To this purpose, the Belgian AIDS Reference Laboratories collected HIV-1 pol sequences from all sub-subtype F1-infected patients for whom genotypic drug resistance testing was requested as part of routine clinical follow-up. This data was complemented with HIV-1 pol sequences from countries with a high burden of F1 infections or a potential role in the global origin of sub-subtype F1. The molecular epidemiology of the Belgian subtype F1 epidemic was investigated using Bayesian phylogenetic inference and transmission dynamics were characterized based on birth-death models. F1 sequences were retained from 297 patients diagnosed and linked to care in Belgium between 1988 and 2015. Phylogenetic inference indicated that among the 297 Belgian F1 sequences, 191 belonged to a monophyletic group that mainly contained sequences from people likely infected in Belgium (OR 26.67, 95% CI 9.59-74.15), diagnosed in Flanders (OR 7.28, 95% CI 4.23-12.53), diagnosed at a recent stage of infection (OR 7.19, 95% CI 2.88-17.95) or declared to be MSM (OR 34.8, 95% CI 16.0-75.6). Together with a Spanish clade, this Belgian clade was embedded in the genetic diversity of Brazilian subtype F1 strains and most probably emerged after one or only a few migration events from Brazil to the European continent before 2002. The origin of the Belgian outbreak was dated back to 2002 (95% higher posterior density 2000-2004) and birth-death models suggested that its extensive growth had been controlled (Re < 1) by 2012, coinciding with a time period where delay in antiretroviral treatment initiation substantially declined. In conclusion, phylogenetic reconstruction of the Belgian HIV-1 sub-subtype F1 epidemic illustrates the introduction and substantial dissemination of viral strains in a geographically restricted risk group that was most likely controlled by effective treatment as prevention.publishersversionpublishe

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment. In this study, we compared four FLs trained with different sequence populations. Epistatic interactions were learned from three different cross-sectional BNs, trained with sequence from patients experienced with indinavir (BNT), all protease inhibitors (PIs) (BNP) or all PI except indinavir (BND). Scaling the fitness landscape was done using cross-sectional data from drug naïve and indinavir experienced patients (Fcross using BNT) and using longitudinal sequences from patients failing indinavir (FlongT using BNT, FlongP using BNP, FlongD using BND). Evaluation to predict the failing sequence and therapy outcome was performed on independent sequences of patients on indinavir. Parameters included estimated fitness (LogF), the number of generations (GF) or mutations (MF) to reach the fitness threshold (average fitness when a major resistance mutation appeared), the number of generations (GR) or mutations (MR) to reach a major resistance mutation and compared to genotypic susceptibility score (GSS) from Rega and HIVdb algorithms. In pairwise FL comparisons we found significant correlation between fitness values for individual sequences, and this correlation improved after correcting for the subtype. Furthermore, FLs could predict the failing sequence under indinavir-containing combinations. At 12 and 48 weeks, all parameters from all FLs and indinavir GSS (both for Rega and HIVdb) were predictive of therapy outcome, except MR for FlongT and FlongP. The fitness landscapes have similar predictive power for treatment response under indinavir-containing regimen as standard rules-based algorithms, and additionally allow predicting genetic evolution under indinavir selective pressure