Kristel Van Laethem

The international spread of HIV-1 sub-subtype A6 raises concerns due to its association with contraindications for long-acting injectable formulations of cabotegravir (LA-CAB) and rilpivirine (LA-RPV). This study investigated its increasing proportion in Belgium, assessing transmission dynamics and potential migration links. Additionally, genotypic drug resistance in the Belgian HIV-1 sub-subtype A6 population were analyzed and four automatic subtyping tools were compared. A dataset of 4764 HIV-1 protease and reverse transcriptase (RT) sequences from newly diagnosed, treatment-naïve individuals in Belgium (2013–2022) was analyzed. A combination of phylogenetic analysis and online subtyping tools identified 136 sub-subtype A6 sequences. The increase in the proportion of HIV-1 sub-subtype A6 observed in Belgium since 2020 reflects changing transmission patterns, especially among Belgium-born men having sex with men, and cannot be solely linked to the recent influx of Ukrainian migrants. Of these sub-subtype A6 sequences, less than 10% showed LA-CAB + LA-RPV resistance, mainly due to E138A within RT. HIVdb and ANRS reliably assessed resistance in this therapy-naïve cohort, and HIVdb, COMET, and SmartGene^® produced concordant subtyping results. While algorithm choice has little impact at low resistance prevalence, further research is necessary and HIVdb and ANRS remain more suitable for ongoing clinical and research use.

Motivation: The emergence of multidrug class resistance (MDR) in Human Immunodeficiency Virus (HIV) is a rare but significant challenge in antiretroviral therapy (ART). MDR, which may arise from prolonged drug exposure, treatment failures, or transmission of resistant strains, accelerates disease progression and poses particular challenges in resource-limited settings with restricted access to resistance testing and advanced therapies. Early prediction of future MDR development is important to inform therapeutic decisions and mitigate its occurrence. Results: In this study, we employ various machine learning classifiers to predict future resistance to all four major antiretroviral drug classes using features extracted from clinical HIV sequence data. We systematically explore several variations of the problem that differ in the pre-existing resistance level and the temporal gap between sample collection and observed MDR occurrence. Our models show the ability to predict multidrug class resistance even in the most challenging variations, albeit at a reduced accuracy. Feature importance analysis reveals that our models primarily utilize known drug resistance mutations for easier classification tasks, but rely on new mutations for the difficult task of distinguishing four class drug resistance from three class drug resistance. Availability and implementation: All analysis was performed using the Euresist Integrated DataBase (EIDB). Researchers wishing to reproduce, validate or extend these findings can request access to the latest EIDB release via the Euresist Network.

The hepatitis C virus (HCV) epidemic in Western countries is primarily perpetuated by the sub-populations of men who have sex with men (MSM) and people who inject drugs (PWID). Understanding the dynamics of transmission in these communities is crucial for removing the remaining hurdles towards HCV elimination. We sequenced 269 annotated HCV plasma samples using probe enrichment and next-generation sequencing, obtaining 224 open reading frames of HCV (OR497849-OR498072). Maximum likelihood phylogenies were generated on the four most prevalent subtypes in this study (HCV1a, 1b, 3a, 4d) with a subsequent transmission cluster analysis. The highest rate of clustering was observed for HCV4d samples (13/17 (76.47%)). The second highest rate of clustering was observed in HCV1a samples (42/78 (53.85%)) with significant association with HIV-positive MSM. HCV1b and HCV3a had very low rates of clustering (2/83 (2.41%) and (0/29)). The spread of the prevalent subtype HCV1b appears to have been largely curtailed, and we demonstrate the onwards transmission of HCV1a and HCV4d in the HIV-positive MSM population across municipal borders. More systematic data collection and sequencing is needed to allow a better understanding of the HCV transmission among the community of PWID and overcome the remaining barriers for HCV elimination in Belgium.

From early 2020, a high demand for SARS-CoV-2 tests was driven by several testing indications, including asymptomatic cases, resulting in the massive roll-out of PCR assays to combat the pandemic. Considering the dynamic of viral shedding during the course of infection, the demand to report cycle threshold (Ct) values rapidly emerged. As Ct values can be affected by a number of factors, we considered that harmonization of semi-quantitative PCR results across laboratories would avoid potential divergent interpretations, particularly in the absence of clinical or serological information. A proposal to harmonize reporting of test results was drafted by the National Reference Centre (NRC) UZ/KU Leuven, distinguishing four categories of positivity based on RNA copies/mL. Pre-quantified control material was shipped to 124 laboratories with instructions to setup a standard curve to define thresholds per assay. For each assay, the mean Ct value and corresponding standard deviation was calculated per target gene, for the three concentrations (10⁷, 10⁵ and 10³ copies/mL) that determine the classification. The results of 17 assays are summarized. This harmonization effort allowed to ensure that all Belgian laboratories would report positive PCR results in the same semi-quantitative manner to clinicians and to the national database which feeds contact tracing interventions.

Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.

This retrospective study evaluated the reactivity of three HIV confirmatory assays (INNO-LIA®, Geenius^TM and MP) and seven HIV rapid tests, on samples from two different study populations in Belgium. For the early-treated cohort (83 HIV-1 adult patients treated within 3 months after infection), HIV-1 diagnosis was not obtained in at least one confirmatory assay in 12.0% (10/83) and in an HIV rapid test in 31.3% (26/83). Confirmation assay sensitivities ranged 87.5-95.2%, whereas rapid test assay sensitivities ranged 75.9-100%. The time to treatment initiation or the length of time on treatment did not have a statistical influence on the probability to obtain a false negative test result. The fastest reversion was demonstrated after 4 months of treatment. Among the long-term treated cohort (390 HIV-1 patients with ≥9 years of undetectable viral load), false-negative test results were found in at least one HIV confirmatory assay for 2.1% (8/390) of the patients and in a HIV rapid tests for 4.9% (19/390). Confirmation assay sensitivities ranged 98.1-99.5%, whereas rapid test sensitivities ranged 96.2-100%. Longer treatment increased non-reactivity of the HIV rapid tests (p=0.033). Undetectable viral load decreases the sensitivities of HIV diagnostic tests and further monitoring of the performance of serological assays is advised.

HIV-1 pol sequences obtained through baseline drug resistance testing of patients newly diagnosed between 2013 and 2017 were analyzed for genetic similarity. For 927 patients the information on genetic similarity was combined with demographic data and with information on the recency of infection. Overall, 48.3% of the patients were genetically linked with 11.4% belonging to a pair and 36.9% involved in a cluster of ≥3 members. The percentage of early diagnosed (≤4 months after infection) was 28.6%. Patients of Belgian origin were more frequently involved in transmission clusters (49.7% compared to 15.3%) and diagnosed earlier (37.4% compared to 12.2%) than patients of Sub-Saharan African origin. Of the infections reported to be locally acquired, 69.5% were linked (14.1% paired and 55.4% in a cluster). Equal parts of early and late diagnosed individuals (59.9% and 52.4%, respectively) were involved in clusters. The identification of a genetically linked individual for the majority of locally infected patients suggests a high rate of diagnosis in this population. Diagnosis however is often delayed for >4 months after infection increasing the opportunities for onward transmission. Prevention of local infection should focus on earlier diagnosis and protection of the still uninfected members of sexual networks with human immunodeficiency virus (HIV)-infected members.