HIV-1 Genetic Diversity and Drug Resistance Mutations Among Treatment-Naive Adult Patients in Suriname

Checklist for studies of HIV drug resistance prevalence or incidence: rationale and recommended use

HIV drug resistance (HIVDR) is a major challenge to the effectiveness of antiretroviral therapy. Global efforts in addressing HIVDR require clear, transparent, and replicable reporting in HIVDR studies. We describe the rationale and recommended use of a checklist that should be included in reports of HIVDR incidence and prevalence. After preliminary consultations with experts on HIVDR and establishing the need for guidance on HIVDR reporting, we used a sequential, explanatory, mixed methods approach to create the checklist; together with the accompanying articles, the checklist was reviewed by the authors and validated externally. The checklist for studies on HIVDR prevalence or incidence (CEDRIC-HIV) includes 15 recommended items that would enhance transparency and facilitate interpretation, comparability, and replicability of HIVDR studies. CEDRIC-HIV will help authors of HIVDR studies prepare research reports and assist reviewers and editors in assessments of completeness of reporting. The checklist will also facilitate statistical pooling and interpretation of HIVDR data.

Sexually transmitted infections on the border between Suriname and French Guiana: A scoping review

Purpose

The Maroni basin –delineating the border between Suriname and French Guiana— presents sociocultural, geographical and economic circumstances that have been conducive to the circulation of sexually transmitted infections and to delays in diagnosis and care. Given the scarcity of published data, we aimed to describe different sexually transmitted infections along the Maroni and to gain a broader understanding of the epidemiologic situation.

Methods

We conducted a scoping review of the efforts to approach the problem of sexually transmitted infections in this complex border area. Temporal trends were plotted and crude numbers were divided by local population numbers.

Results

For HIV, despite increasing testing efforts, most patients still present at the advanced HIV stage (median CD4 count at diagnosis is < 20 per mm³), and 25% of patients in Saint Laurent du Maroni were lost to follow-up within 6 years. However, progress on both sides has led to a decline in AIDS cases and mortality. Despite a rapid increase in the 1990’s along the Maroni, the current HIV prevalence seemed lower (0.52%) in the rural villages than in coastal urban centers (> 1%). High risk HPV infection prevalence among women reaches 23.3%. The incidence of gonorrhea was 4.2 per 1,000 population aged 15-59. For chlamydiasis it was 3.4 per 1,000 population aged 15-59. For syphilis, the incidence was 2.5 per 1,000 population aged 15-59. Gonorrhea, chlamydiasis, hepatitis B detection increased over time with greater testing efforts and new diagnostic tests. Since the COVID-19 epidemic, congenital syphilis has dramatically increased in Saint Laurent du Maroni reaching 808 per 100,000 live births.

Conclusion

Sexually transmitted infections seemed more prevalent in Saint Laurent du Maroni –the sole urban center—than in the remote villages along the Maroni. The syndromic approach and the heterogeneity of diagnostic platforms presumably overlook most infections in the region. Therefore, a concerted approach and a shared diagnostic upgrade with molecular diagnosis and rapid diagnostic tests seem necessary to reduce the burden of sexually transmitted infections on both sides of the Maroni. Congenital syphilis resulting from COVID-19 disruption of health services requires urgent attention.

First Assessment of Acquired HIV-1 Drug Resistance and Mutation Patterns in Suriname

HIV drug resistance testing is fundamental in clinical patient management, but data on HIV-1 drug-resistant mutations (DRMs) is scarce in the Caribbean and in Suriname limited to one survey on transmitted resistance. The aim of this study was to address this gap, to gain insight in acquired HIV drug resistance (ADR) prevalence and mutation patterns, and to improve HIV-1 treatment outcome of people living with HIV (PLHIV) in Suriname. A prospective cross-sectional study was conducted from July 2018 through January 2019 among treatment-experienced PLHIV (n = 72), with either treatment failure or antiretroviral therapy restart. Genotypic drug resistance testing was performed and DRM impact on drug effectiveness was examined. Genotypic drug resistance testing revealed 97.2% HIV-1 subtype B, 2.8% B/D recombinants and a ADR prevalence of 63.2% in treatment failure patients, with a predominance of nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations. The most common DRMs were M184V (23.6%) and K103N (18.8%). A high level of non-DRM polymorphisms was observed in both the reverse transcriptase (RT) and protease (PR) gene. Interesting deviations from the existing mutation datasets were noted at position E248 and R83 of the RT gene and L63 and V77 in the PR gene. Full susceptibility to all examined drugs was 54.2%, while high-level drug resistance was estimated at 37.5%, which seems promising for treatment outcomes for PLHIV in Suriname, although cross-resistance to next-generation NNRTIs was already estimated for nearly a quarter of the patients. The meager 2.9% of PR DRMs rendered protease inhibitors as an effective rescue HIV-1 treatment.

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning

A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has become an ideal target for the development of anti-HIV drugs. A total of 1785 potential HIV-1 IN inhibitors were collected from the databases of ChEMBL, Binding Database, DrugBank, and PubMed, as well as from 40 references. The database was divided into the training set and test set by random sampling. By exploring the correlation between molecular descriptors and inhibitory activity, it is found that the classification and specific activity data of inhibitors can be more accurately predicted by the combination of molecular descriptors and molecular fingerprints. The calculation of molecular fingerprint descriptor provides the additional substructure information to improve the prediction ability. Based on the training set, two machine learning methods, the recursive partition (RP) and naive Bayes (NB) models, were used to build the classifiers of HIV-1 IN inhibitors. Through the test set verification, the RP technique accurately predicted 82.5% inhibitors and 86.3% noninhibitors. The NB model predicted 88.3% inhibitors and 87.2% noninhibitors with correlation coefficient of 85.2%. The results show that the prediction performance of NB model is slightly better than that of RP, and the key molecular segments are also obtained. Additionally, CoMFA and CoMSIA models with good activity prediction ability both were constructed by exploring the structure-activity relationship, which is helpful for the design and optimization of HIV-1 IN inhibitors.

The HIV-1 Subtype B Epidemic in French Guiana and Suriname Is Driven by Ongoing Transmissions of Pandemic and Non-pandemic Lineages

The HIV-1 subtype B epidemic in French Guiana and Suriname is characterized by the co-circulation of the globally disseminated “B_PANDEMIC” lineage and of non-pandemic subtype B lineages of Caribbean origin (B_CAR). To reconstruct the spatiotemporal pattern of spread of those viral lineages circulating in these two countries, a total of 361 HIV-1 subtype B pol sequences recovered from treatment-naive adult patients from French Guiana and Suriname between 2006 and 2012 were combined with B_PANDEMIC and B_CAR reference sequences. Major Guianese/Surinamese B_PANDEMIC and B_CAR lineages were identified by Maximum Likelihood phylogenetic analysis and the spatiotemporal and demographic parameters estimated using a Bayesian coalescent-based method. We detected four B_CAR and three B_PANDEMIC transmission chains of large size that together comprise most pandemic and non-pandemic subtype B sequences from French Guiana (≥52%) and Suriname (≥70%) here analyzed. These major lineages were probably introduced into French Guiana and Suriname from the Caribbean (B_CAR) and North/South America (B_PANDEMIC) between the middle 1970s and the late 1980s and spread among populations from both countries with roughly comparable demographic growth rates. We detected a significant trend for higher viral loads and higher proportion of homosexual/bisexual men among subjects infected with B_PANDEMIC relative to B_CAR strains in French Guiana. These results show that the HIV subtype B epidemic in French Guiana and Suriname has been driven by multiple active B_CAR and B_PANDEMIC transmission chains that arose since the middle 1970s onward and operate in both countries simultaneously. Although no significant differences in the epidemic potential of major B_CAR and B_PANDEMIC lineages were observed, relevant associations between the infecting subtype B lineage and epidemiological and clinical characteristics were detected in French Guiana.