Determinants of Late HIV Presentation at Ndlavela Health Center in Mozambique.

BACKGROUND: There has been tremendous progress in the fight against HIV worldwide; however, challenges persist in the control of HIV infection. These challenges include the high prevalence of late presenters. There are many disadvantages of late presentation-from reduced survival of the infected person to the risk of transmitting the infection. This research aims to analyze the factors that influence the late presentation in patients attending Ndlavela Health Center in Mozambique. METHODOLOGY: A retrospective cross-sectional study was carried out at Ndlavela Health Center including patients diagnosed with HIV between 2015 and 2020. The European Late Presenter Consensus working group definitions were used, and univariate and multivariate logistic regression were used to identify factors associated with late presentation. RESULTS: In total, 519 participants were included in the study, of which nearly 47% were classified as late presenters. The male gender (AOR = 2.41), clinical suspicious test (AOR = 4.03), initiated by the health professional (AOR = 2.1,9), and fear of stigma (AOR = 2.80) were the main risk factors for late HIV presentation. CONCLUSION: Factors that are potentially determinant for late HIV presentation were identified. Actions are needed to focus on risk factors that are most likely to delay presentation.

Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: performance evaluation of the new REGA version 3 and seven other tools.

BACKGROUND: To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3). METHODOLOGY: HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region. RESULTS: The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01_AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02_AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01_AE and CRF02_AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%). CONCLUSIONS: REGAv3 had an improved performance for subtype B and CRF02_AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences.

Phylogeography of dengue virus serotype 4, Brazil, 2010-2011.

Dengue virus serotype 4 (DENV-4) reemerged in Roraima State, Brazil, 28 years after it was last detected in the country in 1982. To study the origin and evolution of this reemergence, full-length sequences were obtained for 16 DENV-4 isolates from northern (Roraima, Amazonas, Pará States) and northeastern (Bahia State) Brazil during the 2010 and 2011 dengue virus seasons and for an isolate from the 1982 epidemic in Roraima. Spatiotemporal dynamics of DENV-4 introductions in Brazil were applied to envelope genes and full genomes by using Bayesian phylogeographic analyses. An introduction of genotype I into Brazil from Southeast Asia was confirmed, and full genome phylogeographic analyses revealed multiple introductions of DENV-4 genotype II in Brazil, providing evidence for >3 introductions of this genotype within the last decade: 2 from Venezuela to Roraima and 1 from Colombia to Amazonas. The phylogeographic analysis of full genome data has demonstrated the origins of DENV-4 throughout Brazil.

Effect of human immunodeficiency virus type 1 protease inhibitor therapy and subtype on development of resistance in subtypes B and G.

Europe is currently observing a significant rise in non-B subtypes. Consequently, the effect of genetic variability on therapy response or genotypic resistance interpretation algorithms is an emerging concern. The purpose of this study is to investigate the amino acid substitutions selected under drug pressure in the protease of human immunodeficiency virus type 1 (HIV-1) subtypes B and G, and determine if there are any significant differences. We investigated therapy-related and subtype-related substitutions in the protease, considering subtype, overall protease inhibitor treatment and individual drug exposure. Many mutations were significantly related to protease inhibitor (PI) therapy, with mutations exclusive to subtype B or subtype G. Some mutations are at positions related to resistance in both subtypes, but the amino acid substitution is different. Other mutations were significantly associated with subtype and PI selective pressure (p<0.05), pointing towards a differential selective pressure in both subtypes. We confirmed previous reports on the subtype-dependent selection of D30N and 89I, and identified a new mutation with such differential selective pressure: 37D was preferentially selected by lopinavir in subtype B. Other novel mutations found under therapy pressure were 13A, 35N, K55R, I66F, I72L/T, T74S, 82M and 89I/V. Our study indicates that even though in general, drug selective pressure and resistance pathways are relatively similar between subtypes B and G, some differences do occur, leading to subtype-dependent substitutions.

Protease mutation M89I/V is linked to therapy failure in patients infected with the HIV-1 non-B subtypes C, F or G.

OBJECTIVE: To investigate whether and how mutations at position 89 of HIV-1 protease were associated with protease inhibitor (PI) failure, and what is the impact of the HIV-1 subtype. METHODS: In a database containing pol nucleotide sequences and treatment history, the correlation between PI experience and mutations at codon 89 was determined separately for subtype B and several non-B subtypes. A Bayesian network model was used to map the resistance pathways in which M89I/V is involved for subtype G. The phenotypic effect of M89I/V for several PIs was also measured. RESULTS: The analysis showed that for the subtypes C, F and G in which the wild-type codon at 89 was M compared to L for subtype B, M89I/V was significantly more frequently observed in PI-treated patients displaying major resistance mutations to PIs than in drug-naive patients. M89I/V was strongly associated with PI resistance mutations at codons 71, 74 and 90. Phenotypically, M89I/V alone did not confer a reduced susceptibility to PIs. However, when combined with L90M, a significantly reduced susceptibility to nelfinavir was observed (P < 0.05) in comparison with strains with L90M alone. CONCLUSIONS: The results of the present study show that M89I/V is associated with PI experience in subtypes C, F and G but not in subtype B. M89I/V should be considered a secondary PI mutation with an important effect on nelfinavir susceptibility in the presence of L90M.