Clinical, molecular, and drug resistance epidemiology of HIV in Jordan, 2019-2021: A national study.

BACKGROUND: Limited epidemiologic studies have been conducted in Jordan describing the HIV epidemic. This study aimed to address this gap to inform HIV prevention and control. METHODS: A nationally-representative cross-sectional study was conducted among adults living with HIV in Jordan. Laboratory testing included HIV viral load and next-generation-sequencing-based clinical genotype. Log-binomial regression estimated risk ratios (RRs) and 95% confidence intervals (CIs). RESULTS: Among 231 (70%) participants, most were male (184/80%), and from Jordan (217/94%). Among 188 treatment-experienced-participants (>6 months), 165 (88%) were virally suppressed. High-level resistance was most frequent against nucleoside reverse transcriptase inhibitor (13/81%), and integrase-strand transfer inhibitor (INSTI) (10/62%) drugs among viremic (≥1000 HIV copies/mL) treatment-experienced participants with drug-resistant mutations (DRMs, n = 16). Common HIV subtypes (n = 43) were B (6/14%), A1 (5/12%), and CRF01_AE (5/12%); additionally, novel recombinant forms were detected. In multivariate analysis, independently higher risk for late diagnosis (n = 49) was observed with diagnosis through blood donation (vs check-up: RR 2.20, 95%CI 1.16-4.17) and earlier time-period of diagnosis (1986-2014 vs 2015-2021: RR 2.87, 95%CI 1.46-5.62). CONCLUSIONS: Late diagnosis and INSTI resistance endanger national HIV prevention and treatment in Jordan-high-level resistance to INSTI suggests therapeutic drug monitoring is needed for treatment efficacy and conservation of treatment options.

Identification of Immune Signatures of Novel Adjuvant Formulations Using Machine Learning.

Adjuvants have long been critical components of vaccines, but the exact mechanisms of their action and precisely how they alter or enhance vaccine-induced immune responses are often unclear. In this study, we used broad immunoprofiling of antibody, cellular, and cytokine responses, combined with data integration and machine learning to gain insight into the impact of different adjuvant formulations on vaccine-induced immune responses. A Self-Assembling Protein Nanoparticles (SAPN) presenting the malarial circumsporozoite protein (CSP) was used as a model vaccine, adjuvanted with three different liposomal formulations: liposome plus Alum (ALFA), liposome plus QS21 (ALFQ), and both (ALFQA). Using a computational approach to integrate the immunoprofiling data, we identified distinct vaccine-induced immune responses and developed a multivariate model that could predict the adjuvant condition from immune response data alone with 92% accuracy (p = 0.003). The data integration also revealed that commonly used readouts (i.e. serology, frequency of T cells producing IFN-γ, IL2, TNFα) missed important differences between adjuvants. In summary, broad immune-profiling in combination with machine learning methods enabled the reliable and clear definition of immune signatures for different adjuvant formulations, providing a means for quantitatively characterizing the complex roles that adjuvants can play in vaccine-induced immunity. The approach described here provides a powerful tool for identifying potential immune correlates of protection, a prerequisite for the rational pairing of vaccines candidates and adjuvants.

Self-assembling protein nanoparticles with built-in flagellin domains increases protective efficacy of a Plasmodium falciparum based vaccine.

To eliminate the problems associated with the use of extraneous adjuvants we have designed a Self-Assembling Protein Nanoparticle (SAPN) containing epitopes from the Plasmodium falciparum circumsporozoite protein (PfCSP) (designated FMP014) and portions of the TLR5 agonist flagellin (designated FMP014D0D1) as an intrinsic adjuvant. By combining different molar ratios of FMP014 to FMP014D0D1 monomers before self-assembly, we generated multiple nanoparticles and investigated their biophysical characteristics, immunogenicity and protective efficacy. Immunization with the construct formulated with the ratio 58:2 of FMP014 to FMP014D0D1 had the highest protective efficacy against a challenge with a transgenic P. berghei sporozoite expressing PfCSP. Increasing the proportion of flagellin per particle resulted in an inverse relationship with levels of both antibody titers and protection. The cytokine profiles of the various immunization groups were evaluated and quantitative amounts of the cytokines IL-2, IFN-γ, IL-12/p70 (Th1); IL4, IL5 (Th2); TNF-α, IL1ß, IL-6, KC/GRO (pro-inflammatory), and IL-10 (immunomodulatory) were measured. The relationship of the cytokines to each other revealed a strong immunomodulatory effect depending on the proportion of flagellin in the construct. Our results demonstrate that SAPNs with flagellin may be a promising strategy for the development and delivery of a safe vaccine for infectious diseases.