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Genetic Landscapes of HIV: Evolutionary Dynamics and Implications for Global Public Health and Therapeutic Strategies

Louis O. Odeigah(1), Olalekan A. Agede(2), Odiakaose P. Odeigah(3), Dapo S. Oyedepo(4), Olawale S. Aiyedun(5), Nasiru Sanni(6), Wemimo A. Alaofin(7), Obinna Christopher Anaduaka(8),


(1) Department of Family Medicine, Faculty of Clinical Sciences, ABUAD/ABUAD Multi-System Hospital, Ado-Ekiti, Ekiti State, Nigeria.
(2) Department of Pharmacology and Therapeutics, University of Ilorin, Ilorin, Kwara State, Nigeria.
(3) Department of Pharmacology and Therapeutics, University of Ilorin, Ilorin, Kwara State, Nigeria. Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria.
(4) Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria.
(5) Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria.
(6) Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria.
(7) Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria.
(8) Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria.
Corresponding Author

Abstract


Background: The genetic diversity of the HIV envelope glycoprotein (Env) gene poses significant challenges for vaccine development and treatment strategies due to its rapid evolution and adaptability. Understanding the genetic variation and evolutionary dynamics of HIV is critical for designing effective public health interventions.

Objectives: This study aims to elucidate the genetic landscapes and evolutionary dynamics of HIV Env gene isolates across different populations and timeframes, to inform global health strategies and contribute to the body of knowledge necessary for HIV control.

Methods: Sequences of the HIV Env gene were systematically retrieved from the NCBI database, representing a diverse array of geographic locations and time points. Following data curation and alignment, comprehensive genetic analyses were conducted using R and GenAlEx. These included SNP detections, allele frequency estimation, Analysis of Molecular Variance (AMOVA), and Principal Coordinates Analysis (PCoA) to assess genetic variability and differentiation.

Results: The analysis revealed substantial fluctuations in genetic diversity among Brazilian isolates, with heterozygosity ranging from 0.42 in 2014 to 0.65 in 2015. Pairwise Nei’s genetic identity demonstrated high similarity between Malaysia (2014) and China (2022) (0.859) and marked divergence within Brazil across consecutive years (2014 vs 2015, Nei distance = 1.602; PhiPT = 0.621). AMOVA indicated that 46% of genetic variance was distributed among populations, with a fixation index of PhiPT = 0.460 and moderate gene flow (Nm = 0.587). Principal Coordinates Analysis (PCoA) captured 58.7% of total variability, showing temporal shifts within Brazil and close clustering of Malaysia–China isolates.

Conclusion: These findings highlight dynamic temporal changes in Brazilian HIV populations, a striking genetic similarity between Malaysian and Chinese isolates, and moderate global gene flow. The observed patterns underscore the need for regionspecific surveillance, timely therapeutic adjustments, and flexible vaccine strategies that accommodate HIV’s rapid evolution.

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