Unveiling ecological/evolutionary insights in HIV viral load dynamics: Allowing random slopes to observe correlational changes to CpG-contents and other molecular and clinical predictors.

In the context of infectious diseases, the dynamic interplay between ever-changing host populations and viral biology demands a more flexible modeling approach than common fixed correlations. Embracing random-effects regression models allows for a nuanced understanding of the intricate ecological and evolutionary dynamics underlying complex phenomena, offering valuable insights into disease progression and transmission patterns. In this article, we employed a random-effects regression to model an observed decreasing median plasma viral load (pVL) among individuals with HIV in Mexico City during 2019-2021. We identified how these functional slope changes (i.e. random slopes by year) improved predictions of the observed pVL median changes between 2019 and 2021, leading us to hypothesize underlying ecological and evolutionary factors. Our analysis involved a dataset of pVL values from 7325 ART-naïve individuals living with HIV, accompanied by their associated clinical and viral molecular predictors. A conventional fixed-effects linear model revealed significant correlations between pVL and predictors that evolved over time. However, this fixed-effects model could not fully explain the reduction in median pVL; thus, prompting us to adopt random-effects models. After applying a random effects regression model-with random slopes and intercepts by year-, we observed potential "functional changes" within the local HIV viral population, highlighting the importance of ecological and evolutionary considerations in HIV dynamics: A notably stronger negative correlation emerged between HIV pVL and the CpG content in the pol gene, suggesting a changing immune landscape influenced by CpG-induced innate immune responses that could impact viral load dynamics. Our study underscores the significance of random effects models in capturing dynamic correlations and the crucial role of molecular characteristics like CpG content. By enriching our understanding of changing host-virus interactions and HIV progression, our findings contribute to the broader relevance of such models in infectious disease research. They shed light on the changing interplay between host and pathogen, driving us closer to more effective strategies for managing infectious diseases. SIGNIFICANCE OF THE STUDY: This study highlights a decreasing trend in median plasma viral loads among ART-naïve individuals living with HIV in Mexico City between 2019 and 2021. It uncovers various predictors significantly correlated with pVL, shedding light on the complex interplay between host-virus interactions and disease progression. By employing a random-slopes model, the researchers move beyond traditional fixed-effects models to better capture dynamic correlations and evolutionary changes in HIV dynamics. The discovery of a stronger negative correlation between pVL and CpG content in HIV-pol sequences suggests potential changes in the immune landscape and innate immune responses, opening avenues for further research into adaptive changes and responses to environmental shifts in the context of HIV infection. The study's emphasis on molecular characteristics as predictors of pVL adds valuable insights to epidemiological and evolutionary studies of viruses, providing new avenues for understanding and managing HIV infection at the population level.

Characteristics and growth of the genetic HIV transmission network of Mexico City during 2020.

INTRODUCTION: Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention. METHODS: All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV-TRACE tool: Seguro HIV-TRACE. Socio-demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions. RESULTS: A total of 3168 HIV sequences from unique individuals were included. One thousand and one-hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3 ) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio-economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub-clusters with high growth potential. CONCLUSIONS: HIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.

HIV-TRACE (TRAnsmission Cluster Engine): a Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens.

In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens.

Evolution and spread of Venezuelan equine encephalitis complex alphavirus in the Americas.

Venezuelan equine encephalitis (VEE) complex alphaviruses are important re-emerging arboviruses that cause life-threatening disease in equids during epizootics as well as spillover human infections. We conducted a comprehensive analysis of VEE complex alphaviruses by sequencing the genomes of 94 strains and performing phylogenetic analyses of 130 isolates using complete open reading frames for the nonstructural and structural polyproteins. Our analyses confirmed purifying selection as a major mechanism influencing the evolution of these viruses as well as a confounding factor in molecular clock dating of ancestors. Times to most recent common ancestors (tMRCAs) could be robustly estimated only for the more recently diverged subtypes; the tMRCA of the ID/IAB/IC/II and IE clades of VEE virus (VEEV) were estimated at ca. 149-973 years ago. Evolution of the IE subtype has been characterized by a significant evolutionary shift from the rest of the VEEV complex, with an increase in structural protein substitutions that are unique to this group, possibly reflecting adaptation to its unique enzootic mosquito vector Culex (Melanoconion) taeniopus. Our inferred tree topologies suggest that VEEV is maintained primarily in situ, with only occasional spread to neighboring countries, probably reflecting the limited mobility of rodent hosts and mosquito vectors.

Identification of major routes of HIV transmission throughout Mesoamerica.

BACKGROUND: Migration and travel are major drivers of the spread of infectious diseases. Geographic proximity and a common language facilitate travel and migration in Mesoamerica, which in turn could affect the spread of HIV in the region. METHODS: 6092 HIV-1 subtype B partial pol sequences sampled from unique antiretroviral treatment-naïve individuals from Mexico (40.7%), Guatemala (24.4%), Honduras (19%), Panama (8.2%), Nicaragua (5.5%), Belize (1.4%), and El Salvador (0.7%) between 2011 and 2016 were included. Phylogenetic and genetic network analyses were performed to infer putative relationships between HIV sequences. The demographic and geographic associations with clustering were analyzed and viral migration patterns were inferred using the Slatkin-Maddison approach on 100 iterations of random subsets of equal number of sequences per location. RESULTS: A total of 1685/6088 (27.7%) of sequences linked with at least one other sequence, forming 603 putative transmission clusters (range: 2-89 individuals). Clustering individuals were significantly more likely to be younger (median age 29 vs 33years, p<0.01) and men-who-have-sex-with-men (40.4% vs 30.3%, p<0.01). Of the 603 clusters, 30 (5%) included sequences from multiple countries with commonly observed linkages between Mexican and Honduran sequences. Eight of the 603 clusters included >10 individuals, including two comprised exclusively of Guatemalans (52 and 89 individuals). Phylogenetic and migration analyses suggested that the Central and Southern regions of Mexico along with Belize were major sources of HIV throughout the region (p<0.01) with genetic flow southward from Mexico to the other nations of Mesoamerica. We also found evidence of significant viral migration within Mexico. CONCLUSION: International clusters were infrequent, suggesting moderate migration between HIV epidemics of the different Mesoamerican countries. Nevertheless, we observed important sources of transnational HIV spread in the region, including Southern and Central Mexico and Belize.

HIV Transmission Networks in the San Diego-Tijuana Border Region.

BACKGROUND: HIV sequence data can be used to reconstruct local transmission networks. Along international borders, like the San Diego-Tijuana region, understanding the dynamics of HIV transmission across reported risks, racial/ethnic groups, and geography can help direct effective prevention efforts on both sides of the border. METHODS: We gathered sociodemographic, geographic, clinical, and viral sequence data from HIV infected individuals participating in ten studies in the San Diego-Tijuana border region. Phylogenetic and network analysis was performed to infer putative relationships between HIV sequences. Correlates of identified clusters were evaluated and spatiotemporal relationships were explored using Bayesian phylogeographic analysis. FINDINGS: After quality filtering, 843 HIV sequences with associated demographic data and 263 background sequences from the region were analyzed, and 138 clusters were inferred (2-23 individuals). Overall, the rate of clustering did not differ by ethnicity, residence, or sex, but bisexuals were less likely to cluster than heterosexuals or men who have sex with men (p = 0.043), and individuals identifying as white (p ≤ 0.01) were more likely to cluster than other races. Clustering individuals were also 3.5 years younger than non-clustering individuals (p < 0.001). Although the sampled San Diego and Tijuana epidemics were phylogenetically compartmentalized, five clusters contained individuals residing on both sides of the border. INTERPRETATION: This study sampled ~ 7% of HIV infected individuals in the border region, and although the sampled networks on each side of the border were largely separate, there was evidence of persistent bidirectional cross-border transmissions that linked risk groups, thus highlighting the importance of the border region as a "melting pot" of risk groups. FUNDING: NIH, VA, and Pendleton Foundation.