Predicting Potential PRRSV-2 Variant Emergence through Phylogenetic Inference

• Published in: Transboundary and emerging diseases 2024-02, Vol.2024, p.1-15
• Main Authors: Pamornchainavakul, Nakarin, Kikuti, Mariana, Paploski, Igor A. D., Corzo, Cesar A., VanderWaal, Kimberly
• Format: Article
• Language: English
• Subjects: Animal diseases; Disease control; Epidemics; Genetic diversity; Hogs; Infectious diseases; Metadata; Phylogenetics; Phylogeny; Population growth; Prediction models; Preempting; Public health; Respiratory diseases; Severe acute respiratory syndrome coronavirus 2; Spatial distribution; Success; Swine; Trees; Vaccine development; Vaccines; Viral diseases; Virulence; Viruses
• ISSN: 1865-1674; 1865-1682
• DOI: 10.1155/2024/7945955

Porcine reproductive and respiratory syndrome (PRRS) is a significant pig disease causing substantial annual losses exceeding half a billion dollars to the United States pork industry. The cocirculation and emergence of genetically distinct PRRSV-2 viruses hinder PRRS control, especially vaccine development. Similar to other viral infections like seasonal flu and SARS-CoV-2, predictive tools for identifying potential emerging viral variants may prospectively aid in preemptive disease mitigation. However, such predictions have not been made for PRRSV-2, despite the abundance of relevant data. In this study, we analyzed a decade’s worth of virus ORF5 sequences (n = 20,700) and corresponding metadata to identify phylogenetic-based early indicators for short-term (12 months) and long-term (24 months) variant emergence. Our analysis focuses on PRRSV-2 Lineage 1, which was the predominant lineage within the U.S. during this period. We evaluated population expansion, spatial distribution, and genetic diversity as key success metrics for variant emergence. Our findings indicate that successful variants were best characterized as those that underwent population expansion alongside widespread geographical spread but had limited genetic diversification. Conditional logistic regression revealed the local branching index as the sole informative indicator for predicting population expansion (balanced accuracy (BA) = 0.75), while ancestral branch length was strongly linked to future genetic diversity (BA = 0.79). Predicting spatial dispersion relied on the branch length and putative antigenic difference (BA = 0.67), but their causal relationships remain unclear. Although the predictive models effectively captured most emerging variants (sensitivity = 0.58–0.81), they exhibited relatively low positive predictive value (PPV = 0.09–0.16). This initial step in PRRSV-2 prediction is a crucial step for more precise prevention strategies against PRRS in the future.