{Reference Type}: Journal Article
{Title}: Multi-Omics Analysis by Machine Learning Identified Lysophosphatidic Acid as a Biomarker and Therapeutic Target for Porcine Reproductive and Respiratory Syndrome.
{Author}: Zhang H;Hu F;Peng O;Huang Y;Hu G;Ashraf U;Cen M;Wang X;Xu Q;Zou C;Wu Y;Zhu B;Li W;Li Q;Li C;Xue C;Cao Y;
{Journal}: Adv Sci (Weinh)
{Volume}: 0
{Issue}: 0
{Year}: 2024 Jul 8
{Factor}: 17.521
{DOI}: 10.1002/advs.202402025
{Abstract}: As a significant infectious disease in livestock, porcine reproductive and respiratory syndrome (PRRS) imposes substantial economic losses on the swine industry. Identification of diagnostic markers and therapeutic targets has been a focal challenge in PPRS prevention and control. By integrating metabolomic and lipidomic serum analyses of clinical pig cohorts through a machine learning approach with in vivo and in vitro infection models, lysophosphatidic acid (LPA) is discovered as a serum metabolic biomarker for PRRS virus (PRRSV) clinical diagnosis. PRRSV promoted LPA synthesis by upregulating the autotaxin expression, which causes innate immunosuppression by dampening the retinoic acid-inducible gene I (RIG-I) and type I interferon responses, leading to enhanced virus replication. Targeting LPA demonstrated protection against virus infection and associated disease outcomes in infected pigs, indicating that LPA is a novel antiviral target against PRRSV. This study lays a foundation for clinical prevention and control of PRRSV infections.