%0 Journal Article
%T Multi-Omics Analysis by Machine Learning Identified Lysophosphatidic Acid as a Biomarker and Therapeutic Target for Porcine Reproductive and Respiratory Syndrome.
%A Zhang H
%A Hu F
%A Peng O
%A Huang Y
%A Hu G
%A Ashraf U
%A Cen M
%A Wang X
%A Xu Q
%A Zou C
%A Wu Y
%A Zhu B
%A Li W
%A Li Q
%A Li C
%A Xue C
%A Cao Y
%J Adv Sci (Weinh)
%V 0
%N 0
%D 2024 Jul 8
%M 38976572
%F 17.521
%R 10.1002/advs.202402025
%X 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.