biostudies-literatureUnknown16(1)Surtees RThe 2022 global mpox outbreak highlighted the risk of zoonotic diseases establishing sustained transmission in human populations and underscored the need for accurate serological tools to monitor orthopoxvirus exposure. However, cross-reactive antibodies induced by Modified Vaccinia Ankara (MVA) vaccination make it difficult to discriminate between monkeypox virus (MPXV) infection and vaccination-induced immunity. Here we present a machine learning (ML)-assisted bead-based serological multiplex assay that distinguishes MPXV infection from MVA vaccination and pre-immune sera by targeting antibody responses to 15 poxviral antigens. Of the six algorithms tested, the Gradient Boosting Classifier (GBC) achieves the highest performance (F1 = 0.83) in sera from the 2022 outbreak and from a followNature communications10943https://www.ebi.ac.uk/biostudies/studies/S-EPMC12686480biostudies-literatureMachine learning-supported framework for the classification of mpox infection and MVA immunization from multiplexed serology data.PMC12686480Grossegesse MAkhmedova SSesver ATreindl FLadewig KKorber NSkiba MKoppe UNitsche AMages HWSurtees RNguyen MLMarcus UBayram FMankertz AMichel JFriedrich NStern DBeslic DRinner TJansen KDorner BGfalseMachine learning-supported framework for the classification of mpox infection and MVA immunization from multiplexed serology data.The 2022 global mpox outbreak highlighted the risk of zoonotic diseases establishing sustained transmission in human populations and underscored the need for accurate serological tools to monitor orthopoxvirus exposure. However, cross-reactive antibodies induced by Modified Vaccinia Ankara (MVA) vaccination make it difficult to discriminate between monkeypox virus (MPXV) infection and vaccination-induced immunity. Here we present a machine learning (ML)-assisted bead-based serological multiplex assay that distinguishes MPXV infection from MVA vaccination and pre-immune sera by targeting antibody responses to 15 poxviral antigens. Of the six algorithms tested, the Gradient Boosting Classifier (GBC) achieves the highest performance (F1 = 0.83) in sera from the 2022 outbreak and from a follow2025-01-01T00:00:00Z2025 Dec2026-06-08T04:59:40.775Z2026-06-08T03:08:41.113ZS-EPMC126864804135054010.1038/s41467-025-66994-0