MethylSense: high accuracy machine learning-based diagnostics for <i>Aspergillus fumigatus</i> infection in chickens using host cell-free DNA methylation and Nanopore sequencing
test (5 DMRs, random forest) for field deployment via methylation-specific PCR achieved 71.4% accuracy (sensitivity 45%, specificity 89.7%). Bootstrap analysis demonstrated exceptional marker stability (80.6%-100%) with minimal batch effects, confirming robust host-based diagnostics.
Authors
- Carolyn Cray (ORCID: https://orcid.org/0000-0002-7180-153X)
- Louise Ladefoged Poulsen (ORCID: https://orcid.org/0000-0002-0675-1353)
- Anders Miki Bojesen (ORCID: https://orcid.org/0000-0003-4030-0019)
- Christina Hvilsom (ORCID: https://orcid.org/0000-0001-7870-6888)
- Christoph Leineweber (ORCID: https://orcid.org/0000-0003-4241-7018)
- Stamatios Alan Tahas (ORCID: https://orcid.org/0000-0003-1036-4898)
- Markus Drag (ORCID: https://orcid.org/0000-0002-7412-6402)
- Mads F. Bertelsen (ORCID: https://orcid.org/0000-0001-9201-7499)
- H Gamst Jensen
Institutions
- University of Copenhagen (DK)
- University of Miami (US)
- Novo Nordisk Foundation (DK)
- Copenhagen Zoo (DK)
- Laboklin (Germany) (DE)
Publication Details
- Journal
- Journal of Clinical Microbiology
- Published
- 2026-04-27
- DOI
- https://doi.org/10.1128/jcm.01054-25
- Primary Topic
- Coccidia and coccidiosis research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Innovationsfonden
- Association of Avian Veterinarians
- Loro Parque Fundación
- Familien Hede Nielsens Fond
- Alfred Benzon Foundation