Evidence map›Paper›PMID 41988658›Full record

ArticleThe Journal of antimicrobial chemotherapy2026

Genome-wide association studies builds a predictive model and reveals novel resistance features for macrolide-resistant Bordetella pertussis.

Jialiang Chen, Guowei Liang

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Article in The Journal of antimicrobial chemotherapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Jialiang ChenDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing 100049, China.ORCID 0009-0003-8005-960X
Guowei LiangDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing 100049, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe macrolide resistance in Bordetella pertussis cannot be fully explained by 23S rRNA mutations, underscoring the need for comprehensive methods to detect resistant isolates and clarify mechanisms.

methodsWhole-genome sequencing data from 556 isolates with macrolide resistance information, including 398 resistant and 158 sensitive strains, were retrieved from the National Center for Biotechnology Information (NCBI). A k-mer-based genome-wide k-mer-based association studies using Pyseer identified 1322 resistance-associated k-mers. Refinement with Scoary2, least absolute shrinkage and selection operator (LASSO) and variable selection using random forests (VSURF) yielded six key k-mers, enabling the construction of a simplified model for predicting resistance.

resultsA total of 1322 different k-mers were involved in resistance. In the further simplified model, only six k-mers were included, in which a DHCW motif cupin fold protein (odds ratio [OR]: 25.84, 95% confidence interval [CI]: 15.58-44.03) and an IS481 insertion sequence located near infA (OR: 28.96, 95% CI: 7.64-243.86) showed strong associations with resistance. Despite the reduced feature set, the simplified model achieved classification performance comparable to the initial model, with similar sensitivity (97.7% versus 98.7%), specificity (92.1% versus 99.5%), and accuracy (93.4% versus 99.3%). Notably, it maintained a robust area under the receiver operating characteristic curve (area under the curve = 0.98), indicating strong predictive capability.

conclusionsThis study developed a simplified k-mer-based model for accurately identifying macrolide-resistant B. pertussis isolates and uncovered novel resistance features.

Indexed as

Anti-Bacterial AgentsBordetella pertussisDrug Resistance, BacterialGenome-Wide Association StudyMacrolidesGenome, BacterialHumansMicrobial Sensitivity TestsRNA, Ribosomal, 23SWhole Genome SequencingWhooping CoughAnti-Bacterial AgentsMacrolidesRNA, Ribosomal, 23S

Identifiers

PMID41988658
PMCPMC13084545

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.