Evidence map›Paper›PMID 42795454›Full record

ArticleMicroorganisms2026

Serum Escape Landscape of SARS-CoV-2 Omicron JN.1 and XEC RBD Under COVID-19 Vaccine Breakthrough Immunity in China.

Chengwei Shao, Jianguang Fu, Fei Deng, Huiyan Yu, Huan Fan, Yanjun Chen, Ke Xu, Mingwei Wei, Siyue Jia, Xiaoyan Jia and 2 more

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Chengwei ShaoSchool of Public Health, Southeast University, Nanjing 210009, China.
Jianguang FuJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.ORCID 0000-0003-0424-7492
Fei DengJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Huiyan YuJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Huan FanJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Yanjun ChenJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Ke XuJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Mingwei WeiJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Siyue JiaJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Xiaoyan JiaInstitute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 511300, China.
Liguo ZhuJiangsu Provincial Medical Innovation Center, National Health Commission Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing 210009, China.
Jingxin LiSchool of Public Health, Southeast University, Nanjing 210009, China.ORCID 0000-0002-7033-5151

Funding

Prevention and Control of Emerging and Major Infectious Diseases-National Science and Tech-nology Major Project 2025ZD01902100
6 · The paper itself

Abstract

Population immune pressure from vaccination and prior infection continues to drive the evolution of SARS-CoV-2. Systematic characterization of RBD mutations under complex immune backgrounds is essential for understanding viral adaptation and evolutionary trajectories. Here, we applied a deep mutational scanning (DMS) to comprehensively map the neutralization escape landscape of the Omicron variant JN.1 and its descendant lineage XEC, under immune pressure from individuals who experienced Omicron breakthrough infections following three doses of inactivated vaccines. A neutralization escape map for the single amino acid substitutions in the RBD of JN.1 or XEC was generated, and the escape efficiency of each mutation was determined. The results show that RBD escape mutations are hierarchically organized: low-intensity signals are widespread, whereas high-intensity escape is confined to a few key sites. These escape mutations are not confined solely to the receptor-binding motif (RBM) but are broadly distributed across the entire RBD. Many escape sites could accommodate multiple amino acid substitutions. Integration of DMS data with genomic surveillance of circulating variants from 2024 to 2025 revealed significant overlap between experimentally identified escape sites and mutations observed in natural isolates. This overlap increased substantially in 2025, with site concordance rising from 27.17% and 26.81% to 45.09% and 47.10% for JN.1 and XEC, respectively. The natural prevalence of these escape mutations is further shaped by factors such as receptor-binding affinity, protein stability, and epistatic interactions. Overall, our findings suggest that SARS-CoV-2 antigenic evolution follows the pattern of multiple pathways within a constrained space, providing new insights into the adaptive mechanisms of Omicron-derived variants under hybrid immune pressure.

Indexed as

deep mutational scanningreceptor-binding domainSARS-CoV-2

Identifiers

PMID42795454
PMCPMC13609519

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.