Evidence map›Paper›PMID 41508051›Full record

ArticleInfectious diseases of poverty2026

Antibody landscapes of arboviral exposure across China revealed by high-throughput seroprofiling from a peptide epitope library.

Nan Zhang, Wei Liu, Feng Zhu, Wan Ni Chia, Dai Kuang, Ying Luo, Yuxuan Han, Hua Pei, Lin-Fa Wang, Qianfeng Xia

Abstract read
In one paragraph

Article in Infectious diseases of poverty, 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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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Nan Zhang *National Health Commission Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, 571199, Hainan, China.
Wei Liu *National Health Commission Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, 571199, Hainan, China.
Feng ZhuProgramme in Emerging Infectious Diseases, Duke-National University of Singapore Medical School, Singapore, Singapore.
Wan Ni ChiaProgramme in Emerging Infectious Diseases, Duke-National University of Singapore Medical School, Singapore, Singapore.
Dai KuangNational Health Commission Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, 571199, Hainan, China.
Ying LuoDepartment of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Yuxuan HanChinese Academy of Sciences Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Hua PeiThe Second Affiliated Hospital and the Transplantation Institute, Hainan Medical University, Hainan, China.
Lin-Fa WangProgramme in Emerging Infectious Diseases, Duke-National University of Singapore Medical School, Singapore, Singapore. linfa.wang@duke-nus.edu.sg.
Qianfeng XiaNational Health Commission Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, 571199, Hainan, China. xiaqianfeng@muhn.edu.cn.ORCID http://orcid.org/0000-0001-5521-5664

Funding

Graduate Research and Innovation Projects of of Hainan Medical University HYYB2024-B001Hainan Provincial Natural Science Foundation of China 822QN324National Natural Science Foundation of China General Program 82370018National Natural Science Foundation of China Regional Joint Key Project U24A20747Singapore National Medical Research Council OFLCG19May-0034
6 · The paper itself

Abstract

backgroundArboviral infections impose significant public health challenges globally, yet routine surveillance typically captures only symptomatic infections, underestimating the true extent of exposure. Insights into how regional and demographic factors influence population immunity are essential for targeted surveillance and prevention, but such multidimensional insights remain limited. This study aimed to quantify population-level arboviral sero exposure and delineate the effects of regional and demographic factors on immunity to inform targeted surveillance and prevention.

methodsWe utilized a programmable phage display platform, ArboScan, which evaluates antibody binding to overlapping peptides that represent the proteomes of 691 human and zoonotic arboviruses. We profiled baseline antibody reactivity in serum samples from 400 healthy individuals, collected before the dengue outbreaks reported in Hainan in 2019. Antibody reactivity was quantified as normalized fold-change (FC) values relative to negative controls, and analyzed by region, sex, and age. Normality was assessed using the Shapiro-Wilk test. Two-group comparisons were conducted using independent two-sample t tests for normally distributed data or Mann-Whitney U tests otherwise; comparisons among > 2 groups were performed using One-way Analysis of Variance for normally distributed data.

resultsRegional ranking by mean product fold change (MPFC) showed northern enrichment for bluetongue virus (MPFC = 3.56), whereas southern cohorts were enriched for mosquito-borne arboviruses-dengue virus (MPFC = 3.54), Alagoas vesiculovirus (MPFC = 3.50), and Venezuelan equine encephalitis virus (MPFC = 3.39). Females exhibited higher FC than males for selected arboviral families (P < 0.001). By family-level analysis, Flaviviridae, Togaviridae, and Phenuiviridae showed no age-stratified differences (P > 0.05). High fold-change values were detected for non-arboviral viruses such as human cytomegaloviruses and human adenoviruses across all regions.

conclusionsOur findings reveal distinct regional and demographic patterns of arboviral antibody reactivity in China, reflecting differing histories of exposure and potentially informing region-specific surveillance strategies. The stable antibody levels across age groups, together with higher fold-change values in females, underscore the influence of biological and social factors on arboviral immunity. The ArboScan platform, and programmable peptide display platforms in general, offer a scalable approach to characterize population-level immunity and could enhance early detection and public health preparedness in arbovirus-endemic areas.

Indexed as

Antibodies, ViralArbovirusesArbovirus InfectionsEpitopesAdolescentAdultAgedAnimalsChildChinaFemaleHumansMaleMiddle AgedPeptide LibraryYoung AdultAntibodies, ViralEpitopesPeptide LibraryArbovirusesPhage immunoprecipitation sequencingRegional differencesSerosurveillance

Identifiers

PMID41508051
PMCPMC12784556

What OpenQuestion holds

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LicenceCC BY
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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.