Evidence map›Paper›PMID 37180108›Full record

ArticleFrontiers in immunology2023

Serological analysis of allergic components of house dust mite provides more insight in epidemiological characteristics and clinical symptom development in North China.

Yi Liu, Lan Zhao, Jiaofeng Wang, Yinshi Guo, Yifei Wang, Lishan Zhang, Zhoujie Wu, Mingzhi Zhu, Xukai Yang, Puyang Xu and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

9 citing papers in PubMed, 10 citations in OpenAlex.

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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

13 authors at 4 institutions in 1 country.

Yi LiuAllergy Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Lan ZhaoCollege of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
Jiaofeng WangR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Yinshi GuoAllergy Department, Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.
Yifei WangR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Lishan ZhangAllergy Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Zhoujie WuR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Mingzhi ZhuR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Xukai YangR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Puyang XuR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Shandong WuR&D Department, Hangzhou Zheda Dixun Biological Gene Engineering Co. Ltd., Zhejiang, China.
Zhongshan GaoCollege of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
Jin-Lyu SunAllergy Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNZhejiang University · CNPeking Union Medical College Hospital · CNRenji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: House dust mite (HDM) is the most common airborne source causing complex allergy symptoms. There are geographic differences in the allergen molecule sensitization profiles. Serological testing with allergen components may provide more clues for diagnosis and clinical management. Objective: This study aims to investigate the sensitization profile of eight HDM allergen components in a large number of patients enrolled in the clinic and to analyze the relation of gender, age, and clinical symptoms in North China. Methods: The 548 serum samples of HDM-allergic patients (ImmunoCAP Results: A greater proportion of male patients was in the younger age groups, while more female patients were in the adult groups. Both the sIgE levels and the positive rates (approximately 60%) against Der p 1/Der f 1 and Der p 2/Der f 2 were higher than for the Der p 7, Der p 10, and Der p 21 components (below 25%). The Der f 1 and Der p 2 positive rates were higher in 2-12-year-old children. The Der p 2 and Der f 2 IgE levels and positive rates were higher in the allergic rhinitis group. The positive rates of Der p 10 increased significantly with age. Der p 21 is relevant in allergic dermatitis symptom, while Der p 23 contributes to asthma development. Conclusion: HDM groups 1 and 2 were the major sensitizing allergens, with group 2 being the most important component relevant to respiratory symptoms in North China. The Der p 10 sensitization tends to increase with age. Der p 21 and Der p 23 might be associated with the development of allergic skin disease and asthma, respectively. Multiple allergen sensitizations increased the risk of allergic asthma.

Indexed as

AsthmaDermatitis, AtopicRhinitis, AllergicAllergensAnimalsAntigens, DermatophagoidesChinaDermatophagoides pteronyssinusFemaleImmunoglobulin EMalePyridinolcarbamatePyroglyphidaeAllergensAntigens, DermatophagoidesImmunoglobulin EPyridinolcarbamateallergen componentclinical epidemiologyhouse dust mite allergyIgEserological analysis

Identifiers

PMID37180108
PMCPMC10172571
OpenAlexW4367183863

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.