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Published on: August 7, 2017
Serum proteomics identifies novel diagnostic biomarkers for asthma in preschool children
Hui Ding1, Zhaoling Shi1, Haibo Lin1
1Department of Pediatrics, Children's Hospital, The Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China.
Insights
Researchers identified novel protein biomarkers in children's serum to improve asthma diagnosis. A new diagnostic model using the protein IGFALS showed high accuracy (AUC 0.959) for preschool children.
Area of Science:
- Biochemistry
- Immunology
- Pediatrics
Background:
- Childhood asthma is a common chronic disease characterized by airway hyperresponsiveness and inflammation.
- Current diagnostic methods for childhood asthma present challenges, highlighting the need for novel diagnostic approaches.
- Accurate diagnosis is crucial for effective management and treatment of pediatric asthma.
Purpose of the Study:
- To identify serum proteomic biomarkers for diagnosing asthma in children.
- To develop and evaluate a diagnostic model for preschool children with asthma.
Main Methods:
- Employed Orbitrap-based data-independent acquisition (DIA) mass spectrometry for serum proteomics analysis.
- Analyzed serum samples from children with acute asthma and healthy controls.
- Identified differentially expressed proteins (DEPs) and performed functional enrichment analysis.
Main Results:
- Identified 747 proteins and 50 DEPs distinguishing asthmatic from healthy children.
- DEPs were significantly enriched in immune-related pathways, suggesting their role in asthma pathogenesis.
- Identified potential diagnostic biomarker candidates including MMP14, ABHD12B, PCYOX1, LTBP1, CFHR4, APOA1, IGHG4, ANG, and IGFALS.
- Developed an asthma diagnostic model for preschool children based on IGFALS with an AUC of 0.959.
Conclusions:
- The DIA proteome strategy identified a large number of proteins related to asthma.
- Proteomic signatures, particularly DEPs involved in inflammation and immunity, offer insights into asthma pathophysiology.
- The IGFALS-based diagnostic model shows promise for clinical decision-making in preschool children with asthma.
Background:
Asthma is characterized by airway hyperresponsiveness, reversible airway obstruction, and chronic airway inflammation. It is the most common chronic disease in childhood. However, the diagnosis of childhood asthma remains challenging, and there is an urgent need to develop new diagnostic methods.
Methods:
To identify biomarkers of asthma in children, we adopted the Orbitrap-based data-independent acquisition (DIA) mass spectrometry proteomics method to analyze the serum proteomic signatures of children with acute asthma and convalescent children.
Results:
We identified 747 proteins in 46 serum samples and 50 differentially expressed proteins (DEPs) that distinguished between asthmatic and healthy children. Next, functional enrichment analysis of the DEPs was conducted, it was indicated that the DEPs were significantly enriched in immune-related and function terms and pathways. Furthermore, we performed statistical analysis and identified MMP14, ABHD12B, PCYOX1, LTBP1, CFHR4, APOA1, IGHG4, ANG and IGFALS proteins as the diagnostic biomarker candidates. Ultimately, a promising asthma diagnostic model for preschool children based on IGFALS was built and evaluated. The area under the curve (AUC) of the IGFALS model was 0.959.
Conclusions:
In this study, the DIA proteome strategy was used and the largest number of proteins of asthmatic children serum proteomics was identified. The proteomics results showed that the DEPs play the central role of the inflammation-immune mechanism in asthma pathogenesis, suggesting that these proteins may be used in asthma diagnosis, prognosis, or therapy, and suggested biomarkers for asthma of preschool children. In conclusion, our results provide insight into the pathophysiology of asthma. We believe that the diagnostic model will facilitate clinical decision-making regarding asthma in preschool children.
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