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Article: Combined Integrative RNA-Seq and Serological sIgE Analysis Enhances Understanding of Fish Allergen Profiles and Diagnostic Strategy for Fish Allergy
Title | Combined Integrative RNA-Seq and Serological sIgE Analysis Enhances Understanding of Fish Allergen Profiles and Diagnostic Strategy for Fish Allergy |
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Authors | Liu, Zhong YiWai, Christine Yee YanLeung, Agnes Sze YinChan, Wai HungRosa Duque, Jaime SouLam, Ivan Cheuk SanCheng, James WesleySit, Jason Ka ChunNgai, Noelle AnneHo, Po KiChua, Gilbert T.Lee, Qun UiChan, Oi ManYau, Yat SunWong, Joshua Sung ChiLuk, David Chi KongHo, Marco Hok KungKwan, Mike Yat WahTang, Man FungLeung, Nicki Yat HinLeung, Ting Fan |
Keywords | allergen discovery component-resolved diagnosis fish allergenicity ladder fish allergy ImmunoCAP sIgE parvalbumin RNA-seq |
Issue Date | 7-Oct-2024 |
Publisher | MDPI |
Citation | International Journal of Molecular Sciences, 2024, v. 25, n. 19 How to Cite? |
Abstract | Fish allergy is a significant health concern, with diagnosis and management complicated by diverse fish species and allergens. We conducted a comprehensive RNA-seq analysis of eight fish species to identify allergen profiles, integrating ImmunoCAP sIgE data to explore associations with allergen expression and diagnostic performance. Over 30 putative fish allergens were identified, with varying sequence similarities and expression levels, roughly classifying fish into two groups based on parvalbumin (PV) expression. Higher similarities in allergen expression correlated with stronger sIgE data relationships among fish extracts. High PV expression and conserved PV sequences were linked to elevated sIgE measurements, potentially indicating higher allergenicity. For diagnosis, species-specific extract sIgE remained the best indicator of corresponding fish allergy diagnosis, while incorporating multiple sIgE data enhanced performance. In component-resolved diagnosis (CRD), the current panel with PV alone showed comparable performance to fish extract for PV-high fish allergy, while PV-low fish may require the inclusion of more minor allergens for improved CRD accuracy. This RNA-seq allergen analysis helps reveal fish allergen profiles, classify fish groups, and predict allergenicity, potentially improving CRD design and food management in fish allergy. |
Persistent Identifier | http://hdl.handle.net/10722/354083 |
ISSN | 2023 Impact Factor: 4.9 2023 SCImago Journal Rankings: 1.179 |
DC Field | Value | Language |
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dc.contributor.author | Liu, Zhong Yi | - |
dc.contributor.author | Wai, Christine Yee Yan | - |
dc.contributor.author | Leung, Agnes Sze Yin | - |
dc.contributor.author | Chan, Wai Hung | - |
dc.contributor.author | Rosa Duque, Jaime Sou | - |
dc.contributor.author | Lam, Ivan Cheuk San | - |
dc.contributor.author | Cheng, James Wesley | - |
dc.contributor.author | Sit, Jason Ka Chun | - |
dc.contributor.author | Ngai, Noelle Anne | - |
dc.contributor.author | Ho, Po Ki | - |
dc.contributor.author | Chua, Gilbert T. | - |
dc.contributor.author | Lee, Qun Ui | - |
dc.contributor.author | Chan, Oi Man | - |
dc.contributor.author | Yau, Yat Sun | - |
dc.contributor.author | Wong, Joshua Sung Chi | - |
dc.contributor.author | Luk, David Chi Kong | - |
dc.contributor.author | Ho, Marco Hok Kung | - |
dc.contributor.author | Kwan, Mike Yat Wah | - |
dc.contributor.author | Tang, Man Fung | - |
dc.contributor.author | Leung, Nicki Yat Hin | - |
dc.contributor.author | Leung, Ting Fan | - |
dc.date.accessioned | 2025-02-07T00:35:33Z | - |
dc.date.available | 2025-02-07T00:35:33Z | - |
dc.date.issued | 2024-10-07 | - |
dc.identifier.citation | International Journal of Molecular Sciences, 2024, v. 25, n. 19 | - |
dc.identifier.issn | 1661-6596 | - |
dc.identifier.uri | http://hdl.handle.net/10722/354083 | - |
dc.description.abstract | Fish allergy is a significant health concern, with diagnosis and management complicated by diverse fish species and allergens. We conducted a comprehensive RNA-seq analysis of eight fish species to identify allergen profiles, integrating ImmunoCAP sIgE data to explore associations with allergen expression and diagnostic performance. Over 30 putative fish allergens were identified, with varying sequence similarities and expression levels, roughly classifying fish into two groups based on parvalbumin (PV) expression. Higher similarities in allergen expression correlated with stronger sIgE data relationships among fish extracts. High PV expression and conserved PV sequences were linked to elevated sIgE measurements, potentially indicating higher allergenicity. For diagnosis, species-specific extract sIgE remained the best indicator of corresponding fish allergy diagnosis, while incorporating multiple sIgE data enhanced performance. In component-resolved diagnosis (CRD), the current panel with PV alone showed comparable performance to fish extract for PV-high fish allergy, while PV-low fish may require the inclusion of more minor allergens for improved CRD accuracy. This RNA-seq allergen analysis helps reveal fish allergen profiles, classify fish groups, and predict allergenicity, potentially improving CRD design and food management in fish allergy. | - |
dc.language | eng | - |
dc.publisher | MDPI | - |
dc.relation.ispartof | International Journal of Molecular Sciences | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | allergen discovery | - |
dc.subject | component-resolved diagnosis | - |
dc.subject | fish allergenicity ladder | - |
dc.subject | fish allergy | - |
dc.subject | ImmunoCAP sIgE | - |
dc.subject | parvalbumin | - |
dc.subject | RNA-seq | - |
dc.title | Combined Integrative RNA-Seq and Serological sIgE Analysis Enhances Understanding of Fish Allergen Profiles and Diagnostic Strategy for Fish Allergy | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.3390/ijms251910784 | - |
dc.identifier.pmid | 39409113 | - |
dc.identifier.scopus | eid_2-s2.0-85206554048 | - |
dc.identifier.volume | 25 | - |
dc.identifier.issue | 19 | - |
dc.identifier.eissn | 1422-0067 | - |
dc.identifier.issnl | 1422-0067 | - |