Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study
<p dir="ltr">Autism spectrum disorder (ASD) is an umbrella term that encompasses several disabling neurodevelopmental conditions. These conditions are characterized by impaired manifestation in social and communication skills with repetitive and restrictive behaviors or interests. Th...
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| مؤلفون آخرون: | , , , , , , , , , , , , , , |
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2023
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| _version_ | 1864513511892189184 |
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| author | Areej Mesleh (17149822) |
| author2 | Hanan Ehtewish (17149825) Alberto de la Fuente (360936) Hawra Al-shamari (18877327) Iman Ghazal (6176756) Fatema Al-Faraj (17281117) Fouad Al-Shaban (17149828) Houari B. Abdesselem (14152827) Mohamed Emara (365494) Nehad M. Alajez (7397276) Abdelilah Arredouani (10914455) Julie Decock (44558) Omar Albagha (8977856) Lawrence W. Stanton (6707191) Sara A. Abdulla (13902015) Omar M. A. El-Agnaf (8809331) |
| author2_role | author author author author author author author author author author author author author author author |
| author_facet | Areej Mesleh (17149822) Hanan Ehtewish (17149825) Alberto de la Fuente (360936) Hawra Al-shamari (18877327) Iman Ghazal (6176756) Fatema Al-Faraj (17281117) Fouad Al-Shaban (17149828) Houari B. Abdesselem (14152827) Mohamed Emara (365494) Nehad M. Alajez (7397276) Abdelilah Arredouani (10914455) Julie Decock (44558) Omar Albagha (8977856) Lawrence W. Stanton (6707191) Sara A. Abdulla (13902015) Omar M. A. El-Agnaf (8809331) |
| author_role | author |
| dc.creator.none.fl_str_mv | Areej Mesleh (17149822) Hanan Ehtewish (17149825) Alberto de la Fuente (360936) Hawra Al-shamari (18877327) Iman Ghazal (6176756) Fatema Al-Faraj (17281117) Fouad Al-Shaban (17149828) Houari B. Abdesselem (14152827) Mohamed Emara (365494) Nehad M. Alajez (7397276) Abdelilah Arredouani (10914455) Julie Decock (44558) Omar Albagha (8977856) Lawrence W. Stanton (6707191) Sara A. Abdulla (13902015) Omar M. A. El-Agnaf (8809331) |
| dc.date.none.fl_str_mv | 2023-04-18T06:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/ijms24087443 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Blood_Proteomics_Analysis_Reveals_Potential_Biomarkers_and_Convergent_Dysregulated_Pathways_in_Autism_Spectrum_Disorder_A_Pilot_Study/26095225 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Neurosciences ASD autism biomarkers early diagnosis PEA proteomics blood profiling machine learning patient stratification |
| dc.title.none.fl_str_mv | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Autism spectrum disorder (ASD) is an umbrella term that encompasses several disabling neurodevelopmental conditions. These conditions are characterized by impaired manifestation in social and communication skills with repetitive and restrictive behaviors or interests. Thus far, there are no approved biomarkers for ASD screening and diagnosis; also, the current diagnosis depends heavily on a physician’s assessment and family’s awareness of ASD symptoms. Identifying blood proteomic biomarkers and performing deep blood proteome profiling could highlight common underlying dysfunctions between cases of ASD, given its heterogeneous nature, thus laying the foundation for large-scale blood-based biomarker discovery studies. This study measured the expression of 1196 serum proteins using proximity extension assay (PEA) technology. The screened serum samples included ASD cases (n = 91) and healthy controls (n = 30) between 6 and 15 years of age. Our findings revealed 251 differentially expressed proteins between ASD and healthy controls, of which 237 proteins were significantly upregulated and 14 proteins were significantly downregulated. Machine learning analysis identified 15 proteins that could be biomarkers for ASD with an area under the curve (AUC) = 0.876 using support vector machine (SVM). Gene Ontology (GO) analysis of the top differentially expressed proteins (TopDE) and weighted gene co-expression analysis (WGCNA) revealed dysregulation of SNARE vesicular transport and ErbB pathways in ASD cases. Furthermore, correlation analysis showed that proteins from those pathways correlate with ASD severity. Further validation and verification of the identified biomarkers and pathways are warranted.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Molecular Sciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/ijms24087443" target="_blank">https://dx.doi.org/10.3390/ijms24087443</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_df5667228f8bd68e3f3b64301a086da3 |
| identifier_str_mv | 10.3390/ijms24087443 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26095225 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot StudyAreej Mesleh (17149822)Hanan Ehtewish (17149825)Alberto de la Fuente (360936)Hawra Al-shamari (18877327)Iman Ghazal (6176756)Fatema Al-Faraj (17281117)Fouad Al-Shaban (17149828)Houari B. Abdesselem (14152827)Mohamed Emara (365494)Nehad M. Alajez (7397276)Abdelilah Arredouani (10914455)Julie Decock (44558)Omar Albagha (8977856)Lawrence W. Stanton (6707191)Sara A. Abdulla (13902015)Omar M. A. El-Agnaf (8809331)Biomedical and clinical sciencesNeurosciencesASDautismbiomarkersearly diagnosisPEAproteomicsblood profilingmachine learningpatient stratification<p dir="ltr">Autism spectrum disorder (ASD) is an umbrella term that encompasses several disabling neurodevelopmental conditions. These conditions are characterized by impaired manifestation in social and communication skills with repetitive and restrictive behaviors or interests. Thus far, there are no approved biomarkers for ASD screening and diagnosis; also, the current diagnosis depends heavily on a physician’s assessment and family’s awareness of ASD symptoms. Identifying blood proteomic biomarkers and performing deep blood proteome profiling could highlight common underlying dysfunctions between cases of ASD, given its heterogeneous nature, thus laying the foundation for large-scale blood-based biomarker discovery studies. This study measured the expression of 1196 serum proteins using proximity extension assay (PEA) technology. The screened serum samples included ASD cases (n = 91) and healthy controls (n = 30) between 6 and 15 years of age. Our findings revealed 251 differentially expressed proteins between ASD and healthy controls, of which 237 proteins were significantly upregulated and 14 proteins were significantly downregulated. Machine learning analysis identified 15 proteins that could be biomarkers for ASD with an area under the curve (AUC) = 0.876 using support vector machine (SVM). Gene Ontology (GO) analysis of the top differentially expressed proteins (TopDE) and weighted gene co-expression analysis (WGCNA) revealed dysregulation of SNARE vesicular transport and ErbB pathways in ASD cases. Furthermore, correlation analysis showed that proteins from those pathways correlate with ASD severity. Further validation and verification of the identified biomarkers and pathways are warranted.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Molecular Sciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/ijms24087443" target="_blank">https://dx.doi.org/10.3390/ijms24087443</a></p>2023-04-18T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/ijms24087443https://figshare.com/articles/journal_contribution/Blood_Proteomics_Analysis_Reveals_Potential_Biomarkers_and_Convergent_Dysregulated_Pathways_in_Autism_Spectrum_Disorder_A_Pilot_Study/26095225CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/260952252023-04-18T06:00:00Z |
| spellingShingle | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study Areej Mesleh (17149822) Biomedical and clinical sciences Neurosciences ASD autism biomarkers early diagnosis PEA proteomics blood profiling machine learning patient stratification |
| status_str | publishedVersion |
| title | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| title_full | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| title_fullStr | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| title_full_unstemmed | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| title_short | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| title_sort | Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study |
| topic | Biomedical and clinical sciences Neurosciences ASD autism biomarkers early diagnosis PEA proteomics blood profiling machine learning patient stratification |