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Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis
The biochemical identification of carotid artery stenosis (CAS) is still a challenge. Hence, 349 male subjects (176 normal controls and 173 stroke patients with extracranial CAS ≥ 50% diameter stenosis) were recruited. Blood samples were collected 14 days after stroke onset with no acute illness. Ca...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9563778/ https://www.ncbi.nlm.nih.gov/pubmed/36230983 http://dx.doi.org/10.3390/cells11193022 |
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author | Lin, Chia-Ni Hsu, Kai-Cheng Huang, Kuo-Lun Huang, Wen-Cheng Hung, Yi-Lun Lee, Tsong-Hai |
author_facet | Lin, Chia-Ni Hsu, Kai-Cheng Huang, Kuo-Lun Huang, Wen-Cheng Hung, Yi-Lun Lee, Tsong-Hai |
author_sort | Lin, Chia-Ni |
collection | PubMed |
description | The biochemical identification of carotid artery stenosis (CAS) is still a challenge. Hence, 349 male subjects (176 normal controls and 173 stroke patients with extracranial CAS ≥ 50% diameter stenosis) were recruited. Blood samples were collected 14 days after stroke onset with no acute illness. Carotid plaque score (≥2, ≥5 and ≥8) was used to define CAS severity. Serum metabolites were analyzed using a targeted Absolute IDQ(®)p180 kit. Results showed hypertension, diabetes, smoking, and alcohol consumption were more common, but levels of diastolic blood pressure, HDL-C, LDL-C, and cholesterol were lower in CAS patients than controls (p < 0.05), suggesting intensive medical treatment for CAS. PCA and PLS-DA did not demonstrate clear separation between controls and CAS patients. Decision tree and random forest showed that acylcarnitine species (C4, C14:1, C18), amino acids and biogenic amines (SDMA), and glycerophospholipids (PC aa C36:6, PC ae C34:3) contributed to the prediction of CAS. Metabolite panel analysis showed high specificity (0.923 ± 0.081, 0.906 ± 0.086 and 0.881 ± 0.109) but low sensitivity (0.230 ± 0.166, 0.240 ± 0.176 and 0.271 ± 0.169) in the detection of CAS (≥2, ≥5 and ≥8, respectively). The present study suggests that metabolomics profiles could help in differentiating between controls and CAS patients and in monitoring the progression of CAS. |
format | Online Article Text |
id | pubmed-9563778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95637782022-10-15 Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis Lin, Chia-Ni Hsu, Kai-Cheng Huang, Kuo-Lun Huang, Wen-Cheng Hung, Yi-Lun Lee, Tsong-Hai Cells Article The biochemical identification of carotid artery stenosis (CAS) is still a challenge. Hence, 349 male subjects (176 normal controls and 173 stroke patients with extracranial CAS ≥ 50% diameter stenosis) were recruited. Blood samples were collected 14 days after stroke onset with no acute illness. Carotid plaque score (≥2, ≥5 and ≥8) was used to define CAS severity. Serum metabolites were analyzed using a targeted Absolute IDQ(®)p180 kit. Results showed hypertension, diabetes, smoking, and alcohol consumption were more common, but levels of diastolic blood pressure, HDL-C, LDL-C, and cholesterol were lower in CAS patients than controls (p < 0.05), suggesting intensive medical treatment for CAS. PCA and PLS-DA did not demonstrate clear separation between controls and CAS patients. Decision tree and random forest showed that acylcarnitine species (C4, C14:1, C18), amino acids and biogenic amines (SDMA), and glycerophospholipids (PC aa C36:6, PC ae C34:3) contributed to the prediction of CAS. Metabolite panel analysis showed high specificity (0.923 ± 0.081, 0.906 ± 0.086 and 0.881 ± 0.109) but low sensitivity (0.230 ± 0.166, 0.240 ± 0.176 and 0.271 ± 0.169) in the detection of CAS (≥2, ≥5 and ≥8, respectively). The present study suggests that metabolomics profiles could help in differentiating between controls and CAS patients and in monitoring the progression of CAS. MDPI 2022-09-27 /pmc/articles/PMC9563778/ /pubmed/36230983 http://dx.doi.org/10.3390/cells11193022 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lin, Chia-Ni Hsu, Kai-Cheng Huang, Kuo-Lun Huang, Wen-Cheng Hung, Yi-Lun Lee, Tsong-Hai Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis |
title | Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis |
title_full | Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis |
title_fullStr | Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis |
title_full_unstemmed | Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis |
title_short | Identification of Metabolomics Biomarkers in Extracranial Carotid Artery Stenosis |
title_sort | identification of metabolomics biomarkers in extracranial carotid artery stenosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9563778/ https://www.ncbi.nlm.nih.gov/pubmed/36230983 http://dx.doi.org/10.3390/cells11193022 |
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