A comparative proteomic analysis for non‐invasive early prediction of hypoxic‐ischemic injury in asphyxiated neonates
Abstract Aim Hypoxic Ischemic Encephalopathy (HIE) is one of the principal causes of neonatal mortality and long‐term morbidity worldwide. The neonatal signs of mild cerebral injury are subtle, making an early precise diagnosis difficult. Delayed detection, poor prognosis, and lack of specific biomarkers for the disease are increasing mortality rates. In this study, we intended to identify specific biomarkers using comparative proteomic analysis to predict the severity of perinatal asphyxia so that its outcome can also be prevented. Experimental Design A case‐control study was conducted on 38 neonates, and urine samples were collected within 24 and 72 h of life. A tandem mass spectrometry‐based quantitative proteomics approach, followed by validation via sandwich ELISA, was performed. Results The LC‐MS/MS‐based proteomics analysis resulted in the identification of 1201 proteins in urine, with 229, 244, and 426 being differentially expressed in HIE‐1, HIE‐2, and HIE‐3, respectively. Axon guidance, Diseases of programmed cell death, and Detoxification of reactive oxygen species pathways were significantly enriched in mild HIE versus severe HIE. Among the differentially expressed proteins in various stages of HIE, we chose to validate four proteins – APP, AGT, FABP1, and FN1 – via sandwich ELISA. Individual and cumulative ROC curves were plotted. AGT and FABP1 together showed high sensitivity, specificity, and accuracy as potential biomarkers for early diagnosis of HIE. Conclusion Establishing putative urinary biomarkers will facilitate clinicians to more accurately screen neonates for brain injury and monitor the disease progression. Prompt treatment of neonates may reduce mortality and neurodevelopmental impairment..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:18 |
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| Enthalten in: |
PROTEOMICS – Clinical Applications - 18(2024), 2 |
| Beteiligte Personen: |
Gurtoo, Sumrati [VerfasserIn] |
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| Anmerkungen: |
© 2024 Wiley‐VCH GmbH. |
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| Umfang: |
18 |
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| doi: |
10.1002/prca.202200054 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
WLY018156975 |
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| 520 | |a Abstract Aim Hypoxic Ischemic Encephalopathy (HIE) is one of the principal causes of neonatal mortality and long‐term morbidity worldwide. The neonatal signs of mild cerebral injury are subtle, making an early precise diagnosis difficult. Delayed detection, poor prognosis, and lack of specific biomarkers for the disease are increasing mortality rates. In this study, we intended to identify specific biomarkers using comparative proteomic analysis to predict the severity of perinatal asphyxia so that its outcome can also be prevented. Experimental Design A case‐control study was conducted on 38 neonates, and urine samples were collected within 24 and 72 h of life. A tandem mass spectrometry‐based quantitative proteomics approach, followed by validation via sandwich ELISA, was performed. Results The LC‐MS/MS‐based proteomics analysis resulted in the identification of 1201 proteins in urine, with 229, 244, and 426 being differentially expressed in HIE‐1, HIE‐2, and HIE‐3, respectively. Axon guidance, Diseases of programmed cell death, and Detoxification of reactive oxygen species pathways were significantly enriched in mild HIE versus severe HIE. Among the differentially expressed proteins in various stages of HIE, we chose to validate four proteins – APP, AGT, FABP1, and FN1 – via sandwich ELISA. Individual and cumulative ROC curves were plotted. AGT and FABP1 together showed high sensitivity, specificity, and accuracy as potential biomarkers for early diagnosis of HIE. Conclusion Establishing putative urinary biomarkers will facilitate clinicians to more accurately screen neonates for brain injury and monitor the disease progression. Prompt treatment of neonates may reduce mortality and neurodevelopmental impairment. | ||
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| 700 | 1 | |a Behera, Santosh Kumar |4 aut | |
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| 700 | 1 | |a Najar, Mohd. Altaf |4 aut | |
| 700 | 1 | |a Modi, Prashant Kumar |4 aut | |
| 700 | 1 | |a KS, Sahana |4 aut | |
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