Putting the "mi" in omics: discovering miRNA biomarkers for pediatric precision care
In the past decade, growing interest in micro-ribonucleic acids (miRNAs) has catapulted these small, non-coding nucleic acids to the forefront of biomarker research. Advances in scientific knowledge have made it clear that miRNAs play a vital role in regulating cellular physiology throughout the human body. Perturbations in miRNA signaling have also been described in a variety of pediatric conditions—from cancer, to renal failure, to traumatic brain injury. Likewise, the number of studies across pediatric disciplines that pair patient miRNA-omics with longitudinal clinical data are growing. Analyses of these voluminous, multivariate data sets require understanding of pediatric phenotypic data, data science, and genomics. Use of machine learning techniques to aid in biomarker detection have helped decipher background noise from biologically meaningful changes in the data. Further, emerging research suggests that miRNAs may have potential as therapeutic targets for pediatric precision care. Here, we review current miRNA biomarkers of pediatric diseases and studies that have combined machine learning techniques, miRNA-omics, and patient health data to identify novel biomarkers and potential therapeutics for pediatric diseases.
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s41390-022-02206-5
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Work Title Putting the "mi" in omics: discovering miRNA biomarkers for pediatric precision care Access Creators - Chengyin Li
- Rhea E Sullivan
- Dongxiao Zhu
- Steven Hicks
Keyword - Biomarkers
- Epigenetics
- Pediatrics
- Machine Learning
- MicroRNA
- Therapeutics
License In Copyright (Rights Reserved) Work Type Article Publisher - Pediatric Research
Publication Date July 29, 2022 Publisher Identifier (DOI) - https://doi.org/10.1038/s41390-022-02206-5
Deposited February 27, 2023 Versions
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PR_2022_0231_Proofs.pdf -
Added Creator C Li
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Added Creator R E Sullivan
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- Biomarkers, Epigenetics, Pediatrics, Machine Learning, MicroRNA, Therapeutics
Pediatr Res.- Pediatric Research
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Renamed Creator Chengyin Li Show Changes
C Li- Chengyin Li
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Renamed Creator Rhea E Sullivan Show Changes
R E Sullivan- Rhea E Sullivan
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Renamed Creator Dongxiao Zhu Show Changes
D Zhu- Dongxiao Zhu
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Updated Description Show ChangesDescription
See abstract online- In the past decade, growing interest in micro-ribonucleic acids (miRNAs) has catapulted these small, non-coding nucleic acids to the forefront of biomarker research. Advances in scientific knowledge have made it clear that miRNAs play a vital role in regulating cellular physiology throughout the human body. Perturbations in miRNA signaling have also been described in a variety of pediatric conditions—from cancer, to renal failure, to traumatic brain injury. Likewise, the number of studies across pediatric disciplines that pair patient miRNA-omics with longitudinal clinical data are growing. Analyses of these voluminous, multivariate data sets require understanding of pediatric phenotypic data, data science, and genomics. Use of machine learning techniques to aid in biomarker detection have helped decipher background noise from biologically meaningful changes in the data. Further, emerging research suggests that miRNAs may have potential as therapeutic targets for pediatric precision care. Here, we review current miRNA biomarkers of pediatric diseases and studies that have combined machine learning techniques, miRNA-omics, and patient health data to identify novel biomarkers and potential therapeutics for pediatric diseases.
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