Ontogeny-related pharmacogene changes in the pediatric liver transcriptome
Richard Meier1, Chengpeng Bi2, Roger Gaedigk2
1Department of Biostatistics, University of Kansas Medical Center.
Pharmacogenetics and Genomics
|January 24, 2018
Summary
Pediatric drug dosing needs improvement beyond size. This study identified key pharmacogenes and pathways in developing livers, revealing age-related changes crucial for accurate medication.
Area of Science:
- Pharmacogenomics
- Pediatric Drug Development
- Liver Development
Background:
- Current pediatric drug dosing primarily relies on adult data adjusted for size and weight.
- Childhood liver development significantly alters drug metabolism, impacting efficacy and safety.
- Understanding ontogeny of liver function is critical for precise pediatric pharmacotherapy.
Purpose of the Study:
- To identify pharmacogenes exhibiting altered expression during childhood liver development.
- To conduct a transcriptome-wide analysis of age-related gene expression changes in the liver.
- To investigate the impact of developmental changes on drug metabolism pathways.
Main Methods:
- Analyzed 47 human liver tissue samples across four pediatric age groups using pair-end sequencing.
- Employed Kruskal-Wallis and Spearman's rank correlation tests to assess age-associated gene expression.
- Utilized KEGG pathway analysis and the gamma method for gene set enrichment, with q-value correction.
Main Results:
- Identified increased expression of key pharmacogenes like F5, ACE, and SLC22A1 with age.
- Observed decreased expression of CYP3A7 transcripts during childhood development.
- Detected significant genome-wide transcriptomic changes, including ADCY1, PTPRD, and others, with implications for the renin-angiotensin pathway.
Conclusions:
- Childhood liver development involves significant, age-dependent changes in pharmacogene expression.
- Increased expression of ACE and PTPRD, alongside renin-angiotensin pathway ontogeny, may influence ACE-inhibitor dosing in children.
- These findings highlight the need for age-specific pharmacogenomic data to optimize pediatric drug therapy.
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