Reanalysis of pediatric exome and genome sequencing identifies a high prevalence of actionable pharmacogenetic alleles in children
Clinical Genetics and Therapeutics
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Primary Categories:
- Genomic Medicine
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Secondary Categories:
- Genomic Medicine
Introduction:
Pharmacogenetics describes the relationship between genetic variants and medication effectiveness. Medications with well-described pharmacogenetic associations are commonly used in children. Pharmacogenetics has not been integrated into standard pediatrics and represents an opportunity to personalize and improve care. Genetic sequencing is a widely utilized diagnostic tool. Exome sequencing and genome sequencing are broad genetic tests that can readily identify pharmacogenetic alleles, but this information is not often captured. This study seeks to reanalyze pediatric sequencing data to characterize the prevalence of actionable pharmacogenetic alleles and correlate alleles with administration of actionable medications.
Methods:
Previously generated exome and genome sequencing data at the Children’s Hospital of Philadelphia was reanalyzed with the PharmCAT v.2.9 tool to identify pharmacogenetic phenotypes for genes with known pharmacogenetic associations. Exome sequencing was generated from children undergoing clinical testing for a variety of indications. Genome sequencing data was generated from subjects enrolled in the Birth Defects Biorepository. Clinical data was accessed through the ARCUS system, which provides de-identified access to medication administrations and diagnostic codes. We focused our medication data on inpatient medication usage. We compared pharmacogenetic phenotypes with medication exposures to identify opportunities for personalized medication dosing.
Results:
The most prescribed inpatient medications included ondansetron and ibuprofen. Actionable pharmacogenetic variants were common, with at least 80% of participants carrying an actionable pharmacogenetic allele. Many children had multiple actionable variants. We identified numerous opportunities for pharmacogenetic optimized dosing.
Conclusion:
Exome and genome sequencing can readily be reanalyzed to identify pharmacogenetic variants and phenotypes. Drugs with known pharmacogenetic associations are used in the inpatient pediatric setting. Children with actionable pharmacogenetic variants are commonly prescribed medications that can be optimized with their genetic information. This study identifies an opportunity to use previously generated information to improve the safety and efficacy of medications commonly given to children.
Pharmacogenetics describes the relationship between genetic variants and medication effectiveness. Medications with well-described pharmacogenetic associations are commonly used in children. Pharmacogenetics has not been integrated into standard pediatrics and represents an opportunity to personalize and improve care. Genetic sequencing is a widely utilized diagnostic tool. Exome sequencing and genome sequencing are broad genetic tests that can readily identify pharmacogenetic alleles, but this information is not often captured. This study seeks to reanalyze pediatric sequencing data to characterize the prevalence of actionable pharmacogenetic alleles and correlate alleles with administration of actionable medications.
Methods:
Previously generated exome and genome sequencing data at the Children’s Hospital of Philadelphia was reanalyzed with the PharmCAT v.2.9 tool to identify pharmacogenetic phenotypes for genes with known pharmacogenetic associations. Exome sequencing was generated from children undergoing clinical testing for a variety of indications. Genome sequencing data was generated from subjects enrolled in the Birth Defects Biorepository. Clinical data was accessed through the ARCUS system, which provides de-identified access to medication administrations and diagnostic codes. We focused our medication data on inpatient medication usage. We compared pharmacogenetic phenotypes with medication exposures to identify opportunities for personalized medication dosing.
Results:
The most prescribed inpatient medications included ondansetron and ibuprofen. Actionable pharmacogenetic variants were common, with at least 80% of participants carrying an actionable pharmacogenetic allele. Many children had multiple actionable variants. We identified numerous opportunities for pharmacogenetic optimized dosing.
Conclusion:
Exome and genome sequencing can readily be reanalyzed to identify pharmacogenetic variants and phenotypes. Drugs with known pharmacogenetic associations are used in the inpatient pediatric setting. Children with actionable pharmacogenetic variants are commonly prescribed medications that can be optimized with their genetic information. This study identifies an opportunity to use previously generated information to improve the safety and efficacy of medications commonly given to children.