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Developing and evaluating pediatric phecodes (Peds-Phecodes) for high-throughput phenotyping using electronic health
Monika E Grabowska1, Sara L Van Driest2, Jamie R Robinson1,3
1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
Insights
Pediatric phecodes (Peds-Phecodes) were developed to improve the analysis of childhood diseases. These specialized codes enhance genotype-phenotype association studies in children, offering superior results compared to existing methods.
Area of Science:
- Genomics
- Pediatric Medicine
- Bioinformatics
Background:
- Existing phecodes inadequately represent the unique disease spectrum in pediatric patients.
- Accurate phenotyping is crucial for understanding pediatric diseases and genetic associations.
Purpose of the Study:
- To develop specialized pediatric phecodes (Peds-Phecodes) for efficient, large-scale phenotypic analysis in children.
- To enhance the capture of pediatric-specific phenotypes from electronic health records (EHRs).
Main Methods:
- A hybrid data- and knowledge-driven approach was used, modifying existing phecodes with EHR and genetic data.
- Phenotype prevalence was compared between pediatric and adult populations to identify distinct conditions.
- Clinical domain expertise was applied to refine and create pediatric-relevant phecodes.
- Phenome-wide association studies (PheWAS) were used to validate Peds-Phecodes against existing phecodes.
Main Results:
- Peds-Phecodes aggregate 15,533 ICD-9-CM and 82,949 ICD-10-CM codes into 2051 distinct phecodes.
- Peds-Phecodes demonstrated superior replication of known pediatric genotype-phenotype associations (248 vs. 192) compared to standard phecodes.
- The developed Peds-Phecodes showed higher quality pediatric phenotype capture.
Conclusions:
- Peds-Phecodes represent a high-throughput phenotyping tool specifically for pediatric populations.
- Validation through genetic replication studies confirms the utility of Peds-Phecodes.
- Peds-Phecodes are expected to facilitate large-scale phenomic and genomic research in pediatrics, potentially uncovering novel associations.
Objective:
Pediatric patients have different diseases and outcomes than adults; however, existing phecodes do not capture the distinctive pediatric spectrum of disease. We aim to develop specialized pediatric phecodes (Peds-Phecodes) to enable efficient, large-scale phenotypic analyses of pediatric patients.
Materials And Methods:
We adopted a hybrid data- and knowledge-driven approach leveraging electronic health records (EHRs) and genetic data from Vanderbilt University Medical Center to modify the most recent version of phecodes to better capture pediatric phenotypes. First, we compared the prevalence of patient diagnoses in pediatric and adult populations to identify disease phenotypes differentially affecting children and adults. We then used clinical domain knowledge to remove phecodes representing phenotypes unlikely to affect pediatric patients and create new phecodes for phenotypes relevant to the pediatric population. We further compared phenome-wide association study (PheWAS) outcomes replicating known pediatric genotype-phenotype associations between Peds-Phecodes and phecodes.
Results:
The Peds-Phecodes aggregate 15 533 ICD-9-CM codes and 82 949 ICD-10-CM codes into 2051 distinct phecodes. Peds-Phecodes replicated more known pediatric genotype-phenotype associations than phecodes (248 vs 192 out of 687 SNPs, P < .001).
Discussion:
We introduce Peds-Phecodes, a high-throughput EHR phenotyping tool tailored for use in pediatric populations. We successfully validated the Peds-Phecodes using genetic replication studies. Our findings also reveal the potential use of Peds-Phecodes in detecting novel genotype-phenotype associations for pediatric conditions. We expect that Peds-Phecodes will facilitate large-scale phenomic and genomic analyses in pediatric populations.
Conclusion:
Peds-Phecodes capture higher-quality pediatric phenotypes and deliver superior PheWAS outcomes compared to phecodes.
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