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Biomedical subjects

Robert J Carroll

Publications and source records attributed to Robert J Carroll.

4 recordsLinked to original sources

Systematic common and rare variant association testing in 392,030 whole genomes in All of Us.

Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We present an analysis of the All of Us Research Program v8 release, which includes whole genome sequencing data and harmonized phenotypic information of 392,030 participants after quality control, enabling a unified investigation of rare and common variants across a spectrum of human traits and diseases. We build an extensive phenome- and genome-wide ("All by All") computational framework to perform GWAS and RVAS on 3,602 phenotypes and identify 49,863 approximately independent, high-quality single-variant and gene-level associations. Meta-analyses of All of Us and UK Biobank, with sample sizes as large as 786,871 participants, further enhance statistical power and find 193 pLoF gene-phenotype associations that are not significant in either cohort alone, including 22 associations not highlighted by previous studies. We also present a public interactive browser that integrates association results for common and rare variants to facilitate interpretation and rapid querying of summary statistics, along with supporting documentation, and a Featured Workspace in the All of Us Researcher Workbench. Our framework will apply to iterative data releases as All of Us grows, empowering researchers worldwide to uncover insights into the functional effects of genetic components on complex traits and diseases.

Journal Article

Next-generation phenotyping: introducing phecodeX for enhanced discovery research in medical phenomics.

MOTIVATION: Phecodes are widely used and easily adapted phenotypes based on International Classification of Diseases codes. The current version of phecodes (v1.2) was designed primarily to study common/complex diseases diagnosed in adults; however, there are numerous limitations in the codes and their structure. RESULTS: Here, we present phecodeX, an expanded version of phecodes with a revised structure and 1,761 new codes. PhecodeX adds granularity to phenotypes in key disease domains that are under-represented in the current phecode structure-including infectious disease, pregnancy, congenital anomalies, and neonatology-and is a more robust representation of the medical phenome for global use in discovery research. AVAILABILITY AND IMPLEMENTATION: phecodeX is available at https://github.com/PheWAS/phecodeX.

Phenomics

The phenotype-genotype reference map: Improving biobank data science through replication.

Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.

Humans

CYP2D6 genotype and adverse events to risperidone in children and adolescents.

BACKGROUND: There are few and conflicting data on the role of cytochrome P450 2D6 (CYP2D6) polymorphisms in relation to risperidone adverse events (AEs) in children. This study assessed the association between CYP2D6 metabolizer status and risk for risperidone AEs in children. METHODS: Children ≤18 years with at least 4 weeks of risperidone exposure were identified using BioVU, a de-identified DNA biobank linked to electronic health record data. The primary outcome of this study was AEs. After DNA sequencing, individuals were classified as CYP2D6 poor, intermediate, normal, or ultrarapid CYP2D6 metabolizers. RESULTS: For analysis, the 257 individuals were grouped as poor/intermediate metabolizers (n = 33, 13%) and normal/ultrarapid metabolizers (n = 224, 87%). AEs were more common in poor/intermediate vs. normal/ultrarapid metabolizers (15/33, 46% vs. 61/224, 27%, P = 0.04). In multivariate analysis adjusting for age, sex, race, and initial dose, poor/intermediate metabolizers had increased AE risk (adjusted odds ratio 2.4, 95% confidence interval 1.1-5.1, P = 0.03). CONCLUSION: Children with CYP2D6 poor or intermediate metabolizer phenotypes are at greater risk for risperidone AEs. Pre-prescription genotyping could identify this high-risk subset for an alternate therapy, risperidone dose reduction, and/or increased monitoring for AEs.

Adolescent