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Multiancestral polygenic risk score for pediatric asthma
Bahram Namjou1, Michael Lape2, Edyta Malolepsza3
1Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio.
Insights
A new polygenic risk score (PRS) effectively identifies children at increased risk for asthma across diverse ancestries. This genetic tool aids in predicting asthma occurrence and understanding its genetic links.
Area of Science:
- Genetics
- Pediatrics
- Computational Biology
Background:
- Asthma is a leading chronic condition and cause of hospitalization in children.
- Existing genome-wide association studies (GWAS) have identified numerous genetic loci for asthma.
- A polygenic risk score (PRS) with predictive value across diverse ancestries for asthma has not been established.
Purpose of the Study:
- To develop and validate a multiancestral PRS for predicting asthma in pediatric populations.
- To assess the PRS's predictive performance across various ancestral groups.
- To explore shared genetic etiology between asthma and other phenotypes using the PRS.
Main Methods:
- Utilized a Bayesian regression framework and GWAS summary statistics from the Trans-National Asthma Genetic Consortium.
- Trained the PRS on one Electronic Medical Records and Genomics (eMERGE) cohort and validated it on a second independent eMERGE cohort.
- Replicated findings using UK Biobank data and performed phenome-wide association studies (PheWAS) with the PRS.
Main Results:
- The multiancestral asthma PRS demonstrated significant association with asthma in pediatric validation datasets (AUCs ranging from 0.66 to 0.70).
- The PRS showed predictive capability across diverse ancestries, including European, African, admixed American, Southeast Asian, and East Asian populations.
- Individuals in the top 5% PRS had significantly increased odds of asthma (2.80-5.82 times) compared to the bottom 5%.
Conclusions:
- A multiancestral PRS derived from Bayesian posterior genomic effect sizes effectively identifies increased odds of pediatric asthma.
- The developed PRS holds potential for predicting asthma risk in diverse pediatric cohorts.
- The PRS also highlights shared genetic underpinnings with other asthma-related phenotypes.
Background:
Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.
Objectives:
This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.
Methods:
This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.
Results:
The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes.
Conclusions:
A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.
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