Predicting allergic diseases in children using genome-wide association study (GWAS) data and family history

Abstract

The recent rise in the prevalence of chronic allergic diseases among children has increased disease burden and reduced quality of life, especially for children with comorbid allergic diseases. Predicting the occurrence of allergic diseases can help prevent its onset for those in high risk groups. Herein, we aimed to construct prediction models for asthma, atopic dermatitis (AD), and asthma-AD comorbidity (also known as atopic march) using a genome-wide association study (GWAS) and family history data from patients of Korean heritage. Among 973 patients and 481 healthy controls, we evaluated single nucleotide polymorphism (SNP) heritability for each disease using genome-based restricted maximum likelihood (GREML) analysis. We then compared the performance of prediction models constructed using Least Absolute Shrinkage and Selection Operator (LASSO) and penalized ridge regression methods. Our results indicate that the addition of family history risk scores to the prediction model greatly increase the predictability of asthma and asthma-AD comorbidity. However, prediction of AD was mostly attributable to GWAS SNPs.

Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity

“…We also demonstrated that the greater diversity of GBMI improved polygenic prediction in asthma, particularly for populations of non-European ancestry. Previous studies on asthma PRS in the literature have primarily focused on using PRS to predict asthma in pediatric cohorts, and overall found limited performance of PRS [28][29][30]85 . Most of these studies used the P+T approach, while a recently published paper, Namjou et al (2022) 32 , applied PRS-CS to the TAGC multi-ancestry GWAS and found improved discriminatory power of their PRS (receiver-operating characteristic area under the curve, or AUC, of 0.66-0.70 across two pediatric cohorts) compared to the prior studies that used P+T.…”

Intrinsic Effects of Exposome in Atopic Dermatitis: Genomics, Epigenomics and Regulatory Layers

“…One of the most profound applications of GWAS-derived data refers to the calculation of polygenic risk scores (PRSs), which summarize the impact of genetic variants in the disease predisposition to a single score, thereby providing an individualized framework for early risk assessment and preventive measures [ 30 , 31 ]. Genetic scores in AD have demonstrated the significant implication of exposure covariates in PRS calculations, including sex, age, and family history risk scores.…”

Cows’ Milk Allergy-Associated Constipation: When to Look for It? A Narrative Review

“…Environmental, behavioural, immunological and genetic factors may contribute to functional constipation [ 9 , 12 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. The typical mechanism is behavioural stool withholding because of pain, inflammation or anal fissure, which can lead to a vicious cycle of large, firm, painful stools and further withholding [ 12 , 18 , 19 , 20 , 21 , 22 ].…”

“…Twin studies demonstrate that 59% of childhood constipation can be explained by genetic predisposition [ 36 ], although the exact genetic mechanisms are yet to be defined [ 9 ]. Of note, in allergy, atopy and autism, complex polygenic influences have been suggested [ 37 , 38 , 39 , 40 ]. Moreover, in autistic children a 50% prevalence of FC [ 23 ] and double the rate of food allergy has been reported compared to controls [ 41 ].…”