Cadherin-related family member 3 gene impacts childhood asthma in Chinese children

Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches

INTRODUCTION

To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting asthma using machine-learning approaches.

METHODS

A case-control study with 123 asthmatics and 100 controls was conducted in the Zhuang population in Guangxi. GWAS risk loci were detected using polymerase chain reaction, and clinical data were collected. Machine-learning approaches were used to identify the major factors that contribute to asthma.

RESULTS

A total of 14 GWAS risk loci with clinical data were analyzed on the basis of 10 times the 10-fold cross-validation for all machine-learning models. Using GWAS risk loci or clinical data, the best performances exhibited area under the curve (AUC) values of 64.3% and 71.4%, respectively. Combining GWAS risk loci and clinical data, the XGBoost established the best model with an AUC of 79.7%, indicating that the combination of genetics and clinical data can enable improved performance. We then sorted the importance of features and found the top six risk factors for predicting asthma to be rs3117098, rs7775228, family history, rs2305480, rs4833095, and body mass index.

CONCLUSION

Asthma-prediction models based on GWAS risk loci and clinical data can accurately predict asthma, and thus provide insights into the disease pathogenesis.

Interactive effects between CDHR3 genotype and rhinovirus species for diagnosis and severity of respiratory tract infections in hospitalized children

Rhinovirus (RV) is the leading pathogen causing childhood wheezing, with rhinovirus C (RV-C) species reported to cause asthma exacerbation. Allele A of single-nucleotide polymorphism (SNP) CDHR3_rs6967330 upregulates epithelial expression of RV-C receptors which results in more severe asthma exacerbations in children. Nevertheless, there are limited data on interactions between CDHR3 variants and their impact on severity of RV-related pediatric respiratory tract infections (RTIs). Medical records of RV-related RTIs in children aged below 18 years who were hospitalized in two public hospitals in 2015-2016 were independently reviewed by two paediatricians. Archived nasopharyngeal aspirates were retrieved for RV detection and sequencing as well as CDHR3 genotyping. HaploView v.5.0 and generalized multifactor dimensionality reduction (GMDR) analysis were employed for haplotypic assignment and gene-environment interaction analyses. Among 1019 studied cases, our results confirmed the relationship between RV-C species and more severe RTIs. Besides the top risk variant rs6967330-A, we identified rs140154310-T to be associated with RV-C susceptibility under the additive model [odds ratio (OR) 2.53, 95% CI 1.15-5.56; P = 0.021]. Rs140154310 was associated with wheezing illness (OR 2.38, 95% CI 1.12-5.04; P = 0.024), with such association being stronger in subjects who wheezed due to RV-C infections (OR 2.71, 95% CI 1.32-5.58; P = 0.007). Haplotype GAG constructed from rs4730125, rs6967330, and rs73195665 was associated with increased risk of RV-C infection (OR 1.71, 95% CI 1.11-2.65; P = 0.016) and oxygen supplementation (OR 1.93, 95% CI 1.13-3.30; P = 0.016). GMDR analyses revealed epistatic interaction between rs140154310 and rs6967330 of CDHR3 for RV-C infection (P = 0.001), RV-C-associated lower RTI (P = 0.004), and RV-C-associated wheeze (P = 0.007). There was synergistic gene-environmental interaction between rs3887998 and RV-C for more severe clinical outcomes (P < 0.001). To conclude, rs140154310-T is another risk variant for RV-C susceptibility and more severe RTIs. Synergistic epistatic interaction is found between CDHR3 SNPs and RV-C for RTI severity, which is likely mediated by susceptibility to RV-C. Haplotypic analysis and GMDR should be included in identifying prediction models of CDHR3 for childhood asthma and RTIs. IMPORTANCE This case-control study investigated the interaction between CDHR3 genotypes and rhinovirus (RV) species on disease severity in Hong Kong children hospitalized for respiratory tract infection (RTI). There were synergistic effects between RV-C and CDHR3 SNPs for RTI severity, which was mainly driven by RV-C. Specifically, rs6967330 and rs140154310 alone and their epistatic interaction were associated with RV-C-related and severe RTIs in our subjects. Therefore, genotyping of CDHR3 SNPs may help physicians formulate prediction models for severity of RV-associated RTIs.

Lung Function in Preschool Children in Low and Middle Income Countries: An Under-Represented Potential Tool to Strengthen Child Health

BACKGROUND

The burden of respiratory disease is high in low-middle income countries (LMIC). Pulmonary function tests are useful as an objective measure of lung health and to track progression. Spirometry is the commonest test, but its use is limited in preschool children. Other lung function methods have been developed but their use in LMIC has not been well described.

AIM

To review the use of preschool lung function testing in children in LMIC, with particular reference to feasibility and clinical applications.

METHODS

Electronic databases "PubMed", "Scopus"," Web of Science", and "EBSCO host" were searched for publications in low and middle income countries on preschool lung function testing, including spirometry, fractional exhaled nitric oxide (FeNO), oscillometry, interrupter technique, tidal breathing and multiple breath washout (MBW), from 1 January 2011 to 31 January 2022. Papers in English were included and those including only children ≥6 years were excluded.

RESULT

A total of 61 papers from LMIC in Asia, South America, Africa, Eurasia or the Middle East were included. Of these, 40 included spirometry, 7 FeNO, 15 oscillometry, 2 interrupter technique, and 2 tidal breathing. The papers covered test feasibility (19/61), clinical application (46/61) or epidemiological studies (13/61). Lung function testing was successful in preschool children from LMIC. Spirometry was the most technically demanding and success gradually increased with age.

CONCLUSION

Preschool lung function testing is under-represented in LMIC for the burden of respiratory disease. These tests have the potential to strengthen respiratory care in LMIC, however access needs to be improved.