Household mold exposure interacts with inflammation-related genetic variants on childhood asthma: a case-control study

Childhood asthma and mould in homes-A meta-analysis

Asthma is a multifaceted and multicausal disease. Childhood asthma is strongly influenced by genetic traits and is characterized by hyperreactivity of the airways so that also unspecific triggers including moulds can trigger an asthma attack. Therefore, it is undisputed that moulds in the home can cause asthma attacks in asthmatic children. It is, however, unclear if mould in homes also induce the development of asthma. Because more and more severe attacks in asthmatic children living in mouldy homes might speed up the diagnosis of asthma, cross-sectional studies are not well-suited to differentiate between mould as a causative or only as a precipitating factor. Cross-sectional studies show an increased asthma risk and poorer lung function in children living in mouldy homes. To better understand the causal role of mould in homes, a systematic review was performed with random effects meta-analysis focusing on cohort and case-control studies only.We found 21 case-control and 11 cohort studies examining the association between mould at home and later advent of childhood asthma. According to the case-control studies, mouldy homes increase the risk of asthma by 53% (95 confidence interval [CI]: 42-65%) with no evidence of heterogeneity or publication bias. Risk estimates based on cohort studies were smaller with 15% (1-31%). The cohort studies also showed no publication bias but substantial heterogeneity (I2 = 60.5, p = 0.005). Heterogeneity could be partly explained by percentage of male children, age of participants, and publication year, but was not affected by study quality.In conclusion, living in mouldy homes during childhood seems to increase the risk of later developing bronchial asthma.

New Insights Relating Gasdermin B to the Onset of Childhood Asthma

Chromosome 17q12-q21 is the most replicated genetic locus for childhood-onset asthma. Polymorphisms in this locus containing ∼10 genes interact with a variety of environmental exposures in the home and outdoors to modify asthma risk. However, the functional basis for these associations and their linkages to the environment have remained enigmatic. Within this extended region, regulation of GSDMB (gasdermin B) expression in airway epithelial cells has emerged as the primary mechanism underlying the 17q12-q21 genome-wide association study signal. Asthma-associated SNPs influence the abundance of GSDMB transcripts as well as the functional properties of GSDMB protein in airway epithelial cells. GSDMB is a member of the gasdermin family of proteins, which regulate pyroptosis and inflammatory responses to microbial infections. The aims of this review are to synthesize recent studies on the relationship of 17q12-q21 SNPs to childhood asthma and the evidence pointing to GSDMB gene expression or protein function as the underlying mechanism and to explore the potential functions of GSDMB that may influence the risk of developing asthma during childhood.

Gene-environment interactions in childhood asthma revisited; expanding the interaction concept

Investigation of gene-environment interactions (GxE) may provide important insights into the gene regulatory framework in response to environmental factors of relevance for childhood asthma. Over the years, different methodological strategies have been applied, more recently using genome-wide approaches. The best example to date is the major asthma locus on the 17q12-21 chromosome region, viral infections, and airway epithelium processes where recent studies have shed much light on mechanisms in childhood asthma. However, there are challenges with the traditional single variant-single exposure interaction models, as they do not encompass the complexity and cumulative effects of multiple exposures or multiple genetic variants. As such, we need to redefine our traditional GxE thinking, and we propose in this review to expand the GxE concept by also evaluating other omics layers, such as epigenetics, transcriptomics, metabolomics, and proteomics. In addition, host factors such as age, gender, and other exposures are very likely to influence GxE effects and need firmly to be considered in future studies.