Psychosocial experiences modulate asthma-associated genes through gene-environment interactions

Association between PRKG1 gene and gene-environment interactions with pediatric asthma

OBJECTIVE

To investigate the relationship between single nucleotide polymorphisms (SNPs) of cGMP-dependent protein kinase I (PRKG1) gene and gene-environment interactions with bronchial asthma in children.

METHODS

109 asthma patients and 158 healthy controls from the General Hospital of Northern Theater Command were enrolled, based case-control study. The iMLDR® multiple SNP typing technique was applied to detect the genotypes of rs7903366, rs7081864, rs7070958 and rs7897633 in PRKG1 gene. The percentage of eosinophils (EOS%) in peripheral blood and serum immunoglobulin E (IgE) in the case group were also measured. Gene-environment interactions were examined using the generalized multi-factor dimensionality reduction (GMDR) method.

RESULTS

There were polymorphisms in four SNPs of PRKG1 gene in the case and control groups. The genotype and allele frequencies distribution of rs7897633 demonstrated statistical significance (p < 0.05). There were no statistically significant differences in EOS% and IgE among genotypes at the four SNPs of PRKG1 gene (p > 0.05). The haplotypes CAGA and TGAC presented significant association with asthma risk (p < 0.05). The four-factor model indicated a potential gene-environment interaction in rs7897633, allergen exposure, residence, and environmental tobacco smoke (ETS) exposure (p < 0.05).

CONCLUSIONS

The rs7897633 in PRKG1 gene was associated with susceptibility to childhood asthma, and C allele is a protective factor. The haplotype CAGA had a protective effect against asthma risk and TGAC was linked to the high risk of developing asthma. Moreover, the interaction of rs7897633, allergen exposure, residence, and ETS exposure conferred susceptibility to childhood asthma.

Genotype × environment interactions in gene regulation and complex traits

Genotype × environment interactions (GxE) have long been recognized as a key mechanism underlying human phenotypic variation. Technological developments over the past 15 years have dramatically expanded our appreciation of the role of GxE in both gene regulation and complex traits. The richness and complexity of these datasets also required parallel efforts to develop robust and sensitive statistical and computational approaches. Although our understanding of the genetic architecture of molecular and complex traits has been maturing, a large proportion of complex trait heritability remains unexplained. Furthermore, there are increasing efforts to characterize the effect of environmental exposure on human health. We therefore review GxE in human gene regulation and complex traits, advocating for a comprehensive approach that jointly considers genetic and environmental factors in human health and disease.

Socioeconomic inequalities in early adulthood disrupt the immune transcriptomic landscape via upstream regulators

Disparities in socio-economic status (SES) predict many immune system-related diseases, and previous research documents relationships between SES and the immune cell transcriptome. Drawing on a bioinformatically-informed network approach, we situate these findings in a broader molecular framework by examining the upstream regulators of SES-associated transcriptional alterations. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of 4543 adults in the United States. Results reveal a network-of differentially expressed genes, transcription factors, and protein neighbors of transcription factors-that shows widespread SES-related dysregulation of the immune system. Mediational models suggest that body mass index (BMI) plays a key role in accounting for many of these associations. Overall, the results reveal the central role of upstream regulators in socioeconomic differences in the molecular basis of immunity, which propagate to increase risk of chronic health conditions in later-life.

CLDN1 silencing suppresses the proliferation and migration of airway smooth muscle cells by modulating MMP14

Airway remodeling is an important pathologic factor in the progression of asthma. Abnormal proliferation and migration of airway smooth muscle cells (ASMCs) are important pathologic mechanisms in severe asthma. In the current study, claudin-1 (CLDN1) was identified as an asthma-related gene and was upregulated in ASMCs stimulated with platelet-derived growth factor BB (PDGF-BB). Cell counting kit-8 and EdU assays were used to evaluate cell proliferation, and transwell assay was carried out to analyze cell migration and invasion. The levels of inflammatory factors were detected using enzyme-linked immunosorbent assay. The results showed that CLDN1 knockdown inhibited the proliferation, migration, invasion, and inflammation of ASMCs treated with PDGF-BB, whereas overexpression of CLDN1 exhibited the opposite effects. Protein-protein interaction assay and co-immunoprecipitation revealed that CLDN1 directly interacted with matrix metalloproteinase 14 (MMP14). CLDN1 positively regulated MMP14 expression in asthma, and MMP14 overexpression reversed cell proliferation, migration, invasion, and inflammation induced by silenced CLDN1. Taken together, CLDN1 promotes PDGF-BB-induced cell proliferation, migration, invasion, and inflammatory responses of ASMCs by upregulating MMP14 expression, suggesting a potential role for CLDN1 in airway remodeling in asthma.

Socioeconomic inequalities in young adulthood disrupt the immune transcriptomic landscape via upstream regulators

Disparities in socio-economic status (SES) predict many immune system-related diseases, and previous research documents relationships between SES and the immune cell transcriptome. Drawing on a bioinformatically-informed network approach, we situate these findings in a broader molecular framework by examining the upstream regulators of SES-associated transcriptional alterations. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of 4,543 adults in the United States. Results reveal a network-of differentially-expressed genes, transcription factors, and protein neighbors of transcription factors- that shows widespread SES-related dysregulation of the immune system. Mediational models suggest that body mass index plays a key role in accounting for many of these associations. Overall, the results reveal the central role of upstream regulators in socioeconomic differences in the molecular basis of immunity, which propagate to increase risk of chronic health conditions in later-life.

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution

Synthetic glucocorticoids, such as dexamethasone, have been used as a treatment for many immune conditions, such as asthma and, more recently, severe COVID-19. Single-cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single-cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated peripheral blood mononuclear cells from 96 African American children. We used novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we showed that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and showed widespread genetic regulation of the transcriptional dynamics of the gene expression response.

Gene-environment interactions and their impact on human health

The molecular processes underlying human health and disease are highly complex. Often, genetic and environmental factors contribute to a given disease or phenotype in a non-additive manner, yielding a gene-environment (G × E) interaction. In this work, we broadly review current knowledge on the impact of gene-environment interactions on human health. We first explain the independent impact of genetic variation and the environment. We next detail well-established G × E interactions that impact human health involving environmental toxicants, pollution, viruses, and sex chromosome composition. We conclude with possibilities and challenges for studying G × E interactions.

Analysis of transcriptional changes in the immune system associated with pubertal development in a longitudinal cohort of children with asthma

Puberty is an important developmental period marked by hormonal, metabolic and immune changes. Puberty also marks a shift in sex differences in susceptibility to asthma. Yet, little is known about the gene expression changes in immune cells that occur during pubertal development. Here we assess pubertal development and leukocyte gene expression in a longitudinal cohort of 251 children with asthma. We identify substantial gene expression changes associated with age and pubertal development. Gene expression changes between pre- and post-menarcheal females suggest a shift from predominantly innate to adaptive immunity. We show that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.

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.

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single cell resolution.. [PMID: 35313584 PMCID: PMC8936121 DOI: 10.1101/2021.09.30.462672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Synthetic glucocorticoids, such as dexamethasone, have been used as treatment for many immune conditions, such as asthma and more recently severe COVID-19. Single cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.

Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type, and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing and were highly variable across contexts. For thousands of genes, we identified variable allelic expression across contexts and characterized different types of gene-environment interactions, many of which are associated with complex traits. Promoter functional and evolutionary features distinguished genes with elevated allelic imbalance mean and variance. On average, half of the genes with dynamic regulatory interactions were missed by large eQTL mapping studies, indicating the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.