Genetic associations of the response to inhaled corticosteroids in asthma: a systematic review

Altered static and dynamic functional network connectivity and combined Machine learning in asthma

Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. Previous neuroimaging studies have shown structural and functional abnormalities in the brains of individuals with asthma. However, earlier research has primarily focused on static changes in brain activity, neglecting the effects of asthma on the dynamic characteristics of functional brain networks. This study included 31 asthma patients and 31 healthy controls (HCs). Independent component analysis (ICA) was employed to extract changes in static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) from the acquired data. Compared to the HC group, the overall functional connectivity (FC) within the visual network (VN) in asthma patients declined, whereas the FC in the auditory network (AN) and cerebellar network (CN) increased. Additionally, functional network connectivity (FNC) analysis revealed enhanced connectivity between the VN and AN, as well as between the VN and executive control network (ECN), while AN-AN functional connectivity was reduced. The dFNC was primarily characterized by abnormal connections among the default mode network (DMN), AN, and other brain regions. The support vector machine (SVM) model based on FC and FNC demonstrates excellent performance in distinguishing asthma patients from HCs. Our findings highlight significant alterations in functional connectivity within the sFNC and dFNC of asthma patients. These results enhance our understanding of the potential neurobiological mechanisms underlying emotional deficits and cognitive impairments in asthma patients. Furthermore, they provide additional neuroimaging evidence that may be helpful for researchers in identifying potential neurobiological markers to differentiate asthma patients from HCs.

Single cell analysis identifies distinct CD4 + T cells associated with the pathobiology of pediatric obesity related asthma

Pediatric obesity-related asthma is characterized by non-atopic T helper 1 (Th1) inflammation and steroid resistance. CDC42 upregulation in CD4 + T cells underlies Th1 inflammation but the CD4 + T cell subtype(s) with CDC42 upregulation and their contribution to steroid resistance are not known. Compared to healthy-weight asthma, obesity-alone and healthy-weight controls, single-cell transcriptomics of obese asthma CD4 + T cells revealed CDC42 upregulation in 3 clusters comprised of naïve and central memory T cells, which differed from the cluster enriched for Th1 responses that was comprised of effector T cells. NR3C1, coding for the glucocorticoid receptor, was downregulated, while genes coding for NLRP3 inflammasome were upregulated, in clusters with CDC42 upregulation and Th1 responses. Conserved genes in these clusters correlated with pulmonary function deficits in obese asthma. These findings suggest that several distinct CD4 + T cell subtypes are programmed in obese asthma for CDC42 upregulation, Th1 inflammation, and steroid resistance, and together contribute to the obese asthma phenotype.

Single-cell analysis identifies distinct CD4+ T cells associated with the pathobiology of pediatric obesity-related asthma

Pediatric obesity-related asthma is characterized by non-atopic T helper 1 (Th1) inflammation and steroid resistance. CDC42 upregulation in CD4+T cells underliesTh1 inflammation but the CD4+T cell subtype(s) with CDC42 upregulation and their contribution to steroid resistance are not known. Compared to healthy-weight asthma, obesity-alone and healthy-weight controls, single-cell transcriptomics of obese asthma CD4+T cells revealed CDC42 upregulation in 3 clusters comprised of naïve and central memory T cells, which differed from the cluster enriched for Th1 responses that was comprised of effector T cells. NR3C1, coding for glucocorticoid receptor, was downregulated, while genes coding for NLRP3 inflammasome were upregulated, in clusters with CDC42 upregulation and Th1 responses. Conserved genes in these clusters correlated with pulmonary function deficits in obese asthma. These findings suggest that several distinct CD4+T cell subtypes are programmed in obese asthma for CDC42 upregulation, Th1 inflammation, and steroid resistance, and together contribute to obese asthma phenotype.

Summary

CD4+T cells from obese children with asthma are distinctly programmed for non-allergic immune responses, steroid resistance and inflammasome activation, that underlie the obese asthma phenotype.

Impact of CYP3A5 Polymorphisms on Pediatric Asthma Outcomes

Genetic variation among inhaled corticosteroid (ICS)-metabolizing enzymes may affect asthma control, but evidence is limited. This study tested the hypothesis that single-nucleotide polymorphisms (SNPs) in Cytochrome P450 3A5 (CYP3A5) would affect asthma outcomes. Patients aged 2-18 years with persistent asthma were recruited to use the electronic AsthmaTracker (e-AT), a self-monitoring tool that records weekly asthma control, medication use, and asthma outcomes. A subset of patients provided saliva samples for SNP analysis and participated in a pharmacokinetic study. Multivariable regression analysis adjusted for age, sex, race, and ethnicity was used to evaluate the impact of CYP3A5 SNPs on asthma outcomes, including asthma control (measured using the asthma symptom tracker, a modified version of the asthma control test or ACT), exacerbations, and hospital admissions. Plasma corticosteroid and cortisol concentrations post-ICS dosing were also assayed using liquid chromatography-tandem mass spectrometry. Of the 751 patients using the e-AT, 166 (22.1%) provided saliva samples and 16 completed the PK study. The e-AT cohort was 65.1% male, and 89.6% White, 6.0% Native Hawaiian, 1.2% Black, 1.2% Native American, 1.8% of unknown race, and 15.7% Hispanic/Latino; the median age was 8.35 (IQR: 5.51-11.3) years. CYP3A5*3/*3 frequency was 75.8% in White subjects, 50% in Native Hawaiians and 76.9% in Hispanic/Latino subjects. Compared with CYP3A5*3/*3, the CYP3A5*1/*x genotype was associated with reduced weekly asthma control (OR: 0.98; 95% CI: 0.97-0.98; p < 0.001), increased exacerbations (OR: 6.43; 95% CI: 4.56-9.07; p < 0.001), and increased asthma hospitalizations (OR: 1.66; 95% CI: 1.43-1.93; p < 0.001); analysis of 3/*3, *1/*1 and *1/*3 separately showed an allelic copy effect. Finally, PK analysis post-ICS dosing suggested muted changes in cortisol concentrations for patients with the CYP3A5*3/*3 genotype, as opposed to an effect on ICS PK. Detection of CYP3A5*3/3, CYPA35*1/*3, and CYP3A5*1/*1 could impact inhaled steroid treatment strategies for asthma in the future.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

GSDMB/ORMDL3 Rare/Common Variants Are Associated with Inhaled Corticosteroid Response among Children with Asthma

Inhaled corticosteroids (ICS) are efficacious in the treatment of asthma, which affects more than 300 million people in the world. While genome-wide association studies have identified genes involved in differential treatment responses to ICS in asthma, few studies have evaluated the effects of combined rare and common variants on ICS response among children with asthma. Among children with asthma treated with ICS with whole exome sequencing (WES) data in the PrecisionLink Biobank (91 White and 20 Black children), we examined the effect and contribution of rare and common variants with hospitalizations or emergency department visits. For 12 regions previously associated with asthma and ICS response (DPP10, FBXL7, NDFIP1, TBXT, GLCCI1, HDAC9, TBXAS1, STAT6, GSDMB/ORMDL3, CRHR1, GNGT2, FCER2), we used the combined sum test for the sequence kernel association test (SKAT) adjusting for age, sex, and BMI and stratified by race. Validation was conducted in the Biorepository and Integrative Genomics (BIG) Initiative (83 White and 134 Black children). Using a Bonferroni threshold for the 12 regions tested (i.e., 0.05/12 = 0.004), GSDMB/ORMDL3 was significantly associated with ICS response for the combined effect of rare and common variants (p-value = 0.003) among White children in the PrecisionLink Biobank and replicated in the BIG Initiative (p-value = 0.02). Using WES data, the combined effect of rare and common variants for GSDMB/ORMDL3 was associated with ICS response among asthmatic children in the PrecisionLink Biobank and replicated in the BIG Initiative. This proof-of-concept study demonstrates the power of biobanks of pediatric real-life populations in asthma genomic investigations.

Machine Learning Prediction of Treatment Response to Inhaled Corticosteroids in Asthma

BACKGROUND

Although inhaled corticosteroids (ICS) are the first-line therapy for patients with persistent asthma, many patients continue to have exacerbations. We developed machine learning models to predict the ICS response in patients with asthma.

METHODS

The subjects included asthma patients of European ancestry (n = 1371; 448 children; 916 adults). A genome-wide association study was performed to identify the SNPs associated with ICS response. Using the SNPs identified, two machine learning models were developed to predict ICS response: (1) least absolute shrinkage and selection operator (LASSO) regression and (2) random forest.

RESULTS

The LASSO regression model achieved an AUC of 0.71 (95% CI 0.67-0.76; sensitivity: 0.57; specificity: 0.75) in an independent test cohort, and the random forest model achieved an AUC of 0.74 (95% CI 0.70-0.78; sensitivity: 0.70; specificity: 0.68). The genes contributing to the prediction of ICS response included those associated with ICS responses in asthma (TPSAB1, FBXL16), asthma symptoms and severity (ABCA7, CNN2, PTRN3, and BSG/CD147), airway remodeling (ELANE, FSTL3), mucin production (GAL3ST), leukotriene synthesis (GPX4), allergic asthma (ZFPM1, SBNO2), and others.

CONCLUSIONS

An accurate risk prediction of ICS response can be obtained using machine learning methods, with the potential to inform personalized treatment decisions. Further studies are needed to examine if the integration of richer phenotype data could improve risk prediction.

F-Box and Leucine-Rich Repeat Protein 7 Is a Prognostic Biomarker and Is Correlated with the Immunosuppressive Microenvironment in Colorectal Cancer

Background: Colorectal cancer (CRC) is a common malignancy of the digestive system, but its specific mechanisms of occurrence and development remain incompletely understood. F-Box and leucine-rich repeat protein 7 (FBXL7) is a subunit of the Skp-cullin-F-box ubiquitin ligase, involved in cell cycle regulation, endothelial cell damage, and inflammatory immunological responses. However, the role of FBXL7 in CRC remains unknown. In this study, we investigated the clinical significance and potential mechanism of FBXL7 expression in CRC progression. Methods: We utilized data from The Cancer Genome Atlas (TCGA) and the University of California Santa Cruz Xena (UCSC Xena) database for bioinformatic analyses. Clinical CRC samples were used to confirm FBXL7 expression. Gene set enrichment analysis (GSEA) and various databases, such as TCGA, UCSC Xena, cBioPortal, University of ALabama at Birmingham CANcer data analysis portal, MethSurv, Tumor Immune Estimation Resource (TIMER), TIMER2.0, Tumor-Immune System Interaction Database, and Tumor Immune Dysfunction and Exclusion Database (TIDB), were used to investigate the role of FBXL7 in CRC. Statistical analysis was performed using R (v.3.6.3) or GraphPad Prism 8.0. Results: Our findings revealed the predictive significance of FBXL7 in CRC patients. FBXL7 expression was associated with tumor stage, lymph node stage, pathological stage, perineural invasion, and lymphatic invasion. GSEA analysis identified associations between FBXL7 and extracellular matrix organization, as well as immune-related pathways. Immunological analysis revealed a correlation between high FBXL7 expression and the development of an immunosuppressive microenvironment. Conclusion: Identifying FBXL7 as a novel biomarker for CRC could shed light on the promotion of CRC development by the immune environment.

Severe Asthma and Biological Therapies: Now and the Future

Recognition of phenotypic variability in pediatric asthma allows for a more personalized therapeutic approach. Knowledge of the underlying pathophysiological and molecular mechanisms (endotypes) of corresponding biomarkers and new treatments enables this strategy to progress. Biologic therapies for children with severe asthma are becoming more relevant in this sense. The T2 phenotype is the most prevalent in childhood and adolescence, and non-T2 phenotypes are usually rare. This document aims to review the mechanism of action, efficacy, and potential predictive and monitoring biomarkers of biological drugs, focusing on the pediatric population. The drugs currently available are omalizumab, mepolizumab, benralizumab, dupilumab, and 1ezepelumab, with some differences in administrative approval prescription criteria between the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Previously, we described the characteristics of severe asthma in children and its diagnostic and therapeutic management.

Genetic Determinants of the Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition that arises from multiple causes, including sepsis, pneumonia, trauma, and severe coronavirus disease 2019 (COVID-19). Given the heterogeneity of causes and the lack of specific therapeutic options, it is crucial to understand the genetic and molecular mechanisms that underlie this condition. The identification of genetic risks and pharmacogenetic loci, which are involved in determining drug responses, could help enhance early patient diagnosis, assist in risk stratification of patients, and reveal novel targets for pharmacological interventions, including possibilities for drug repositioning. Here, we highlight the basis and importance of the most common genetic approaches to understanding the pathogenesis of ARDS and its critical triggers. We summarize the findings of screening common genetic variation via genome-wide association studies and analyses based on other approaches, such as polygenic risk scores, multi-trait analyses, or Mendelian randomization studies. We also provide an overview of results from rare genetic variation studies using Next-Generation Sequencing techniques and their links with inborn errors of immunity. Lastly, we discuss the genetic overlap between severe COVID-19 and ARDS by other causes.

Immunogenetics and pharmacogenetics of allergic asthma in Africa

Asthma is a common chronic condition in children and in an African setting is often highly prevalent in urban areas as compared to rural areas. Asthma is a heritable disease and the genetic risk is often exacerbated by unique localised environmental factors. The Global Initiative for Asthma (GINA) recommendation for the control of asthma includes inhaled corticosteroids (ICS) alone or together with short-acting β₂-agonists (SABA) or long-acting β₂-agonists (LABA). While these drugs can relieve asthma symptoms, there is evidence of reduced efficacy in people of African ancestry. Whether this is due to immunogenetics, genomic variability in drug metabolising genes (pharmacogenetics) or genetics of asthma-related traits is not well defined. Pharmacogenetic evidence of first-line asthma drugs in people of African ancestry is lacking and is further compounded by the lack of representative genetic association studies in the continent. In this review, we will discuss the paucity of data related to the pharmacogenetics of asthma drugs in people of African ancestry, mainly drawing from African American data. We will further discuss how this gap can be bridged to improve asthma health outcomes in Africa.

Novel genetic variants associated with inhaled corticosteroid treatment response in older adults with asthma

INTRODUCTION

Older adults have the greatest burden of asthma and poorest outcomes. The pharmacogenetics of inhaled corticosteroid (ICS) treatment response is not well studied in older adults.

METHODS

A genome-wide association study of ICS response was performed in asthmatics of European ancestry in Genetic Epidemiology Research on Adult Health and Aging (GERA) by fitting Cox proportional hazards regression models, followed by validation in the Mass General Brigham (MGB) Biobank and Rotterdam Study. ICS response was measured using two definitions in asthmatics on ICS treatment: (1) absence of oral corticosteroid (OCS) bursts using prescription records and (2) absence of asthma-related exacerbations using diagnosis codes. A fixed-effect meta-analysis was performed for each outcome. The validated single-nucleotide polymorphisms (SNPs) were functionally annotated to standard databases.

RESULTS

In 5710 subjects in GERA, 676 subjects in MGB Biobank, and 465 subjects in the Rotterdam Study, four novel SNPs on chromosome six near PTCHD4 validated across all cohorts and met genome-wide significance on meta-analysis for the OCS burst outcome. In 4541 subjects in GERA and 505 subjects in MGB Biobank, 152 SNPs with p<5 × 10-5 were validated across these two cohorts for the asthma-related exacerbation outcome. The validated SNPs included methylation and expression quantitative trait loci for CPED1, CRADD and DST for the OCS burst outcome and GM2A, SNW1, CACNA1C, DPH1, and RPS10 for the asthma-related exacerbation outcome.

CONCLUSIONS

Multiple novel SNPs associated with ICS response were identified in older adult asthmatics. Several SNPs annotated to genes previously associated with asthma and other airway or allergic diseases, including PTCHD4.

Polymorphisms in the FCER2 gene have associations with asthma and chronic obstructive pulmonary disease

Background

Asthma and chronic obstructive pulmonary disease (COPD) are heterogenetic diseases and exhibit many similarities. Dutch hypothesis proposed that these two diseases may have common genetic origins. This study aims to investigate whether asthma and COPD share a common genetic background in Chinese patients.

Methods

In this case-control study, single nucleotide polymorphisms (SNPs) were genotyped using SNaPshot. Haplotype disease analysis and haplotype phenotype analysis were applied to assess the relationship between three polymorphisms of the FCER2 gene and the risk of COPD/asthma. Additionally, associations between polymorphisms of the FCER2 gene and phenotypes were analyzed.

Results

We detected ten SNPs of seven genes (FCER1A, FCGR2A, FCGR2B, CHI3L1, ADRB2, STAT6, and FCER2) expressed by airway epithelial cells. We detected genotypes and allele distributions in 251 COPD patients, 597 asthma patients, and 632 healthy controls. A significant difference was found in the FCER2 gene (rs28364072) between COPD patients and controls (P=0.009). Significant differences were observed in the genotype and allele distributions of rs1801274 (FCGR2A), rs12368672 (STAT6), and rs2228137 (FCER2) between asthma patients and controls (P=0.004, 0.007 and 0.010, respectively). Notably, polymorphisms of FCER2 gene were associated with the risk of both COPD (P=0.009 for rs28364072) and asthma (P=0.01 for rs2228137). Haplotype analysis revealed that haplotype T-G-T (alleles of rs28364072, rs2228137, and rs3760687, respectively) was significantly associated with a higher risk of asthma [odds ratios (OR) =2.25, 95% confidence interval (CI): 1.26-4.01, P=0.006]. Further analysis showed that the C-A-C haplotype and C-G-T haplotype were associated with increased blood eosinophils in either COPD or asthma patients (P=0.034, and P<0.001, respectively). Moreover, haplotypes C-A-C, C-G-C, and T-G-C showed significant associations with serum IgE levels in asthma patients (P=0.002, 0.041, and 0.004, respectively).

Conclusions

Our data suggest that the FCER2 gene might associate with predisposition to asthma and COPD, while FCER2 haplotypes were associated with pulmonary function measurements and blood eosinophils counts in both diseases. Our findings support the common genetic basis for asthma and COPD, suggesting a potential therapeutic target for the two diseases.

ER22/23EK AND TTH111I POLYMORPHIC VARIANTS IN THE GLUCOCORTICOID RECEPTOR GENE IN PATIENTS WITH BRONCHIAL ASTHMA

OBJECTIVE

Aim: The objective of the study was to evaluate the frequency of the ER22/23EK and Tth111I polymorphic variants in the glucocorticoid receptor (GR) gene in patients with BA and to assess the risk of BA development with regard to these polymorphisms.

PATIENTS AND METHODS

Materials and Methods: We examined 553 BA patients and 95 apparently healthy individuals. BA was diagnosed according to the 2016 GINA recommendations and its later versions. The study was approved by the Bioethics Committee of the Medical Institute of Sumy State University. The ER22/23EK (rs 6189/6190) and Tth111I (rs10052957) polymorphisms in the GR gene were determined using polymerase chain reaction-restriction fragment length polymorphism analysis. Statistical analysis of obtained results was performed using SPSS-17 program.

RESULTS

Results: The obtained distribution of genotypes for the ER22/23EK and Tth111I polymorphisms in the GR gene corresponded to the Hardy-Weinberg expectations (p > 0.05). We revealed no significant difference in the distribution of alleles and genotypes for the ER22/23EK polymorphism in the GR gene in patients with asthma and apparently healthy individuals (χ2 = 4.14; p = 0.126); apart from that, we found no statistically significant association with BA risk in any model of inheritance. A statistically significant difference was observed in the distribution of genotypes for the Tth111I polymorphism in the GR gene in patients with asthma and apparently healthy individuals (χ2 = 6.278; p = 0.043). BA risk was 2.69 times higher in the carriers of TT genotype for the Tth111I polymorphism in the GR gene vs. major allele carriers. No gender-specific difference was observed in the distribution of genotypes and alleles for the ER22/23EK and Tth111I polymorphisms in the GR gene.

CONCLUSION

Conclusions: We found no gender-specific difference in the distribution of alleles and genotypes for the ER22/23EK and Tth111I polymorphisms in the GR gene; no difference in the distribution of alleles and genotypes for the ER22/23EK polymorphism in the GR gene in patients with asthma and apparently healthy individuals; and no statistically significant association with BA risk. A statistically significant difference was observed in the distribution of genotypes for the Tth111I polymorphism in the GR gene in patients with asthma and apparently healthy individuals; also, BA risk was 2.69 times higher in the minor allele homozygous patients vs. major allele carriers.

Functional characterization of FBXL7 as a novel player in human cancers

F-box and leucine-rich repeat protein 7 (FBXL7), an F-box protein responsible for substrate recognition by the SKP1-Cullin-1-F-box (SCF) ubiquitin ligases, plays an emerging role in the regulation of tumorigenesis and tumor progression. FBXL7 promotes polyubiquitylation and degradation of diverse substrates and is involved in many biological processes, including apoptosis, cell proliferation, cell migration and invasion, tumor metastasis, DNA damage, glucose metabolism, planar cell polarity, and drug resistance. In this review, we summarize the downstream substrates and upstream regulators of FBXL7. We then discuss its role in tumorigenesis and tumor progression as either an oncoprotein or a tumor suppressor, and further describe its aberrant expression and association with patient survival in human cancers. Finally, we provide future perspectives on validating FBXL7 as a cancer biomarker for diagnosis and prognosis and/or as a potential therapeutic target for anticancer treatment.

Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

Adrenal suppression in patients with chronic obstructive pulmonary disease treated with glucocorticoids: Role of specific glucocorticoid receptor polymorphisms

BACKGROUND

Single-nucleotide polymorphisms (SNPs) of the glucocorticoid receptor (GR) gene NR3C1 have been associated with an altered sensitivity to glucocorticoids, and thus may alter the therapeutic effects of glucocorticoids. We investigated the prevalence of adrenal suppression after treatment with glucocorticoids and evaluated whether GR SNPs were associated with altered risks of adrenal suppression and metabolic disorders in patients with chronic obstructive pulmonary disease (COPD).

METHODS

In an observational prospective cohort study, we recruited 78 patients with severe COPD receiving 5 days glucocorticoid treatment for an exacerbation of COPD. In total, 55% of these patients were also receiving regular inhaled corticosteroids (ICS). Adrenal function was evaluated with a corticotropin test 30 days after the exacerbation. Patients were genotyped for Bcl1, N363S, ER22/23EK, and 9β SNPs.

RESULTS

The prevalence of adrenal suppression (corticotropin-stimulated plasma-cortisol ≤ 420 nmol/L) 30 days after glucocorticoid treatment was 4/78 (5%). There was no difference between carriers and non-carriers of the polymorphisms (Bcl1, 9β, ER22/23K, and N363S) in corticotropin stimulated plasma-cortisol concentrations. In the haplotype analyses, we included the 50 patients who had a high-sensitivity (76%), a low-sensitivity (4%), or a wild-type (20%) GR haplotype. There was no difference in the frequency of adrenal suppression or metabolic disorders between the two stratified groups: (a) high-sensitivity (Bcl1 and/or N363S) haplotypes vs. (b) low-sensitivity (9β and/or ER22/23K) plus wild-type haplotypes (p > 0.05). Carriers of the high-sensitivity GR gene haplotype exhibited a steeper decline in stimulated P-cortisol with increased ICS dose (slope, -1.35 vs. 0.94; p = 0.17), compared to the group with low-sensitivity or wild-type haplotypes, respectively.

CONCLUSIONS

In total, 5% of patients exhibited insufficient adrenal function. The Bcl1 and N363S polymorphisms did not seem to increase the risk of glucocorticoid suppression or metabolic disorders in adults treated with glucocorticoids for COPD exacerbations.

NR3C1 Glucocorticoid Receptor Gene Polymorphisms Are Associated with Membranous and IgA Nephropathies

Glomerular diseases (GNs) are responsible for approximately 20% of chronic kidney diseases. Glucocorticoid receptor gene (NR3C1) single nucleotide polymorphisms (SNPs) are implicated in differences in predisposition to autoimmunity and steroid sensitivity. The aim of this study was to evaluate the frequency of the NR3C1 SNPs—rs6198, rs41423247 and rs17209237—in 72 IgA nephropathy (IgAN) and 38 membranous nephropathy (MN) patients compared to 175 healthy controls and to correlate the effectiveness of treatment in IgAN and MN groups defined as a reduction of proteinuria <1 g/24 h after 12 months of treatment. Real-time polymerase chain reactions and SNP array-based typing were used. We found significant rs41423247 association with MN (p = 0.026); a significant association of rs17209237 with eGFR reduction after follow-up period in all patients with GNs (p = 0.021) and with the degree of proteinuria after 1 year of therapy in all patients with a glomerulopathy (p = 0.013) and IgAN (p = 0.021); and in the same groups treated with steroids (p = 0.021; p = 0.012). We also observed the association between rs41423247 and IgAN histopathologic findings (p = 0.012). In conclusion, our results indicate that NR3C1 polymorphisms may influence treatment susceptibility and clinical outcome in IgAN and MN.

Identification of the Core MicroRNAs and Potential Molecular Mechanismsin Sarcoidosis Using Bioinformatics Analysis

Sarcoidosis is a systemic heterogeneous inflammatory disease; however, the etiology and pathogenesis of sarcoidosis are still unknown. Herein, we investigated the core microRNAs and potential molecular mechanisms in sarcoidosis. The DE-miRNAs were diagnosed using the LIMMA software package. DIANA-mirPath was employed to perform pathway and GO enrichment analysis of the DE-miRNAs. PPI networks and miRNA-target gene regulatory networks were used to obtain insight into the actions of DE-miRNAs. Expression of the hub genes along with miRNAs was validated in clinical specimens. Overall, 266 DE-miRNAs were screened. Among these DE-miRNAs, hsa-miR-144, hsa-miR-126, as well as hsa-miR-106a were the upmost upregulated miRNAs; hsa-miR-151-3p, hsa-miR-320d, and hsa-miR-324-3p were the top downregulated miRNAs. NR3C1, ZBTB7A, NUFIP2, BZW1, ERGIC2, and VEGFA were mapped as the most targeted hub genes in the upregulation of miRNAs, and MCL1 and SAE1 were the most targeted hub genes in the downregulation of miRNA. VEGFA and NR3C1 were selected and potentially modulated by hsa-miR-20b, hsa-miR-126, and hsa-miR-106a. In sarcoidosis pathological tissue, hsa-miR-126 was highly expressed, and VEGFA and NR3C1 were overexpressed. In conclusion, our results revealed the dysregulation of hsa-miR-126 and a potential regulatory mechanism for pathogenesis in sarcoidosis.

Genome-wide association study of asthma exacerbations despite inhaled corticosteroid use

RATIONALE

Substantial variability in response to asthma treatment with inhaled corticosteroids (ICS) has been described among individuals and populations, suggesting the contribution of genetic factors. Nonetheless, only a few genes have been identified to date. We aimed to identify genetic variants associated with asthma exacerbations despite ICS use in European children and young adults and to validate the findings in non-Europeans. Moreover, we explored whether a gene-set enrichment analysis could suggest potential novel asthma therapies.

METHODS

A genome-wide association study (GWAS) of asthma exacerbations was tested in 2681 children of European descent treated with ICS from eight studies. Suggestive association signals were followed up for replication in 538 European asthma patients. Further evaluation was performed in 1773 non-Europeans. Variants revealed by published GWAS were assessed for replication. Additionally, gene-set enrichment analysis focused on drugs was performed.

RESULTS

10 independent variants were associated with asthma exacerbations despite ICS treatment in the discovery phase (p≤5×10-6). Of those, one variant at the CACNA2D3-WNT5A locus was nominally replicated in Europeans (rs67026078; p=0.010), but this was not validated in non-European populations. Five other genes associated with ICS response in previous studies were replicated. Additionally, an enrichment of associations in genes regulated by trichostatin A treatment was found.

CONCLUSIONS

The intergenic region of CACNA2D3 and WNT5A was revealed as a novel locus for asthma exacerbations despite ICS treatment in European populations. Genes associated were related to trichostatin A, suggesting that this drug could regulate the molecular mechanisms involved in treatment response.

Genetic Determinants of Poor Response to Treatment in Severe Asthma

Severe asthma is a multifactorial disorder with marked phenotypic heterogeneity and complex interactions between genetics and environmental risk factors, which could, at least in part, explain why during standard pharmacologic treatment, many patients remain poorly controlled and at an increased risk of airway remodeling and disease progression. The concept of “precision medicine” to better suit individual unique needs is an emerging trend in the management of chronic respiratory diseases. Over the past few years, Genome-Wide Association Studies (GWAS) have revealed novel pharmacogenetic variants related to responses to inhaled corticosteroids and the clinical efficacy of bronchodilators. Optimal clinical response to treatment may vary between racial/ethnic groups or individuals due to genetic differences. It is also plausible to assume that epigenetic factors play a key role in the modulation of gene expression patterns and inflammatory cytokines. Remarkably, specific genetic variants related to treatment effectiveness may indicate promising pathways for novel therapies in severe asthma. In this review, we provide a concise update of genetic determinants of poor response to treatment in severe asthma and future directions in the field.

Pharmacogenetic Polygenic Risk Score for Bronchodilator Response in Children and Adolescents with Asthma: Proof-of-Concept

Genome-wide association studies (GWAS) of response to asthma medications have primarily focused on Caucasian populations, with findings that may not be generalizable to minority populations. We derived a polygenic risk score (PRS) for response to albuterol as measured by bronchodilator response (BDR), and examined the PRS in a cohort of Hispanic school-aged children with asthma. We leveraged a published GWAS of BDR to identify relevant genetic variants, and ranked the top variants according to their Combined Annotation Dependent Depletion (CADD) scores. Variants with CADD scores greater than 10 were used to compute the PRS. Once we derived the PRS, we determined the association of the PRS with BDR in a cohort of Hispanic children with asthma (the Genetics of Asthma in Costa Rica Study (GACRS)) in adjusted linear regression models. Mean BDR in GACRS participants was5.6% with a standard deviation of 10.2%. We observed a 0.63% decrease in BDR in response to albuterol for a standard deviation increase in the PRS (p = 0.05). We also observed decreased odds of a BDR response at or above the 12% threshold for a one standard deviation increase in the PRS (OR = 0.80 (95% CI 0.67 to 0.95)). Our findings show that combining variants from a pharmacogenetic GWAS into a PRS may be useful for predicting medication response in asthma.

Drug Repurposing to Treat Glucocorticoid Resistance in Asthma

Corticosteroid resistance causes significant morbidity in asthma, and drug repurposing may identify timely and cost-effective adjunctive treatments for corticosteroid resistance. In 95 subjects from the Childhood Asthma Management Program (CAMP) and 19 subjects from the Severe Asthma Research Program (SARP), corticosteroid response was measured by the change in percent predicted forced expiratory volume in one second (FEV₁). In each cohort, differential gene expression analysis was performed comparing poor (resistant) responders, defined as those with zero to negative change in FEV₁, to good responders, followed by Connectivity Map (CMap) analysis to identify inversely associated (i.e., negatively connected) drugs that reversed the gene expression profile of poor responders to resemble that of good responders. Mean connectivity scores weighted by sample size were calculated. The top five drug compound candidates underwent in vitro validation in NF-κB-based luciferase reporter A549 cells stimulated by IL-1β ± dexamethasone. In CAMP and SARP, 134 and 178 respective genes were differentially expressed in poor responders. CMap analysis identified 46 compounds in common across both cohorts with connectivity scores < −50. γ-linolenic acid, ampicillin, exemestane, brinzolamide, and INCA-6 were selected for functional validation. γ-linolenic acid, brinzolamide, and INCA-6 significantly reduced IL-1β induced luciferase activity and potentiated the anti-inflammatory effect of dexamethasone in A549/NF-κB-luc reporter cells. These results demonstrate how existing drugs, including γ-linolenic acid, brinzolamide, and INCA-6, may be repurposed to improve corticosteroid response in asthmatics.

Advances in asthma genetics

While asthma has a strong genetic component, our current ability to systematically understand and predict asthma risk remains low, despite over a hundred genetic associations. The reasons for this unfilled gap range from technical limitations of current approaches to fundamental deficiencies in the way we understand asthma. These are discussed in the context of genomic advances.

Pharmacogenetics of inhaled corticosteroids and exacerbation risk in adults with asthma

BACKGROUND

Inhaled corticosteroids (ICS) are a cornerstone of asthma treatment. However, their efficacy is characterized by wide variability in individual responses.

OBJECTIVE

We investigated the association between genetic variants and risk of exacerbations in adults with asthma and how this association is affected by ICS treatment.

METHODS

We investigated the pharmacogenetic effect of 10 single nucleotide polymorphisms (SNPs) selected from the literature, including SNPs previously associated with response to ICS (assessed by change in lung function or exacerbations) and novel asthma risk alleles involved in inflammatory pathways, within all adults with asthma from the Dutch population-based Rotterdam study with replication in the American GERA cohort. The interaction effects of the SNPs with ICS on the incidence of asthma exacerbations were assessed using hurdle models adjusting for age, sex, BMI, smoking and treatment step according to the GINA guidelines. Haplotype analyses were also conducted for the SNPs located on the same chromosome.

RESULTS

rs242941 (CRHR1) homozygotes for the minor allele (A) showed a significant, replicated increased risk for frequent exacerbations (RR = 6.11, P < 0.005). In contrast, rs1134481 T allele within TBXT (chromosome 6, member of a family associated with embryonic lung development) showed better response with ICS. rs37973 G allele (GLCCI1) showed a significantly poorer response on ICS within the discovery cohort, which was also significant but in the opposite direction in the replication cohort.

CONCLUSION

rs242941 in CRHR1 was associated with poor ICS response. Conversely, TBXT variants were associated with improved ICS response. These associations may reveal specific endotypes, potentially allowing prediction of exacerbation risk and ICS response.

Highlights and recent developments in allergic diseases in EAACI journals (2019)

The European Academy of Allergy and Clinical Immunology (EAACI) owns three journals: Allergy, Pediatric Allergy and Immunology and Clinical and Translational Allergy. One of the major goals of EAACI is to support health promotion in which prevention of allergy and asthma plays a critical role and to disseminate the knowledge of allergy to all stakeholders including the EAACI junior members. There was substantial progress in 2019 in the identification of basic mechanisms of allergic and respiratory disease and the translation of these mechanisms into clinics. Better understanding of molecular and cellular mechanisms, efforts for the development of biomarkers for disease prediction, novel prevention and intervention studies, elucidation of mechanisms of multimorbidities, entrance of new drugs in the clinics as well as recently completed phase three clinical studies and publication of a large number of allergen immunotherapy studies and meta-analyses have been the highlights of the last year.

Insights into glucocorticoid responses derived from omics studies

Glucocorticoid drugs are commonly used in the treatment of several conditions, including autoimmune diseases, asthma and cancer. Despite their widespread use and knowledge of biological pathways via which they act, much remains to be learned about the cell type-specific mechanisms of glucocorticoid action and the reasons why patients respond differently to them. In recent years, human and in vitro studies have addressed these questions with genomics, transcriptomics and other omics approaches. Here, we summarize key insights derived from omics studies of glucocorticoid response, and we identify existing knowledge gaps related to mechanisms of glucocorticoid action that future studies can address.

Pharmacogenomic Response of Inhaled Corticosteroids for the Treatment of Asthma: Considerations for Therapy

There is a large interindividual variability in response to ICSs in asthma. About 70% of the variance in ICS response is likely due at least partially to genetically determined characteristics of target genes. In this article, we examine the effects on the ICS response of gene variations in the corticosteroid pathway, and in the pharmacokinetics of corticosteroids, and also those outside the corticosteroid pathway, which have the potential to influence corticosteroid activity. Although the available evidence indicates that responses to ICSs in asthma are influenced by different genetic variants, there are still deep uncertainties as to whether a real association between these genetic variants and corticosteroid response could also possibly exist because there are difficulties in reproducing pharmacogenetic findings. This explains at least partly the insufficient use of pharmacogenomic data when treating asthmatic patients, which creates a real limitation to the proper use of ICSs in an era of precision medicine that links the right patient to the right treatment. Knowing and dealing with the genetic factors that influence the therapeutic ICS response is a fundamental condition for prescribing the right dose of ICS to the right patient at the right time.

Novel Comprehensive Bioinformatics Approaches to Determine the Molecular Genetic Susceptibility Profile of Moderate and Severe Asthma

Background: Asthma is a chronic inflammatory condition linked to hyperresponsiveness in the airways. There is currently no cure available for asthma, and therapy choices are limited. Asthma is the result of the interplay between genes and the environment. The exact molecular genetic mechanism of asthma remains elusive. Aims: The aim of this study is to provide a comprehensive, detailed molecular etiology profile for the molecular factors that regulate the severity of asthma and pathogenicity using integrative bioinformatics tools. Methods: The GSE43696 omnibus gene expression dataset, which contains 50 moderate cases, 38 severe cases, and 20 healthy controls, was used to investigate differentially expressed genes (DEGs), susceptible chromosomal loci, gene networks, pathways, gene ontologies, and protein–protein interactions (PPIs) using an intensive bioinformatics pipeline. Results: The PPI network analysis yielded DEGs that contribute to interactions that differ from moderate-to-severe asthma. The combined interaction scores resulted in higher interactions for the genes STAT3, AGO2, COL1A1, CLCN6, and KSR for moderate asthma and JAK2, INSR, ERBB2, NR3C1, and PTK6 for severe asthma. Enrichment analysis (EA) demonstrated differential enrichment between moderate and severe asthma phenotypes; the ion transport regulation pathway was significantly enhanced in severe asthma phenotypes compared to that in moderate asthma phenotypes and involved PER2, GCR, IRS-2, KCNK7, KCNK6, NOX1, and SCN7A. The most enriched common pathway in both moderate and severe asthma is the development of the glucocorticoid receptor (GR) signaling pathway followed by glucocorticoid-mediated inhibition of proinflammatory and proconstrictory signaling in the airway of smooth muscle cell pathways. Gene sets were shared between severe and moderate asthma at 16 chromosome locations, including 17p13.1, 16p11.2, 17q21.31, 1p36, and 19q13.2, while 60 and 48 chromosomal locations were unique for both moderate and severe asthma, respectively. Phylogenetic analysis for DEGs showed that several genes have been intersected in phases of asthma in the same cluster of genes. This could indicate that several asthma-associated genes have a common ancestor and could be linked to the same biological function or gene family, implying the importance of these genes in the pathogenesis of asthma. Conclusion: New genetic risk factors for the development of moderate-to-severe asthma were identified in this study, and these could provide a better understanding of the molecular pathology of asthma and might provide a platform for the treatment of asthma.

Precision Medicine in Childhood Asthma: Omic Studies of Treatment Response

Asthma is a heterogeneous and multifactorial respiratory disease with an important impact on childhood. Difficult-to-treat asthma is not uncommon among children, and it causes a high burden to the patient, caregivers, and society. This review aims to summarize the recent findings on pediatric asthma treatment response revealed by different omic approaches conducted in 2018–2019. A total of 13 studies were performed during this period to assess the role of genomics, epigenomics, transcriptomics, metabolomics, and the microbiome in the response to short-acting beta agonists, inhaled corticosteroids, and leukotriene receptor antagonists. These studies have identified novel associations of genetic markers, epigenetic modifications, metabolites, bacteria, and molecular mechanisms involved in asthma treatment response. This knowledge will allow us establishing molecular biomarkers that could be integrated with clinical information to improve the management of children with asthma.

Understanding the genetics of asthma and implications for clinical practice

Asthma is one of the most common heritable diseases globally, with variable clinical expression and response to treatment that is attributed to underlying genetic differences. Hundreds of loci on multiple chromosomes are associated with asthma. Although routine genetic screening is not recommended, testing for medication responsiveness might soon play a role in clinical management. Pharmacogenetic research remains early stage but has demonstrated potential for both clinical and cost effectiveness. Furthermore, recognition of clinically apparent asthma phenotypes, the result of genetic and environmental interactions, can help to inform treatment decisions. Phenotypes are divided into two broad categories of atopic and nonatopic disease, with further subdivisions that are associated with clinical presentation patterns and responsiveness to treatment. In general, earlier onset and allergic disease will respond well to traditional therapy with inhaled corticosteroids (ICSs) and leukotrienes because these medications target inflammatory pathways for allergic disease. However, patients with late-onset, symptom predominant (lacking inflammation), and obese asthma might be resistant to standard therapy and may require treatment modification. These patients are at risk for overuse of ICSs with poor response and may benefit more by use of long-acting beta agonists, long-acting muscarinic agonists, weight reduction, and exercise.

Pharmacogenetics of Pediatric Asthma: Current Perspectives

Asthma is a chronic respiratory disease that affects 339 million people worldwide and has a considerable impact on the pediatric population. Asthma symptoms can be controlled by pharmacological treatment. However, some patients do not respond to therapy and continue suffering from symptoms, which impair the quality of life of patients and limit their daily activity. Genetic variation has been shown to have a role in treatment response. The aim of this review is to update the main findings described in pharmacogenetic studies of pediatric asthma published from January 1, 2018 to December 31, 2019. During this period, the response to short-acting beta-agonists and inhaled corticosteroids in childhood asthma has been evaluated by eleven candidate-gene studies, one meta-analysis of a candidate gene, and six pharmacogenomic studies. The findings have allowed validating the association of genes previously related to asthma treatment response (ADRB2, GSDMB, FCER2, VEGFA, SPAT2SL, ASB3, and COL2A1), and identifying novel associations (PRKG1, DNAH5, IL1RL1, CRISPLD2, MMP9, APOBEC3B-APOBEC3C, EDDM3B, and BBS9). However, some results are not consistent across studies, highlighting the need to conduct larger studies in diverse populations with more homogeneous definitions of treatment response. Once stronger evidence was established, genetic variants will have the potential to be applied in clinical practice as biomarkers of treatment response enhancing asthma management and improving the quality of life of asthma patients.