Genetic Architectures of Childhood- and Adult-Onset Asthma Are Partly Distinct

Genetically predicted asthma and the risk of abnormal spermatozoa

Background

Several previous animal and human studies have found a strong association between asthma and spermatozoa quality, but whether these associations are causal or due to bias remains to be elucidated.

Methods

We performed a two-sample Mendelian randomization (MR) analysis to assess the causal effect of genetically predicted asthma on the risk of abnormal spermatozoa. Asthma, childhood-onset asthma (COA), and adult-onset asthma (AOA) (sample sizes ranging from 327,670 to 408,442) were included as the exposures. Genetic information for abnormal spermatozoa was obtained from a genome-wide association study (GWAS) comprising 209,921 participants. In univariable MR (UVMR) analysis, the inverse variance weighted (IVW) method was conducted as the primary method, with the MR Egger and weighted median used as supplementary methods for causal inference. Sensitivity analyses, including the Cochran Q test, Egger intercept test, MR-PRESSO, and leave-one-out analysis, were performed to verify the robustness of the MR results. Multivariable MR (MVMR) was conducted to evaluate the direct causal effects of asthma on abnormal spermatozoa risk.

Results

UVMR detected causal associations between genetically predicted asthma and an increased risk of abnormal spermatozoa (OR: 1.270, 95% CI: 1.045-1.545, p = 0.017). Moreover, we found that AOA (OR: 1.46, 95% CI: 1.051, 2.018, p = 0.024) has positive causal effects on the risk of abnormal spermatozoa rather than COA (p = 0.558). Sensitivity analysis found little evidence of bias in the current study (p > 0.05). MVMR further confirmed that asthma directly affected the risk of abnormal spermatozoa.

Conclusion

Our MR study suggested that genetically predicted asthma could be associated with an increased risk of abnormal spermatozoa, and similar results were obtained in AOA. Further studies are warranted to explain the underlying mechanisms of this association and may provide new avenues for prevention and treatment.

An integrated molecular risk score early in life for subsequent childhood asthma risk

BACKGROUND

Numerous children present with early wheeze symptoms, yet solely a subgroup develops childhood asthma. Early identification of children at risk is key for clinical monitoring, timely patient-tailored treatment, and preventing chronic, severe sequelae. For early prediction of childhood asthma, we aimed to define an integrated risk score combining established risk factors with genome-wide molecular markers at birth, complemented by subsequent clinical symptoms/diagnoses (wheezing, atopic dermatitis, food allergy).

METHODS

Three longitudinal birth cohorts (PAULINA/PAULCHEN, n = 190 + 93 = 283, PASTURE, n = 1133) were used to predict childhood asthma (age 5-11) including epidemiological characteristics and molecular markers: genotype, DNA methylation and mRNA expression (RNASeq/NanoString). Apparent (ap) and optimism-corrected (oc) performance (AUC/R2) was assessed leveraging evidence from independent studies (Naïve-Bayes approach) combined with high-dimensional logistic regression models (LASSO).

RESULTS

Asthma prediction with epidemiological characteristics at birth (maternal asthma, sex, farm environment) yielded an ocAUC = 0.65. Inclusion of molecular markers as predictors resulted in an improvement in apparent prediction performance, however, for optimism-corrected performance only a moderate increase was observed (upto ocAUC = 0.68). The greatest discriminate power was reached by adding the first symptoms/diagnosis (up to ocAUC = 0.76; increase of 0.08, p = .002). Longitudinal analysis of selected mRNA expression in PASTURE (cord blood, 1, 4.5, 6 years) showed that expression at age six had the strongest association with asthma and correlation of genes getting larger over time (r = .59, p < .001, 4.5-6 years).

CONCLUSION

Applying epidemiological predictors alone showed moderate predictive abilities. Molecular markers from birth modestly improved prediction. Allergic symptoms/diagnoses enhanced the power of prediction, which is important for clinical practice and for the design of future studies with molecular markers.

Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis

BACKGROUND

To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved.

METHODS

Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations.

RESULTS

Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL.

CONCLUSIONS

Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.

Trans-eQTL mapping in gene sets identifies network effects of genetic variants

Nearly all trait-associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these variants have been extensively characterized, but how they affect gene regulation in trans has been the subject of fewer studies because of the difficulty in detecting trans-expression quantitative loci (eQTLs). We developed trans-PCO for detecting trans effects of genetic variants on gene networks. Our simulations demonstrate that trans-PCO substantially outperforms existing trans-eQTL mapping methods. We applied trans-PCO to two gene expression datasets from whole blood, DGN (N = 913) and eQTLGen (N = 31,684), and identified 14,985 high-quality trans-eSNP-module pairs associated with 197 co-expression gene modules and biological processes. We performed colocalization analyses between GWAS loci of 46 complex traits and the trans-eQTLs. We demonstrated that the identified trans effects can help us understand how trait-associated variants affect gene regulatory networks and biological pathways.

Higher risk of osteoporosis in adult-onset asthma than childhood-onset asthma: from genetic and prospective evidence

Both COA and AOA have a genetically causal effect on osteoporosis. COA and AOA were independently associated with incident osteoporosis, and the risk was greatly higher in AOA. Besides corticosteroids, the increased risk of osteoporosis among asthma patients should be attributed to genetic susceptibility and other asthma medications.

PURPOSE/INTRODUCTION

Childhood-onset asthma (COA) differs with adult-onset asthma (AOA) on genetic susceptibility, severity, and co-morbidities. Whether COA or AOA is independently associated with osteoporosis is unexplored. We aimed to determine the effects of COA and AOA on osteoporosis at genetic and individual level.

METHODS

We used two-sample Mendelian randomization analysis to explore the causal effects of COA and AOA on osteoporosis. In the UK Biobank cohort, we included 478,289 osteoporosis-free participants at baseline (2006-2010). Participants were classified as non-asthma, COA, and AOA at recruitment. Multivariate Cox regression analysis was used to evaluate the effects of COA, AOA, and multiple asthma medications on incident osteoporosis risk.

RESULTS

COA and AOA were causally related to osteoporosis, with odds ratio of 1.007 (95% confidence interval (CI), 1.0003-1.0132) and 1.012 (95% CI, 1.002-1.023), respectively. Multivariate Cox regression analysis suggested that COA (hazard ratio (HR), 1.46; 95% CI, 1.32-1.61) and AOA (HR, 1.70; 95% CI, 1.61-1.80) were independently associated with incident osteoporosis, and the risk was greatly higher in AOA (HR, 1.51; 95% CI, 1.34-1.70). In addition to corticosteroids, monotherapy with leukotriene modifiers (HR, 1.70; 95% CI, 1.20-2.42), long-acting beta agonists (HR, 1.49; 95% CI, 1.18-1.87), and short-acting beta agonists (HR, 1.72; 95% CI1.01-2.93) were independently associated with a higher risk of osteoporosis.

CONCLUSIONS

Both COA and AOA have a genetically causal effect on osteoporosis, and the risk of osteoporosis is greatly higher in AOA. Besides corticosteroids, the increased risk of osteoporosis among asthma patients should be attributed to genetic susceptibility and other asthma medications.

Cell-type-specific and disease-associated expression quantitative trait loci in the human lung

Common genetic variants confer substantial risk for chronic lung diseases, including pulmonary fibrosis. Defining the genetic control of gene expression in a cell-type-specific and context-dependent manner is critical for understanding the mechanisms through which genetic variation influences complex traits and disease pathobiology. To this end, we performed single-cell RNA sequencing of lung tissue from 66 individuals with pulmonary fibrosis and 48 unaffected donors. Using a pseudobulk approach, we mapped expression quantitative trait loci (eQTLs) across 38 cell types, observing both shared and cell-type-specific regulatory effects. Furthermore, we identified disease interaction eQTLs and demonstrated that this class of associations is more likely to be cell-type-specific and linked to cellular dysregulation in pulmonary fibrosis. Finally, we connected lung disease risk variants to their regulatory targets in disease-relevant cell types. These results indicate that cellular context determines the impact of genetic variation on gene expression and implicates context-specific eQTLs as key regulators of lung homeostasis and disease.

Structural and genetic diversity in the secreted mucins, MUC5AC and MUC5B

The secreted mucins MUC5AC and MUC5B play critical defensive roles in airway pathogen entrapment and mucociliary clearance by encoding large glycoproteins with variable number tandem repeats (VNTRs). These polymorphic and degenerate protein coding VNTRs make the loci difficult to investigate with short reads. We characterize the structural diversity of MUC5AC and MUC5B by long-read sequencing and assembly of 206 human and 20 nonhuman primate (NHP) haplotypes. We find that human MUC5B is largely invariant (5761-5762aa); however, seven haplotypes have expanded VNTRs (6291-7019aa). In contrast, 30 allelic variants of MUC5AC encode 16 distinct proteins (5249-6325aa) with cysteine-rich domain and VNTR copy number variation. We grouped MUC5AC alleles into three phylogenetic clades: H1 (46%, ~5654aa), H2 (33%, ~5742aa), and H3 (7%, ~6325aa). The two most common human MUC5AC variants are smaller than NHP gene models, suggesting a reduction in protein length during recent human evolution. Linkage disequilibrium (LD) and Tajima's D analyses reveal that East Asians carry exceptionally large MUC5AC LD blocks with an excess of rare variation (p<0.05). To validate this result, we used Locityper for genotyping MUC5AC haplogroups in 2,600 unrelated samples from the 1000 Genomes Project. We observed signatures of positive selection in H1 and H2 among East Asians and a depletion of the likely ancestral haplogroup (H3). In Africans and Europeans, H3 alleles show an excess of common variation and deviate from Hardy-Weinberg equilibrium, consistent with heterozygote advantage and balancing selection. This study provides a generalizable strategy to characterize complex protein coding VNTRs for improved disease associations.

Genetics of chronic respiratory disease

Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma and interstitial lung diseases are frequently occurring disorders with a polygenic basis that account for a large global burden of morbidity and mortality. Recent large-scale genetic epidemiology studies have identified associations between genetic variation and individual respiratory diseases and linked specific genetic variants to quantitative traits related to lung function. These associations have improved our understanding of the genetic basis and mechanisms underlying common lung diseases. Moreover, examining the overlap between genetic associations of different respiratory conditions, along with evidence for gene-environment interactions, has yielded additional biological insights into affected molecular pathways. This genetic information could inform the assessment of respiratory disease risk and contribute to stratified treatment approaches.

The Asthma Risk Gene, GSDMB, Promotes Mitochondrial DNA-induced ISGs Expression

Released mitochondrial DNA (mtDNA) in cells activates cGAS-STING pathway, which induces expression of interferon-stimulated genes (ISGs) and thereby promotes inflammation, as frequently seen in asthmatic airways. However, whether the genetic determinant, Gasdermin B (GSDMB), the most replicated asthma risk gene, regulates this pathway remains unknown. We set out to determine whether and how GSDMB regulates mtDNA-activated cGAS-STING pathway and subsequent ISGs induction in human airway epithelial cells. Using qPCR, ELISA, native polyacrylamide gel electrophoresis, co-immunoprecipitation and immunofluorescence assays, we evaluated the regulation of GSDMB on cGAS-STING pathway in both BEAS-2B cells and primary normal human bronchial epithelial cells (nHBEs). mtDNA was extracted in plasma samples from human asthmatics and the correlation between mtDNA levels and eosinophil counts was analyzed. GSDMB is significantly associated with RANTES expression in asthmatic nasal epithelial brushing samples from the Genes-environments and Admixture in Latino Americans (GALA) II study. Over-expression of GSDMB promotes DNA-induced IFN and ISGs expression in bronchial epithelial BEAS-2B cells and nHBEs. Conversely, knockout of GSDMB led to weakened induction of interferon (IFNs) and ISGs in BEAS-2B cells. Mechanistically, GSDMB interacts with the C-terminus of STING, promoting the translocation of STING to Golgi, leading to the phosphorylation of IRF3 and induction of IFNs and ISGs. mtDNA copy number in serum from asthmatics was significantly correlated with blood eosinophil counts especially in male subjects. GSDMB promotes the activation of mtDNA and poly (dA:dT)-induced activation of cGAS-STING pathway in airway epithelial cells, leading to enhanced induction of ISGs.

Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions

Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

Rhinovirus infection of airway epithelial cells uncovers the non-ciliated subset as a likely driver of genetic susceptibility to childhood-onset asthma

Asthma is a complex disease caused by genetic and environmental factors. Epidemiological studies have shown that in children, wheezing during rhinovirus infection (a cause of the common cold) is associated with asthma development during childhood. This has led scientists to hypothesize there could be a causal relationship between rhinovirus infection and asthma or that RV-induced wheezing identifies individuals at increased risk for asthma development. However, not all children who wheeze when they have a cold develop asthma. Genome-wide association studies (GWAS) have identified hundreds of genetic variants contributing to asthma susceptibility, with the vast majority of likely causal variants being non-coding. Integrative analyses with transcriptomic and epigenomic datasets have indicated that T cells drive asthma risk, which has been supported by mouse studies. However, the datasets ascertained in these integrative analyses lack airway epithelial cells. Furthermore, large-scale transcriptomic T cell studies have not identified the regulatory effects of most non-coding risk variants in asthma GWAS, indicating there could be additional cell types harboring these "missing regulatory effects". Given that airway epithelial cells are the first line of defense against rhinovirus, we hypothesized they could be mediators of genetic susceptibility to asthma. Here we integrate GWAS data with transcriptomic datasets of airway epithelial cells subject to stimuli that could induce activation states relevant to asthma. We demonstrate that epithelial cultures infected with rhinovirus significantly upregulate childhood-onset asthma-associated genes. We show that this upregulation occurs specifically in non-ciliated epithelial cells. This enrichment for genes in asthma risk loci, or 'asthma heritability enrichment' is also significant for epithelial genes upregulated with influenza infection, but not with SARS-CoV-2 infection or cytokine activation. Additionally, cells from patients with asthma showed a stronger heritability enrichment compared to cells from healthy individuals. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.

Evaluation of penalized and machine learning methods for asthma disease prediction in the Korean Genome and Epidemiology Study (KoGES)

BACKGROUND

Genome-wide association studies have successfully identified genetic variants associated with human disease. Various statistical approaches based on penalized and machine learning methods have recently been proposed for disease prediction. In this study, we evaluated the performance of several such methods for predicting asthma using the Korean Chip (KORV1.1) from the Korean Genome and Epidemiology Study (KoGES).

RESULTS

First, single-nucleotide polymorphisms were selected via single-variant tests using logistic regression with the adjustment of several epidemiological factors. Next, we evaluated the following methods for disease prediction: ridge, least absolute shrinkage and selection operator, elastic net, smoothly clipped absolute deviation, support vector machine, random forest, boosting, bagging, naïve Bayes, and k-nearest neighbor. Finally, we compared their predictive performance based on the area under the curve of the receiver operating characteristic curves, precision, recall, F1-score, Cohen's Kappa, balanced accuracy, error rate, Matthews correlation coefficient, and area under the precision-recall curve. Additionally, three oversampling algorithms are used to deal with imbalance problems.

CONCLUSIONS

Our results show that penalized methods exhibit better predictive performance for asthma than that achieved via machine learning methods. On the other hand, in the oversampling study, randomforest and boosting methods overall showed better prediction performance than penalized methods.

Genetics of preschool wheeze and its progression to childhood asthma

Wheezing is a common and heterogeneous condition in preschool children. In some countries, the prevalence can be as high as 30% and up to 50% of all children experience wheezing before the age of 6. Asthma often starts with preschool wheeze, but not all wheezing children will develop asthma at school age. At this moment, it is not possible to accurately predict which wheezing children will develop asthma. Recently, studying the genetics of wheeze and the childhood-onset of asthma have grown in interest. Childhood-onset asthma has a stronger heritability in comparison with adult-onset asthma. In early childhood asthma exacerbations, CDHR3, which encodes the receptor for Rhinovirus C, was identified, as well as IL33, and the 17q locus that includes GSDMB and ORMDL3 genes. The 17q locus is the strongest wheeze and childhood-onset asthma locus, and was shown to interact with many environmental factors, including smoking and infections. Finally, ANXA1 was recently associated with early-onset, persistent wheeze. ANXA1 may help resolve eosinophilic inflammation. Overall, despite its complexities, genetic approaches to unravel the early-onset of wheeze and asthma are promising, since these shed more light on mechanisms of childhood asthma-onset. Implicated genes point toward airway epithelium and its response to external factors, such as viral infections. However, the heterogeneity of wheeze phenotypes complicates genetic studies. It is therefore important to define accurate wheezing phenotypes and forge larger international collaborations to gain a better understanding of the pathways underlying early-onset asthma.

Identification of differences in CD4+ T-cell gene expression between people with asthma and healthy controls

Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that CD4+ T-cells play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. To fill the gap, 3'-RNA-Seq was used to generate gene expression data on CD4+ T-cells (isolated within 2 h from collection) from peripheral blood from participants with well-controlled asthma (n = 32) and healthy controls (n = 11). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules) associated with the asthma phenotype. We identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Through integration of publicly available eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data, we identified PTPRC, a potential druggable target, as a putative master regulator of the asthma gene-expression profiles. Using a co-expression network approach, with integration of external genetic and PPI data, we showed that CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, albeit small in magnitude, compared to healthy controls, for sets of genes involved in immune response to viral infections (upregulated) and antigen processing/presentation (downregulated).

A lifecourse Mendelian randomization study uncovers age-dependent effects of adiposity on asthma risk

Evaluating the long-term consequences of childhood lifestyle factors on asthma risk can be exceptionally challenging in epidemiology given that cases are typically diagnosed at various timepoints throughout the lifecourse. In this study, we used human genetic data to evaluate the effects of childhood and adulthood adiposity on risk of pediatric (n = 13,962 cases) and adult-onset asthma (n = 26,582 cases) with a common set of controls (n = 300,671) using a technique known as lifecourse Mendelian randomization. We found that childhood adiposity directly increases risk of pediatric asthma (OR = 1.20, 95% CI = 1.03-1.37, p = 0.03), but limited evidence that it has an effect on adult-onset asthma after accounting for adiposity during adulthood (OR = 1.05, 95% CI = 0.93-1.17, p = 0.39). Conversely, there was strong evidence that adulthood adiposity increases asthma risk in midlife (OR = 1.37, 95% CI = 1.28-1.46, P = 7 × 10-12). These findings suggest that childhood and adulthood adiposity are independent risk factors for asthma at each of their corresponding timepoints in the lifecourse.

Causal relationship between asthma and ulcerative colitis and the mediating role of interleukin-18: a bidirectional Mendelian study and mediation analysis

Objective

Numerous observational investigations have documented a correlation between asthma and ulcerative colitis(UC). In this Mendelian Randomization (MR) study, we utilized extensive summary data from Genome-Wide Association Studies (GWAS) to further estimate the association between adult-onset asthma and the risk of UC, and to investigate the role of Interleukin-18 (IL-18) as a potential mediator.

Materials and methods

A two-step, two-sample MR study was conducted through mediation analysis. For this study, we employed a two-sample MR analysis using the inverse variance-weighted (IVW), weighted median, weighted mode, and MR-Egger regression techniques. We utilized publicly accessible summary statistics from a GWAS meta-analysis of adult-onset asthma in the UK Biobank (n=327,253; cases=26,582; controls=300,671) as the exposure factor. The outcomes were derived from GWAS data of individuals with European ancestry (n=26,405; cases=6,687; controls=19,718). GWAS data for IL-18 were obtained from individuals of European ancestry (n=9,785,222; cases=3,636; controls=9,781,586).

Results

The MR analysis indicates that adult-onset asthma is associated with an increased risk of UC, with an odds ratio (OR) of 1.019 (95% CI 1.001-1.045, P=0.006). However, there is no strong evidence to suggest that UC significantly impacts the risk of adult-onset asthma. IL-18 may act as a potential mediator in the causal relationship between adult-onset asthma and UC, with a mediation proportion of 3.9% (95% CI, 0.6%-6.9%).

Conclusion

In summary, our study established a causal relationship between asthma and UC, in which IL-18 contributes to a small extent. However, the primary factors underlying the influence of asthma on UC remain unclear. Future research should focus on identifying other potential mediators. In clinical practice, it is important to pay greater attention to intestinal lesions in patients with asthma.

Living in environmental justice areas worsens asthma severity and control: Differential interactions with disease duration, age at onset, and pollution

BACKGROUND

Impoverished and historically marginalized communities often reside in areas with increased air pollution.

OBJECTIVE

We evaluated the association between environmental justice (EJ) track and asthma severity and control as modified by traffic-related air pollution (TRAP).

METHODS

We performed a retrospective study of 1526 adult asthma patients in Allegheny County, Pa, enrolled in an asthma registry during 2007-20. Asthma severity and control were determined using global guidelines. EJ tract designation was based on residency in census tracts with ≥30% non-White and/or ≥20% impoverished populations. TRAP exposures (NO2 and black carbon) for each census tract were normalized into pollution quartiles. Generalized linear model analyses determined the effect of EJ tract and TRAP on asthma.

RESULTS

TRAP exposure in the highest quartile range was more frequent among patients living in an EJ tract (66.4% vs 20.8%, P < .05). Living in an EJ tract increased the odds of severe asthma in later onset asthma. The odds of uncontrolled asthma increased with disease duration in all patients living in EJ tracts (P < .05). Living in the highest quartile of NO2 also increased the odds of uncontrolled asthma in patients with severe disease (P < .05), while there was no effect of TRAP on uncontrolled asthma in patients with less severe disease (P > .05).

CONCLUSIONS

Living in an EJ tract increased the odds of severe and uncontrolled asthma and was influenced by age at onset, disease duration, and potentially by TRAP exposure. This study underscores the need to better understand the complex environmental interactions that affect lung health in groups that have been economically and/or socially marginalized.

Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases

Noncoding variants of presumed regulatory function contribute to the heritability of neuropsychiatric disease. A total of 2,221 noncoding variants connected to risk for ten neuropsychiatric disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, bipolar disorder, borderline personality disorder, major depression, generalized anxiety disorder, panic disorder, post-traumatic stress disorder, obsessive-compulsive disorder and schizophrenia, were studied in developing human neural cells. Integrating epigenomic and transcriptomic data with massively parallel reporter assays identified differentially-active single-nucleotide variants (daSNVs) in specific neural cell types. Expression-gene mapping, network analyses and chromatin looping nominated candidate disease-relevant target genes modulated by these daSNVs. Follow-up integration of daSNV gene editing with clinical cohort analyses suggested that magnesium transport dysfunction may increase neuropsychiatric disease risk and indicated that common genetic pathomechanisms may mediate specific symptoms that are shared across multiple neuropsychiatric diseases.

Identification of asthma-related genes using asthmatic blood eQTLs of Korean patients

BACKGROUND

More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects.

METHODS

We performed a blood eQTL analysis using transcriptomic and genotypic data from 433 Korean asthma patients. To identify asthma-related genes, we carried out colocalization, Summary-based Mendelian Randomization (SMR) analysis, and Transcriptome-Wide Association Study (TWAS) using the results of asthma GWASs and eQTL data. In addition, we compared the results of disease eQTL data and asthma-related genes with two normal blood eQTL data from Genotype-Tissue Expression (GTEx) project and a Japanese study.

RESULTS

We identified 340,274 cis-eQTL and 2,875 eGenes from asthmatic eQTL analysis. We compared the disease eQTL results with GTEx and a Japanese study and found that 64.1% of the 2,875 eGenes overlapped with the GTEx eGenes and 39.0% with the Japanese eGenes. Following the integrated analysis of the asthmatic eQTL data with asthma GWASs, using colocalization and SMR methods, we identified 15 asthma-related genes specific to the Korean asthmatic eQTL data.

CONCLUSIONS

We provided Korean asthmatic cis-eQTL data and identified asthma-related genes by integrating them with GWAS data. In addition, we suggested these asthma-related genes as therapeutic targets for asthma. We envisage that our findings will contribute to understanding the etiological mechanisms of asthma and provide novel therapeutic targets.

Global impact of aberrant splicing on human gene expression levels

Alternative splicing (AS) is pervasive in human genes, yet the specific function of most AS events remains unknown. It is widely assumed that the primary function of AS is to diversify the proteome, however AS can also influence gene expression levels by producing transcripts rapidly degraded by nonsense-mediated decay (NMD). Currently, there are no precise estimates for how often the coupling of AS and NMD (AS-NMD) impacts gene expression levels because rapidly degraded NMD transcripts are challenging to capture. To better understand the impact of AS on gene expression levels, we analyzed population-scale genomic data in lymphoblastoid cell lines across eight molecular assays that capture gene regulation before, during, and after transcription and cytoplasmic decay. Sequencing nascent mRNA transcripts revealed frequent aberrant splicing of human introns, which results in remarkably high levels of mRNA transcripts subject to NMD. We estimate that ~15% of all protein-coding transcripts are degraded by NMD, and this estimate increases to nearly half of all transcripts for lowly-expressed genes with many introns. Leveraging genetic variation across cell lines, we find that GWAS trait-associated loci explained by AS are similarly likely to associate with NMD-induced expression level differences as with differences in protein isoform usage. Additionally, we used the splice-switching drug risdiplam to perturb AS at hundreds of genes, finding that ~3/4 of the splicing perturbations induce NMD. Thus, we conclude that AS-NMD substantially impacts the expression levels of most human genes. Our work further suggests that much of the molecular impact of AS is mediated by changes in protein expression levels rather than diversification of the proteome.

Revealing polygenic pleiotropy using genetic risk scores for asthma

In this study we examined how genetic risk for asthma associates with different features of the disease and with other medical conditions and traits. Using summary statistics from two multi-ancestry genome-wide association studies of asthma, we modeled polygenic risk scores (PRSs) and validated their predictive performance in the UK Biobank. We then performed phenome-wide association studies of the asthma PRSs with 371 heritable traits in the UK Biobank. We identified 228 total significant associations across a variety of organ systems, including associations that varied by PRS model, sex, age of asthma onset, ancestry, and human leukocyte antigen region alleles. Our results highlight pervasive pleiotropy between asthma and numerous other traits and conditions and elucidate pathways that contribute to asthma and its comorbidities.

Investigations of a combination of atopic status and age of asthma onset identify asthma subphenotypes

OBJECTIVE

Subphenotypes of asthma may be determined by age onset and atopic status. We sought to characterize early or late onset atopic asthma with fungal or non-fungal sensitization (AAFS or AANFS) and non-atopic asthma (NAA) in children and adults in the Severe Asthma Research Program (SARP). SARP is an ongoing project involving well-phenotyped patients with mild to severe asthma.

METHODS

Phenotypic comparisons were performed using Kruskal-Wallis or chi-square test. Genetic association analyses were performed using logistic or linear regression.

RESULTS

Airway hyper-responsiveness, total serum IgE levels, and T2 biomarkers showed an increasing trend from NAA to AANFS and then to AAFS. Children and adults with early onset asthma had greater % of AAFS than adults with late onset asthma (46% and 40% vs. 32%; P < 0.00001). In children, AAFS and AANFS had lower % predicted FEV1 (86% and 91% vs. 97%) and greater % of patients with severe asthma than NAA (61% and 59% vs. 43%). In adults with early or late onset asthma, NAA had greater % of patients with severe asthma than AANFS and AAFS (61% vs. 40% and 37% or 56% vs. 44% and 49%). The G allele of rs2872507 in GSDMB had higher frequency in AAFS than AANFS and NAA (0.63 vs. 0.55 and 0.55), and associated with earlier age onset and asthma severity.

CONCLUSIONS

Early or late onset AAFS, AANFS, and NAA have shared and distinct phenotypic characteristics in children and adults. AAFS is a complex disorder involving genetic susceptibility and environmental factors.

Genetic analyses of chr11p15.5 region identify MUC5AC-MUC5B associated with asthma-related phenotypes

OBJECTIVE

Genome-wide association studies (GWASs) have identified single nucleotide polymorphisms (SNPs) in chr11p15.5 region associated with asthma and idiopathic interstitial pneumonias (IIPs). We sought to identify functional genes for asthma by combining SNPs and mRNA expression in bronchial epithelial cells (BEC) in the Severe Asthma Research Program (SARP).

METHODS

Correlation analyses of mRNA expression of six candidate genes (AP2A2, MUC6, MUC2, MUC5AC, MUC5B, and TOLLIP) and asthma phenotypes were performed in the longitudinal cohort (n = 156) with RNAseq in BEC, and replicated in the cross-sectional cohort (n = 155). eQTL (n = 114) and genetic association analysis of asthma severity (426 severe vs. 531 non-severe asthma) were performed, and compared with previously published GWASs of IIPs and asthma.

RESULTS

Higher expression of AP2A2 and MUC5AC and lower expression of MUC5B in BEC were correlated with asthma, asthma exacerbations, and T2 biomarkers (P < 0.01). SNPs associated with asthma and IIPs in previous GWASs were eQTL SNPs for MUC5AC, MUC5B, or TOLLIP, however, they were not in strong linkage disequilibrium. The risk alleles for asthma or protective alleles for IIPs were associated with higher expression of MUC5AC and lower expression of MUC5B. rs11603634, rs12788104, and rs28415845 associated with moderate-to-severe asthma or adult onset asthma in previous GWASs were not associated with asthma severity (P > 0.8).

CONCLUSIONS

SNPs associated with asthma in chr11p15.5 region are not associated with asthma severity neither with IIPs. Higher expression of MUC5AC and lower expression of MUC5B are risk for asthma but protective for IIPs.

Single‑nucleotide polymorphism rs6592645 confers asthma risk through regulating LRRC32 expression

Asthma is a complex disease, often with evident genetic predisposition; for example, the single-nucleotide polymorphism (SNP) rs7130588 was significantly associated with asthma by genome-wide association study (GWAS). Analysis of 1000 Genomes Project data suggests that there is another SNP, rs6592645, in complete linkage disequilibrium with rs7130588 and should present the same signal in GWAS. However, the causal SNP and the mechanism for the association between rs7130588 and asthma remain to be elucidated. In the presents study, results from dual-luciferase assays indicated that the A/G alleles of rs7130588 failed to present significantly different reporter gene expression. By contrast, A allele of rs6592645 presented a significant increase in relative luciferase activity than G allele, thus suggesting that rs6592645 may be a causal SNP. Using chromosome conformation capture, the enhancer region containing rs6592645 was observed to interact with promoter region of leucine-rich repeat-containing 32 (LRRC32). Gene expression quantification suggested that LRRC32 expression is significantly increased in lung tissue of patients with asthma and is dependent on the genotype of this locus, thus verifying that LRRC32 may be involved in asthma onset and that rs6592645 can regulate LRRC32 expression. Through chromatin immunoprecipitation, transcription factor 3 (TCF3) was identified to bind to rs6592645 surrounding region and the interaction between TCF3 and rs6592645 surrounding region was investigated. Results from the present study may improve our understanding of the mechanism by which the genetic variation in this locus might influence asthma susceptibility.

Priority index for asthma (PIA): In silico discovery of shared and distinct drug targets for adult- and childhood-onset disease

Asthma is a chronic disease that is caused by a combination of genetic risks and environmental triggers and can affect both adults and children. Genome-wide association studies have revealed partly distinct genetic architectures for its two age-of-onset subtypes (namely, adult-onset and childhood-onset). We reason that identifying shared and distinct drug targets between these subtypes may inform the development of subtype-specific therapeutic strategies. In attempting this, we here introduce Priority Index for Asthma or PIA, a genetics-led and network-driven drug target prioritisation tool for asthma. We demonstrate the validity of the tool in improving drug target prioritisation for asthma compared to the status quo methods, as well as in capturing the underlying etiology and existing therapeutics for the disease. We also illustrate how PIA can be used to prioritise drug targets for adult- and childhood-onset asthma, as well as to identify shared and distinct pathway crosstalk genes. Shared crosstalk genes are mostly involved in JAK-STAT signaling, with clinical evidence supporting that targeting this pathway may be a promising drug repurposing opportunity for both subtypes. Crosstalk genes specific to childhood-onset asthma are enriched for PI3K-AKT-mTOR signaling, and we identify genes that are already targeted by licensed medications as repurposed drug candidates for this subtype. We make all our results accessible and reproducible at http://www.genetictargets.com/PIA. Collectively, our study has significant implications for asthma computational medicine research and can guide the future development of subtype-specific therapeutic strategies for the disease.

Gene-Smoking Interaction Analysis for the Identification of Novel Asthma-Associated Genetic Factors

Asthma is a complex heterogeneous disease caused by gene-environment interactions. Although numerous genome-wide association studies have been conducted, these interactions have not been systemically investigated. We sought to identify genetic factors associated with the asthma phenotype in 66,857 subjects from the Health Examination Study, Cardiovascular Disease Association Study, and Korea Association Resource Study cohorts. We investigated asthma-associated gene-environment (smoking status) interactions at the level of single nucleotide polymorphisms, genes, and gene sets. We identified two potentially novel (SETDB1 and ZNF8) and five previously reported (DM4C, DOCK8, MMP20, MYL7, and ADCY9) genes associated with increased asthma risk. Numerous gene ontology processes, including regulation of T cell differentiation in the thymus (GO:0033081), were significantly enriched for asthma risk. Functional annotation analysis confirmed the causal relationship between five genes (two potentially novel and three previously reported genes) and asthma through genome-wide functional prediction scores (combined annotation-dependent depletion, deleterious annotation of genetic variants using neural networks, and RegulomeDB). Our findings elucidate the genetic architecture of asthma and improve the understanding of its biological mechanisms. However, further studies are necessary for developing preventive treatments based on environmental factors and understanding the immune system mechanisms that contribute to the etiology of asthma.

Increased Risk of Rheumatoid Arthritis in Patients With Asthma: A Genetic Association Study Using Two-Sample Mendelian Randomization Analysis

OBJECTIVE

Observational studies have explored the association between asthma and some types of arthritis, including rheumatoid arthritis and osteoarthritis, but the results are largely contradictory. We aimed to investigate the causal effects of asthma on arthritis, including osteoarthritis, rheumatoid arthritis, gout, and ankylosing spondylitis.

METHODS

Two-sample Mendelian randomization (MR) analysis was used to investigate the causal effects of asthma on each arthritis. The genetic instruments for asthma were obtained from a large genome-wide association study of asthma. The inverse-variance weighted (IVW) method was used as the main analysis of MR. Bonferroni-adjusted P value threshold was used to account for multiple comparisons.

RESULTS

MR-IVW analysis suggested that adult-onset asthma (AOA) was associated with increased risk of rheumatoid arthritis. The odds ratio for rheumatoid arthritis associated with AOA and childhood-onset asthma (COA) were 1.018 (95% confidence interval [95% CI], 1.011-1.025; P < 0.001) and 1.006 (95% CI 1.001-1.012; P = 0.046), respectively. For osteoarthritis, gout, or ankylosing spondylitis, all the MR analyses showed no significant causal effects of AOA or COA on them. We also performed a reverse MR analysis to explore the causal effects of rheumatoid on all asthma, allergic asthma, or nonallergic asthma and found no significant causal effects on them.

CONCLUSION

Genetically predicted AOA predisposes patients to an increased risk of rheumatoid arthritis but has no causal effects on osteoarthritis, gout, and ankylosing spondylitis. The result of COA on rheumatoid arthritis is suggestive of potential causal relationship but needs to be confirmed in further studies.

Assessing causal relationships between gut microbiota and asthma: evidence from two sample Mendelian randomization analysis

Background

Accumulating evidence has suggested that gut microbiota dysbiosis is commonly observed in asthmatics. However, it remains unclear whether dysbiosis is a cause or consequence of asthma. We aimed to examine the genetic causal relationships of gut microbiota with asthma and its three phenotypes, including adult-onset asthma, childhood-onset asthma, and moderate-severe asthma.

Methods

To elucidate the causality of gut microbiota with asthma, we applied two sample Mendelian randomization (MR) based on the largest publicly available genome-wide association study (GWAS) summary statistics. Inverse variance weighting meta-analysis (IVW) was used to obtain the main estimates; and Weighted median, MR-Egger, Robust Adjusted Profile Score (MR-RAPS), Maximum likelihood method (ML), and MR pleiotropy residual sum and outlier (MR-PRESSO) methods were applied in sensitivity analyses. Finally, a reverse MR analysis was performed to evaluate the possibility of reverse causation.

Results

In the absence of heterogeneity and horizontal pleiotropy, the IVW method revealed that genetically predicted Barnesiella and RuminococcaceaeUCG014 were positively correlated with the risk of asthma, while the association between genetically predicted CandidatusSoleaferrea and asthma was negative. And for the three phenotypes of asthma, genetically predicted Akkermansia reduced the risk of adult-onset asthma, Collinsella and RuminococcaceaeUCG014 increased the risk of childhood-onset asthma, and FamilyXIIIAD3011group, Eisenbergiella, and Ruminiclostridium6 were correlated with the risk of moderate-severe asthma (all P<0.05). The reverse MR analysis didn't find evidence supporting the reverse causality from asthma and its three phenotypes to the gut microbiota genus.

Conclusion

This study suggested that microbial genera were causally associated with asthma as well as its three phenotypes. The findings deepened our understanding of the role of gut microbiota in the pathology of asthma, which emphasizes the potential of opening up a new vista for the prevention and diagnosis of asthma.

3D chromatin reprogramming primes human memory TH2 cells for rapid recall and pathogenic dysfunction

Memory T cells provide long-lasting defense responses through their ability to rapidly reactivate, but how they efficiently "recall" an inflammatory transcriptional program remains unclear. Here, we show that human CD4⁺ memory T helper 2 (T_H2) cells carry a chromatin landscape synergistically reprogrammed at both one-dimensional (1D) and 3D levels to accommodate recall responses, which is absent in naive T cells. In memory T_H2 cells, recall genes were epigenetically primed through the maintenance of transcription-permissive chromatin at distal (super)enhancers organized in long-range 3D chromatin hubs. Precise transcriptional control of key recall genes occurred inside dedicated topologically associating domains ("memory TADs"), in which activation-associated promoter-enhancer interactions were preformed and exploited by AP-1 transcription factors to promote rapid transcriptional induction. Resting memory T_H2 cells from patients with asthma showed premature activation of primed recall circuits, linking aberrant transcriptional control of recall responses to chronic inflammation. Together, our results implicate stable multiscale reprogramming of chromatin organization as a key mechanism underlying immunological memory and dysfunction in T cells.

Genetic differences according to onset age and lung function in asthma: A cluster analysis

BACKGROUND

The extent of differences between genetic risks associated with various asthma subtypes is still unknown. To better understand the heterogeneity of asthma, we employed an unsupervised method to identify genetic variants specifically associated with asthma subtypes. Our goal was to gain insight into the genetic basis of asthma.

METHODS

In this study, we utilized the UK Biobank dataset to select asthma patients (All asthma, n = 50,517) and controls (n = 283,410). We excluded 14,431 individuals who had no information on predicted values of forced expiratory volume in one second percent (FEV1%) and onset age, resulting in a final total of 36,086 asthma cases. We conducted k-means clustering based on asthma onset age and predicted FEV1% using these samples (n = 36,086). Cluster-specific genome-wide association studies were then performed, and heritability was estimated via linkage disequilibrium score regression. To further investigate the pathophysiology, we conducted eQTL analysis with GTEx and gene-set enrichment analysis with FUMA.

RESULTS

Clustering resulted in four distinct clusters: early onset asthma^normalLF (early onset with normal lung function, n = 8172), early onset asthma^reducedLF (early onset with reduced lung function, n = 8925), late-onset asthma^normalLF (late-onset with normal lung function, n = 12,481), and late-onset asthma^reducedLF (late-onset with reduced lung function, n = 6508). Our GWASs in four clusters and in All asthma sample identified 5 novel loci, 14 novel signals, and 51 cluster-specific signals. Among clusters, early onset asthma^normalLF and late-onset asthma^reducedLF were the least correlated (r_g  = 0.37). Early onset asthma^reducedLF showed the highest heritability explained by common variants (h²  = 0.212) and was associated with the largest number of variants (71 single nucleotide polymorphisms). Further, the pathway analysis conducted through eQTL and gene-set enrichment analysis showed that the worsening of symptoms in early onset asthma correlated with lymphocyte activation, pathogen recognition, cytokine receptor activation, and lymphocyte differentiation.

CONCLUSIONS

Our findings suggest that early onset asthma^reducedLF was the most genetically predisposed cluster, and that asthma clusters with reduced lung function were genetically distinct from clusters with normal lung function. Our study revealed the genetic variation between clusters that were segmented based on onset age and lung function, providing an important clue for the genetic mechanism of asthma heterogeneity.

Cell type-specific and disease-associated eQTL in the human lung

Common genetic variants confer substantial risk for chronic lung diseases, including pulmonary fibrosis (PF). Defining the genetic control of gene expression in a cell-type-specific and context-dependent manner is critical for understanding the mechanisms through which genetic variation influences complex traits and disease pathobiology. To this end, we performed single-cell RNA-sequencing of lung tissue from 67 PF and 49 unaffected donors. Employing a pseudo-bulk approach, we mapped expression quantitative trait loci (eQTL) across 38 cell types, observing both shared and cell type-specific regulatory effects. Further, we identified disease-interaction eQTL and demonstrated that this class of associations is more likely to be cell-type specific and linked to cellular dysregulation in PF. Finally, we connected PF risk variants to their regulatory targets in disease-relevant cell types. These results indicate that cellular context determines the impact of genetic variation on gene expression, and implicates context-specific eQTL as key regulators of lung homeostasis and disease.

Variants in JAZF1 are associated with asthma, type 2 diabetes, and height in the United Kingdom biobank population

Background: Asthma, type 2 diabetes (T2D), and anthropometric measures are correlated complex traits that all have a major genetic component. Objective: To investigate the overlap in genetic variants associated with these complex traits. Methods: Using United Kingdom Biobank data, we performed univariate association analysis, fine-mapping, and mediation analysis to identify and dissect shared genomic regions associated with asthma, T2D, height, weight, body mass index (BMI), and waist circumference (WC). Results: We found several genome-wide significant variants in and around the JAZF1 gene that are associated with asthma, T2D, or height with two of these variants shared by the three phenotypes. We also observed an association in this region with WC when adjusted for BMI. However, there was no association with WC when it was not adjusted for BMI or weight. Additionally, only suggestive associations between variants in this region and BMI were observed. Fine-mapping analyses suggested that within JAZF1 there are non-overlapping regions harboring causal susceptibility variants for asthma, T2D, and height. Mediation analyses supported the conclusion that these are independent associations. Conclusion: Our findings indicate that variants in the JAZF1 are associated with asthma, T2D, and height, but the associated causal variant(s) are different for each of the three phenotypes.

Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex immune trait variants using single nucleus ATAC-seq in peripheral blood

Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. Clustering chromatin accessibility profiles of 96,002 total nuclei identified 17 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type using individuals of European ancestry which identified 6,901 caQTLs at FDR < .10 and 4,220 caQTLs at FDR < .05, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For 3,941 caQTLs we further annotated putative target genes of variant activity using single cell co-accessibility, and caQTL variants were significantly correlated with the accessibility level of linked gene promoters. We fine-mapped loci associated with 16 complex immune traits and identified immune cell caQTLs at 622 candidate causal variants, including those with cell type-specific effects. At the 6q15 locus associated with type 1 diabetes, in line with previous reports, variant rs72928038 was a naïve CD4+ T cell caQTL linked to BACH2 and we validated the allelic effects of this variant on regulatory activity in Jurkat T cells. These results highlight the utility of snATAC-seq for mapping genetic effects on accessible chromatin in specific cell types.

Novel Functional Features of cGMP Substrate Proteins IRAG1 and IRAG2

The inositol triphosphate-associated proteins IRAG1 and IRAG2 are cGMP kinase substrate proteins that regulate intracellular Ca²⁺. Previously, IRAG1 was discovered as a 125 kDa membrane protein at the endoplasmic reticulum, which is associated with the intracellular Ca²⁺ channel IP₃R-I and the PKGIβ and inhibits IP₃R-I upon PKGIβ-mediated phosphorylation. IRAG2 is a 75 kDa membrane protein homolog of IRAG1 and was recently also determined as a PKGI substrate. Several (patho-)physiological functions of IRAG1 and IRAG2 were meanwhile elucidated in a variety of human and murine tissues, e.g., of IRAG1 in various smooth muscles, heart, platelets, and other blood cells, of IRAG2 in the pancreas, heart, platelets, and taste cells. Hence, lack of IRAG1 or IRAG2 leads to diverse phenotypes in these organs, e.g., smooth muscle and platelet disorders or secretory deficiency, respectively. This review aims to highlight the recent research regarding these two regulatory proteins to envision their molecular and (patho-)physiological tasks and to unravel their functional interplay as possible (patho-)physiological counterparts.

Socioeconomic status and asthma: A bidirectional Mendelian randomization study

Background

Asthma is closely associated with lower socioeconomic status (SES), while the causal relationship between asthma and SES is undetermined. We aim to examine bidirectional relationships between asthma and SES using two-sample bidirectional Mendelian randomization (MR) for assessing potential causal inference.

Methods

Education attainment (years of schooling), household income, and Townsend deprivation index (TDI) were 3 indicators of SES considered in our study. The genetic summary data for SES and asthma were retrieved from publicly available genome-wide association studies (GWASs) conducted in participants of European ancestry. The MR estimates from each genetic instrument were combined using random effects inverse variance weighted (IVW) meta-analysis, with alternate methods (eg, MR-Egger, weighted median). Horizontal pleiotropy was assessed by sensitivity analyses. Analyses were performed using the package TwoSampleMR in R.

Results

The genetically instrumented years of schooling, household income, and TDI were not associated with the risk of asthma. However, according to the IVW method, 1.72 times increase in the odds ratio (OR) for asthma will lead to 0.024 standard deviation (SD) decrease in the years of schooling, 0.026 SD decrease in the household income, and 0.016 SD increase in the TDI. Although the substantial heterogeneity may undermine the reliability of results to some extent, sensitivity analyses further supported the causation of low household income by asthma.

Conclusion

Our study indicated that genetically predicted asthma may play a causal role in lowering the household income. However, the causal role of lower SES in asthma development was not supported by our MR analyses. Considering the heterogeneity in the current study, additional MR studies are needed to validate the results in the future.

Risk Factors and Age-Related Patterns of Asthma-Like Symptoms in Early Childhood

BACKGROUND

Episodes of asthma-like symptoms in young children are common, but little is known about risk factors and their patterns for the daily symptom burden.

OBJECTIVE

We investigated a variety of possible risk factors and their age-related impact on the number of asthma-like episodes during age 0 to 3 years.

METHODS

The study population included 700 children from the Copenhagen Prospective Studies on Asthma in Childhood2010 mother-child cohort followed prospectively from birth. Asthma-like symptoms were recorded until age 3 by daily diaries. Risk factors were analyzed by quasi-Poisson regressions, and interaction with age was explored.

RESULTS

Diary data were available in 662 children. Male sex, maternal asthma, low birth weight, maternal antibiotic use, high asthma exacerbation polygenic risk score, and high airway immune score were associated with a higher number of episodes in a multivariable analysis. Maternal asthma, preterm birth, caesarean section, and low birth weight showed an increasing impact with age, whereas sibling(s) at birth showed a decreased association with age. The remaining risk factors had a stable pattern during age 0 to 3 years. For every additional clinical risk factor (male sex, low birth weight, and maternal asthma) a child had, we found 34% more episodes (incidence rate ratio: 1.34, 95% confidence interval: 1.21-1.48; P < .001).

CONCLUSION

Using unique day-to-day diary recordings, we identified risk factors for the burden of asthma-like symptoms in the first 3 years of life and described their unique age-related patterns. This provides novel insight into the origin of asthma-like symptoms in early childhood that potentially pave a path for personalized prognostics and treatment.

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.

CLEC16A-An Emerging Master Regulator of Autoimmunity and Neurodegeneration

CLEC16A is emerging as an important genetic risk factor for several autoimmune disorders and for Parkinson disease (PD), opening new avenues for translational research and therapeutic development. While the exact role of CLEC16A in health and disease is still being elucidated, the gene plays a critical role in the regulation of autophagy, mitophagy, endocytosis, intracellular trafficking, immune function, and in biological processes such as insulin secretion and others that are important to cellular homeostasis. As shown in both human and animal modeling studies, CLEC16A hypofunction predisposes to both autoinflammatory phenotype and neurodegeneration. While the two are clearly related, further functional studies are needed to fully understand the mechanisms involved for optimized therapeutic interventions. Based on recent data, mitophagy-inducing drugs may be warranted, and such therapy should be tested in clinical trials as these drugs would tackle the underlying pathogenic mechanism (s) and could treat or prevent symptoms of autoimmunity and neurodegeneration in individuals with CLEC16A risk variants. Accordingly, interventions directed at reversing the dysregulated mitophagy and the consequences of loss of function of CLEC16A without activating other detrimental cellular pathways could present an effective therapy. This review presents the emerging role of CLEC16A in health and disease and provides an update on the disease processes that are attributed to variants located in the CLEC16A gene, which are responsible for autoimmune disorders and neurodegeneration with emphasis on how this information is being translated into practical and effective applications in the clinic.

Understanding the relationship between asthma and autism spectrum disorder: a population-based family and twin study

BACKGROUND

There is some evidence that autism spectrum disorder (ASD) frequently co-occurs with immune-mediated conditions including asthma. We aimed to explore the familial co-aggregation of ASD and asthma using different genetically informed designs.

METHODS

We first examined familial co-aggregation of asthma and ASD in individuals born in Sweden from 1992 to 2007 (n = 1 569 944), including their full- and half-siblings (n = 1 704 388 and 356 544 pairs) and full cousins (n = 3 921 890 pairs), identified using Swedish register data. We then applied quantitative genetic modeling to siblings (n = 620 994 pairs) and twins who participated in the Child and Adolescent Twin Study in Sweden (n = 15 963 pairs) to estimate the contribution of genetic and environmental factors to the co-aggregation. Finally, we estimated genetic correlations between traits using linkage disequilibrium score regression (LDSC).

RESULTS

We observed a within-individual association [adjusted odds ratio (OR) 1.33, 95% confidence interval (CI) 1.28-1.37] and familial co-aggregation between asthma and ASD, and the magnitude of the associations decreased as the degree of relatedness decreased (full-siblings: OR 1.44, 95% CI 1.38-1.50, maternal half-siblings: OR 1.28, 95% CI 1.18-1.39, paternal half-siblings: OR 1.05, 95% CI 0.96-1.15, full cousins: OR 1.06, 95% CI 1.03-1.09), suggesting shared familial liability. Quantitative genetic models estimated statistically significant genetic correlations between ASD traits and asthma. Using the LDSC approach, we did not find statistically significant genetic correlations between asthma and ASD (coefficients between -0.09 and 0.12).

CONCLUSIONS

Using different genetically informed designs, we found some evidence of familial co-aggregation between asthma and ASD, suggesting the weak association between these disorders was influenced by shared genetics.

Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease

STAT6 (signal transducer and activator of transcription 6) is a transcription factor that plays a central role in the pathophysiology of allergic inflammation. We have identified 16 patients from 10 families spanning three continents with a profound phenotype of early-life onset allergic immune dysregulation, widespread treatment-resistant atopic dermatitis, hypereosinophilia with esosinophilic gastrointestinal disease, asthma, elevated serum IgE, IgE-mediated food allergies, and anaphylaxis. The cases were either sporadic (seven kindreds) or followed an autosomal dominant inheritance pattern (three kindreds). All patients carried monoallelic rare variants in STAT6 and functional studies established their gain-of-function (GOF) phenotype with sustained STAT6 phosphorylation, increased STAT6 target gene expression, and TH2 skewing. Precision treatment with the anti-IL-4Rα antibody, dupilumab, was highly effective improving both clinical manifestations and immunological biomarkers. This study identifies heterozygous GOF variants in STAT6 as a novel autosomal dominant allergic disorder. We anticipate that our discovery of multiple kindreds with germline STAT6 GOF variants will facilitate the recognition of more affected individuals and the full definition of this new primary atopic disorder.

Upregulated Expression of the IL-9 Receptor on TRAF3-Deficient B Lymphocytes Confers Ig Isotype Switching Responsiveness to IL-9 in the Presence of Antigen Receptor Engagement and IL-4

The pleiotropic cytokine IL-9 signals to target cells by binding to a heterodimeric receptor consisting of the unique subunit IL-9R and the common subunit γ-chain shared by multiple cytokines of the γ-chain family. In the current study, we found that the expression of IL-9R was strikingly upregulated in mouse naive follicular B cells genetically deficient in TNFR-associated factor 3 (TRAF3), a critical regulator of B cell survival and function. The highly upregulated IL-9R on Traf3-/- follicular B cells conferred responsiveness to IL-9, including IgM production and STAT3 phosphorylation. Interestingly, IL-9 significantly enhanced class switch recombination to IgG1 induced by BCR crosslinking plus IL-4 in Traf3-/- B cells, which was not observed in littermate control B cells. We further demonstrated that blocking the JAK-STAT3 signaling pathway abrogated the enhancing effect of IL-9 on class switch recombination to IgG1 induced by BCR crosslinking plus IL-4 in Traf3-/- B cells. Our study thus revealed, to our knowledge, a novel pathway that TRAF3 suppresses B cell activation and Ig isotype switching by inhibiting IL-9R-JAK-STAT3 signaling. Taken together, our findings provide (to our knowledge) new insights into the TRAF3-IL-9R axis in B cell function and have significant implications for the understanding and treatment of a variety of human diseases involving aberrant B cell activation such as autoimmune disorders.

Celiac Disease Is a Risk Factor for Mature T and NK Cell Lymphoma: A Mendelian Randomization Study

Celiac disease (CeD) is an immune-mediated disorder triggered by gluten ingestion that damages the small intestine. Although CeD has been associated with a higher risk for cancer, the role of CeD as a risk factor for specific malignancies, such as enteropathy-associated T-cell lymphoma (EATL), remains controversial. Using two-sample Mendelian randomization (2SMR) methods and the summarized results of large genome-wide association studies from public repositories, we addressed the causal relationship between CeD and eight different malignancies. Eleven non-HLA SNPs were selected as instrumental variables (IVs), and causality estimates were obtained using four 2SMR methods: random-effects inverse variance-weighted, weighted median estimation, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO). We identified a significant causal relationship between CeD and mature T/NK cell lymphomas. Under a multivariate Mendelian randomization model, we observed that the causal effect of CeD was not dependent on other known lymphoma risk factors. We found that the most instrumental IV was located in the TAGAP locus, suggesting that aberrant T cell activation might be relevant in the T/NK cell malignization process. Our findings provide new insights into the connection between immune imbalance and the development of severe comorbidities, such as EATL, in patients with CeD.

Asthma

Asthma is one of the most common chronic non-communicable diseases worldwide and is characterised by variable airflow obstruction, causing dyspnoea and wheezing. Highly effective therapies are available; asthma morbidity and mortality have vastly improved in the past 15 years, and most patients can attain good asthma control. However, undertreatment is still common, and improving patient and health-care provider understanding of when and how to adjust treatment is crucial. Asthma management consists of a cycle of assessment of asthma control and risk factors and adjustment of medications accordingly. With the introduction of biological therapies, management of severe asthma has entered the precision medicine era-a shift that is driving clinical ambitions towards disease remission. Patients with severe asthma often have co-existing conditions contributing to their symptoms, mandating a multidimensional management approach. In this Seminar, we provide a clinically focused overview of asthma; epidemiology, pathophysiology, diagnosis, and management in children and adults.

Benchmarking omics-based prediction of asthma development in children

BACKGROUND

Asthma is a heterogeneous disease with high morbidity. Advancement in high-throughput multi-omics approaches has enabled the collection of molecular assessments at different layers, providing a complementary perspective of complex diseases. Numerous computational methods have been developed for the omics-based patient classification or disease outcome prediction. Yet, a systematic benchmarking of those methods using various combinations of omics data for the prediction of asthma development is still lacking.

OBJECTIVE

We aimed to investigate the computational methods in disease status prediction using multi-omics data.

METHOD

We systematically benchmarked 18 computational methods using all the 63 combinations of six omics data (GWAS, miRNA, mRNA, microbiome, metabolome, DNA methylation) collected in The Vitamin D Antenatal Asthma Reduction Trial (VDAART) cohort. We evaluated each method using standard performance metrics for each of the 63 omics combinations.

RESULTS

Our results indicate that overall Logistic Regression, Multi-Layer Perceptron, and MOGONET display superior performance, and the combination of transcriptional, genomic and microbiome data achieves the best prediction. Moreover, we find that including the clinical data can further improve the prediction performance for some but not all the omics combinations.

CONCLUSIONS

Specific omics combinations can reach the optimal prediction of asthma development in children. And certain computational methods showed superior performance than other methods.

Decoding the genetic and epigenetic basis of asthma

Asthma is a complex and heterogeneous chronic inflammatory disease of the airways. Alongside environmental factors, asthma susceptibility is strongly influenced by genetics. Given its high prevalence and our incomplete understanding of the mechanisms underlying disease susceptibility, asthma is frequently studied in genome-wide association studies (GWAS), which have identified thousands of genetic variants associated with asthma development. Virtually all these genetic variants reside in non-coding genomic regions, which has obscured the functional impact of asthma-associated variants and their translation into disease-relevant mechanisms. Recent advances in genomics technology and epigenetics now offer methods to link genetic variants to gene regulatory elements embedded within non-coding regions, which have started to unravel the molecular mechanisms underlying the complex (epi)genetics of asthma. Here, we provide an integrated overview of (epi)genetic variants associated with asthma, focusing on efforts to link these disease associations to biological insight into asthma pathophysiology using state-of-the-art genomics methodology. Finally, we provide a perspective as to how decoding the genetic and epigenetic basis of asthma has the potential to transform clinical management of asthma and to predict the risk of asthma development.

Lipid-induced transcriptomic changes in blood link to lipid metabolism and allergic response

Immune cell function can be altered by lipids in circulation, a process potentially relevant to lipid-associated inflammatory diseases including atherosclerosis and rheumatoid arthritis. To gain further insight in the molecular changes involved, we here perform a transcriptome-wide association analysis of blood triglycerides, HDL cholesterol, and LDL cholesterol in 3229 individuals, followed by a systematic bidirectional Mendelian randomization analysis to assess the direction of effects and control for pleiotropy. Triglycerides are found to induce transcriptional changes in 55 genes and HDL cholesterol in 5 genes. The function and cell-specific expression pattern of these genes implies that triglycerides downregulate both cellular lipid metabolism and, unexpectedly, allergic response. Indeed, a Mendelian randomization approach based on GWAS summary statistics indicates that several of these genes, including interleukin-4 (IL4) and IgE receptors (FCER1A, MS4A2), affect the incidence of allergic diseases. Our findings highlight the interplay between triglycerides and immune cells in allergic disease.

FGF20 and PGM2 variants are associated with childhood asthma in family-based whole-genome sequencing studies

BACKGROUND

Asthma is a heterogeneous common respiratory disease that remains poorly understood. The established genetic associations fail to explain the high estimated heritability, and the prevalence of asthma differs between populations and geographic regions. Robust association analyses incorporating different genetic ancestries and whole-genome sequencing data may identify novel genetic associations.

METHODS

We performed family-based genome-wide association analyses of childhood-onset asthma based on whole-genome sequencing (WGS) data for the 'The Genetic Epidemiology of Asthma in Costa Rica' study (GACRS) and the Childhood Asthma Management Program (CAMP). Based on parent-child trios with children diagnosed with asthma, we performed a single variant analysis using an additive and a recessive genetic model and a region-based association analysis of low-frequency and rare variants.

RESULTS

Based on 1180 asthmatic trios (894 GACRS trios and 286 CAMP trios, a total of 3540 samples with WGS data), we identified three novel genetic loci associated with childhood-onset asthma: rs4832738 on 4p14 ($P=1.72\ast{10}^{-9}$, recessive model), rs1581479 on 8p22 ($P=1.47\ast{10}^{-8}$, additive model) and rs73367537 on 10q26 ($P=1.21\ast{10}^{-8}$, additive model in GACRS only). Integrative analyses suggested potential novel candidate genes underlying these associations: PGM2 on 4p14 and FGF20 on 8p22.

CONCLUSION

Our family-based whole-genome sequencing analysis identified three novel genetic loci for childhood-onset asthma. Gene expression data and integrative analyses point to PGM2 on 4p14 and FGF20 on 8p22 as linked genes. Furthermore, region-based analyses suggest independent potential low-frequency/rare variant associations on 8p22. Follow-up analyses are needed to understand the functional mechanisms and generalizability of these associations.

Mendelian Randomization Analysis Reveals a Complex Genetic Interplay among Atopic Dermatitis, Asthma, and Gastroesophageal Reflux Disease

Rationale: Gastroesophageal reflux disease (GERD) is commonly associated with atopic disorders, but cause-effect relationships remain unclear. Objectives: We applied Mendelian randomization analysis to explore whether GERD is causally related to atopic disorders of the lung (asthma) and/or skin (atopic dermatitis [AD]). Methods: We conducted two-sample bidirectional Mendelian randomization to infer the magnitude and direction of causality between asthma and GERD, using summary statistics from the largest genome-wide association studies conducted on asthma (Ncases = 56,167) and GERD (Ncases = 71,522). In addition, we generated instrumental variables for AD from the latest population-level genome-wide association study meta-analysis (Ncases = 22,474) and assessed their fidelity and confidence of predicting the likely causal pathway(s) leading to asthma and/or GERD. Measurements and Main Results: Applying three different methods, each method revealed similar magnitude of causal estimates that were directionally consistent across the sensitivity analyses. Using an inverse variance-weighted method, the largest effect size was detected for asthma predisposition to AD (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.34-1.59), followed by AD to asthma (OR, 1.34; 95% CI, 1.24-1.45). A significant association was detected for genetically determined asthma on risk of GERD (OR, 1.06; 95% CI, 1.03-1.09) but not genetically determined AD on GERD. In contrast, GERD equally increased risks of asthma (OR, 1.21; 95% CI, 1.09-1.35) and AD (OR, 1.21; 95% CI, 1.07-1.37). Conclusions: This study uncovers previously unrecognized causal pathways that have clinical implications in European-ancestry populations: 1) asthma is a causal risk for AD, and 2) the predisposition to AD, including asthma, can arise from specific pathogenic mechanisms manifested by GERD.

Genetic adaptation to pathogens and increased risk of inflammatory disorders in post-Neolithic Europe

Ancient genomics can directly detect human genetic adaptation to environmental cues. However, it remains unclear how pathogens have exerted selective pressures on human genome diversity across different epochs and affected present-day inflammatory disease risk. Here, we use an ancestry-aware approximate Bayesian computation framework to estimate the nature, strength, and time of onset of selection acting on 2,879 ancient and modern European genomes from the last 10,000 years. We found that the bulk of genetic adaptation occurred after the start of the Bronze Age, <4,500 years ago, and was enriched in genes relating to host-pathogen interactions. Furthermore, we detected directional selection acting on specific leukocytic lineages and experimentally demonstrated that the strongest negatively selected candidate variant in immunity genes, lipopolysaccharide-binding protein (LBP) D283G, is hypomorphic. Finally, our analyses suggest that the risk of inflammatory disorders has increased in post-Neolithic Europeans, possibly because of antagonistic pleiotropy following genetic adaptation to pathogens.