Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks

Dissecting the genetic basis and mechanisms underlying the associations between multiple extrahepatic factors and autoimmune liver diseases

Background

Autoimmune liver diseases (AILDs) encompass autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC). The onset of these diseases is fundamentally influenced by genetic susceptibility. Although various extrahepatic factors are potentially linked to AILDs, the genetic underpinnings and mechanisms of these associations remain unclear.

Methods

Utilizing large-scale genome-wide association study (GWAS) data, this study systematically investigated the relationships between extrahepatic autoimmune diseases (EHAIDs), immune cells, and various triggering factors with AILDs. Mendelian randomization (MR) was employed to assess the causal effects of these extrahepatic factors on AILDs, complemented by linkage disequilibrium score (LDSC) regression to uncover shared genetic architecture and causal effects underlying the associations between autoimmune diseases. We employed colocalization, enrichment analysis, and protein-protein interaction (PPI) network to identify the functions of shared loci. Additionally, we proposed that activated immune cells in the circulation may contribute to liver and biliary tract inflammation via migration, mediating the impact of extrahepatic factors on AILDs. This hypothesis was tested using two mediation analysis methods: two-step MR (TSMR) and multivariable MR (MVMR).

Results

Causal associations between multiple extrahepatic factors and AILDs were identified. Notably, CD27+ B cells were found to be a risk factor for PBC, while PSC progression was associated with CD28+ CD8+ T cells exhaustion and increased levels of CD28- CD8+ T cells. Mediation analyses revealed 64 pathways via TSMR and 15 pathways via MVMR, indicating that the effects of extrahepatic factors on AILDs may be mediated by circulating immune cells. The shared genetic architecture also contributed to these associations. Analysis of shared loci and gene functions identified ATXN2 as being shared between PBC and 9 EHAIDs, while SH2B3 and PSMG1 were shared with 6 and 5 EHAIDs, respectively, in PSC.

Conclusions

Our research compared three distinct AILDs, enhancing the understanding of their etiology and providing new evidence on risk factors, diagnostic markers, and potential therapeutic targets.

Advances in asthma and allergic disease genetics

PURPOSE OF REVIEW

Asthma and allergic disease are common chronic conditions affecting individuals of all ages. The contribution of genetics to the risk of asthma and allergic diseases is well established, yet the mechanisms through which genetic variation contribute to risk continues to be investigated. This review focuses on recent advances made in genetic studies of asthma and allergic disease phenotypes.

RECENT FINDINGS

Progress has been made at expanding genetic studies of asthma and allergic diseases in more diverse and non-European populations, and genetic associations have been made with loci and more refined phenotypes associated with these conditions. Among the 11 large genome-wide association studies or admixture mapping studies published recently, 52 novel associations were identified for asthma and allergic disease phenotypes. As in previous studies, variant- and genome-based heritability remains relatively low. The use of polygenic risk scores in asthma and allergic diseases has increased and reinforces the remarkable overlap of the genetic risk of these conditions. Whole genome and exome sequencing has led to associations of specific genes with these conditions, including rare STAT6 gain-of-function mutations that were identified in individuals with multiple, severe and early life allergic diseases and asthma.

SUMMARY

Overall, we have learned that asthma and allergic diseases phenotypes are highly polygenic and have considerable overlap in their genetic landscapes.

Chronic overlapping pain conditions and nociplastic pain

Chronic overlapping pain conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and individuals assigned female at birth (AFAB). Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome-wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic pain, followed by genetic correlation (linkage disequilibrium score regression), gene set, and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic pain, and showed nociplastic pain to be a polygenic trait with significant SNP heritability. We found significant genetic overlap between multisite chronic pain and nociplastic pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic pain along with distinct pathology in migraine and headache. We used a well-powered network approach to investigate nociplastic pain using existing COPC GWAS output, and show nociplastic pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.

Copy Number Variation in Asthma: An Integrative Review

Asthma is a complex disease with varied clinical manifestations resulting from the interaction between environmental and genetic factors. While chronic airway inflammation and hyperresponsiveness are central features, the etiology of asthma is multifaceted, leading to a diversity of phenotypes and endotypes. Although most research into the genetics of asthma focused on the analysis of single nucleotide polymorphisms (SNPs), studies highlight the importance of structural variations, such as copy number variations (CNVs), in the inheritance of complex characteristics, but their role has not yet been fully elucidated in asthma. In this context, an integrative review was conducted to identify the genes and pathways involved, the location, size, and classes of CNVs, as well as their contribution to asthma risk, severity, control, and response to treatment. As a result of the review, 16 articles were analyzed, from different types of observational studies, such as case-control, cohort studies and genotyped-proband or trios design, that have been carried out in populations from different countries, ethnicities, and ages. Chromosomes 12 and 17 were the most studied in three publications each. CNVs located on 12 chromosomes were associated with asthma, the majority being found on chromosome 6p and 17q, of the deletion type, encompassing 30 different coding-protein genes and one pseudogene region. Six genes with CNVs were identified as significant expression quantitative locus (eQTLs) with mean expression in asthma-related tissues, such as the lung and whole blood. The phenotypic variability of asthma may hinder the clinical application of these findings, but the research shows the importance of investigating these genetic variations as possible biomarkers in asthma patients.

Human intraepithelial mast cell differentiation and effector function are directed by TGF-β signaling

Mast cells (MCs) expressing a distinctive protease phenotype (MCTs) selectively expand within the epithelium of human mucosal tissues during type 2 (T2) inflammation. While MCTs are phenotypically distinct from subepithelial MCs (MCTCs), signals driving human MCT differentiation and this subset's contribution to inflammation remain unexplored. Here, we have identified TGF-β as a key driver of the MCT transcriptome in nasal polyps. We found that short-term TGF-β signaling alters MC cell surface receptor expression and partially recapitulated the in vivo MCT transcriptome, while TGF-β signaling during MC differentiation upregulated a larger number of MCT-associated transcripts. TGF-β inhibited the hallmark MCTC proteases chymase and cathepsin G at both the transcript and protein level, allowing selective in vitro differentiation of MCTs for functional study. We identified discrete differences in effector phenotype between in vitro-derived MCTs and MCTCs, with MCTs exhibiting enhanced proinflammatory lipid mediator generation and a distinct cytokine, chemokine, and growth factor production profile in response to both innate and adaptive stimuli, recapitulating functional features of their tissue-associated counterpart MC subsets. Thus, our findings support a role for TGF-β in promoting human MCT differentiation and identified a discrete contribution of this cell type to T2 inflammation.

Polygenic scores and their applications in kidney disease

Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications.

A genome-wide meta-analysis reveals shared and population-specific variants for allergic sensitization

BACKGROUND

Allergic diseases are major causes of morbidity in both developed and developing countries and represent a global burden on health care systems. Allergic sensitization is defined as the production of IgE specific to common environmental allergens and is an important indicator in the assessment of allergic diseases.

OBJECTIVE

We sought to clarify the genetic basis of allergic sensitization.

METHODS

We performed a genome-wide association study (GWAS) of allergic sensitization in the Japanese population followed by a cross-ancestry meta-analysis with a European population including 20,492 cases and 23,342 controls for Japanese and 8,246 cases and 16,786 controls for Europeans. We also performed a polysensitization GWAS of a Japanese population including 4,923 cases and 17,009 controls.

RESULTS

Allergic sensitization GWAS identified 18 susceptibility loci for Japanese only and 23 loci for the cross-ancestry population, among which 4 loci were novel. Polysensitization GWAS identified 8 significant loci. Expression quantitative trait locus colocalization analysis revealed polysensitization GWAS significant variants affecting both the phenotype and the expression of the CD28, LPP, and LRCC32 genes. Cross-population genetic correlation analysis of allergic sensitization suggested that heterogeneity exists in allergic sensitization between Europeans and Japanese, indicating that more genetic heterogeneity may exist in allergic sensitization than allergic diseases.

CONCLUSIONS

Our investigation provides new insights into the molecular mechanism of allergic sensitization that could enhance current understanding of allergy and allergic diseases.

Mendelian randomization study on the association of circulating ketone bodies with lung cancer and respiratory diseases

The liver produces various ketone bodies (KBs) including 3-Hydroxybutyrate (3-OHB), acetoacetate (AcAc), and acetone, with 3-OHB being the major component. Previous studies have shown that KBs protect against respiratory diseases; however, there is no evidence of a genetic link. To avoid biases existing in traditional observational studies, a two-sample Mendelian randomization (MR) analysis was carried out to investigate genetic causation and novel therapeutic uses for KBs. This study used databases from genome-wide association studies (GWAS) and single nucleotide polymorphisms as instrumental variables for KBs from a recently published metabonomics study (n = 121,584) and respiratory diseases [lung cancer, n = 85,716; asthma, n = 127,669; chronic bronchitis, n = 450,422; chronic obstructive pulmonary disease (COPD), n = 468,475; FEV1/FVC < 0.7, n = 353,315] from their publicly available GWAS, respectively. Strong sets of instrumental variables (P < 5 × 10- 8) were selected, with inverse-variance weighted as the primary MR method. Sensitivity analyses included Cochran's Q test, MR Egger, MR-PRESSO, leave-one-out test, and funnel plots. The Steiger test and reversed MR were used to exclude reverse causality. Additionally, independent replication MR studies were conducted using databases from another large public GWAS and similar methods as described above. After MR analyses and sensitivity filtering, we discovered a protective effect of 3-OHB on lung cancer (odds ratio [OR] = 0.771; 95% confidence interval [CI] = 0.648-0.916; PFDR=0.006), small cell carcinoma (OR = 0.485, 95% CI = 0.301-0.781, PFDR=0.006), asthma (OR = 0.585, 95% CI = 0.395-0.867, PFDR=0.010), chronic bronchitis (OR = 0.753, 95% CI = 0.570-0.994, PFDR=0.045), COPD (OR = 0.690, 95% CI = 0.535-0.890, PFDR=0.008) and lung function (OR = 0.970, 95%CI = 0.950-0.990, PFDR =0.008). In summary, our findings suggest that 3-OHB acts as a protective factor against lung cancer and respiratory diseases. However, heterogeneity implies that other mechanisms may also be involved in COPD improvement by 3-OHB.

Breastfeeding, genetic susceptibility, and the risk of asthma and allergic diseases in children and adolescents: a retrospective national population-based cohort study

BACKGROUND

Asthma and allergic diseases (such as allergic rhinitis) are multifactorial chronic respiratory diseases, and have many common pathogenic mechanisms. This study aimed to assess the joint effects of breastfeeding and genetic susceptibility on asthma, allergic disease in children and adolescents and sought to examine whether the effect of breastfeeding was consistent under distinct levels of genetic risk.

METHODS

A total of 351,931 UK Biobank participants were analyzed. Firstly, Cox proportional hazards model was used to evaluate the relation between breastfeeding and asthma, allergic disease and their comorbidity. Next, we incorporated the polygenic risk score as an additional covariate into the model. Then, we explored the role of breastfeeding at each stage of asthma and allergic disease through a multi-state model. Meanwhile, several sensitivity analyses were conducted to evaluate the robustness of our results. Finally, we calculated the attributable protection and population attributable protection of breastfeeding.

RESULTS

Breastfeeding was related to a reduced risk of occurring asthma (adjusted hazard ratio [HR] = 0.89, 95% confidence interval [CI] 0.86 ~ 0.93), allergic disease (HR = 0.89, 95%CI 0.87 ~ 0.91) and comorbidity (HR = 0.89, 95%CI 0.83 ~ 0.94). The effect of breastfeeding was almost unchanged after considering PRS and did not substantially differ across distinct genetic risk levels. Breastfeeding showed a stronger risk-decreased impact on individuals who developed from allergic rhinitis to comorbidity (HR = 0.83, 95%CI 0.73 ~ 0.93). Further, the influence of breastfeeding was robust against covariates considered and the confounding influence of adolescent smoking. Finally, due to breastfeeding, 12.0%, 13.0% or 13.0% of the exposed population would not suffer from asthma, allergic diseases and the comorbidity, while 7.1%, 7.6% or 7.6% of the general population would not suffer from these diseases.

CONCLUSIONS

This study provided supportive evidence for the risk-reduced effect of breastfeeding on asthma, allergic diseases, and the comorbidity in children and adolescents, and further revealed that such an influence was consistent across distinct genetic risk levels.

Epigenetic signatures of asthma: a comprehensive study of DNA methylation and clinical markers

BACKGROUND

Asthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma.

METHODS

The Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood from 319 participants from 94 families. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 individuals. Principal component analysis on the clinical asthma markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates.

RESULTS

221 unique CpGs reached genome-wide significance at timepoint 1 after Bonferroni correction. PC7, which correlated with loadings of eosinophil counts and immunoglobulin levels, accounted for the majority of associations (204). Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points yielded a correlation of 0.81.

CONCLUSION

We identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to a robust DNA methylation profile as a new, stable biomarker for asthma.

Ambient air pollution and risk of allergic respiratory diseases in European and East Asian populations: A Mendelian randomization study

BACKGROUND

Ambient air pollution has become a challenging global health issue since industrialization, especially affecting respiratory diseases. However, the causal link between air pollution and allergic respiratory diseases (ARDs) remains unclear due to confounding factors in conventional epidemiological studies across different populations. Thus, we aimed to clarify the causal associations between air pollution and ARDs in European and East Asian populations using Mendelian randomization (MR).

METHODS

MR utilizes genetic variants and provides a satisfactory level of causal evidence. Genetic data for exposures (PM2.5, PM2.5 absorbance, PM10, PMcoarse, NO2 and NOx) and outcomes (allergic rhinitis, chronic rhinosinusitis, asthma, and obesity related asthma) were obtained from genome-wide association studies. Instrumental variables were strictly filtered based on core assumptions. Two-sample MR and sensitivity analyses were conducted separately for European and East Asian populations.

RESULTS

PMcoarse was causally associated with an increased risk of chronic rhinosinusitis (OR = 1.588 [1.002-2.518]; p = 0.049) and obesity related asthma (OR = 1.956 [1.012-3.780]; p = 0.046) in European population, and PM10 was associated with a decreased risk of allergic rhinitis in East Asian population (OR = 0.882 [0.798-0.974]; p = 0.013). No heterogeneity or pleiotropy was detected in any significant causal association.

CONCLUSION

Our findings indicate that ambient air pollution has opposite impacts on the etiology of ARDs in European and East Asian populations, which provides evidence for decisions on public policies and suggests that different responses to environmental factors such as air pollution may contribute to racial heterogeneity of ARDs.

House dust mite allergens, store-operated Ca2+ channels and asthma

The house dust mite is the principal source of aero-allergen worldwide. Exposure to mite-derived allergens is associated with the development of asthma in susceptible individuals, and the majority of asthmatics are allergic to the mite. Mite-derived allergens are functionally diverse and activate multiple cell types within the lung that result in chronic inflammation. Allergens activate store-operated Ca2+ release-activated Ca2+ (CRAC) channels, which are widely expressed in multiple cell types within the lung that are associated with the pathogenesis of asthma. Opening of CRAC channels stimulates Ca2+-dependent transcription factors, including nuclear factor of activated T cells and nuclear factor-κB, which drive expression of a plethora of pro-inflammatory cytokines and chemokines that help to sustain chronic inflammation. Here, I describe drivers of asthma, properties of mite-derived allergens, how the allergens are recognized by cells, the signalling pathways used by the receptors and how these are transduced into functional effects, with a focus on CRAC channels. In vivo experiments that demonstrate the effectiveness of targeting CRAC channels as a potential new therapy for treating mite-induced asthma are also discussed, in tandem with other possible approaches.

Genetically Proxied Interleukin-13 Inhibition Is Associated With Risk of Psoriatic Disease: A Mendelian Randomization Study

OBJECTIVE

Inhibitors of the interleukin 13 (IL-13) pathway, such as dupilumab, are licensed for atopic dermatitis and asthma. Adverse events resembling psoriatic disease after dupilumab initiation have been reported, but evidence is limited to case reports with uncertain causality. We aimed to investigate whether genetically mimicked IL-13 inhibition (IL-13i) is associated with risk of psoriatic arthritis (PsA) and psoriasis.

METHODS

We instrumented IL-13i using a protein-coding variant in the IL13 gene, rs20541, that is associated with circulating eosinophil count (biomarker of IL-13i) at genome-wide significance in a study of 563,946 individuals. Outcome genetic data were taken from studies of PsA, psoriasis, and related spondyloarthritis traits in up to 10,588 cases and 209,287 controls. Colocalization analysis was performed to examine genetic confounding. We additionally used circulating IgE as a biomarker to test whether associations were replicated, both in the test and in an independent genetic dataset. We also replicated analyses using individual-level data from the UK Biobank.

RESULTS

Genetically proxied IL-13i was associated with increased risk of PsA (odds ratio [OR] 37.39; 95% confidence interval [95% CI] 11.52-121.34; P = 1.64 × 10-9) and psoriasis (OR 20.08; 95% CI 4.38-92.01; P = 1.12 × 10-4). No consistent associations were found for Crohn disease, ulcerative colitis, ankylosing spondylitis, or iritis. Colocalization showed no strong evidence of genetic confounding for psoriatic disease. Results were replicated using circulating IgE for the exposure, using independent outcome data and using individual-level data.

CONCLUSION

We provide supportive genetic evidence that IL-13i is linked to increased risk of PsA and psoriasis. Physicians prescribing IL-13 inhibitors should be vigilant for these adverse events.

The Relationship Between Asthma and Food Allergies in Children

Asthma and food allergy are two complex allergic diseases with an increasing prevalence in childhood. They share risk factors, including atopic family history, atopic dermatitis, allergen sensitization, and T2 inflammatory pathways. Several studies have shown that in children with a food allergy, the risk of developing asthma, particularly in early childhood, is high. Food allergen intake or the inhalation of aerosolized allergens can induce respiratory symptoms such as bronchospasm. Patients with both conditions have an increased risk of severe asthma exacerbations, hospitalization, and mortality. The current management of clinical food hypersensitivity primarily involves the dietary avoidance of food allergens and the use of self-injectable adrenaline for severe reactions. Poorly controlled asthma limits the prescription of oral immunotherapy to foods, which has emerged as an alternative therapy for managing food allergies. Biological therapies that are effective in severe asthma have been explored for treating food allergies. Omalizumab improves asthma control and, either alone or in combination with oral immunotherapy, increases the threshold of allergen tolerance. Understanding the interplay between asthma and food allergy is crucial for developing successful treatment approaches and ameliorating patient results.

Integration of genetic and chromatin modification data pinpoints autoimmune-specific remodeling of enhancer landscape in CD4+ T cells

CD4+ T cells play a crucial role in adaptive immune responses and have been implicated in the pathogenesis of autoimmune diseases (ADs). Despite numerous studies, the molecular mechanisms underlying T cell dysregulation in ADs remain incompletely understood. Here, we used chromatin immunoprecipitation (ChIP)-sequencing of active chromatin and transcriptomic data from CD4+ T cells of healthy donors and patients with systemic lupus erythematosus (SLE), psoriasis, juvenile idiopathic arthritis (JIA), and Graves' disease to investigate the role of enhancers in AD pathogenesis. By generating enhancer-based gene regulatory networks (eGRNs), we identified disease-specific dysregulated pathways and potential downstream target genes of enhancers harboring AD-associated single-nucleotide polymorphisms (SNPs), which we also validated using chromatin-capture (HiC) data and CRISPR interference (CRISPRi) in primary CD4+ T cells. Our results suggest that alterations in the regulatory landscapes of CD4+ T cells, including enhancers, contribute to the development of ADs and provide a basis for developing new therapeutic approaches.

SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations

Polygenic risk scores are widely used in disease risk stratification, but their accuracy varies across diverse populations. Recent methods large-scale leverage multi-ancestry data to improve accuracy in under-represented populations but require labelling individuals by ancestry for prediction. This poses challenges for practical use, as clinical practices are typically not based on ancestry. We propose SPLENDID, a novel penalized regression framework for diverse biobank-scale data. Our method utilizes ancestry principal component interactions to model genetic ancestry as a continuum within a single prediction model for all ancestries, eliminating the need for discrete labels. In extensive simulations and analyses of 9 traits from the All of Us Research Program (N=224,364) and UK Biobank (N=340,140), SPLENDID significantly outperformed existing methods in prediction accuracy and model sparsity. By directly incorporating continuous genetic ancestry in model training, SPLENDID stands as a valuable tool for robust risk prediction across diverse populations and fairer clinical implementation.

Immunologic aspects of asthma: from molecular mechanisms to disease pathophysiology and clinical translation

In the present review, we focused on recent translational and clinical discoveries in asthma immunology, facilitating phenotyping and stratified or personalized interventions for patients with this condition. The immune processes behind chronic inflammation in asthma exhibit marked heterogeneity, with diverse phenotypes defining discernible features and endotypes illuminating the underlying molecular mechanisms. In particular, two primary endotypes of asthma have been identified: "type 2-high," characterized by increased eosinophil levels in the airways and sputum of patients, and "type 2-low," distinguished by increased neutrophils or a pauci-granulocytic profile. Our review encompasses significant advances in both innate and adaptive immunities, with emphasis on the key cellular and molecular mediators, and delves into innovative biological and targeted therapies for all the asthma endotypes. Recognizing that the immunopathology of asthma is dynamic and continuous, exhibiting spatial and temporal variabilities, is the central theme of this review. This complexity is underscored through the innumerable interactions involved, rather than being driven by a single predominant factor. Integrated efforts to improve our understanding of the pathophysiological characteristics of asthma indicate a trend toward an approach based on disease biology, encompassing the combined examination of the clinical, cellular, and molecular dimensions of the disease to more accurately correlate clinical traits with specific disease mechanisms.

Causal Relationship Between Gastroesophageal Reflux Disease and the Risk of Chronic Rhinosinusitis: Insights from Multivariable and Mediation Mendelian Randomization Analysis

Background: Previous studies have shown an association between chronic rhinosinusitis (CRS) and gastroesophageal reflux disease (GERD). However, the findings of these studies are controversial, and evaluating this association could help in the treatment of CRS. Thus, we aimed to clarify the relationship between GERD and CRS. Methods: We conducted a Mendelian randomization (MR) study. Pooled data on CRS, GERD, and their associated risk factors were extracted from large genome-wide association studies. Independent single-nucleotide polymorphisms were rigorously screened as instrumental variables. Causal associations between GERD and CRS were assessed, and mediation analyses were performed using multivariate and 2-step MR. Asthma served as a mediator because of its association with both CRS and GERD. Sensitivity tests were also performed. Results: MR analysis showed that genetically predicted GERD was associated with an increased risk of CRS (P < .001). Multivariate MR analysis showed that the effect of GERD on CRS was relatively independent. Mediation analysis showed that asthma mediated the association with a mediation effect of 21.07% (95% CI, 2.70%-40.18%). Sensitivity analyses did not reveal any significant effects of pleiotropy and heterogeneity. Conclusions: We found a causal relationship between genetically predicted GERD and an increase in the risk of CRS. As a mediator, asthma contributed to the effect of GERD on CRS. This study provides high-quality causal evidence for the prevention of CRS.

Improving on polygenic scores across complex traits using select and shrink with summary statistics (S4) and LDpred2

BACKGROUND

As precision medicine advances, polygenic scores (PGS) have become increasingly important for clinical risk assessment. Many methods have been developed to create polygenic models with increased accuracy for risk prediction. Our select and shrink with summary statistics (S4) PGS method has previously been shown to accurately predict the polygenic risk of epithelial ovarian cancer. Here, we applied S4 PGS to 12 phenotypes for UK Biobank participants, and compared it with the LDpred2 and a combined S4 + LDpred2 method.

RESULTS

The S4 + LDpred2 method provided overall improved PGS accuracy across a variety of phenotypes for UK Biobank participants. Additionally, the S4 + LDpred2 method had the best estimated PGS accuracy in Finnish and Japanese populations. We also addressed the challenge of limited genotype level data by developing the PGS models using only GWAS summary statistics.

CONCLUSIONS

Taken together, the S4 + LDpred2 method represents an improvement in overall PGS accuracy across multiple phenotypes and populations.

Human milk oligosaccharides are associated with maternal genetics and respiratory health of human milk-fed children

Breastfeeding provides many health benefits, but its impact on respiratory health remains unclear. This study addresses the complex and dynamic nature of the mother-milk-infant triad by investigating maternal genomic factors regulating human milk oligosaccharides (HMOs), and their associations with respiratory health among human milk-fed infants. Nineteen HMOs are quantified from 980 mothers of the CHILD Cohort Study. Genome-wide association studies identify HMO-associated loci on chromosome 19p13.3 and 19q13.33 (lowest P = 2.4e-118), spanning several fucosyltransferase (FUT) genes. We identify novel associations on chromosome 3q27.3 for 6'-sialyllactose (P = 2.2e-9) in the sialyltransferase (ST6GAL1) gene. These, plus additional associations on chromosomes 7q21.32, 7q31.32 and 13q33.3, are replicated in the independent INSPIRE Cohort. Moreover, gene-environment interaction analyses suggest that fucosylated HMOs may modulate overall risk of recurrent wheeze among preschoolers with variable genetic risk scores (P < 0.01). Thus, we report novel genetic factors associated with HMOs, some of which may protect the respiratory health of children.

Asthma-Genomic Advances Toward Risk Prediction

Asthma is a common complex airway disease whose prediction of disease risk and most severe outcomes is crucial in clinical practice for adequate clinical management. This review discusses the latest findings in asthma genomics and current obstacles faced in moving forward to translational medicine. While genome-wide association studies have provided valuable insights into the genetic basis of asthma, there are challenges that must be addressed to improve disease prediction, such as the need for diverse representation, the functional characterization of genetic variants identified, variant selection for genetic testing, and refining prediction models using polygenic risk scores.

Global impact of unproductive splicing on human gene expression

Alternative splicing (AS) in human genes is widely viewed as a mechanism for enhancing proteomic diversity. AS can also impact gene expression levels without increasing protein diversity by producing 'unproductive' transcripts that are targeted for rapid degradation by nonsense-mediated decay (NMD). However, the relative importance of this regulatory mechanism remains underexplored. To better understand the impact of AS-NMD relative to other regulatory mechanisms, we analyzed population-scale genomic data across eight molecular assays, covering various stages from transcription to cytoplasmic decay. We report threefold more unproductive splicing compared with prior estimates using steady-state RNA. This unproductive splicing compounds across multi-intronic genes, resulting in 15% of transcript molecules from protein-coding genes being unproductive. Leveraging genetic variation across cell lines, we find that GWAS trait-associated loci explained by AS are as often associated with NMD-induced expression level differences as with differences in protein isoform usage. Our findings suggest that much of the impact of AS is mediated by NMD-induced changes in gene expression rather than diversification of the proteome.

Fast and scalable ensemble learning method for versatile polygenic risk prediction

Polygenic risk scores (PRS) enhance population risk stratification and advance personalized medicine, but existing methods face several limitations, encompassing issues related to computational burden, predictive accuracy, and adaptability to a wide range of genetic architectures. To address these issues, we propose Aggregated L0Learn using Summary-level data (ALL-Sum), a fast and scalable ensemble learning method for computing PRS using summary statistics from genome-wide association studies (GWAS). ALL-Sum leverages a L0L2 penalized regression and ensemble learning across tuning parameters to flexibly model traits with diverse genetic architectures. In extensive large-scale simulations across a wide range of polygenicity and GWAS sample sizes, ALL-Sum consistently outperformed popular alternative methods in terms of prediction accuracy, runtime, and memory usage by 10%, 20-fold, and threefold, respectively, and demonstrated robustness to diverse genetic architectures. We validated the performance of ALL-Sum in real data analysis of 11 complex traits using GWAS summary statistics from nine data sources, including the Global Lipids Genetics Consortium, Breast Cancer Association Consortium, and FinnGen Biobank, with validation in the UK Biobank. Our results show that on average, ALL-Sum obtained PRS with 25% higher accuracy on average, with 15 times faster computation and half the memory than the current state-of-the-art methods, and had robust performance across a wide range of traits and diseases. Furthermore, our method demonstrates stable prediction when using linkage disequilibrium computed from different data sources. ALL-Sum is available as a user-friendly R software package with publicly available reference data for streamlined analysis.

Epigenomic partitioning of a polygenic risk score for asthma reveals distinct genetically driven disease pathways

BACKGROUND

Individual differences in susceptibility to developing asthma, a heterogeneous chronic inflammatory lung disease, are poorly understood. Whether genetics can predict asthma risk and how genetic variants modulate the complex pathophysiology of asthma are still debated.

AIM

To build polygenic risk scores for asthma risk prediction and epigenomically link predictive genetic variants to pathophysiological mechanisms.

METHODS

Restricted polygenic risk scores were constructed using single nucleotide variants derived from genome-wide association studies and validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14 926 individuals. Outcomes used were asthma, childhood-onset asthma, adulthood-onset asthma, eosinophilic asthma and asthma exacerbations. Genome-wide chromatin analysis data from 19 disease-relevant cell types were used for epigenomic polygenic risk score partitioning.

RESULTS

The polygenic risk scores obtained predicted asthma and related outcomes, with the strongest associations observed for childhood-onset asthma (2.55 odds ratios per polygenic risk score standard deviation, area under the curve of 0.760). Polygenic risk scores allowed for the classification of individuals into high-risk and low-risk groups. Polygenic risk score partitioning using epigenomic profiles identified five clusters of variants within putative gene regulatory regions linked to specific asthma-relevant cells, genes and biological pathways.

CONCLUSIONS

Polygenic risk scores were associated with asthma(-related traits) in a Dutch prospective cohort, with substantially higher predictive power observed for childhood-onset than adult-onset asthma. Importantly, polygenic risk score variants could be epigenomically partitioned into clusters of regulatory variants with different pathophysiological association patterns and effect estimates, which likely represent distinct genetically driven disease pathways. Our findings have potential implications for personalised risk mitigation and treatment strategies.

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.

Epigenetic Signatures of Asthma: A Comprehensive Study of DNA Methylation and Clinical Markers

Background

Asthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma. The Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood samples from 319 participants. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 of these individuals. Principal component analysis (PCA) on the clinical markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates.

Results

221 unique CpGs reached genome-wide significance at timepoint 1 (T1) after Bonferroni correction. PC7 accounted for the majority of associations (204), which correlated with loadings of eosinophil counts and immunoglobulin levels. Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint (T2) identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points (271 in total) yielded a correlation of 0.81.

Conclusion

We identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to using this robust DNA methylation profile as a new, stable biomarker for asthma.

Biomarkers of type 2 and non-type 2 inflammation in asthma exacerbations

Introduction

In adult-onset asthma, two major endotypes have been proposed: T2 with eosinophilia and non-T2 characterised by neutrophils and interleukin (IL)-17. The objective of the study was to examine the endotype marker profile in patients with severe asthma who were hospitalized for exacerbations, with a focus on differentiating between viral and non-viral triggers.

Material and methods

Forty-nine patients with asthma, admitted for exacerbations, and 51 healthy controls (HCs) were recruited. We further categorized the exacerbated asthma patients into two groups: non-viral infected (n = 38) and viral infected (n = 11) groups. Blood was drawn and a nasopharyngeal swab taken at the time of admission and eosinophil numbers, eosinophil cationic protein (ECP), immuno- globulin E (IgE), tryptase and viral infection were determined. Additionally, levels of IL-17, IL-33 and IL-31 were assessed.

Results

The majority of patients had adult onset asthma (age of diagnosis, 42.8 ±16.1) with a duration of 7.7 ±10.8 years, 24.5% being atopic. Patients had higher levels of eosinophils, ECP and IgE than healthy controls (eosinophils, p = 0.003; ECP and IgE, p = 0.0001). Immunohistochemistry confirmed eosinophils as a source of ECP. Tryptase (p = 0.0001), IL-17 (p = 0.0005), IL-31 (p = 0.0001) and IL-33 (p = 0.0002) were also higher in patients than controls. ECP correlated with tryptase (r = 0.08, p = 0.62). IL-17 showed the best correlation with other mediators, including ECP (r = 0.35, p = 0.24), tryptase (r = 0.69, p = 0.0001), IgE (r = 0.50, p = 0.0001), IL-33 (r = 0.95, p = 0.0001) and IL-31 (r = 0.89, p = 0.0001). IgE, IL-17, and IL-31 had a high AUC when differentiating those with severe and non-severe asthma. The group with exacerbated viral infection showed elevated levels of serum IL-17 and IL-31 compared to the non-infected group.

Conclusions

Patients with asthmatic exacerbations were found to have higher levels of both T2 and non-T2 inflammatory markers than healthy controls. In the study, levels of IgE, IL-17, and IL-31 differentiated between patients with severe and non-severe asthma. The last two cytokines were also able to distinguish between exacerbated asthma caused by viral infection and exacerbated asthma caused by non-viral infection.

A distal enhancer of GATA3 regulates Th2 differentiation and allergic inflammation

Asthma is a widespread airway disorder where GATA3-dependent Type-2 helper T (Th2) cells and group 2 innate lymphoid cells (ILC2s) play vital roles. Asthma-associated single nucleotide polymorphisms (SNPs) are enriched in a region located 926-970 kb downstream from GATA3 in the 10p14 (hG900). However, it is unknown how hG900 affects the pathogenesis of allergic airway inflammation. To investigate the roles of the asthma-associated GATA3 enhancer region in experimental allergic airway inflammation, we first examined the correlation between GATA3 expression and the activation of the hG900 region was analyzed by flow cytometry and ChIP-qPCR. We found that The activation of enhancers in the hG900 region was strongly correlated to the levels of GATA3 in human peripheral T cell subsets. We next generated mice lacking the mG900 region (mG900KO mice) were generated by the CRISPR-Cas9 system, and the development and function of helper T cells and ILCs in mG900KO mice were analyzed in steady-state conditions and allergic airway inflammation induced by papain or house dust mite (HDM). The deletion of the mG900 did not affect the development of lymphocytes in steady-state conditions or allergic airway inflammation induced by papain. However, mG900KO mice exhibited reduced allergic inflammation and Th2 differentiation in the HDM-induced allergic airway inflammation. The analysis of the chromatin conformation around Gata3 by circular chromosome conformation capture coupled to high-throughput sequencing (4C-seq) revealed that the mG900 region interacted with the transcription start site of Gata3 with an influencing chromatin conformation in Th2 cells. These findings indicate that the mG900 region plays a pivotal role in Th2 differentiation and thus enhances allergic airway inflammation.

Gastroesophageal Reflux and Chronic Rhinosinusitis: A Mendelian Randomization Study

OBJECTIVE

Chronic rhinosinusitis (CRS) is associated with gastroesophageal reflux (GERD). However, the causal relationship is controversial. We conducted a two-sample Mendelian Randomization (MR) analysis to explore this potential association.

METHODS

Based on genome-wide association studies (GWAS), a univariable MR was performed to explore the causal relationship of GERD with CRS. Instrumental variables (IVs) pertinent to anti-GERD treatment were employed as a means of validation. The primary MR outcome was established using an inverse variance weighted (IVW) method, supplemented by multiple sensitivity analyses. Subsequently, a multivariable MR was conducted to account for potential confounding variables, thereby ascertaining a direct effect of GERD on CRS. Finally, a network MR analysis was carried out to elucidate the mediating role of asthma in the relationship between GERD and CRS.

RESULTS

The univariable MR demonstrated an association between GERD and an elevated risk of CRS (IVW OR = 1.30, 95% CI = 1.18-1.45, p = 4.19 × 10-7). Omeprazole usage was associated with a reduction in CRS risk (IVW OR = 0.64, 95% CI = 0.42-0.98, p = 0.039). The causal relationship between GERD and CRS remained after adjusting for potential confounders, such as smoking characteristics, body mass index, asthma, allergic rhinitis, in the multivariable MR analysis. Besides, the proportion of the causal effect of GERD on CRS mediated by asthma was 19.65% (95% CI = 2.69%-36.62%).

CONCLUSION

GERD was independently associated with an increased risk of CRS. The mediating role of asthma between GERD and CRS also reveals that GERD is one of the mechanisms underlying unified airway disease.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:3086-3092, 2024.

Causal association of rheumatoid arthritis with frailty and the mediation role of inflammatory cytokines: A Mendelian randomization study

BACKGROUND

Previous observational studies have suggested the association between rheumatoid arthritis (RA) and frailty. However, it remains obscure whether this association is causal. This study aims to investigate the causal association of RA with frailty and the mediation effect of inflammatory cytokines using Mendelian randomization (MR) design.

METHODS

Summary-level data for RA (N = 58,284), frailty index (FI) (N = 175,226), Fried frailty score (FFS) (N = 386,565), and 41 inflammatory cytokines (N = 8,293) were obtained from recent genome-wide association studies. Univariable and multivariable MR analyses were conducted to investigate and verify the causal association of RA with frailty. The potential mediation effects of inflammatory cytokines were estimated using two-step MR.

RESULTS

Univariable inverse variance weighted MR analysis suggested that genetically determined RA was associated with increased FI (beta=0.021; 95 % CI: 0.012, 0.03; p = 2.2 × 10-6) and FFS (beta=0.011; 95 %CI: 0.007, 0.015; p = 8.811 × 10-8). The consistent results were observed in multivariable MR analysis after adjustment for asthma, smoking, BMI, physical activity, telomere length, and depression. Mediation analysis showed evidence of an indirect effect of RA on FI through monokine induced by interferon-gamma (MIG) with a mediated proportion of 9.8 % (95 %CI: 4.76 %, 19.05 %), on FFS via MIG and stromal cell-derived factor-1 alpha with a mediated proportion of 9.6 % (95 %CI: 0 %, 18.18 %) and 8.44 % (95 %CI: 0 %, 18.18 %), respectively.

CONCLUSION

This study provided credible evidence that genetically predicted RA was associated with a higher risk of frailty. Additionally, inflammatory cytokines were involved in the mechanism of RA-induced frailty.

shaPRS: Leveraging shared genetic effects across traits or ancestries improves accuracy of polygenic scores

We present shaPRS, a method that leverages widespread pleiotropy between traits or shared genetic effects across ancestries, to improve the accuracy of polygenic scores. The method uses genome-wide summary statistics from two diseases or ancestries to improve the genetic effect estimate and standard error at SNPs where there is homogeneity of effect between the two datasets. When there is significant evidence of heterogeneity, the genetic effect from the disease or population closest to the target population is maintained. We show via simulation and a series of real-world examples that shaPRS substantially enhances the accuracy of polygenic risk scores (PRSs) for complex diseases and greatly improves PRS performance across ancestries. shaPRS is a PRS pre-processing method that is agnostic to the actual PRS generation method, and as a result, it can be integrated into existing PRS generation pipelines and continue to be applied as more performant PRS methods are developed over time.

Inhibition of Interleukin-33 to Reduce Glomerular Endothelial Inflammation in Diabetic Kidney Disease

Introduction

Inflammation is a significant contributor to cardiorenal morbidity and mortality in diabetic kidney disease (DKD). The pathophysiological mechanisms linking systemic, subacute inflammation and local, kidney injury-initiated immune maladaptation is partially understood.

Methods

Here, we explored the expression of proinflammatory cytokines in patients with DKD; investigated mouse models of type 1 and type 2 diabetes (T2D); evaluated glomerular signaling in vitro; performed post hoc analyses of systemic and urinary markers of inflammation; and initiated a phase 2b clinical study (FRONTIER-1; NCT04170543).

Results

Transcriptomic profiling of kidney biopsies from patients with DKD revealed significant glomerular upregulation of interleukin-33 (IL-33). Inhibition of IL-33 signaling reduced glomerular damage and albuminuria in the uninephrectomized db/db mouse model (T2D/DKD). On a cellular level, inhibiting IL-33 improved glomerular endothelial health by decreasing cellular inflammation and reducing release of proinflammatory cytokines. Therefore, FRONTIER-1 was designed to test the safety and efficacy of the IL-33-targeted monoclonal antibody tozorakimab in patients with DKD. So far, 578 patients are enrolled in FRONTIER-1. The baseline inflammation status of participants (N > 146) was assessed in blood and urine. Comparison to independent reference cohorts (N > 200) validated the distribution of urinary tumor necrosis factor receptor 1 (TNFR1) and C-C motif chemokine ligand 2 (CCL2). Treatment with dapagliflozin for 6 weeks did not alter these biomarkers significantly.

Conclusion

We show that blocking the IL-33 pathway may mitigate glomerular endothelial inflammation in DKD. The findings from the FRONTIER-1 study will provide valuable insights into the therapeutic potential of IL-33 inhibition in DKD.

Multi-omics in nasal epithelium reveals three axes of dysregulation for asthma risk in the African Diaspora populations

Asthma has striking disparities across ancestral groups, but the molecular underpinning of these differences is poorly understood and minimally studied. A goal of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to understand multi-omic signatures of asthma focusing on populations of African ancestry. RNASeq and DNA methylation data are generated from nasal epithelium including cases (current asthma, N = 253) and controls (never-asthma, N = 283) from 7 different geographic sites to identify differentially expressed genes (DEGs) and gene networks. We identify 389 DEGs; the top DEG, FN1, was downregulated in cases (q = 3.26 × 10-9) and encodes fibronectin which plays a role in wound healing. The top three gene expression modules implicate networks related to immune response (CEACAM5; p = 9.62 × 10-16 and CPA3; p = 2.39 × 10-14) and wound healing (FN1; p = 7.63 × 10-9). Multi-omic analysis identifies FKBP5, a co-chaperone of glucocorticoid receptor signaling known to be involved in drug response in asthma, where the association between nasal epithelium gene expression is likely regulated by methylation and is associated with increased use of inhaled corticosteroids. This work reveals molecular dysregulation on three axes - increased Th2 inflammation, decreased capacity for wound healing, and impaired drug response - that may play a critical role in asthma within the African Diaspora.

Impact of Interleukin-17 Receptor A Gene Variants on Asthma Susceptibility and Clinical Manifestations in Children and Adolescents

Several single nucleotide polymorphisms (SNPs) in multiple interleukin receptor genes could be associated with asthma risk and/or phenotype. Interleukin-17 (IL-17) has been implicated in tissue inflammation and autoimmune diseases. As no previous studies have uncovered the potential role of IL17 receptor A (RA) gene variants in asthma risk, we aimed to explore the association of four IL17RA SNPs (i.e., rs4819554A/G, rs879577C/T, rs41323645G/A, and rs4819555C/T) with asthma susceptibility/phenotype in our region. TaqMan allelic discrimination analysis was used to genotype 192 individuals. We found that the rs4819554 G/G genotype significantly reduced disease risk in the codominant (OR = 0.15, 95%CI = 0.05-0.45, p < 0.001), dominant (OR = 0.49, 95%CI = 0.26-0.93, p = 0.028), and recessive (OR = 0.18, 95%CI = 0.07-0.52, p < 0.001) models. Similarly, rs879577 showed reduced disease risk associated with the T allele across all genetic models. However, the A allele of rs41323645 was associated with increased disease risk in all models. The G/A and A/A genotypes have higher ORs of 2.47 (95%CI = 1.19-5.14) and 3.86 (95%CI = 1.62-9.18), respectively. Similar trends are observed in the dominant 2.89 (95%CI = 1.47-5.68, p = 0.002) and recessive 2.34 (95%CI = 1.10-4.98, p = 0.025) models. For the rs4819555 variant, although there was no significant association identified under any models, carriers of the rs4819554*A demonstrated an association with a positive family history of asthma (71.4% in carriers vs. 27% in non-carriers; p = 0.025) and the use of relievers for >2 weeks (52.2% of carriers vs. 28.8% of non-carriers; p = 0.047). Meanwhile, the rs4819555*C carriers displayed a significant divergence in the asthma phenotype, specifically atopic asthma (83.3% vs. 61.1%; p = 0.007), showed a higher prevalence of chest tightness (88.9% vs. 61.5%; p = 0.029), and were more likely to report comorbidities (57.7% vs. 16.7%, p = 0.003). The most frequent haplotype in the asthma group was ACAC, with a frequency of 22.87% vs. 1.36% in the controls (p < 0.001). In conclusion, the studied IL17RA variants could be essential in asthma susceptibility and phenotype in children and adolescents.

Chronic Overlapping Pain Conditions and Nociplastic Pain

Chronic Overlapping Pain Conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and assigned female at birth (AFAB) individuals. Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic type pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic type pain, followed by genetic correlation (linkage-disequilibrium score regression), gene-set and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic type pain, and showed nociplastic type pain to be a polygenic trait with significant SNP-heritability. We found significant genetic overlap between multisite chronic pain and nociplastic type pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic type pain along with distinct pathology in migraine and headache. We use a well-powered network approach to investigate nociplastic type pain using existing COPC GWAS output, and show nociplastic type pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.

A powerful approach to identify replicable variants in genome-wide association studies

Replicability is the cornerstone of modern scientific research. Reliable identifications of genotype-phenotype associations that are significant in multiple genome-wide association studies (GWASs) provide stronger evidence for the findings. Current replicability analysis relies on the independence assumption among single-nucleotide polymorphisms (SNPs) and ignores the linkage disequilibrium (LD) structure. We show that such a strategy may produce either overly liberal or overly conservative results in practice. We develop an efficient method, ReAD, to detect replicable SNPs associated with the phenotype from two GWASs accounting for the LD structure. The local dependence structure of SNPs across two heterogeneous studies is captured by a four-state hidden Markov model (HMM) built on two sequences of p values. By incorporating information from adjacent locations via the HMM, our approach provides more accurate SNP significance rankings. ReAD is scalable, platform independent, and more powerful than existing replicability analysis methods with effective false discovery rate control. Through analysis of datasets from two asthma GWASs and two ulcerative colitis GWASs, we show that ReAD can identify replicable genetic loci that existing methods might otherwise miss.

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.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

Plasma protein signatures of adult asthma

BACKGROUND

Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma.

METHODS

Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy (n = 207), asthma without atopy (n = 554), atopy without asthma (n = 147), compared to neither (n = 948)).

RESULTS

Meta-analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75-0.79 in training set; AUC = 0.72, 95% CI = 0.69-0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma-atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis.

CONCLUSION

This first large-scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.

The Rotterdam Study. Design update and major findings between 2020 and 2024

The Rotterdam Study is a population-based cohort study, started in 1990 in the district of Ommoord in the city of Rotterdam, the Netherlands, with the aim to describe the prevalence and incidence, unravel the etiology, and identify targets for prediction, prevention or intervention of multifactorial diseases in mid-life and elderly. The study currently includes 17,931 participants (overall response rate 65%), aged 40 years and over, who are examined in-person every 3 to 5 years in a dedicated research facility, and who are followed-up continuously through automated linkage with health care providers, both regionally and nationally. Research within the Rotterdam Study is carried out along two axes. First, research lines are oriented around diseases and clinical conditions, which are reflective of medical specializations. Second, cross-cutting research lines transverse these clinical demarcations allowing for inter- and multidisciplinary research. These research lines generally reflect subdomains within epidemiology. This paper describes recent methodological updates and main findings from each of these research lines. Also, future perspective for coming years highlighted.

No causal association between atopic dermatitis and COVID-19 outcomes: A Mendelian randomization study

BACKGROUND

Frequent hand washing and disinfection during the corona virus disease (COVID-19) pandemic may lead to skin-related disability. The causal relationship between atopic dermatitis (AD), the most common chronic, noninfectious, inflammatory skin disease, and COVID-19 remains unclear. We used Mendelian randomization (MR) to explore the causal inference of atopic dermatitis with COVID-19 outcomes.

METHODS

Genome-wide association study (GWAS) data for AD, consisting of 8383 cases and 236,162 controls of European ethnicity, were provided by the FinnGen database. The GWAS outcome data were derived from the COVID-19 Host Genetics Initiative and consisted of COVID-19 susceptibility (122,616 cases and 2,475,240 controls), hospitalization (32,519 cases and 2,062,805 controls), and very severe respiratory disease (13,769 cases and 1,072,442 controls). The inverse variance weighted with a fixed effects model (IVW (fe)) was used as the main statistical approach to assess the causality between AD and COVID-19 in this study. Several other analytical methods have also been used to complement or identify pleiotropy and heterogeneity.

RESULTS

MR analysis showed no causality between AD and COVID-19 outcomes. The odds ratios (OR) were 1.00 (95% confidence interval (CI), 0.99-1.02) for susceptibility, 1.00 (95% CI, 0.96-1.04) for hospitalization, 0.97 (95% CI, 0.92-1.03) for very severe respiratory disease by the method of IVW (fe).

CONCLUSION

In conclusion, we found no causal relationship between AD and COVID-19 outcomes. This study provides additional ideas for the exploration of the risk factors for COVID-19.

Genetic relationships between high blood eosinophil count, asthma susceptibility, and asthma severity

OBJECTIVE

Genetic relationships between blood eosinophil count (BEC), asthma susceptibility, and severity are unclear. We sought to identify the genetic difference between type 2 (T2) and nontype 2 (non-T2) asthma (defined by BEC) and investigate genetic relationships between high BEC, asthma susceptibility, and severity.

METHODS

Genome-wide association studies (GWASs) were performed for T2 (n = 9,064; BEC ≥ 300 cells/μL) versus non-T2 asthma (n = 14,379; BEC < 150 cells/μL) and asthma susceptibility (37,227 asthmatics vs. 124,132 nonasthma controls) in the UK Biobank and asthma severity (moderate-to-severe asthma [n = 2,153] vs. mild asthma [n = 5165]) in the All of Us Research Program (AoURP). Genetic causality between BEC, asthma susceptibility, and severity were dissected using Mendelian randomization (MR).

RESULTS

High BEC was associated with asthma and decreased pulmonary function. GWASs revealed four sets of genetic variants (p < 5 × 10-8): genes associated with only BEC or asthma and genes associated with high BEC and asthma in the same or opposite direction. The C allele of rs653178 in ATXN2 was associated with high BEC, risk for autoimmune diseases, and protection for asthma. Genetic variants associated with BEC or asthma were not associated with asthma severity. MR indicated high BEC and asthma were in bidirectional causal relationship (p < .001); however, they were not causal for asthma severity.

CONCLUSIONS

Genetic variants associated with asthma or BEC and asthma severity are distinctive. High BEC is a risk factor for asthma; however, it is neither necessary nor sufficient for asthma susceptibility and severity.

A systematic two-sample and bidirectional MR process highlights a unidirectional genetic causal effect of allergic diseases on COVID-19 infection/severity

BACKGROUND

Allergic diseases (ADs) such as asthma are presumed risk factors for COVID-19 infection. However, recent observational studies suggest that the assumed correlation contradicts each other. We therefore systematically investigated the genetic causal correlations between various ADs and COVID-19 infection/severity.

METHODS

We performed a two-sample, bidirectional Mendelian randomization (MR) study for five types of ADs and the latest round of COVID-19 GWAS meta-analysis datasets (critically ill, hospitalized, and infection cases). We also further validated the significant causal correlations and elucidated the potential underlying molecular mechanisms.

RESULTS

With the most suitable MR method, asthma consistently demonstrated causal protective effects on critically ill and hospitalized COVID-19 cases (OR < 0.93, p < 2.01 × 10-2), which were further confirmed by another validated GWAS dataset (OR < 0.92, p < 4.22 × 10-3). In addition, our MR analyses also observed significant causal correlations of food allergies such as shrimp allergy with the risk of COVID-19 infection/severity. However, we did not find any significant causal effect of COVID-19 phenotypes on the risk of ADs. Regarding the underlying molecular mechanisms, not only multiple immune-related cells such as CD4+ T, CD8+ T and the ratio of CD4+/CD8+ T cells showed significant causal effects on COVID-19 phenotypes and various ADs, the hematology traits including monocytes were also significantly correlated with them. Conversely, various ADs such as asthma and shrimp allergy may be causally correlated with COVID-19 infection/severity by affecting multiple hematological traits and immune-related cells.

CONCLUSIONS

Our systematic and bidirectional MR analyses suggest a unidirectional causal effect of various ADs, particularly of asthma on COVID-19 infection/severity, but the reverse is not true. The potential underlying molecular mechanisms of the causal effects call for more attention to clinical monitoring of hematological cells/traits and may be beneficial in developing effective therapeutic strategies for allergic patients following infection with COVID-19.

Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery

MOTIVATION

Genome-wide association studies (GWAS) have enabled large-scale analysis of the role of genetic variants in human disease. Despite impressive methodological advances, subsequent clinical interpretation and application remains challenging when GWAS suffer from a lack of statistical power. In recent years, however, the use of information diffusion algorithms with molecular networks has led to fruitful insights on disease genes.

RESULTS

We present an overview of the design choices and pitfalls that prove crucial in the application of network propagation methods to GWAS summary statistics. We highlight general trends from the literature, and present benchmark experiments to expand on these insights selecting as case study three diseases and five molecular networks. We verify that the use of gene-level scores based on GWAS P-values offers advantages over the selection of a set of 'seed' disease genes not weighted by the associated P-values if the GWAS summary statistics are of sufficient quality. Beyond that, the size and the density of the networks prove to be important factors for consideration. Finally, we explore several ensemble methods and show that combining multiple networks may improve the network propagation approach.

A Bayesian approach to Mendelian randomization using summary statistics in the univariable and multivariable settings with correlated pleiotropy

Mendelian randomization uses genetic variants as instrumental variables to make causal inferences on the effect of an exposure on an outcome. Due to the recent abundance of high-powered genome-wide association studies, many putative causal exposures of interest have large numbers of independent genetic variants with which they associate, each representing a potential instrument for use in a Mendelian randomization analysis. Such polygenic analyses increase the power of the study design to detect causal effects; however, they also increase the potential for bias due to instrument invalidity. Recent attention has been given to dealing with bias caused by correlated pleiotropy, which results from violation of the "instrument strength independent of direct effect" assumption. Although methods have been proposed that can account for this bias, a number of restrictive conditions remain in many commonly used techniques. In this paper, we propose a Bayesian framework for Mendelian randomization that provides valid causal inference under very general settings. We propose the methods MR-Horse and MVMR-Horse, which can be performed without access to individual-level data, using only summary statistics of the type commonly published by genome-wide association studies, and can account for both correlated and uncorrelated pleiotropy. In simulation studies, we show that the approach retains type I error rates below nominal levels even in high-pleiotropy scenarios. We demonstrate the proposed approaches in applied examples in both univariable and multivariable settings, some with very weak instruments.

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.

Applications of Genome-Editing Technologies for Type 1 Diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the destruction of insulin-producing pancreatic β-cells by the immune system. Although conventional therapeutic modalities, such as insulin injection, remain a mainstay, recent years have witnessed the emergence of novel treatment approaches encompassing immunomodulatory therapies, such as stem cell and β-cell transplantation, along with revolutionary gene-editing techniques. Notably, recent research endeavors have enabled the reshaping of the T-cell repertoire, leading to the prevention of T1D development. Furthermore, CRISPR-Cas9 technology has demonstrated remarkable potential in targeting endogenous gene activation, ushering in a promising avenue for the precise guidance of mesenchymal stem cells (MSCs) toward differentiation into insulin-producing cells. This innovative approach holds substantial promise for the treatment of T1D. In this review, we focus on studies that have developed T1D models and treatments using gene-editing systems.

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).

Inferring disease architecture and predictive ability with LDpred2-auto

LDpred2 is a widely used Bayesian method for building polygenic scores (PGSs). LDpred2-auto can infer the two parameters from the LDpred model, the SNP heritability h2 and polygenicity p, so that it does not require an additional validation dataset to choose best-performing parameters. The main aim of this paper is to properly validate the use of LDpred2-auto for inferring multiple genetic parameters. Here, we present a new version of LDpred2-auto that adds an optional third parameter α to its model, for modeling negative selection. We then validate the inference of these three parameters (or two, when using the previous model). We also show that LDpred2-auto provides per-variant probabilities of being causal that are well calibrated and can therefore be used for fine-mapping purposes. We also introduce a formula to infer the out-of-sample predictive performance r2 of the resulting PGS directly from the Gibbs sampler of LDpred2-auto. Finally, we extend the set of HapMap3 variants recommended to use with LDpred2 with 37% more variants to improve the coverage of this set, and we show that this new set of variants captures 12% more heritability and provides 6% more predictive performance, on average, in UK Biobank analyses.