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.

Candidate genes did not have an impact on the risk of wheezing in children born preterm

AIM

Our aim was to investigate whether risk factors, including selected genetic variants, appeared with the same frequency in preterm-born and term-born children with respiratory symptoms.

METHODS

We conducted an observational study on a cohort at Copenhagen University Hospital Hillerød, Denmark, consisting of 63 preterm-born and 86 term-born children who were included at birth and followed to 6 years of age. Odd ratios (OR) and 95% CIs were calculated.

RESULTS

Valid genotyping data were obtained from 135 children and 126 and 64 parents completed questionnaires at the 1-year and 6-year follows-ups, respectively. The C allele of rs3751972 was associated with an increased wheezing risk at 6 years of age in term-born children, but not in preterm-born children (OR 8.84, 95% CI 1.02-76.72, p = 0.05 versus OR 2.33, 95% CI 0.59-9.20, p = 0.23, respectively). At 1 year of age, preterm-born children with respiratory symptoms were three times as likely to have parents who smoked than those without such symptoms (65% and 21%, respectively, p = 0.005).

CONCLUSION

Genetic variants known to affect the risk of respiratory symptoms did not seem to affect the risk of wheezing in preterm children. Parental smoking was a significant risk factor for respiratory symptoms.

Residential greenness, genetic susceptibility, and asthma risk: Mediating roles of air pollution in UK and Chinese populations

BACKGROUND

The relationship between residential greenness and asthma remains a topic of interest, especially in understanding the pathways involved and how genetic factors might influence this association. This study aimed to explore the association between residential greenness and asthma incidence, while also examining potential mediating pathways and the role of genetic susceptibility.

METHODS

Data were analyzed from two independent cohorts: the UK Biobank and the Chinese Biomarkers for the Prediction of Respiratory Disease Outcomes (C-BIOPRED) study. Greenness was measured by normalized difference vegetation index (NDVI). Polygenic risk scores were constructed from 145 asthma-associated single nucleotide polymorphisms. Cox proportional hazard models and logistics regression models were used to assess the association between residential greenness and asthma incidence, and mediation analysis was conducted to explore potential mediators.

RESULTS

Over a median follow-up of 11.85 years in UK Biobank, higher NDVI exposure was associated with reduced asthma incidence (hazard ratio per IQR increase in NDVI300 m: 0.965, 95 % CI: 0.949-0.982). The association was more pronounced among non-smokers and individuals with highest genetic risk. PM2.5 mediated 40.4 % (95 % CI: 5.1 %-76.4 %) of the protective effect. In the C-BIOPRED study, greenness was inversely associated with severe asthma (odd ratio: 0.645, 95 % CI: 0.441-0.943) and improved clinical outcomes.

CONCLUSION

Residential greenness is associated with a lower risk of asthma, particularly in genetically susceptible and socioeconomically disadvantaged populations, partially through improving air quality. Our findings advocate for integrating green space optimization into urban planning as a precision public health strategy.

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.

Enhancer RNA transcription pinpoints functional genetic variants linked to asthma

Bidirectional enhancer RNA (eRNA) transcription is a widespread response to environmental signals and glucocorticoids. We investigated whether single nucleotide polymorphisms (SNPs) within dynamically regulated eRNA-transcribing regions contribute to genetic variation in asthma. Through applying multivariate regression modeling with permutation-based significance thresholding to a large clinical cohort, we identified novel associations between asthma and 35 SNPs located in eRNA-transcribing regions implicated in regulating cellular processes relevant to asthma, including rs258760 (mean allele frequency = 0.34, asthma odds ratio = 0.95; P = 5.04E-03). We show that rs258760 disrupts an active aryl hydrocarbon receptor (AHR) response element linked to transcriptional regulation of the glucocorticoid receptor gene by AHR ligands, which are commonly found in combusted air pollution. The role of rs258760 as a protective variant for asthma was independently validated using UK Biobank data. Our findings establish eRNA signatures as a tool for discovery of functional genetic variants and define a novel association between air pollution, glucocorticoid signaling and asthma.

Sequencing and health data resource of children of African ancestry

Purpose

Individuals who self-report as Black or African American are historically underrepresented in genome-wide studies of disease risk, a disparity particularly evident in pediatric disease research. To address this gap, Cincinnati Children's Hospital Medical Center (CCHMC) established a biorepository and developed a comprehensive DNA sequencing resource including 15,684 individuals who self-identified as African American or Black and received care at CCHMC.

Methods

Participants were enrolled through the CCHMC Discover Together Biobank and sequenced. Admixture analyses confirmed the genetic ancestry of the cohort, which was then linked to electronic medical records.

Results

High-quality genome-wide genotypes from common variants accompanied by medical recordsourced data are available through the Genomic Information Commons. This dataset performs well in genetic studies. Specifically, we replicated known associations in sickle cell disease (HBB, p = 4.05 × 10-1), anxiety (PLAA3, p = 6.93 × 10-), and asthma (PCDH15, p = 5.6 × 10-1), while also identifying novel loci associated with asthma severity.

Conclusion

We present the acquisition and quality of genetic and disease-associated data and present an analytical framework for using this resource. In partnership with a community advisory council, we have co-developed a valuable framework for data use and future research.

Leveraging pleiotropic clustering to address high proportion correlated horizontal pleiotropy in Mendelian randomization studies

Mendelian randomization harnesses genetic variants as instrumental variables to infer causal relationships between exposures and outcomes. However, certain genetic variants can affect both the exposure and the outcome through a shared factor. This phenomenon, called correlated horizontal pleiotropy, may result in false-positive causal findings. Here, we propose a Pleiotropic Clustering framework for Mendelian randomization, PCMR. PCMR detects correlated horizontal pleiotropy and extends the zero modal pleiotropy assumption to enhance causal inference in trait pairs with correlated horizontal pleiotropic variants. Simulations show that PCMR can effectively detect correlated horizontal pleiotropy and avoid false positives in the presence of correlated horizontal pleiotropic variants, even when they constitute a high proportion of the variants connecting both traits (e.g., 30-40%). In datasets consisting of 48 exposure-common disease pairs, PCMR detects horizontal correlated pleiotropy in 7 out of the exposure-common disease pairs, and avoids detecting false positive causal links. Additionally, PCMR can facilitate the integration of biological information to exclude correlated horizontal pleiotropic variants, enhancing causal inference. We apply PCMR to study causal relationships between three common psychiatric disorders as examples.

Shared genetic investigation of asthma and blood eosinophils in relation to chronic rhinosinusitis

BACKGROUND

An epidemiological association among asthma, blood eosinophil level and chronic rhinosinusitis (CRS) is well established, but whether consistent genetic relationships exist, and whether this reflects a shared genetic etiology between CRS and asthma or blood eosinophil level remains unclear.

METHODS

Data from CRS patients (N = 1,255) and healthy controls (N = 1,032) were reviewed retrospectively to investigate associations between clinical characteristics and CRS. Data from white blood cells in the UK biobank (N = 173,480), asthma in the Trans-National Asthma Genetic Consortium (127,669) and CRS (N = 272,922) or nasal polyps (N = 264,107) in the FinnGen consortium were used to conduct genetic study, including linkage disequilibrium score regression analysis to detect genetic associations between aforementioned variables, Mendelian randomization (MR) analysis to investigate causal relationships of asthma and blood eosinophil levels on CRS, and Bayesian co-localization to consolidate MR findings and to identify shared genetic signals.

RESULTS

We found that blood eosinophil count, blood eosinophil percentages and asthma shared positive and causal genetic correlations with CRS (all q < 0.0001) and CRS with nasal polyps (CRSwNP) (all q < 0.0001) in both our observational and genetic study. Through colocalization analysis, 4 loci are shared among asthma, CRS and CRSwNP, 7 loci are shared among blood eosinophil count, CRS and CRSwNP, 2 loci are unique to blood eosinophil count and CRS, and 3 loci are unique to blood eosinophil count and CRSwNP.

CONCLUSIONS

These findings contribute to understanding CRS etiology, and provide insights for intervention and treatment target for CRS comorbid with asthma or high blood eosinophil levels.

Comprehensive causal analysis between autoimmune diseases and glioma: A Mendelian randomization study

The causal association between the autoimmune disease and the development of glioma and its subtypes remains unclear. We performed a comprehensive Mendelian randomization (MR) to clarify their causal association from genetic perspective. We obtained the summary-level datasets for autoimmune diseases from recently published genome-wide association studies in the UK Biobank (UKB) and the FinnGen consortium. Additionally, we collected summary statistics datasets related to glioma and its subtypes from a comprehensive meta-analysis genome-wide association study, which included 12,488 cases and 18,169 controls. We primarily used inverse variance weighting method, supplemented by Bonferroni correction to account for multiple tests to reduce the probability of false positive results. We also performed sensitivity analyses to address potential pleiotropy and strengthen the reliability of the results. After meta-analysis, pernicious anemia may decrease the risk of glioblastoma (GBM) (UKB: odds ratio (OR) = 0.01, 95% confidence interval (CI) = 0.01-0.02, P = 1.01E-12; FinnGen: OR = 0.86, 95% CI = 0.79-0.93, P = .0002; Meta: OR = 0.04, 95% CI = 0.03-0.04). In reverse MR analysis, GBM decreased the risk of celiac disease (UKB: OR = 0.96, 95% CI = 0.95-0.98, P = .0000; FinnGen: OR = 0.89, 95% CI = 0.84-0.94, P = .0001; Meta: OR = 0.95, 95% CI = 0.94-0.97). Heterogeneity and pleiotropy analyses, and reverse analysis, confirmed the robustness of these results. From the genetic perspective, our MR study uncovered that pernicious anemia may decrease the risk of GBM. Conversely, GBM appeared to mitigate the risk of celiac disease. Future studies are required to validate the causal association and illuminate the underlying mechanisms.

Evolution, genetic diversity, and health

Human genetic diversity in today's world has been shaped by evolutionary history, demographic shifts and environmental exposures, influencing complex traits, disease susceptibility and drug responses. Capturing this diversity is essential for advancing precision medicine and promoting equitable healthcare. Despite the great progress achieved with initiatives such as the human Pangenome and large biobanks that aim for a better representation of human diversity, important challenges remain. In this Perspective, we discuss the importance of diversity in clinical genomics through an evolutionary lens. We highlight progress and challenges and outline key clinical applications of diverse genetic data. We argue that diversifying both datasets and methodologies-integrating ancestral and environmental factors-is crucial for fully understanding the genetic basis of human health and disease.

Integrating genomics as clinical biomarkers in pediatric pulmonology

Respiratory diseases often result from complex interactions between an individual's genetic predisposition and their exposure to various environmental and other risk factors. Here we will briefly review how various types of "omics", particularly epigenomics and transcriptomics, hold promise for translation into clinical biomarkers in pediatric pulmonary medicine, using asthma and cystic fibrosis as examples.

Identifying chronic obstructive pulmonary disease subtypes using multi-trait genetics

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) has a broad spectrum of clinical characteristics. The aetiology of these differences is not well understood. The objective of this study is to assess whether respiratory genetic variants cluster by phenotype and associate with COPD heterogeneity.

METHODS

We clustered genome-wide association studies of COPD, lung function, and asthma and phenotypes from the UK Biobank using non-negative matrix factorization. We constructed cluster-specific genetic risk scores and tested these scores for association with phenotypes in non-Hispanic white subjects in the COPDGene study.

FINDINGS

We identified three clusters from 482 variants and 44 traits from genetic associations in 379,337 UK Biobank participants. Variants from asthma, COPD, and lung function were found in all three clusters. Clusters displayed varying effects on white blood cell counts, height, and body mass index (BMI)-related phenotypes in the UK Biobank. In the COPDGene cohort, cluster-specific genetic risk scores were associated with differences in steroid use, BMI, lymphocyte counts, and chronic bronchitis, as well as variations in gene and protein expression.

INTERPRETATION

Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.

FUNDING

MHC was supported by R01HL149861, R01HL135142, R01HL137927, R01HL147148, and R01HL089856. HA and HJ were supported by ANR-20-CE36-0009-02 and ANR-16-CONV-0005. The COPDGene study (NCT00608764) is supported by grants from the NHLBI (U01HL089897 and U01HL089856), by NIH contract 75N92023D00011, and by the COPD Foundation through contributions made to an Industry Advisory Committee that has included AstraZeneca, Bayer Pharmaceuticals, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer and Sunovion.

Blood-Based EWAS of Asthma Polygenic Burden in The Netherlands Twin Register

Asthma, a chronic respiratory condition characterized by airway inflammation, affects millions of individuals worldwide. Challenges remain in asthma prediction and diagnosis from its complex etiology involving genetic and environmental factors. Here, we investigated the relationship between genome-wide DNA methylation and genetic risk for asthma quantified via polygenic scores in two cohorts from the Netherlands Twin Register; one enriched with asthmatic families measured on the Illumina EPIC array (n = 526) and a general population cohort measured on the Illumina HM450K array (n = 2680). We performed epigenome-wide association studies of asthma polygenic scores in each cohort with results combined through meta-analysis (total samples = 3206). The EWAS meta-analysis identified 63 significantly associated CpGs, (following Bonferroni correction, α = 0.05/358,316). An investigation of previous mQTL associations identified 48 mQTL associations between 24 unique CpGs and 48 SNPs, of which two SNPs have previous associations with asthma. Enrichment analysis using the 63 significant CpGs highlighted previous associations with ancestry, smoking, and air pollution. A dizygotic twin within-pair analysis of the 63 CpGs revealed similar directional effects between the two cohorts in 33 of the 63 CpGs. These findings further characterize the intricate relationship between DNA methylation and genetics relative to asthma.

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.

Environmental exposures associated with atopy in a rural community in Gwanda district, Zimbabwe: a cross-sectional study

Introduction

The increasing prevalence of allergic diseases in Zimbabwe may be attributed to changing environmental exposure patterns. In this study, we sought to identify the most influential environmental and lifestyle factors that may explain the observed atopy in a rural community in Zimbabwe.

Methods

Using a cross-sectional study, information on a wide array of environmental and lifestyle exposures was self-reported by a sample of participants (children aged <18 years and adults aged ≥18 years) in the Gwanda district, Zimbabwe. To consenting participants, we performed skin prick testing (SPT) at a local clinic in Gwanda district to identify atopic individuals. Variables with a p value <0.25 from univariate analysis were included in backward-elimination multiple logistic regression analysis. Separate regression analyses were conducted for children (n = 108), adults (n = 388), and a subgroup of adults who reported ever being employed in any potentially harmful occupation (n = 153).

Results

Compared with boys, girls were more likely to be sensitised to at least one allergen (OR = 4.87, 95% CI = 1.22-19.51). Among adults, the likelihood of sensitisation increased with increasing age (OR = 1.02, 95% CI = 1.01-1.03) and with a history of bloody urine and/or schistosomiasis (OR = 2.20, 95% CI = 0.98-4.95). In the subgroup of adults who reported ever being employed in any potentially harmful occupation, atopic sensitisation was associated with a history of tuberculosis (TB; OR = 3.37, 95% CI = 1.08-10.52) and a history of bloody urine and/or schistosomiasis (OR = 4.36, 95% CI = 1.40-13.65). Other notable, though not significant, factors were passive or parental smoking, alcohol consumption, indoor dampness and visible mould on walls.

Conclusion

Girls were more likely to be sensitised to at least one allergen when compared to boys. Among adults, atopic sensitisation was positively associated with age, parental smoking, alcohol consumption and history of bloody urine or schistosomiasis but negatively associated with indoor cooking. A history of TB or helminth infection increased the likelihood of atopy among adults with history of employment. Longitudinal studies to explore the temporal and causal relationships between these factors and allergic outcomes are essential. There is a need for early public health interventions to address environmental and lifestyle factors for the prevention and control of allergic diseases in African rural communities.

The clinical value and most informative threshold of polygenic risk score in the Quebec City Case-Control Asthma Cohort

Genome-wide association studies (GWAS) have identified genetic variants robustly associated with asthma. A potential near-term clinical application is to calculate polygenic risk score (PRS) to improve disease risk prediction. The value of PRS, as part of numerous multi-source variables used to define asthma, remains unclear. This study aims to evaluate PRS and define most informative thresholds in relation to conventional clinical and physiological criteria of asthma using a multivariate statistical method. Clinical and genome-wide genotyping data were obtained from the Quebec City Case-Control Asthma Cohort (QCCCAC), which is an independent cohort from previous GWAS. PRS was derived using LDpred2 and integrated with other asthma phenotypes by means of Principal Component Analysis with Optimal Scaling (PCAOS). PRS was considered using 'ordinal level of scaling' to account for non-linear information. In two dimensional PCAOS space, the first component delineated individuals with and without asthma, whereas the severity of asthma was discerned on the second component. The positioning of high vs. low PRS in this space matched the presence and absence of airway hyperresponsiveness, showing that PRS delineated cases and controls at the same extent as a positive bronchial challenge test. The top 10% and the bottom 5% of the PRS were the most informative thresholds to define individuals at high and low genetic risk of asthma in this cohort. PRS used in a multivariate method offers a decision-making space similar to hyperresponsiveness in this cohort and highlights the most informative and asymmetrical thresholds to define high and low genetic risk of asthma.

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.

Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma

Asthma is a common complex disease with susceptibility defined through an interplay of genetic and environmental factors. Responsiveness to asthma treatment varies between individuals and is largely determined by genetic variability. The polygenic score (PGS) approach enables an individual risk of asthma and respective response to drug therapy. PGS models could help to predict the individual risk of asthma using 26 SNPs of drug pathway genes involved in the metabolism of glucocorticosteroids (GCS), and beta-2-agonists, antihistamines, and antileukotriene drugs associated with the response to asthma treatment within GWAS were built. For PGS, summary statistics from the Trans-National Asthma Genetic Consortium GWAS meta-analysis, and genotype data for 882 individuals with asthma/controls from the Volga-Ural region, were used. The study group was comprised of Russian, Tatar, Bashkir, and mixed ethnicity individuals with asthma (N = 378) aged 2-18 years. and individuals without features of atopic disease (N = 504) aged 4-67 years from the Volga-Ural region. The DNA samples for the study were collected from 2000 to 2021. The drug pathway genes' PGS revealed a higher odds for childhood asthma risk (p = 2.41 × 10-12). The receiver operating characteristic (ROC) analysis showed an Area Under the Curve, AUC = 0.63. The AUC of average significance for moderate-to-severe and severe asthma was observed (p = 5.7 × 10-9, AUC = 0.64). Asthma drug response pathway gene variant PGS models may contribute to the development of modern approaches to optimise asthma diagnostics and treatment.

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.