Genes Involved in Interleukin-1 Receptor Type II Activities Are Associated With Asthmatic Phenotypes

Influence of Single Nucleotide Polymorphisms on CRS Outcomes: A Preliminary Observational Study

OBJECTIVE(S)

To conduct a preliminary investigation into the relationship between specific SNP variants, type II inflammation, and the effectiveness of dupilumab therapy and surgery in patients with CRS.

METHODS

In this prospective study, 48 subjects were enrolled, comprising 32 CRS patients and 16 healthy controls. The CRS patients were subjected to either dupilumab therapy or endoscopic surgery according to EPOS guidelines. SNP variants were identified using the TaqMan SNP genotyping technique. The identified SNP profiles were compared between the control group and CRS patients, and their potential influence on treatment outcomes was evaluated. Treatment responses were assessed based on symptom scores, such as SS-I, SNOT-22, disease progression using the NPS findings, and SNP profiles at a 6-month follow-up. The primary measures included the Nasal Polyp Score, Smell Identification Test (SIT) score, and SNOT-22 outcomes.

RESULTS

Dupilumab therapy and surgery significantly decreased NPS, with the last showing superior results. However, dupilumab therapy resulted in a significantly improved SIT score. Significant differences were observed in SNP profiles, particularly with rs1800629 (TNFA), rs2856838 (IL1a), rs17561 (IL1a), and rs1805011 (IL4R). In particular, the expression of rs2856838 and rs1805011 variants in the dupilumab group was associated with significantly better SIT and SNOT-22 outcomes than non-expressors. Also, the surgery group patients expressing the rs2856838 variant reported significant improvements in SNOT-22 scores.

CONCLUSION

These preliminary findings suggest that SNP genotypes may guide personalized treatment strategies for CRS. Further larger prospective studies are required to confirm these initial observations.

LEVEL OF EVIDENCE

2 Laryngoscope, 135:570-578, 2025.

MOSES: a methylation-based gene association approach for unveiling environmentally regulated genes linked to a trait or disease

BACKGROUND

DNA methylation is a critical regulatory mechanism of gene expression, influencing various human diseases and traits. While traditional expression quantitative trait loci (eQTL) studies have helped elucidate the genetic regulation of gene expression, there is a growing need to explore environmental influences on gene expression. Existing methods such as PrediXcan and FUSION focus on genotype-based associations but overlook the impact of environmental factors. To address this gap, we present MOSES (methylation-based gene association), a novel approach that utilizes DNA methylation to identify environmentally regulated genes associated with traits or diseases without relying on measured gene expression.

RESULTS

MOSES involves training, imputation, and association testing. It employs elastic-net penalized regression models to estimate the influence of CpGs and SNPs (if available) on gene expression. We developed and compared four MOSES versions incorporating different methylation and genetic data: (1) cis-DNA methylation within 1 Mb of promoter regions, (2) both cis-SNPs and cis-CpGs, 3) both cis- and a part of trans- CpGs (±5Mb away) from promoter regions), and 4) long-range DNA methylation (±10 Mb away) from promoter regions. Our analysis using nasal epithelium and white blood cell data from the Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR) study demonstrated that MOSES, particularly the version incorporating long-range CpGs (MOSES-DNAm 10 M), significantly outperformed existing methods like PrediXcan, MethylXcan, and Biomethyl in predicting gene expression. MOSES-DNAm 10 M identified more differentially expressed genes (DEGs) associated with atopic asthma, particularly those involved in immune pathways, highlighting its superior performance in uncovering environmentally regulated genes. Further application of MOSES to lung tissue data from idiopathic pulmonary fibrosis (IPF) patients confirmed its robustness and versatility across different diseases and tissues.

CONCLUSION

MOSES represents an innovative advancement in gene association studies, leveraging DNA methylation to capture the influence of environmental factors on gene expression. By incorporating long-range CpGs, MOSES-DNAm 10 M provides superior predictive accuracy and gene association capabilities compared to traditional genotype-based methods. This novel approach offers valuable insights into the complex interplay between genetics and the environment, enhancing our understanding of disease mechanisms and potentially guiding therapeutic strategies. The user-friendly MOSES R package is publicly available to advance studies in various diseases, including immune-related conditions like asthma.

Selective sweep analysis of the adaptability of the Yarkand hare (Lepus yarkandensis) to hot arid environments using SLAF-seq

The Yarkand hare (Lepus yarkandensis) inhabits arid desert areas and is endemic to China. It has evolved various adaptations to survive in hot arid environments, including stress responses, the ability to maintain water homeostasis and heat tolerance. Here, we performed a selective sweep analysis to identify the candidate genes for adaptation to hot arid environments in the Yarkand hare. A total of 397 237 single-nucleotide polymorphisms were obtained from 80 Yarkand hares, which inhabit hot arid environments, and 36 Tolai hares (Lepus tolai), which inhabit environments with a mild climate, via specific-locus amplified fragment sequencing. We identified several candidate genes that were associated with the heat stress response (HSPE1), oxidative stress response (SLC23A and GLRX2), immune response (IL1R1 and IRG1), central nervous system development (FGF13, THOC2, FMR1 and MECP2) and regulation of water homeostasis (CDK1) according to fixation index values and θπ ratios in the selective sweep analysis, and six of these genes (GLRX2, IRG1, FGF13, FMR1, MECP2 and CDK1) are newly discovered genes. To the best of our knowledge, this is the first study to identify candidate genes for adaptation to hot arid environments in the Yarkand hare. The results of this study enhance our understanding of the adaptation of the Yarkand hare to hot arid environments and will aid future studies aiming to functionally verify these candidate genes.

Deciphering the shared mechanisms of Gegen Qinlian Decoction in treating type 2 diabetes and ulcerative colitis via bioinformatics and machine learning

Background

Although previous clinical studies and animal experiments have demonstrated the efficacy of Gegen Qinlian Decoction (GQD) in treating Type 2 Diabetes Mellitus (T2DM) and Ulcerative Colitis (UC), the underlying mechanisms of its therapeutic effects remain elusive.

Purpose

This study aims to investigate the shared pathogenic mechanisms between T2DM and UC and elucidate the mechanisms through which GQD modulates these diseases using bioinformatics approaches.

Methods

Data for this study were sourced from the Gene Expression Omnibus (GEO) database. Targets of GQD were identified using PharmMapper and SwissTargetPrediction, while targets associated with T2DM and UC were compiled from the DrugBank, GeneCards, Therapeutic Target Database (TTD), DisGeNET databases, and differentially expressed genes (DEGs). Our analysis encompassed six approaches: weighted gene co-expression network analysis (WGCNA), immune infiltration analysis, single-cell sequencing analysis, machine learning, DEG analysis, and network pharmacology.

Results

Through GO and KEGG analysis of weighted gene co-expression network analysis (WGCNA) modular genes and DEGs intersection, we found that the co-morbidity between T2DM and UC is primarily associated with immune-inflammatory pathways, including IL-17, TNF, chemokine, and toll-like receptor signaling pathways. Immune infiltration analysis supported these findings. Three distinct machine learning studies identified IGFBP3 as a biomarker for GQD in treating T2DM, while BACE2, EPHB4, and EPHA2 emerged as biomarkers for GQD in UC treatment. Network pharmacology revealed that GQD treatment for T2DM and UC mainly targets immune-inflammatory pathways like Toll-like receptor, IL-17, TNF, MAPK, and PI3K-Akt signaling pathways.

Conclusion

This study provides insights into the shared pathogenesis of T2DM and UC and clarifies the regulatory mechanisms of GQD on these conditions. It also proposes novel targets and therapeutic strategies for individuals suffering from T2DM and UC.

Methyl-TWAS: A powerful method for in silico transcriptome-wide association studies (TWAS) using long-range DNA methylation

In silico transcriptome-wide association studies (TWAS) are commonly used to test whether expression of specific genes is linked to a complex trait. However, genotype-based in silico TWAS such as PrediXcan, exhibit low prediction accuracy for a majority of genes because genotypic data lack tissue- and disease-specificity and are not affected by the environment. Because methylation is tissue-specific and, like gene expression, can be modified by environment or disease status, methylation should predict gene expression with more accuracy than SNPs. Therefore, we propose Methyl-TWAS, the first approach that utilizes long-range methylation markers to impute gene expression for in silico TWAS through penalized regression. Methyl-TWAS 1) predicts epigenetically regulated/associated expression (eGReX), which incorporates tissue-specific expression and both genetically- (GReX) and environmentally-regulated expression to identify differentially expressed genes (DEGs) that could not be identified by genotype-based methods; and 2) incorporates both cis- and trans- CpGs, including various regulatory regions to identify DEGs that would be missed using cis- methylation only. Methyl-TWAS outperforms PrediXcan and two other methods in imputing gene expression in the nasal epithelium, particularly for immunity-related genes and DEGs in atopic asthma. Methyl-TWAS identified 3,681 (85.2%) of the 4,316 DEGs identified in a previous TWAS of atopic asthma using measured expression, while PrediXcan could not identify any gene. Methyl-TWAS also outperforms PrediXcan for expression imputation as well as in silico TWAS in white blood cells. Methyl-TWAS is a valuable tool for in silico TWAS, leveraging a growing body of publicly available genome-wide DNA methylation data for a variety of human tissues.

The priming effect of diesel exhaust on native pollen exposure at the air-liquid interface

Pollen related allergic diseases have been increasing for decades. The reasons for this increase are unknown, but environmental pollution like diesel exhaust seem to play a role. While previous studies explored the effects of pollen extracts, we studied here for the first time priming effects of diesel exhaust on native pollen exposure using a novel experimental setup.

METHODS

Human bronchial epithelial BEAS-2B cells were exposed to native birch pollen (real life intact pollen, not pollen extracts) at the air-liquid interface (pollen-ALI). BEAS-2B cells were also pre-exposed in a diesel-ALI to diesel CAST for 2 h (a model for diesel exhaust) and then to pollen in the pollen-ALI 24 h later. Effects were analysed by genome wide transcriptome analysis after 2 h 25 min, 6 h 50 min and 24 h. Selected genes were confirmed by qRT-PCR.

RESULTS

Bronchial epithelial cells exposed to native pollen showed the highest transcriptomic changes after about 24 h. About 3157 genes were significantly up- or down-regulated for all time points combined. After pre-exposure to diesel exhaust the maximum reaction to pollen had shifted to about 2.5 h after exposure, plus the reaction to pollen was desensitised as only 560 genes were differentially regulated. Only 97 genes were affected synergistically. Of these, enrichment analysis showed that genes involved in immune and inflammatory response were involved.

CONCLUSION

Diesel exhaust seems to prime cells to react more rapidly to native pollen exposure, especially inflammation related genes, a factor known to facilitate the development of allergic sensitization. The marker genes here detected could guide studies in humans when investigating whether modern and outdoor diesel exhaust exposure is still detrimental for the development of allergic disease.

Whole-genome sequencing of Tarim red deer (Cervus elaphus yarkandensis) reveals demographic history and adaptations to an arid-desert environment

Background

The initiation of desert conditions in the Tarim Basin in China since the late Miocene has led to the significant genetic structuring of local organisms. Tarim Red Deer (Cervus elaphus yarkandensis, TRD) have adapted to the harsh environmental conditions in this basin, including high solar radiation and temperature, aridity, and poor nutritional conditions. However, the underlying genetic basis of this adaptation is poorly understood.

Results

We sequenced the whole genomes of 13 TRD individuals, conducted comparative genomic analyses, and estimated demographic fluctuation. The ∂a∂i model estimated that the TRD and Tule elk (Cervus canadensis nannodes) populations diverged approximately 0.98 Mya. Analyses revealed a substantial influence of the Earth’s climate on the effective population size of TRD, associated with glacial advances and retreat, and human activities likely underlie a recent serious decline in population. A marked bottleneck may have profoundly affected the genetic diversity of TRD populations. We detected a set of candidate genes, pathways, and GO categories related to oxidative stress, water reabsorption, immune regulation, energy metabolism, eye protection, heat stress, respiratory system adaptation, prevention of high blood pressure, and DNA damage and repair that may directly or indirectly be involved in the adaptation of TRD to an arid-desert environment.

Conclusions

Our analyses highlight the role of historical global climates in the population dynamics of TRD. In light of ongoing global warming and the increasing incidence of droughts, our study offers insights into the genomic adaptations of animals, especially TRD, to extreme arid-desert environments and provides a valuable resource for future research on conservation design and biological adaptations to environmental change.

Effects of Allergic Sensitization on Antiviral Immunity: Allergen, Virus, and Host Cell Mechanisms

PURPOSE OF REVIEW

Multiple clinical and epidemiological studies demonstrate links between allergic sensitization and virus-induced atopic disease exacerbations. This review summarizes the recent findings regarding allergen, viral, and host cellular mechanisms relevant to these observations.

RECENT FINDINGS

Recent studies have focused on the molecular pathways and genetic influences involved in allergen-mediated inhibition of innate antiviral immune responses. Multiple tissue and cell types from atopic individuals across the atopy spectrum exhibit deficient interferon responses to a variety of virus infections. Impairment in barrier function, viral RNA and DNA recognition by intracellular sensing molecules, and dysregulation of signaling components are broadly affected by allergic sensitization. Finally, genetic predisposition by numerous nucleotide polymorphisms also impacts immune pathways and potentially contributes to virus-associated atopic disease pathogenesis. Allergen-virus interactions in the setting of atopy involve complex tissue and cellular mechanisms. Future studies defining the pathways underlying these interactions could uncover potential therapeutic targets. Available data suggest that therapies tailored to restore specific components of antiviral responses will likely lead to improved clinical outcomes in allergic disease.