LPP polymorphisms are risk factors for allergic rhinitis in the Chinese Han population.

BACKGROUND: Lipoma preferred partner (LPP) polymorphisms are related to immune diseases, but the role of LPP gene in the pathogenesis of allergic rhinitis (AR) is unclear. The current study aimed to explore the contribution of LPP variants to AR susceptibility in the Chinese Han population. METHODS: A total of 992 healthy controls and 992 patients with AR were recruited. Agena MassARRAY system was applied for genotyping. Odds ratios (OR) and 95% confidence intervals (CI) adjusted by age, sex, and body mass index (BMI) were calculated to conduct the risk assessment of LPP variants in people with a predisposition to AR. Additionally, multifactor dimensionality reduction (MDR) was applied to identify high-order interaction models for AR risk. RESULTS: We found that rs2030519-G (p = 0.027, OR: 1.15, 95% CI: 1.02-1.31), rs6780858-G (p = 0.019, OR: 1.16, 95% CI: 1.03-1.32), and rs60946162-T (p = 0.014, OR: 1.18, 95% CI: 1.03-1.34) were associated with increased susceptibility to AR. Subgroup analyses indicated the interaction of LPP polymorphisms in terms of age, gender, and BMI with AR susceptibility (p < 0.05, OR > 1). MDR analysis revealed that rs60946162 had the information gain (0.40%) of individual attribute regarding AR. CONCLUSION: Our results first determined that rs2030519, rs6780858, and rs60946162 were correlated with increased susceptibility to AR in the Chinese Han population, which add to our understanding of the impact of LPP gene variants on AR development.

Genetically predicted N-methylhydroxyproline levels mediate the association between naive CD8+ T cells and allergic rhinitis: a mediation Mendelian randomization study.

Background: Allergic rhinitis (AR), a prevalent chronic inflammatory condition triggered by immunoglobulin E (IgE), involves pivotal roles of immune and metabolic factors in its onset and progression. However, the intricacies and uncertainties in clinical research render current investigations into their interplay somewhat inadequate. Objective: To elucidate the causal relationships between immune cells, metabolites, and AR, we conducted a mediation Mendelian randomization (MR) analysis. Methods: Leveraging comprehensive publicly accessible summary-level data from genome-wide association studies (GWAS), this study employed the two-sample MR research method to investigate causal relationships among 731 immune cell phenotypes, 1400 metabolite levels, and AR. Additionally, employing the mediation MR approach, the study analyzed potential mediated effect of metabolites in the relationships between immune cells and AR. Various sensitivity analysis methods were systematically employed to ensure the robustness of the results. Results: Following false discovery rate (FDR) correction, we identified three immune cell phenotypes as protective factors for AR: Naive CD8br %CD8br (odds ratio (OR): 0.978, 95% CI = 0.966-0.990, P = 4.5×10-4), CD3 on CD39+ activated Treg (OR: 0.947, 95% CI = 0.923-0.972, P = 3×10-5), HVEM on CD45RA- CD4+ (OR: 0.967, 95% CI = 0.948-0.986, P = 4×10-5). Additionally, three metabolite levels were identified as risk factors for AR: N-methylhydroxyproline levels (OR: 1.219, 95% CI = 1.104-1.346, P = 9×10-5), N-acetylneuraminate levels (OR: 1.133, 95% CI = 1.061-1.211, P = 1.7×10-4), 1-stearoyl-2-arachidonoyl-gpc (18:0/20:4) levels (OR: 1.058, 95% CI = 1.029-1.087, P = 5×10-5). Mediation MR analysis indicated a causal relationship between Naive CD8br %CD8br and N-methylhydroxyproline levels, acting as a protective factor (OR: 0.971, 95% CI = 0.950-0.992, P = 8.31×10-3). The mediated effect was -0.00574, accounting for 26.1% of the total effect, with a direct effect of -0.01626. Naive CD8+ T cells exert a protective effect on AR by reducing N-methylhydroxyproline levels. Conclusion: Our study, delving into genetic information, has substantiated the intricate connection between immune cell phenotypes and metabolite levels with AR. This reveals a potential pathway to prevent the onset of AR, providing guiding directions for future clinical investigations.

Evaluation of droplet deposition parameters based on the Genetic-Otsu algorithm.

Pesticide spraying is a cost-effective way to control crop pests and diseases. The effectiveness of this method relies on the deposition and distribution of the spray droplets within the targeted application area. There is a critical need for an accurate and stable detection algorithm to evaluate the liquid droplet deposition parameters on the water-sensitive paper (WSP) and reduce the impact of image noise. This study acquired 90 WSP samples with diverse coverage through field spraying experiments. The droplets on the WSP were subsequently isolated, and the coverage and density were computed, employing the fixed threshold method, the Otsu threshold method, and our Genetic-Otsu threshold method. Based on the benchmark of manually measured data, an error analysis was conducted on the accuracy of three methods, and a comprehensive evaluation was carried out. The relative error results indicate that the Genetic-Otsu method proposed in this research demonstrates superior performance in detecting droplet coverage and density. The relative errors of droplet density in the sparse, medium, and dense droplet groups are 2.7%, 1.5%, and 2.0%, respectively. The relative errors of droplet coverage are 1.5%, 0.88%, and 1.2%, respectively. These results demonstrate that the Genetic-Otsu algorithm outperforms the other two algorithms. The proposed algorithm effectively identifies small-sized droplets and accurately distinguishes the multiple independent contours of adjacent droplets even in dense droplet groups, demonstrating excellent performance. Overall, the Genetic-Otsu algorithm offered a reliable solution for detecting droplet deposition parameters on WSP, providing an efficient tool for evaluating droplet deposition parameters in UAV pesticide spraying applications.

RORA polymorphisms are risk factors for allergic rhinitis susceptibility in the Shaanxi Han population.

BACKGROUND: Allergic rhinitis (AR) is the most common inflammatory disorder induced by complex interactions between genetic and environmental factors. Genetic predisposition is the most important factor in the progression of AR. Previous studies have indicated that RORA is involved in the occurrence of AR. The present study aimed to determine the roles of RORA polymorphisms in AR susceptibility. METHODS: Peripheral blood samples were collected from 990 patients with AR and 1004 normal controls. Four single nucleotide polymorphisms (SNPs) in the RORA gene were detected by MassARRAY iPLEX platform. The associations of RORA polymorphisms with AR risk were determined according to logistic regression analysis. We further evaluated the impact of SNP-SNP interaction on AR risk using multifactor dimensionality reduction (MDR) method. RESULTS: Our results showed that rs10519067 (OR 0.38, p = 0.021), rs10519068 (OR 0.45, p = 0.030), and rs11071559 (OR 0.83, p = 0.032) were significantly related to a decreased susceptibility to AR. Stratified analyses found that rs10519067 (OR 0.71, p = 0.046) and rs10519068 (OR 0.63, p = 0.010) could decrease the risk of AR in males. Rs10519068 (OR 0.73, p = 0.022), rs11071559 (OR 0.77, p = 0.041), and rs9302216 (OR 0.38, p = 0.017) significantly reduced the susceptibility to AR in people aged > 43 years. Furthermore, it was found that rs10519067 (OR 0.29, p = 0.032), rs10519068 (OR 0.72, p = 0.013), and rs11071559 (OR 0.36, p = 0.015) had a protective effect on AR patients with BMI ≤ 24 kg/m2. MDR revealed that the combination of rs10519067, rs10519068, rs11071559, and rs9302216 was the best predictive model for AR. CONCLUSION: Our study suggests that RORA polymorphisms may play a protective role in the development of AR.