Vitamin D receptor gene polymorphisms and multiple myeloma: a meta-analysis.

Vitamin D acts through the vitamin D receptor (VDR), and vitamin D level decreases in multiple myeloma (MM) patients. Single nucleotide polymorphisms in VDR alter its functions to affect the vitamin D status. This raises the question of whether VDR gene polymorphisms are associated with MM risk, which has been investigated in case‒control studies, but the results have been inconsistent. This meta-analysis aimed to investigate the relationship between VDR gene polymorphisms and MM risk. The PubMed, Web of Science, Medline, Embase, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journal (VIP), Wanfang Databases (WANFANG) were searched from inception to June 1, 2023, without language restriction or publication preference. Pooled odds ratio (OR) and 95% confidence interval (CI) for each variable were calculated. Leave-one-out sensitivity analysis was performed to determine the source of heterogeneity. Publication bias was assessed using Begg' and Egger's tests, and the trim-and-fill method was used to compensate for publication bias. The correlation meta-analysis was conducted using Comprehensive Meta-Analysis 3.0 and STATA 12.0 software. All the included studies were based on Asian populations and involved four VDR gene polymorphisms, TaqI (rs731236), ApaI (rs7975232), BsmI (rs1544410) and FokI (rs2228570). The results showed that TaqI (C vs. T: OR = 1.487, 95% CI 1.052, 2.104, P = 0.025; CC + CT vs. TT: OR = 1.830, 95% CI 1.138, 2.944, P = 0.013), ApaI (T vs. G: OR = 1.292, 95% CI 1.101, 1.517, P = 0.002; TT vs. GG: OR = 1.600, 95% CI 1.106, 2.314, P = 0.013; TG vs. GG: OR 1.305, 95% CI 1.050, 1.622; P = 0.016; TT + TG vs. GG: OR = 1.353, 95% CI 1.103, 1.662, P = 0.004), BsmI (GG vs. AA: OR = 1.918, 95% CI 1.293, 2.844, P = 0.001; GA vs. AA: OR = 1.333, 95% CI 1.058, 1.679, P = 0.015; G vs. A: OR = 1.398, 95% CI 1.180, 1.657, P = 0.000; GG vs. AA + GA: OR = 1.686, 95% CI 1.174, 2.423, P = 0.005), and FokI (T vs. C: OR = 1.687, 95% CI 1.474, 1.931, P = 0.000; TT vs. CC: OR = 2.829, 95% CI 2.066, 3.872, P = 0.000; TC vs. CC: OR = 1.579, 95% CI 1.304, 1.913, P = 0.000, TT + TC vs. CC: OR = 1.771, 95% CI 1.477, 2.125, P = 0.000; TT vs. CC + TC: OR = 2.409, 95% CI 1.814, 3.200, P = 0.000) are associated with MM risk. VDR gene polymorphisms including ApaI, BsmI, TaqI, and FokI are associated with MM risk in Asian populations. Additional studies with large sample sizes and different ethnicities are needed.

A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism.

BACKGROUND: MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn't been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training. RESULTS: The experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227. CONCLUSIONS: The model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others.

Increased risk of hearing loss associated with MT-RNR1 gene mutations: a real-world investigation among Han Taiwanese Population.

BACKGROUND: Previous studies have implicated inherited mutations in mitochondrial DNA (mtDNA) in sensorineural hearing loss (SNHL). However, the definitive association between mitochondrial 12S rRNA (MT-RNR1) variants and hearing loss in the population has not been well established, particularly in Asia. The objective of this retrospective cohort study was to assess the association between MT-RNR1 variants and the risk of SNHL in patients in Taiwan. METHODS: The cohort included 306,068 participants from Taiwan between January 2003 and December 2020. Participants were classified based on genetic variants, particularly mitochondrial mutations (rs267606618, rs267606619, rs267606617). MT-RNR1 variant cases were matched 1:10 with non-mutant patients by age, gender, and visit year, excluding those with pre-existing hearing loss. The primary endpoint was SNHL, identified using specific ICD-TM codes with a 90% positive predictive value. Medication exposure history was determined via self-report or electronic medical records in the hospital. Cox proportional hazard regression models were used to assess the association between MT-RNR1 variants and hearing loss, adjusting for various covariates. Kaplan-Meier survival curves and log-rank tests compared hearing loss incidence between groups. RESULTS: The mean age of the mtDNA variants group is 32.4 years, with a standard deviation of 19.2 years. The incidence density of hearing loss for the mutation group was 36.42 per 10,000 person-years (95% Confidence Interval [CI], 27.21-47.73), which was higher than the 23.77per 10,000 person-years (95% CI, 21.32-26.42) in the wild-type group (p = 0.0036). Additionally, diabetes mellitus was associated with an increased risk of developing SNHL in individuals with MT-RNR1 variants (adjusted hazard ratio = 1.76 [95% CI, 1.00-3.09], p < 0.05). CONCLUSION: This study highlights the increased risk of hearing loss in patients carrying MT-RNR1 variants, particularly those with diabetes mellitus. Future research that integrates genetic and clinical data is crucial for developing more precise interventions to monitor and treat hearing loss in this vulnerable population.

A cross-tissue transcriptome-wide association study reveals novel susceptibility genes for migraine.

BACKGROUND: Migraine is a common neurological disorder with a strong genetic component. Despite the identification of over 100 loci associated with migraine susceptibility through genome-wide association studies (GWAS), the underlying causative genes and biological mechanisms remain predominantly elusive. METHODS: The FinnGen R10 dataset, consisting of 333,711 subjects (20,908 cases and 312,803 controls), was utilized in conjunction with the Genotype-Tissue Expression Project (GTEx) v8 EQTls files to conduct cross-tissue transcriptome association studies (TWAS). Functional Summary-based Imputation (FUSION) was employed to validate these findings in single tissues. Additionally, candidate susceptibility genes were screened using Gene Analysis combined with Multi-marker Analysis of Genomic Annotation (MAGMA). Subsequent Mendelian randomization (MR) and colocalization analyses were conducted. Furthermore, GeneMANIA analysis was employed to enhance our understanding of the functional implications of these susceptibility genes. RESULTS: We identified a total of 19 susceptibility genes associated with migraine in the cross-tissue TWAS analysis. Two novel susceptibility genes, REV1 and SREBF2, were validated through both single tissue TWAS and MAGMA analysis. Mendelian randomization and colocalization analyses further confirmed these findings. REV1 may reduce the migraine risk by regulating DNA damage repair, while SREBF2 may increase the risk of migraine by regulating cholesterol metabolism. CONCLUSION: Our study identified two novel genes whose predicted expression was associated with the risk of migraine, providing new insights into the genetic framework of migraine.

Genetic liability of gut microbiota for idiopathic pulmonary fibrosis and lung function: a two-sample Mendelian randomization study.

Background: The microbiota-gut-lung axis has elucidated a potential association between gut microbiota and idiopathic pulmonary fibrosis (IPF). However, there is a paucity of population-level studies with providing robust evidence for establishing causality. This two-sample Mendelian randomization (MR) analysis aimed to investigate the causal relationship between the gut microbiota and IPF as well as lung function. Materials and methods: Adhering to Mendel's principle of inheritance, this MR analysis utilized summary-level data from respective genome-wide association studies (GWAS) involving 211 gut microbial taxa, IPF, and lung function indicators such as FEV1, FVC, and FEV1/FVC. A bidirectional two-sample MR design was employed, utilizing multiple MR analysis methods, including inverse variance-weighted (IVW), weighted median, MR-Egger, and weighted mode. Multivariable MR (MVMR) was used to uncover mediating factors connecting the exposure and outcome. Additionally, comprehensive sensitivity analyses were conducted to ensure the robustness of the results. Results: The MR results confirmed four taxa were found causally associated with the risk of IPF. Order Bifidobacteriales (OR=0.773, 95% CI: 0.610-0.979, p=0.033), Family Bifidobacteriaceae (OR=0.773, 95% CI: 0.610-0.979, p=0.033), and Genus RuminococcaceaeUCG009 (OR=0.793, 95% CI: 0.652-0.965, p=0.020) exerted protective effects on IPF, while Genus Coprococcus2 (OR=1.349, 95% CI: 1.021-1.783, p=0.035) promote the development of IPF. Several taxa were causally associated with lung function, with those in Class Deltaproteobacteria, Order Desulfovibrionales, Family Desulfovibrionaceae, Class Verrucomicrobiae, Order Verrucomicrobiales and Family Verrucomicrobiaceae being the most prominent beneficial microbiota, while those in Family Lachnospiraceae, Genus Oscillospira, and Genus Parasutterella were associated with impaired lung function. As for the reverse analysis, MR results confirmed the effects of FEV1 and FVC on the increased abundance of six taxa (Phylum Actinobacteria, Class Actinobacteria, Order Bifidobacteriales, Family Bifidobacteriaceae, Genus Bifidobacterium, and Genus Ruminiclostridium9) with a boosted level of evidence. MVMR suggested monounsaturated fatty acids, total fatty acids, saturated fatty acids, and ratio of omega-6 fatty acids to total fatty acids as potential mediating factors in the genetic association between gut microbiota and IPF. Conclusion: The current study suggested the casual effects of the specific gut microbes on the risk of IPF and lung function. In turn, lung function also exerted a positive role in some gut microbes. A reasonable dietary intake of lipid substances has a certain protective effect against the occurrence and progression of IPF. This study provides novel insights into the potential role of gut microbiota in IPF and indicates a possible gut microbiota-mediated mechanism for the prevention of IPF.

Diastolic and systolic blood pressure and gout: a Mendelian randomization study.

Background: Although there is solid epidemiological evidence supporting the connection between hypertension and gout, little has been said about the relationship between diastolic and systolic blood pressure and gout, the causal relationship and direction associated are uncertain, so we aim to research the causal relationship between diastolic and systolic blood pressure and gout. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effect between 2 blood pressure phenotypes (including diastolic blood pressure and systolic blood pressure) and 5 gout phenotypes (including gout, drug-induced gout, idiopathic gout, unspecified gout, and strictly defined gout) using genome-wide association study statistics. The inverse variance weighting method was used to generate the main results, while sensitivity analyses using MR-Egger, weighted median, Cochran's Q test, Egger intercept test, and leave-one-out analysis, were performed to assess the stability and reliability of the results. Results: After the screening, we found a causal relationship between diastolic blood pressure and gout, idiopathic gout, unspecified gout, and strictly defined gout, and a causal relationship between systolic blood pressure and gout, idiopathic gout, unspecified gout, and strictly defined gout. Conclusion: From a genetic predisposition, controlling blood pressure may reduce the risk of gout.

Genetic variants in UNC93B1 predispose to childhood-onset systemic lupus erythematosus.

Rare genetic variants in toll-like receptor 7 (TLR7) are known to cause lupus in humans and mice. UNC93B1 is a transmembrane protein that regulates TLR7 localization into endosomes. In the present study, we identify two new variants in UNC93B1 (T314A, located proximally to the TLR7 transmembrane domain, and V117L) in a cohort of east Asian patients with childhood-onset systemic lupus erythematosus. The V117L variant was associated with increased expression of type I interferons and NF-κB-dependent cytokines in patient plasma and immortalized B cells. THP-1 cells expressing the variant UNC93B1 alleles exhibited exaggerated responses to stimulation of TLR7/-8, but not TLR3 or TLR9, which could be inhibited by targeting the downstream signaling molecules, IRAK1/-4. Heterozygous mice expressing the orthologous Unc93b1V117L variant developed a spontaneous lupus-like disease that was more severe in homozygotes and again hyperresponsive to TLR7 stimulation. Together, this work formally identifies genetic variants in UNC93B1 that can predispose to childhood-onset systemic lupus erythematosus.

Quantifying variations associated with dental caries reveals disparity in effect allele frequencies across diverse populations.

BACKGROUND: Dental caries (DC) is a multifaceted oral condition influenced by genetic and environmental factors. Recent advancements in genotyping and sequencing technologies, such as Genome-Wide Association Studies (GWAS) have helped researchers to identify numerous genetic variants associated with DC, but their prevalence and significance across diverse global populations remain poorly understood as most of the studies were conducted in European populations, and very few were conducted in Asians specifically in Indians. AIM: This study aimed to evaluate the genetic affinity of effect alleles associated with DC to understand the genetic relationship between global populations with respect to the Indian context. METHODOLOGY: This present study used an empirical approach in which variants associated with DC susceptibility were selected. These variants were identified and annotated using the GWAS summary. The genetic affinity was evaluated using Fst. RESULTS: The effect of allele frequencies among different populations was examined, revealing variations in allele distribution. African populations exhibited higher frequencies of specific risk alleles, whereas East Asian and European populations displayed distinct profiles. South Asian populations showed a unique genetic cluster. CONCLUSION: Our study emphasises the complex genetic landscape of DC and highlights the need for population-specific research as well as validation of GWAS-identified markers in Indians before defining them as established candidate genes.

Single-cell and genome-wide Mendelian randomization identifies causative genes for gout.

BACKGROUND: Gout is a prevalent manifestation of metabolic osteoarthritis induced by elevated blood uric acid levels. The purpose of this study was to investigate the mechanisms of gene expression regulation in gout disease and elucidate its pathogenesis. METHODS: The study integrated gout genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and methylation quantitative trait loci (mQTL) data for analysis, and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and gout. RESULTS: We identified 17 association signals for gout at unique genetic loci, including four genes related by protein-protein interaction network (PPI) analysis: TRIM46, THBS3, MTX1, and KRTCAP2. Additionally, we discerned 22 methylation sites in relation to gout. The study also found that genes such as TRIM46, MAP3K11, KRTCAP2, and TM7SF2 could potentially elevate the risk of gout. Through a Mendelian randomization (MR) analysis, we identified three proteins causally associated with gout: ADH1B, BMP1, and HIST1H3A. CONCLUSION: According to our findings, gout is linked with the expression and function of particular genes and proteins. These genes and proteins have the potential to function as novel diagnostic and therapeutic targets for gout. These discoveries shed new light on the pathological mechanisms of gout and clear the way for future research on this condition.

Mendelian randomization evidence based on European ancestry for the causal effects of leukocyte telomere length on prostate cancer.

BACKGROUND: Several lines of evidence suggest that leukocyte telomere length (LTL) can affect the development of prostate cancer (PC). METHODS: Here, we employed single nucleoside polymorphisms (SNPs) as instrumental variables (IVs) for LTL (n = 472,174) and conducted Mendelian randomization analysis to estimate their causal impact on PCs (79,148 patients/61,106 controls and 6311 patients/88,902 controls). RESULTS: Every 1-s.d extension of LTL increased the risk of PCs by 34%. Additionally, the analysis of candidate mediators between LTL and PCs via two-step Mendelian randomization revealed that among the 23 candidates, Alzheimer's disease, liver iron content, sex hormone binding global levels, naive CD4-CD8-T cell% T cell, and circulating leptin levels played substantial mediating roles. There is no robust evidence to support the reverse causal relationship between LTL and the selected mediators of PCs. Adjusting for the former four mediators, rather than adjusting for circulating leptin levels, decreased the impact of LTL on PCs. CONCLUSION: This study provides potential intervention measures for preventing LTL-induced PCs.

Genetic, epigenetic and environmental factors in diverticular disease: systematic review.

BACKGROUND: Diverticulosis is a normal anatomical variant of the colon present in more than 70% of the westernized population over the age of 80. Approximately 3% will develop diverticulitis in their lifetime. Many patients present emergently, suffer high morbidity rates and require substantial healthcare resources. Diverticulosis is the most common finding at colonoscopy and has the potential for causing a significant morbidity rate and burden on healthcare. There is a need to better understand the aetiology and pathogenesis of diverticular disease. Research suggests a genetic susceptibility of 40-50% in the formation of diverticular disease. The aim of this review is to present the hypothesized functional effects of the identified gene loci and environmental factors. METHODS: A systematic literature review was performed using PubMed, MEDLINE and Embase. Medical subject headings terms used were: 'diverticular disease, diverticulosis, diverticulitis, genomics, genetics and epigenetics'. A review of grey literature identified environmental factors. RESULTS: Of 995 articles identified, 59 articles met the inclusion criteria. Age, obesity and smoking are strongly associated environmental risk factors. Intrinsic factors of the colonic wall are associated with the presence of diverticula. Genetic pathways of interest and environmental risk factors were identified. The COLQ, FAM155A, PHGR1, ARHGAP15, S100A10, and TNFSF15 genes are the strongest candidates for further research. CONCLUSION: There is increasing evidence to support the role of genomics in the spectrum of diverticular disease. Genomic, epigenetic and omic research with demographic context will help improve the understanding and management of this complex disease.

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement.

BACKGROUND: Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets. METHODS: We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer's disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups. RESULTS: Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations. CONCLUSIONS: This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.

The Relationship Between the hOGG1 rs1052133 Polymorphism and the Occurrence of Nasopharyngeal Carcinoma: A Systematic Review and Meta-Analysis.

Objectives: Exploring the relationship between the hOGG1 rs1052133 polymorphism and the occurrence of nasopharyngeal carcinoma (NPC). Methods: PubMed, Web of Science, Scopus, CNKI, Wanfangdata, and VIP were used to search for studies and the NOS evaluation scale was used to evaluate the quality. All studies were grouped according to different genotypes. The Cochrane's Q test and I2 test were used for heterogeneity evaluations. If heterogeneity was small, the fixed effects model was used, and conversely, the random effects model was used. Publication bias was also detected. P < .05 in all results indicated statistically significant. Results: We ultimately included 6 studies with 2021 NPC patients in the study group and 2375 healthy populations in the control group. After meta-analysis, it was found that the total OR value of the "Ser/Cys (CG) vs Ser/Ser (CC)" group was 1.00 (95% CI: 0.85-1.18) and the "Cys/Cys (GG) vs Ser/Ser (CC)" group was 1.06 (95% CI: 0.87-1.28). These results were not statistically significant (P > .05). Furthermore, the integrated total OR values of each group were not statistically significant with or without the smoking history, even in other genotype models (Allele, Dominant, Recessive, and Additive) (P > .05). Conclusion: There is no clear correlation between the hOGG1 rs1052133 polymorphism and the occurrence of NPC, even with or without the smoking history.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies.

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

Prospective of Mitochondrial DNA Variations in Cancer on Genomic Medicine.

Mitochondrial DNA (mtDNA) has emerged as a pivotal component in understanding the etiology and susceptibility of cancer. A recent study by Chen and colleagues delineated the germline genetic effect of mtDNA single-nucleotide polymorphisms (SNP) and haplogroups across pan-cancer risk. They identified a subset of mtSNPs and the corresponding risk score, as well as haplogroups A and M7 alongside their genetic interactions, conferring a protective effect against various cancers. These findings underscored the value of mtDNA variations as biomarkers for cancer etiology and as tools for cancer risk stratification. Future investigations are encouraged to integrate comprehensive omics data of genomics, transcriptomics, proteomics, and metabolomics, etc., from nuclear DNA with mtDNA variations, alongside single-cell and spatial technologies, to unravel the tumor mechanism and identify the drug targets. Moreover, the incorporation of polygenic risk score, that included mtDNA variations with both rare and common frequencies, and liquid biopsy-based biomarkers would enhance the predictive performance of cancer risk assessment and refine the risk stratification of population-based cancer screening. This commentary advocates for the validation across diverse populations to harness the full potential of mitochondrial genomics, and ultimately paves the prospective way for advancements in personalized cancer therapeutics and prevention strategies. See related article by Chen and colleagues, Cancer Epidemiol Biomarkers Prev 2024;33:381-8.

Circulating interleukin-27 is associated with the risk of chronic periodontitis and allergic rhinitis: A Mendelian randomization analysis.

BACKGROUND: Chronic periodontitis (CP) and allergic rhinitis (AR) have attracted wide attention as global public health problems with high incidence. Recent studies have shown that circulating interleukin-27 (IL-27) is associated with the risk of CP and AR. The aim of this study is to analyze the causal effect between them using Mendelian randomization (MR). METHODS: Bidirectional MR analyses were performed with the use of publicly available genome-wide association study (GWAS) data. Summary data on circulating IL-27, CP, and AR published in genome-wide association studies were collected. Instrumental variables (IV) were extracted using assumptions of correlation, independence and exclusivity as criteria. Inverse variance weighting (IVW) was used as the main method, combined with weighted median method (WM) and MR-Egger and other MR Analysis methods for causal inference of exposure and outcome. Cochran's Q and MR-Egger intercept were used for sensitivity analysis. RESULTS: The IVW study showed a causal effect between increased circulating IL-27 levels and increased risk of CP (OR = 1.14, 95%CI = 1.02-1.26, p = .020). Similarly, the increase of circulating IL-27 level had a causal effect on the decreased risk of AR (OR = 0.88, 95%CI = 0.80-0.97, p = .012). In addition, IVW study found that there was a causal between the increased risk of CP and circulating IL-27 level (OR = 1.05, 95%CI = 1.01-1.10, p = .016). However, there was no significant causal relationship between the risk of AR and circulating IL-27 levels (OR = 0.97, 95%CI = 0.91-1.02, p = .209). no significant heterogeneity or horizontal pleiotropy was found in sensitivity analysis. CONCLUSIONS: There is a causal effect between circulating IL-27 level and CP, AR, which will help to find new ideas and methods for the diagnosis and treatment of CP and AR.

Shared genetic aetiology of respiratory diseases: a genome-wide multitraits association analysis.

OBJECTIVE: This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms. METHODS: This genome-wide pleiotropic association study uses multiple statistical methods to systematically analyse the shared genetic basis between five respiratory diseases (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, lung cancer and snoring) using the largest publicly available genome wide association studies summary statistics. The missions of this study are to evaluate global and local genetic correlations, to identify pleiotropic loci, to elucidate biological pathways at the multiomics level and to explore causal relationships between respiratory diseases. Data were collected from 27 November 2022 to 30 March 2023 and analysed from 14 April 2023 to 13 July 2023. MAIN OUTCOMES AND MEASURES: The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects. RESULTS: Significant genetic correlations were found for 10 paired traits in 5 respiratory diseases. Cross-Phenotype Association identified 12 400 significant potential pleiotropic single-nucleotide polymorphism at 156 independent pleiotropic loci. In addition, multitrait colocalisation analysis identified 15 colocalised loci and a subset of colocalised traits. Gene-based analyses identified 432 potential pleiotropic genes and were further validated at the transcriptome and protein levels. Both pathway enrichment and single-cell enrichment analyses supported the role of the immune system in respiratory diseases. Additionally, five pairs of respiratory diseases have a causal relationship. CONCLUSIONS AND RELEVANCE: This study reveals the common genetic basis and pleiotropic genes among respiratory diseases. It provides strong evidence for further therapeutic strategies and risk prediction for the phenomenon of respiratory disease comorbidity.