Zhe Chen, Ning Gao, Xuanye Wang, Xiangming Chen, YaQi Zeng, Cong Li, Xiahong Yang, Qidong Cai, Xiang Wang
{"title":"呼吸系统疾病的共同遗传病因：全基因组多特征关联分析。","authors":"Zhe Chen, Ning Gao, Xuanye Wang, Xiangming Chen, YaQi Zeng, Cong Li, Xiahong Yang, Qidong Cai, Xiang Wang","doi":"10.1136/bmjresp-2023-002148","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms.</p><p><strong>Methods: </strong>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.</p><p><strong>Main outcomes and measures: </strong>The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions and relevance: </strong>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.</p>","PeriodicalId":9048,"journal":{"name":"BMJ Open Respiratory Research","volume":"11 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11163672/pdf/","citationCount":"0","resultStr":"{\"title\":\"Shared genetic aetiology of respiratory diseases: a genome-wide multitraits association analysis.\",\"authors\":\"Zhe Chen, Ning Gao, Xuanye Wang, Xiangming Chen, YaQi Zeng, Cong Li, Xiahong Yang, Qidong Cai, Xiang Wang\",\"doi\":\"10.1136/bmjresp-2023-002148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms.</p><p><strong>Methods: </strong>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.</p><p><strong>Main outcomes and measures: </strong>The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions and relevance: </strong>This study reveals the common genetic basis and pleiotropic genes among respiratory diseases. 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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.
期刊介绍：
BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.
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