DOI: 10.57760/sciencedb.j00173.00035
title: 250796 Enhance publishing | Identification of Novel Protein Drug Targets for Respiratory Diseases by Integrating Human Plasma Proteome with Genome
title: 250796增强出版 | 整合血浆蛋白质组与全基因组关联研究鉴定呼吸系统疾病新型药物靶标

description: Solemn statement: If this open source content is used in papers, books, academic reports, and other works, please cite the following references (the latest citation format is available in the original link): MA Xinqian, NI Wentao. Identification of Novel Protein Drug Targets for Respiratory Diseases by Integrating Human Plasma Proteome with Genome[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250796Authors: Ma Xinqian, Ni Wentao* Unit: Department of Respiratory and Critical Care Medicine, Peking University People's Hospital DOI：10.11999/JEIT250796 Original text: https://jeit.ac.cn/article/doi/10.11999/JEIT250796Corresponding author: Ni Wentao, wentao.qingdao@163.com Open source date: February 6, 2026 Fund Project: National Natural Science Foundation of China (81903672) Open source contentAbstract: Respiratory system diseases seriously endanger human health, and the analysis of their etiological mechanisms and the exploration of new drug targets have always been key areas of medical research. This article adopts Mendelian randomization (MR) and co localization analysis of proteomics, summarizes data using large-scale protein quantitative trait loci, evaluates the causal association between plasma proteins and 27 respiratory disease phenotypes, and conducts co localization analysis to control for confounding factors and potential biases of linkage disequilibrium. We used validation queue MR analysis and Mendelian randomization analysis (SMR) based on aggregated data to verify causal associations, and evaluated reverse causal associations through bidirectional MR and Steiger test. The results showed that MR analysis identified a total of 600 plasma protein disease phenotype associations, with 29 associations showing positive co localization analysis (PP4&gt;0.8) and 26 associations showing positive SMR analysis. This study identified significant associations between five proteins including NRX3A and chronic obstructive pulmonary disease, three proteins including IL7R and asthma, FUT3-FUT5 and idiopathic pulmonary fibrosis, and found causal associations between CSF3 and severe COVID-19, BTN2A1 and different subtypes of lung cancer. In summary, this study reveals various plasma proteins associated with respiratory system diseases, providing new directions for disease mechanism research and drug development. This open source content is a supplementary chart and explanation to the main body of the paper. 
description: Solemn statement: If this open source content is used in papers, books, academic reports, and other works, please cite the following references (the latest citation format is available in the original link): MA Xinqian, NI Wentao. Identification of Novel Protein Drug Targets for Respiratory Diseases by Integrating Human Plasma Proteome with Genome[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250796Authors: Ma Xinqian, Ni Wentao* Unit: Department of Respiratory and Critical Care Medicine, Peking University People's Hospital DOI：10.11999/JEIT250796 Original text: https://jeit.ac.cn/article/doi/10.11999/JEIT250796Corresponding author: Ni Wentao, wentao.qingdao@163.com Open source date: February 6, 2026 Fund Project: National Natural Science Foundation of China (81903672) Open source contentAbstract: Respiratory system diseases seriously endanger human health, and the analysis of their etiological mechanisms and the exploration of new drug targets have always been key areas of medical research. This article adopts Mendelian randomization (MR) and co localization analysis of proteomics, summarizes data using large-scale protein quantitative trait loci, evaluates the causal association between plasma proteins and 27 respiratory disease phenotypes, and conducts co localization analysis to control for confounding factors and potential biases of linkage disequilibrium. We used validation queue MR analysis and Mendelian randomization analysis (SMR) based on aggregated data to verify causal associations, and evaluated reverse causal associations through bidirectional MR and Steiger test. The results showed that MR analysis identified a total of 600 plasma protein disease phenotype associations, with 29 associations showing positive co localization analysis (PP4&gt;0.8) and 26 associations showing positive SMR analysis. This study identified significant associations between five proteins including NRX3A and chronic obstructive pulmonary disease, three proteins including IL7R and asthma, FUT3-FUT5 and idiopathic pulmonary fibrosis, and found causal associations between CSF3 and severe COVID-19, BTN2A1 and different subtypes of lung cancer. In summary, this study reveals various plasma proteins associated with respiratory system diseases, providing new directions for disease mechanism research and drug development. This open source content is a supplementary chart and explanation to the main body of the paper.