Li Yang, Zhu Weixi, Chen Yijing, Kang Qingqing, Zhang Ying, Yang Pan, Wang Shumin, Liu Chao, Zhang Yi, Zhang Qiu
Department of Endocrinology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
Sci Rep. 2025 Jun 6;15(1):19898. doi: 10.1038/s41598-025-04902-8.
Autoimmune thyroid diseases (AITD) are the most common autoimmune disorders. Identifying new biomarkers and therapeutic targets in plasma proteins is crucial. We conducted a proteome-wide Mendelian randomization (MR) and colocalization analysis to determine plasma proteins causally associated with AITD. Proteome-wide summary-level genome-wide association studies (GWAS) were collected from the UK Biobank Pharma Proteomics Project (UKB-PPP) and deCODE genetics, encompassing 2922 and 4719 plasma proteins, respectively. Genetic associations with AITD were derived from an AITD GWAS meta-analysis study (30,234 cases and 725,172 controls) and the FinnGen database (40,926 cases and 274,069 controls). MR analysis, including summary-data-based Mendelian randomization (SMR), Wald Ratio, and IVW methods, was employed to estimate the causal effects between plasma proteins and AITD. Colocalization analysis was used to assess whether identified proteins and AITD shared the common causal variants. Genetically predicted levels of 11 plasma proteins were found to have a causal association with AITD. Colocalization analysis revealed that five of these proteins had evidence of colocalization, including leukemia inhibitory factor (LIF), interleukin-7 receptor subunit alpha (IL7RA), CD226, tumor necrosis factor ligand superfamily member 11 (TNF11), and transcription factor junD (JUND). Genetically predicted levels of LIF and IL7RA were associated with an increased risk of AITD, whereas CD226, TNF11, and JUND were inversely related to AITD risk. This study has identified multiple candidate plasma proteins causally associated with AITD. Among these proteins, LIF, IL7RA, CD226, TNF11, and JUND are considered to have potential as disease biomarkers and therapeutic targets, but further clinical and experimental validation is still necessary in the future.
自身免疫性甲状腺疾病（AITD）是最常见的自身免疫性疾病。识别血浆蛋白中的新生物标志物和治疗靶点至关重要。我们进行了全蛋白质组孟德尔随机化（MR）和共定位分析，以确定与AITD有因果关系的血浆蛋白。全蛋白质组汇总水平的全基因组关联研究（GWAS）分别从英国生物银行药物蛋白质组计划（UKB-PPP）和 deCODE 遗传学公司收集，分别涵盖 2922 种和 4719 种血浆蛋白。与 AITD 的遗传关联来自一项 AITD GWAS 荟萃分析研究（30234 例病例和 725172 例对照）以及 FinnGen 数据库（40926 例病例和 274069 例对照）。采用 MR 分析，包括基于汇总数据的孟德尔随机化（SMR）、Wald 比率和 IVW 方法，来估计血浆蛋白与 AITD 之间的因果效应。共定位分析用于评估所识别的蛋白质和 AITD 是否共享共同的因果变异。发现 11 种血浆蛋白的遗传预测水平与 AITD 有因果关系。共定位分析表明，其中五种蛋白质有共定位证据，包括白血病抑制因子（LIF）、白细胞介素-7 受体亚基α（IL7RA）、CD226、肿瘤坏死因子配体超家族成员 11（TNF11）和转录因子 junD（JUND）。LIF 和 IL7RA 的遗传预测水平与 AITD 风险增加相关，而 CD226、TNF11 和 JUND 与 AITD 风险呈负相关。本研究已识别出多种与 AITD 有因果关系的候选血浆蛋白。在这些蛋白质中，LIF、IL7RA、CD226.TNF11 和 JUND 被认为有作为疾病生物标志物和治疗靶点的潜力，但未来仍需要进一步的临床和实验验证。
