• 中国核心期刊数据库收录期刊
  • 中文科技期刊数据库收录期刊
  • 中国期刊全文数据库收录期刊
  • 中国学术期刊综合评价数据库统计源期刊等

快速检索引用检索图表检索高级检索

临床医药

基于孟德尔随机化的代谢综合征及其组成部分与甲状腺疾病的因果关系探讨

  • 赵梁 ,
  • 李佳睿 ,
  • 赵博言 ,
  • 孙树德 ,
  • 杜丽坤
展开
  • 1.黑龙江中医药大学,黑龙江 哈尔滨 150040;
    2.黑龙江中医药大学附属第一医院,黑龙江 哈尔滨 150040
赵梁,男,在读硕士,研究方向:中医药治疗内分泌及代谢性疾病的研究

收稿日期: 2025-08-07

  修回日期: 2025-11-05

  录用日期: 2025-12-24

  网络出版日期: 2026-05-26

基金资助

哈尔滨市科技计划自筹经费项目(2023ZCZJNS108)

Exploration of the Causal Relationship between Metabolic Syndrome and Its Components and Thyroid Diseases Based on Mendelian Randomization

Expand
  • 1.Heilongjiang University of Chinese Medicine Heilongjiang Harbin 150040, China
    2.First Affiliated Hospital Heilongjiang University of Chinese Medicine Heilongjiang Harbin 150040, China

Received date: 2025-08-07

  Revised date: 2025-11-05

  Accepted date: 2025-12-24

  Online published: 2026-05-26

摘要

目的:采用孟德尔随机化(MR)分析,探讨代谢综合征(MetS)及其组成部分与常见甲状腺疾病之间的因果关联。方法:从欧洲人群公开的遗传变异汇总数据库,提取筛选MetS及其组成部分与甲状腺功能障碍性疾病相关的单核苷酸多态性信息作为遗传工具变量,以逆方差加权法(IVW)作为主要因果效应评估方法,MR-Egger 回归、加权中位数法和Weighted Mode 法等作为补充,用错误发现率(FDR)矫正结果,随后进行敏感性分析。若正向MR发现暴露与结局呈正相关,则进行反向MR分析。结果:经FDR纠正后,强关联结果显示:MetS是甲状腺癌(OR=1.5195%CI=1.11~2.05PFDR=0.039)、甲状腺功能减退症(OR=1.02 95%CI=1.01~1.02PFDR=4.80×10-9)和桥本甲状腺炎(OR=1.7295%CI=1.43~2.07PFDR=5.54×10-8)的危险因素;腰围是甲状腺功能减退症(OR=1.0295%CI=1.01~1.02PFDR=1.09×10-23)和桥本甲状腺炎(OR=1.5595%CI=1.35~1.78PFDR=4.80×10-9)的危险因素;高血压是桥本甲状腺炎(OR=2.6395%CI=1.85~3.73PFDR=3.59×10-7)的危险因素。反向MR分析结果均为阴性,敏感性分析证明结果稳健性。结论:MetS与甲状腺癌、甲状腺功能减退症和桥本甲状腺炎;腰围与甲状腺功能减退症和桥本甲状腺炎;高血压与桥本甲状腺炎均存在正向因果关联,评估MetS及其组成部分可以作为预防和诊断特定甲状腺功能障碍疾病的手段。


本文引用格式

赵梁 , 李佳睿 , 赵博言 , 孙树德 , 杜丽坤 .

基于孟德尔随机化的代谢综合征及其组成部分与甲状腺疾病的因果关系探讨

[J]. 中国医药导刊, 2026 , 28(4) : 431 -431-439 . DOI: 10.1009-0959.2026.010005

Abstract

Objective: This study utilized Mendelian randomization MR analysis to investigate the causal relationships between Metabolic syndrome MetS and its individual components and common thyroid diseases.Methods: Genetic instrumental variables were selected based on single nucleotide polymorphisms SNPs associated with MetS its components and thyroid dysfunction extracted from publicly available genome-wide association study GWAS summary datasets of European ancestry populations. The inverse-variance weighted IVW method was employed as the primary analytical approach to estimate causal effects supplemented by MR-Egger regression weighted median and weighted mode methods. False discovery rate FDR correction was applied to account for multiple testing followed by comprehensive sensitivity analyses to assess the validity of instrumental variables and the robustness of results. In cases where a significant forward association was observed reverse MR analyses were conducted to evaluate bidirectional causality.Results: Following FDR correction robust associations indicated that MetS was causally associated with an increased risk of thyroid cancer OR=1.51 95%CI=1.11-2.05PFDR=0.039), hypothyroidism OR=1.02 95%CI=1.01-1.02PFDR=4.80×10-9), and Hashimoto's thyroiditis OR=1.72 95%CI=1.43-2.07PFDR=5.54×10-8. Additionally elevated waist circumference was identified as a causal risk factor for hypothyroidism OR=1.02 95%CI=1.01-1.02PFDR=1.09×10-23 and Hashimoto's thyroiditis OR=1.55 95%CI=1.35-1.78PFDR=4.80×10-9), while hypertension was significantly associated with an increased risk of Hashimoto's thyroiditis OR=2.63 95%CI=1.85-3.73PFDR=3.59×10-7. Reverse MR analyses yielded no significant associations supporting the directionality of the observed effects. Sensitivity analyses confirmed the reliability and robustness of the findings with no evidence of substantial pleiotropy or bias.Conclusion: This study provides evidence of positive causal associations between MetS and thyroid cancer hypothyroidism and Hashimoto's thyroiditis between waist circumference and both hypothyroidism and Hashimoto's thyroiditis and between hypertension and Hashimoto's thyroiditis. These findings suggest that monitoring MetS and its constituent components may serve as a valuable strategy for the early identification and prevention of specific thyroid disorders.


参考文献

    [1 Lin Z Sun L. Research advances in the therapy of metabolic syndromeJ.Front Pharmacol2024151364881.

         2  Grundy SM Cleeman JI Daniels SR et al. Diagnosis and management of the metabolic syndrome an American Heart Association/National Heart Lung and Blood Institute Scientific StatementJ.Circulation 200511217):2735-2752.

         3  Noubiap JJ Nansseu JR Lontchi-Yimagou E et al. Geographic distribution of metabolic syndrome and its components in the general adult population a meta-analysis of global data from 28 million individualsJ.Diabetes Res Clin Pract 2022188109924.

         4  Chong B Kong G Shankar K et al. The global syndemic of metabolic diseases in the young adult population a consortium of trends and projections from the global burden of disease 2000-2019J.Metabolism 2023141155402.

         5  Verma DP Chaudhary SC Singh A et al. Hypothyroidism in metabolic syndromeJ.Ann Afr Med2024234):717-722.

         6  Kim HJ Park SJ Park HK et al. Thyroid autoimmunity and metabolic syndrome a nationwide population-based studyJ.Eur J Endocrinol. 20211855):707-715.

         7  Raposo L Martins S Ferreira D et al. Metabolic syndrome thyroid function and autoimmunity - the PORMETS studyJ.Endocr Metab Immune Disord Drug Targets. 2019191):75-83.

         8  Pingitore A Gaggini M Mastorci F et al. Metabolic syndrome thyroid dysfunction and cardiovascular risk the triptych of evilJ.Int J Mol Sci 20242519):10628.

         9  Skrivankova VW Richmond RC Woolf BAR et al. Strengthening the reporting of observational studies in epidemiology using mendelian randomization the STROBE-MR statementJ.JAMA 202132616):1614-1621.

         10 Davey Smith G Ebrahim S. What can Mendelian randomisation tell us about modifiable behavioural and environmental exposures?[J.BMJ 20053307499):1076-1079.

         11 Gagliano Taliun SA Evans DM. Ten simple rules for conducting a mendelian randomization studyJ.PLoS Comput Biol 2021178):e1009238.

         12 Glickman ME Rao SR Schultz MR. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studiesJ.J Clin Epidemiol 2014678):850-857.

         13 van Walree ES Jansen IE Bell NY et al. Disentangling genetic risks for metabolic syndromeJ.Diabetes20227111):2447-2457.

         14 Chen J Spracklen CN Marenne G et al. The trans-ancestral genomic architecture of glycemic traitsJ.Nat Genet 2021536):840-860.

         15 Kurki MI Karjalainen J Palta P et al. FinnGen provides genetic insights from a well-phenotyped isolated populationJ.Nature 20236137944):508-518.

         16 Cerezo M Sollis E Ji Y et al. The NHGRI-EBI GWAS Catalog standards for reusability sustainability and diversityJ.Nucleic Acids Res 202553D1):D998-D1005.

         17 Hemani G Tilling K Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary dataJ.PLoS Genet 20171311):e1007081.

         18 Burgess S Bowden J Fall T et al. Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variantsJ.Epidemiology 2017281):30-42.

         19 Bowden J Davey Smith G Burgess S. Mendelian randomization with invalid instruments effect estimation and bias detection through Egger regressionJ.Int J Epidemiol 2015442):512-525.

         20 Bowden J Davey Smith G Haycock PC et al. Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimatorJ.Genet Epidemiol 2016404):304-314.

         21 Hartwig FP Davey Smith G Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumptionJ.Int J Epidemiol 2017466):1985-1998.

         22 Zhu J Zhou D Wang J et al. Frailty and cardiometabolic diseases a bidirectional Mendelian randomisation studyJ.Age Ageing 20225111):256.

         23 Verbanck M Chen CY Neale B et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseasesJ.Nat Genet 2018508):1196.

         24 Bowden J. Improving the visualization interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regressionJ.Int J Epidemiol 2018474):1264-1278.

         25 Taylor PN Albrecht D Scholz A et al. Global epidemiology of hyperthyroidism and hypothyroidismJ.Nat Rev Endocrinol 2018145):301-316.

         26 Tan H Wang S Huang F et al. Association between breast cancer and thyroid cancer risk a two-sample Mendelian randomization studyJ.Front Endocrinol Lausanne), 2023141138149.

         27 Islam MS Wei P Suzauddula M et al. The interplay of factors in metabolic syndrome understanding its roots and complexityJ.Mol Med 2024301):279.

         28 He J Lai Y Yang J et al. The relationship between thyroid function and metabolic syndrome and its components a cross-sectional study in a Chinese populationJ.Front Endocrinol Lausanne), 202112661160.

         29 Esposito K Chiodini P Colao A et al. Metabolic syndrome and risk of cancer a systematic review and meta-analysisJ.Diabetes Care 20123511):2402-2411.

         30 Lee JS Cho SI Park HS. Metabolic syndrome and cancer-related mortality among Korean men and womenJ.Ann Oncol 2010213):640-645.

         31 Park JH Choi M Kim JH et al. Metabolic syndrome and the risk of thyroid cancer a nationwide population-based cohort studyJ.Thyroid 20203010):1496-1504.

         32 Grimm D. Recent advances in thyroid cancer researchJ.Int J Mol Sci 2022239):4631.

         33 Vella V Malaguarnera R. The emerging role of insulin receptor isoforms in thyroid cancer clinical implications and new perspectivesJ.Int J Mol Sci 20181912):3814.

         34 Zhou Y Yang Y Zhou T et al. Adiponectin and thyroid cancer insight into the association between adiponectin and obesityJ.Aging Dis 2021122):597-613.

         35 Kitahara CM Sosa JA Shiels MS. Influence of nomenclature changes on trends in papillary thyroid cancer incidence in the United States 2000 to 2017J.J Clin Endocrinol Metab 202010512):e4823-e4830.

         36 Chaker L Bianco AC Jonklaas J et al. HypothyroidismJ.Lancet 201739010101):1550-1562.

         37 Brenta G. Why can insulin resistance be a natural consequence of thyroid dysfunction?[J.J Thyroid Res 20112011152850.

         38 Vyakaranam S Vanaparthy S Nori S et al. Study of insulin resistance in subclinical hypothyroidismJ.Int J Health Sci Res 201449):147-153.

         39 Völzke H Alte D Dörr M et al. The association between subclinical hyperthyroidism and blood pressure in a population-based studyJ.J Hypertens 20062410):1947-1953.

         40 Duntas LH Orgiazzi J Brabant G. The interface between thyroid and diabetes mellitusJ.Clin Endocrinol Oxf), 2011751):1-9.

         41 Ralli M Angeletti D Fiore M et al. Hashimoto's thyroiditis an update on pathogenic mechanisms diagnostic protocols therapeutic strategies and potential malignant transformationJ.Autoimmun Rev 20201910):102649.

         42 Ragusa F Fallahi P Elia G et al. Hashimotos' thyroiditis epidemiology pathogenesis clinic and therapyJ.Best Pract Res Clin Endocrinol Metab 2019336):101367.

         43 Pyzik A Grywalska E Matyjaszek-Matuszek B et al. Immune disorders in Hashimoto's thyroiditis what do we know so far?[J.J Immunol Res 20152015979167.

         44 Marzullo P Minocci A Tagliaferri MA et al. Investigations of thyroid hormones and antibodies in obesity leptin levels are associated with thyroid autoimmunity independent of bioanthropometric hormonal and weight-related determinantsJ.J Clin Endocrinol Metab 2010958):3965-3972.

         45 Cui B Chen A Xu C et al. Causal relationship between antihypertensive drugs and Hashimoto's thyroiditis a drug-target Mendelian randomization studyJ.Front Endocrinol Lausanne), 2024151419346.

文章导航

/