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Article(id=1241023934477423183, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202409005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1725120000000, receivedDateStr=2024-09-01, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812763089, onlineDateStr=2026-03-18, pubDate=1739116800000, pubDateStr=2025-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812763089, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812763089, creator=13701087609, updateTime=1773812763089, updator=13701087609, issue=Issue{id=1241023927812682133, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='3', pageStart='385', pageEnd='576', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812761500, creator=13701087609, updateTime=1773812858867, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024336258200259, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024336258200260, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=418, endPage=423, ext={EN=ArticleExt(id=1241023935278535267, articleId=1241023934477423183, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Increased uric acid and the risk of hepatic steatosis and non-alcoholic fatty liver disease based on NHANES and Mendelian randomization studies, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the relationship between uric acid and the risk of hepatic steatosis and non-alcoholic fatty liver disease (NAFLD), providing new insights for the prevention of NAFLD.

Methods

Utilizing data from the 2017-2018 NHANES population and summary data from genome-wide association studies (GWAS), the association between uric acid and the risk of hepatic steatosis and NAFLD was analyzed using restricted cubic spline models, generalized linear models, and binary logistic regression models. The inverse variance weighted method was employed as the primary approach for Mendelian randomization (MR) analysis to assess the causal relationship between uric acid and NAFLD. Additional verification of results was conducted using MR Egger regression, weighted median methods, simple models, and weighted models, followed by sensitivity testing.

Results

After adjusting for all covariates, a linear relationship was observed between uric acid and the risks of hepatic steatosis and NAFLD (Pnon-linear > 0.05). Populations with higher uric acid levels exhibited increased risks of hepatic steatosis (β=3.559,95%CI: 1.722-5.395, P < 0.001) and NAFLD (OR=1.151, 95%CI: 1.048-1.265, P=0.003). The MR analysis using the inverse variance weighted method indicated a causal relationship between uric acid and NAFLD (OR=1.68, 95%CI: 1.01-2.81, P=0.049),with the other four analytical methods providing similar directional causal inferences. Sensitivity tests suggested no significant heterogeneity or horizontal pleiotropy among instrumental variables (P > 0.05), and the results were not influenced by individual genetic variations.

Conclusion

Uric acid is positively linearly correlated with the risk of hepatic steatosis and NAFLD, indicating that controlling uric acid levels may play a crucial role in the prevention and management of NAFLD.

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目的

探讨尿酸与肝脏脂肪变性及非酒精性脂肪性肝病（NAFLD）风险之间的关系，为NAFLD的预防提供新思路。

方法

基于2017-2018年NHANES人群数据及全基因组关联研究汇总数据（GWAS），采用限制性立方样条模型、广义线性模型、二元logistic回归模型分析尿酸与肝脏脂肪变性及NAFLD风险的关联，运用逆方差加权法作为孟德尔随机化（MR）分析的主要方法，评估尿酸与NAFLD之间的因果关系，MR Egger回归法、加权中位数法、简单模型和加权模型对结果进行补充验证，随后进行敏感性检验。

结果

在调整所有协变量后，尿酸与肝脏脂肪变性及NAFLD风险均呈线性关系（Pnon-linear>0.05）,且较高尿酸水平的人群，肝脏脂肪变性（β=3.559,95%CI:1.722～5.395,P<0.001）及NAFLD风险（OR=1.151,95%CI:1.048～1.265, P=0.003）更高。MR分析逆方差加权法显示，尿酸与NAFLD之间存在因果关系（OR=1.68,95%CI:1.01～2.81,P=0.049）,其它四种分析方法提供相同方向的因果推断。敏感性检验提示工具变量间无明显异质性及水平多效性（P>0.05），且结果不受单个遗传变异的影响。

结论

尿酸与肝脏脂肪变性及NAFLD风险呈正线性相关，控制尿酸水平可能在预防和管理NAFLD中发挥重要作用。

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陈思，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=sufmSrGp2XsuyExb+KT8cQ==, magXml=5WgIfqhEITAqJaCdKoIFCQ==, pdfUrl=null, pdf=mDg+d0oFdIX4PNL+vV+UzQ==, pdfFileSize=1054715, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=R9Fd/95ajk7jlCgnesz0Kg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=g7MYuSrMychA9EzX2VGz6Q==, mapNumber=null, authorCompany=null, fund=null, authors=

谭杰（1987—），男，硕士在读，主治医师，研究方向：胃肠道及肝脏疾病

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谭杰（1987—），男，硕士在读，主治医师，研究方向：胃肠道及肝脏疾病

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Journal of Clinical Endocrinology &Metabolism, 2022, 107(8): e3497-e3503., articleTitle=Serum uric acid levels and nonalcoholic fatty liver disease: a 2-Sample bidirectional mendelian randomization study, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1241023938076136262, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, xref=1., ext=[AuthorCompanyExt(id=1241023938088719175, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, companyId=1241023938076136262, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Gastroenterology, First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital), Hefei, Anhui 230001, China), AuthorCompanyExt(id=1241023938097107784, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, companyId=1241023938076136262, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国科学技术大学附属第一医院（安徽省立医院）消化内科，安徽 合肥 230001)]), AuthorCompany(id=1241023939477033810, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, xref=2., ext=[AuthorCompanyExt(id=1241023939514782551, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, companyId=1241023939477033810, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.安徽理工大学医学院)])], figs=[ArticleFig(id=1241023942060724294, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=EN, label=Figure 1, caption=Flowchart for the screening of research subjects, figureFileSmall=4oNmk4y6QGt/0b/SAtYv9w==, figureFileBig=R9Fd/95ajk7jlCgnesz0Kg==, tableContent=null), ArticleFig(id=1241023942169776211, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=CN, label=图1, caption=研究对象筛选流程图, figureFileSmall=4oNmk4y6QGt/0b/SAtYv9w==, figureFileBig=R9Fd/95ajk7jlCgnesz0Kg==, tableContent=null), ArticleFig(id=1241023942400462953, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=EN, label=Figure 2, caption=Study protocol for MR analysis, figureFileSmall=h8qd8yLZap1w+50RJUCN/g==, figureFileBig=bPJGX0LTEV3s7T9vLXYK6w==, tableContent=null), ArticleFig(id=1241023943482593397, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=CN, label=图2, caption=MR分析的研究方案, figureFileSmall=h8qd8yLZap1w+50RJUCN/g==, figureFileBig=bPJGX0LTEV3s7T9vLXYK6w==, tableContent=null), ArticleFig(id=1241023943591645311, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=EN, label=Figure 3, caption=RCS plot between uric acid and CAP and NAFLD, figureFileSmall=gWlyLjsc/ltWN17584rE2g==, figureFileBig=9aA7RW+M6r4CXxQ5d9D6Jg==, tableContent=null), ArticleFig(id=1241023943688114313, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=CN, label=图3, caption=尿酸与CAP及NAFLD风险之间RCS曲线

注：图A调整所有协变量后尿酸与CAP的RCS曲线；图B调整所有协变量后尿酸与NAFLD风险RCS曲线。

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Specific information on MR analysis data

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露与结局数据来源GWAS ID种族样本数纳入SNPs
尿酸EBIebi-a-GCST90018977欧洲343 83655
NAFLDFinnGenfinn-b-NAFLD欧洲2 179 792—
), ArticleFig(id=1241023944724107481, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=CN, label=表1, caption=

MR分析数据具体信息

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露与结局数据来源GWAS ID种族样本数纳入SNPs
尿酸EBIebi-a-GCST90018977欧洲343 83655
NAFLDFinnGenfinn-b-NAFLD欧洲2 179 792—
), ArticleFig(id=1241023944900268262, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=EN, label=Table 2, caption=

Baseline characteristics of study subjects ［n（%），M（P25，P75）］

, figureFileSmall=null, figureFileBig=null, tableContent=
因素对照组（n=1 107）NAFLD组（n=624）统计量P值
性别7.6740.014
男450（40.7）332（53.2）
女657（59.3）292（46.8）
年龄（岁）48（33,62）55（43,66）6.679<0.001
种族3.1790.038
墨西哥裔美国人107（9.7）91（14.6）
其他西班牙裔104（9.4）54（8.7）
非西班牙裔白人377（34.1）242（38.8）
非西班牙裔黑人288（26.0）128（20.5）
其他种族231（20.8）109（17.4）
教育水平4.0670.029
高中毕业/同等学历或以下339（30.6）218（34.9）
部分大学教育或副学士学位372（33.6）238（38.1）
大学本科或以上396（35.8）167（18.6）
家庭年收入与贫困比2.9（1.6,5.0）2.7（1.6,4.7）-1.2390.236
体力活动（d/wk）3.0（2.0,5.0）3.0（2.0,5.0）-0.9620.352
吸烟状态0.0890.884
每天111（10.0）61（9.8）
有时32（2.9）17（2.7）
否250（22.6）187（30.0）
高血压病史75.798<0.001
有285（25.7）287（46.0）
无822（74.3）337（54.0）
糖尿病病史82.103<0.001
有76（6.9）150（24.0）
无1003（90.6）446（71.5）
CAP中位数（dB/m）233.0（202.0，258.0）321.5（301.0,350.0）69.136<0.001
BMI（kg/m2）26.4(23.3，30.3)32.4(28.3，37.05)11.707<0.001
尿酸（mg/L）50.0(41.0，59.0)57.0（49.0，68.0）5.666<0.001
ALT（U/L）16.0（12.0，21.0）22.0（16.0，31.0）10.38<0.001
AST（U/L）18.0（16.0，22.0）20.0（17.0，25.0）2.8880.012
ALP（IU/L）69.0（58.0，84.0）77.0（64.0，92.3）4.827<0.001
ALB（g/L）44.0（39.0，43.0）41.0（38.0，43.0）-2.1660.048
GGT（IU/L）18.0（13.0，26.0）27.0（19.0，41.0）12.523<0.001
TC（mmol/L）4.8（4.2，5.5）4.9（4.2，5.7）0.3240.750
HDL（mmol/L）1.5（1.2，1.7）1.2（1.0，1.5）-9.779<0.001
HbA1c（%）5.5（5.2，5.7）5.8（5.4，6.4）12.781<0.001
GIU(mmol/L)5.7（5.3，6.1）6.1（5.6，6.9）9.415<0.001
LDL（mmol/L）2.8（2.3，3.5）3.1（2.4，3.7）2.3150.036
TG（mmol/L）0.9（0.6，1.7）1.2（0.8，1.7）6.081<0.001
), ArticleFig(id=1241023945017708779, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=CN, label=表2, caption=

研究对象基线特征［n（%），M（P25，P75）］

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因素对照组（n=1 107）NAFLD组（n=624）统计量P值
性别7.6740.014
男450（40.7）332（53.2）
女657（59.3）292（46.8）
年龄（岁）48（33,62）55（43,66）6.679<0.001
种族3.1790.038
墨西哥裔美国人107（9.7）91（14.6）
其他西班牙裔104（9.4）54（8.7）
非西班牙裔白人377（34.1）242（38.8）
非西班牙裔黑人288（26.0）128（20.5）
其他种族231（20.8）109（17.4）
教育水平4.0670.029
高中毕业/同等学历或以下339（30.6）218（34.9）
部分大学教育或副学士学位372（33.6）238（38.1）
大学本科或以上396（35.8）167（18.6）
家庭年收入与贫困比2.9（1.6,5.0）2.7（1.6,4.7）-1.2390.236
体力活动（d/wk）3.0（2.0,5.0）3.0（2.0,5.0）-0.9620.352
吸烟状态0.0890.884
每天111（10.0）61（9.8）
有时32（2.9）17（2.7）
否250（22.6）187（30.0）
高血压病史75.798<0.001
有285（25.7）287（46.0）
无822（74.3）337（54.0）
糖尿病病史82.103<0.001
有76（6.9）150（24.0）
无1003（90.6）446（71.5）
CAP中位数（dB/m）233.0（202.0，258.0）321.5（301.0,350.0）69.136<0.001
BMI（kg/m2）26.4(23.3，30.3)32.4(28.3，37.05)11.707<0.001
尿酸（mg/L）50.0(41.0，59.0)57.0（49.0，68.0）5.666<0.001
ALT（U/L）16.0（12.0，21.0）22.0（16.0，31.0）10.38<0.001
AST（U/L）18.0（16.0，22.0）20.0（17.0，25.0）2.8880.012
ALP（IU/L）69.0（58.0，84.0）77.0（64.0，92.3）4.827<0.001
ALB（g/L）44.0（39.0，43.0）41.0（38.0，43.0）-2.1660.048
GGT（IU/L）18.0（13.0，26.0）27.0（19.0，41.0）12.523<0.001
TC（mmol/L）4.8（4.2，5.5）4.9（4.2，5.7）0.3240.750
HDL（mmol/L）1.5（1.2，1.7）1.2（1.0，1.5）-9.779<0.001
HbA1c（%）5.5（5.2，5.7）5.8（5.4，6.4）12.781<0.001
GIU(mmol/L)5.7（5.3，6.1）6.1（5.6，6.9）9.415<0.001
LDL（mmol/L）2.8（2.3，3.5）3.1（2.4，3.7）2.3150.036
TG（mmol/L）0.9（0.6，1.7）1.2（0.8，1.7）6.081<0.001
), ArticleFig(id=1241023945130954997, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=EN, label=Table 3, caption=

Regression analysis of the relationship between uric acid and CAP and NAFLD

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因素CAP（dB/m）NAFLD
P值β（95%CI）P值OR（95%CI）
尿酸模型1<0.00112.706（10.897～14.515）<0.0011.425（1.330～1.530）
模型2<0.00111.536（9.547～13.524）<0.0011.410（1.302～1.529）
模型3<0.0013.559（1.722～5.395）0.0031.151（1.048～1.265）
), ArticleFig(id=1241023945235812604, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934477423183, language=CN, label=表3, caption=

尿酸与CAP及NAFLD风险关系回归分析

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因素CAP（dB/m）NAFLD
P值β（95%CI）P值OR（95%CI）
尿酸模型1<0.00112.706（10.897～14.515）<0.0011.425（1.330～1.530）
模型2<0.00111.536（9.547～13.524）<0.0011.410（1.302～1.529）
模型3<0.0013.559（1.722～5.395）0.0031.151（1.048～1.265）
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尿酸增加肝脏脂肪变性及非酒精性脂肪性肝病风险——基于NHANES及孟德尔随机化研究
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谭杰 1 , 曹玉萍 2 , 陈思 1
现代预防医学 | 流行病与统计方法 2025,52(3): 418-423
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现代预防医学 | 流行病与统计方法 2025, 52(3): 418-423
尿酸增加肝脏脂肪变性及非酒精性脂肪性肝病风险——基于NHANES及孟德尔随机化研究
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谭杰1, 曹玉萍2, 陈思1
作者信息
  • 1.中国科学技术大学附属第一医院（安徽省立医院）消化内科，安徽 合肥 230001
  • 2.安徽理工大学医学院

    • 谭杰（1987—），男，硕士在读，主治医师，研究方向：胃肠道及肝脏疾病

通讯作者:

陈思，E-mail:
Increased uric acid and the risk of hepatic steatosis and non-alcoholic fatty liver disease based on NHANES and Mendelian randomization studies
Jie TAN1, Yu-ping CAO2, Si CHEN1
Affiliations
  • Department of Gastroenterology, First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital), Hefei, Anhui 230001, China
出版时间: 2025-02-10 doi: 10.20043/j.cnki.MPM.202409005
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摘要
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目的

探讨尿酸与肝脏脂肪变性及非酒精性脂肪性肝病（NAFLD）风险之间的关系，为NAFLD的预防提供新思路。

方法

基于2017-2018年NHANES人群数据及全基因组关联研究汇总数据（GWAS），采用限制性立方样条模型、广义线性模型、二元logistic回归模型分析尿酸与肝脏脂肪变性及NAFLD风险的关联，运用逆方差加权法作为孟德尔随机化（MR）分析的主要方法，评估尿酸与NAFLD之间的因果关系，MR Egger回归法、加权中位数法、简单模型和加权模型对结果进行补充验证，随后进行敏感性检验。

结果

在调整所有协变量后，尿酸与肝脏脂肪变性及NAFLD风险均呈线性关系（Pnon-linear>0.05）,且较高尿酸水平的人群，肝脏脂肪变性（β=3.559,95%CI:1.722～5.395,P<0.001）及NAFLD风险（OR=1.151,95%CI:1.048～1.265, P=0.003）更高。MR分析逆方差加权法显示，尿酸与NAFLD之间存在因果关系（OR=1.68,95%CI:1.01～2.81,P=0.049）,其它四种分析方法提供相同方向的因果推断。敏感性检验提示工具变量间无明显异质性及水平多效性（P>0.05），且结果不受单个遗传变异的影响。

结论

尿酸与肝脏脂肪变性及NAFLD风险呈正线性相关，控制尿酸水平可能在预防和管理NAFLD中发挥重要作用。

尿酸  /  非酒精性脂肪性肝病  /  NHANES  /  孟德尔随机化  /  因果推断
Objective

To explore the relationship between uric acid and the risk of hepatic steatosis and non-alcoholic fatty liver disease (NAFLD), providing new insights for the prevention of NAFLD.

Methods

Utilizing data from the 2017-2018 NHANES population and summary data from genome-wide association studies (GWAS), the association between uric acid and the risk of hepatic steatosis and NAFLD was analyzed using restricted cubic spline models, generalized linear models, and binary logistic regression models. The inverse variance weighted method was employed as the primary approach for Mendelian randomization (MR) analysis to assess the causal relationship between uric acid and NAFLD. Additional verification of results was conducted using MR Egger regression, weighted median methods, simple models, and weighted models, followed by sensitivity testing.

Results

After adjusting for all covariates, a linear relationship was observed between uric acid and the risks of hepatic steatosis and NAFLD (Pnon-linear > 0.05). Populations with higher uric acid levels exhibited increased risks of hepatic steatosis (β=3.559,95%CI: 1.722-5.395, P < 0.001) and NAFLD (OR=1.151, 95%CI: 1.048-1.265, P=0.003). The MR analysis using the inverse variance weighted method indicated a causal relationship between uric acid and NAFLD (OR=1.68, 95%CI: 1.01-2.81, P=0.049),with the other four analytical methods providing similar directional causal inferences. Sensitivity tests suggested no significant heterogeneity or horizontal pleiotropy among instrumental variables (P > 0.05), and the results were not influenced by individual genetic variations.

Conclusion

Uric acid is positively linearly correlated with the risk of hepatic steatosis and NAFLD, indicating that controlling uric acid levels may play a crucial role in the prevention and management of NAFLD.

Uric acid  /  Non-alcoholic fatty liver disease  /  NHANES  /  Mendelian randomization  /  Causal inference
谭杰, 曹玉萍, 陈思. 尿酸增加肝脏脂肪变性及非酒精性脂肪性肝病风险——基于NHANES及孟德尔随机化研究. 现代预防医学, 2025 , 52 (3) : 418 -423 . DOI: 10.20043/j.cnki.MPM.202409005
Jie TAN, Yu-ping CAO, Si CHEN. Increased uric acid and the risk of hepatic steatosis and non-alcoholic fatty liver disease based on NHANES and Mendelian randomization studies[J]. Modern Preventive Medicine, 2025 , 52 (3) : 418 -423 . DOI: 10.20043/j.cnki.MPM.202409005
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非酒精性脂肪性肝病（non-alcoholic fatty liver disease，NAFLD）是全球最常见的慢性肝病，其患病率逐年上升。截至2020年，NAFLD全球患病率约25%[1]，低于10%的患者在诊断后10～20年内发展为肝硬化和肝癌[2]，虽然改变生活方式对改善NAFLD效果显著，但难以长期保持，而且目前没有被批准用于治疗NAFLD的药物[3]。故关注NAFLD潜在的风险因素，对于NAFLD的预防及控制尤为重要。
尿酸是嘌呤代谢的终产物，在健康和疾病中作用复杂，因为它即是抗氧化剂又是促氧化剂[4]，在肝脏中，尿酸可以通过炎症反应、氧化应激、线粒体应激导致肝脏脂肪变性[5]，同时也能通过清除活性氧发挥抗氧化作用[6]，故尿酸与NAFLD的关系仍未定论。高尿酸血症和NAFLD作为代谢综合征的表现形式，通常伴有肥胖、血脂异常和胰岛素抵抗。由于混杂因素及中介效应的影响，很难获得尿酸与NAFLD之间独立关联的证据。
本研究基于美国国家健康和营养调查（National Health and Nutrition Examination Survey，NHANES）人群数据开展观察性研究，并通过孟德尔随机化（Mendelian randomization，MR）方法在基因层面评估尿酸与NAFLD的因果关联。NHANES是一项针对美国成人及儿童的横断面调查，涵盖多种健康及营养指标。MR分析是使用遗传变异作为工具变量，调查临床特征与疾病之间因果关系的流行病学统计方法，由于遗传等位基因在减数分裂过程中随机分配，不受环境影响，因此MR分析能有效控制混杂因素和反向因果关系[7]。
1　对象与方法
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1.1　研究对象
本研究选取NHANES 2017-2018周期数据，年龄≥20岁、完成肝脏弹性检测、具有受控衰减参数（controlled attenuation parameter，CAP）值、具有血清尿酸值的4 210例个体作为研究对象。排除标准：（1）大量饮酒（男性>2杯/d或女性>1杯/d）或缺失饮酒信息[8]；（2）感染乙型或丙型肝炎；（3）过去1个月口服影响尿酸药物（别嘌呤醇、非布司他、苯溴马隆、氢氯噻嗪），口服致肝脂肪变性药物（甲氨蝶呤、胺碘酮、他莫昔芬）至少3个月。最终共有1 731名个体纳入研究。CAP值与肝脂肪变性程度呈正相关，CAP大于285 dB/m作为NAFLD状态的标准，该值因较高的灵敏度和特异性，已用于检测美国人群的肝脂肪变性[9]。参考以上标准，研究个体分为对照组及NAFLD组，流程见图1。NHANES研究方案由美国国家卫生统计中心研究伦理审查委员会授权，研究程序符合《赫尔辛基宣言》的要求，已获得所有NHANES参与者的知情同意。
1.2　资料收集
参与者的资料由数据库中问卷调查、人口统计学数据、检查及实验室数据得到。
1.3　MR数据信息及研究设计
本研究使用单核苷酸多态性（single nucleotide polymorphism，SNP）作为工具变量。尿酸与NAFLD遗传数据均来自IEU开放GWAS项目平台（IEU OpenGWAS project (mrcieu.ac.uk)），数据具体信息见表1。MR分析须满足三个条件[10]，条件1：工具变量与暴露强相关；条件2：工具变量不能通过混杂因素影响结局；条件3：工具变量必须仅通过暴露因素，而不是其他途径影响结局。研究方案见图2。
1.4　工具变量的筛选
提取暴露数据时，强相关显著水平设置为P<5×10-10，连锁不平衡（linkage disequilibrium，LD）设置为R2<0.001，KB=10 000kb。剔除统计量F<10的弱工具变量。共获得194个有效SNPs。使用Ldtrait Tool（https://ldlink.nih.gov/）检查并排除137个与混杂因素高血压、糖尿病、血脂异常、肥胖、BMI、抽烟、腰围[11-12]相关的SNPs，在提取结局数据时，使用代理SNPs（rs79896211、rs1967551、rs79464364）替代了缺失的3个SNPs。同时，排除了2个具有回文结构的SNPs（rs12510175、rs7039），最终获得55个SNPs用于后续分析。
1.5　统计分析
按照NHANES提供的权重对2017-2018年数据重新加权，分类变量使用χ2检验，数值变量使用Mann-Whitney U检验，分别以n（%）及中位数（四分位间距）描述。使用限制性立方样条（restricted cubic spline，RCS）模型、广义线性回归及二元logistic回归模型评估尿酸与肝脏脂肪变性及NAFLD风险之间的关系。建立以下3个模型逐步调整协变量：模型1未调整；模型2调整性别、年龄、种族、教育水平；模型3调整性别、年龄、种族、教育水平、高血压、糖尿病病史、高密度脂蛋白、低密度脂蛋白、甘油三酯、空腹血糖、体质指数（BMI）。采用“多重插补法”处理缺失的非正态分布数据，此方法可减少偏差并提高统计效能[13]。使用R 4.4.0进行统计分析，结果以回归系数β或比值比［OR，95%置信区间（CI）］表示，检验水准α=0.05。逆方差加权法作为MR分析主要方法，MR Egger回归法、加权中位数法、简单模型和加权模型作为补充分析[14]。使用Cochran Q检验、MR Egger截距测试检验异质性和水平多效性，采用孟德尔随机多态性残差和离群值（Mendelian randomization pleiotropy residual sum and outlier, MR-PRESSO）全局检验进一步检验和校正水平多效性。通过留一法评估每个SNP对结果的影响。
2　结果
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2.1　研究对象基线特征
与对照组相比，NAFLD组人群主要为男性、年龄较大、非西班牙裔白人，具有高血压和糖尿病病史，且CAP中位数、尿酸、BMI、谷丙转氨酶（ALT）、谷草转氨酶（AST）、碱性磷酸酶（ALP）、白蛋白（ALB）、谷氨酰转肽酶（GGT）、低密度脂蛋白（LDL）、甘油三酯（TG）、空腹血糖（GLU）、糖化血红蛋白（HbA1c）均显著升高，而高密度脂蛋白（HDL）则显著低于对照组。见表2。
2.2　RCS模型分析
在调整所有协变量后，尿酸与CAP及NAFLD风险均呈线性剂量反应关系，尿酸的非线性效应对CAP（P=0.911）及NAFLD风险无显著影响（P=0.915）。见图3。
2.3　广义线性回归及二元logistic回归分析
尿酸与CAP在模型1（β=12.706，95%CI:10.897～14.515，P<0.001）、模型2（β=11.536, 95%CI:9.547～13.524, P<0.001）和模型3（β=3.559，95%CI:1.722～5.395，P<0.001）中均显著正相关。尿酸与NAFLD风险在3个模型中也显著相关，在调整所有协变量后，尿酸每升高10mg/L，NAFLD风险增加15.1%（OR=1.151，95%CI:1.048～1.265，P=0.003）。见表3。
2.4　MR分析及敏感性检验
逆方差加权法显示，尿酸与NAFLD之间存在因果关系（OR=1.68,95%CI:1.01～2.81,P=0.049），其它四种补充方法提供相同方向的因果推断，进一步验证了结果的可靠，见图4、5。敏感性检验显示，Cochran Q检验（Cochran Q=47.982，P=0.704）未发现工具变量间显著异质性。MR Egger截距测试（P=0.598）、MR-PRESSO全局检验（P=0.709）也未检测到水平多效性。在留一法中，剔除任意一个SNP后，剩余SNPs均位于无效线右侧，且与总效应区间接近，提示结果不依赖单个遗传变异的影响，见图6。
3　讨论
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本研究利用NHANES人群数据进行观察性研究，并结合MR分析方法，发现尿酸与肝脏脂肪变性及NAFLD风险之间的正线性关系，为尿酸作为NAFLD风险因素提供了新的证据。
NAFLD是一类临床病理综合征，病理表现为无大量饮酒的情况下，肝实质细胞脂质沉积及肝小叶炎症，NAFLD包括单纯性脂肪肝和非酒精性脂肪性肝炎（NASH）两个病理阶段，并可能进一步发展为肝硬化及肝细胞癌[15]。尽管针对NAFLD的药物治疗正在研究中，但临床上仍未取得显著突破。同时，美国肝病研究协会的指南建议将药物限制用于NASH和伴随纤维化的患者[16]，这为早期NAFLD药物治疗留下了空白。2020年，国际专家组将NAFLD更名为代谢功能障碍相关脂肪肝病（metabolic dysfunction-associated fatty liver disease，MAFLD），新定义更突出代谢异常特征，使其更适用于临床的识别和疾病的防控。MAFLD的新诊断标准有望促进早期药物治疗的启动[1]。本研究结果显示，尿酸每升高10 mg/L，NAFLD风险增加15.1%，提示高尿酸水平是NAFLD的独立风险因素。这一发现表明，通过控制尿酸水平可能有助于降低NAFLD的发病风险，从而为NAFLD的预防及早期药物治疗提供了新的方向。
本研究结果与目前研究存在异同之处，一项基于中国2 382名受试者的前瞻性队列研究表明，尿酸与NAFLD风险呈正相关，且高尿酸水平可作为NAFLD的独立预测指标[17]，此外，针对欧洲地中海人群的一项横断面病例对照研究同样显示，尿酸升高增加NAFLD患病风险[18]，这一结论在2023年涵盖24个国家或地区的93项研究的荟萃分析中得到验证，且不同亚组分析结果一致[19]。然而，另一项针对巴西儿童和青少年的横断面研究表明，高尿酸水平与代谢综合征和青春期相关，但与NAFLD风险无关[20]。这些研究结果并不一致，可能是由于地域、人种、样本量和研究方法等差异所致。
由于尿酸在体内的双向作用，使其与某些疾病或病理状态呈“U”型关联[21]，尽管以上文献报道了尿酸与NAFLD的相关性[17-19]，但针对具体关联模式的研究仍然有限，本研究发现，尿酸与NAFLD风险呈线性相关。由于尿酸在细胞代谢、信号通路中的复杂作用，从机制上解释这种线性关系较为困难，可能有如下原因：在肝细胞中，尿酸增强黄嘌呤氧化酶（XO）和烟酰胺腺嘌呤二核苷酸磷酸（NADPH）氧化酶的活性、增加活性氧的生成[22-23]，这种促氧化效应是NAFLD发病机制中的关键因素之一。而尿酸的抗氧化作用在细胞外更为显著[6]，由于NAFLD的主要病理变化在肝细胞内，故促氧化效应在病理进程中发挥主导作用。随着尿酸水平的升高，XO与NADPH氧化酶之间相互促进，形成恶性循环，促氧化效应不断增强[6]，导致肝脏脂肪沉积和功能损伤加剧，而抗氧化效应则相对有限，故并未出现非线性的阈值效应。
基于尿酸与NAFLD的线性相关，故本研究采用线性MR方法进行遗传学层面的因果推断。逆方差加权结果表明尿酸与NAFLD存在遗传学因果关联，这一结论也得到了其他四种补充分析方法的支持。敏感性检验说明结果的稳健与可靠。值得注意的是，Li等[24]的尿酸与NAFLD的MR分析与本研究结果不同，这可能是排除的混杂因素不同所致。高血压作为NAFLD风险因素[12]，且已发现与NAFLD存在遗传关联[11]，故本研究将高血压作为混杂因素排除。我们应谨慎客观的看待不同的MR结果，并期待未来通过更全面的遗传数据进一步评估两者的因果关系。
本研究具有以下优势：一方面，观察性研究数据来源可靠且样本量大，并通过MR方法进行因果关系验证，结果更可信。另一方面，根据暴露与结局的关联模式，采用相应的MR分析方法，研究方法更科学严谨。此外，严格的纳入及排除标准，最大程度地减少了数据的缺失及混杂因素引起的偏倚。然而，本研究也存在一些局限性，研究数据来源于美国及欧洲人群，结果能否全面推广仍需论证。尽管调整了多个协变量，仍无法完全排除所有潜在的混杂因素。
总之，本研究揭示了尿酸增加肝脏脂肪变性及NAFLD的风险，支持尿酸作为NAFLD风险因素的可能性。这一发现强调了在高尿酸血症人群中NAFLD筛查的重要性，提示控制尿酸水平可能在预防和管理NAFLD及其并发症方面发挥重要作用，并为NAFLD早期药物治疗提供了新的方向。
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doi: 10.20043/j.cnki.MPM.202409005
  • 接收时间：2024-09-01
  • 首发时间：2026-03-18
  • 出版时间：2025-02-10
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  • 收稿日期：2024-09-01
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    1.中国科学技术大学附属第一医院（安徽省立医院）消化内科，安徽 合肥 230001
    2.安徽理工大学医学院

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
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