Article(id=1206995211880846298, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1206995206415668023, articleNumber=null, orderNo=null, doi=10.11855/j.issn.0577-7402.2022.11.1116, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1623859200000, receivedDateStr=2021-06-17, revisedDate=null, revisedDateStr=null, acceptedDate=1638460800000, acceptedDateStr=2021-12-03, onlineDate=1765699683399, onlineDateStr=2025-12-14, pubDate=1669564800000, pubDateStr=2022-11-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1765699683399, onlineIssueDateStr=2025-12-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1765699683399, creator=13701087609, updateTime=1765699683399, updator=13701087609, issue=Issue{id=1206995206415668023, tenantId=1146029695717560320, journalId=1189873630562394117, year='2022', volume='47', issue='11', pageStart='1063', pageEnd='1167', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1765699682092, creator=13701087609, updateTime=1765700231511, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1206997510904693630, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1206995206415668023, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1206997510908887935, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1206995206415668023, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1116, endPage=1124, ext={EN=ArticleExt(id=1206995213621482492, articleId=1206995211880846298, tenantId=1146029695717560320, journalId=1189873630562394117, language=EN, title=Correlation and potential mechanism of plasma magnesium concentration with blood lipids and uric acid, columnId=1190310109000602400, journalTitle=Medical Journal of Chinese People’s Liberation Army, columnName=Clinical Research, runingTitle=null, highlight=null, articleAbstract=

Objective To explore the correlation and potential mechanism of plasma magnesium (Mg2+) concentration with blood lipids and uric acid. Methods The physical examination data of healthy population from September 2018 to May 2021 were collected from the Second Affiliated Hospital of Xi'an Jiaotong University, and divided into two groups according to the plasma Mg2+ concentration (low Mg2+ group, ≤1.65 mmol/L; high Mg2+ group, >1.65 mmol/L). The differences of blood lipids and uric acid were compared between the two groups. Spearman correlation analysis was performed to analyze the correlation of plasma Mg2+ concentration and the metabolism of blood lipids and uric acid. Subgroups were set up according to gender and age, and based on the Comparative Toxicogenomics Database (CTD) and other disease-related databases, genes related to Mg2+ and dyslipidemia were extracted and matched, protein interaction (PPI) network was constructed, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Results Uric acid [(288.88±80.44) mg/dl vs. (325.00±83.38) mg/dl, P<0.001], total cholesterol [TC, (4.27±0.85) mmol/L vs. (4.52±0.87) mmol/L, P<0.001],triglyceride [TG, (1.31±0.97) mmol/L vs. (1.70±1.33) mmol/L, P<0.001] and low-density lipoprotein cholesterol [LDL-C,(2.62±0.76) mmol/L vs. (2.85±0.75) mmol/L, P<0.001] were significantly increased in healthy population with higher Mg2+ concentration, while high-density lipoprotein cholesterol (HDL-C) decreased significantly [(1.33±0.34) mmol/L vs.(1.25±0.30) mmol/L, P<0.001]. Spearman correlation analysis showed that plasma Mg2+ was positively correlated with uric acid(r=0.237, P<0.001), TC (r=0.154, P<0.001), TG (r=0.254, P<0.001), LDL-C (r=0.170, P<0.001), while negatively correlated with HDL-C (r=–0.154, P<0.001). Analyzed results in male and female subgroups were basically consistent with the above results, and the differences mainly come from the age group of 20-40 years old and 40-60 years old. In addition, there were 12 matched genes between Mg2+ and dyslipidemia. GO and KEGG enrichment analysis indicated that Mg2+ may act on insulin, SREBF1, HMGCR, LCAT, CD36 and other liver lipid synthesis and metabolic targets, and thus affect adenosine monophosphate protein kinase (AMPK) signaling, insulin resistance, and atherosclerosis. Conclusion The raised plasma Mg2+ concentration is often correlated with dyslipidemia and hyperuricemia in healthy population. Magnesium may involve in liver lipid metabolism and insulin pathway, and play a role in dyslipidemia, insulin resistance and atherosclerosis.

, correspAuthors=Cong-Xia Wang, authorNote=null, correspAuthorsNote=
*E-mail:
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目的 探讨血浆Mg2+浓度与血脂、血尿酸代谢之间的关系及其潜在机制。方法 收集西安交通大学第二附属医院2018年9月-2021年5月的健康人群体检数据,根据血浆Mg2+浓度分为低Mg2+组(≤1.65 mmol/L)与高Mg2+组(>1.65 mmol/L),比较两组间血脂与血尿酸的差异;采用Spearman检验分析Mg2+浓度与血脂、血尿酸代谢之间的相关性;按性别与年龄分亚组进行比较;基于毒性与基因比较数据库(CTD)及OMIM等疾病相关数据库,挖掘与Mg2+及血脂异常相关的基因并进行匹配,构建蛋白互作(PPI)网络,并进行GO与KEGG富集分析。结果 与低Mg2+组比较,高Mg2+组血尿酸[(288.88±80.44) mg/dl vs.(325.00±83.38) mg/dl,P<0.001]、总胆固醇[TC,(4.27±0.85) mmol/L vs. (4.52±0.87) mmol/L,P<0.001]、三酰甘油[TG,(1.31±0.97) mmol/L vs. (1.70±1.33) mmol/L,P<0.001]及低密度脂蛋白胆固醇[LDL-C,(2.62±0.76) mmol/L vs. (2.85±0.75) mmol/L,P<0.001]水平均明显升高,高密度脂蛋白胆固醇水平[HDL-C,(1.33±0.34) vs. (1.25±0.30) mmol/L,P<0.001]明显降低。Spearman相关分析显示,血浆Mg2+与血尿酸、TC、TG、LDL-C呈明显正相关(r分别为0.237、0.154、0.254、0.170,P<0.001),而与HDL-C呈明显负相关(r=–0.154,P<0.001)。男性与女性亚组分析与上述结果基本一致,且差异主要集中于20~40岁及40~60岁年龄段人群。基因挖掘结果显示,Mg2+与血脂异常之间存在12个共同基因;GO和KEGG富集分析结果显示,Mg2+可能作用于胰岛素、SREBF1、HMGCR、LCAT、CD36等肝脏脂质合成与代谢靶点,影响腺苷酸蛋白活化激酶(AMPK)通路及胰岛素抵抗、动脉粥样硬化等的发生与进展。结论 健康人群中血浆Mg2+升高与血脂异常和高尿酸血症具有一定相关性,Mg2+可能调控肝脏脂质代谢与胰岛素通路,参与血脂异常、胰岛素抵抗及动脉粥样硬化的发生。

, correspAuthors=王聪霞, authorNote=null, correspAuthorsNote=
王聪霞,E-mail:
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韩拓,博士研究生,主要从事心血管代谢性疾病方面的研究

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韩拓,博士研究生,主要从事心血管代谢性疾病方面的研究

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TC. 总胆固醇;TG. 三酰甘油;HDL-C. 高密度脂蛋白胆固醇;LDL-C. 低密度脂蛋白胆固醇

, figureFileSmall=GWtouqnf6F4XRVOllig9kQ==, figureFileBig=N7tZ9kHpMP+WCwEE+9rntw==, tableContent=null), ArticleFig(id=1207064235713057737, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1206995211880846298, language=EN, label=Fig. 2, caption=Comparison of plasma Mg2+ concentrations between different genders (A) and age (B) subgroups, figureFileSmall=zaBnuBKM//I0rMbdbzLaCg==, figureFileBig=k04AAq+D050LKyAteSj+jA==, tableContent=null), ArticleFig(id=1207064235801138126, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1206995211880846298, language=CN, label=图2, caption=不同性别(A)与年龄(B)组间血Mg2+浓度比较

与男性比较,(1)P<0.05;与20~40岁年龄组比较,(2)P<0.001, (3)P<0.01

, figureFileSmall=zaBnuBKM//I0rMbdbzLaCg==, figureFileBig=k04AAq+D050LKyAteSj+jA==, tableContent=null), ArticleFig(id=1207064235889218514, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1206995211880846298, language=EN, label=Fig. 3, caption=Comparison of blood lipids and uric acid in male (A) and female (B) subgroups with different plasma Mg2+ levels, figureFileSmall=LXKiMX1pQaHI0ebqG+vWpA==, figureFileBig=LYuq4gjUZHJBaG69bkoJ7Q==, tableContent=null), ArticleFig(id=1207064235973104596, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1206995211880846298, language=CN, label=图3, caption=男性(A)与女性(B)不同血Mg2+浓度组间血脂、血尿酸水平比较

与低Mg2+组比较,(1)P<0.05, (2)P<0.001

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与低Mg2+组比较,(1)P<0.01,(2)P<0.001

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Comparison of the clinical information between the subgroups with different plasma Mg2+ concentration

, figureFileSmall=null, figureFileBig=null, tableContent=
指标总体(n=2541)低Mg2+组(n=1290)高Mg2+组(n=1251)χ2/tP
男/女(例)1394/1147537/753857/394185.266<0.001
年龄(岁,$\bar{x}±s$)40.8±12.839.9±12.841.8±12.8–3.746<0.001
心率(次/min, $\bar{x}±s$)76.28±9.1876.71±9.1375.82±9.212.4470.014
BMI (kg/m2, $\bar{x}±s$)23.87±3.5223.26±3.4024.50±3.53–9.016<0.001
收缩压 (mmHg, $\bar{x}±s$)120.81±15.06119.56±15.13122.11±14.88–4.286<0.001
舒张压 (mmHg, $\bar{x}±s$)78.38±11.1877.13±11.1479.68±11.07–5.783<0.001
吸烟 [例(%)]208(8.2)65(5.0)143(11.4)34.527<0.001
血尿酸 (mg/dl, $\bar{x}±s$)306.65±83.85288.88±80.44325.00±83.38–11.062<0.001
TC (mmol/L, $\bar{x}±s$)4.39±0.874.27±0.854.52±0.87–7.148<0.001
TG (mmol/L, $\bar{x}±s$)1.50±1.181.31±0.971.70±1.33–8.418<0.001
HDL-C (mmol/L, $\bar{x}±s$)1.29±0.321.33±0.341.25±0.306.739<0.001
LDL-C (mmol/L, $\bar{x}±s$)2.74±0.762.62±0.762.85±0.75–7.764<0.001
FBG (mmol/L, $\bar{x}±s$)5.16±1.135.09±1.125.23±1.13–3.2710.001
总蛋白 (g/L, $\bar{x}±s$)71.31±4.7871.36±4.8471.27±4.730.4400.660
白蛋白 (g/L, $\bar{x}±s$)45.35±2.9445.18±2.9345.51±2.94–2.6600.008
ALT (U/L, $\bar{x}±s$)22.25±16.1719.60±13.8124.99±17.88–8.464<0.001
AST(U/L, $\bar{x}±s$)21.05±8.2720.09±7.5022.05±8.88–6.010<0.001
BUN (mmol/L, $\bar{x}±s$)4.55±1.204.43±1.224.67±1.16–5.044<0.001
Scr (μmol/L, $\bar{x}±s$)65.27±14.2962.17±14.0068.46±13.87–11.307<0.001
), ArticleFig(id=1207064236761633776, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1206995211880846298, language=CN, label=表1, caption=

研究人群整体及不同血Mg2+浓度组间临床资料比较

, figureFileSmall=null, figureFileBig=null, tableContent=
指标总体(n=2541)低Mg2+组(n=1290)高Mg2+组(n=1251)χ2/tP
男/女(例)1394/1147537/753857/394185.266<0.001
年龄(岁,$\bar{x}±s$)40.8±12.839.9±12.841.8±12.8–3.746<0.001
心率(次/min, $\bar{x}±s$)76.28±9.1876.71±9.1375.82±9.212.4470.014
BMI (kg/m2, $\bar{x}±s$)23.87±3.5223.26±3.4024.50±3.53–9.016<0.001
收缩压 (mmHg, $\bar{x}±s$)120.81±15.06119.56±15.13122.11±14.88–4.286<0.001
舒张压 (mmHg, $\bar{x}±s$)78.38±11.1877.13±11.1479.68±11.07–5.783<0.001
吸烟 [例(%)]208(8.2)65(5.0)143(11.4)34.527<0.001
血尿酸 (mg/dl, $\bar{x}±s$)306.65±83.85288.88±80.44325.00±83.38–11.062<0.001
TC (mmol/L, $\bar{x}±s$)4.39±0.874.27±0.854.52±0.87–7.148<0.001
TG (mmol/L, $\bar{x}±s$)1.50±1.181.31±0.971.70±1.33–8.418<0.001
HDL-C (mmol/L, $\bar{x}±s$)1.29±0.321.33±0.341.25±0.306.739<0.001
LDL-C (mmol/L, $\bar{x}±s$)2.74±0.762.62±0.762.85±0.75–7.764<0.001
FBG (mmol/L, $\bar{x}±s$)5.16±1.135.09±1.125.23±1.13–3.2710.001
总蛋白 (g/L, $\bar{x}±s$)71.31±4.7871.36±4.8471.27±4.730.4400.660
白蛋白 (g/L, $\bar{x}±s$)45.35±2.9445.18±2.9345.51±2.94–2.6600.008
ALT (U/L, $\bar{x}±s$)22.25±16.1719.60±13.8124.99±17.88–8.464<0.001
AST(U/L, $\bar{x}±s$)21.05±8.2720.09±7.5022.05±8.88–6.010<0.001
BUN (mmol/L, $\bar{x}±s$)4.55±1.204.43±1.224.67±1.16–5.044<0.001
Scr (μmol/L, $\bar{x}±s$)65.27±14.2962.17±14.0068.46±13.87–11.307<0.001
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血浆Mg2+浓度与血脂、血尿酸的关系及其初步机制分析
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韩拓 1 , 姚智会 1 , 范雅洁 1 , 巩红 2 , 郑阳 1 , 王丽霞 1 , 王怡雯 1 , 王聪霞 1, *
解放军医学杂志 | 临床研究 2022,47(11): 1116-1124
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解放军医学杂志 | 临床研究 2022, 47(11): 1116-1124
血浆Mg2+浓度与血脂、血尿酸的关系及其初步机制分析
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韩拓1, 姚智会1, 范雅洁1, 巩红2, 郑阳1, 王丽霞1, 王怡雯1, 王聪霞1, *
作者信息
  • 1西安交通大学第二附属医院心血管内科,陕西西安 710004
  • 2西安交通大学第二附属医院健康管理部,陕西西安 710004
  • 韩拓,博士研究生,主要从事心血管代谢性疾病方面的研究

通讯作者:

王聪霞,E-mail:
Correlation and potential mechanism of plasma magnesium concentration with blood lipids and uric acid
Tuo Han1, Zhi-Hui Yao1, Ya-Jie Fan1, Hong Gong2, Yang Zheng1, Li-Xia Wang1, Yi-Wen Wang1, Cong-Xia Wang1, *
Affiliations
  • 1Department of Cardiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710004, China
  • 2Department of Health Management, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710004, China
出版时间: 2022-11-28 doi: 10.11855/j.issn.0577-7402.2022.11.1116
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目的 探讨血浆Mg2+浓度与血脂、血尿酸代谢之间的关系及其潜在机制。方法 收集西安交通大学第二附属医院2018年9月-2021年5月的健康人群体检数据,根据血浆Mg2+浓度分为低Mg2+组(≤1.65 mmol/L)与高Mg2+组(>1.65 mmol/L),比较两组间血脂与血尿酸的差异;采用Spearman检验分析Mg2+浓度与血脂、血尿酸代谢之间的相关性;按性别与年龄分亚组进行比较;基于毒性与基因比较数据库(CTD)及OMIM等疾病相关数据库,挖掘与Mg2+及血脂异常相关的基因并进行匹配,构建蛋白互作(PPI)网络,并进行GO与KEGG富集分析。结果 与低Mg2+组比较,高Mg2+组血尿酸[(288.88±80.44) mg/dl vs.(325.00±83.38) mg/dl,P<0.001]、总胆固醇[TC,(4.27±0.85) mmol/L vs. (4.52±0.87) mmol/L,P<0.001]、三酰甘油[TG,(1.31±0.97) mmol/L vs. (1.70±1.33) mmol/L,P<0.001]及低密度脂蛋白胆固醇[LDL-C,(2.62±0.76) mmol/L vs. (2.85±0.75) mmol/L,P<0.001]水平均明显升高,高密度脂蛋白胆固醇水平[HDL-C,(1.33±0.34) vs. (1.25±0.30) mmol/L,P<0.001]明显降低。Spearman相关分析显示,血浆Mg2+与血尿酸、TC、TG、LDL-C呈明显正相关(r分别为0.237、0.154、0.254、0.170,P<0.001),而与HDL-C呈明显负相关(r=–0.154,P<0.001)。男性与女性亚组分析与上述结果基本一致,且差异主要集中于20~40岁及40~60岁年龄段人群。基因挖掘结果显示,Mg2+与血脂异常之间存在12个共同基因;GO和KEGG富集分析结果显示,Mg2+可能作用于胰岛素、SREBF1、HMGCR、LCAT、CD36等肝脏脂质合成与代谢靶点,影响腺苷酸蛋白活化激酶(AMPK)通路及胰岛素抵抗、动脉粥样硬化等的发生与进展。结论 健康人群中血浆Mg2+升高与血脂异常和高尿酸血症具有一定相关性,Mg2+可能调控肝脏脂质代谢与胰岛素通路,参与血脂异常、胰岛素抵抗及动脉粥样硬化的发生。

镁  /  血脂异常  /  尿酸  /  胰岛素抵抗  /  动脉粥样硬化

Objective To explore the correlation and potential mechanism of plasma magnesium (Mg2+) concentration with blood lipids and uric acid. Methods The physical examination data of healthy population from September 2018 to May 2021 were collected from the Second Affiliated Hospital of Xi'an Jiaotong University, and divided into two groups according to the plasma Mg2+ concentration (low Mg2+ group, ≤1.65 mmol/L; high Mg2+ group, >1.65 mmol/L). The differences of blood lipids and uric acid were compared between the two groups. Spearman correlation analysis was performed to analyze the correlation of plasma Mg2+ concentration and the metabolism of blood lipids and uric acid. Subgroups were set up according to gender and age, and based on the Comparative Toxicogenomics Database (CTD) and other disease-related databases, genes related to Mg2+ and dyslipidemia were extracted and matched, protein interaction (PPI) network was constructed, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Results Uric acid [(288.88±80.44) mg/dl vs. (325.00±83.38) mg/dl, P<0.001], total cholesterol [TC, (4.27±0.85) mmol/L vs. (4.52±0.87) mmol/L, P<0.001],triglyceride [TG, (1.31±0.97) mmol/L vs. (1.70±1.33) mmol/L, P<0.001] and low-density lipoprotein cholesterol [LDL-C,(2.62±0.76) mmol/L vs. (2.85±0.75) mmol/L, P<0.001] were significantly increased in healthy population with higher Mg2+ concentration, while high-density lipoprotein cholesterol (HDL-C) decreased significantly [(1.33±0.34) mmol/L vs.(1.25±0.30) mmol/L, P<0.001]. Spearman correlation analysis showed that plasma Mg2+ was positively correlated with uric acid(r=0.237, P<0.001), TC (r=0.154, P<0.001), TG (r=0.254, P<0.001), LDL-C (r=0.170, P<0.001), while negatively correlated with HDL-C (r=–0.154, P<0.001). Analyzed results in male and female subgroups were basically consistent with the above results, and the differences mainly come from the age group of 20-40 years old and 40-60 years old. In addition, there were 12 matched genes between Mg2+ and dyslipidemia. GO and KEGG enrichment analysis indicated that Mg2+ may act on insulin, SREBF1, HMGCR, LCAT, CD36 and other liver lipid synthesis and metabolic targets, and thus affect adenosine monophosphate protein kinase (AMPK) signaling, insulin resistance, and atherosclerosis. Conclusion The raised plasma Mg2+ concentration is often correlated with dyslipidemia and hyperuricemia in healthy population. Magnesium may involve in liver lipid metabolism and insulin pathway, and play a role in dyslipidemia, insulin resistance and atherosclerosis.

magnesium  /  dyslipidemia  /  uric acid  /  insulin resistance  /  atherosclerosis
韩拓, 姚智会, 范雅洁, 巩红, 郑阳, 王丽霞, 王怡雯, 王聪霞. 血浆Mg2+浓度与血脂、血尿酸的关系及其初步机制分析. 解放军医学杂志, 2022 , 47 (11) : 1116 -1124 . DOI: 10.11855/j.issn.0577-7402.2022.11.1116
Tuo Han, Zhi-Hui Yao, Ya-Jie Fan, Hong Gong, Yang Zheng, Li-Xia Wang, Yi-Wen Wang, Cong-Xia Wang. Correlation and potential mechanism of plasma magnesium concentration with blood lipids and uric acid[J]. Medical Journal of Chinese People’s Liberation Army, 2022 , 47 (11) : 1116 -1124 . DOI: 10.11855/j.issn.0577-7402.2022.11.1116
血脂异常是以血浆总胆固醇(cholesterol,TC)和(或)三酰甘油(triacylglycerol,TG)升高为主要特征的一组疾病[1-2],与动脉粥样硬化、肥胖、非酒精性脂肪肝、2型糖尿病等密切相关[3-5]。据统计,中国成人血脂异常患病率高达40.4%,以高甘油三酯血症(13.1%)和低高密度脂蛋白胆固醇(high density lipoprotein cholesterol,HDL-C)血症(33.9%)最为常见[1]。高尿酸血症是由嘌呤代谢障碍引起的血尿酸水平升高[6],是导致痛风的主要原因[7-8],也是高血压、卒中等心脑血管疾病的重要危险因素[9-10]。他汀类降脂药物和降尿酸药物可有效降低心血管疾病患者的血脂及血尿酸水平,但仍存在心血管“残留风险”[11-12]。长期服用上述药物还会引起相关不良反应,如肌痛及肝酶升高等[13]。镁是人体必需的无机微量元素,参与体内多种生物过程的酶促反应,如糖酵解、线粒体氧化磷酸化等[14]。有研究发现,血Mg2+浓度降低或Mg2+摄入减少与动脉粥样硬化、冠心病、心律失常等疾病的发生相关[15-16]。然而,目前有关血Mg2+与血脂异常之间的相关性研究较少,且结果存在较大争议。本研究分析健康体检人群中血浆Mg2+浓度与血脂、血尿酸的相关性,并进行数据库挖掘与基因富集分析,旨在探究血浆Mg2+与血脂/尿酸代谢之间的作用靶点和潜在机制,为临床制定治疗决策提供理论依据。
收集2018年9月-2021年5月西安交通大学第二附属医院的健康体检数据,纳入自诉既往无特殊病史,且具有血清微量元素与血脂检测结果者,排除合并高血压、糖尿病、冠心病、恶性肿瘤等基础疾病者,以及基线资料不完整者,最终共纳入2541例,其中男1394例(54.9%),女1147例(45.1%),年龄18~86(40.8±12.8)岁,呈左偏态分布。血Mg2+浓度0.62~3.20(1.65±0.25) mmol/L(参考范围1.12~2.16 mmol/L),呈正态分布,根据Mg2+浓度分为低Mg2+组(≤1.65 mmol/L)与高Mg2+组(>1.65 mmol/L)。本研究获西安交通大学第二附属医院伦理委员会批准(2022202)。
收集所有研究对象的人体学测量指标,包括身高、体重、腰围、臀围等;采用电子血压计于坐位安静状态下测量左侧上臂肱动脉血压(型号Hem-7124,日本Omron公司),并记录脉搏、心率;所有体检者均于次日清晨空腹抽取静脉血,采用德国贝克曼全自动生化分析仪检测血脂成分,采用原子吸收光谱仪检测血浆微量元素含量(型号BH5100S,北京博晖创新生物技术股份有限公司)。
比较低Mg2+组与高Mg2+组间性别、年龄、体重指数(BMI)、血尿酸、血脂谱、肝功能、肾功能等指标的差异,并进一步探究血Mg2+浓度与血尿酸、血脂谱之间的相关性。为排除性别与年龄的混杂影响,分别在不同性别与不同年龄段分层中比较低Mg2+组与高Mg2+组血尿酸及血脂的差异。
基于毒性与基因比较数据库(CTD,https://ctdbase.org/),检索关键词“Magnesium”,获得与Mg2+相关基因靶点。针对OMIM数据库(https://www.omim.org/),GeneCards(https://www.genecards.org/),Therapeutic Target Database[17](http://db.idrblab.net/ttd/),利用关键词“dyslipidemia”检索与高脂血症相关的基因,归纳并删除重复项,以获得与高脂血症相关的靶基因。
利用在线Venny软件(https://bioinfogp.cnb.csic.es/tools/venny/)对Mg2+与血脂异常相关基因进行匹配,获得共同相关基因。基于String数据库(https://string-db.org/)对匹配基因进行PPI网络分析。
基于R软件调用clusterProfiler包和org. Hs.eg.db注释包,进行基因本体(gene ontology,GO)功能注释与京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析。
采用SPSS 23.0软件进行统计分析。对计量资料进行Kolmogorov-Smirnov 正态性检验,符合正态分布者以$\bar{x}±s$表示,两组间比较采用独立样本t检验,多组间比较采用单因素方差分析,进一步两两比较采用LSD-t检验;不符合正态分布者以M(Q1Q3)表示,组间比较采用非参数Mann-Whitney U检验。计数资料以例(%)表示,组间比较采用χ2检验或Fisher精确检验;相关性分析采用Spearman检验。P<0.05为差异有统计学意义。
高Mg2+组男性比例更高,年龄偏大,BMI及收缩压、舒张压较高,吸烟比例更高,差异均有统计学意义(P<0.001)。与低Mg2+组比较,高Mg2+组血尿酸、TC、TG及低密度脂蛋白胆固醇(LDL-C)水平均明显升高(P<0.001),而高密度脂蛋白胆固醇(HDL-C)水平明显降低(P<0.001)。此外,高Mg2+组空腹血糖(FBG)水平明显高于低Mg2+组(P<0.05),且谷丙转氨酶(ALT)、谷草转氨酶(AST)和血肌酐(Scr)、尿素氮(BUN)水平也明显高于低Mg2+组(P<0.001)(表1)。
Spearman相关分析结果显示,血Mg2+浓度与血尿酸水平呈明显正相关(r=0.237,P<0.001),与血浆TC(r=0.154,P<0.001)、TG(r=0.254,P<0.001)、LDL-C(r=0.170,P<0.001)及非HDL-C(r=0.208,P<0.001)亦呈明显正相关,而与HDL-C呈明显负相关(r=–0.154,P<0.001)(图1)。
普通健康人群中女性血Mg2+浓度明显低于男性(P<0.05,图2A);此外,随着年龄的增长,血Mg2+浓度也逐渐升高,组间比较差异有统计学意义(F=6.341,P<0.001),其中40~60岁及>60岁年龄组血Mg2+浓度均明显高于20~40岁年龄组(P<0.001,P<0.01,图2B)。亚组分析结果显示,无论男性还是女性,高Mg2+组TC、TG、LDL-C及血尿酸水平均明显高于低Mg2+组(P<0.001或P<0.05),而两组HDL-C水平则无明显差异(图3);在20~40岁及40~60岁年龄段,高Mg2+组TC、TG、LDL-C、非HDL-C及血尿酸水平均明显高于低Mg2+组(P<0.01或P<0.001),HDL-C水平明显低于低Mg2+组(P<0.001);而在0~20岁及≥60岁年龄段,两组各项血脂指标与血尿酸水平差异均无统计学意义(图4)。
基于CTD和疾病相关数据库,分别挖掘与Mg2+和血脂异常相关的基因,进行作用靶点匹配,共获得12个匹配基因(图5A),分别为胰岛素(insulin,INS)、固醇调节元件结合蛋白1(sterol regulatory element-binding protein 1,SREBF1)、P选择素(P-selectin,SELP)、补体C3(complement,C3)、羟甲基戊二酰辅酶A还原酶(HMG-CoA reductase,HMGCR)、卵磷脂胆固醇酰基转移酶(lecithin cholesterol acyl transferase,LCAT)、纤溶酶原激活物抑制剂1(plasminogen activator inhibitor 1,SERPINE1)、C-X-C趋化因子2(C-X-C motif chemokine 2,CXCL2)、CD36、生长激素受体(growth hormone receptor,GHR)、甘油激酶(glycerol kinase,GK)及RalA结合蛋白1(RalA-binding protein 1,RALBP1),并利用String数据库建立了PPI网络(图5B)。
GO结果显示,上述12个匹配基因主要参与脂质代谢(lipid metabolic process)、三酰甘油合成(triglyceride biosynthetic process)、中性脂与酰基甘油合成(neutral lipid biosynthetic process)、促进凝血(blood coagulation)以及调节伤口愈合(regulation of wound healing)等生物学过程(图6A);KEGG富集分析结果显示,上述基因主要参与腺苷酸蛋白活化激酶(AMP activated protein kinase,AMPK)通路、胰岛素抵抗(insulin resistance)、胆固醇代谢(cholesterol metabolism)与动脉粥样硬化(lipid and atherosclerosis)等过程(图6B)。
镁是机体必需的微量元素之一,参与体内多种重要的生物酶促反应过程。人体内镁主要在小肠进行吸收,再由肾脏排泄和重吸收,可参与组织细胞内外钾、钙等多种离子的交换[14]。机体内绝大多数镁位于细胞内,主要储存于骨组织中,仅约1%的镁以离子形式存在于血浆或组织液中[18]。正常血Mg2+浓度参考范围为0.75~1.00 mmol/L,<0.75 mmol/L通常被定义为是低镁血症[14]。血Mg2+浓度与血脂紊乱、肥胖、2型糖尿病等多种心血管疾病相关[15,19],然而,由于不同研究之间的异质性,血Mg2+含量及补充镁剂与血脂代谢之间的相关性仍存在较大争议[15,20]
既往研究报道低镁血症与血脂异常的发生相关。2型糖尿病患者中低镁血症的发生率明显高于健康人群,且血Mg2+浓度与血浆TC、LDL-C呈负相关,与HDL-C呈明显正相关[21-22]。此外,高胆固醇血症和血脂异常患者中血Mg2+浓度明显降低[23-24]。然而,最近一项研究发现,地中海人群中低镁血症(<0.70 mmol/L)的整体发生率高达18.6%,低镁血症与血浆TC、TG及血尿酸水平之间并无明显相关性;相反,高胆固醇血症患者中血Mg2+浓度明显升高,血Mg2+浓度最高的四分位数组的血浆TC与LDL-C水平较最低组明显升高[25]。另一项针对西欧人群的调查发现,在健康人群中血Mg2+浓度与主要血脂成分呈正相关,亚组及回归分析结果显示,血Mg2+与TC水平仍明显相关[26],提示健康人群中血Mg2+与血脂间的相关性可能与糖尿病患者不同。此外,血Mg2+与血脂间的相关性还与年龄、性别,以及种族、饮食习惯等因素有关[27]。国内学者研究发现,高尿酸血症患者同时伴有血Mg2+浓度升高,而给予降尿酸药物治疗后,血Mg2+浓度也随之降低[28]。基于以上研究,本研究利用我院健康体检数据,发现血Mg2+浓度>1.65 mmol/L的普通人群中血尿酸、TC、TG及LDL-C均明显升高,性别与年龄亚组分析结果基本一致;相关性分析结果显示,血Mg2+与上述指标均呈明显正相关,而与HDL-C呈明显负相关。以上结果表明,不同于既往特定疾病或疾病前期人群研究,健康人群中血Mg2+升高可能与血脂异常和高尿酸血症的发生相关。
为探究血Mg2+与血脂代谢之间的作用机制,本研究对Mg2+和血脂异常相关基因进行匹配和富集分析,发现了包括胰岛素、SREBF1HMGCRLCATCD36等在内的12个共同基因,主要参与脂质代谢、三酰甘油合成,以及促进凝血、调节伤口愈合等过程,并可能与腺苷酸蛋白活化激酶(AMPK)信号通路及胰岛素抵抗、动脉粥样硬化进展相关。有研究报道,Mg2+可抑制胆固醇合成限速酶即HMGCR的活性,直接抑制肝脏胆固醇的合成[29-30]。此外,Mg2+对卵磷脂胆固醇酰基转移酶(LCAT)的活性也是必需的,后者能够使血浆LDL-C和TG水平降低,HDL-C水平升高[29]。Mg2+缺乏还可能与机体免疫炎症反应和氧化应激有关[31],从而间接影响血脂异常、2型糖尿病等的发生与进展。冠脉中度狭窄患者口服硫酸镁300 mg/d治疗6个月后,血清氧化低密度脂蛋白(ox-LDL)及其受体水平较对照组明显降低[32],且血清C-反应蛋白等反映炎症水平的指标也明显降低[33]。然而,大部分同类研究并未能证实补充镁剂对血脂具有改善作用[19,34-35],提示Mg2+与血脂代谢之间并非简单的上下游调控关系。由于血Mg2+浓度并不能准确反映体内镁含量,受制于现有检测手段,目前关于机体Mg2+缺乏的诊断仍存在争议[36]。此外,对于血Mg2+浓度正常范围也存在分歧,现行参考标准并不能准确反映临床结局[37]。而本研究中低镁血症(<0.75 mmol/L)者仅25例(1.8%),与国外报道的低镁血症10%~30%的发生率相差悬殊[25,38],这可能也与西方饮食中Mg2+普遍缺乏有关[38]
综上所述,不同于既往特定疾病或疾病前期人群的研究结果,本研究发现普通健康人群中血Mg2+浓度与TC、TG、LDL-C、非HDL-C及血尿酸水平之间存在明显正相关,性别和年龄亚组分析进一步验证了上述结果。此外,通过公共数据库挖掘和基因功能富集分析发现,Mg2+可能作用于胰岛素、SREBF1、HMGCR、LCAT、CD36等肝脏脂质合成与代谢的相关靶点,进而影响AMPK信号通路及胰岛素抵抗、动脉粥样硬化的发生与进展。但本研究仍存在一些不足之处。首先,研究基于我院健康体检管理数据,对于研究对象既往疾病史、用药史等背景信息筛查可能存在不规范和错漏情况;其次,本研究结果仅提示相关性而不足以作出因果推断,因此结论仍需进一步验证;最后,基因富集分析仅能预测作用靶点和潜在机制,无法明确Mg2+对血脂异常的影响究竟是促进还是抑制作用。血Mg2+水平与脂代谢异常密切相关,且与个体疾病状态有关。开展前瞻性队列研究及临床试验将有助于阐明Mg2+与血脂之间的相关性,以及明确补充镁剂在脂代谢方面的获益。
  • 国家自然科学基金(81273878)
  • 陕西省自然科学基金青年基金(2021JQ-409)
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2022年第47卷第11期
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doi: 10.11855/j.issn.0577-7402.2022.11.1116
  • 接收时间:2021-06-17
  • 首发时间:2025-12-14
  • 出版时间:2022-11-28
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  • 收稿日期:2021-06-17
  • 录用日期:2021-12-03
基金
National Natural Science Foundation of China(81273878)
国家自然科学基金(81273878)
Natural Science Foundation of Shaanxi Province(2021JQ-409)
陕西省自然科学基金青年基金(2021JQ-409)
作者信息
    1西安交通大学第二附属医院心血管内科,陕西西安 710004
    2西安交通大学第二附属医院健康管理部,陕西西安 710004

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2种不同金属材料的力学参数

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Percentage of
total species (%)

Genus
种数
Number of
species
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Percentage of total
species (%)
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
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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