Article(id=1311350168713266000, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349984730116963, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202601227, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1768320000000, receivedDateStr=2026-01-14, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579843928, onlineDateStr=2026-09-28, pubDate=1784908800000, pubDateStr=2026-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579843928, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579843928, creator=13701087609, updateTime=1790579843928, updator=13701087609, issue=Issue{id=1311349984730116963, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='1784908800000', pubDateStr='2026-07-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579800064, creator='13701087609', updateTime=1790588348354, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311385838924169506, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349984730116963, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311385838924169507, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349984730116963, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2639, endPage=2647, ext={EN=ArticleExt(id=1311350170596508497, articleId=1311350168713266000, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Genome-wide cross-trait association analysis reveals the shared genetic architecture between alcohol consumption and bone mineral density, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To systematically investigate the genetic association and shared biological mechanisms between weekly alcohol consumption (DrnkWk) and estimated heel bone mineral density (eBMD) in adults.

Methods

Leveraging large-scale genome-wide association study (GWAS) summary statistics from the UK Biobank and the GSCAN consortium, we integrated linkage disequilibrium score regression (LDSC), local genetic correlation analysis (SUPERGNOVA), cross-trait meta-analysis (PLEIO), gene-based association analysis (MAGMA), and bidirectional two-sample Mendelian randomization (MR) to comprehensively assess global and local genetic correlations, pleiotropic loci, and causal relationships between DrnkWk and eBMD.

Results

No significant genome-wide genetic correlation was observed (rg=-0.018, 95%CI: -0.050-0.014, P=0.26); while SUPERGNOVA identified 3 genomic regions with significant local genetic correlations. PLEIO revealed 35 pleiotropic loci (including 9 novel loci), and MAGMA implicated 30 shared genes. Bidirectional MR provided no evidence of a causal effect (forward MR:β=-0.051, P=0.12; reverse MR:β=-0.009, P=0.08).

Conclusion

The epidemiological association between alcohol consumption and bone density is likely driven by shared biological pathways and pleiotropic genetic architecture rather than direct causality, offering new insights for genetic risk stratification and targeted prevention strategies for osteoporosis.

, authors=Si-rui ZHENG1, Tao HAN1, Ting YU2, Jin-yu ZHOU1, Xia JIANG1, 2, Qin ZHAO3, authorsList=Si-rui ZHENG, Tao HAN, Ting YU, Jin-yu ZHOU, Xia JIANG, Qin ZHAO, authorCompany=null, correspAuthors=Qin ZHAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311350171787690838, articleId=1311350168713266000, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=全基因组跨性状关联分析揭示饮酒与骨密度的共享遗传基础, columnId=1228016572640461823, journalTitle=现代预防医学, columnName=健康与社会行为, runingTitle=null, highlight=null, articleAbstract=
目的

系统解析每周饮酒量(DrnkWk)与成人估算骨密度(eBMD)的遗传关联及共享机制。

方法

基于英国生物银行和GSCAN联盟的大规模全基因组关联研究汇总数据,采用连锁不平衡分数回归(LDSC)、局部遗传相关性分析(SUPERGNOVA)、跨性状荟萃分析(PLEIO)、基因水平关联分析(MAGMA)及双向孟德尔随机化(MR)方法,全面评估DrnkWk与eBMD的遗传相关性、多效性基因位点及因果关联。

结果

DrnkWk与eBMD在全基因组水平未观察到显著遗传相关性(rg=-0.018, 95% CI: -0.050~0.014, P=0.26),但SUPERGNOVA鉴定出3个显著信号区域。PLEIO共发现35个多效性位点(含9个新发位点),MAGMA分析识别出30个显著的多效性基因。双向MR分析未发现两性状间存在显著因果关联(正向MR:β=-0.051, P=0.12;反向MR:β=-0.009, P=0.08)。

结论

饮酒与骨密度的流行病学关联主要源于共享的生物学通路与多效性遗传架构,而非直接因果效应,为骨质疏松的遗传风险分层与靶向干预提供了新思路。

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郑思睿(2000—),女,硕士在读,研究方向:营养与食品卫生学

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赵琴,E-mail:
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Source and description of GWAS summary statistics

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露样本量人群参考基因组序列PMID
每周饮酒量2 428 851欧洲人群GRCh3736 477 530
估算骨密度462 824欧洲人群GRCh3730 598 549
), ArticleFig(id=1311350176959267724, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=CN, label=表1, caption=

GWAS汇总数据来源和描述

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露样本量人群参考基因组序列PMID
每周饮酒量2 428 851欧洲人群GRCh3736 477 530
估算骨密度462 824欧洲人群GRCh3730 598 549
), ArticleFig(id=1311350177038959501, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=EN, label=Table 2, caption=

Significant Pleiotropic loci between DrnkWk and eBMD

, figureFileSmall=null, figureFileBig=null, tableContent=
SNP染色体碱基位置效应/非效应等位基因DrnkWk
βP值
已知的共享SNPs(在两个性状中均显著且PPLEIO<5×10-8的SNPs)
rs10066412551304343T/A-0.015.34×10-09
rs104912785132884744C/A-0.012.96×10-08
rs108386131146690228C/A-0.019.92×10-09
rs71073561147654618G/A0.011.12×10-16
rs560946411653772541G/A-0.011.06×10-10
rs26846411745442752G/A-0.021.31×10-20
rs559381361745720994G/A-0.021.22×10-27
rs626419671745969850G/T-0.031.74×10-30
rs13783581746709946T/C-0.023.83×10-25
单性状驱动的共享SNPs(在单一性状中均显著且PPLEIO<5×10-8的SNPs)
rs66910531173899817T/C-0.011.24×10-10
rs72808612254808212C/T0.027.92×10-07
rs2048370254659468C/T0.019.25×10-06
rs1128280993142438693A/G0.011.68×10-06
rs27265184105252042C/A-0.014.97×10-06
rs168771498108077969A/G-0.019.64×10-06
rs2005617933791166C/T-0.012.48×10-06
rs356776031147246759T/C-0.016.27×10-11
rs112282401168450822T/C-0.018.22×10-06
rs111691621249813343C/T-0.011.70×10-06
rs289294741494378610T/C-0.053.28×10-14
rs787338831669412045A/G-0.021.37×10-06
rs97888031669658092T/A0.013.44×10-07
rs112111542172287092C/T0.018.62×10-06
连锁不平衡的共享SNPs(单一性状GWAS未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且与已知SNPs连锁不平衡)
rs2300669338499827A/C-0.013.12×10-07
rs28806631624766425T/G-0.015.94×10-06
rs729026901845186271G/A-0.012.09×10-07
SNPeBMDPPLEIO聚类范围内的基因
βP值
已知的共享SNPs(在两个性状中均显著且PPLEIO<5×10-8的SNPs)
rs10066412-0.021.60×10-143.01×10-33ISL1, LOC642366
rs104912780.021.80×10-134.09×10-34AFF4, GDF9, HSPA4, LEAP2, SHROOM1, SOWAHA, UQCRQ, ZCCHC10
rs10838613-0.032.70×10-221.27×10-46AMBRA1, ARFGAP2, ARHGAP1, ATG13, C11orf49, CHRM4, CKAP5, CREB3L1, DGKZ, F2, HARBI1, LRP4, LRP4-AS1, MDK, MIR3160-1, MIR3160-2, MIR4688, MIR5582, MIR6745, PACSIN3, SNORD67, ZNF408
rs7107356-0.014.20×10-094.36×10-25AGBL2, C1QTNF4, CELF1, FAM180B, FNBP4, KBTBD4, MTCH2, MYBPC3, NDUFS3, NUP160, PSMC3, PTPMT1, RAPSN, SLC39A13, SPI1
rs560946410.026.80×10-209.78×10-43FTO
rs2684641-0.022.00×10-201.32×10-74ARHGAP27, MIR4315-1, MIR4315-2, PLEKHM1
rs55938136-0.021.60×10-211.93×10-76CRHR1
rs62641967-0.029.10×10-215.13×10-87CRHR1, CRHR1-IT1, KANSL1, KANSL1-AS1, LOC644172, LRRC37A4P, MAPT, MAPT-AS1, MAPT-IT1, MGC57346, MIR4315-1, MIR4315-2, PLEKHM1, SPPL2C, STH
rs1378358-0.022.50×10-172.63×10-69NSF, WNT3
单性状驱动的共享SNPs(在单一性状中均显著且PPLEIO<5×10-8的SNPs)
rs6691053-0.021.60×10-085.88×10-28ANKRD45, CENPL, DARS2, GAS5, GAS5-AS1, KLHL20, LOC730159, RABGAP1L, RC3H1, SERPINC1, SLC9C2, SNORD44, SNORD47, SNORD74, SNORD75, SNORD76, SNORD77, SNORD78, SNORD79, SNORD80, SNORD81, ZBTB37
rs728086120.058.60×10-221.48×10-42EML6, SPTBN1
rs20483700.045.50×10-531.73×10-110EML6, RPL23AP32, SPTBN1
rs112828099-0.025.20×10-092.20×10-21ATR, PCOLCE2, PLS1, TRPC1, XRN1
rs2726518-0.012.00×10-102.29×10-20PPA2, TET2
rs16877149-0.023.20×10-106.52×10-23EIF3E, EMC2, RSPO2
rs20056170.011.10×10-105.51×10-17DCAF12, KIF24, LINC01251, PRSS3, PTENP1, PTENP1-AS, SNORD121A, SNORD121B, UBAP1, UBAP2, UBE2R2
rs35677603-0.011.40×10-081.18×10-23ACP2, ARFGAP2, C11orf49, DDB2, MADD, MIR6745, MYBPC3, NR1H3, PACSIN3
rs11228240-0.048.00×10-774.30×10-152GAL, LRP5, PPP6R3
rs111691620.012.80×10-102.47×10-20BCDIN3D, BCDIN3D-AS1, FAIM2, NCKAP5L
rs28929474-0.032.60×10-075.11×10-25PPP4R4, SERPINA1, SERPINA2, SERPINA6, SERPINA10
rs787338830.038.10×10-106.96×10-21CHTF8, CIRH1A, COG8, CYB5B, HAS3, MIR1538, NFAT5, NIP7, NOB1, NQO1, PDF, SNTB2, TANGO6, TERF2, TMED6, VPS4A, WWP2
rs9788803-0.026.40×10-123.40×10-22MIR1538, NFAT5, NOB1, NQO1, WWP2
rs1121115420.025.60×10-102.70×10-16DPH1, HIC1, LOC101927839, MIR132, MIR212, OVCA2, SMG6, SRR
连锁不平衡的共享SNPs(单一性状GWAS未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且与已知SNPs连锁不平衡)
rs2300669-0.015.20×10-069.25×10-12ACVR2B, ACVR2B-AS1, EXOG, XYLB
rs28806630.013.70×10-074.10×10-13SLC5A11, TNRC6A
rs729026900.012.20×10-061.23×10-16SETBP1, SLC14A2
), ArticleFig(id=1311350177122845582, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=CN, label=表2, caption=

每周饮酒量与估算骨密度间显著的多效性位点

, figureFileSmall=null, figureFileBig=null, tableContent=
SNP染色体碱基位置效应/非效应等位基因DrnkWk
βP值
已知的共享SNPs(在两个性状中均显著且PPLEIO<5×10-8的SNPs)
rs10066412551304343T/A-0.015.34×10-09
rs104912785132884744C/A-0.012.96×10-08
rs108386131146690228C/A-0.019.92×10-09
rs71073561147654618G/A0.011.12×10-16
rs560946411653772541G/A-0.011.06×10-10
rs26846411745442752G/A-0.021.31×10-20
rs559381361745720994G/A-0.021.22×10-27
rs626419671745969850G/T-0.031.74×10-30
rs13783581746709946T/C-0.023.83×10-25
单性状驱动的共享SNPs(在单一性状中均显著且PPLEIO<5×10-8的SNPs)
rs66910531173899817T/C-0.011.24×10-10
rs72808612254808212C/T0.027.92×10-07
rs2048370254659468C/T0.019.25×10-06
rs1128280993142438693A/G0.011.68×10-06
rs27265184105252042C/A-0.014.97×10-06
rs168771498108077969A/G-0.019.64×10-06
rs2005617933791166C/T-0.012.48×10-06
rs356776031147246759T/C-0.016.27×10-11
rs112282401168450822T/C-0.018.22×10-06
rs111691621249813343C/T-0.011.70×10-06
rs289294741494378610T/C-0.053.28×10-14
rs787338831669412045A/G-0.021.37×10-06
rs97888031669658092T/A0.013.44×10-07
rs112111542172287092C/T0.018.62×10-06
连锁不平衡的共享SNPs(单一性状GWAS未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且与已知SNPs连锁不平衡)
rs2300669338499827A/C-0.013.12×10-07
rs28806631624766425T/G-0.015.94×10-06
rs729026901845186271G/A-0.012.09×10-07
SNPeBMDPPLEIO聚类范围内的基因
βP值
已知的共享SNPs(在两个性状中均显著且PPLEIO<5×10-8的SNPs)
rs10066412-0.021.60×10-143.01×10-33ISL1, LOC642366
rs104912780.021.80×10-134.09×10-34AFF4, GDF9, HSPA4, LEAP2, SHROOM1, SOWAHA, UQCRQ, ZCCHC10
rs10838613-0.032.70×10-221.27×10-46AMBRA1, ARFGAP2, ARHGAP1, ATG13, C11orf49, CHRM4, CKAP5, CREB3L1, DGKZ, F2, HARBI1, LRP4, LRP4-AS1, MDK, MIR3160-1, MIR3160-2, MIR4688, MIR5582, MIR6745, PACSIN3, SNORD67, ZNF408
rs7107356-0.014.20×10-094.36×10-25AGBL2, C1QTNF4, CELF1, FAM180B, FNBP4, KBTBD4, MTCH2, MYBPC3, NDUFS3, NUP160, PSMC3, PTPMT1, RAPSN, SLC39A13, SPI1
rs560946410.026.80×10-209.78×10-43FTO
rs2684641-0.022.00×10-201.32×10-74ARHGAP27, MIR4315-1, MIR4315-2, PLEKHM1
rs55938136-0.021.60×10-211.93×10-76CRHR1
rs62641967-0.029.10×10-215.13×10-87CRHR1, CRHR1-IT1, KANSL1, KANSL1-AS1, LOC644172, LRRC37A4P, MAPT, MAPT-AS1, MAPT-IT1, MGC57346, MIR4315-1, MIR4315-2, PLEKHM1, SPPL2C, STH
rs1378358-0.022.50×10-172.63×10-69NSF, WNT3
单性状驱动的共享SNPs(在单一性状中均显著且PPLEIO<5×10-8的SNPs)
rs6691053-0.021.60×10-085.88×10-28ANKRD45, CENPL, DARS2, GAS5, GAS5-AS1, KLHL20, LOC730159, RABGAP1L, RC3H1, SERPINC1, SLC9C2, SNORD44, SNORD47, SNORD74, SNORD75, SNORD76, SNORD77, SNORD78, SNORD79, SNORD80, SNORD81, ZBTB37
rs728086120.058.60×10-221.48×10-42EML6, SPTBN1
rs20483700.045.50×10-531.73×10-110EML6, RPL23AP32, SPTBN1
rs112828099-0.025.20×10-092.20×10-21ATR, PCOLCE2, PLS1, TRPC1, XRN1
rs2726518-0.012.00×10-102.29×10-20PPA2, TET2
rs16877149-0.023.20×10-106.52×10-23EIF3E, EMC2, RSPO2
rs20056170.011.10×10-105.51×10-17DCAF12, KIF24, LINC01251, PRSS3, PTENP1, PTENP1-AS, SNORD121A, SNORD121B, UBAP1, UBAP2, UBE2R2
rs35677603-0.011.40×10-081.18×10-23ACP2, ARFGAP2, C11orf49, DDB2, MADD, MIR6745, MYBPC3, NR1H3, PACSIN3
rs11228240-0.048.00×10-774.30×10-152GAL, LRP5, PPP6R3
rs111691620.012.80×10-102.47×10-20BCDIN3D, BCDIN3D-AS1, FAIM2, NCKAP5L
rs28929474-0.032.60×10-075.11×10-25PPP4R4, SERPINA1, SERPINA2, SERPINA6, SERPINA10
rs787338830.038.10×10-106.96×10-21CHTF8, CIRH1A, COG8, CYB5B, HAS3, MIR1538, NFAT5, NIP7, NOB1, NQO1, PDF, SNTB2, TANGO6, TERF2, TMED6, VPS4A, WWP2
rs9788803-0.026.40×10-123.40×10-22MIR1538, NFAT5, NOB1, NQO1, WWP2
rs1121115420.025.60×10-102.70×10-16DPH1, HIC1, LOC101927839, MIR132, MIR212, OVCA2, SMG6, SRR
连锁不平衡的共享SNPs(单一性状GWAS未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且与已知SNPs连锁不平衡)
rs2300669-0.015.20×10-069.25×10-12ACVR2B, ACVR2B-AS1, EXOG, XYLB
rs28806630.013.70×10-074.10×10-13SLC5A11, TNRC6A
rs729026900.012.20×10-061.23×10-16SETBP1, SLC14A2
), ArticleFig(id=1311350177219314575, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=EN, label=Table 3, caption=

Novel Significant Pleiotropic loci between DrnkWk and eBMD

, figureFileSmall=null, figureFileBig=null, tableContent=
SNP染色体碱基位置效应/非效应等位基因DrnkWk
βP值
新发现的共享SNPs(两个性状均未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且不与已知SNPs连锁不平衡)
rs74054769115533652C/A-0.016.32×10-06
rs146016966115789386T/C-0.026.24×10-06
rs11587434172149435A/G-0.011.10×10-06
rs60762909273646375T/C0.013.20×10-06
rs11885942299387702G/A-0.015.27×10-06
rs592433382143527665C/T-0.013.04×10-06
rs8434612239397395T/C0.011.69×10-06
rs754941381146443811T/C0.021.71×10-06
rs7479886514103921780T/A-0.014.41×10-06
SNPeBMDPPLEIO聚类范围内的基因
βP值
新发现的共享SNPs(两个性状均未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且不与已知SNPs连锁不平衡)
rs740547690.017.50×10-062.57×10-10AGMAT, CASP9, CELA2A, CELA2B, DDI2, DNAJC16, PLEKHM2, RSC1A1
rs1460169660.032.00×10-085.62×10-15AGMAT, C1orf64, CLCNKA, CLCNKB, DDI2, DNAJC16, FAM131C, FBLIM1, FLJ37453, HSPB7, PLEKHM2, RSC1A1, SLC25A34, SPEN, TMEM82, UQCRHL, ZBTB17
rs115874340.011.00×10-061.28×10-14NEGR1
rs607629090.013.30×10-061.26×10-12ALMS1, ALMS1-IT1, ALMS1P, NAT8, NAT8B
rs118859420.019.30×10-082.71×10-15AFF3, C2orf15, EIF5B, LIPT1, LYG1, LYG2, MITD1, MRPL30, REV1, TSGA10, TXNDC9
rs59243338-0.014.30×10-081.39×10-18ARHGAP15
rs843461-0.014.40×10-082.79×10-13HDAC4
rs754941380.023.90×10-067.04×10-15AMBRA1, CHRM4, CREB3L1, DGKZ, MDK, MIR3160-1, MIR3160-2, MIR4688
rs74798865-0.021.30×10-067.56×10-14C14orf2, RD3L, TDRD9
), ArticleFig(id=1311350177370309520, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=CN, label=表3, caption=

新发现的每周饮酒量与估算骨密度间显著的多效性位点

, figureFileSmall=null, figureFileBig=null, tableContent=
SNP染色体碱基位置效应/非效应等位基因DrnkWk
βP值
新发现的共享SNPs(两个性状均未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且不与已知SNPs连锁不平衡)
rs74054769115533652C/A-0.016.32×10-06
rs146016966115789386T/C-0.026.24×10-06
rs11587434172149435A/G-0.011.10×10-06
rs60762909273646375T/C0.013.20×10-06
rs11885942299387702G/A-0.015.27×10-06
rs592433382143527665C/T-0.013.04×10-06
rs8434612239397395T/C0.011.69×10-06
rs754941381146443811T/C0.021.71×10-06
rs7479886514103921780T/A-0.014.41×10-06
SNPeBMDPPLEIO聚类范围内的基因
βP值
新发现的共享SNPs(两个性状均未达到全基因组显著性水平但Psingle-trait<1.0×10-5,PPLEIO<5×10-8,且不与已知SNPs连锁不平衡)
rs740547690.017.50×10-062.57×10-10AGMAT, CASP9, CELA2A, CELA2B, DDI2, DNAJC16, PLEKHM2, RSC1A1
rs1460169660.032.00×10-085.62×10-15AGMAT, C1orf64, CLCNKA, CLCNKB, DDI2, DNAJC16, FAM131C, FBLIM1, FLJ37453, HSPB7, PLEKHM2, RSC1A1, SLC25A34, SPEN, TMEM82, UQCRHL, ZBTB17
rs115874340.011.00×10-061.28×10-14NEGR1
rs607629090.013.30×10-061.26×10-12ALMS1, ALMS1-IT1, ALMS1P, NAT8, NAT8B
rs118859420.019.30×10-082.71×10-15AFF3, C2orf15, EIF5B, LIPT1, LYG1, LYG2, MITD1, MRPL30, REV1, TSGA10, TXNDC9
rs59243338-0.014.30×10-081.39×10-18ARHGAP15
rs843461-0.014.40×10-082.79×10-13HDAC4
rs754941380.023.90×10-067.04×10-15AMBRA1, CHRM4, CREB3L1, DGKZ, MDK, MIR3160-1, MIR3160-2, MIR4688
rs74798865-0.021.30×10-067.56×10-14C14orf2, RD3L, TDRD9
), ArticleFig(id=1311350177470972817, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=EN, label=Table 4, caption=

Significant Pleiotropic genes between DrnkWk and eBMD

, figureFileSmall=null, figureFileBig=null, tableContent=
基因名染色体起始碱基位置终止碱基位置DrnkWkeBMD
NSNPsZ值P值NSNPsZ值P值
已知的共享基因
AUTS2769 063 90570 257 8854 1387.4773.82×10-144 1344.7719.16×10-07
BDNF1127 676 44027 743 6051695.4822.11×10-082006.1095.00×10-10
CREB3L11146 299 18946 342 9721484.8685.63×10-071427.7733.83×10-15
AGBL21147 681 14347 736 9281847.8661.83×10-151994.7081.25×10-06
FTO1653 737 87554 148 3791 8925.4113.13×10-081 8589.2221.46×10-20
SLC14A21842 792 94743 263 0721 9895.2965.91×10-082 3064.8237.07×10-07
单性状驱动的共享基因
BMPR1B495 679 12896 079 6012 1745.7145.50×10-091 8595.6498.07×10-09
CYP3A4799 354 58399 381 811935.2607.19×10-08664.5782.35×10-06
DGKZ1146 354 45546 402 1041175.9981.00×10-091266.6441.53×10-11
AMBRA11146 417 96246 615 6194146.3441.12×10-104496.1095.00×10-10
HARBI11146 624 85646 638 933275.9271.54×10-09317.2831.64×10-13
ATG131146 638 82646 697 5691426.1095.00×10-101416.8035.11×10-12
ARHGAP11146 698 62546 722 215666.0377.86×10-10706.1095.00×10-10
F21146 740 74346 761 056455.5231.67×10-08856.1095.00×10-10
LRP41146 878 26846 940 1731734.8526.12×10-071796.1095.00×10-10
DDB21147 236 49347 260 7691024.6701.50×10-06816.1095.00×10-10
MYBPC31147 352 95747 374 2531067.2452.17×10-13727.6599.38×10-15
CPT1A1168 522 08868 611 8782674.6211.91×10-062919.0964.71×10-20
DNAH2177 620 6317 737 0585276.2472.09×10-104965.0492.23×10-07
COPZ21746 103 53346 120 9081196.1095.00×10-10636.8184.62×10-12
NFE2L11746 125 68646 138 907917.4743.89×10-14436.5642.61×10-11
CBX11746 147 41446 178 8832207.0687.88×10-131215.9581.28×10-09
SNX111746 184 91146 200 1091016.1095.00×10-10635.5371.54×10-08
全新的共享基因
NR1H31147 269 85147 290 584685.5981.08×10-08717.4883.50×10-14
MADD1147 290 92747 351 5821964.9603.52×10-072206.1095.00×10-10
MTL51168 474 90868 518 9881524.5462.73×10-061337.0548.67×10-13
SLC11A21251 373 56651 422 1181775.8812.04×10-091686.0776.11×10-10
CSRNP21251 454 98851 477 454555.7923.48×10-09835.1421.36×10-07
TFCP21251 487 53951 566 9262446.1095.00×10-103166.0009.90×10-10
PNPO1746 018 88946 026 674377.6728.55×10-15265.7833.68×10-09
), ArticleFig(id=1311350177563247506, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350168713266000, language=CN, label=表4, caption=

每周饮酒量与估算骨密度间显著的基因

, figureFileSmall=null, figureFileBig=null, tableContent=
基因名染色体起始碱基位置终止碱基位置DrnkWkeBMD
NSNPsZ值P值NSNPsZ值P值
已知的共享基因
AUTS2769 063 90570 257 8854 1387.4773.82×10-144 1344.7719.16×10-07
BDNF1127 676 44027 743 6051695.4822.11×10-082006.1095.00×10-10
CREB3L11146 299 18946 342 9721484.8685.63×10-071427.7733.83×10-15
AGBL21147 681 14347 736 9281847.8661.83×10-151994.7081.25×10-06
FTO1653 737 87554 148 3791 8925.4113.13×10-081 8589.2221.46×10-20
SLC14A21842 792 94743 263 0721 9895.2965.91×10-082 3064.8237.07×10-07
单性状驱动的共享基因
BMPR1B495 679 12896 079 6012 1745.7145.50×10-091 8595.6498.07×10-09
CYP3A4799 354 58399 381 811935.2607.19×10-08664.5782.35×10-06
DGKZ1146 354 45546 402 1041175.9981.00×10-091266.6441.53×10-11
AMBRA11146 417 96246 615 6194146.3441.12×10-104496.1095.00×10-10
HARBI11146 624 85646 638 933275.9271.54×10-09317.2831.64×10-13
ATG131146 638 82646 697 5691426.1095.00×10-101416.8035.11×10-12
ARHGAP11146 698 62546 722 215666.0377.86×10-10706.1095.00×10-10
F21146 740 74346 761 056455.5231.67×10-08856.1095.00×10-10
LRP41146 878 26846 940 1731734.8526.12×10-071796.1095.00×10-10
DDB21147 236 49347 260 7691024.6701.50×10-06816.1095.00×10-10
MYBPC31147 352 95747 374 2531067.2452.17×10-13727.6599.38×10-15
CPT1A1168 522 08868 611 8782674.6211.91×10-062919.0964.71×10-20
DNAH2177 620 6317 737 0585276.2472.09×10-104965.0492.23×10-07
COPZ21746 103 53346 120 9081196.1095.00×10-10636.8184.62×10-12
NFE2L11746 125 68646 138 907917.4743.89×10-14436.5642.61×10-11
CBX11746 147 41446 178 8832207.0687.88×10-131215.9581.28×10-09
SNX111746 184 91146 200 1091016.1095.00×10-10635.5371.54×10-08
全新的共享基因
NR1H31147 269 85147 290 584685.5981.08×10-08717.4883.50×10-14
MADD1147 290 92747 351 5821964.9603.52×10-072206.1095.00×10-10
MTL51168 474 90868 518 9881524.5462.73×10-061337.0548.67×10-13
SLC11A21251 373 56651 422 1181775.8812.04×10-091686.0776.11×10-10
CSRNP21251 454 98851 477 454555.7923.48×10-09835.1421.36×10-07
TFCP21251 487 53951 566 9262446.1095.00×10-103166.0009.90×10-10
PNPO1746 018 88946 026 674377.6728.55×10-15265.7833.68×10-09
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全基因组跨性状关联分析揭示饮酒与骨密度的共享遗传基础
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郑思睿 1 , 韩韬 1 , 于婷 2 , 周进宇 1 , 姜侠 1, 2 , 赵琴 3
现代预防医学 | 健康与社会行为 2026,53(14): 2639-2647
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现代预防医学 |健康与社会行为 2026 , 53 (14) : 2639 -2647
全基因组跨性状关联分析揭示饮酒与骨密度的共享遗传基础
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郑思睿1, 韩韬1, 于婷2, 周进宇1, 姜侠1, 2, 赵琴3
作者信息
  • 1.四川大学华西公共卫生学院/四川大学华西第四医院营养与食品卫生学,四川 成都 610041
  • 2.四川大学华西公共卫生学院/四川大学华西第四医院流行病与统计学
  • 3.四川大学华西公共卫生学院/四川大学华西第四医院超声医学科
通讯作者:
赵琴,E-mail:
作者简介:

郑思睿(2000—),女,硕士在读,研究方向:营养与食品卫生学

Genome-wide cross-trait association analysis reveals the shared genetic architecture between alcohol consumption and bone mineral density
Si-rui ZHENG1, Tao HAN1, Ting YU2, Jin-yu ZHOU1, Xia JIANG1, 2, Qin ZHAO3
Affiliations
  • Department of Nutrition and Food Hygiene, West China School of Public Health/West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2026-07-25 doi: 10.20043/j.cnki.MPM.202601227
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目的

系统解析每周饮酒量(DrnkWk)与成人估算骨密度(eBMD)的遗传关联及共享机制。

方法

基于英国生物银行和GSCAN联盟的大规模全基因组关联研究汇总数据,采用连锁不平衡分数回归(LDSC)、局部遗传相关性分析(SUPERGNOVA)、跨性状荟萃分析(PLEIO)、基因水平关联分析(MAGMA)及双向孟德尔随机化(MR)方法,全面评估DrnkWk与eBMD的遗传相关性、多效性基因位点及因果关联。

结果

DrnkWk与eBMD在全基因组水平未观察到显著遗传相关性(rg=-0.018, 95% CI: -0.050~0.014, P=0.26),但SUPERGNOVA鉴定出3个显著信号区域。PLEIO共发现35个多效性位点(含9个新发位点),MAGMA分析识别出30个显著的多效性基因。双向MR分析未发现两性状间存在显著因果关联(正向MR:β=-0.051, P=0.12;反向MR:β=-0.009, P=0.08)。

结论

饮酒与骨密度的流行病学关联主要源于共享的生物学通路与多效性遗传架构,而非直接因果效应,为骨质疏松的遗传风险分层与靶向干预提供了新思路。

饮酒  /  骨密度  /  全基因组关联研究  /  遗传多效性  /  孟德尔随机化
Objective

To systematically investigate the genetic association and shared biological mechanisms between weekly alcohol consumption (DrnkWk) and estimated heel bone mineral density (eBMD) in adults.

Methods

Leveraging large-scale genome-wide association study (GWAS) summary statistics from the UK Biobank and the GSCAN consortium, we integrated linkage disequilibrium score regression (LDSC), local genetic correlation analysis (SUPERGNOVA), cross-trait meta-analysis (PLEIO), gene-based association analysis (MAGMA), and bidirectional two-sample Mendelian randomization (MR) to comprehensively assess global and local genetic correlations, pleiotropic loci, and causal relationships between DrnkWk and eBMD.

Results

No significant genome-wide genetic correlation was observed (rg=-0.018, 95%CI: -0.050-0.014, P=0.26); while SUPERGNOVA identified 3 genomic regions with significant local genetic correlations. PLEIO revealed 35 pleiotropic loci (including 9 novel loci), and MAGMA implicated 30 shared genes. Bidirectional MR provided no evidence of a causal effect (forward MR:β=-0.051, P=0.12; reverse MR:β=-0.009, P=0.08).

Conclusion

The epidemiological association between alcohol consumption and bone density is likely driven by shared biological pathways and pleiotropic genetic architecture rather than direct causality, offering new insights for genetic risk stratification and targeted prevention strategies for osteoporosis.

Alcohol consumption  /  Bone mineral density  /  Genome-wide association study  /  Genetic pleiotropy  /  Mendelian randomization
郑思睿, 韩韬, 于婷, 周进宇, 姜侠, 赵琴. 全基因组跨性状关联分析揭示饮酒与骨密度的共享遗传基础. 现代预防医学, 2026 , 53 (14) : 2639 -2647 . DOI: 10.20043/j.cnki.MPM.202601227
Si-rui ZHENG, Tao HAN, Ting YU, Jin-yu ZHOU, Xia JIANG, Qin ZHAO. Genome-wide cross-trait association analysis reveals the shared genetic architecture between alcohol consumption and bone mineral density[J]. Modern Preventive Medicine, 2026 , 53 (14) : 2639 -2647 . DOI: 10.20043/j.cnki.MPM.202601227
骨质疏松症(osteoporosis, OP)是以骨密度(bone mineral density, BMD)降低和骨微结构破坏为核心特征的代谢性骨病,可显著增加骨脆性和骨折风险[1],是全球老龄化背景下的重大公共卫生挑战。据统计,全球OP患者约2亿人,每年骨质疏松性骨折超900万例[2],严重损害患者的生活质量,也带来了沉重的经济负担。
饮酒作为全球疾病负担的重要行为危险因素,其与BMD及OP的关联备受关注。其中,每周饮酒量作为量化饮酒行为的核心指标,被广泛用于评估饮酒对骨骼健康的长期影响。尽管临床实践证实饮酒是BMD降低的临床风险因素[3-6],现有关于饮酒与OP关联的流行病学证据仍存在争议。一项纳入11项观察性研究的meta分析显示,轻度至中度饮酒者的BMD显著高于不饮酒者[7];相反,另一项涵盖8项前瞻性队列研究的伞状meta分析则表明,饮酒量越低,OP发病风险越低[8]。但这些观察性研究结果可能受到偏倚、混杂因素或反向因果关系的影响[9]。
全基因组关联研究(genome-wide association studies, GWAS)为突破传统流行病学研究的局限提供了可行途径。既往一项遗传学研究报告每周饮酒量与估算骨密度(estimated heel bone mineral density, eBMD)的遗传相关性无统计学意义(rg=-0.013, P=0.48)[10]。但整体遗传相关分析常存在因共享遗传变异的效应方向混杂而统计效力不足的问题[11],通过区域或变异水平分析可以更精准地量化共享遗传成分[12]。一项双变量GWAS研究已识别出多个同时影响饮酒行为与多部位BMD的多效性遗传位点(如DYNC2H1、GRIK4、OPRM1、IL1RN)[13],提示饮酒与OP的表型关联至少在局部可以由共享遗传因素解释。然而,这类遗传关联的性质与程度仍有待进一步明确。
孟德尔随机化(Mendelian randomization, MR)以遗传变异作为工具变量(instrumental variables, IVs),可有效减少混杂因素和反向因果关系的干扰,推断暴露对结局的因果效应[14]。目前已有3项MR研究探讨饮酒与BMD的潜在因果关联,但结论存在矛盾。其中两项研究均未发现每周饮酒量与eBMD存在显著因果关联[15-16],而Choi等人的单样本MR研究仅采用1个IV,发现饮酒对男性髋部和腰椎BMD存在保护作用[17],但有限的IVs数量可能降低该研究的统计效力与结果可靠性,存在假阳性风险。随GWAS样本量持续扩大,纳入更多与饮酒行为相关的IVs,并结合能够有效校正多效性的新型分析策略,对既往存在矛盾的研究发现进行重新评估。
为深入探究饮酒与eBMD的遗传学关联,本研究基于迄今最大规模的GWAS数据,采用全基因组跨性状分析方法,系统解析两个表型的共享遗传基础,识别影响二者的多效性位点,并通过双向两样本MR进行因果推断。整体研究设计旨在扩展既往研究结果,揭示饮酒和eBMD之间的多效性效应,为识别潜在药物靶点、发展基于共享通路的精准预防策略提供遗传学依据。
迄今为止规模最大的饮酒GWAS汇总数据来源于GSCAN(https://gscan.psych.umn.edu/)的meta分析[10],以每周饮酒量(drinks per week, DrnkWk)为量化指标,共纳入2 428 851名欧洲受试者。研究报道了501个全基因组显著性(P<5×10-9)的独立单核苷酸多态性位点(single nucleotide polymorphisms, SNPs),作为本研究MR分析中的IVs。
eBMD GWAS汇总数据来源GEFOS联盟(http://www.gefos.org/)基于英国生物样本库(UK Biobank,UKB)的研究[18],共纳入462 824名欧洲受试者。研究报道了1 078个全基因组显著(P<6.6×10-9)的独立SNPs,作为本研究MR分析中的IVs。
上述原始研究均已通过伦理审查并获取受试者知情同意,基本信息详见表1。
采用连锁不平衡分数回归(linkage disequilibrium score regression, LDSC)[19]评估DrnkWk与eBMD的全基因组遗传关联,使用基于1000 Genomes欧洲人群预计算的LD分数文件(eur_w_ld_chr.tar.gz,Version v1),估算两性状间的遗传相关系数(rg),量化两性状在全基因组范围内共享遗传效应的方向与强度,其取值范围为-1至+1。
采用SUPERGNOVA开展局部遗传相关性分析[12],识别对DrnkWk与eBMD之间共享遗传有突出贡献的特定区域。参考1000 Genomes Project欧洲人群的LD结构,以r2<0.05为阈值,将全基因组划分为约2 353个相互独立的LD区域,在每个区块内量化两性状的局部遗传相关性,反映区域水平的遗传结构重叠。统计显著性阈值采用Bonferroni校正(P<0.05/2 353)。
遗传相关性分析提示两个性状间有共享的遗传结构,但这可以来源于两个部分:一是水平多效性(horizontal pleiotropy),简称多效性,即单个遗传变异同时对两个或多个性状有独立的影响,是局部遗传相关性的底层生物学基础;二是垂直多效性(vertical pleiotropy),也就是因果效应,即遗传变异通过对一个性状的影响来影响另一个性状。本研究采用Pleiotropic Locus Exploration and Interpretation using Optimal test(PLEIO)方法进行跨性状全基因组meta分析,探索DrnkWk与eBMD共享的多效性位点。通过PLINK软件的clump函数识别独立的多效性位点[20](--clump-pl 5e-8 --clump-p2 le-5 --clump-r2 0.2 --clump-kb 250),参考既往GWAS研究的显著性阈值[21-22],将具有统计学显著性的多效性位点定义为PPLEIO<5.0×10-8且单个性状的P值(Psingle-trait)<1.0×10-5。为进一步探索这些多效性位点的生物学意义,利用Ensembl Variant Effect Predictor(VEP)工具[23],基于最邻近基因原则筛选候选基因,为功能注释和机制研究提供线索。
采用Multi-marker Analysis of GenoMic Annotation(MAGMA)软件进行基因水平关联分析[24],识别在DrnkWk与eBMD中具有多效性的基因。MAGMA通过多重回归模型整合映射至同一基因的所有SNP的联合效应,利用参考人群的LD结构校正SNP间相关性,从而有效避免假阳性。MAGMA采用NCBI 37.3基因注释文件进行基因映射,窗口为基因转录起始位点上下游35kb。根据映射基因总数(DrnkWk映射17 926个基因,eBMD映射18 873个基因),以Bonferroni校正后的P<0.05为显著性阈值。
采用双向两样本MR分析评估DrnkWk与eBMD之间的因果关联。以逆方差加权法(Inverse-Variance Weighted, IVW)为主要分析方法[25],以MR-Egger回归和加权中位数法(Weighted Median)作为敏感性检验[26-27]。通过剔除回文SNPs和多效性SNPs(检索GWAS Catalog数据发现与混杂因素显著关联的SNPs)进一步验证结果的稳健性。此外,计算IVs对应的F统计量(F=β2/se2)评估弱工具变量偏倚,F值>10被认为无显著弱工具偏倚。
尽管未发现DrnkWk与eBMD之间存在显著的全基因组水平遗传相关性(rg=-0.018, 95%CI: -0.050~0.014, P=0.26),但在将全基因组划分为2 353个独立LD区域后,SUPERGNOVA识别出3个显著信号(3p22.2、11q13.2和14q32.31)(图1)。
其中最显著的局部遗传相关信号位于11q13.2区域(chr11:66 835 372-68 515 239;P=6.05×10-7),该区域包含基因PPP6R3,该基因同时与每周饮酒量及全身BMD显著相关[10,28,29]。其次显著的信号位于3p22.2区域(chr3:38 080 101-38 723 967;P=8.46×10-7),该区域包含XYLB、ACVR2B和EXOG等多个基因,均被既往研究证实与饮酒行为显著相关[10,30]。另一显著信号位于14q32.31(chr14: 102 341 650-104 759 919;P=1.23×10-5),其中包含MARK3基因,同时与eBMD和每周饮酒量存在关联[10,18]。
PLEIO共鉴定出35个达到显著的多效性位点(PPLEIO<5×10-8),其中“单性状驱动的”共享位点14个,“已知的”共享位点9个(表2),全新的多效性位点9个(表3)。
在“已知的”共享位点中,最显著的位点是rs62641967(PPLEIO =5.13×10-87),定位于17q21.31区域,覆盖CRHR1、MAPT等基因,其中CRHR1是下丘脑-垂体-肾上腺轴的关键调控因子[31],已被证实与成人酒精依赖患者的大量饮酒行为和eBMD相关[32-33]。另一代表性位点rs10838613(PPLEIO=1.27×10-46)位于11p11.2区域,映射CREB3L1等基因。CREB3L1编码一个内质网应激激活的转录因子,在成骨细胞分化和骨基质矿化过程中发挥关键作用[34]。此外,rs56094641(PPLEIO=9.78×10-43)位于16q12.2区域,映射的FTO基因是肥胖和能量代谢的核心调控因子,与每周饮酒量高度相关[35]。
此外,本研究还鉴定了9个全新的多效性位点,其在任一单性状GWAS中虽未达到全基因组显著水平但Psingle-trait<1.0×10-5,且不与已知SNPs连锁不平衡。其中,rs75494138(PPLEIO =7.04×10-15)位于11q13.2,同样映射到CREB3L1基因。另外,rs59243338(PPLEIO=1.39×10-18)定位于2q22.2-q22.3,映射的ARHGAP15基因编码Rho GTP酶激活蛋白,调控细胞骨架动态[36];rs74798865(PPLEIO=7.56×10-14)位于14q32.33,覆盖TDRD9等基因,参与piRNA通路与生殖细胞发育过程[37]。
MAGMA共识别30个显著的多效性基因,通过GWAS Catalog检索是否已报道与DrnkWk和eBMD显著相关,发现其中包括17个“单性状驱动的”共享基因,6个“已知的”共享基因,此外还鉴定出7个全新的多效性基因(表4)。
在“已知的”共享基因中AGBL2(PDrnkWk=1.83×10-15;PeBMD=1.25×10-6)、FTO(PDrnkWk=3.13×10-8;PeBMD=1.46×10-20)、CREB3L1(PDrnkWk=5.63×10-7;PeBMD=3.83×10-15)均在前述PLEIO分析中被鉴定出来,提示这些基因在DrnkWk与eBMD关联中的潜在作用。
本研究鉴定的7个全新的共享基因中,NR1H3(PDrnkWk=1.08×10-8;PeBMD=3.50×10-14)位于11p11.2,在肝脏、脂肪组织、巨噬细胞等部位中高度表达,参与脂质稳态和炎症反应等生物过程[38];MTL5(PDrnkWk=2.67×10-6;PeBMD=8.67×10-13)位于11q13.2-q13.3,在高BMD人群中呈现出高表达[39];MADD(PDrnkWk=3.52×10-7;PeBMD=5.00×10-10)位于11p11.2,可以通过激活MAP激酶调节细胞的应激反应和凋亡信号[40]。
本研究采用双向两样本MR评估DrnkWk与eBMD的潜在因果关系。所选IVs的平均F统计量大于70,提示弱工具变量偏倚可忽略不计。在以DrnkWk为暴露,eBMD为结局的正向MR分析中,IVW法结果显示,DrnkWk对eBMD无显著因果效应(β=-0.051,P=0.12)。进一步的敏感性分析以及剔除回文SNP或多效性SNP后重复分析均得到一致结论(图2)。在反向MR分析中(以eBMD为暴露,DrnkWk为结局),同样未发现eBMD对饮酒存在因果关联(β=-0.009,P=0.08)。
本研究基于迄今最大规模的每周饮酒量与估算骨密度GWAS汇总数据,整合遗传相关性、多效性位点、基因水平关联及因果推断,全面解析酒精摄入与eBMD之间的遗传基础。尽管二者的全基因组遗传相关性并不显著,但在三个特定基因组区域存在显著的局部共享遗传基础。该结果也得到跨性状关联分析所鉴定的35个多效性位点及基因水平关联研究识别的30个共享基因的验证。综合证据表明,每周饮酒量与eBMD之间的流行病学关联更可能源于共享的生物学通路或致病机制,而非直接的因果效应。
本研究的全基因组遗传相关结果与既往大型研究的结论一致[10]。但通过SUPERGNOVA成功识别出三个具有高度统计学意义的局部遗传相关信号。其中,11q13.2区域信号最为突出,该区域包含的PPP6R3基因是蛋白磷酸酶6的调节亚基,既是调控股骨几何形态、骨密度及椎体微结构的关键因子[29],也被证实与饮酒行为相关[10],提示其可能作枢纽基因协调物质代谢与骨代谢过程。
本研究双向MR分析结果与既往两项MR研究一致,均未发现每周饮酒量与BMD之间存在显著的因果关联[15,16]。需注意的是,本研究基于大样本GWAS数据,纳入多种MR敏感性分析方法,统计效能虽已大幅提升,但仍不能排除饮酒与BMD之间的真实因果效应极其微弱、现有样本量不足以稳定检出的可能。而另一项仅依赖单个IV的单样本MR研究报道,男性每日饮酒对全髋BMD(β=0.01 g/cm2,95%CI: 0.004~0.010)和腰椎BMD(β=0.01 g/cm2,95%CI: 0.005~0.013)具有保护作用[17]。这一不一致很可能源于该研究IVs数量严重不足,分析易受水平多效性或潜在混杂因素的影响[25],统计效能与结果可靠性存在局限。
此外,PLEIO和MAGMA分析共同揭示了丰富的多效性遗传区域。PLEIO分析识别的35个显著的多效性位点中,有多个基因座位于局部遗传相关显著区域。其中,rs10838613和rs75494138共同映射了CREB3L1基因。该基因编码的转录因子是成骨细胞分化、胶原合成及骨基质矿化的关键调控因子,其功能缺失可导致严重骨发育异常[34]。CREB3L1同时作为神经内分泌调控枢纽参与应激响应[41],而酒精暴露可诱导内质网应激并改变CREB3L1的剪切活化状态[42],提示CREB3L1可能通过“神经-骨骼轴”同时影响应激相关饮酒行为与骨代谢稳态。
MAGMA分析进一步确认了30个显著的多效性基因,除CREB3L1外,FTO基因也在PLEIO和MAGMA分析中被重复识别。FTO是能量平衡与脂质代谢的核心调控因子[43],既与高热量饮食偏好及酒精摄入增加相关[44],也可通过调控RNA m6A甲基化修饰影响成骨/破骨细胞谱系决定,介导脂肪组织对骨微环境的旁分泌调节[45]。其双重调控作用为饮酒-骨密度关联提供了合理的生物学解释。此外,全新的NR1H3基因作为胆固醇代谢与炎症感应器,其表达增加与酒精摄入高度相关[46],同时也参与调节内质网介导的成骨分化[47]。类似的,MADD基因是细胞应激反应、细胞凋亡及MAPK信号通路的核心调控因子[48],可通过激活ERK/MAPK信号通路,调控酒精暴露诱导的神经细胞凋亡与氧化应激反应[49]和成骨细胞增殖、分化与凋亡[50]。MTL5基因作为金属硫蛋白样家族成员,亦可通过调控氧化应激[51],同时参与酒精暴露的组织损伤响应与骨代谢稳态维持。
本研究具有多项优势,研究利用大规模遗传数据、充分考虑水平多效性影响,并通过多种敏感性分析严格验证孟德尔随机化模型假设。从公共卫生视角看,饮酒与eBMD通过生物学多效性相互关联,提示应加强对饮酒人群的骨质疏松风险筛查,并在骨质疏松患者管理中关注其饮酒行为。深入解析这一关联背后的共享机制,不仅有助于深化对骨生物学的理解,也为未来开发靶向共同通路的骨质疏松创新疗法提供理论依据。当然,本研究亦存在若干局限。首先,所有分析均基于欧洲血统人群,限制了结果向其他族群的外推。其次,尽管本研究对多效性位点和基因进行了深入的生物信息学注释和功能推测,但其确切的分子机制仍需通过体内外实验验证。第三,本研究纳入的GWAS数据存在一定程度的样本重叠,尽管采用了多种敏感性分析方法验证结果稳健性,仍无法完全排除样本重叠以及残余多效性的影响。此外,GWAS汇总数据无法进行性别分层分析,可能掩盖了饮酒行为和骨密度的性别特异性效应。最后,本研究仅采用eBMD作为OP的替代表型,未纳入腰椎、股骨颈等其他部位的骨密度指标,而eBMD与临床常用的腰椎、髋部BMD相关性中等,结果外推至其他骨骼部位需谨慎。未来需依托更大规模、部位特异性的GWAS数据,以明确酒精相关遗传变异对不同骨骼区域的潜在差异性影响。
综上所述,本研究基于迄今最大规模的全基因组遗传数据与先进的统计遗传学方法,系统分析发现饮酒对骨质疏松的发生无直接因果效应,但二者存在显著的生物学多效性。该结果深化了对既往观察性关联的理解,并从遗传学层面为骨质疏松的早期预防及可干预策略提供了理论依据。
  • 四川省青年科技创新研究团队项目(2024NSFTD0030)
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2026年第53卷第14期
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doi: 10.20043/j.cnki.MPM.202601227
  • 接收时间:2026-01-14
  • 首发时间:2026-09-28
  • 出版时间:2026-07-25
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  • 收稿日期:2026-01-14
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四川省青年科技创新研究团队项目(2024NSFTD0030)
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    1.四川大学华西公共卫生学院/四川大学华西第四医院营养与食品卫生学,四川 成都 610041
    2.四川大学华西公共卫生学院/四川大学华西第四医院流行病与统计学
    3.四川大学华西公共卫生学院/四川大学华西第四医院超声医学科

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种数
Number of
species
占总种数比例
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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