Cheng Shiqiang, Qi Xin, Ma Mei, Zhang Lu, Cheng Bolun, Liang Chujun, Liu Li, Li Ping, Kafle Om Prakash, Wen Yan, Zhang Feng
Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
Front Genet. 2020 Jan 31;11:6. doi: 10.3389/fgene.2020.00006. eCollection 2020.
Recent study demonstrates the comprehensive effects of gut microbiota on complex diseases or traits. However, limited effort has been conducted to explore the potential relationships between gut microbiota and BMD.
We performed a polygenetic risk scoring (PRS) analysis to systematically explore the relationships between gut microbiota and body BMD. Significant SNP sets associated with gut microbiota were derived from previous genome-wide association study (GWAS). In total, 2,294 to 5,065 individuals with BMD values of different sites and their genotype data were obtained from UK Biobank cohort. The gut microbiota PRS of each individual was computed from the SNP genotype data for each study subject of UK Biobank by PLINK software. Using computed PRS as the instrumental variables of gut microbiota, Pearson correlation analysis of individual PRS values and BMD values was finally conducted to test the potential association between gut microbiota and target trait.
In total, 31 BMD traits were selected as outcome to assess their relationships with gut microbiota. After adjusted for age, sex, body mass index, and the first 5 principal components (PCs) as the covariates using linear regression model, pelvis BMD ( = 0.0437) showed suggestive association signal with gut microbiota after multiple testing correction.
Our study findings support the weak relevance of gut microbiota with the development of BMD.
近期研究表明肠道微生物群对复杂疾病或性状具有综合影响。然而,在探索肠道微生物群与骨密度(BMD)之间的潜在关系方面所做的工作有限。
我们进行了多基因风险评分(PRS)分析,以系统地探索肠道微生物群与身体骨密度之间的关系。与肠道微生物群相关的显著单核苷酸多态性(SNP)集来自先前的全基因组关联研究(GWAS)。总共从英国生物银行队列中获取了2294至5065名不同部位骨密度值及其基因型数据的个体。通过PLINK软件根据英国生物银行每个研究对象的SNP基因型数据计算每个个体的肠道微生物群PRS。使用计算得到的PRS作为肠道微生物群的工具变量,最终进行个体PRS值与骨密度值的Pearson相关性分析,以检验肠道微生物群与目标性状之间的潜在关联。
总共选择了31个骨密度性状作为结果,以评估它们与肠道微生物群的关系。使用线性回归模型将年龄、性别、体重指数和前5个主成分(PCs)作为协变量进行调整后,在多次检验校正后,骨盆骨密度(=0.0437)显示出与肠道微生物群有提示性的关联信号。
我们的研究结果支持肠道微生物群与骨密度发展之间存在微弱相关性。