中国组织工程研究

中国组织工程研究 ›› 2025, Vol. 29 ›› Issue (12): 2605-2613.doi: 10.12307/2025.376

• 组织构建相关数据分析 Date analysis of organization construction • 上一篇    下一篇

外周血细胞与骨质疏松症的因果关系

刘科第1，陈勇喜2，覃海飚2，郭圣挥1，覃忠设1，蒙觉威1，崔善林1，范俊鸿1   

  1. 1广西中医药大学研究生学院，广西壮族自治区南宁市  530003；2广西中医药大学第一附属医院，广西壮族自治区南宁市  530003

  • 收稿日期:2024-03-22 接受日期:2024-06-13 出版日期:2025-04-28 发布日期:2024-09-11
  • 通讯作者: 陈勇喜，硕士生导师，副主任医师，广西中医药大学第一附属医院，广西壮族自治区南宁市 530003
  • 作者简介:刘科第，男，1996年生，广西壮族自治区柳州市人，壮族，硕士在读，主要从事脊柱脊髓相关疾病的诊治研究。
  • 基金资助:
    广西中医药适宜技术开发与推广项目(GZSY-23-28)，项目负责人：陈勇喜；广西中医药大学校级科研项目(2022MS043)，项目负责人：陈勇喜

Causal relationship between peripheral blood cells and osteoporosis

Liu Kedi1, Chen Yongxi2, Qin Haibiao2, Guo Shenghui1, Qin Zhongshe1, Meng Juewei1, Cui Shanlin1, Fan Junhong1   

  1. 1Graduate School of Guangxi University of Chinese Medicine, Nanning 530003, Guangxi Zhuang Autonomous Region, China; 2The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530003, Guangxi Zhuang Autonomous Region, China 
  • Received:2024-03-22 Accepted:2024-06-13 Online:2025-04-28 Published:2024-09-11
  • Contact: Chen Yongxi, Master supervisor, Associate chief physician, Graduate School of Guangxi University of Chinese Medicine, Nanning 530003, Guangxi Zhuang Autonomous Region, China
  • About author:Liu Kedi, Master candidate, Graduate School of Guangxi University of Chinese Medicine, Nanning 530003, Guangxi Zhuang Autonomous Region, China
  • Supported by:
    Guangxi Traditional Chinese Medicine Appropriate Technology Development and Promotion Project, No. GZSY-23-28 (to CYX); Guangxi University of Chinese Medicine Research Project, No. 2022MS043 (to CYX)

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摘要：




文题释义：
外周血细胞：是指血液中各种类型的细胞，主要分为红细胞、白细胞和血小板3大类。通过检查外周血细胞的数量和比例，可以反映造血过程的活跃程度以及血液系统健康状况。
孟德尔随机化分析：是一种新兴的研究方法，该方法基于孟德尔遗传定律的研究，利用多个或单个不受混杂因素影响的单核苷酸多态性作为工具变量来评估暴露因素对疾病风险影响。孟德尔随机化分析的优点在于可以减少混杂因素的影响，可为疾病的因果关系提供更可信的证据支持。

背景：流行病学调查和一些实验表明，外周血细胞和骨质疏松症存在密切关系，但两者在遗传学层面上的因果关系尚不清楚。
目的：运用孟德尔随机化探究外周血细胞和骨质疏松症的因果关系。
方法：从BCX、MRC-IEU等数据库分别获取外周血细胞、不同年龄段全身骨密度、跟骨骨密度的GWAS数据集，将血细胞作为暴露数据，不同年龄段骨密度及跟骨骨密度作为结局数据，使用逆方差加权法、MR-Egger、加权中值法、加权中位数、简单中位数等方法进行孟德尔随机化分析，使用Cochran’s Q、MR-Egger回归、Leave-one-out法等检验对结果进行异质性、多效性和敏感性评估，用β值评估暴露与结局的因果关系。
结果与结论：①因Cochran’s Q结果显示孟德尔随机化结果存在异质性，故研究结果以逆方差加权法结果为标准。逆方差加权结果显示：当不同年龄段骨密度作为结局时，白细胞计数与(45-60岁)全身骨密度呈负向因果关系(β=-0.07，95%CI：-0.13， -0.01，P=0.02)，单核细胞计数与(45-60岁)全身骨密度呈正向因果关系(β=0.05，95%CI：0.00，0.10，P=0.037)，白细胞计数、嗜碱性粒细胞计数与(> 60岁)全身骨密度呈负向因果关系(β=-0.04，95%CI：-0.07，-0.01，P=0.005；β=-0.04，95%CI：-0.07，-0.00，P=0.038)，血红蛋白浓度及红细胞压积与(> 60岁)全身骨密度呈正向因果关系(β=0.04，95%CI：0.01， 0.08，P=0.012；β=0.04，95%CI：0.00， 0.07，P=0.039)，白细胞计数与(未区分年龄段)全身骨密度呈负向因果关系(β=-0.10，95%CI：-0.16，-0.03，P=0.002)；当跟骨骨密度作为结局时，白细胞计数与跟骨骨密度呈负向因果关系(β=-0.04，95%CI：-0.07， -0.01，P=0.016)，血红蛋白浓度、红细胞压积与跟骨骨密度呈正向因果关系(β=0.05，95%CI：0.01，0.08，P=0.007；β=0.05，95%CI：0.01，0.08，P=0.004)。②为保证结果稳健性，将外周血细胞与不同年龄段全身骨密度、跟骨骨密度的孟德尔随机化结果进行Meta分析，结果提示对数变换后的白细胞计数每降低一个标准差，会使骨密度降低的风险减少5%(OR=0.95，95%CI：0.94，0.97，P < 0.001)；血红蛋白浓度、红细胞压积每增加一个标准差，会使骨密度降低风险减少4%(OR=1.04，95%CI：1.03，1.06，P < 0.001)。③结果提示：外周血细胞中白细胞计数增加是骨密度的风险因素；红细胞压积、血红蛋白浓度增高是骨密度的保护因素。

https://orcid.org/0009-0000-7484-2081(刘科第)

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

关键词: 孟德尔随机化, 骨质疏松症, 骨密度, 外周血细胞, 因果关系

Abstract: BACKGROUND:  Epidemiologic investigations and some experiments have shown that there is a close relationship between peripheral blood cells and osteoporosis, but the causal relationship between the two at the genetic level is still unclear.
OBJECTIVE: To explore the causal relationship between peripheral blood cells and osteoporosis using Mendelian randomization methods. 
METHODS: Genome-wide association study data sets on peripheral blood cells, overall bone density at different ages, and calcaneal bone density were obtained from databases such as Blood Cell Consortium and MRC Integrative Epidemiology Unit. Blood cells were used as exposure data, with bone density at different ages and calcaneal bone density serving as outcome data. Mendelian randomization analyses were performed using methods such as inverse variance weighting, MR-Egger, weighted median method, and simple median. The results were assessed for heterogeneity, pleiotropy, and sensitivity using Cochran’s Q, MR-Egger regression, and Leave-one-out method. The causal relationship between exposure and outcomes was evaluated using β values.
RESULTS AND CONCLUSION: Due to the heterogeneity revealed by Cochran’s Q test in the Mendelian randomization results, the results of the study were based on the inverse variance weighting method. The inverse variance weighting results showed that when age-specific bone density was used as an outcome, there was a negative causal relationship between white blood cell count and whole-body bone mineral density at the age of 45-60 years [β=-0.07, 95% confidence interval (CI): -0.13, -0.01, P=0.02], a positive causal relationship between monocyte count and whole-body bone mineral density at the age of 45-60 years (β=0.05, 95% CI: 0.00, 0.10, P=0.037), a negative causal relationship between white blood cell and basophil counts and whole-body bone mineral density over 60 years old (β=-0.04, 95% CI: -0.07, -0.01, P=0.005; β=-0.04, 95% CI: -0.07, -0.00, P=0.038), a positive causal relationship between hemoglobin concentration and hematocrit and whole-body bone mineral density over 60 years old (β=0.04, 95% CI: 0.01, 0.08, P=0.012; β=0.04, 95% CI: 0.00, 0.07, P=0.039), and a negative causal relationship between white cell count and whole-body bone mineral density at an undistinguished age (β=-0.10, 95% CI: -0.16, -0.03, P=0.002). When heel bone mineral density was used as an outcome, there was a negative causal relationship between white cell count and heel bone mineral density (β=-0.04, 95% CI: -0.07, -0.01, P=0.016), and a positive causal relationship between hemoglobin concentration and hematocrit and heel bone mineral density (β=0.05, 95% CI: 0.01, 0.08, P=0.007; β=0.05, 95% CI: 0.01, 0.08, P=0.004). To ensure the robustness of the results, meta-analyses of Mendelian randomization results of peripheral blood cells and whole-body bone mineral density as well as heel bone mineral density in different age groups were conducted. The results suggested that for every standard deviation decrease in log-transformed white blood cell count, there was a 5% reduction in the risk of decreased bone mineral density (OR=0.95, 95% CI: 0.94, 0.97, P < 0.001); whereas for every standard deviation increase in hemoglobin concentration and hematocrit, there was a 4% reduction in the risk of decreased bone density (OR=1.04, 95% CI: 1.03, 1.06, P < 0.001). In conclusion, increased white blood cell count in peripheral blood is a risk factor for bone mineral density; whereas increased hematocrit and hemoglobin concentration are protective factors for bone mineral density.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: Mendelian randomization, osteoporosis, bone mineral density, peripheral blood cell, causal relationship

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