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Wang J, Wang Y, Zheng Y, Li Y, Fan M, Tian W, Jiang Y, Wang Y, Cui M, Suo C, Zhang T, Jin L, Chen X, Xu K. Lipid metabolism mediates the association between body mass index change and bone mineral density: The Taizhou imaging study. Prev Med 2024; 184:107999. [PMID: 38735587 DOI: 10.1016/j.ypmed.2024.107999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/08/2024] [Accepted: 05/09/2024] [Indexed: 05/14/2024]
Abstract
BACKGROUND Limited research explores the impact of body mass index (BMI) change on osteoporosis, regarding the role of lipid metabolism. We aimed to cross-sectionally investigate these relationships in 820 Chinese participants aged 55-65 from the Taizhou Imaging Study. METHODS We used the baseline data collected between 2013 and 2018. T-score was calculated by standardizing bone mineral density and was used for osteoporosis and osteopenia diagnosis. Multinomial logistic regression was used to examine the effect of BMI change on bone health status. Multivariable linear regression was employed to identify the metabolites corrected with BMI change and T-score. Exploratory factor analysis (EFA) and mediation analysis were conducted to ascertain the involvement of the metabolites. RESULTS BMI increase served as a protective factor against osteoporosis (OR = 0.79[0.71-0.88], P-value<0.001) and osteopenia (OR = 0.88[0.82-0.95], P-value<0.001). Eighteen serum metabolites were associated with both BMI change and T-score. Specifically, high-density lipoprotein (HDL) substructures demonstrated negative correlations (β = -0.08 to -0.06 and - 0.12 to -0.08, respectively), while very low-density lipoprotein (VLDL) substructions showed positive correlations (β = 0.09 to 0.10 and 0.10 to 0.11, respectively). The two lipid factors (HDL and VLDL) extracted by EFA acted as mediators between BMI change and T-score (Prop. Mediated = 8.16% and 10.51%, all P-value<0.01). CONCLUSION BMI gain among Chinese aged 55-65 is beneficial for reducing the risk of osteoporosis. The metabolism of HDL and VLDL partially mediates the effect of BMI change on bone loss. Our research offers novel insights into the prevention of osteoporosis, approached from the perspective of weight management and lipid metabolomics.
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Affiliation(s)
- Jiacheng Wang
- School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - Yawen Wang
- School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - Yi Zheng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yucan Li
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China
| | - Min Fan
- Taixing Disease Control and Prevention Center, Taizhou, Jiangsu, China
| | - Weizhong Tian
- Department of Medical Imaging, Taizhou People's Hospital Affiliated to Nanjing Medical University, Taizhou, Jiangsu, China
| | - Yanfeng Jiang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Yingzhe Wang
- Department of Neurology, Huashan Hospital Affiliated to Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Mei Cui
- Department of Neurology, Huashan Hospital Affiliated to Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Chen Suo
- School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Tiejun Zhang
- School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China; Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Xingdong Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital Affiliated to Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China; Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China.
| | - Kelin Xu
- School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China.
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Wu Y, Ma W, Cheng Z, Zhang Q, Li Z, Weng P, Li B, Huang Z, Fu C. Causal relationships between body mass index, low-density lipoprotein and bone mineral density: Univariable and multivariable Mendelian randomization. PLoS One 2024; 19:e0298610. [PMID: 38870109 PMCID: PMC11175445 DOI: 10.1371/journal.pone.0298610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/27/2024] [Indexed: 06/15/2024] Open
Abstract
SUMMARY Utilizing the Mendelian randomization technique, this research clarifies the putative causal relationship between body mass index (BMI) andbone mineral density (BMD), and the mediating role of low-density lipoprotein (LDL). The implications of these findings present promising opportunities for enhancing our understanding of complex bone-related characteristics and disorders, offering potential directions for treatment and intervention. OBJECTIVE The objective of this study is to examine the correlation between BMI and BMD, while exploring the intermediary role of LDL in mediating the causal impact of BMI on BMD outcomes via Mendelian randomization. METHODS In this study, we employed genome-wide association study (GWAS) data on BMI, LDL, and BMD to conduct a comparative analysis using both univariate and multivariate Mendelian randomization. RESULTS Our study employed a two-sample Mendelian randomization design. Considering BMI as the exposure and BMD as the outcome, our results suggest that BMI may function as a potential protective factor for BMD (β = 0.05, 95% CI 1.01 to 1.09, P = 0.01). However, when treating LDL as the exposure and BMD as the outcome, our findings indicate LDL as a risk factor for BMD (β = -0.04, 95% CI 0.92 to 0.99, P = 0.04). In our multivariate Mendelian randomization (MVMR) model, the combined influence of BMI and LDL was used as the exposure for BMD outcomes. The analysis pointed towards a substantial protective effect of LDL on BMD (β = 0.08, 95% CI 0.85 to 0.97, P = 0.006). In the analysis of mediation effects, LDL was found to mediate the relationship between BMI and BMD, and the effect was calculated at (β = 0.05, 95% CI 1.052 to 1.048, P = 0.04). CONCLUSION Our findings suggest that BMI may be considered a protective factor for BMD, while LDL may act as a risk factor. Moreover, LDL appears to play a mediatory role in the causal influence of BMI on BMD.
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Affiliation(s)
- Yuxiang Wu
- Quanzhou Hospital of Traditional Chinese Medicine, Quanzhou, Fujian, China
- Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Weiwei Ma
- School of Acupuncture-Moxibustion and Orthopaedics College of Acupuncture, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Zhenda Cheng
- Quanzhou Hospital of Traditional Chinese Medicine, Quanzhou, Fujian, China
- Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Qiwei Zhang
- Department of Orthopaedics, Dongzhimen Hospital, Beijing University of Chinese Medicine, National Center for Traditional Chinese Medicine, Beijing, China
| | - Zhaodong Li
- Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, China
| | - Punan Weng
- Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Bushuang Li
- Department of body conditioning, Xiamen Hospital of Beijing University of Chinese Medicine, Xiamen, Fujian, China
| | - Zhiqiang Huang
- Quanzhou Hospital of Traditional Chinese Medicine, Quanzhou, Fujian, China
| | - Changlong Fu
- Academy of Integrative Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
- Fujian Provincial Key Laboratory of Integrative Medicine on Geriatrics, Fuzhou, Fujian, China
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Chen Q, Chen J, Zeng R, Shi J. Path analysis to identify factors influencing osteoporosis: A cross-sectional study. Exp Gerontol 2024; 188:112392. [PMID: 38447925 DOI: 10.1016/j.exger.2024.112392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 03/01/2024] [Accepted: 03/03/2024] [Indexed: 03/08/2024]
Abstract
BACKGROUND Osteoporosis is characterized by low bone mass and deterioration of bone tissue, which is influenced by both environmental factors and nutritional metabolism. The relationship between biochemical indicators and bone mineral density (BMD) is intricate and involves complex mechanisms. Path analysis, a statistical method that investigates causal relationships and the strength of associations among multiple factors, can be valuable in elucidating the connection between biochemical indicators and BMD. METHODS In this study, we employed advanced statistical techniques, specifically structural equation modeling (SEM) to investigate the intricate interrelationships among a myriad of factors that exert influence on BMD. This analytical approach facilitated not only the identification of the direct relationships between specific variables and BMD but also the exploration of the intricate of indirect pathway through which other variables contribute to the oval impact on BMD. By delving into the direct and indirect effects, we aimed to unravel the complex influences that collectively shape the state of bone health, providing a nuanced understanding of the multifaceted nature of the factors affecting BMD. RESULTS Our findings revealed that lipid levels had a significant indirect influence on BMD, which was mediated by body mass index (BMI). BMI exhibited both direct and indirect effects on BMD. Uric acid (UA) exerted a significant direct and indirect influence on BMD, with glomerular filtration rate (GFR) acting as the mediator. However, the total effect of UA on BMD was not significant due to the cancellation of positive effect UA on BMD but negative indirect effects of UA through GFR. For females, albumin had a significant direct effect on BMD, whereas this effect was not observed in males. The path analysis models generated results that demonstrated an acceptable fit for both female data (χ2 = 9.63, df = 7, p = 0.21, comparative fit index (CFI) = 0.98, root mean square error of approximation (RMSEA) = 0.05) and male data (χ2 = 6.26, df = 4, p = 0.18, CFI = 0.97, RMSEA = 0.06). CONCLUSIONS Nutritional metabolism plays a crucial role in maintaining BMD in elderly females and males.
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Affiliation(s)
- Qiaofeng Chen
- Department of Orthopaedics, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China
| | - Jie Chen
- University of Massachusetts Boston, Boston, MA, USA
| | - Rongdong Zeng
- Department of Orthopaedics, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China.
| | - Jianhui Shi
- Department of Orthopaedics, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China.
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Raggi P, Takyar FM, Gadiyaram V, Zhang C, Stillman AE, Davarpanah AH. Differential effect of atorvastatin and pravastatin on thoracic spine attenuation: A sub-analysis of a randomized clinical trial. Atherosclerosis 2024; 388:117425. [PMID: 38109819 DOI: 10.1016/j.atherosclerosis.2023.117425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 11/29/2023] [Accepted: 12/07/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND Statins reduce cardiovascular events and may improve bone mineral density. METHODS We conducted a sub-analysis of a randomized clinical trial that investigated the differential effect of moderate vs intensive low-density lipoprotein cholesterol (LDL-C) lowering therapies on coronary artery calcium (CAC) scores, and used the acquired images to assess the change in radiological attenuation of selected thoracic vertebrae. Baseline and 12-month unenhanced chest CT scans were performed in 420 hyperlipidemic, postmenopausal women randomized to atorvastatin (ATV) 80 mg/day or pravastatin (PRV) 40 mg/day in the Beyond Endorsed Lipid Lowering with Electron Beam Tomography Scanning (BELLES) trial. Bone attenuation was measured in three contiguous thoracic vertebrae at baseline and 12 months. RESULTS There were no differences in baseline demographic and clinical characteristics between treatment arms. The median percent lowering (interquartile range) in LDL-C was significantly greater with ATV than PRV [-53 (-69 to 20)% vs -28 (-55 to 74)%, p < 0.001], although the CAC score change was similar [12 (-63 to 208)% vs 13 (-75 to 358)%; p = 0.44]. At follow-up, the median bone attenuation loss was significantly greater with PRV than with ATV [-2.6 (-27 to 11)% vs 0 (-11 to 25)%; p < 0.001]. The attenuation loss in the PRV group was comparable to that of a historical untreated general population sample. In the entire cohort, the changes in LDL-C and total cholesterol were inversely correlated with bone attenuation change (p < 0.01). In adjusted multivariable linear regression analyses, race and percent change in LDL-C were independent predictors of bone attenuation change. Age, body mass index, history of smoking, diabetes mellitus, hypertension, peripheral vascular disease, or hormone replacement therapy did not affect percent change in BMD. CONCLUSIONS These findings support the hypothesis that there is an interaction between bone and cardiometabolic health and that intensive lipid lowering has a beneficial effect on bone health.
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Affiliation(s)
- Paolo Raggi
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
| | - Farzin M Takyar
- Endocrine Research Center, Research Institute for Endocrine Sciences, Tehran, Iran
| | - Varuna Gadiyaram
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Chao Zhang
- Pediatric Biostatistics Core, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; General Dynamics Information Technology, Falls Church, VA, USA
| | - Arthur E Stillman
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Amir H Davarpanah
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA.
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Szulc P, Lewis JR, Chapurlat R. Accelerated Bone Loss in Older Men With Severe Abdominal Aortic Calcification-the Prospective MINOS Study. J Clin Endocrinol Metab 2023; 109:e32-e39. [PMID: 37610245 DOI: 10.1210/clinem/dgad459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 06/30/2023] [Accepted: 08/07/2023] [Indexed: 08/24/2023]
Abstract
CONTEXT Data on the association between the severity of abdominal aortic calcification (AAC) and bone loss are discordant. OBJECTIVE Our aim was to assess the association between baseline AAC and prospectively assessed bone loss in older men. METHODS This prospective cohort study started in 1995 (MINOS). Men aged 50 to 85 years (n = 778) had AAC assessed on the lateral radiograph of the spine using Kauppila's semiquantitative score and was followed prospectively for 7.5 years. Bone mineral density (BMD) and bone mineral content (BMC) were measured by dual-energy x-ray absorptiometry every 18 months. Statistical analysis was performed using linear mixed models. RESULTS In comparison to men without AAC (AAC = 0), severe AAC (>6) was associated with more rapid bone loss at the total hip (-0.62 ± 0.06 vs -0.32 ± 0.04%/year; P < .001), trochanter, and distal forearm (-0.72 ± 0.06 vs -0.45 ± 0.03%/year; P < .001). The highest decile (AAC >10) was associated with more rapid bone loss at the femoral neck, whole body, and ultradistal radius (-0.86 ± 0.12 vs -0.34 ± 0.05%/year; P < .001). The results were similar for BMD and for BMC. The patterns were similar in sensitivity analyses (eg, after excluding men with abdominal obesity, after excluding current smokers, after excluding men with ischemic heart disease or with diabetes mellitus, after excluding men with abnormal concentrations of lipids, bioavailable 17β-estradiol or 25-hydroxycholecalciferol, after excluding men with glomerular filtration rate <60 mL/min). CONCLUSION Severe AAC is associated with faster bone loss in older men and may contribute to the higher fracture risk observed in this population.
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Affiliation(s)
- Pawel Szulc
- INSERM UMR 1033, University of Lyon, Hospices Civils de Lyon, 69437, Lyon, France
| | - Joshua R Lewis
- Institute for Nutrition Research, Edith Cowan University, Joondalup, Perth, WA 6027, Australia
- Medical School, the University of Western Australia, Perth, WA 6009, Australia
| | - Roland Chapurlat
- INSERM UMR 1033, University of Lyon, Hospices Civils de Lyon, 69437, Lyon, France
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Kang J, Zhao S, Wu X, Wang C, Jiang Z, Wang S. The association of lipid metabolism with bone metabolism and the role of human traits: a Mendelian randomization study. Front Endocrinol (Lausanne) 2023; 14:1271942. [PMID: 38125793 PMCID: PMC10731031 DOI: 10.3389/fendo.2023.1271942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 11/15/2023] [Indexed: 12/23/2023] Open
Abstract
Background The impact of lipid metabolism on bone metabolism remains controversial, and the extent to which human traits mediate the effects of lipid metabolism on bone metabolism remains unclear. Objective This study utilized mendelian randomization to investigate the effects of blood lipids on bone mineral density (BMD) at various skeletal sites and examined the mediating role of human traits in this process. Methods We leveraged genetic data from large-scale genome-wide association studies on blood lipids (n=1,320,016), forearm bone mineral density (FA-BMD) (n=10,805), lumbar spine bone mineral density (LS-BMD) (n=44,731), and femoral neck bone mineral density (FN-BMD) (n=49,988) to infer causal relationships between lipid and bone metabolism. The coefficient product method was employed to calculate the indirect effects of human traits and the proportion of mediating effects. Results The results showed that a 1 standard deviation(SD) increase in HDL-C, LDL-C and TC was associated with a decrease in LS-BMD of 0.039 g/cm2, 0.045 g/cm2 and 0.054 g/cm2, respectively. The proportion of mediating effects of systolic blood pressure (SBP) on HDL-C to LS-BMD was 3.17%, but suppression effects occurred in the causal relationship of LDL-C and TC to LS-BMD. Additionally, the proportion of mediating effects of hand grip strength (HGS) on the TC to LS-BMD pathway were 6.90% and 4.60% for the left and right hands, respectively. Conclusion In conclusion, a negative causal relationship was established between lipid metabolism and bone metabolism. Our results indicated that SBP and HGS served as mediators for the effects of lipid metabolism on bone metabolism.
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Affiliation(s)
- Jian Kang
- Graduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, China
| | - Shuangli Zhao
- Orthopedics and Traumatology, The Second Hospital of Liaoning University of Chinese Medicine, Shenyang, China
| | - Xize Wu
- Department of Critical Care Medicine, Nantong Hospital of Traditional Chinese Medicine, Nantong, China
| | - Can Wang
- Clinical College, Jinzhou Medical University, Jinzhou, China
| | - Zongkun Jiang
- Orthopedics and Traumatology, The Second Hospital of Liaoning University of Chinese Medicine, Shenyang, China
| | - Shixuan Wang
- Orthopedics and Traumatology, The Second Hospital of Liaoning University of Chinese Medicine, Shenyang, China
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Zhao X, Tan N, Zhang Y, Xiao M, Li L, Ning Z, Liu M, Jin H. Associations between apolipoprotein B and bone mineral density: a population-based study. BMC Musculoskelet Disord 2023; 24:861. [PMID: 37919727 PMCID: PMC10621203 DOI: 10.1186/s12891-023-06990-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 10/25/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Lipids are critical in bone metabolism, and several studies have highlighted their importance. This study aimed to investigate the relationship between apolipoprotein B (apo B) and bone mineral density (BMD) at different skeletal sites (lumbar spine, femoral neck, and total femur) and to compare the influence of apo B with other traditional lipid markers. METHODS The study included participants from the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2016 who had complete data for apo B and BMD at the three skeletal sites. We used weighted multivariate regression analysis, subgroup analysis, and interaction tests to examine associations. Restricted cubic spline (RCS) was used to examine the non-linear relationship. RESULTS A total of 4,258 adults were included in the study. Multivariate linear regression analysis showed that the relationship between apo B and BMD varied by skeletal site: a negative association was found with lumbar spine BMD [β = -0.054, 95%CI: (-0.073, -0.035)]. In contrast, a positive association was found with femoral neck BMD [β = 0.031, 95%CI: (0.011, 0.051)] and no significant association between apo B and total femur BMD. CONCLUSIONS Our findings suggest that apo B is associated with BMD in a site-specific manner.
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Affiliation(s)
- Xuefei Zhao
- Department of Spine Surgery, The Affiliated Second Hospital, Hengyang Medical School, University of South China, Hengyang, 421009, China
| | - Ning Tan
- Department of Urology, The Affiliated Second Hospital, Hengyang Medical School, University of South China, Hengyang, 421009, China
| | - Ya Zhang
- Department of Gland Surgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, China
| | - Mengde Xiao
- Department of Gland Surgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, China
| | - Lihong Li
- Department of Gland Surgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, China
| | - Zhongxing Ning
- Department of Intensive Care Unit, The People's Hospital of Guangxi Zhuang Autonomous Region & Research Center of Intensive Care Unit, Nanning, 530021, China
| | - Mingjiang Liu
- Department of Hand & Microsurgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, China
| | - Haimin Jin
- Department of Neurology, Wenzhou Central Hospital, Dingli Clinical Institute of Wenzhou Medical University, Wenzhou, 325000, China.
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Huang X, Zhang Z, Zou L, Li W, He J. Association between androgen receptor gene alteration and osteoporosis in Chinese Han elderly men. PeerJ 2023; 11:e14782. [PMID: 36815982 PMCID: PMC9933766 DOI: 10.7717/peerj.14782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 01/03/2023] [Indexed: 02/15/2023] Open
Abstract
Objective To explore the role of blood glucose, blood lipids, and androgen receptor gene (CAG)n genotype in the pathogenesis of osteoporosis in Chinese Han men and to provide theoretical value for screening people susceptible to osteoporosis. Methods Patients who visited the First Affiliated Hospital of Chengdu Medical College from February 2021 to October 2021 were selected as research subjects to measure bone density by double-energy X-ray, osteoporosis patients as osteoporosis group (40 patients), and non-osteoporosis patients as the control group (40 patients). The STR method detected the repeat times of the androgen receptor gene (CAG)n in the two groups. The repeat times ≤22 were the SS genotype, and >22 were the LL genotype. Meanwhile, the patient's age, body mass index (BMI), blood glucose, blood lipids, calcium, phosphorus, and alkaline phosphatase examined on day one after admission were collected, and the statistical analysis was performed using SPSS 26.0. Results The results of the univariate analysis showed that there was no significant difference in age, calcium, phosphorus, alkaline phosphatase, and glycosylated hemoglobin between the two groups (P > 0.05). There were significant differences in average blood glucose, total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, and genotype frequency (P < 0.05). The multivariate logistic regression analysis results showed significant differences in total cholesterol and genotype frequency between the two groups (P < 0.05). Conclusion Androgen receptor LL genotype and elevated total cholesterol may be the risk factors for osteoporosis in older men of Han nationality.
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Affiliation(s)
- Xin Huang
- Collaborative Innovation Center of Sichuan for Elderly Care and Health, Chengdu Medical College, Sichuan, China,Department of Orthopedics, Chengdu Seventh People’s Hospital (Orthopedics, Affiliated Cancer Hospital, Chengdu Medical College), Sichuan, China,Department of Orthopedics, First Affiliated Hospital of Chengdu Medical College, Sichuan, China
| | - Zhengdong Zhang
- Collaborative Innovation Center of Sichuan for Elderly Care and Health, Chengdu Medical College, Sichuan, China,Department of Orthopedics, First Affiliated Hospital of Chengdu Medical College, Sichuan, China
| | - Liangxuan Zou
- Collaborative Innovation Center of Sichuan for Elderly Care and Health, Chengdu Medical College, Sichuan, China,Department of Orthopedics, Chengdu Seventh People’s Hospital (Orthopedics, Affiliated Cancer Hospital, Chengdu Medical College), Sichuan, China,Department of Orthopedics, First Affiliated Hospital of Chengdu Medical College, Sichuan, China
| | - Wenbo Li
- Collaborative Innovation Center of Sichuan for Elderly Care and Health, Chengdu Medical College, Sichuan, China,Department of Orthopedics, Chengdu Seventh People’s Hospital (Orthopedics, Affiliated Cancer Hospital, Chengdu Medical College), Sichuan, China,Department of Orthopedics, First Affiliated Hospital of Chengdu Medical College, Sichuan, China
| | - Jun He
- Department of Orthopedics, Chengdu Seventh People’s Hospital (Orthopedics, Affiliated Cancer Hospital, Chengdu Medical College), Sichuan, China
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Yang G, Schooling CM. Investigating sex-specific associations of lipid traits with type 2 diabetes, glycemic traits and sex hormones using Mendelian randomization. Cardiovasc Diabetol 2023; 22:3. [PMID: 36624450 PMCID: PMC9830908 DOI: 10.1186/s12933-022-01714-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Accepted: 12/01/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Low-density lipoprotein (LDL)-cholesterol is positively associated with cardiovascular disease (CVD) and inversely associated with type 2 diabetes, which could detract from lipid modification. Here, we examined whether lipid traits potentially relevant to CVD aetiology, i.e. apolipoprotein B (apoB), triglycerides (TG) and lipoprotein(a) [Lp(a)] exhibited the same associations. We investigated sex-specifically, including the role of sex hormones, because sex disparities exist in lipid profile and type 2 diabetes. We also replicated where possible. METHODS We used Mendelian randomization (MR) to examine sex-specific associations of apoB, TG and Lp(a) with type 2 diabetes, HbA1c, fasting insulin, fasting glucose, testosterone and estradiol in the largest relevant sex-specific genome-wide association studies (GWAS) in people of European ancestry and replicated where possible. We also assessed sex-specific associations of liability to type 2 diabetes with apoB, TG and Lp(a). RESULTS Genetically predicted apoB and Lp(a) had little association with type 2 diabetes or glycemic traits in women or men. Genetically predicted higher TG was associated with higher type 2 diabetes risk [odds ratio (OR) 1.44 per standard deviation (SD), 95% confidence interval (CI) 1.26 to 1.65], HbA1c and fasting insulin specifically in women. Higher TG was associated with lower testosterone in women and higher testosterone in men, but with lower estradiol in men and women. Genetic liability to type 2 diabetes was associated with higher TG in women, and possibly with lower apoB in men. CONCLUSIONS Lipid traits potentially relevant to CVD aetiology do not exhibit contrasting associations with CVD and type 2 diabetes. However, higher TG is associated with higher type 2 diabetes risk and glycemic traits, which in turn further increases TG specifically in women, possibly driven by sex hormones.
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Affiliation(s)
- Guoyi Yang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- Graduate School of Public Health and Health Policy, City University of New York, New York, USA.
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Galvez-Fernandez M, Rodriguez-Hernandez Z, Grau-Perez M, Chaves FJ, Garcia-Garcia AB, Amigo N, Monleon D, Garcia-Barrera T, Gomez-Ariza JL, Briongos-Figuero LS, Perez-Castrillon JL, Redon J, Tellez-Plaza M, Martin-Escudero JC. Metabolomic patterns, redox-related genes and metals, and bone fragility endpoints in the Hortega Study. Free Radic Biol Med 2023; 194:52-61. [PMID: 36370960 DOI: 10.1016/j.freeradbiomed.2022.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/06/2022] [Accepted: 11/06/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND The potential joint influence of metabolites on bone fragility has been rarely evaluated. We assessed the association of plasma metabolic patterns with bone fragility endpoints (primarily, incident osteoporosis-related bone fractures, and, secondarily, bone mineral density BMD) in the Hortega Study participants. Redox balance plays a key role in bone metabolism. We also assessed differential associations in participant subgroups by redox-related metal exposure levels and candidate genetic variants. MATERIAL AND METHODS In 467 participants older than 50 years from the Hortega Study, a representative sample from a region in Spain, we estimated metabolic principal components (mPC) for 54 plasma metabolites from NMR-spectrometry. Metals biomarkers were measured in plasma by AAS and in urine by HPLC-ICPMS. Redox-related SNPs (N = 341) were measured by oligo-ligation assay. RESULTS The prospective association with incident bone fractures was inverse for mPC1 (non-essential and essential amino acids, including branched-chain, and bacterial co-metabolites, including isobutyrate, trimethylamines and phenylpropionate, versus fatty acids and VLDL) and mPC4 (HDL), but positive for mPC2 (essential amino acids, including aromatic, and bacterial co-metabolites, including isopropanol and methanol). Findings from BMD models were consistent. Participants with decreased selenium and increased antimony, arsenic and, suggestively, cadmium exposures showed higher mPC2-associated bone fractures risk. Genetic variants annotated to 19 genes, with the strongest evidence for NCF4, NOX4 and XDH, showed differential metabolic-related bone fractures risk. CONCLUSIONS Metabolic patterns reflecting amino acids, microbiota co-metabolism and lipid metabolism were associated with bone fragility endpoints. Carriers of redox-related variants may benefit from metabolic interventions to prevent the consequences of bone fragility depending on their antimony, arsenic, selenium, and, possibly, cadmium, exposure levels.
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Affiliation(s)
- Marta Galvez-Fernandez
- Department of Preventive Medicine and Microbiology, School of Medicine, Universidad Autónoma de Madrid, Arzobispo Morcillo, 4, 28029, Madrid, Spain; Department of Preventive Medicine, Hospital Universitario Severo Ochoa, Avenida de Orellana, s/n, 28911, Madrid, Spain; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Monforte de Lemos, 5, 28029, Madrid, Spain
| | - Zulema Rodriguez-Hernandez
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Monforte de Lemos, 5, 28029, Madrid, Spain; Department of Biotechnology, Universitat Politècnica de València, Camí de Vera, s/n, 46022, Valencia, Spain
| | - Maria Grau-Perez
- Department of Preventive Medicine and Microbiology, School of Medicine, Universidad Autónoma de Madrid, Arzobispo Morcillo, 4, 28029, Madrid, Spain; INCLIVA Biomedical Research Institute, Menéndez y Pelayo, 4, 46010, Valencia, Spain
| | - F Javier Chaves
- INCLIVA Biomedical Research Institute, Menéndez y Pelayo, 4, 46010, Valencia, Spain; CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain
| | - Ana Barbara Garcia-Garcia
- INCLIVA Biomedical Research Institute, Menéndez y Pelayo, 4, 46010, Valencia, Spain; CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain
| | - Nuria Amigo
- Biosfer Teslab, Plaça de Prim, 10, 43201, Tarragona, Spain; Department of Basic Medical Sciences, Universidad de Rovira I virgili, Carrer de Sant Llorenç, 21, 43201, Tarragona, Spain
| | - Daniel Monleon
- INCLIVA Biomedical Research Institute, Menéndez y Pelayo, 4, 46010, Valencia, Spain; Department of Pathology, School of Medicine, Universidad de Valencia, Avenida de Blasco Ibáñez, 15, 46010, Valencia, Spain; Center for Biomedical Research Network on Frailty and Health Aging (CIBERFES), Madrid, Spain
| | - Tamara Garcia-Barrera
- Department of Chemistry, Universidad de Huelva, Avenida de las Fuerzas Armadas, 21007, Huelva, Spain
| | - Jose L Gomez-Ariza
- Department of Chemistry, Universidad de Huelva, Avenida de las Fuerzas Armadas, 21007, Huelva, Spain
| | - Laisa S Briongos-Figuero
- Department of Internal Medicine, Hospital Universitario Rio Hortega, Calle Dulzaina, 2, 47012, Valladolid, Spain
| | - Jose L Perez-Castrillon
- Department of Internal Medicine, Hospital Universitario Rio Hortega, Calle Dulzaina, 2, 47012, Valladolid, Spain
| | - Josep Redon
- INCLIVA Biomedical Research Institute, Menéndez y Pelayo, 4, 46010, Valencia, Spain
| | - Maria Tellez-Plaza
- Department of Preventive Medicine and Microbiology, School of Medicine, Universidad Autónoma de Madrid, Arzobispo Morcillo, 4, 28029, Madrid, Spain; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Monforte de Lemos, 5, 28029, Madrid, Spain; INCLIVA Biomedical Research Institute, Menéndez y Pelayo, 4, 46010, Valencia, Spain.
| | - Juan C Martin-Escudero
- Department of Internal Medicine, Hospital Universitario Rio Hortega, Calle Dulzaina, 2, 47012, Valladolid, Spain
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11
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Chen Y, Lu T, Pettersson-Kymmer U, Stewart ID, Butler-Laporte G, Nakanishi T, Cerani A, Liang KYH, Yoshiji S, Willett JDS, Su CY, Raina P, Greenwood CMT, Farjoun Y, Forgetta V, Langenberg C, Zhou S, Ohlsson C, Richards JB. Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases. Nat Genet 2023; 55:44-53. [PMID: 36635386 PMCID: PMC7614162 DOI: 10.1038/s41588-022-01270-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 87.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 11/18/2022] [Indexed: 01/14/2023]
Abstract
Metabolic processes can influence disease risk and provide therapeutic targets. By conducting genome-wide association studies of 1,091 blood metabolites and 309 metabolite ratios, we identified associations with 690 metabolites at 248 loci and associations with 143 metabolite ratios at 69 loci. Integrating metabolite-gene and gene expression information identified 94 effector genes for 109 metabolites and 48 metabolite ratios. Using Mendelian randomization (MR), we identified 22 metabolites and 20 metabolite ratios having estimated causal effect on 12 traits and diseases, including orotate for estimated bone mineral density, α-hydroxyisovalerate for body mass index and ergothioneine for inflammatory bowel disease and asthma. We further measured the orotate level in a separate cohort and demonstrated that, consistent with MR, orotate levels were positively associated with incident hip fractures. This study provides a valuable resource describing the genetic architecture of metabolites and delivers insights into their roles in common diseases, thereby offering opportunities for therapeutic targets.
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Affiliation(s)
- Yiheng Chen
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
| | | | - Isobel D Stewart
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Guillaume Butler-Laporte
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Tomoko Nakanishi
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Agustin Cerani
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Kevin Y H Liang
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
| | - Satoshi Yoshiji
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Julian Daniel Sunday Willett
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
- McGill Genome Centre, McGill University, Montreal, Quebec, Canada
| | - Chen-Yang Su
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Computer Science, McGill University, Montreal, Quebec, Canada
| | - Parminder Raina
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- McMaster Institute for Research on Aging, McMaster University, Hamilton, Ontario, Canada
| | - Celia M T Greenwood
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, Quebec, Canada
| | - Yossi Farjoun
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Fulcrum Genomics, Boulder, CO, USA
| | - Vincenzo Forgetta
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Sirui Zhou
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Claes Ohlsson
- Sahlgrenska Osteoporosis Centre, Centre of Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada.
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
- 5 Prime Sciences Inc, Montreal, Quebec, Canada.
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada.
- Department of Medicine, McGill University, Montreal, Quebec, Canada.
- Department of Twin Research, King's College London, London, UK.
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12
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Wu Q, Li J, Zhu J, Sun X, He D, Li J, Cheng Z, Zhang X, Xu Y, Chen Q, Zhu Y, Lai M. Gamma-glutamyl-leucine levels are causally associated with elevated cardio-metabolic risks. Front Nutr 2022; 9:936220. [PMID: 36505257 PMCID: PMC9729530 DOI: 10.3389/fnut.2022.936220] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/31/2022] [Indexed: 11/26/2022] Open
Abstract
Objective Gamma-glutamyl dipeptides are bioactive peptides involved in inflammation, oxidative stress, and glucose regulation. Gamma-glutamyl-leucine (Gamma-Glu-Leu) has been extensively reported to be associated with the risk of cardio-metabolic diseases, such as obesity, metabolic syndrome, and type 2 diabetes. However, the causality remains to be uncovered. The aim of this study was to explore the causal-effect relationships between Gamma-Glu-Leu and metabolic risk. Materials and methods In this study, 1,289 subjects were included from a cross-sectional survey on metabolic syndrome (MetS) in eastern China. Serum Gamma-Glu-Leu levels were measured by untargeted metabolomics. Using linear regressions, a two-stage genome-wide association study (GWAS) for Gamma-Glu-Leu was conducted to seek its instrumental single nucleotide polymorphisms (SNPs). One-sample Mendelian randomization (MR) analyses were performed to evaluate the causality between Gamma-Glu-Leu and the metabolic risk. Results Four SNPs are associated with serum Gamma-Glu-Leu levels, including rs12476238, rs56146133, rs2479714, and rs12229654. Out of them, rs12476238 exhibits the strongest association (Beta = -0.38, S.E. = 0.07 in discovery stage, Beta = -0.29, S.E. = 0.14 in validation stage, combined P-value = 1.04 × 10-8). Each of the four SNPs has a nominal association with at least one metabolic risk factor. Both rs12229654 and rs56146133 are associated with body mass index, waist circumference (WC), the ratio of WC to hip circumference, blood pressure, and triglyceride (5 × 10-5 < P < 0.05). rs56146133 also has nominal associations with fasting insulin, glucose, and insulin resistance index (5 × 10-5 < P < 0.05). Using the four SNPs serving as the instrumental SNPs of Gamma-Glu-Leu, the MR analyses revealed that higher Gamma-Glu-Leu levels are causally associated with elevated risks of multiple cardio-metabolic factors except for high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (P > 0.05). Conclusion Four SNPs (rs12476238, rs56146133, rs2479714, and rs12229654) may regulate the levels of serum Gamma-Glu-Leu. Higher Gamma-Glu-Leu levels are causally linked to cardio-metabolic risks. Future prospective studies on Gamma-Glu-Leu are required to explain its role in metabolic disorders.
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Affiliation(s)
- Qiong Wu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Epidemiology and Biostatistics, School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Jiankang Li
- Institute of Medical Research, Northwestern Polytechnical University, Xi’an, China
| | - Jinghan Zhu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Xiaohui Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Di He
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jun Li
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zongxue Cheng
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xuhui Zhang
- Hangzhou Center for Disease Control and Prevention, Hangzhou, China,Affiliated Hangzhou Center of Disease Control and Prevention, School of Public Health, Zhejiang University, Hangzhou, China
| | - Yuying Xu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qing Chen
- Zhejiang Provincial Centers for Disease Control and Prevention, Hangzhou, China,*Correspondence: Qing Chen,
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Cancer Center, Zhejiang University, Hangzhou, China,Yimin Zhu,
| | - Maode Lai
- Key Laboratory of Disease Proteomics of Zhejiang Province, Department of Pathology, School of Medicine, Zhejiang University, Hangzhou, China,State Key Laboratory of Natural Medicines, School of Basic Medical Sciences and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China,Maode Lai,
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13
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Chung PC, Chan TC. Environmental and personal factors for osteoporosis or osteopenia from a large health check-up database: a retrospective cohort study in Taiwan. BMC Public Health 2022; 22:1531. [PMID: 35948894 PMCID: PMC9367101 DOI: 10.1186/s12889-022-13938-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/02/2022] [Indexed: 11/20/2022] Open
Abstract
Background Osteoporosis is an important public health issue in aging societies because of its associated morbidity, mortality, and decreased quality of life. The study aims to identify the association of low bone mineral density, including osteoporosis and osteopenia, with environmental and personal factors. Methods The data of participants aged ≥ 20 years with multiple visits were obtained from a health check-up database in Taiwan from 2008 to 2016. Multivariable logistic regressions were performed to identify the selected factors associated with low bone mineral density for multiple visit data. Results A total of 194,910 participants with 359,943 visits were included in this study. The prevalence of low bone mineral density (BMD) in the study population was 10.6% (n = 20.615). Older women, ever and current smokers (odds ratio (OR) = 1.04 [95% confidence interval (CI) = 1.01, 1.08]), or participants who were underweight (OR = 1.72 [1.64, 1.81]), consumed a vegetarian diet (OR = 1.32 [1.25, 1.39]), or had higher triglyceride levels (OR = 1.04 [1.01, 1.06]) were significantly associated with a higher risk of low BMD. Participants who had higher educational years (OR = 0.43 [0.41, 0.46]), higher physical activity (OR = 0.93 [0.89, 0.97]), appropriate sleep duration and better quality (OR = 0.98 [0.97, 0.99]), dairy intake (≥ 1 slice of yogurt or cheese/week, OR = 0.97 [0.95, 0.99]), higher uric acid (OR = 0.93 [0.91, 0.95]), higher walkability (OR = 0.997 [0.995,0.999]), and higher solar radiation exposure (OR = 0.997 [0.97,0.99]) were significantly associated with a lower risk of low BMD. Conclusion Interventions in different directions, such as having better health behaviors, increasing sun exposure, and residing in a highly walkable environment, are beneficial for reducing the risk of low BMD.
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Affiliation(s)
- Ping-Chen Chung
- Department of Dentistry, Puzi Hospital, Ministry of Health and Welfare, Chiayi, Taiwan
| | - Ta-Chien Chan
- Research Center for Humanities and Social Sciences, Academia Sinica, 128 Academia Road, Section 2, Taipei, Taiwan. .,Institute of Public Health, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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14
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Xiao F, Peng P, Gao S, Lin T, Fang W, He W. Inverse association between low-density lipoprotein cholesterol and bone mineral density in young- and middle-aged people: The NHANES 2011–2018. Front Med (Lausanne) 2022; 9:929709. [PMID: 36035390 PMCID: PMC9399501 DOI: 10.3389/fmed.2022.929709] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/20/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesLow-density lipoprotein cholesterol (LDL-C) plays an essential part in bone metabolism. However, the correlation between LDL-C levels and bone mineral density (BMD) is still controversial. This study aimed to explore the relationship between LDL-C levels and lumbar BMD in young- and middle-aged people.MethodsWe conducted a cross-sectional study comprising 4,441 participants aged 20–59 from the National Health and Nutrition Examination Survey (NHANES). LDL-C levels and lumbar BMD were used as independent and dependent variables, respectively. We evaluated the correlation between LDL-C levels and lumbar BMD through a weighted multivariate linear regression model. We performed a subgroup analysis of the relationship between LDL-C levels and lumbar BMD based on age, gender, and body mass index (BMI).ResultsAfter adjusting for confounding factors, LDL-C levels were negatively correlated with lumbar BMD. In subgroup analyses stratified by gender, this negative association was statistically significant in men and women. In the subgroup analysis stratified by age, a negative connection existed in people aged 30–49 years. In the subgroup analysis divided by BMI, there was an inverse correlation in overweight people (25 ≤ BMI < 30).ConclusionsOur research observed an inverse association between LDL-C levels and lumbar BMD in young- and middle-aged people, especially in people aged 30–49 years and who are overweight. Close monitoring of BMD and early intervention may be required for these people.
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Affiliation(s)
- Fangjun Xiao
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peng Peng
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shihua Gao
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tianye Lin
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Weihua Fang
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wei He
- Guangdong Research Institute for Orthopedics and Traumatology of Chinese Medicine, Guangzhou, China
- Joint Center, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- *Correspondence: Wei He
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15
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Wang P, Chen C, Song C, Jia J, Wang Y, Mu W. High cholesterol and low triglycerides are associated with total lumbar bone mineral density among adults aged 50 years and over: The NHANES 2017–2020. Front Med (Lausanne) 2022; 9:923730. [PMID: 36004377 PMCID: PMC9393595 DOI: 10.3389/fmed.2022.923730] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe association between cholesterol and triglycerides with the lumbar bone mineral density (BMD) was widely investigated, but the results remained conflicting. This study aimed to investigate the relationship between total cholesterol, triglycerides, and total lumbar BMD in adults.Materials and methodsThis cross-sectional study included 1,985 individuals aged 50 years and over. The data on total cholesterol, triglycerides, total lumbar BMD, and other covariates were obtained from the National Health and Nutritional (NHANES) between 2017 and March 2020 pre-pandemic. Multivariate logistic regression models were utilized to investigate the association between cholesterol, triglycerides, and total lumbar BMD. Smooth curve fittings and generalized additive models were also used to analyze the potential non-linearity.ResultsA total of 901 men and 1,084 women with a mean age of 63.02 ± 8.72 years (age 50–80 years) were included in this study. In multivariate regression analysis, the association between cholesterol and total lumbar BMD was negative (β = −0.026, 95% CI: −0.033, −0.020). This relationship still existed after adjusted for gender and race (β = −0.018, 95% CI: −0.025, −0.012) and fully adjusted for all covariates (β = −0.022, 95% CI: −0.029, −0.015). The association between triglycerides and total lumbar BMD was positive (β = 0.024, 95% CI: 0.017, 0.031). This relationship still existed after adjusted for gender and race (β = 0.021, 95% CI: 0.015, 0.028) and fully adjusted for all covariates (β = 0.021, 95% CI: 0.014, 0.028). In threshold effect analysis, the relationship between triglycerides and total lumbar BMD was an inverted U-shaped curve with the inflection point at 2.597 mmol/L.ConclusionHigh levels of total cholesterol and relatively low levels of triglycerides are significantly associated with the total lumbar BMD in adults aged 50 years and over.
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Affiliation(s)
- Peng Wang
- Department of Spine Surgery, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Cong Chen
- Department of Spine Surgery, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Chunhao Song
- Department of Medical Imaging, Weihai Wendeng District People’s Hospital, Weihai, China
| | - Jun Jia
- Department of Spine Surgery, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Yuanhao Wang
- Department of Spine Surgery, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Weidong Mu
- Department of Traumatic Orthopaedics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- *Correspondence: Weidong Mu,
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16
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Xie R, Huang X, Zhang Y, Liu Q, Liu M. High Low-Density Lipoprotein Cholesterol Levels are Associated with Osteoporosis Among Adults 20–59 Years of Age. Int J Gen Med 2022; 15:2261-2270. [PMID: 35250302 PMCID: PMC8896571 DOI: 10.2147/ijgm.s353531] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 02/10/2022] [Indexed: 12/31/2022] Open
Abstract
Background Serum lipids are highly inheritable and play a major role in bone health. However, the relationship between low-density lipoprotein cholesterol (LDL-C) and bone mineral density (BMD) remains uncertain. The goal of this study was to see if there was a link between LDL-C levels and BMD in persons aged 20 to 59. Methods Using data from the National Health and Nutrition Examination Survey (NHANES) 2011–2018, multivariate logistic regression models were utilized to investigate the association between LDL-C and lumbar BMD. Fitted smoothing curves and generalized additive models were also used. Results The analysis included a total of 4909 adults. After controlling for various variables, we discovered that LDL-C was negatively linked with lumbar BMD. The favorable connection of LDL-C with lumbar BMD was maintained in subgroup analyses stratified by gender and race in both males and females, Whites and Mexican Americans, but not in Blacks and other races. The relationship between LDL-C and lumbar BMD in other races was an inverted U-shaped curve with the inflection point: 2.327 (mmol/L). Conclusion In people aged 20 to 59, our research discovered a negative relationship among LDL-C and lumbar BMD. Among races other than Whites, Blacks, Mexican Americans, this relationship followed an inverted U-shaped curve (inflection point: 2.327mmol/L). LDL-C measurement might be used as a responsive biomarker for detecting osteoporosis early and guiding therapy.
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Affiliation(s)
- Ruijie Xie
- Department of Hand Surgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, People’s Republic of China
| | - Xiongjie Huang
- Department of Hand Surgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, People’s Republic of China
| | - Ya Zhang
- Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533099, People’s Republic of China
| | - Qianlong Liu
- The Affiliated Changsha Central Hospital, Hengyang Medical school, University of South China, Changsha, 410004, People’s Republic of China
| | - Mingjiang Liu
- Department of Hand Surgery, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421002, People’s Republic of China
- Correspondence: Mingjiang Liu, Email
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17
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Huang R, Wang H, Shen Z, Cai T, Zhou Y, Wang Y, Xia W, Ding B, Yan R, Li H, Wu J, Ma J. Increased Glycemic Variability Evaluated by Continuous Glucose Monitoring is Associated with Osteoporosis in Type 2 Diabetic Patients. Front Endocrinol (Lausanne) 2022; 13:861131. [PMID: 35733774 PMCID: PMC9207512 DOI: 10.3389/fendo.2022.861131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Subjects with type 2 diabetes mellitus (T2DM) are susceptible to osteoporosis. This study was conducted to evaluate the association between glycemic variability evaluated by continuous glucose monitoring (CGM) and osteoporosis in type 2 diabetic patient. METHODS A total of 362 type 2 diabetic subjects who underwent bone mineral density (BMD) measurement and were monitored by a CGM system from Jan 2019 to May 2020 were enrolled in this cross-sectional study. Glycemic variability was calculated with the Easy GV software, including 24-hour mean blood glucose (24-h MBG), the standard deviation of 24-h MBG (SDBG), coefficient of variation (CV), mean amplitude of glycemic excursions (MAGE), and time in range between 3.9 and 10.0 mmol/L (TIR). Other potential influence factors for osteoporosis were also examined. RESULTS Based on the T-scores of BMD measurement, there were 190 patients with normal bone mass, 132 patients with osteopenia and 40 patients with osteoporosis. T2DM patients with osteoporosis showed a higher 24-h MBG, SDBG, CV, and MAGE, but a lower TIR (all p < 0.05). Multivariate logistic regression analysis revealed that age, female gender, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), serum uric acid (SUA) and MAGE independently contribute to osteoporosis, and corresponding odds ratio [95% confidence interval (CI)] was 1.129 (1.072-1.190), 4.215 (1.613-11.012), 0.801 (0.712-0.901), 2.743 (1.385-5.431), 0.993 (0.988-0.999), and 1.380 (1.026-1.857), respectively. Further receiver operating characteristic analysis with Youden index indicated that the area under the curve and its 95% CI were 0.673 and 0.604-0.742, with the optimal cut-off value of MAGE predicting osteoporosis being 4.31 mmol/L. CONCLUSION In addition to conventional influence factors including age, female gender, BMI, LDL-C and SUA, increased glycemic variability assessed by MAGE is associated with osteoporosis in type 2 diabetic patients.
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18
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Zeng H, Ge J, Xu W, Ma H, Chen L, Xia M, Pan B, Lin H, Wang S, Gao X. Type 2 Diabetes Is Causally Associated With Reduced Serum Osteocalcin: A Genomewide Association and Mendelian Randomization Study. J Bone Miner Res 2021; 36:1694-1707. [PMID: 33956999 DOI: 10.1002/jbmr.4330] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 04/06/2021] [Accepted: 04/29/2021] [Indexed: 12/20/2022]
Abstract
Recent advances indicate that bone and energy metabolism are closely related. However, little direct evidence on causality has been provided in humans. We aimed to assess the association of three bone-related biomarkers-25 hydroxyvitamin D (25OHD), parathyroid hormone (PTH), and osteocalcin (OCN)-with several metabolic phenotypes and investigate any causal relevance to the associations using a Mendelian randomization (MR) study. Serum 25OHD, PTH, and total OCN were measured at baseline in 5169 eligible Chinese participants in Changfeng study. Partial correlation and bivariate GREML analysis were used to estimate phenotypic and genetic correlations, respectively. Multiple linear regression and logistic regression were used to assess linear associations. Genomewide association analysis (GWAS) was performed. Bidirectional two-sample MR analyses were conducted to examine causal relationships between OCN and body mass index (BMI), diastolic blood pressure (DBP), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), glycated hemoglobin A1c (HbA1c), and type 2 diabetes (T2DM), using our GWAS result of OCN and GWAS statistics from Biobank Japan project (BBJ) and the largest meta-analysis of T2DM GWAS in East Asian population. Circulating OCN was significantly associated with higher DBP and HDL-C and decreased TG, blood glucose level, insulin resistance, liver fat content, bone mineral density, BMI, and a favorable body fat distribution pattern. GWAS identified one novel serum PTH locus and two novel serum OCN loci, explaining 0.81% and 1.98% of variances of PTH and OCN levels, respectively. MR analysis suggested a causal effect of T2DM on lower circulating OCN concentration (causal effect: -0.03; -0.05 to -0.01; p = 0.006 for T2DM_BBJ and -0.03; -0.05 to -0.01; p = 0.001 for T2DM_EAS). These findings indicate that T2DM might impact bone remodeling and provide a resource for understanding complex relationships between osteocalcin and metabolic (and related) traits in humans. © 2021 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Hailuan Zeng
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Jieyu Ge
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wenjie Xu
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Hui Ma
- Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lingyan Chen
- Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China
| | - Baishen Pan
- Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Huandong Lin
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
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19
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Ma B, Li C, Pan J, Zhang S, Dong H, Wu Y, Lv J. Causal Associations of Anthropometric Measurements With Fracture Risk and Bone Mineral Density: A Mendelian Randomization Study. J Bone Miner Res 2021; 36:1281-1287. [PMID: 33784428 DOI: 10.1002/jbmr.4296] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 03/16/2021] [Accepted: 03/24/2021] [Indexed: 01/01/2023]
Abstract
Uncovering additional causal clinical traits and exposure variables is important when studying osteoporosis mechanisms and for the prevention of osteoporosis. Until recently, the causal relationship between anthropometric measurements and osteoporosis had not been fully revealed. In the present study, we utilized several state-of-the-art Mendelian randomization (MR) methods to investigate whether height, body mass index (BMI), waist-to-hip ratio (WHR), hip circumference (HC), and waist circumference (WC) are causally associated with two major characteristics of osteoporosis, bone mineral density (BMD) and fractures. Genomewide significant (p ≤ 5 × 10-8 ) single-nucleotide polymorphisms (SNPs) associated with the five anthropometric variables were obtained from previous large-scale genomewide association studies (GWAS) and were utilized as instrumental variables. Summary-level data of estimated bone mineral density (eBMD) and fractures were obtained from a large-scale UK Biobank GWAS. Of the MR methods utilized, the inverse-variance weighted method was the primary method used for analysis, and the weighted-median, MR-Egger, mode-based estimate, and MR pleiotropy residual sum and outlier methods were utilized for sensitivity analyses. The results of the present study indicated that each increase in height equal to a single standard deviation (SD) was associated with a 9.9% increase in risk of fracture (odds ratio [OR] = 1.099; 95% confidence interval [CI] 1.067-1.133; p = 8.793 × 10-10 ) and a 0.080 SD decrease of estimated bone mineral density (95% CI -0.106-(-0.054); p = 2.322 × 10-9 ). We also found that BMI was causally associated with eBMD (beta = 0.129, 95% CI 0.065-0.194; p = 8.113 × 10-5 ) but not associated with fracture. The WHR adjusted for BMI, HC adjusted for BMI, and WC adjusted for BMI were not found to be related to fracture occurrence or eBMD. In conclusion, the present study provided genetic evidence for certain causal relationships between anthropometric measurements and bone mineral density or fracture risk. © 2021 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Baoshan Ma
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
| | - Chongyang Li
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
| | - Jianqiao Pan
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
| | - Shuzheng Zhang
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
| | - Heng Dong
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
| | - Yiming Wu
- College of Information Science and Technology, Dalian Maritime University, Dalian, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
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20
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Fan R, Liu K, Zhou Z. Abnormal Lipid Profile in Fast-Growing Broilers With Spontaneous Femoral Head Necrosis. Front Physiol 2021; 12:685968. [PMID: 34194339 PMCID: PMC8236708 DOI: 10.3389/fphys.2021.685968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 04/26/2021] [Indexed: 11/13/2022] Open
Abstract
This study investigated lipid metabolism in broilers with spontaneous femoral head necrosis (FHN) by determining the levels of markers of the blood biochemistry and bone metabolism. The birds were divided into a normal group and FHN group according to the femoral head scores of 3-, 4-, and 5-week-old chickens with FHN, and a comparative study was conducted. The study showed that spontaneous FHN broilers had a lipid metabolism disorder, hyperlipidemia, and an accumulation of lipid droplets in the femur. In addition, there were significant changes in the bone parameters and blood bone biochemistry markers, and the expression of genes related to lipid metabolism in the femoral head was also significantly increased. Therefore, FHN may result from dyslipidemia, which affects the bone growth and development of broilers.
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Affiliation(s)
| | | | - Zhenlei Zhou
- Department of Veterinary Clinical Science, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
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21
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Sun JY, Zhang H, Zhang Y, Wang L, Sun BL, Gao F, Liu G. Impact of serum calcium levels on total body bone mineral density: A mendelian randomization study in five age strata. Clin Nutr 2021; 40:2726-2733. [PMID: 33933738 DOI: 10.1016/j.clnu.2021.03.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 03/01/2021] [Accepted: 03/09/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND & AIMS Mendelian randomization (MR) studies have reported the causal association between serum calcium levels and bone mineral density (BMD). The results showed that genetically increased serum calcium levels in individuals with normal calcium levels did not increase BMD and could even reduce BMD. However, whether there are differences in the association between serum calcium and BMD in different age strata remains unclear. METHODS We selected eight serum calcium genetic variants with genome-wide significance (P < 5.00E-08) as the potential instrumental variables. We conducted an MR analysis to evaluate the impact of serum calcium levels on total body BMD in five age strata, 0-15, 15-30, 30-45, 45-60, and ≥60 years, using large-scale serum calcium (61,079 individuals) and total body BMD genome-wide association study (66,628 individuals) datasets. For pleiotropy analysis, we used a manual method and four common statistical methods, namely the MR-Egger intercept, MR-PRESSO, heterogeneity, and Steiger filtering tests. For MR analysis, we selected four MR methods, namely inverse-variance weighted, weighted median, MR-Egger, and MR-PRESSO. In addition to the univariable MR analysis, we conducted a multivariate MR analysis taking into account the effect of serum parathyroid hormone levels. RESULTS Univariable MR analysis using the inverse-variance weighted method indicated that per 0.5-mg/dL increase (about 1 standard deviation) in serum calcium levels was statistically significantly associated with reduced total body BMD only in the ≥60 years stratum (effect estimate (beta) = -0.545, 95% confidence interval (CI): -0.892 to -0.198, P = 0.002). The weighted median regression (beta = -0.446, 95% CI: -0.821 to -0.094, P = 1.40E-02) and MR-PRESSO (beta = -0.545, 95% CI: -0.892 to -0.198, P = 0.022) MR methods further supported this suggestive association. The multivariable MR analysis also found a significant association between increased serum calcium levels and reduced total body BMD in the ≥60 years stratum (beta = -0.547, 95% CI: -0.934 to -0.16, P = 0.006). CONCLUSIONS Our results provide genetic evidence that increased serum calcium levels did not improve BMD in the general population and that the elevated serum calcium levels in generally healthy populations, especially in adults older than 60 years, may even reduce the BMD. Our results are comparable with those of recent MR findings.
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Affiliation(s)
- Jing-Yi Sun
- Shandong Provincial Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250021, China
| | - Haihua Zhang
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100069, China
| | - Yan Zhang
- Department of Pathology, The Affiliated Hospital of Weifang Medical University, Weifang, 261053, China
| | - Longcai Wang
- Department of Anesthesiology, The Affiliated Hospital of Weifang Medical University, Weifang, 261053, China
| | - Bao-Liang Sun
- Key Laboratory of Cerebral Microcirculation in Universities of Shandong, Department of Neurology, Second Affiliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China
| | - Feng Gao
- Department of Trauma and Emergency Surgeon, The Second Affiliated Hospital, Harbin Medical University, Harbin, China.
| | - Guiyou Liu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100069, China; Key Laboratory of Cerebral Microcirculation in Universities of Shandong, Department of Neurology, Second Affiliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China; National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Hypoxia Translational Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
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22
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Kho PF, Amant F, Annibali D, Ashton K, Attia J, Auer PL, Beckmann MW, Black A, Brinton L, Buchanan DD, Chanock SJ, Chen C, Chen MM, Cheng THT, Cook LS, Crous-Bous M, Czene K, De Vivo I, Dennis J, Dörk T, Dowdy SC, Dunning AM, Dürst M, Easton DF, Ekici AB, Fasching PA, Fridley BL, Friedenreich CM, García-Closas M, Gaudet MM, Giles GG, Goode EL, Gorman M, Haiman CA, Hall P, Hankinson SE, Hein A, Hillemanns P, Hodgson S, Hoivik EA, Holliday EG, Hunter DJ, Jones A, Kraft P, Krakstad C, Lambrechts D, Le Marchand L, Liang X, Lindblom A, Lissowska J, Long J, Lu L, Magliocco AM, Martin L, McEvoy M, Milne RL, Mints M, Nassir R, Otton G, Palles C, Pooler L, Proietto T, Rebbeck TR, Renner SP, Risch HA, Rübner M, Runnebaum I, Sacerdote C, Sarto GE, Schumacher F, Scott RJ, Setiawan VW, Shah M, Sheng X, Shu XO, Southey MC, Tham E, Tomlinson I, Trovik J, Turman C, Tyrer JP, Van Den Berg D, Wang Z, Wentzensen N, Xia L, Xiang YB, Yang HP, Yu H, Zheng W, Webb PM, Thompson DJ, Spurdle AB, Glubb DM, O'Mara TA. Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer. Int J Cancer 2021; 148:307-319. [PMID: 32851660 PMCID: PMC7757859 DOI: 10.1002/ijc.33206] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 05/08/2020] [Accepted: 05/26/2020] [Indexed: 01/14/2023]
Abstract
Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.
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Affiliation(s)
- Pik-Fang Kho
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Frederic Amant
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals KU Leuven, University of Leuven, Leuven, Belgium
| | - Daniela Annibali
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals KU Leuven, University of Leuven, Leuven, Belgium
| | - Katie Ashton
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Centre for Information Based Medicine, University of Newcastle, Callaghan, New South Wales, Australia
- Discipline of Medical Genetics, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - John Attia
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Paul L. Auer
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin
| | - Matthias W. Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Amanda Black
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Louise Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Daniel D. Buchanan
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia
| | - Stephen J. Chanock
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Chu Chen
- Epidemiology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Maxine M. Chen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Timothy H. T. Cheng
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Linda S. Cook
- University of New Mexico Health Sciences Center, Albuquerque, New Mexico
- Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, Alberta, Canada
| | - Marta Crous-Bous
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Sean C. Dowdy
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Matthias Dürst
- Department of Gynaecology, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Arif B. Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, California
| | - Brooke L. Fridley
- Department of Biostatistics, Kansas University Medical Center, Kansas City, Kansas
| | - Christine M. Friedenreich
- Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, Alberta, Canada
| | - Montserrat García-Closas
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Mia M. Gaudet
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Ellen L. Goode
- Department of Health Science Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Maggie Gorman
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Susan E. Hankinson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Biostatistics & Epidemiology, University of Massachusetts, Amherst, Amherst, Massachusetts
| | - Alexander Hein
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Peter Hillemanns
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Shirley Hodgson
- Department of Clinical Genetics, St George's, University of London, London, UK
| | - Erling A. Hoivik
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Elizabeth G. Holliday
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - David J. Hunter
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Angela Jones
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Camilla Krakstad
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Diether Lambrechts
- VIB Center for Cancer Biology, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Xiaolin Liang
- Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Cancer Center, Oncology Institute, Warsaw, Poland
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Lingeng Lu
- Chronic Disease Epidemiology, Yale School of Medicine, New Haven, Connecticut
| | - Anthony M. Magliocco
- Department of Anatomic Pathology, Moffitt Cancer Center & Research Institute, Tampa, Florida
| | - Lynn Martin
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Mark McEvoy
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Miriam Mints
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Rami Nassir
- Department of Biochemistry and Molecular Medicine, University of California Davis, Davis, California
| | - Geoffrey Otton
- School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Claire Palles
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Loreall Pooler
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Tony Proietto
- School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Timothy R. Rebbeck
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Stefan P. Renner
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Harvey A. Risch
- Chronic Disease Epidemiology, Yale School of Medicine, New Haven, Connecticut
| | - Matthias Rübner
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Ingo Runnebaum
- Department of Gynaecology, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | - Carlotta Sacerdote
- Center for Cancer Prevention (CPO-Peimonte), Turin, Italy
- Human Genetics Foundation (HuGeF), Turin, Italy
| | - Gloria E. Sarto
- Department of Obstetrics and Gynecology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin
| | - Fredrick Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio
| | - Rodney J. Scott
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Discipline of Medical Genetics, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Callaghan, New South Wales, Australia
- Division of Molecular Medicine, Pathology North, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - V. Wendy Setiawan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Xin Sheng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Melissa C. Southey
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Emma Tham
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Clinical Genetics, Karolinska Institutet, Stockholm, Sweden
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Jone Trovik
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jonathan P. Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - David Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Lucy Xia
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Yong-Bing Xiang
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hannah P. Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Herbert Yu
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Penelope M. Webb
- Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Deborah J. Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Amanda B. Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Dylan M. Glubb
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tracy A. O'Mara
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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Cui Z, Feng H, He B, He J, Tian Y. Relationship Between Serum Amino Acid Levels and Bone Mineral Density: A Mendelian Randomization Study. Front Endocrinol (Lausanne) 2021; 12:763538. [PMID: 34858335 PMCID: PMC8630695 DOI: 10.3389/fendo.2021.763538] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND This study aimed to explore the association between serum amino acids (AAs) levels and bone mineral density (BMD). METHODS We performed a two-sample Mendelian randomization (MR) analysis to analyze the associations between the levels of eight AAs and BMD values by using summary-level genome-wide association study (GWAS) data. We applied the MR Steiger filtering method and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test to check for and remove single nucleotide polymorphisms (SNPs) that were horizontally pleiotropic. The associations were estimated with the inverse variance weighted (IVW), MR-Egger, weighted median and MR Robust Adjusted Profile Score (MR.RAPS) methods. RESULTS Our study found that genetically increased isoleucine (Ile) [IVW: effect = 0.1601, 95% confidence interval (CI) = 0.0604 ~ 0.2597, p = 0.0016] and valine (Val) levels (IVW: effect = 0.0953, 95% CI = 0.0251 ~ 0.1655, p = 0.0078) were positively associated with total body BMD (TB-BMD). The results also revealed that genetically increased tyrosine (Tyr) levels were negatively associated with TB-BMD (IVW: effect = -0.1091, 95% CI = -0.1863 ~ -0.0320, p = 0.0055). CONCLUSIONS In this study, associations between serum AA levels and BMD were established. These findings underscore the important role that serum AAs play in the development of osteoporosis and provide evidence that osteoporosis can be prevented and treated by the intake of certain AAs.
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Affiliation(s)
- Zhiyong Cui
- Department of Orthopaedics, Peking University Third Hospital, Beijing, China
- Peking University Third Hospital, Beijing Key Laboratory of Spinal Disease Research, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing, China
| | - Hui Feng
- Department of Orthopaedics, Peking University Third Hospital, Beijing, China
- Peking University Third Hospital, Beijing Key Laboratory of Spinal Disease Research, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing, China
| | - Baichuan He
- Department of Orthopaedics, Peking University Third Hospital, Beijing, China
- Peking University Third Hospital, Beijing Key Laboratory of Spinal Disease Research, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing, China
| | - Jinyao He
- Department of Orthopaedics, Peking University Third Hospital, Beijing, China
- Peking University Third Hospital, Beijing Key Laboratory of Spinal Disease Research, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing, China
| | - Yun Tian
- Department of Orthopaedics, Peking University Third Hospital, Beijing, China
- Peking University Third Hospital, Beijing Key Laboratory of Spinal Disease Research, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing, China
- *Correspondence: Yun Tian,
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Zheng K, Lin L, Cui P, Liu T, Chen L, Yang C, Jiang W. Association of Fibroblast Growth Factor 23 With Ischemic Stroke and Its Subtypes: A Mendelian Randomization Study. Front Genet 2020; 11:608517. [PMID: 33424930 PMCID: PMC7785587 DOI: 10.3389/fgene.2020.608517] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 12/01/2020] [Indexed: 11/13/2022] Open
Abstract
Fibroblast growth factor 23 (FGF23), which is involved in the regulation of vitamin D, is an emerging independent risk factor for cardiovascular diseases. Previous studies have demonstrated a positive association between FGF23 and stroke. In this study, we aimed to assess the association of FGF23 with ischemic stroke and its subtypes by applying a Mendelian randomization (MR) framework. Five genetic variants obtained from a genome-wide association study involving 16,624 European subjects were used as valid instruments of circulating FGF23 levels. MR was applied to infer the causality of FGF23 levels and the risk of ischemic stroke using data from the MEGASTROKE consortium. Subsequently, several MR analyses, including inverse-variance weighted meta-analysis, MR-Egger, weighted median estimate (WME), MR Pleiotropy Residual Sum and Outlier were performed. The heterogeneity test analysis, including Cochran's Q, I 2 test and leave-one-out analysis were also applied. Furthermore, potential horizontal/vertical pleiotropy was assessed. Lastly, the power of MR analysis was tested. Three validated variants were found to be associated with circulating FGF23 levels and were used for further investigation. We found that high expression level of FGF23 was not associated with any ischemic stroke. However, a causal association between genetically predicted FGF23 levels and the risk of large-artery atherosclerotic stroke (LAS) was significant, with an odds ratio of 1.74 (95% confidence interval = 1.08-2.81) per standard deviation increase in circulating FGF23 levels. Our findings provide support for the causal association between FGF23 and LAS, and therefore, offer potential therapeutic targets for LAS. The specific roles of FGF23 in LAS and associated molecules require further investigation.
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Affiliation(s)
- Kai Zheng
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Lingmin Lin
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
- School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
| | - Pan Cui
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Tao Liu
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lin Chen
- Department of Physical Medicine and Rehabilitation, Tianjin Medical University General Hospital, Tianjin, China
| | - Chunsheng Yang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Jiang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
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Mukherjee S, Aseer KR, Yun JW. Roles of Macrophage Colony Stimulating Factor in White and Brown Adipocytes. BIOTECHNOL BIOPROC E 2020. [DOI: 10.1007/s12257-020-0023-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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26
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Mishra BH, Mishra PP, Mononen N, Hilvo M, Sievänen H, Juonala M, Laaksonen M, Hutri-Kähönen N, Viikari J, Kähönen M, Raitakari OT, Laaksonen R, Lehtimäki T. Lipidomic architecture shared by subclinical markers of osteoporosis and atherosclerosis: The Cardiovascular Risk in Young Finns Study. Bone 2020; 131:115160. [PMID: 31759205 DOI: 10.1016/j.bone.2019.115160] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 11/02/2019] [Accepted: 11/18/2019] [Indexed: 11/24/2022]
Abstract
BACKGROUND Studies have shown that osteoporosis and atherosclerosis are comorbid conditions sharing common risk factors and pathophysiological mechanisms. Understanding these is crucial in order to develop shared methods for risk stratification, prevention, diagnosis and treatment. The aim of this study was to apply a system-level bioinformatics approach to lipidome-wide data in order to pinpoint the lipidomic architecture jointly associated with surrogate markers of these complex comorbid diseases. SUBJECTS AND METHODS The study was based on the Cardiovascular Risk in Young Finns Study cohort from the 2007 follow-up (n = 1494, aged 30-45 years, women: 57%). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to analyse the serum lipidome, involving 437 molecular lipid species. The subclinical osteoporotic markers included indices of bone mineral density and content, measured using peripheral quantitative computer tomography from the distal and shaft sites of both the tibia and the radius. The subclinical atherosclerotic markers included carotid and bulbus intima media thickness measured with high-resolution ultrasound. Weighted co-expression network analysis was performed to identify networks of densely interconnected lipid species (i.e. lipid modules) associated with subclinical markers of both osteoporosis and atherosclerosis. The levels of lipid species (lipid profiles) of each of the lipid modules were summarized by the first principal component termed as module eigenlipid. Then, Pearson's correlation (r) was calculated between the module eigenlipids and the markers. Lipid modules that were significantly and jointly correlated with subclinical markers of both osteoporosis and atherosclerosis were considered to be related to the comorbidities. The hypothesis that the eigenlipids and profiles of the constituent lipid species in the modules have joint effects on the markers was tested with multivariate analysis of variance (MANOVA). RESULTS Among twelve studied molecular lipid modules, we identified one module with 105 lipid species significantly and jointly associated with both subclinical markers of both osteoporosis (r = 0.24, p-value = 2 × 10-20) and atherosclerosis (r = 0.16, p-value = 2 × 10-10). The majority of the lipid species in this module belonged to the glycerolipid (n = 60), glycerophospholipid (n = 13) and sphingolipid (n = 29) classes. The module was also enriched with ceramides (n = 20), confirming their significance in cardiovascular outcomes and suggesting their joint role in the comorbidities. The top three of the 37 statistically significant (adjusted p-value < 0.05) lipid species jointly associated with subclinical markers of both osteoporosis and atherosclerosis within the module were all triacylglycerols (TAGs) - TAG(18:0/18:0/18:1) with an adjusted p-value of 8.6 × 10-8, TAG(18:0/18:1/18:1) with an adjusted p-value of 3.7 × 10-6, and TAG(16:0/18:0/18:1) with an adjusted p-value of 8.5 × 10-6. CONCLUSION This study identified a novel lipid module associated with both surrogate markers of both subclinical osteoporosis and subclinical atherosclerosis. Alterations in the metabolism of the identified lipid module and, more specifically, the TAG related molecular lipids within the module may provide potential new biomarkers for testing the comorbidities, opening avenues for the emergence of dual-purpose prevention measures.
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Affiliation(s)
- Binisha H Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | | | | | - Markus Juonala
- Department of Medicine, University of Turku, Turku, Finland; Division of Medicine, Turku University Hospital, Turku, Finland; Research centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | | | - Nina Hutri-Kähönen
- Department of Paediatrics, Tampere University Hospital, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jorma Viikari
- Department of Medicine, University of Turku, Turku, Finland; Division of Medicine, Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Clinical Physiology, Tampere University Hospital, Tampere Finland
| | - Olli T Raitakari
- Research centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland; Centre for Population Health Research, University of Turku and Turku University Hospital, Turku Finland
| | - Reijo Laaksonen
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Zora Biosciences Oy, Espoo, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
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27
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Zheng J, Frysz M, Kemp JP, Evans DM, Davey Smith G, Tobias JH. Use of Mendelian Randomization to Examine Causal Inference in Osteoporosis. Front Endocrinol (Lausanne) 2019; 10:807. [PMID: 31824424 PMCID: PMC6882110 DOI: 10.3389/fendo.2019.00807] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 11/04/2019] [Indexed: 12/15/2022] Open
Abstract
Epidemiological studies have identified many risk factors for osteoporosis, however it is unclear whether these observational associations reflect true causal effects, or the effects of latent confounding or reverse causality. Mendelian randomization (MR) enables causal relationships to be evaluated, by examining the relationship between genetic susceptibility to the risk factor in question, and the disease outcome of interest. This has been facilitated by the development of two-sample MR analysis, where the exposure and outcome are measured in different studies, and by exploiting summary result statistics from large well-powered genome-wide association studies that are available for thousands of traits. Though MR has several inherent limitations, the field is rapidly evolving and at least 14 methodological extensions have been developed to overcome these. The present paper aims to discuss some of the limitations in the MR analytical framework, and how this method has been applied to the osteoporosis field, helping to reinforce conclusions about causality, and discovering potential new regulatory pathways, exemplified by our recent MR study of sclerostin.
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Affiliation(s)
- Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Monika Frysz
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - John P. Kemp
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
| | - David M. Evans
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jonathan H. Tobias
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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