Impact of serum calcium levels on total body bone mineral density: A mendelian randomization study in five age strata

Association of coffee intake with bone mineral density: a Mendelian randomization study

Background

In observational studies, the relationship between coffee intake and bone mineral density (BMD) is contradictory. However, residual confounding tends to bias the results of these studies. Therefore, we used a two-sample Mendelian randomization (MR) approach to further investigate the potential causal relationship between the two.

Methods

Genetic instrumental variables (IVs) associated with coffee intake were derived from genome-wide association studies (GWAS) of the Food Frequency Questionnaire (FFQ) in 428,860 British individuals and matched using phenotypes in PhenoScanner. Summarized data on BMD were obtained from 537,750 participants, including total body BMD (TB-BMD), TB-BMD in five age brackets ≥60, 45-60, 30-45, 15-30, and 0-15 years, and BMD in four body sites: the lumbar spine, the femoral neck, the heel, and the ultradistal forearm. We used inverse variance weighting (IVW) methods as the primary analytical method for causal inference. In addition, several sensitivity analyses (MR-Egger, Weighted median, MR-PRESSO, Cochran's Q test, and Leave-one-out test) were used to test the robustness of the results.

Results

After Bonferroni correction, Coffee intake has a potential positive correlation with total body BMD (effect estimate [Beta]: 0.198, 95% confidence interval [Cl]: 0.05-0.35, P=0.008). In subgroup analyses, coffee intake was potentially positively associated with TB-BMD (45-60, 30-45 years) (Beta: 0.408, 95% Cl: 0.12-0.69, P=0.005; Beta: 0.486, 95% Cl: 0.12-0.85, P=0.010). In addition, a significant positive correlation with heel BMD was also observed (Beta: 0.173, 95% Cl: 0.08-0.27, P=0.002). The results of the sensitivity analysis were generally consistent.

Conclusion

The results of the present study provide genetic evidence for the idea that coffee intake is beneficial for bone density. Further studies are needed to reveal the biological mechanisms and offer solid support for clinical guidelines on osteoporosis prevention.

Hair and Serum Trace Element and Mineral Levels Profiles in Women with Premenopausal and Postmenopausal Osteoporosis

The objective of the present study was to evaluate serum and hair trace element and mineral levels in women with osteoporosis, as well as to estimate the impact of menopausal status on the profile of trace element and mineral status in women with osteoporosis. 207 women with diagnosed osteoporosis 22-85 years-of-age, and 197 healthy women of the respective age participated in the present study. Analysis of the levels of mineral and trace element in hair and serum samples was performed by inductively-coupled plasma mass-spectrometry (ICP-MS). Women with osteoporosis were characterized by significantly lower hair Ca, Mg, Co, I, Li, and Mn levels, as well as serum Ca, Mg, Co, Fe, V, and Zn concentrations compared to women in the control group. After additional grouping according to menopausal status, the lowest hair Ca and Mg content was observed in postmenopausal osteoporotic women, whereas serum Ca and Mg concentrations were the lowest in premenopausal osteoporotic women. Hair Co, Mn, and Zn levels in postmenopausal osteoporotic women were lower than in healthy postmenopausal women. The lowest circulating Zn levels were observed in osteoporotic postmenopausal women. Taken together, decreased hair and serum levels in osteoporotic women are indicative of increased risk of Ca, Mg, Co, and Zn deficiency in women with osteoporosis. In turn, alterations in hair trace element and mineral levels in osteoporosis are more profound in postmenopausal women. Hypothetically, improvement in trace element and mineral metabolism especially in postmenopausal women may be considered as a potential strategy for mitigating osteoporosis.

A diagnostic approach integrated multimodal radiomics with machine learning models based on lumbar spine CT and X-ray for osteoporosis

INTRODUCTION

The aim of this analysis is to construct a combined model that integrates radiomics, clinical risk factors, and machine learning algorithms to diagnose osteoporosis in patients and explore its potential in clinical applications.

MATERIALS AND METHODS

A retrospective analysis was conducted on 616 lumbar spine. Radiomics features were extracted from the computed tomography (CT) scans and anteroposterior and lateral X-ray images of the lumbar spine. Logistic regression (LR), support vector machine (SVM), and random forest (RF) algorithms were used to construct radiomics models. The receiver operating characteristic curve (ROC) was employed to select the best-performing model. Clinical risk factors were identified through univariate logistic regression analysis (ULRA) and multivariate logistic regression analysis (MLRA) and utilized to develop a clinical model. A combined model was then created by merging radiomics and clinical risk factors. The performance of the models was evaluated using ROC curve analysis, and the clinical value of the models was assessed using decision curve analysis (DCA).

RESULTS

A total of 4858 radiomics features were extracted. Among the radiomics models, the SVM model demonstrated the optimal diagnostic capabilities and accuracy, with an area under the curve (AUC) of 0.958 (0.9405-0.9762) in the training cohort and 0.907 (0.8648-0.9492) in the test cohort. Furthermore, the combined model exhibited an AUC of 0.959 (0.9412-0.9763) in the training cohort and 0.910 (0.8690-0.9506) in the test cohort.

CONCLUSION

The combined model displayed outstanding ability in diagnosing osteoporosis, providing a safe and efficient method for clinical decision-making.

Age-specific effects of weight-based body size on fracture risk in later life: a lifecourse Mendelian randomisation study

Musculoskeletal conditions, including fractures, can have severe and long-lasting consequences. Higher body mass index in adulthood is widely acknowledged to be protective for most fracture sites. However, sources of bias induced by confounding factors may have distorted previous findings. Employing a lifecourse Mendelian randomisation (MR) approach by using genetic instruments to separate effects at different life stages, this investigation aims to explore how prepubertal and adult body size independently influence fracture risk in later life.Using data from a large prospective cohort, univariable and multivariable MR were conducted to simultaneously estimate the effects of age-specific genetic proxies for body size (n = 453,169) on fracture risk (n = 416,795). A two-step MR framework was additionally applied to elucidate potential mediators. Univariable and multivariable MR indicated strong evidence that higher body size in childhood reduced fracture risk (OR, 95% CI: 0.89, 0.82 to 0.96, P = 0.005 and 0.76, 0.69 to 0.85, P = 1 × 10- 6, respectively). Conversely, higher body size in adulthood increased fracture risk (OR, 95% CI: 1.08, 1.01 to 1.16, P = 0.023 and 1.26, 1.14 to 1.38, P = 2 × 10- 6, respectively). Two-step MR analyses suggested that the effect of higher body size in childhood on reduced fracture risk was mediated by its influence on higher estimated bone mineral density (eBMD) in adulthood.This investigation provides novel evidence that higher body size in childhood reduces fracture risk in later life through its influence on increased eBMD. From a public health perspective, this relationship is complex since obesity in adulthood remains a major risk factor for co-morbidities. Results additionally indicate that higher body size in adulthood is a risk factor for fractures. Protective effect estimates previously observed are likely attributed to childhood effects.

Effects of <em>eleutherine bulbosa</em> (mill.) urb. bulb extract on mice glucocorticoid-induced osteoporosis models

Background: Low bone mass accompanied by microarchitectural alterations in the bone that cause fragility fractures is known as secondary osteoporosis and occurs when there is an underlying condition or medication present. Eleutherine bulbosa bulb extract has been shown to affect bone because of its content, which can help osteoblast differentiation and inhibit osteoclast differentiation. Objective: This study aimed to assess the effects of 70% ethanol extract of E. bulbosa Bulbs (EBE) from Pasuruan-East Java on blood calcium levels, osteoblast cell count, and bone density of trabecular femur in osteoporosis rats. Methods: Six groups of 30 female Wistar rats were created. There were no test materials offered to the healthy group; the negative group received 0.5% CMC; the positive group received alendronate 0.9 mg/kg BW; and the dose group received 30, 60, and 120 mg/kg BW. Glucocorticoid (Dexamethasone) 0.1015 mg/kg BW/day induction was given to all groups except the healthy group to create osteoporosis rats for approximately four weeks. Then they were given oral therapy for approximately 28 days. Followed by the determination of blood calcium levels, the number of osteoblast cells, and bone density of the rat femur trabecular. Results: The result showed that E. bulbosa bulbs extract could raise blood calcium levels and bone density percentage at doses of 60 and 120 mg/kg BW, as well as raise osteoblast cell levels at doses of 120 mg/kg BW. Conclusions: The findings indicate that E.bulbosa bulb extract is a potential complementary medicine for osteoporosis.

Causal association of genetically determined circulating vitamin D metabolites and calcium with multiple sclerosis in participants of European descent

BACKGROUND

Vitamin D is an important regulator of calcium. Mendelian randomization (MR) studies exclusively focused on the circulating total 25-hydroxyvitamin D (25(OH)D) as a biomarker of vitamin D status, and have found the causal association between 25(OH)D and the risk of multiple sclerosis (MS). However, it currently remains unclear about the causal association of the 25(OH)D subtypes including 25(OH)D3 and C3-epi-25(OH)D3, as well as calcium with the risk of MS.

METHODS

We performed a two-sample MR study to evaluate the causal association of circulating total 25(OH)D, 25(OH)D3, C3-epi-25(OH)D3, and calcium with the risk of MS using large-scale genome-wide association studies (GWAS) datasets from total 25(OH)D (n = 417,580), 25(OH)D3 (n = 40,562), C3-epi-25(OH)D3 (n = 40,562), calcium (n = 305,349), and MS (14,802 MS and 26,703 controls). We selected five MR methods including inverse-variance weighted (IVW), simple median, weighted median, MR-Egger, MR-PRESSO (Mendelian Randomization Pleiotropy Residual Sum and Outlier), and contamination mixture method.

RESULTS

IVW showed that the genetically increased circulating 25(OH)D level (OR = 0.81, 95% CI: 0.70-0.94, P = 4.00E-03), circulating 25(OH)D3 level (OR = 0.85, 95% CI: 0.76-0.95, P = 5.00E-03), and circulating C3-epi-25(OH)D3 level (OR = 0.85, 95% CI: 0.74-0.98, P = 2.30E-02) were causally associated with reduced risk of MS. However, IVW showed no causal association between circulating calcium level and the risk of MS with OR = 2.85, 95% CI: 0.42-19.53, P = 2.85E-01.

CONCLUSIONS

Our current findings together with evidence from other MR studies support the use of vitamin D but not calcium supplementation for the prevention of MS.

A Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field

Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non-expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Mendelian randomization analysis of the causal association of bone mineral density and fracture with multiple sclerosis

Multiple sclerosis (MS) is a neurodegenerative disorder and an autoimmune disease. Until now, observational studies have indicated the association of bone mineral density (BMD) and fracture with the risk of MS. However, these studies indicated inconsistent findings. Until now, genome-wide association studies (GWAS) have been conducted in BMD, fracture, and MS, which provide large-scale datasets to investigate the causal association of BMD and fracture with the risk of MS using the Mendelian randomization (MR) study. Here, we performed an MR study to clarify the causal association between BMD/fracture and the risk of MS using large-scale publicly available GWAS datasets from BMD, fracture, and MS. We first evaluated the bidirectional causal effects of BMD and MS. The main analysis method inverse-variance weighted (IVW) showed no significant causal effect of BMD on the risk of MS (β = 0.058, and p = 1.98E-01), and MS on the risk of BMD (β = −0.001, and p = 7.83E-01). We then evaluated the bidirectional causal effects of fracture and MS. However, we only identified a significant causal effect of fracture on the risk of MS using IVW (β = −0.375, p = 0.002), but no significant causal effect of MS on the risk of the fracture using IVW (β = 0.011, p = 2.39E-01). Therefore, our main analysis method IVW only found a significant causal effect of fracture on MS using the threshold for the statistically significant association p < 0.05/4 = 0.0125. Meanwhile, multivariable MR analyses showed that the causal effect of fracture on MS was independent of smoking, drinking, and obesity, but dependent on BMD. In summary, our MR analysis demonstrates that genetically increased fracture may reduce the risk of MS. Our findings should be further verified and the underlying mechanisms should be further evaluated by future studies.

Total Brain Volumetric Measures and Schizophrenia Risk: A Two-Sample Mendelian Randomization Study

Schizophrenia (SCZ) is an idiopathic psychiatric disorder with a heritable component and a substantial public health impact. Although abnormalities in total brain volumetric measures (TBVMs) have been found in patients with SCZ, it is still unknown whether these abnormalities have a causal effect on the risk of SCZ. Here, we performed a Mendelian randomization (MR) study to investigate the possible causal associations between each TBVM and SCZ risk. Specifically, genome-wide association study (GWAS) summary statistics of total gray matter volume, total white matter volume, total cerebrospinal fluid volume, and total brain volume were obtained from the United Kingdom Biobank database (33,224 individuals), and SCZ GWAS summary statistics were provided by the Psychiatric Genomics Consortium (150,064 individuals). The main MR analysis was conducted using the inverse variance weighted method, and other MR methods, including MR-Egger, weighted median, simple mode, and weighted mode methods, were performed to assess the robustness of our findings. For pleiotropy analysis, we employed three approaches: MR-Egger intercept, MR-PRESSO, and heterogeneity tests. No TBVM was causally associated with SCZ risk according to the MR results, and no significant pleiotropy or heterogeneity was found for instrumental variables. Taken together, this study suggested that alterations in TBVMs were not causally associated with the risk of SCZ.

Educational Attainment and Ischemic Stroke: A Mendelian Randomization Study

Observational studies have evaluated the potential association of socioeconomic factors such as higher education with the risk of stroke but reported controversial findings. The objective of our study was to evaluate the potential causal association between higher education and the risk of stroke. Here, we performed a Mendelian randomization analysis to evaluate the potential association of educational attainment with ischemic stroke (IS) using large-scale GWAS datasets from the Social Science Genetic Association Consortium (SSGAC, 293,723 individuals), UK Biobank (111,349 individuals), and METASTROKE consortium (74,393 individuals). We selected three Mendelian randomization methods including inverse-variance-weighted meta-analysis (IVW), weighted median regression, and MR–Egger regression. IVW showed that each additional 3.6-year increase in years of schooling was significantly associated with a reduced IS risk (OR = 0.54, 95% CI: 0.41–0.71, and p = 1.16 × 10^–5). Importantly, the estimates from weighted median (OR = 0.49, 95% CI: 0.33–0.73, and p = 1.00 × 10^–3) and MR–Egger estimate (OR = 0.18, 95% CI: 0.06–0.60, and p = 5.00 × 10^–3) were consistent with the IVW estimate in terms of direction and magnitude. In summary, we provide genetic evidence that high education could reduce IS risk.

Health effects of high serum calcium levels: Updated phenome-wide Mendelian randomisation investigation and review of Mendelian randomisation studies

Background

Calcium plays a role in a wide range of biological functions. Here we conducted a phenome-wide Mendelian randomisation (MR-PheWAS) analysis and a systematic review for MR studies to comprehensively investigate the health effects of serum calcium.

Methods

One-hundred and thirty genetic variants strongly associated with serum calcium levels were used as instrumental variables. A phenome-wide association analysis (PheWAS) was conducted to examine the associations of genetically predicted serum calcium with 1473 distinct phenotypes in the UK Biobank including 339,197 individuals. Observed associations in PheWAS were further tested for replication in two-sample MR replication analysis. A systematic review for MR studies on serum calcium was performed to synthesize the published evidence and compare with the current MR-PheWAS findings.

Findings

Higher genetically predicted calcium levels were associated with decreased risk of 5 diseases in dermatologic and musculoskeletal systems and increased risk of 17 diseases in circulatory, digestive, endocrine, genitourinary and immune systems. Eight associations were replicated in two-sample MR analysis. These included decreased risk of osteoarthritis and increased risk of coronary artery disease, myocardial infarction, coronary atherosclerosis, hyperparathyroidism, disorder of parathyroid gland, gout, and calculus of kidney and ureter with increased serum calcium. Systematic review of 25 MR studies provided supporting evidence on five out of the eight disease outcomes, while the increased risk of gout, hyperparathyroidism and disorder of parathyroid gland were novel findings.

Interpretation

This study found wide-ranged health effects of high serum calcium, which suggests that the benefits and adversities of strategies promoting calcium intake should be assessed.

Funding

ET is supported by a CRUK Career Development Fellowship (C31250/A22804). XL is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province. SCL acknowledges research funding from the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council (Vetenskapsrådet, 2019-00977), and the Swedish Cancer Society (Cancerfonden).

Matrix Metalloproteinases in Relation to Bone Mineral Density: A Two-Sample Mendelian Randomization Study

Background: We aimed at investigating causal associations between matrix metalloproteinases (MMPs) and bone mineral density (BMD) by the Mendelian randomization (MR) analysis. Methods: From genome-wide association studies of European ancestry, we selected instrumental variables for MMP-1, MMP-3, MMP-7, MMP-8, MMP-10, and MMP-12. Accordingly, we retrieved summary statistics of three site-specific BMD, namely, forearm, femoral neck, and lumbar spine. We conducted an inverse variance weighted MR as the primary method to compute overall effects from multiple instruments, while additional MR approaches and sensitivity analyses were implemented. Bonferroni-adjusted significance threshold was set at p < 0.05/18 = 0.003. Results: Totally, there was no evidence for causal effects of genetically-predicted levels of MMPs on BMD measurement at three common sites. MR results indicated that there were no causal associations of circulating MMPs with forearm BMD (all p ≥ 0.023) by the inverse variance weighted method. Similarly, there were no causal effects of MMPs on femoral neck BMD (all p ≥ 0.120) and MR results did not support causal relationships between MMPs and lumbar spine BMD (all p ≥ 0.017). Multiple sensitivity analyses suggested the robustness of MR results, which were less likely to be biased by unbalanced pleiotropy or evident heterogeneity. Conclusion: We found no evidence for the causal relationship between MMPs and BMD in the European population.

An Updated Mendelian Randomization Analysis of the Association Between Serum Calcium Levels and the Risk of Alzheimer's Disease

It has been a long time that the relationship between serum calcium levels and Alzheimer’s disease (AD) remains unclear. Until recently, observational studies have evaluated the association between serum calcium levels and the risk of AD, however, reported inconsistent findings. Meanwhile, a Mendelian randomization (MR) study had been conducted to test the causal association between serum calcium levels and AD risk, however, only selected 6 serum calcium SNPs as the instrumental variables. Hence, these findings should be further verified using additional more genetic variants and large-scale genome-wide association study (GWAS) dataset to increase the statistical power. Here, we conduct an updated MR analysis of the causal association between serum calcium levels and the risk of AD using a two-stage design. In discovery stage, we conducted a MR analysis using 14 SNPs from serum calcium GWAS dataset (N = 61,079), and AD GWAS dataset (N = 63,926, 21,982 cases, 41,944 cognitively normal controls). All four MR methods including IVW, weighted median, MR-Egger, and MR-PRESSO showed a reduced trend of AD risk with the increased serum calcium levels. In the replication stage, we performed a MR analysis using 166 SNPs from serum calcium GWAS dataset (N = 305,349), and AD GWAS dataset (N = 63,926, 21,982 cases, 41,944 cognitively normal controls). Only the weighted median indicated that genetically increased serum calcium level was associated with the reduced risk of AD. Hence, additional studies are required to investigate these findings.

Evaluating the Causal Association Between Educational Attainment and Asthma Using a Mendelian Randomization Design

Asthma is a common chronic respiratory disease. In the past 10 years, genome-wide association study (GWAS) has been widely used to identify the common asthma genetic variants. Importantly, these publicly available asthma GWAS datasets provide important data support to investigate the causal association of kinds of risk factors with asthma by a Mendelian randomization (MR) design. It is known that socioeconomic status is associated with asthma. However, it remains unclear about the causal association between socioeconomic status and asthma. Here, we selected 162 independent educational attainment genetic variants as the potential instruments to evaluate the causal association between educational attainment and asthma using large-scale GWAS datasets of educational attainment (n = 405,072) and asthma (n = 30,810). We conducted a pleiotropy analysis using the MR-Egger intercept test and the MR pleiotropy residual sum and outlier (MR-PRESSO) test. We performed an MR analysis using inverse-variance weighted, weighted median, MR-Egger, and MR-PRESSO. The main analysis method inverse-variance weighted indicated that each 1 standard deviation increase in educational attainment (3.6 years) could reduce 35% asthma risk [odds ratio (OR) = 0.65, 95% confidence interval (CI) 0.51–0.85, P = 0.001]. Importantly, evidence from other MR methods further supported this finding, including weighted median (OR = 0.55, 95% CI 0.38–0.80, P = 0.001), MR-Egger (OR = 0.48, 95% CI 0.16–1.46, P = 0.198), and MR-PRESSO (OR = 0.65, 95% CI 0.51–0.85, P = 0.0015). Meanwhile, we provide evidence to support that educational attainment protects against asthma risk dependently on cognitive performance using multivariable MR analysis. In summary, we highlight the protective role of educational attainment against asthma. Our findings may have public health applications and deserve further investigation.