A Mendelian Randomization Study of the Effect of Type-2 Diabetes and Glycemic Traits on Bone Mineral Density

Insulin resistance, bone health, and fracture risk

Insulin resistance, defined as an impaired biological response to insulin stimulation in target tissues, arises most frequently in the presence of central obesity. Although obesity is generally associated with increased bone mass, recent data challenge this view and, if complicated by T2DM, obese patients are at high risk for fragility fractures. IR may play a key role in this increased fracture risk through effects on bone quality rather than bone quantity. Further understanding of the mechanisms and approaches to prevent osteoporotic fractures in IR-related diseases is needed.

CLINICAL RELEVANCE

The dramatic increase in obesity and metabolic syndrome (MetS) over the last half-century has led to a worldwide epidemic of type 2 diabetes mellitus (T2DM) as well as in the incidence of insulin resistance (IR). IR is defined as an impaired biological response to insulin stimulation in target tissues and is primarily related to the liver, muscle, and adipose tissue. The most frequent underlying cause is central obesity, and it is known that excess abdominal adipose tissue secretes increased amounts of free fatty acids, which directly affects insulin signalling, reduces glucose uptake in muscle, and triggers excessive triglyceride synthesis and gluconeogenesis in the liver. When pancreatic β cells are unable to secrete the higher levels of insulin needed, T2DM, the main complication of IR, occurs.

OBSERVATIONS

Although obesity is generally associated with increased bone mass, recent data challenge this view and highlight the multifaceted nature of the obesity-bone relationship. Patients with T2DM are at significant risk for well-known complications of diabetes, including retinopathy, nephropathy, macrovascular disease, and neuropathy, but it is clear that they are also at high risk for fragility fractures. Moreover, recent data provide strong evidence that IR may key role in the increased fracture risk observed in both obesity and T2DM.

CONCLUSIONS

In this concise review article, the role of IR in increased risk of osteoporotic fractures in MetS, obesity, and T2DM is discussed and summarised, including consideration of the need for fracture risk assessment as a 'preventive measure', especially in patients with T2DM and chronic MetS with abdominal obesity. Personalised and targeted diagnostic and therapeutic approaches to prevent osteoporotic fractures in IR-related diseases are needed and could make significant contributions to health outcomes.

Mining Candidate Genes and Identifying Risk Factors for Leg Disease in Broilers: A Mendelian Randomization Study

Clinical investigations have highlighted disruptions in bone metabolic processes and abnormal fluctuations in serum indicator levels during the onset of leg disease (LD) in broilers. However, the presence of a genetic causal relationship for this association remains undetermined. Therefore, the aim of this study is to discern the risk factors underlying LD development using 1235 sequenced white-feathered broilers. We employed Mendelian randomization (MR) analysis to assess the associations of bone strength (BS), bone mineral density (BMD), tibial bone weight (TBW), tibial bone length (TBL), tibial bone diameter (TBD), bone ash (BA), ash calcium (Ash Ca), ash phosphorus (Ash P), serum calcium (Ca), serum phosphorus (P), serum alkaline phosphatase (ALP), and serum osteoprotegerin (OPG) with the incidence of LD. Compelling evidence underscores a causal link between the risk of developing LD and decreased BMD (odds ratio (OR) = 0.998; 95% CI: 0.983, 0.993; P < 0.001) and narrower TBD (OR = 0.985, 95% CI: 0.975, 0.994, P = 0.002). Additionally, serum OPG concentrations (OR: 0.995, 95% CI: 0.992, 0.999, P = 0.008) were associated with BMD (OR = 0.0078, 95% CI = 0.0043 to 0.0140, P < 0.001), indicating a robust genetic relationship between ALP concentrations (OR: 0.988, 95% CI: 0.984, 0.993, P < 0.001) and TBD (OR = 0.0046, 95% CI = 0.0026, 0.0083, P < 0.001). Moreover, elevated serum Ca (OR: 0.564, 95% CI: 0.487, 0.655, P < 0.001) and P (OR: 0.614, 95% CI: 0.539, 0.699, P < 0.001) levels were associated with a narrower TBD. Elevated serum levels of Ca, P, ALP, and OPG contribute to disturbances in bone metabolism, while decreased BMD and narrower TBD are associated with a greater risk of developing LD in broilers. This discovery elucidates the metabolic risk factors for LD in broilers and could provide information on LDs, such as osteoporosis, in humans.

Effect of Tai Chi exercise on bone health and fall prevention in postmenopausal women: a meta-analysis

BACKGROUND

The bone status of postmenopausal women is worsening. In fact, postmenopausal period is the high incidence stage of osteoporosis and falls. Notably, a recent study has pointed out that exercise can improve bone health in postmenopausal women. However, the effect of Tai Chi exercise on postmenopausal women is controversial. Therefore, a meta-analysis was designed to analyze the effect of Tai Chi exercise on bone health and fall prevention in postmenopausal women.

METHODS

The researches on Tai Chi improving the bone health of postmenopausal women before August 31, 2023 were collected from Chinese and English databases, such as PubMed, Embase, and Web of Science, etc. The risk of bias of the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials. Besides, R software 4.3.1 was employed to analyze the effect sizes in the meta-analysis to summarize the impact of Tai Chi on vertebral bone mineral density, serum calcium, clinical balance scores, the number of falls, total falls, and health status scores in postmenopausal women.

RESULTS

There were 12 studies eventually included in this meta-analysis. A total of 1,272 postmenopausal women were involved, including 628 in the experimental group (intervention with Tai Chi exercise) and 644 in the control group (without any intervention). Briefly, postmenopausal women practicing Tai Chi presented a significant increase in vertebral bone density [standardized mean difference (SMD) = 0.37, 95% confidence interval (CI) (0.04-0.71), P = 0.03] and health status score [SMD = 0.25, 95% CI (0.01-0.49), P = 0.04]. In contrast, there were no significant differences for postmenopausal women between the two groups in terms of serum calcium [SMD = -0.01, 95% CI (-0.39, 0.36), P = 0.77], clinical balance [SMD = 0.17, 95% CI (-0.01, 0.46), P = 0.23], number of falls [SMD = -0.61, 95% CI (-1.24, 0.02), P = 0.06] and total falls [odds ratio = 0.35, 95% CI (0.11-1.12), P = 0.07].

CONCLUSION

Tai Chi exercise can improve the bone mineral density of postmenopausal women, thereby maintaining bone health. Hence, Tai Chi exercise is necessary to prevent osteoporosis.

Genetic predisposition to bone mineral density and their health conditions in East Asians

Osteoporosis, a condition defined by low BMD (typically < -2.5 SD), causes a higher fracture risk and leads to significant economic, social, and clinical impacts. Genome-wide studies mainly in Caucasians have found many genetic links to osteoporosis, fractures, and BMD, with limited research in East Asians (EAS). We investigated the genetic aspects of BMD in 86 716 individuals from the Taiwan Biobank and their causal links to health conditions within EAS. A genome-wide association study (GWAS) was conducted, followed by observational studies, polygenic risk score assessments, and genetic correlation analyses to identify associated health conditions linked to BMD. GWAS and gene-based GWAS studies identified 78 significant SNPs and 75 genes related to BMD, highlighting pathways like Hedgehog, WNT-mediated, and TGF-β. Our cross-trait linkage disequilibrium score regression analyses for BMD and osteoporosis consistently validated their genetic correlations with BMI and type 2 diabetes (T2D) in EAS. Higher BMD was linked to lower osteoporosis risk but increased BMI and T2D, whereas osteoporosis linked to lower BMI, waist circumference, hemoglobinA1c, and reduced T2D risk. Bidirectional Mendelian randomization analyses revealed that a higher BMI causally increases BMD in EAS. However, no direct causal relationships were found between BMD and T2D, or between osteoporosis and either BMI or T2D. This study identified key genetic factors for bone health in Taiwan, and revealed significant health conditions in EAS, particularly highlighting the genetic interplay between bone health and metabolic traits like T2D and BMI.

Is Type 2 Diabetes Mellitus Associated with Spinal Degenerative Disorders?: Evidence from Observational and 2-Sample Mendelian Randomization Analyses

BACKGROUND

Type 2 diabetes mellitus (T2DM) and spinal degenerative disorders (SDD) are common diseases that frequently coexist. However, both traditional observational studies and recent Mendelian randomization (MR) studies have demonstrated conflicting evidence on the association between T2DM and SDD. This comparative study explored and compared the association between T2DM and SDD using observational and MR analyses.

METHODS

For observational analyses, cross-sectional studies (44,972 participants with T2DM and 403,095 participants without T2DM), case-control studies (38,234 participants with SDD and 409,833 participants without SDD), and prospective studies (35,550 participants with T2DM and 392,046 participants without T2DM with follow-up information until 2022) were performed to test the relationship between T2DM and SDD using individual-level data from the U.K. Biobank from 2006 to 2022. For MR analyses, the associations between single-nucleotide polymorphisms with SDD susceptibility obtained using participant data from the U.K. Biobank, which had 407,938 participants from 2006 to 2022, and the FinnGen Consortium, which had 227,388 participants from 2017 to 2022, and genetic predisposition to T2DM obtained using summary statistics from a pooled genome-wide association study involving 1,407,282 individuals were examined. The onset and severity of T2DM are not available in the databases being used.

RESULTS

Participants with T2DM were more likely to have SDD than their counterparts. Logistic regression analysis identified T2DM as an independent risk factor for SDD, which was confirmed by the Cox proportional hazard model results. However, using single-nucleotide polymorphisms as instruments, the MR analyses demonstrated no causal relationship between T2DM and SDD. The lack of such an association was robust in the sensitivity analysis, and no pleiotropy was seen.

CONCLUSIONS

Our results suggest that the association between T2DM and SDD may be method-dependent. Researchers and clinicians should be cautious in interpreting the association, especially the causal association, between T2DM and SDD. Our findings provide fresh insights into the association between T2DM and SDD by various analysis methods and guide future research and clinical efforts in the effective prevention and management of T2DM and SDD.

LEVEL OF EVIDENCE

Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

The single point insulin sensitivity estimator (SPISE) is associated with bone health in Arab adults

BACKGROUND

The Single Point Insulin Sensitivity Estimator (SPISE) index is a surrogate marker for insulin sensitivity. Given the emerging role of bone as an active endocrine organ, its associations with non-invasive measures of extra-skeletal functions such as insulin sensitivity warrant investigation.

AIMS

This study aimed to explore the relationship between the SPISE index and Bone Mineral Density (BMD) in an adult population.

METHODS

Data from a total of 1270 Arab adults (84% females, mean age 56.7 ± 8.1 years) from the Osteoporosis Registry Database of the Chair for Biomarkers of Chronic Diseases in King Saud University, Riyadh, Saudi Arabia was used in this study. T-scores and SPISE were calculated. Regression models were used to determine associations between SPISE and bone health indices.

RESULTS

The low BMD group (N = 853; T-score <-1.0) had significantly higher SPISE values than those with normal BMD (N = 417; T-score - 1.0 and above) (4.6 ± 1.3 vs. 4.3 ± 1.2, p < 0.001). Multivariate linear regression, adjusted for covariates, confirmed a significant inverse association between SPISE and BMD for all participants (β=-0.22, p < 0.001), as well as both groups [normal BMD (β = -0.10, p = 0.02) and low BMD groups (β = -0.15, p < 0.001)]. SPISE, family history of T2DM, and history of fractures collectively account for 17% of the variances perceived in T-score for all participants (p < 0.001).

CONCLUSIONS

A significant inverse association between the SPISE index and BMD was observed in adults, suggesting a link between BMD and extra-skeletal health. Underlying mechanisms need to be investigated prospectively using BMD as secondary outcomes in lifestyle modification programs.

Dynamic Foot Pressure During Walking: A Potential Indicator of Bone Mineral Density

BACKGROUND

Physical skeletal loading can affect the bone mineral density (BMD). This study investigated the association between BMD and dynamic foot pressure during gait.

METHODS

A total of 104 patients (mean age, 62.6 ± 12.4 years; 23 male and 81 female) who underwent dual x-ray absorptiometry and pedobarography were included. BMD values of the lumbar spine, femoral neck, and total femur were assessed. The mean and maximum pressures were measured at the hallux, lesser toes, 1st metatarsal head, 2nd and 3rd metatarsal heads, 4th and 5th metatarsal heads, midfoot, medial heel, and lateral heel. Multivariable regression analysis was performed to identify factors significantly associated with BMD.

RESULTS

The lumbar spine BMD was significantly associated with the mean pressure at the 4th and 5th metatarsal heads (p = 0.041, adjusted R 2 of model = 0.081). The femoral neck BMD was significantly associated with the maximum pressure at the 2nd and 3rd metatarsal heads (p = 0.002, adjusted R 2 = 0.213). The total femoral BMD also showed a significant association with the maximum pressure at the 2nd and 3rd metatarsal heads (p = 0.003, adjusted R 2 = 0.360).

CONCLUSIONS

Foot plantar pressure during gait was significantly associated with BMD, and could potentially be used to predict the presence of osteoporosis.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Effects of sodium-glucose cotransporter 2 inhibitors on bone metabolism in patients with type 2 diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Sodium glucose cotransporter 2 (SGLT2) inhibitors are widely used in type 2 diabetes mellitus (T2DM) therapy. The impact of SGLT2 inhibitors on bone metabolism has been widely taken into consideration. But there are controversial results in the study on the effect of SGLT2 inhibitors on bone metabolism in patients with T2DM. Therefore, we aimed to examine whether and to what extent SGLT2 inhibitors affect bone metabolism in patients with T2DM.

METHODS

A literature search of randomized controlled trials (RCTs) was conducted through PubMed, Web of Science, Embase, Cochrane databases, and Scopus from inception until 15 April 2023. Eligible RCTs compared the effects of SGLT2 inhibitors versus placebo on bone mineral density and bone metabolism in patients with T2DM. To evaluate the differences between groups, a meta-analysis was conducted using the random effects inverse-variance model by utilizing standardized mean differences (SMD).

RESULTS

Through screening, 25 articles were finally included, covering 22,828 patients. The results showed that, compared with placebo, SGLT2 inhibitors significantly increased parathyroid hormone (PTH, SMD = 0.13; 95%CI: 0.06, 0.20), and cross-linked C-terminal telopeptides of type I collagen (CTX, SMD = 0.11; 95%CI: 0.01, 0.21) in patients with T2DM, decreased serum alkaline phosphatase levels (ALP, SMD = -0.06; 95%CI: -0.10, -0.03), and had no significant effect on bone mineral density (BMD), procollagen type 1 N-terminal propeptide (P1NP), 25-hydroxy vitamin D, tartrate resistant acid phosphatase-5b (TRACP-5b) and osteocalcin.

CONCLUSIONS

SGLT2 inhibitors may negatively affect bone metabolism by increasing serum PTH, CTX, and decreasing serum ALP. This conclusion needs to be verified by more studies due to the limited number and quality of included studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, identifier CRD42023410701.

Diabetes and osteoporosis: a two-sample mendelian randomization study

BACKGROUND

The effects on bone mineral density (BMD)/fracture between type 1 (T1D) and type 2 (T2D) diabetes are unknown. Therefore, we aimed to investigate the causal relationship between the two types of diabetes and BMD/fracture using a Mendelian randomization (MR) design.

METHODS

A two-sample MR study was conducted to examine the causal relationship between diabetes and BMD/fracture, with three phenotypes (T1D, T2D, and glycosylated hemoglobin [HbA1c]) of diabetes as exposures and five phenotypes (femoral neck BMD [FN-BMD], lumbar spine BMD [LS-BMD], heel-BMD, total body BMD [TB-BMD], and fracture) as outcomes, combining MR-Egger, weighted median, simple mode, and inverse variance weighted (IVW) sensitivity assessments. Additionally, horizontal pleiotropy was evaluated and corrected using the residual sum and outlier approaches.

RESULTS

The IVW method showed that genetically predicted T1D was negatively associated with TB-BMD (β = -0.018, 95% CI: -0.030, -0.006), while T2D was positively associated with FN-BMD (β = 0.033, 95% CI: 0.003, 0.062), heel-BMD (β = 0.018, 95% CI: 0.006, 0.031), and TB-BMD (β = 0.050, 95% CI: 0.022, 0.079). Further, HbA1c was not associated with the five outcomes (β ranged from - 0.012 to 0.075).

CONCLUSIONS

Our results showed that T1D and T2D have different effects on BMD at the genetic level. BMD decreased in patients with T1D and increased in those with T2D. These findings highlight the complex interplay between diabetes and bone health, suggesting potential age-specific effects and genetic influences. To better understand the mechanisms of bone metabolism in patients with diabetes, further longitudinal studies are required to explain BMD changes in different types of diabetes.

Deciphering the complex relationship between type 2 diabetes and fracture risk with both genetic and observational evidence

The 'diabetic bone paradox' suggested that type 2 diabetes (T2D) patients would have higher areal bone mineral density (BMD) but higher fracture risk than individuals without T2D. In this study, we found that the genetically predicted T2D was associated with higher BMD and lower risk of fracture in both weighted genetic risk score (wGRS) and two-sample Mendelian randomization (MR) analyses. We also identified ten genomic loci shared between T2D and fracture, with the top signal at SNP rs4580892 in the intron of gene RSPO3. And the higher expression in adipose subcutaneous and higher protein level in plasma of RSPO3 were associated with increased risk of T2D, but decreased risk of fracture. In the prospective study, T2D was observed to be associated with higher risk of fracture, but BMI mediated 30.2% of the protective effect. However, when stratified by the T2D-related risk factors for fracture, we observed that the effect of T2D on the risk of fracture decreased when the number of T2D-related risk factors decreased, and the association became non-significant if the T2D patients carried none of the risk factors. In conclusion, the genetically determined T2D might not be associated with higher risk of fracture. And the shared genetic architecture between T2D and fracture suggested a top signal around RSPO3 gene. The observed effect size of T2D on fracture risk decreased if the T2D-related risk factors could be eliminated. Therefore, it is important to manage the complications of T2D to prevent the risk of fracture.

Lobeglitazone and Its Therapeutic Benefits: A Review

Lobeglitazone is a newer oral hypoglycemic agent that has been tested in type 2 diabetes mellitus (T2DM). We aim to conduct a narrative review to find out the therapeutic benefits of lobeglitazone in patients with T2DM. We scientifically searched the electronic database of PubMed from inception until September 12, 2023, using Medical Subject Heading (MeSH) keywords. Additionally, we searched for pre-clinical trials related to lobeglitazone. We retrieved all available results of phase 1 to phase 3 studies of lobeglitazone in T2DM. Subsequently, we reviewed the results narratively. Three double-blind, randomized, placebo-controlled studies and a phase 3 trial of lobeglitazone showed that 0.5 mg daily dose exhibits effective therapeutic activity in glycemic, lipid, and hepatic control, and is also used as a secondary treatment in non-alcoholic fatty liver disease. Lobeglitazone exhibits as much antidiabetic activity as other thiazolidinediones such as pioglitazone and rosiglitazone. Side effects of lobeglitazone included peripheral edema, weight gain, and bone mineral density, which did not require hospitalization for these effects. This article highlights the pharmacological, pre-clinical, clinical, and safety pharmacology of novel thiazolidinedione lobeglitazone.

Causal relationship between breakfast skipping and bone mineral density: a two-sample Mendelian randomized study

Objective

To explore the causal association between breakfast skipping and bone mineral density (BMD) through two-sample Mendelian randomisation (MR) analysis.

Methods

A two-sample MR approach was adopted to explore the causal relationship of breakfast skipping with BMDs (across three skeletal sites and five age groups). Publicly available genome-wide association study summary data were used for MR analysis. We used five methods to estimate the causal associations between breakfast skipping and BMDs: inverse-variance weighting (IVW), MR-Egger, weighted median, simple mode, and weighted mode. IVW was used for the main analysis and the remaining four methods were used as supplementary analyses. The heterogeneity of the MR results was determined using IVW and MR-Egger methods. The pleiotropy of the MR results was determined using MR-Egger intercept. Furthermore, a leave-one-out test was performed to determine whether the MR results were affected by a single nucleotide polymorphism.

Results

With the IVW method, we did not find any causal relationship between breakfast skipping and forearm, femoral neck, and lumbar spine BMD. Subsequently, when we included BMD data stratified by five different age groups in the analysis, the results showed that there was no apparent causal effect between breakfast skipping and age-stratified BMD. This finding was supported by all four supplementary methods (P > 0.05 for all methods). No heterogeneity or horizontal pleiotropy was detected in any of the analyses (P > 0.05). The leave-one-out tests conducted in the analyses did not identify any single nucleotide polymorphism that could have influenced the MR results, indicating the reliability of our findings.

Conclusion

No causal effect was found between breakfast skipping and BMD (across three skeletal sites and five age groups).

Causal relationship between type 2 diabetes mellitus and bone mineral density: a Mendelian randomization study in an East Asian population

It remains unclear whether the relationship between type 2 diabetes mellitus (T2DM) and bone mineral density (BMD) reflects causality in East Asian populations. Herein, a Mendelian randomization study conducted in East Asian population enhances the current clinical cognition that T2DM is not associated with reduction in BMD.

PURPOSE

A Mendelian randomization (MR) approach was utilized to investigate the relationship between type 2 diabetes mellitus (T2DM) and bone mineral density (BMD) in East Asian populations.

METHODS

Genome-wide association study summary data from BioBank Japan were used to identify genetic variants strongly related to T2DM risk (36,614 cases and 155,150 controls) and osteoporosis (7788 cases and 204,665 controls). Heel BMD GWAS data of 1260 East Asian people from ieu open gwas project was considered as a second outcome. Inverse variance-weighted (IVW) analysis was mainly applied; MR-Egger and the weighted median were also used to obtain robust estimates. A series of sensitivity analyses including Cochran's Q test, MR-Egger regression, and leave-one-out analysis were used to detect pleiotropy or heterogeneity.

RESULTS

In the main analysis, IVW estimates indicated that T2DM significantly associated with the risk of osteoporosis (odds ratio = 0.92, 95% CI: 0.86-0.99, p = 0.016) and with higher BMD (OR: 1.25, 95% CI: 1.06-1.46, p = 6.49 × 10-3). Results of comprehensive sensitivity analysis were consistent with the main causality estimate. Horizontal pleiotropy and heterogeneity were absent in our MR study.

CONCLUSIONS

T2DM is not associated with reduction in BMD in terms of genetic polymorphism in East Asian populations.

Causal relationship between Type 1 diabetes and osteoporosis and fracture occurrence: a two-sample Mendelian randomization analysis

We used two-sample Mendelian Randomization to reveal causal estimates of type 1 diabetes and bone. Type 1 diabetes was found to be a risk factor for bone metabolic health, although there was no clear evidence to support a genetic association between type 1 diabetes and osteoporosis and fracture risk.

INTRODUCTION

Based on the random assignment of gametes at conception, Mendelian randomization (MR) analysis simulates randomized controlled trials in an observational setting. Therefore, we used MR to assess the association causality of type 1 diabetes (T1D) with fractures and osteoporosis.

METHODS

From a genome-wide association meta-analysis, independent single nucleotide polymorphisms closely associated with T1D were selected as instrumental variables. Data on fracture and osteoporosis were obtained from the FinnGen Consortium. We performed a two-sample MR analysis, using inverse-variance weighted (IVW) as the primary analysis method, to assess possible causal associations between T1D and bone risk. The results were verified by MR-Egger regression and median weighted method (WME). MR-PRESSO and MR-Egger intercepts were used to evaluate the horizontal pleiotropy of instrumental variables, and the Q-test and "leave-one-out" methods were used to test the heterogeneity of MR results.

RESULTS

IVW (OR=1.040, 95% CI=0.974-1.109, P=0.238), MR-Egger regression (OR=1.077, 95% CI=0.921-1.260, P=0.372) and WME (OR=1.021, 95% CI=0.935-1.114, P=0.643) all showed that there was no causal relationship between T1D and osteoporosis, but the direction was consistent. The indicative significance of IVW results in T1D and forearm fractures (OR=1.062, 95% CI=1.010-1.117, P=0.020), but the results are not robust enough. There was no causal effect in femur, lumbar and pelvis, or shoulder and upper arm fractures.

CONCLUSIONS

After MR analysis, although T1D may be a risk factor for bone health, we do not have sufficient evidence to support a causal effect of T1D on osteoporosis and fractures at a genetically predicted level. More cases need to be included for analysis.

A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach

In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.

Metabolically favorable adiposity and bone mineral density: a Mendelian randomization analysis

OBJECTIVE

This analysis assessed the putative causal association between genetically predicted percent body fat and areal bone mineral density (aBMD) and, more specifically, the association between genetically predicted metabolically "favorable adiposity" (MFA) and aBMD at clinically relevant bone sites.

METHODS

Mendelian randomization was used to assess the relationship of MFA and percent body fat with whole-body, lumbar spine, femoral neck, and forearm aBMD. Sex-stratified and age-stratified exploratory analyses were conducted.

RESULTS

In all MR analyses, genetically predicted MFA was inversely associated with aBMD for the whole body (β = -0.053, p = 0.0002), lumbar spine (β = -0.075; p = 0.0001), femoral neck (β = -0.045; p = 0.008), and forearm (β = -0.115; p = 0.001). This negative relationship was strongest in older individuals and did not differ by sex. The relationship between genetically predicted percent body fat and aBMD was nonsignificant across all Mendelian randomization analyses. Several loci that were associated at a genome-wide significance level (p < 5 × 10^-8 ) in opposite directions with body fat and aBMD measures were also identified.

CONCLUSIONS

This study did not support the hypothesis that MFA protects against low aBMD. Instead, it showed that MFA may result in lower aBMD. Further research is needed to understand how MFA affects aBMD and other components of bone health such as bone turnover, bone architecture, and osteoporotic fractures.

Association between trajectories of fasting plasma glucose and risk of osteoporosis in non-diabetic and diabetic populations

Introduction

Previous studies based on a single measure of fasting plasma glucose (FPG) showed an inconsistent conclusion about the association between FPG and osteoporosis risk. Not accounting for time-varying and cumulative average of FPG over time could bias the true relation between FPG and osteoporosis. Our study aims to investigate the association between the trajectories of FPG and osteoporosis risk for non-diabetic and diabetic populations.

Methods

A total of 18,313 participants who attended physical examinations during 2008-2018 were included. They were free of osteoporosis at their first physical examination and followed until their last physical examination before December 31, 2018. We recorded their incidence of osteoporosis and at least three FPG values during follow-up. Their longitudinal FPG trajectories were identified by the latent class growth analysis model based on the changes in FPG. Multivariable logistic regression models were used to analyze the association between the trajectories of FPG and osteoporosis diagnosed in the follow-up physical examination in both non-diabetics and diabetics.

Results

There were 752 incident osteoporosis among 16,966 non-diabetic participants, and 57 incident osteoporosis among 1,347 diabetic participants. Among non-diabetics, the elevated-increasing FPG trajectory was negatively associated with osteoporosis risk in women (odds ratio (OR), 0.62; 95% confidence interval (CI), 0.43-0.88). Premenopausal women with elevated-increasing FPG trajectory had lower osteoporosis risk than those women with normal-stable FPG trajectory (OR, 0.41; 95% CI, 0.20-0.88), while this association was insignificant in postmenopausal women. Among diabetics, those whose longitudinal FPG is kept at a very high level had the highest risk of osteoporosis (OR, 3.09; 95% CI, 1.16-8.22), whereas those whose FPG starts with the high level and keeps on increasing did not exhibit a significantly increased risk (OR, 1.75; 95% CI, 0.81-3.76) compared with those who keep stable moderate-high level of FPG, except in men (OR, 2.49; 95% CI, 1.02-6.12).

Conclusion

Distinct trajectories of FPG are associated with differential risk of osteoporosis in non-diabetic and diabetic populations. Controlling a proper FPG level in different populations is necessary for osteoporosis prevention.

Positive association of fasting plasma glucose with bone mineral density in non-diabetic elderly females

INTRODUCTION

Previous studies involving diabetics have shown different associations between fasting plasma glucose (FPG) and bone mineral density (BMD). The different effects of FPG on BMD are due to varying effects of antidiabetic drugs, glycemic control and diabetic complications in the diabetic patients. It is necessary to identify the association in subjects without diabetes.

MATERIALS AND METHODS

A total of 2367 females over 65 were included in this cross-sectional study. Subjects were grouped by FPG quartile. BMD and the prevalence of osteoporosis were compared among different FPG quartiles. Multiple logistic regression was used to analyze the independent contribution of FPG to osteoporosis.

RESULTS

Subjects in lower FPG quartile had lower BMD (P < 0.05). Subjects with osteoporosis had a lower FPG than the subjects of osteopenia, and both were lower than subjects with normal bone mass (P < 0.001 for all). Compared with the lowest FPG quartile, subjects in the 3rd and the 4th quartiles have a lower risk of osteoporosis in the lumbar spine (OR 0.77, 95% CI 0.59-0.98; OR 0.76, 95% CI 0.56-0.99, respectively), the total hip (OR 0.72, 95% CI 0.56-0.96; OR 0.75, 95% CI 0.53-0.99, respectively), and the femoral neck (OR 0.73, 95% CI 0.50-0.97; OR 0.71, 95% CI 0.54-0.92, respectively) after adjustment for age, BMI, education, physical activity and menopausal age.

CONCLUSION

FPG was positively associated with BMD in non-diabetic elderly females. Low FPG may increase the risk of osteoporosis in the non-diabetic elderly females in China.

Interpreting Mendelian-randomization estimates of the effects of categorical exposures such as disease status and educational attainment

BACKGROUND

Mendelian randomization has been previously used to estimate the effects of binary and ordinal categorical exposures-e.g. Type 2 diabetes or educational attainment defined by qualification-on outcomes. Binary and categorical phenotypes can be modelled in terms of liability-an underlying latent continuous variable with liability thresholds separating individuals into categories. Genetic variants influence an individual's categorical exposure via their effects on liability, thus Mendelian-randomization analyses with categorical exposures will capture effects of liability that act independently of exposure category.

METHODS AND RESULTS

We discuss how groups in which the categorical exposure is invariant can be used to detect liability effects acting independently of exposure category. For example, associations between an adult educational-attainment polygenic score (PGS) and body mass index measured before the minimum school leaving age (e.g. age 10 years), cannot indicate the effects of years in full-time education on this outcome. Using UK Biobank data, we show that a higher educational-attainment PGS is strongly associated with lower smoking initiation and higher odds of glasses use at age 15 years. These associations were replicated in sibling models. An orthogonal approach using the raising of the school leaving age (ROSLA) policy change found that individuals who chose to remain in education to age 16 years before the reform likely had higher liability to educational attainment than those who were compelled to remain in education to age 16 years after the reform, and had higher income, lower pack-years of smoking, higher odds of glasses use and lower deprivation in adulthood. These results suggest that liability to educational attainment is associated with health and social outcomes independently of years in full-time education.

CONCLUSIONS

Mendelian-randomization studies with non-continuous exposures should be interpreted in terms of liability, which may affect the outcome via changes in exposure category and/or independently.

Greater Carboxy-Methyl-Lysine Is Associated With Increased Fracture Risk in Type 2 Diabetes

Accumulation of advanced glycation end-products (AGE) in bone alters collagen structure and function. Fluorescent AGEs are associated with fractures but less is known regarding non-fluorescent AGEs. We examined associations of carboxy-methyl-lysine (CML), with incident clinical and prevalent vertebral fractures by type 2 diabetes (T2D) status, in the Health, Aging, and Body Composition cohort of older adults. Incident clinical fractures and baseline vertebral fractures were assessed. Cox regression was used to analyze the associations between serum CML and clinical fracture incidence, and logistic regression for vertebral fracture prevalence. At baseline, mean ± standard deviation (SD) age was 73.7 ± 2.8 and 73.6 ± 2.9 years in T2D (n = 712) and non-diabetes (n = 2332), respectively. Baseline CML levels were higher in T2D than non-diabetes (893 ± 332 versus 771 ± 270 ng/mL, p < 0.0001). In multivariate models, greater CML was associated with higher risk of incident clinical fracture in T2D (hazard ratio [HR] 1.49; 95% confidence interval [CI], 1.24-1.79 per 1-SD increase in log CML) but not in non-diabetes (HR 1.03; 95% CI, 0.94-1.13; p for interaction = 0.001). This association was independent of bone mineral density (BMD), glycated hemoglobin (hemoglobin A1c), weight, weight loss, smoking, cystatin-C, and medication use. CML was not significantly associated with the odds of prevalent vertebral fractures in either group. In conclusion, higher CML levels are associated with increased risk of incident clinical fractures in T2D, independent of BMD. These results implicate CML in the pathogenesis of bone fragility in diabetes. © 2021 American Society for Bone and Mineral Research (ASBMR).

Association Analysis of Insulin Resistance and Osteoporosis Risk in Chinese Patients with T2DM

Background

To explore the relationship between insulin resistance and osteoporosis risk in Chinese patients with type 2 diabetes mellitus (T2DM).

Methods

A total of 234 T2DM patients were retrospectively analyzed, and their lumbar bone mineral density (BMD) and insulin resistance using C-peptide-based homeostasis model of insulin resistance [HOMA-IR (CP)] were assessed. Univariate and multivariable logistic regression methods were used to evaluate the association between HOMA-IR (CP) and osteoporosis, and subgroup analysis was performed on female and male patients.

Results

After fully adjusting the covariates, the association between HOMA-IR (CP) and osteoporosis was only significant in female patients (P = 0.022); the interaction effect with gender was significant (P for interaction <0.05). Curve fitting showed that the relationship between HOMA-IR (CP) and osteoporosis in women was nonlinear. When HOMA-IR (CP) is <4.00, its effect on osteoporosis was not significant (P = 0.474); when HOMA-IR (CP) is >4.00, the risk of osteoporosis increased significantly, with OR = 26.88 (95% CI: 2.75-262.69, P = 0.005). The relationship between insulin resistance and osteoporosis risk in T2DM patients is significantly affected by gender.

Conclusion

The higher the degree of insulin resistance in female patients, the greater the risk of osteoporosis, but the two are not linearly associated.

Type 2 Diabetes Is Causally Associated With Reduced Serum Osteocalcin: A Genomewide Association and Mendelian Randomization Study

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).

Causal Associations of Anthropometric Measurements With Fracture Risk and Bone Mineral Density: A Mendelian Randomization Study

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).

Genetic Predisposition to Type 2 Diabetes and Insulin Levels Is Positively Associated With Serum Urate Levels

PURPOSE

Previous epidemiological evidence showed that type 2 diabetes (T2D) is related with gout. However, the causality and the direction of this association are still not definitely elucidated. We investigated bidirectional associations of T2D and glycemic traits with serum urate concentrations and gout using a Mendelian randomization approach.

METHODS

Summary statistics from the large-scale genomewide association studies conducted for T2D (Ncase = 62 892, Ncontrol = 596 424), fasting glucose (N = 133 010), fasting insulin (N = 133 010), hemoglobin A1c (N = 123 665), homeostasis model assessment of insulin resistance (N = 46 186), urate (N = 110 347), and gout (Ncase = 2115, Ncontrol = 67 259) among participants of European ancestry were analyzed. For each trait of interest, independent genomewide significant (P < 5 × 10-8) single nucleotide polymorphisms were selected as instrumental variables. The inverse-variance weighted method was used for the primary analyses.

RESULTS

Genetic predisposition to higher risk of T2D [beta = 0.042; 95% confidence interval (CI) = 0.016-0.068; P = 0.002] and higher levels of fasting insulin (beta = 0.756; 95% CI = 0.408-1.102; P = 1.96e-05) were significantly associated with increased serum urate concentrations. Moreover, we found suggestively significant evidence supporting a causal role of fasting insulin on risk of developing gout (odds ratio = 3.06; 95% CI = 0.88-10.61; P = 0.078). In the reverse direction analysis, genetic predisposition to both urate and gout were not associated with T2D or any of 4 glycemic traits being investigated.

CONCLUSIONS

This study provides supportive evidence on causal associations of T2D and fasting insulin with serum urate concentrations and a suggestive association of fasting insulin with risk of gout. Future research is required to examine the underlying biological mechanisms on such relationships.

Fasting glucose, bone area and bone mineral density: a Mendelian randomisation study

AIMS/HYPOTHESIS

Observational studies indicate that type 2 diabetes mellitus and fasting glucose levels are associated with a greater risk for hip fracture, smaller bone area and higher bone mineral density (BMD). However, these findings may be biased by residual confounding and reverse causation. Mendelian randomisation (MR) utilises genetic variants as instruments for exposures in an attempt to address these biases. Thus, we implemented MR to determine whether fasting glucose levels in individuals without diabetes are causally associated with bone area and BMD at the total hip.

METHODS

We selected 35 SNPs strongly associated with fasting glucose (p < 5 × 10-8) in a non-diabetic European-descent population from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) (n = 133,010). MR was used to assess the associations of genetically predicted fasting glucose concentrations with total hip bone area and BMD in 4966 men and women without diabetes from the Swedish Mammography Cohort, Prospective Investigation of Vasculature in Uppsala Seniors and Uppsala Longitudinal Study of Adult Men.

RESULTS

In a meta-analysis of the three cohorts, a genetically predicted 1 mmol/l increment of fasting glucose was associated with a 2% smaller total hip bone area (-0.67 cm2 [95% CI -1.30, -0.03; p = 0.039]), yet was also associated, albeit without reaching statistical significance, with a 4% higher total hip BMD (0.040 g/cm2 [95% CI -0.00, 0.07; p = 0.060]).

CONCLUSIONS/INTERPRETATION

Fasting glucose may be a causal risk factor for smaller bone area at the hip, yet possibly for greater BMD. Further MR studies with larger sample sizes are required to corroborate these findings.

Increasing fasting glucose and fasting insulin associated with elevated bone mineral density-evidence from cross-sectional and MR studies

We performed a cross-sectional study using the National Health Examination and Nutrition Survey (NHANES) data and a Mendelian randomisation (MR) study using the GWAS summary statistics from European populations. The T2D-related indices (fasting plasma glucose (FPG), fasting insulin (FI), and insulin resistance (IR)) were found to associate with elevated bone mineral density (BMD).

INTRODUCTION

The known associations amongst FPG, FI, IR, and BMD remain inconsistent. This study aims to explore the abovementioned associations by using cross-sectional and MR designs.

METHODS

Data from adults aged ≥ 20 years (n = 7170) in four rounds of the U.S. NHANES (2005-2010 and 2013-2014) were analysed in this cross-sectional study. Multiple linear and logistic regression models were used for statistical analyses. A two-sample MR study was performed using the genome-wide association study summary statistics obtained from the Meta-analyses of Glucose and Insulin-related traits Consortium (n = 108,557) and Genetic Factors for Osteoporosis Consortium (n = 32,735) to examine the causality of the FI-BMD association.

RESULTS

Multiple linear regression revealed that FPG was positively associated with the BMDs at the hip, femur neck, and 1st lumbar spine (L1). Multiple logistic regressions revealed that FPG levels were associated with elevated BMDs at the hip and L1, and FI and IR levels were associated with elevated BMD at the hip. Patients with type 2 diabetes had higher hip BMD than those without diabetes. In the MR study, the lumbar spine BMD increased by 0.49 g/cm² (95% confidence interval: 0.01, 0.97) in response to per unit increase in log-transformed FI.

CONCLUSION

Findings from our cross-sectional and MR studies revealed the associations between the studied diabetic indices and BMD measurements in the US and European adults.

Relationship between Serum Nutritional Factors and Bone Mineral Density: A Mendelian Randomization Study

PURPOSE

Multiple risk factors have been implicated in the development of osteoporosis. This study examined potential associations between serum nutritional factors and bone mineral density (BMD).

METHODS

Six nutritional factors were selected as exposures. Outcomes included total body BMD (n = 66 945); BMD at the forearm (FA), femoral neck (FN) and lumbar spine (LS) (n = 8143, n = 32 735, and n = 28 498, respectively); estimated heel BMD (HL eBMD) (n = 394 929); and HL eBMD stratified by sex (n = 206 496). A 2-sample Mendelian randomization approach was adopted to estimate the association between serum nutritional factors and BMD. The threshold for adjusted P value was 1.39 × 10-3.

RESULTS

Serum calcium levels were inversely associated with LS BMD (effect = -0.55; 95% CI, -0.86 to -0.24; P = 0.001), whereas serum selenium levels were positively correlated with HL eBMD (effect = 0.22; 95% CI, 0.10 to 0.33; P = 1.70 × 10-4). Regarding nominal significance, there was a positive association between serum selenium levels and FA BMD. Nominally significant results were also obtained for serum retinol as well as vitamin E levels and HL eBMD. Moreover, sex-specific effects of serum retinol and vitamin E levels on BMD were observed in men.

CONCLUSION

Serum calcium and selenium levels influence BMD at specific skeletal sites. This implies that these nutritional factors play crucial roles in bone metabolism.

Twelve years of GWAS discoveries for osteoporosis and related traits: advances, challenges and applications

Osteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction. Despite the fruitful GWAS discoveries in the bone field, most of these GWAS participants were of European descent, and more genetic studies should be carried out in other ethnic populations to benefit disease prediction in the corresponding population.

Detecting causal relationship between metabolic traits and osteoporosis using multivariable Mendelian randomization

By adopting the extension approaches of Mendelian randomization, we successfully detected and prioritized the potential causal risk factors for BMD traits, which might provide us novel insights for treatment and intervention into bone-related complex traits and diseases.

INTRODUCTION

Osteoporosis (OP) is a common metabolic skeletal disease characterized by reduced bone mineral density (BMD). The identified SNPs for BMD can only explain approximately 10% of the variability, and very few causal factors have been identified so far.

METHODS

The Mendelian randomization (MR) approach enables us to assess the potential causal effect of a risk factor on the outcome by using genetic IVs. By using extension methods of MR-multivariable MR (mvMR) and MR based on Bayesian model averaging (MR-BMA)-we intend to estimate the causal relationship between fifteen metabolic risk factors for BMD and try to prioritize the most potential causal risk factors for BMD.

RESULTS

Our analysis identified three risk factors T2D, FG, and HCadjBMI for FN BMD; four risk factors FI, T2D, HCadjBMI, and WCadjBMI for FA BMD; and three risk factors FI, T2D, and HDL cholesterol for LS BMD, and all risk factors were causally associated with heel BMD except for triglycerides and WCadjBMI. Consistent with the mvMR results, MR-BMA confirmed those risk factors as top risk factors for each BMD trait individually.

CONCLUSIONS

By combining MR approaches, we identified the potential causal risk factors for FN, FA, LS, and heel BMD individually and we also prioritized and ranked the potential causal risk factors for BMD, which might provide us novel insights for treatment and intervention into bone-related complex traits and diseases.

Genetically Predicted Sex Hormone-Binding Globulin and Bone Mineral Density: A Mendelian Randomization Study

Previous observational studies have identified various risk factors associated with the development of osteoporosis, including sex hormone-binding globulin (SHBG). The aim of this study was to determine the potential causal effects of circulating SHBG concentrations on bone mineral density (BMD). Two-sample Mendelian randomization (MR) approach was applied in analyses. From summary-level data of genome-wide association studies (GWAS), we selected 11 single-nucleotide polymorphisms (SNPs) associated with SHBG levels as instrumental variable, and used summary statistics for BMD at forearm (FA) (n = 8143), femoral neck (FN) (n = 32,735), lumbar spine (LS) (n = 28,498) and heel (HL) (n = 394,929), and total-body BMD of different age-stages (15 or less, 15-30, 30-45, 45-60, 60 or more years old) (n = 67,358). Inverse causal associations was observed between SHBG levels and FA BMD (Effect = - 0.26; 95% CI - 0.49 to - 0.04; P = 0.022), HL eBMD (Effect = - 0.09; 95% CI - 0.12 to - 0.06; P = 3.19 × 10^-9), and total-body BMD in people aged 45-60 years (Effect = - 0.16; 95% CI - 0.31 to - 2.4 × 10^-3; P = 0.047) and over 60 years (Effect = - 0.19; 95% CI - 0.33 to - 0.05; P = 0.006). Our study demonstrates that circulating SHBG concentrations are inversely associated with FA and HL eBMD, and total-body BMD in people aged over 45 years, suggesting that the role of SHBG in the development of osteoporosis might be affected by chronological age of patients and skeletal sites.

Parathyroid Hormone and Bone Mineral Density: A Mendelian Randomization Study

PURPOSE

Accumulating evidence implicates parathyroid hormone (PTH) in the development of osteoporosis. However, the causal effect of PTH on bone mineral density (BMD) remains unclear. Thus, this study is aimed at exploring the association between the concentrations of serum PTH and BMD.

METHODS

The instrumental variables for PTH were selected from a large-scale genome-wide association study (GWAS; n = 29 155). Outcomes included BMD of the forearm (FA; n = 8143), femoral neck (FN; n = 33 297), lumbar spine (LS; n = 32 735), heel (HL; n = 394 929), and risk of fractures in these bones (n = 361 194). Furthermore, the BMD of 5 different age groups: 15 years or younger (n = 11 807), 15-30 (n = 4180), 30-45 (n = 10 062), 45-60 (n = 18 805), and 60 years or older (n = 22 504) were extracted from a GWAS meta-analysis study. The analyses were performed using the 2-sample Mendelian randomization method.

RESULTS

Mendelian randomization analysis revealed that the level of serum PTH was inversely associated with BMD of FA (95% CI: -0.763 to -0.016), FN (95% CI: -0.669 to -0.304), and LS (95% CI: -0.667 to -0.243). A causal relationship between serum PTH levels and BMD was observed in individuals aged 30-45 (95% CI: -0.888 to -0.166), 45-60 (95% CI: -0.758 to -0.232), and over 60 years (95% CI: -0.649 to -0.163).

MAIN CONCLUSIONS

This study demonstrated that the concentrations of serum PTH is inversely associated with BMD of several bones. Further analysis revealed site- and age-specific correlations between serum PTH levels and BMD, which implies that the levels of serum PTH contribute to the development of osteoporosis.

Genetic Pleiotropy of Bone-Related Phenotypes: Insights from Osteoporosis

PURPOSE OF REVIEW

We summarize recent evidence on the shared genetics within and outside the musculoskeletal system (mostly related to bone density and osteoporosis).

RECENT FINDINGS

Osteoporosis is determined by an interplay between multiple genetic and environmental factors. Significant progress has been made regarding its genetic background revealing a number of robustly validated loci and respective pathways. However, pleiotropic factors affecting bone and other tissues are not well understood. The analytical methods proposed to test for potential associations between genetic variants and multiple phenotypes can be applied to bone-related data. A number of recent genetic studies have shown evidence of pleiotropy between bone density and other different phenotypes (traits, conditions, or diseases), within and outside the musculoskeletal system. Power benefits of combining correlated phenotypes, as well as unbiased discovery, make these studies promising. Studies in humans are supported by evidence from animal models. Drug development and repurposing should benefit from the pleiotropic approach. We believe that future studies should take into account shared genetics between the bone and related traits.

Mendelian Randomization Study: The Association Between Metabolic Pathways and Colorectal Cancer Risk

Background: The roles of obesity-related biomarkers and their molecular pathways in the development of postmenopausal colorectal cancer (CRC) have been inconclusive. We examined insulin resistance (IR) as a major hormonal pathway mediating the association between obesity and CRC risk in a Mendelian randomization (MR) framework.

Methods: We performed MR analysis using individual-level data of 11,078 non-Hispanic white postmenopausal women from our earlier genome-wide association study. We identified four independent single-nucleotide polymorphisms associated with fasting glucose (FG), three with fasting insulin (FI), and six with homeostatic model assessment–IR (HOMA-IR), which were not associated with obesity. We estimated hazard ratios (HRs) for CRC by adjusting for potential confounding factors plus genetic principal components.

Results: Overall, we observed no direct association between combined 13 IR genetic instruments and CRC risk (HR = 0.96, 95% confidence interval [CI]: 0.78–1.17). In phenotypic analysis, genetically raised HOMA-IR exhibited its effects on the increased risk and FG and FI on the reduced risk for CRC, but with a lack of statistical power. Subgroup analyses by physical activity level and dietary fat intake with combined phenotypes showed that genetically determined IR was associated with reduced CRC risk in both physical activity-stratified (single contributor: MTRR rs722025; HR = 0.12, 95% CI: 0.02–0.62) and high-fat diet subgroups (main contributor: G6PC2 rs560887; HR = 0.59, 95% CI: 0.37–0.94).

Conclusions: Complex evidence was observed for a potential causal association between IR and CRC risk. Our findings may provide an additional value of intervention trials to lower IR and reduce CRC risk.

Use of Mendelian Randomization to Examine Causal Inference in Osteoporosis

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.

Mendelian randomization in the bone field

Identification of causative risk factors amenable for modification is essential for the prevention and treatment of osteoporosis. Observational studies have identified associations between several potentially modifiable risk factors and osteoporosis. However, observational studies are susceptible to confounding, reverse causation bias, and measurement error, all of which limit their ability to provide causal estimates of the effect of exposures on outcomes, thereby reducing their ability to inform prevention and treatment strategies against bone loss and fractures. In addition, not all risk factors are suitable for an analysis in a randomized clinical trial. Mendelian randomization is a genetic epidemiological method that exploits genetic variants as unbiased proxies for modifiable exposures (e.g., biomarkers, adiposity measures, dietary factors, and behaviors) to determine the causal relationships between exposures and health outcomes. This technique has been used to provide evidence of causal associations of serum estradiol concentrations, smoking, body mass index, and type 2 diabetes with bone mineral density and the lack of associations of serum thyroid stimulating hormone, urate, C-reactive protein, and 25‑hydroxyvitamin D concentrations with bone mineral density in generally healthy populations. This review will briefly explain the concept of Mendelian randomization, the advantages and potential limitations of this study design, and give examples of how Mendelian randomization has been used to investigate questions relevant to osteoporosis.

Effect of Insulin Resistance on BMD and Fracture Risk in Older Adults

CONTEXT

Adults with type 2 diabetes (T2D) have higher fracture risk compared with nondiabetics, despite having higher bone mineral density (BMD). Insulin resistance (IR) has been associated with increased BMD. It is not known if IR increases fracture risk.

OBJECTIVE

We investigated the relationship among IR HOMA-IR, BMD, and incident nonspine fractures in nondiabetic individuals.

DESIGN

Participants included 2398 community-dwelling, nondiabetic older adults (age 74 ± 3 years, 53% women, 38% black) in the Health, Aging and Body Composition Prospective Cohort Study [median follow-up: 12 (interquartile range: 6) years].

RESULTS

The cut-off values for the HOMA-IR quartiles were 1.05, 1.54, and 2.33. Total hip BMD was 0.104 g/cm2 higher in the fourth vs the first HOMA-IR quartile (P < 0.001). This difference was attenuated after adjustment for BMI (adjusted mean difference 0.007 g/cm2; P = 0.371). In unadjusted models, fracture risk was lower in those with higher HOMA-IR [hazard ratio (HR) 0.86 (95% CI 0.73 to 1.01) and 0.65 (95% CI 0.47 to 0.89) for the third and fourth quartile, respectively, vs the first quartile]. However, after adjustment for BMD and BMI, fracture risk was significantly higher in the third quartile (HR 1.19, 95% CI 1.00 to 1.41) and tended to be increased in the fourth quartile (HR 1.12, 95% CI 0.87 to 1.46) vs the first quartile.

CONCLUSIONS

Greater IR is associated with higher BMD in nondiabetic older adults. In contrast to the relationship between T2D and fracture risk, we did not find consistent evidence that greater IR is associated with increased fracture risk after adjustment for BMI and BMD.

Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization

PURPOSE

The role of insulin resistance (IR) in developing postmenopausal breast cancer has not been thoroughly resolved and may be confounded by lifestyle factors such as obesity. We examined whether genetically determined IR is causally associated with breast cancer risk.

METHODS

We conducted Mendelian randomization (MR) analyses using individual-level data from our previous meta-analysis of a genome-wide association study (GWAS) (n = 11,109 non-Hispanic white postmenopausal women). Four single-nucleotide polymorphisms were associated with fasting glucose (FG), 2 with fasting insulin (FI), and 6 with homeostatic model assessment-IR (HOMA-IR) but were not associated with obesity. We used this GWAS to employ hazard ratios (HRs) for breast cancer risk by adjusting for potential confounding factors.

RESULTS

No direct association was observed between comprising 12 IR genetic instruments and breast cancer risk (HR = 0.93, 95% CI: 0.76-1.14). In phenotype-specific analysis, genetically elevated FG was associated with reduced risk for breast cancer (main contributor of this MR-effect estimate: G6PC2 rs13431652; HR = 0.59, 95% CI: 0.35-0.99). Genetically driven FI and HOMA-IR were not significantly associated. Stratification analyses by body mass index, exercise, and dietary fat intake with combined phenotypes showed that genetically elevated IR was associated with greater breast cancer risk in overall obesity and inactive subgroups (single contributor: MTRR/LOC729506 rs13188458; HR = 2.21, 95% CI: 1.03-4.75).

CONCLUSIONS

We found complex evidence for causal association between IR and risk of breast cancer, which may support the potential value of intervention trials to lower IR and reduce breast cancer risk.

Effect of Sodium-Glucose Co-transporter 2 Inhibitors on Bone Metabolism and Fracture Risk

The effect of anti-diabetic medications on bone metabolism has received increasing attention, considering that type 2 diabetes mellitus is a common metabolic disorder with adverse effects on bone metabolism. Sodium-glucose co-transporter 2 (SGLT2) inhibitors are novel anti-diabetic medications that prevent glucose resorption at the proximal convoluted tubules in the kidney, increasing urinary glucose excretion, and decreasing the blood glucose level. The superiority of SGLT2 inhibitors shows in reducing the glucose level independent of insulin secretion, lowering the risk of hypoglycemia, and improving cardiovascular outcomes. SGLT2 inhibitors have been associated with genital mycotic infections, increased risk of acute kidney injury, dehydration, orthostatic hypotension, and ketoacidosis. Moreover, the effect of SGLT2 inhibitors on bone metabolism and fracture risk has been widely taken into consideration. Our review summarizes the results of current studies investigating the effects of SGLT2 inhibitors on bone metabolism (possibly including increased bone turnover, disrupted bone microarchitecture, and reduced bone mineral density). Several mechanisms are probably involved, such as bone mineral losses due to the disturbed calcium and phosphate homeostasis, as confirmed by an increase in fibroblast growth factor 23 and parathyroid hormone levels and a decrease in 1,25-dihydroxyvitamin D levels. SGLT2 inhibitors might indirectly increase bone turnover by weight loss. Lowering the blood glucose level might ameliorate bone metabolism impairment in diabetes. The effect of SGLT2 inhibitors on bone fractures remains unclear. Evidence indicating the direct effect of SGLT2 inhibitors on fracture risk is lacking and increased falls probably contribute to fractures.

Is There Causal Relationship of Smoking and Alcohol Consumption with Bone Mineral Density? A Mendelian Randomization Study

Observational studies examining associations of smoking and alcohol consumption with bone mineral density (BMD) have generated inconsistent results and suffer from several methodological limitations. We aim to evaluate whether there are causal associations between smoking, alcohol consumption, and BMD using a Mendelian randomization (MR) design. Genetic variants associated with smoking status (n = 142), no. of cigarettes smoked per day (CPD) (n = 3), smoking initiation (n = 1), and alcohol consumption (n = 6) identified in published genome-wide association studies (GWAS) were used as instruments. Summary statistics data of 32735, 28498, 8143, and 445921 European subjects included in The GEnetic Factors for Osteoporosis Consortium or UK Biobank were used to generate associations of genetically predicted smoking or alcohol consumption with femoral neck (FN-BMD), lumbar spine (LS-BMD), forearm (FA-BMD), and heel BMD, respectively, by using the inverse-variance weighted method. The BMD was measured using either ultrasound (for heel) or Dual-energy X-ray Absorptiometry (for others). In our analyses, smoking status tended to be negatively associated with several types of BMD (heel BMD: β = - 0.053, p = 0.003; FN-BMD: β = - 0.139, p = 0.053; FA-BMD: β = - 0.264, p = 0.077), although the association with LS-BMD was null. Smoking initiation was significantly inversely associated with heel BMD (β = - 0.201, p = 3.60 × 10^-8). CPD was associated with a lower FN-BMD (β = - 0.014, p = 0.047) only. There was no clear association of genetically predicted alcohol consumption with BMD. Our study provided some evidence of a potential association between genetically predicted smoking and lower BMD, especially for heel BMD, but not for alcohol consumption. Considering the inconsistent findings with the different types of BMD and limitations of the current work, further studies are needed to better characterize the exact relationship between smoking, alcohol consumption, and BMD.

Using Mendelian Randomization to Decipher Mechanisms of Bone Disease

PURPOSE OF REVIEW

This review summarizes the basic principles of Mendelian randomization (MR) and provides evidence for the causal effect of multiple modifiable factors on bone outcomes.

RECENT FINDINGS

Several studies using MR approach have provided support for the causal effect of obesity on bone mineral density (BMD). Strikingly, studies have failed to prove a causal association between elevated 25(OH) D concentrations and higher BMD in community-dwelling individuals. The MR approach has been successfully used to evaluate multiple factors related to bone mineral density variation and/or fracture risk. The MR approach avoids some of the classical observational study limitations and provides more robust causal evidence, ensuring bigger success of the clinical trials. The selection of interventions based on genetic evidence could have a substantial impact on clinical practice.

Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study

OBJECTIVES

To identify the genetic determinants of fracture risk and assess the role of 15 clinical risk factors on osteoporotic fracture risk.

DESIGN

Meta-analysis of genome wide association studies (GWAS) and a two-sample mendelian randomisation approach.

SETTING

25 cohorts from Europe, United States, east Asia, and Australia with genome wide genotyping and fracture data.

PARTICIPANTS

A discovery set of 37 857 fracture cases and 227 116 controls; with replication in up to 147 200 fracture cases and 150 085 controls. Fracture cases were defined as individuals (>18 years old) who had fractures at any skeletal site confirmed by medical, radiological, or questionnaire reports. Instrumental variable analyses were performed to estimate effects of 15 selected clinical risk factors for fracture in a two-sample mendelian randomisation framework, using the largest previously published GWAS meta-analysis of each risk factor.

RESULTS

Of 15 fracture associated loci identified, all were also associated with bone mineral density and mapped to genes clustering in pathways known to be critical to bone biology (eg, SOST, WNT16, and ESR1) or novel pathways (FAM210A, GRB10, and ETS2). Mendelian randomisation analyses showed a clear effect of bone mineral density on fracture risk. One standard deviation decrease in genetically determined bone mineral density of the femoral neck was associated with a 55% increase in fracture risk (odds ratio 1.55 (95% confidence interval 1.48 to 1.63; P=1.5×10-68). Hand grip strength was inversely associated with fracture risk, but this result was not significant after multiple testing correction. The remaining clinical risk factors (including vitamin D levels) showed no evidence for an effect on fracture.

CONCLUSIONS

This large scale GWAS meta-analysis for fracture identified 15 genetic determinants of fracture, all of which also influenced bone mineral density. Among the clinical risk factors for fracture assessed, only bone mineral density showed a major causal effect on fracture. Genetic predisposition to lower levels of vitamin D and estimated calcium intake from dairy sources were not associated with fracture risk.

Genetically driven adiposity traits increase the risk of coronary artery disease independent of blood pressure, dyslipidaemia, glycaemic traits

Adiposity has been associated with the risk of coronary artery disease (CAD) in observational studies, but their association may differ according to specific characteristics of studies. In Mendelian randomization (MR) analyses, genetic variants are used as instrumental variables (IVs) of exposures to examine causal effects to overcome confounding factors and reverse causation. We performed MR analyses for adiposity (n = 322,154) on risk of CAD (60,801 cases and 123,504 controls) based on the currently largest genome-wide association studies. The estimated associations between adiposity traits and CAD were calculated by an inverse-variance weighted method with and without excluding the IVs, which are associated with the well-known risk factors of CAD. Genetic variants are identified to be associated with the well-known risk factors of CAD by a cross-phenotype meta-analysis method. Our results furnished strong evidence for a causal role of adiposity in risk of CAD, with the odds ratios (ORs) for CAD being 1.53 (95% CI 1.36-1.72) for body mass index (BMI), 1.48 (1.20-1.96) for waist-hip ratio (WHR), and 1.34 (1.07-1.59) for WHR adjusted for BMI (WHRadjBMI), respectively. After excluding mediators-associated IVs from the MR analyses, the corresponding ORs were 1.46 (1.28-1.67) for BMI, 1.39 (1.01-1.93) for WHR, and 1.38 (1.04-1.84) for WHRadjBMI, respectively. Furthermore, our results suggested that central adiposity and general adiposity might pose a similar risk for CAD. In summary, our data supported that genetically driven adiposity traits imposed the risk of CAD independent of blood pressure, dyslipidaemia, glycaemic traits, and type 2 diabetes.

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

PURPOSE OF REVIEW

The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction.

RECENT FINDINGS

In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.

Identification of 153 new loci associated with heel bone mineral density and functional involvement of GPC6 in osteoporosis

Osteoporosis is a common disease diagnosed primarily by measurement of bone mineral density (BMD). We undertook a genome-wide association study (GWAS) in 142,487 individuals from the UK Biobank to identify loci associated with BMD as estimated by quantitative ultrasound of the heel. We identified 307 conditionally independent single-nucleotide polymorphisms (SNPs) that attained genome-wide significance at 203 loci, explaining approximately 12% of the phenotypic variance. These included 153 previously unreported loci, and several rare variants with large effect sizes. To investigate the underlying mechanisms, we undertook (1) bioinformatic, functional genomic annotation and human osteoblast expression studies; (2) gene-function prediction; (3) skeletal phenotyping of 120 knockout mice with deletions of genes adjacent to lead independent SNPs; and (4) analysis of gene expression in mouse osteoblasts, osteocytes and osteoclasts. The results implicate GPC6 as a novel determinant of BMD, and also identify abnormal skeletal phenotypes in knockout mice associated with a further 100 prioritized genes.

Diabetes, bone and glucose-lowering agents: clinical outcomes

Older adults with diabetes are at higher risk of fracture and of complications resulting from a fracture. Hence, fracture risk reduction is an important goal in diabetes management. This review is one of a pair discussing the relationship between diabetes, bone and glucose-lowering agents; an accompanying review is provided in this issue of Diabetologia by Beata Lecka-Czernik (DOI 10.1007/s00125-017-4269-4 ). Specifically, this review discusses the challenges of accurate fracture risk assessment in diabetes. Standard tools for risk assessment can be used to predict fracture but clinicians need to be aware of the tendency for the bone mineral density T-score and the fracture risk assessment tool (FRAX) to underestimate risk in those with diabetes. Diabetes duration, complications and poor glycaemic control are useful clinical markers of increased fracture risk. Glucose-lowering agents may also affect fracture risk, independent of their effects on glycaemic control, as seen with the negative skeletal effects of the thiazolidinediones; in this review, the potential effects of glucose-lowering medications on fracture risk are discussed. Finally, the current understanding of effective fracture prevention in older adults with diabetes is reviewed.