0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Diabetes and osteoporosis: a two-sample mendelian randomization study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12891-024-07430-0.

          Related collections

          Most cited references64

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

          ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045

            Since the year 2000, IDF has been measuring the prevalence of diabetes nationally, regionally and globally.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040.

              To produce current estimates of the national, regional and global impact of diabetes for 2015 and 2040.
                Bookmark

                Author and article information

                Contributors
                gd2hqy@163.com
                gd2hxcp@163.com
                Journal
                BMC Musculoskelet Disord
                BMC Musculoskelet Disord
                BMC Musculoskeletal Disorders
                BioMed Central (London )
                1471-2474
                23 April 2024
                23 April 2024
                2024
                : 25
                : 317
                Affiliations
                [1 ]The Second School of Clinical Medicine, Guangdong Second Provincial General Hospital, Southern Medical University, ( https://ror.org/01vjw4z39) Guangzhou, Guangdong P.R. China
                [2 ]GRID grid.284723.8, ISNI 0000 0000 8877 7471, Clinical Research Centre, Zhujiang Hospital, , Southern Medical University, ; Guangzhou, Guangdong China
                [3 ]Department of Orthopaedics, Guangdong Second Provincial General Hospital, The Second School of Clinical Medicine, Southern Medical University, ( https://ror.org/01vjw4z39) Guangzhou, Guangdong P.R. China
                [4 ]GRID grid.413405.7, ISNI 0000 0004 1808 0686, Department of Orthopaedics, , Guangdong Second Provincial General Hospital, ; No. 466 Xingang Road, Haizhu District, Guangzhou, 510317 Guangdong People’s Republic of China
                Article
                7430
                10.1186/s12891-024-07430-0
                11036742
                38654244
                6306bad1-09d6-4dce-919b-5a64ecc8bba5
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 16 September 2023
                : 9 April 2024
                Funding
                Funded by: Science and Technology Planning Project of Guangzhou
                Award ID: 202201020303, 202102080052, 202102010057, 201804010226
                Award ID: 202201020303, 202102080052, 202102010057, 201804010226
                Funded by: Foundation of Guangdong Second Provincial General Hospital
                Award ID: 3D-A2020004, 3D-A2020002, YQ2019-009, C2020019
                Award ID: 3D-A2020004, 3D-A2020002, YQ2019-009, C2020019
                Funded by: National Natural Science Foundation of China
                Award ID: 81972083
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Orthopedics
                diabetes,bone mineral density,osteoporosis,fracture,mendelian randomization
                Orthopedics
                diabetes, bone mineral density, osteoporosis, fracture, mendelian randomization

                Comments

                Comment on this article