3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Pharmacogenomic Effects of β-Blocker Use on Femoral Neck Bone Mineral Density

      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

          Context

          Recent studies have shown that β-blocker (BB) users have a decreased risk of fracture and higher bone mineral density (BMD) compared to nonusers, likely due to the suppression of adrenergic signaling in osteoblasts, leading to increased BMD. There is also variability in the effect size of BB use on BMD in humans, which may be due to pharmacogenomic effects.

          Objective

          To investigate potential single-nucleotide variations (SNVs) associated with the effect of BB use on femoral neck BMD, we performed a cross-sectional analysis using clinical data, dual-energy x-ray absorptiometry, and genetic data from the Framingham Heart Study’s (FHS) Offspring Cohort. We then sought to validate our top 4 genetic findings using data from the Rotterdam Study, the BPROOF Study, the Malta Osteoporosis Fracture Study (MOFS), and the Hertfordshire Cohort Study.

          Methods

          We used sex-stratified linear mixed models to determine SNVs that had a significant interaction effect with BB use on femoral neck (FN) BMD across 11 gene regions. We also evaluated the association of our top SNVs from the FHS with microRNA (miRNA) expression in blood and identified potential miRNA-mediated mechanisms by which these SNVs may affect FN BMD.

          Results

          One variation (rs11124190 in HDAC4) was validated in females using data from the Rotterdam Study, while another (rs12414657 in ADRB1) was validated in females using data from the MOFS. We performed an exploratory meta-analysis of all 5 studies for these variations, which further validated our findings.

          Conclusion

          This analysis provides a starting point for investigating the pharmacogenomic effects of BB use on BMD measures.

          Related collections

          Most cited references109

          • Record: found
          • Abstract: found
          • Article: not found

          GCTA: a tool for genome-wide complex trait analysis.

          For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Expanded encyclopaedias of DNA elements in the human and mouse genomes

            The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE 1 and Roadmap Epigenomics 2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants.

              Assessing linkage disequilibrium (LD) across ancestral populations is a powerful approach for investigating population-specific genetic structure as well as functionally mapping regions of disease susceptibility. Here, we present LDlink, a web-based collection of bioinformatic modules that query single nucleotide polymorphisms (SNPs) in population groups of interest to generate haplotype tables and interactive plots. Modules are designed with an emphasis on ease of use, query flexibility, and interactive visualization of results. Phase 3 haplotype data from the 1000 Genomes Project are referenced for calculating pairwise metrics of LD, searching for proxies in high LD, and enumerating all observed haplotypes. LDlink is tailored for investigators interested in mapping common and uncommon disease susceptibility loci by focusing on output linking correlated alleles and highlighting putative functional variants.
                Bookmark

                Author and article information

                Contributors
                Journal
                J Endocr Soc
                J Endocr Soc
                jes
                Journal of the Endocrine Society
                Oxford University Press (US )
                2472-1972
                01 August 2021
                15 May 2021
                15 May 2021
                : 5
                : 8
                : bvab092
                Affiliations
                [1 ] Graduate School of Biomedical Sciences, Tufts University , Boston, MA, 02111, USA
                [2 ] Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute , Portland, ME 04101, USA
                [3 ] Department of Internal Medicine, Erasmus MC, University Medical Center , Rotterdam 3015 GD, the Netherlands
                [4 ] Department of Epidemiology, Erasmus MC, University Medical Center , Rotterdam 3015 GD, the Netherlands
                [5 ] Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta , Msida MSD 2080, Malta
                [6 ] Centre for Molecular Medicine and Biobanking , MSD 2080, Malta
                [7 ] Department of Internal Medicine, Geriatrics, Amsterdam Public Health Research Institute, Amsterdam University Medical Center , Amsterdam, 1105 AZ, the Netherlands
                [8 ] MRC Lifecourse Epidemiology Unit, University of Southampton , Southampton, SO16 6YD, UK
                [9 ] NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust , Southampton, UK
                [10 ] Victoria University of Wellington , Wellington, New Zealand
                [11 ] NIHR Oxford Biomedical Research Centre, University of Oxford , Oxford, UK
                [12 ] Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School , Boston, MA 02215, USA
                [13 ] Hinda and Arthur Marcus Institute for Aging Research Hebrew SeniorLife , Boston, MA 02131, USA
                [14 ] Center for Molecular Medicine, Maine Medical Center Research Institute, Maine Medical Center , Scarborough, ME 04074, USA
                Author notes
                Correspondence: Christine W. Lary, PhD, Center for Outcomes Research and Evaluation, 509 Forest Ave, Ste 200, Portland, ME 04101, USA. Email: clary@ 123456mmc.org .
                Author information
                https://orcid.org/0000-0002-7618-3523
                https://orcid.org/0000-0002-6477-6209
                https://orcid.org/0000-0001-8474-0310
                https://orcid.org/0000-0001-5399-9602
                Article
                bvab092
                10.1210/jendso/bvab092
                8237849
                34195528
                b5f0d10d-2b26-4041-beb4-fc9b81f8ce84
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 25 January 2021
                : 07 May 2021
                : 28 June 2021
                Page count
                Pages: 15
                Funding
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: P20GM121301
                Award ID: K01AR067858
                Award ID: R01 AR041398
                Funded by: Framingham Contract Number;
                Award ID: 75N92019D00031
                Funded by: The Netherlands Organization for Health Research and Development;
                Award ID: 6130.0031
                Funded by: Ministry of Economic Affairs, Agriculture and Innovation, DOI 10.13039/501100016239;
                Award ID: KB-15-004-003
                Funded by: Medical Research Council University Unit Partnership;
                Award ID: MRC_MC_UP_A620_1014
                Categories
                Clinical Research Articles
                AcademicSubjects/MED00250

                β-blocker,beta blocker,bone,pharmacogenomics,mirna,genomics
                β-blocker, beta blocker, bone, pharmacogenomics, mirna, genomics

                Comments

                Comment on this article