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


Journal

Obesity (Silver Spring, Md.)
ISSN: 1930-739X
Titre abrégé: Obesity (Silver Spring)
Pays: United States
ID NLM: 101264860

Informations de publication

Date de publication:
01 2023
Historique:
revised: 23 08 2022
received: 15 12 2021
accepted: 30 08 2022
pubmed: 12 12 2022
medline: 23 12 2022
entrez: 11 12 2022
Statut: ppublish

Résumé

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. 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. 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 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.

Identifiants

pubmed: 36502291
doi: 10.1002/oby.23604
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

267-278

Subventions

Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom

Informations de copyright

© 2022 The Obesity Society.

Références

Holroyd C, Cooper C, Dennison E. Epidemiology of osteoporosis. Best Pract Res Clin Endocrinol Metab. 2008;22:671-685.
Bonjour J-P, Chevalley T, Ferrari S, Rizzoli R. Chapter 9: Peak bone mass and its regulation. In: Glorieux F, Pettifor J, Jüppner H, eds. Pediatric Bone: Biology and Diseases. 2nd ed. Elsevier; 2012: 189-221.
Pocock NA, Eisman JA, Hopper JL, Yeates MG, Sambrook PN, Eberl S. Genetic determinants of bone mass in adults: a twin study. J Clin Invest. 1987;80:706-710.
Blake GM, Fogelman I. The role of DXA bone density scans in the diagnosis and treatment of osteoporosis. Postgrad Med J. 2007;83:509-517.
Fall T, Mendelson M, Speliotes EK. Recent advances in human genetics and epigenetics of adiposity: pathway to precision medicine? Gastroenterology. 2017;152:1695-1706.
World Health Organization. Obesity: Preventing and Managing the Global Epidemic: Report of a WHO Consultation. World Health Organization; 2000.
Deurenberg P, Yap M, Van Staveren WA. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord. 1998;22:1164-1171.
Piché M-E, Poirier P, Lemieux I, Després J-P. Overview of epidemiology and contribution of obesity and body fat distribution to cardiovascular disease: an update. Prog Cardiovasc Dis. 2018;61:103-113.
Tchkonia T, Thomou T, Zhu Y, et al. Mechanisms and metabolic implications of regional differences among fat depots. Cell Metab. 2013;17:644-656.
Hammarstedt A, Gogg S, Hedjazifar S, Nerstedt A, Smith U. Impaired adipogenesis and dysfunctional adipose tissue in human hypertrophic obesity. Physiol Rev. 2018;98:1911-1941.
Taylor R, Holman RR. Normal weight individuals who develop type 2 diabetes: the personal fat threshold. Clin Sci. 2015;128:405-410.
Ji Y, Yiorkas AM, Frau F, et al. Genome-wide and abdominal MRI data provide evidence that a genetically determined favorable adiposity phenotype is characterized by lower ectopic liver fat and lower risk of type 2 diabetes, heart disease, and hypertension. Diabetes. 2019;68:207-219.
Felson DT, Zhang Y, Hannan MT, Anderson JJ. Effects of weight and body mass index on bone mineral density in men and women: the Framingham study. J Bone Miner Res. 1993;8:567-573.
Looker A, Flegal K, Melton LJ. Impact of increased overweight on the projected prevalence of osteoporosis in older women. Osteoporos Int. 2007;18:307-313.
Katzmarzyk PT, Barreira TV, Harrington DM, Staiano AE, Heymsfield SB, Gimble JM. Relationship between abdominal fat and bone mineral density in white and African American adults. Bone. 2012;50:576-579.
Zhu K, Hunter M, James A, Lim E, Cooke B, Walsh J. Relationship between visceral adipose tissue and bone mineral density in Australian baby boomers. Osteoporos Int. 2020;31:2439-2448.
Teumer A. Common methods for performing Mendelian randomization. Front Cardiovasc Med. 2018;5:51. doi:10.3389/fcvm.2018.00051
Song J, Zhang R, Lv L, et al. The relationship between body mass index and bone mineral density: a Mendelian randomization study. Calcif Tissue Int. 2020;107:440-445.
Shea J, King M, Yi Y, Gulliver W, Sun G. Body fat percentage is associated with cardiometabolic dysregulation in BMI-defined normal weight subjects. Nutr Metab Cardiovasc Dis. 2012;22:741-747.
McFarlane SI, Muniyappa R, Shin JJ, Bahtiyar G, Sowers JR. Osteoporosis and cardiovascular disease. Endocrine. 2004;23:1-10.
Loh P-R, Kichaev G, Gazal S, Schoech AP, Price AL. Mixed-model association for biobank-scale datasets. Nat Genet. 2018;50:906-908.
Zheng HF, Forgetta V, Hsu YH, et al. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature. 2015;526:112-117.
Medina-Gomez C, Kemp JP, Trajanoska K, et al. Life-course genome-wide association study meta-analysis of total body BMD and assessment of age-specific effects. Am J Hum Genet. 2018;102:88-102.
Estrada K, Styrkarsdottir U, Evangelou E, et al. Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat Genet. 2012;44:491-501.
Burgess S, Thompson SG. CRP CHD Genetics Collaboration. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40:755-764.
Hemani G, Zheng J, Elsworth B, et al. The MR-base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408. doi:10.7554/eLife.34408
Wallace C. Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses. PLoS Genet. 2020;16:e1008720. doi:10.1371/journal.pgen.1008720
Giambartolomei C, Vukcevic D, Schadt EE, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 2014;10:e1004383. doi:10.1371/journal.pgen.1004383
Zillikens MC, Uitterlinden AG, van Leeuwen JP, et al. The role of body mass index, insulin, and adiponectin in the relation between fat distribution and bone mineral density. Calcif Tissue Int. 2010;86:116-125.
Gilsanz V, Chalfant J, Mo AO, Lee DC, Dorey FJ, Mittelman SD. Reciprocal relations of subcutaneous and visceral fat to bone structure and strength. J Clin Endocrinol Metab. 2009;94:3387-3393.
Zhang Q, Greenbaum J, Shen H, et al. Detecting causal relationship between metabolic traits and osteoporosis using multivariable Mendelian randomization. Osteoporos Int. 2021;32:715-725.
Ahmad OS, Leong A, Miller JA, et al. A Mendelian randomization study of the effect of type-2 diabetes and glycemic traits on bone mineral density. J Bone Miner Res. 2017;32:1072-1081.
Ammann P, Rizzoli R. Bone strength and its determinants. Osteoporos Int. 2003;14:13-18.
Fonseca H, Moreira-Goncalves D, Coriolano HJ, Duarte JA. Bone quality: the determinants of bone strength and fragility. Sports Med. 2014;44:37-53.
Rubin MR, Patsch JM. Assessment of bone turnover and bone quality in type 2 diabetic bone disease: current concepts and future directions. Bone Res. 2016;4:16001. doi:10.1038/boneres.2016.1
Kawai M, de Paula FJ, Rosen CJ. New insights into osteoporosis: the bone-fat connection. J Intern Med. 2012;272:317-329.
Duncan EL, Danoy P, Kemp JP, et al. Genome-wide association study using extreme truncate selection identifies novel genes affecting bone mineral density and fracture risk. PLoS Genet. 2011;7:e1001372. doi:10.1371/journal.pgen.1001372
Loh NY, Minchin JE, Pinnick KE, et al. RSPO3 impacts body fat distribution and regulates adipose cell biology in vitro. Nat Commun. 2020;11:2797. doi:10.1038/s41467-020-16592-z
Heid IM, Jackson AU, Randall JC, et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat Genet. 2010;42:949-960.
Nam J-S, Turcotte TJ, Smith PF, Choi S, Yoon JK. Mouse cristin/R-spondin family proteins are novel ligands for the frizzled 8 and LRP6 receptors and activate β-catenin-dependent gene expression. J Biol Chem. 2006;281:13247-13257.
Ohkawara B, Glinka A, Niehrs C. Rspo3 binds syndecan 4 and induces Wnt/PCP signaling via clathrin-mediated endocytosis to promote morphogenesis. Dev Cell. 2011;20:303-314.
Seifert A, Werheid DF, Knapp SM, Tobiasch E. Role of Hox genes in stem cell differentiation. World J Stem Cells. 2015;7:583-595.
Cesar AS, Regitano LC, Koltes JE, et al. Putative regulatory factors associated with intramuscular fat content. PloS One. 2015;10:e0128350. doi:10.1371/journal.pone.0128350
Elks CE, Perry JR, Sulem P, et al. Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies. Nat Genet. 2010;42:1077-1085.
Demerath EW, Liu C-T, Franceschini N, et al. Genome-wide association study of age at menarche in African-American women. Hum Mol Genet. 2013;22:3329-3346.
Dvornyk V. Genetics of age at menarche: a systematic review. Hum Reprod Update. 2012;18:198-210.
Heymsfield SB, Ebbeling CB, Zheng J, et al. Multi-component molecular-level body composition reference methods: evolving concepts and future directions. Obes Rev. 2015;16:282-294.

Auteurs

Victoria L Bland (VL)

School of Nutritional Sciences and Wellness, University of Arizona, Tucson, Arizona, USA.

Jennifer W Bea (JW)

Department of Health Promotion Sciences, University of Arizona, Tucson, Arizona, USA.
The University of Arizona Cancer Center, Tucson, Arizona, USA.

Scott B Going (SB)

School of Nutritional Sciences and Wellness, University of Arizona, Tucson, Arizona, USA.

Hanieh Yaghootkar (H)

Centre for Inflammation Research and Translational Medicine, Department of Life Sciences, Brunel University London, Uxbridge, UK.
Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Royal Devon & Exeter Hospital, Exeter, UK.

Amit Arora (A)

Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA.

Ferris Ramadan (F)

Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA.

Janet L Funk (JL)

School of Nutritional Sciences and Wellness, University of Arizona, Tucson, Arizona, USA.
Department of Medicine, University of Arizona, Tucson, Arizona, USA.

Zhao Chen (Z)

Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA.

Yann C Klimentidis (YC)

Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA.

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