Top

Diabetologia

Published in:

01-05-2019 | Insulins | Article

Lean mass, grip strength and risk of type 2 diabetes: a bi-directional Mendelian randomisation study

Authors: Chris Ho Ching Yeung, Shiu Lun Au Yeung, Shirley Siu Ming Fong, C. Mary Schooling

Published in: Diabetologia | Issue 5/2019

Abstract

Aims/hypothesis

Muscle mass and strength may protect against type 2 diabetes as a sink for glucose disposal. In randomised controlled trials, resistance training improves glucose metabolism in people with the metabolic syndrome. Whether increasing muscle mass and strength protects against diabetes in the general population is unknown. We assessed the effect of markers of muscle mass and strength on diabetes and glycaemic traits using bi-directional Mendelian randomisation.

Methods

Inverse variance weighting estimates were obtained by applying genetic variants that predict male lean mass, female lean mass and grip strength, obtained from the UK Biobank GWAS, to the largest available case–control study of diabetes (DIAbetes Genetics Replication And Meta-analysis [DIAGRAM]; n = 74,124 cases and 824,006 controls) and to a study of glycaemic traits (Meta-Analyses of Glucose and Insulin-related traits Consortium [MAGIC]). Conversely, we also applied genetic variants that predict diabetes, HbA_1c, fasting glucose, fasting insulin and HOMA-B to UK Biobank summary statistics for genetic association with lean mass and grip strength. As sensitivity analyses we used weighted median, Mendelian randomisation (MR)-Egger and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and removed pleiotropic SNPs.

Results

Grip strength was not significantly associated with diabetes using inverse variance weighting (OR 0.72 per SD increase in grip strength, 95% CI 0.51, 1.01, p = 0.06) and including pleiotropic SNPs but was significantly associated with diabetes using MR-PRESSO (OR 0.77, 95% CI 0.62, 0.95, p = 0.02) after removing pleiotropic SNPs. Female lean mass was significantly associated with diabetes (OR 0.91, 95% CI 0.84, 0.99, p = 0.02) while male lean mass was not significant but directionally similar (OR 0.94, 95% CI 0.88, 1.01, p = 0.09). Conversely, diabetes was inversely and significantly associated with male lean mass (β −0.02 SD change in lean mass, 95% CI −0.04, −0.00, p = 0.04) and grip strength (β −0.01, 95% CI −0.02, −0.00, p = 0.01).

Conclusions/interpretation

Increased muscle mass and strength may be related to lower diabetes risk. Diabetes may also be associated with grip strength and lean mass. Muscle strength could warrant further investigation as a possible target of intervention for diabetes prevention.

Available only for authorised users

Yoon KH, Lee JH, Kim JW et al (2006) Epidemic obesity and type 2 diabetes in Asia. Lancet (London, England) 368(9548):1681–1688. https://doi.org/10.1016/s0140-6736(06)69703-1 CrossRef

Wang T, Huang T, Li Y et al (2016) Low birthweight and risk of type 2 diabetes: a Mendelian randomisation study. Diabetologia 59(9):1920–1927. https://doi.org/10.1007/s00125-016-4019-z CrossRefPubMedPubMedCentral

Bann D, Wills A, Cooper R et al (2014) Birth weight and growth from infancy to late adolescence in relation to fat and lean mass in early old age: findings from the MRC National Survey of Health and Development. Int J Obes 38(1):69–75. https://doi.org/10.1038/ijo.2013.115 CrossRefPubMed

Smith AG, Muscat GEO (2005) Skeletal muscle and nuclear hormone receptors: implications for cardiovascular and metabolic disease. Int J Biochem Cell Biol 37(10):2047–2063. https://doi.org/10.1016/j.biocel.2005.03.002 CrossRefPubMed

Schooling CM, Jiang C, Zhang W, Lam TH, Cheng KK, Leung GM (2011) Adolescent build and diabetes: the Guangzhou Biobank Cohort Study. Ann Epidemiol 21(1):61–66. https://doi.org/10.1016/j.annepidem.2010.08.010 CrossRefPubMed

Strasser B, Siebert U, Schobersberger W (2010) Resistance training in the treatment of the metabolic syndrome: a systematic review and meta-analysis of the effect of resistance training on metabolic clustering in patients with abnormal glucose metabolism. Sports Med (Auckland, NZ) 40(5):397–415. https://doi.org/10.2165/11531380-000000000-00000 CrossRef

Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey Smith G (2008) Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 27(8):1133–1163. https://doi.org/10.1002/sim.3034 CrossRefPubMed

Zheng J, Baird D, Borges MC et al (2017) Recent developments in Mendelian randomization studies. Curr Epidemiol Rep 4(4):330–345. https://doi.org/10.1007/s40471-017-0128-6 CrossRefPubMedPubMedCentral

Lawlor DA (2016) Commentary: Two-sample Mendelian randomization: opportunities and challenges. Int J Epidemiol 45(3):908–915. https://doi.org/10.1093/ije/dyw127 CrossRefPubMedPubMedCentral

10.

Taylor AE, Davies NM, Ware JJ, VanderWeele T, Smith GD, Munafo MR (2014) Mendelian randomization in health research: using appropriate genetic variants and avoiding biased estimates. Econ Hum Biol 13:99–106. https://doi.org/10.1016/j.ehb.2013.12.002 CrossRefPubMedPubMedCentral

11.

Xu L, Hao YT (2017) Effect of handgrip on coronary artery disease and myocardial infarction: a Mendelian randomization study. Sci Rep 7(1):954. https://doi.org/10.1038/s41598-017-01073-z CrossRefPubMedPubMedCentral

12.

The Neale Lab (2018) GWAS results. Available from http://www.nealelab.is/uk-biobank/, accessed 28 Oct 2018

13.

Sudlow C, Gallacher J, Allen N et al (2015) UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 12(3):e1001779. https://doi.org/10.1371/journal.pmed.1001779 CrossRefPubMedPubMedCentral

14.

UK Biobank (2011) Grip strength measurement. Available from http://biobank.ctsu.ox.ac.uk/crystal/docs/Gripstrength.pdf, accessed 28 Oct 2018

15.

Howrigan D (2017) Details and considerations of the UK Biobank GWAS. Available from http://www.nealelab.is/blog/2017/9/11/details-and-considerations-of-the-uk-biobank-gwas, accessed 28 Oct 2018

16.

Zillikens MC, Demissie S, Hsu YH et al (2017) Large meta-analysis of genome-wide association studies identifies five loci for lean body mass. Nat Commun 8(1):80. https://doi.org/10.1038/s41467-017-00031-7 CrossRefPubMedPubMedCentral

17.

Visser M, Fuerst T, Lang T, Salamone L, Harris TB (1999) Validity of fan-beam dual-energy X-ray absorptiometry for measuring fat-free mass and leg muscle mass. Health, Aging, and Body Composition Study—Dual-Energy X-ray Absorptiometry and Body Composition Working Group. J Appl Physiol 87(4):1513–1520. https://doi.org/10.1152/jappl.1999.87.4.1513 CrossRefPubMed

18.

Tikkanen E, Gustafsson S, Amar D et al (2018) Biological insights into muscular strength: genetic findings in the UK Biobank. Sci Rep 8(1):6451. https://doi.org/10.1038/s41598-018-24735-y CrossRefPubMedPubMedCentral

19.

Wind AE, Takken T, Helders PJ, Engelbert RH (2010) Is grip strength a predictor for total muscle strength in healthy children, adolescents, and young adults? Eur J Pediatr 169(3):281–287. https://doi.org/10.1007/s00431-009-1010-4 CrossRefPubMed

20.

Mahajan A, Taliun D, Thurner M et al (2018) Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat Genet 50(11):1505–1513. https://doi.org/10.1038/s41588-018-0241-6 CrossRefPubMedPubMedCentral

21.

Wheeler E, Leong A, Liu C-T et al (2017) Impact of common genetic determinants of hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: a transethnic genome-wide meta-analysis. PLoS Med 14(9):e1002383. https://doi.org/10.1371/journal.pmed.1002383 CrossRefPubMedPubMedCentral

22.

Dupuis J, Langenberg C, Prokopenko I et al (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 42(2):105–116. https://doi.org/10.1038/ng.520 CrossRefPubMedPubMedCentral

23.

Manning AK, Hivert M-F, Scott RA et al (2012) A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet 44(6):659–669. https://doi.org/10.1038/ng.2274 CrossRefPubMedPubMedCentral

24.

Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28(7):412–419. https://doi.org/10.1007/BF00280883 CrossRefPubMed

25.

Scott RA, Lagou V, Welch RP et al (2012) Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 44(9):991–1005. https://doi.org/10.1038/ng.2385 CrossRefPubMedPubMedCentral

26.

Pierce BL, Ahsan H, VanderWeele TJ (2011) Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol 40(3):740–752. https://doi.org/10.1093/ije/dyq151 CrossRefPubMed

27.

Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan NA, Thompson JR (2016) Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I ² statistic. Int J Epidemiol 45(6):1961–1974. https://doi.org/10.1093/ije/dyw220 CrossRefPubMedPubMedCentral

28.

Burgess S (2014) Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome. Int J Epidemiol 43(3):922–929. https://doi.org/10.1093/ije/dyu005 CrossRefPubMedPubMedCentral

29.

Staley JR, Blackshaw J, Kamat MA et al (2016) PhenoScanner: a database of human genotype–phenotype associations. Bioinformatics (Oxford, England) 32(20):3207–3209. https://doi.org/10.1093/bioinformatics/btw373 CrossRef

30.

MacArthur J, Bowler E, Cerezo M et al (2017) The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res 45(D1):D896–D901. https://doi.org/10.1093/nar/gkw1133 CrossRefPubMed

31.

Verbanck M, Chen C-Y, Neale B, Do R (2018) Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 50(5):693–698. https://doi.org/10.1038/s41588-018-0099-7 CrossRefPubMedPubMedCentral

32.

Brion M-JA, Shakhbazov K, Visscher PM (2013) Calculating statistical power in Mendelian randomization studies. Int J Epidemiol 42(5):1497–1501. https://doi.org/10.1093/ije/dyt179 CrossRefPubMed

33.

Robinson C, Tomek S, Schumacker R (2013) Tests of moderation effects: difference in simple slopes versus the interaction term. Multiple Linear Regression Viewpoints 39:16–25

34.

Hemani G, Zheng J, Elsworth B et al (2018) The MR-Base platform supports systematic causal inference across the human phenome. eLife 7:e34408. https://doi.org/10.7554/eLife.34408 CrossRefPubMedPubMedCentral

35.

R Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria

36.

Bowden J, Davey Smith G, Haycock PC, Burgess S (2016) Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol 40(4):304–314. https://doi.org/10.1002/gepi.21965 CrossRefPubMedPubMedCentral

37.

Bowden J, Davey Smith G, Burgess S (2015) Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 44(2):512–525. https://doi.org/10.1093/ije/dyv080 CrossRefPubMedPubMedCentral

38.

Gomez-Ambrosi J, Silva C, Galofre JC et al (2011) Body adiposity and type 2 diabetes: increased risk with a high body fat percentage even having a normal BMI. Obesity 19(7):1439–1444. https://doi.org/10.1038/oby.2011.36 CrossRefPubMed

39.

Li JJ, Wittert GA, Vincent A et al (2016) Muscle grip strength predicts incident type 2 diabetes: population-based cohort study. Metabolism 65(6):883–892. https://doi.org/10.1016/j.metabol.2016.03.011 CrossRefPubMed

40.

Kalyani RR, Corriere M, Ferrucci L (2014) Age-related and disease-related muscle loss: the effect of diabetes, obesity, and other diseases. Lancet Diabetes Endocrinol 2(10):819–829. https://doi.org/10.1016/s2213-8587(14)70034-8 CrossRef

41.

Kalyani RR, Saudek CD, Brancati FL, Selvin E (2010) Association of diabetes, comorbidities, and A1C with functional disability in older adults: results from the National Health and Nutrition Examination Survey (NHANES), 1999-2006. Diabetes Care 33(5):1055–1060. https://doi.org/10.2337/dc09-1597 CrossRefPubMedPubMedCentral

42.

Holten MK, Zacho M, Gaster M, Juel C et al (2004) Strength training increases insulin-mediated glucose uptake, GLUT4 content, and insulin signaling in skeletal muscle in patients with type 2 diabetes. Diabetes 53(2):294–305. https://doi.org/10.2337/diabetes.53.2.294 CrossRefPubMed

43.

Geirsdottir OG, Arnarson A, Briem K, Ramel A, Jonsson PV, Thorsdottir I (2012) Effect of 12-week resistance exercise program on body composition, muscle strength, physical function, and glucose metabolism in healthy, insulin-resistant, and diabetic elderly Icelanders. J Gerontol A Biol Sci Med Sci 67(11):1259–1265. https://doi.org/10.1093/gerona/gls096 CrossRefPubMed

44.

Ramachandran A, Wan Ma RC, Snehalatha C (2010) Diabetes in Asia. Lancet 375(9712):408–418. https://doi.org/10.1016/S0140-6736(09)60937-5 CrossRefPubMed

45.

Rush EC, Freitas I, Plank LD (2009) Body size, body composition and fat distribution: comparative analysis of European, Maori, Pacific Island and Asian Indian adults. Br J Nutr 102(04):632–641. https://doi.org/10.1017/S0007114508207221 CrossRefPubMed

46.

Hou WW, Tse MA, Lam TH, Leung GM, Schooling CM (2015) Adolescent testosterone, muscle mass and glucose metabolism: evidence from the ‘Children of 1997’ birth cohort in Hong Kong. Diabet Med 32(4):505–512. https://doi.org/10.1111/dme.12602 CrossRefPubMed

47.

Davey Smith G, Lawlor DA, Harbord R, Timpson N, Day I, Ebrahim S (2007) Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology. PLoS Med 4(12):e352. https://doi.org/10.1371/journal.pmed.0040352 CrossRef

48.

Schooling CM (2018) Selection bias in population-representative studies? A commentary on Deaton and Cartwright. Soc Sci Med. https://doi.org/10.1016/j.socscimed.2018.04.047 CrossRef

49.

Anderson CD, Nalls MA, Biffi A et al (2011) The effect of survival bias on case-control genetic association studies of highly lethal diseases. Circ Cardiovasc Genet 4(2):188–196. https://doi.org/10.1161/CIRCGENETICS.110.957928 CrossRefPubMedPubMedCentral

Title: Lean mass, grip strength and risk of type 2 diabetes: a bi-directional Mendelian randomisation study
Authors: Chris Ho Ching Yeung
Shiu Lun Au Yeung
Shirley Siu Ming Fong
C. Mary Schooling
Publication date: 01-05-2019
Publisher: Springer Berlin Heidelberg
Keywords: Insulins
Insulins
Type 2 Diabetes
Published in: Diabetologia / Issue 5/2019
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI: https://doi.org/10.1007/s00125-019-4826-0

Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Pediatric Cardiology Video

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

Cardiopulmonary Comorbidity Video

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Valvular Heart Disease Video

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

Watch now

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits

Illustration of figure on mountain summit/© Orapun / Stock.adobe.com, STEP AAG HeroTeaserCollection image/© Tarek / Generated with AI / Stock.adobe.com, ACC 2024 Pediatric and Congenital Heart Disease: Year in Review/© 2024 American College of Cardiology, ACC 2024 Pulmonary Vascular Disease: Year in Review/© 2024 American College of Cardiology, ACC 2024 Valvular Heart Disease: Year in Review/© 2024 American College of Cardiology, ACC 2024 HF and Cardiomyopathies: Year in Review/© 2024 American College of Cardiology, Woman out walking/© Seventyfour / stock.adobe.com (symbolic image with model), Woman checking smartwatch /© saltdium / stock.adobe.com (symbolic image with model), Cardiac catheterization/© Damian / stock.adobe.com

At a glance: The STEP trials

Springer Medicine

Abstract

Aims/hypothesis

Methods

Results

Conclusions/interpretation

Please log in to get access to this content

Other articles of this Issue 5/2019

Alcohol consumption and incident diabetes: The Atherosclerosis Risk in Communities (ARIC) study

Rationale for enteroviral vaccination and antiviral therapies in human type 1 diabetes

Black African men with early type 2 diabetes have similar muscle, liver and adipose tissue insulin sensitivity to white European men despite lower visceral fat

Selective deletion of endothelial cell calpain in mice reduces diabetic cardiomyopathy by improving angiogenesis

Up front

Long-term exposure to ambient fine particulate matter (PM2.5) and incident type 2 diabetes: a longitudinal cohort study

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

Highlights from the ACC 2024 Congress

ACC 2024 Congress Coverage