Application of Mendelian randomization: can we establish causal risk factors for type 2 diabetes in low-to-middle income countries?

Autores/as

  • Ryan James Quentin Langdon University of Bristol
  • Kaitlin Hazel Wade University of Bristol

DOI:

https://doi.org/10.15649/cuidarte.v8i1.373

Palabras clave:

diabetes

Resumen

The global burden of type 2 diabetes (T2D) is increasing, partially facilitated by a sharp increase in the disease in low and middle income countries (LMICs). LMICs not only show a high prevalence of T2D (8.7%), but have shown a much faster increase in this prevalence over the past 30 years when compared to high-income countries (HICs). Conventional risk factors for T2D in HICs, such as high body mass index (BMI), low levels of physical activity, and poor dietary behaviours, do not fully account for the greater increase in prevalence of T2D in LMICs. Therefore, risk factors for T2D specifically within an LMIC context need to be determined. 

How to cite this article: Langdon RJQ, Wade KH. Application of Mendelian randomization: can we establish causal risk factors for type 2 diabetes in low-to-middle income countries? Rev Cuid. 2017; 8(1): 1391-406. http://dx.doi.org/10.15649/cuidarte.v8i1.373

Biografía del autor/a

Ryan James Quentin Langdon, University of Bristol

BSc, Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom. Corresponding author, E-mail: ryan.langdon@bristol.ac.uk

Kaitlin Hazel Wade, University of Bristol

PhD, Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom, E-mail: kaitlin.wade@bristol.ac.uk

Referencias

NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet. 2016; 387 (10027): 1513-30. http://dx.doi.org/10.1016/S0140-6736(16)00618-8

Dagenais GR, Gerstein HC, Zhang X, McQueen M, Lear S, Lopez-Jaramillo P, et al. Variations in Diabetes Prevalence in Low-, Middle-, and High-Income Countries: Results From the Prospective Urban and Rural Epidemiological Study. Diabetes Care. 2016; 39(5):780-7. http://dx.doi.org/10.2337/dc15-2338

Prospective Studies Collaboration, Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Halsey J, et al. Body-mass index and cause-specific mortality in 900000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009; 373(9669):1083-96. http://dx.doi.org/10.1016/S0140-6736(09)60318-4

Zaccardi F, O'Donovan G, Webb DR, Yates T, Kurl S, Khunti K, et al. Cardiorespiratory fitness and risk of type 2 diabetes mellitus: A 23-year cohort study and a meta-analysis of prospective studies. Atherosclerosis. 2015; 243(1):131-7. http://doi.org/10.1016/j.atherosclerosis.2015.09.016

Ezzati M, Riboli E. Behavioral and dietary risk factors for noncommunicable diseases. N Engl J Med. 2013; 369(10):954-64. https://doi.org/10.1056/NEJMra1203528

Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith G. Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies. Am J Clin Nutr. 2016; 103(4): 965-78. https://doi.org/10.3945/ajcn.115.118216

Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014; 15; 23(R1): R89-98. https://doi.org/10.1093/hmg/ddu328

Sandhu MS, Debenham SL, Barroso I, Loos RJ. Mendelian randomisation studies of type 2 diabetes: future prospects. Diabetologia. 2008; 51(2):211-3. https://doi.org/10.1007/s00125-007-0903-x

Swerdlow DI. Mendelian Randomization and Type 2 Diabetes. Cardiovasc Drugs Ther. 2016; 30(1):51-7. https://doi.org/10.1007/s10557-016-6638-5

Corbin LJ, Richmond RC, Wade KH, Burgess S, Bowden J, Davey Smith G, et al. BMI as a modifiable risk factor for type 2 diabetes: refining and understanding causal estimates using Mendelian randomisation. Diabetes. 2016; 65(10): 3002-7. https://doi.org/10.2337/db16-0418

Borges MC, Hartwig FP, Oliveira IO, Horta BL. Is there a causal role for homocysteine concentration in blood pressure? A Mendelian randomization study. Am J Clin Nutr. 2016;103(1):39-49. https://doi.org/10.3945/ajcn.115.116038

van Meurs JB, Pare G, Schwartz SM, Hazra A, Tanaka T, Vermeulen SH, et al. Common genetic loci influencing plasma homocysteine concentrations and their effect on risk of coronary artery disease. Am J Clin Nutr. 2013; 98(3):668-76. https://doi.org/10.3945/ajcn.112.044545

The International Consortium for Blood Pressure Genome-Wide Association Studies. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature. 2011; 478(7367):103-9. https://doi.org/10.1038/nature10405

Hartwig FP, Horta BL, Davey Smith G, de Mola CL, Victora CG. Association of lactase persistence genotype with milk consumption, obesity and blood pressure: a Mendelian randomization study in the 1982 Pelotas (Brazil) Birth Cohort, with a systematic review and meta-analysis. Int J Epidemiol. 2016; 45(5): 1573- 87. https://doi.org/10.1093/ije/dyw074

Ehret GB, Ferreira T, Chasman DI, Jackson AU, Schmidt EM, Johnson T, et al. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nat Genet. 2016;48(10):1171-84. https://doi.org/10.1038/ng.3667

Zanetti D, Weale ME. True causal effect size heterogeneity is required to explain trans-ethnic differences in GWAS signals. bioRxiv. 2016. http://dx.doi.org/10.1101/085092

Publicado

2017-01-01

Cómo citar

1.
Langdon RJQ, Wade KH. Application of Mendelian randomization: can we establish causal risk factors for type 2 diabetes in low-to-middle income countries?. Revista Cuidarte [Internet]. 1 de enero de 2017 [citado 19 de abril de 2024];8(1):1391-406. Disponible en: https://revistas.udes.edu.co/cuidarte/article/view/373

Altmetrics

Descargas

Los datos de descargas todavía no están disponibles.