Zheng Y, Ley SH, Hu FB (2018) Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol 14(2):88–98. https://doi.org/10.1038/nrendo.2017.151
Article
PubMed
Google Scholar
Federation ID (2020) IDF Diabetes atlas 9th edn 2019. Available from https://diabetesatlas.org/en/ Accessed 20 Jan 2020
Naqshbandi M, Harris SB, Esler JG, Antwi-Nsiah F (2008) Global complication rates of type 2 diabetes in indigenous peoples: a comprehensive review. Diabetes Res Clin Pract 82(1):1–17. https://doi.org/10.1016/j.diabres.2008.07.017
Article
PubMed
Google Scholar
Bellou V, Belbasis L, Tzoulaki I, Evangelou E (2018) Risk factors for type 2 diabetes mellitus: an exposure-wide umbrella review of meta-analyses. PLoS One 13(3):e0194127. https://doi.org/10.1371/journal.pone.0194127
CAS
Article
PubMed
PubMed Central
Google Scholar
Dendup T, Feng X, Clingan S, Astell-Burt T (2018) Environmental risk factors for developing type 2 diabetes mellitus: a systematic review. Int J Environ Res Public Health 15(1):78. https://doi.org/10.3390/ijerph15010078
Article
PubMed Central
Google Scholar
Sattar N, Wannamethee SG, Forouhi NG (2008) Novel biochemical risk factors for type 2 diabetes: pathogenic insights or prediction possibilities? Diabetologia 51(6):926–940. https://doi.org/10.1007/s00125-008-0954-7
CAS
Article
PubMed
Google Scholar
Davey Smith G, Ebrahim S (2005) What can mendelian randomisation tell us about modifiable behavioural and environmental exposures? BMJ 330(7499):1076–1079. https://doi.org/10.1136/bmj.330.7499.1076
Article
PubMed
PubMed Central
Google Scholar
Burgess S, Thompson SG (2015) Mendelian randomization: methods for using genetic variants in causal estimation. Chapman and Hall/CRC Press, London, UK
Book
Google Scholar
Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith G (2016) Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies. Am J Clin Nutr 103(4):965–978. https://doi.org/10.3945/ajcn.115.118216
CAS
Article
PubMed
PubMed Central
Google Scholar
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
CAS
Article
PubMed
PubMed Central
Google Scholar
Pulit SL, Stoneman C, Morris AP et al (2019) Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet 28(1):166–174. https://doi.org/10.1093/hmg/ddy327
CAS
Article
PubMed
Google Scholar
Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG (2017) Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants. Epidemiology 28(1):30–42. https://doi.org/10.1097/ede.0000000000000559
Article
PubMed
Google Scholar
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
Article
PubMed
PubMed Central
Google Scholar
Burgess S, Thompson SG (2017) Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol 32(5):377–389. https://doi.org/10.1007/s10654-017-0255-x
Article
PubMed
PubMed Central
Google Scholar
Greco MF, Minelli C, Sheehan NA, Thompson JR (2015) Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med 34(21):2926–2940. https://doi.org/10.1002/sim.6522
Article
Google Scholar
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
Article
PubMed
PubMed Central
Google Scholar
Burgess S, Thompson SG (2015) Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. Am J Epidemiol 181(4):251–260. https://doi.org/10.1093/aje/kwu283
Article
PubMed
PubMed Central
Google Scholar
Brion MJ, 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
Article
PubMed
Google Scholar
Spiller W, Davies NM, Palmer TM (2019) Software application profile: mrrobust—a tool for performing two-sample summary Mendelian randomization analyses. Int J Epidemiol. https://doi.org/10.1093/ije/dyy195
Yavorska OO, Burgess S (2017) MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol 46(6):1734–1739. https://doi.org/10.1093/ije/dyx034
Article
PubMed
PubMed Central
Google Scholar
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Stat Methodol 57(1):11. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Article
Google Scholar
Noordam R, Oudt CH, Bos MM, Smit RAJ, van Heemst D (2018) High-sensitivity C-reactive protein, low-grade systemic inflammation and type 2 diabetes mellitus: a two-sample Mendelian randomization study. Nutr Metab Cardiovasc Dis 28(8):795–802. https://doi.org/10.1016/j.numecd.2018.03.008
CAS
Article
PubMed
Google Scholar
Cheng L, Zhuang H, Yang S, Jiang H, Wang S, Zhang J (2018) Exposing the causal effect of C-reactive protein on the risk of type 2 diabetes mellitus: a Mendelian randomization study. Front Genet 9:657. https://doi.org/10.3389/fgene.2018.00657
CAS
Article
PubMed
PubMed Central
Google Scholar
Kumar J, Ingelsson E, Lind L, Fall T (2015) No evidence of a causal relationship between plasma homocysteine and type 2 diabetes: a Mendelian randomization study. Front Cardiovasc Med 2:11. https://doi.org/10.3389/fcvm.2015.00011
CAS
Article
PubMed
PubMed Central
Google Scholar
Huang T, Ren J, Huang J, Li D (2013) Association of homocysteine with type 2 diabetes: a meta-analysis implementing Mendelian randomization approach. BMC Genomics 14:867. https://doi.org/10.1186/1471-2164-14-867
CAS
Article
PubMed
PubMed Central
Google Scholar
Yuan S, Larsson SC (2019) A causal relationship between cigarette smoking and type 2 diabetes mellitus: a Mendelian randomization study. Sci Rep 9(1):19342. https://doi.org/10.1038/s41598-019-56014-9
CAS
Article
PubMed
PubMed Central
Google Scholar
Vgontzas AN, Liao D, Pejovic S, Calhoun S, Karataraki M, Bixler EO (2009) Insomnia with objective short sleep duration is associated with type 2 diabetes: a population-based study. Diabetes Care 32(11):1980–1985. https://doi.org/10.2337/dc09-0284
Article
PubMed
PubMed Central
Google Scholar
Hein M, Lanquart JP, Loas G, Hubain P, Linkowski P (2018) Prevalence and risk factors of type 2 diabetes in insomnia sufferers: a study on 1311 individuals referred for sleep examinations. Sleep Med 46:37–45. https://doi.org/10.1016/j.sleep.2018.02.006
Article
PubMed
Google Scholar
Shan Z, Ma H, Xie M et al (2015) Sleep duration and risk of type 2 diabetes: a meta-analysis of prospective studies. Diabetes Care 38(3):529–537. https://doi.org/10.2337/dc14-2073
Article
PubMed
Google Scholar
Chen GC, Liu MM, Chen LH et al (2018) Daytime napping and risk of type 2 diabetes: a meta-analysis of prospective studies. Sleep Breath 22(3):815–824. https://doi.org/10.1007/s11325-017-1528-z
Article
PubMed
Google Scholar
Theorell-Haglow J, Lemming EW, Michaelsson K, Elmstahl S, Lind L, Lindberg E (2020) Sleep duration is associated with healthy diet scores and meal patterns: results from the population-based EpiHealth study. J Clin Sleep Med 16(1):9–18. https://doi.org/10.5664/jcsm.8112
Article
PubMed
PubMed Central
Google Scholar
Baliunas DO, Taylor BJ, Irving H et al (2009) Alcohol as a risk factor for type 2 diabetes: a systematic review and meta-analysis. Diabetes Care 32(11):2123–2132. https://doi.org/10.2337/dc09-0227
CAS
Article
PubMed
PubMed Central
Google Scholar
Faurschou M, Ahlstrom MG, Lindhardsen J, Obel N, Baslund B (2017) Risk of diabetes mellitus among patients diagnosed with giant cell arteritis or granulomatosis with polyangiitis: comparison with the general population. J Rheumatol 44(1):78–83. https://doi.org/10.3899/jrheum.160797
CAS
Article
PubMed
Google Scholar
Jakobsson K, Jacobsson L, Warrington K et al (2015) Body mass index and the risk of giant cell arteritis: results from a prospective study. Rheumatology (Oxford) 54(3):433–440. https://doi.org/10.1093/rheumatology/keu331
Article
Google Scholar
Lyall DM, Celis-Morales C, Ward J et al (2017) Association of body mass index with cardiometabolic disease in the UK Biobank: a Mendelian randomization study. JAMA Cardiol 2(8):882–889. https://doi.org/10.1001/jamacardio.2016.5804
Article
PubMed
PubMed Central
Google Scholar
Li XH, Yu FF, Zhou YH, He J (2016) Association between alcohol consumption and the risk of incident type 2 diabetes: a systematic review and dose-response meta-analysis. Am J Clin Nutr 103(3):818–829. https://doi.org/10.3945/ajcn.115.114389
CAS
Article
PubMed
Google Scholar
Knott C, Bell S, Britton A (2015) Alcohol consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of more than 1.9 million individuals from 38 observational studies. Diabetes Care 38(9):1804–1812. https://doi.org/10.2337/dc15-0710
CAS
Article
PubMed
Google Scholar
Carlstrom M, Larsson SC (2018) Coffee consumption and reduced risk of developing type 2 diabetes: a systematic review with meta-analysis. Nutr Rev 76(6):395–417. https://doi.org/10.1093/nutrit/nuy014
Article
PubMed
Google Scholar
Cornelis MC, Munafo MR (2018) Mendelian randomization studies of coffee and caffeine consumption. Nutrients 10(10):1343. https://doi.org/10.3390/nu10101343
CAS
Article
PubMed Central
Google Scholar
Hu G, Jousilahti P, Peltonen M, Lindstrom J, Tuomilehto J (2005) Urinary sodium and potassium excretion and the risk of type 2 diabetes: a prospective study in Finland. Diabetologia 48(8):1477–1483. https://doi.org/10.1007/s00125-005-1824-1
CAS
Article
PubMed
Google Scholar
Provenzano LF, Stark S, Steenkiste A, Piraino B, Sevick MA (2014) Dietary sodium intake in type 2 diabetes. Clin Diabetes 32(3):106–112. https://doi.org/10.2337/diaclin.32.3.106
Article
PubMed
PubMed Central
Google Scholar
Kivimaki M, Batty GD, Pentti J et al (2020) Association between socioeconomic status and the development of mental and physical health conditions in adulthood: a multi-cohort study. Lancet Public Health. https://doi.org/10.1016/s2468-2667(19)30248-8
Thyssen JP, Halling-Overgaard AS, Andersen YMF, Gislason G, Skov L, Egeberg A (2018) The association with cardiovascular disease and type 2 diabetes in adults with atopic dermatitis: a systematic review and meta-analysis. Br J Dermatol 178(6):1272–1279. https://doi.org/10.1111/bjd.16215
CAS
Article
PubMed
Google Scholar
Deschenes SS, Burns RJ, Graham E, Schmitz N (2016) Prediabetes, depressive and anxiety symptoms, and risk of type 2 diabetes: a community-based cohort study. J Psychosom Res 89:85–90. https://doi.org/10.1016/j.jpsychores.2016.08.011
Article
PubMed
Google Scholar
Edwards LE, Mezuk B (2012) Anxiety and risk of type 2 diabetes: evidence from the Baltimore Epidemiologic Catchment Area Study. J Psychosom Res 73(6):418–423. https://doi.org/10.1016/j.jpsychores.2012.09.018
Article
PubMed
PubMed Central
Google Scholar
Roshanzamir F, Miraghajani M, Rouhani MH, Mansourian M, Ghiasvand R, Safavi SM (2018) The association between circulating fetuin-A levels and type 2 diabetes mellitus risk: systematic review and meta-analysis of observational studies. J Endocrinol Investig 41(1):33–47. https://doi.org/10.1007/s40618-017-0697-8
CAS
Article
Google Scholar
Merino J, Leong A, Liu CT et al (2018) Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose. Diabetologia 61(6):1315–1324. https://doi.org/10.1007/s00125-018-4599-x
CAS
Article
PubMed
PubMed Central
Google Scholar
Tang B, Yuan S, Xiong Y, He Q, Larsson SC (2020) Major depressive disorder and cardiometabolic diseases: a bidirectional Mendelian randomisation study. Diabetologia. https://doi.org/10.1007/s00125-020-05131-6
Yuan S, Xiong Y, Michaelsson M, Michaelsson K, Larsson SC (2020) Health related effects of education levels: a Mendelian randomization study. medRχiv. https://doi.org/10.1101/2020.02.01.20020008
Bluher M (2019) Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol 15(5):288–298. https://doi.org/10.1038/s41574-019-0176-8
Article
PubMed
Google Scholar
Aikens RC, Zhao W, Saleheen D et al (2017) Systolic blood pressure and risk of type 2 diabetes: a Mendelian randomization study. Diabetes 66(2):543–550. https://doi.org/10.2337/db16-0868
CAS
Article
PubMed
Google Scholar
Telomeres Mendelian Randomization Collaboration, Haycock PC, Burgess S et al (2017) Association between telomere length and risk of cancer and non-neoplastic diseases: a Mendelian randomization study. JAMA Oncol 3(5):636–651. https://doi.org/10.1001/jamaoncol.2016.5945
Article
Google Scholar
Perry JR, Ferrucci L, Bandinelli S et al (2009) Circulating β-carotene levels and type 2 diabetes-cause or effect? Diabetologia. 52(10):2117–2121. https://doi.org/10.1007/s00125-009-1475-8
CAS
Article
PubMed
PubMed Central
Google Scholar
Moen GH, Qvigstad E, Birkeland KI, Evans DM, Sommer C (2018) Are serum concentrations of vitamin B-12 causally related to cardiometabolic risk factors and disease? A Mendelian randomization study. Am J Clin Nutr 108(2):398–404. https://doi.org/10.1093/ajcn/nqy101
Article
PubMed
Google Scholar
Cheng WW, Zhu Q, Zhang HY (2019) Mineral nutrition and the risk of chronic diseases: a Mendelian randomization study. Nutrients 11(2):378. https://doi.org/10.3390/nu11020378
CAS
Article
PubMed Central
Google Scholar
Yarmolinsky J, Bonilla C, Haycock PC et al (2018) Circulating selenium and prostate cancer risk: a Mendelian randomization analysis. J Natl Cancer Inst 110(9):1035–1038. https://doi.org/10.1093/jnci/djy081
CAS
Article
PubMed
PubMed Central
Google Scholar
Bos MM, Smit RAJ, Trompet S, van Heemst D, Noordam R (2017) Thyroid signaling, insulin resistance, and 2 diabetes mellitus: a Mendelian randomization study. J Clin Endocrinol Metab 102(6):1960–1970. https://doi.org/10.1210/jc.2016-2816
Article
PubMed
Google Scholar
White J, Swerdlow DI, Preiss D et al (2016) Association of lipid fractions with risks for coronary artery disease and diabetes. JAMA Cardiol 1(6):692–699. https://doi.org/10.1001/jamacardio.2016.1884
Article
PubMed
PubMed Central
Google Scholar
De Silva NMG, Borges MC, Hingorani AD et al (2019) Liver function and risk of type 2 diabetes: bidirectional Mendelian randomization study. Diabetes 68(8):1681–1691. https://doi.org/10.2337/db18-1048
CAS
Article
PubMed
PubMed Central
Google Scholar
Keenan T, Zhao W, Rasheed A et al (2016) Causal assessment of serum urate levels in cardiometabolic diseases through a Mendelian randomization study. J Am Coll Cardiol 67(4):407–416. https://doi.org/10.1016/j.jacc.2015.10.086
CAS
Article
PubMed
PubMed Central
Google Scholar
Abbasi A (2015) Mendelian randomization studies of biomarkers and type 2 diabetes. Endocr Connect 4(4):249–260. https://doi.org/10.1530/EC-15-0087
CAS
Article
PubMed
PubMed Central
Google Scholar
Kröger J, Meidtner K, Stefan N et al (2018) Circulating fetuin-a and risk of type 2 diabetes: a Mendelian randomization analysis. Diabetes 67(6):1200–1205. https://doi.org/10.2337/db17-1268
CAS
Article
PubMed
Google Scholar
Abbasi A, Deetman PE, Corpeleijn E et al (2015) Bilirubin as a potential causal factor in type 2 diabetes risk: a Mendelian randomization study. Diabetes 64(4):1459–1469. https://doi.org/10.2337/db14-0228
CAS
Article
PubMed
Google Scholar
Lotta LA, Scott RA, Sharp SJ et al (2016) Genetic predisposition to an impaired metabolism of the branched-chain amino acids and risk of type 2 diabetes: a Mendelian randomisation analysis. PLoS Med 13(11):e1002179. https://doi.org/10.1371/journal.pmed.1002179
CAS
Article
PubMed
PubMed Central
Google Scholar
Interleukin 1 Genetics Consortium (2015) Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis. Lancet Diabetes Endocrinol 3(4):243–253. https://doi.org/10.1016/S2213-8587(15)00034-0
CAS
Article
Google Scholar
Interleukin-6 Receptor Mendelian Randomisation Analysis (IL6R MR) Consortium, Swerdlow DI, Holmes MV et al (2012) The interleukin-6 receptor as a target for prevention of coronary heart disease: a mendelian randomisation analysis. Lancet 379(9822):1214–1224. https://doi.org/10.1016/S0140-6736(12)60110-X
CAS
Article
Google Scholar
Zhuang H, Han J, Cheng L, Liu SL (2019) A positive causal influence of IL-18 levels on the risk of T2DM: a Mendelian randomization study. Front Genet 10:295. https://doi.org/10.3389/fgene.2019.00295
CAS
Article
PubMed
PubMed Central
Google Scholar
Kwok MK, Leung GM, Schooling CM (2016) Habitual coffee consumption and risk of type 2 diabetes, ischemic heart disease, depression and Alzheimer’s disease: a Mendelian randomization study. Sci Rep 6:36500. https://doi.org/10.1038/srep36500
CAS
Article
PubMed
PubMed Central
Google Scholar
Wang J, Kwok MK, Au Yeung SL et al (2019) Sleep duration and risk of diabetes: observational and Mendelian randomization studies. Prev Med 119:24–30. https://doi.org/10.1016/j.ypmed.2018.11.019
Article
PubMed
Google Scholar
Cao M, Cui B (2020) Negative effects of age at menarche on risk of cardiometabolic diseases in adulthood: a Mendelian randomization study. J Clin Endocrinol Metab 105(2):dgz071. https://doi.org/10.1210/clinem/dgz071
Article
PubMed
Google Scholar
Mohammadi-Shemirani P, Chong M, Pigeyre M, Morton RW, Gerstein HC, Pare G (2019) Clinical benefits and adverse effects of genetically-elevated free testosterone levels: a Mendelian randomization analysis. medRχiv. https://doi.org/10.1101/19005132
Wang Q, Kangas AJ, Soininen P et al (2015) Sex hormone-binding globulin associations with circulating lipids and metabolites and the risk for type 2 diabetes: observational and causal effect estimates. Int J Epidemiol 44(2):623–637. https://doi.org/10.1093/ije/dyv093
CAS
Article
PubMed
Google Scholar
BIRTH-GENE (BIG) Study Working Group, Huang T, Wang T et al (2019) Association of birth weight with type 2 diabetes and glycemic traits: a Mendelian randomization study. JAMA Netw Open 2(9):e1910915. https://doi.org/10.1001/jamanetworkopen.2019.10915
Article
Google Scholar
Geng T, Smith CE, Li C, Huang T (2018) Childhood BMI and adult type 2 diabetes, coronary artery diseases, chronic kidney disease, and cardiometabolic traits: a Mendelian randomization analysis. Diabetes Care 41(5):1089–1096. https://doi.org/10.2337/dc17-2141
CAS
Article
PubMed
Google Scholar
Wainberg M, Mahajan A, Kundaje A et al (2019) Homogeneity in the association of body mass index with type 2 diabetes across the UK Biobank: a Mendelian randomization study. PLoS Med 16(12):e1002982. https://doi.org/10.1371/journal.pmed.1002982
Article
PubMed
PubMed Central
Google Scholar
Karlsson T, Rask-Andersen M, Pan G et al (2019) Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease. Nat Med 25(9):1390–1395. https://doi.org/10.1038/s41591-019-0563-7
CAS
Article
PubMed
Google Scholar
Guo Y, Chung W, Zhu Z et al (2019) Genome-wide assessment for resting heart rate and shared genetics with cardiometabolic traits and type 2 diabetes. J Am Coll Cardiol 74(17):2162–2174. https://doi.org/10.1016/j.jacc.2019.08.1055
CAS
Article
PubMed
Google Scholar
Yuan S, Larsson SC (2020) Association of genetic variants related to plasma fatty acids with type 2 diabetes mellitus and glycaemic traits: a Mendelian randomisation study. Diabetologia 63(1):116–123. https://doi.org/10.1007/s00125-019-05019-0
CAS
Article
PubMed
Google Scholar
Yuan S, Jiang X, Michaëlsson K, Larsson SC (2019) Genetic prediction of serum 25-hydroxyvitamin d, calcium, and parathyroid hormone levels in relation to development of type 2 diabetes: a Mendelian randomization study. Diabetes Care 42(12):2197–2203. https://doi.org/10.2337/dc19-1247
CAS
Article
PubMed
Google Scholar
Yeung CHC, Au Yeung SL, Fong SSM, Schooling CM (2019) Lean mass, grip strength and risk of type 2 diabetes: a bi-directional Mendelian randomisation study. Diabetologia 62(5):789–799. https://doi.org/10.1007/s00125-019-4826-0
Article
PubMed
Google Scholar