Saeedi P, Petersohn I, Salpea P et al (2019) Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the international diabetes federation diabetes atlas, 9(th) edition. Diabetes Res Clin Pract 157:107843. https://doi.org/10.1016/j.diabres.2019.107843
Almgren P, Lehtovirta M, Isomaa B et al (2011) Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia study. Diabetologia 54(11):2811–2819. https://doi.org/10.1007/s00125-011-2267-5
CAS Article PubMed Google Scholar
Willemsen G, Ward KJ, Bell CG et al (2015) The concordance and heritability of type 2 diabetes in 34,166 twin pairs from international twin registers: the discordant twin (DISCOTWIN) consortium. Twin Res Hum Genet 18(6):762–771. https://doi.org/10.1017/thg.2015.83
Ahlqvist E, Storm P, Käräjämäki A et al (2018) Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 6(5):361–369. https://doi.org/10.1016/s2213-8587(18)30051-2
Li L, Cheng WY, Glicksberg BS et al (2015) Identification of type 2 diabetes subgroups through topological analysis of patient similarity. Sci Transl Med 7(311):311ra174. https://doi.org/10.1126/scitranslmed.aaa9364
CAS Article PubMed PubMed Central Google Scholar
Wagner R, Heni M, Tabák AG et al (2021) Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes. Nat Med 27(1):49–57. https://doi.org/10.1038/s41591-020-1116-9
CAS Article PubMed 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
Vujkovic M, Keaton JM, Lynch JA et al (2020) Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat Genet 52(7):680–691. https://doi.org/10.1038/s41588-020-0637-y
CAS Article PubMed PubMed Central Google Scholar
Chen J, Spracklen CN, Marenne G et al (2021) The trans-ancestral genomic architecture of glycemic traits. Nat Genet 53:840–860. https://doi.org/10.1038/s41588-021-00852-9
CAS Article PubMed PubMed Central Google Scholar
Yang J, Bakshi A, Zhu Z et al (2015) Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat Genet 47(10):1114–1120. https://doi.org/10.1038/ng.3390
CAS Article PubMed PubMed Central Google Scholar
Udler MS, Kim J, von Grotthuss M et al (2018) Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis. PLoS Med 15(9):e1002654. https://doi.org/10.1371/journal.pmed.1002654
CAS Article PubMed PubMed Central Google Scholar
Schnurr TM, Stallknecht BM, Sørensen TIA, Kilpeläinen TO, Hansen T (2021) Evidence for shared genetics between physical activity, sedentary behaviour and adiposity-related traits. Obes Rev 22(4):e13182. https://doi.org/10.1111/obr.13182
Hasselbalch AL, Heitmann BL, Kyvik KO, Sørensen TI (2008) Studies of twins indicate that genetics influence dietary intake. J Nutr 138(12):2406–2412. https://doi.org/10.3945/jn.108.087668
CAS Article PubMed Google Scholar
Keskitalo K, Silventoinen K, Tuorila H et al (2008) Genetic and environmental contributions to food use patterns of young adult twins. Physiol Behav 93(1–2):235–242. https://doi.org/10.1016/j.physbeh.2007.08.025
CAS Article PubMed Google Scholar
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
Uusitupa M, Khan TA, Viguiliouk E et al (2019) Prevention of type 2 diabetes by lifestyle changes: a systematic review and Meta-analysis. Nutrients 11(11):2611. https://doi.org/10.3390/nu11112611
CAS Article PubMed Central Google Scholar
Berry SE, Valdes AM, Drew DA et al (2020) Human postprandial responses to food and potential for precision nutrition. Nat Med 26(6):964–973. https://doi.org/10.1038/s41591-020-0934-0
CAS Article PubMed PubMed Central Google Scholar
Muralidharan J, Moreno-Indias I, Bulló M et al (2021) Effect on gut microbiota of a 1-y lifestyle intervention with Mediterranean diet compared with energy-reduced Mediterranean diet and physical activity promotion: PREDIMED-plus study. Am J Clin Nutr 114(3):1148–1158. https://doi.org/10.1093/ajcn/nqab150
Article PubMed PubMed Central Google Scholar
Wu H, Tremaroli V, Schmidt C et al (2020) The gut microbiota in prediabetes and diabetes: a population-based cross-sectional study. Cell Metab 32(3):379–390.e373. https://doi.org/10.1016/j.cmet.2020.06.011
CAS Article PubMed Google Scholar
Blau N, van Spronsen FJ, Levy HL (2010) Phenylketonuria. Lancet 376(9750):1417–1427. https://doi.org/10.1016/s0140-6736(10)60961-0
CAS Article PubMed Google Scholar
Riddle MC, Philipson LH, Rich SS et al (2020) Monogenic diabetes: from genetic insights to population-based precision in care. Reflections from a diabetes care Editors' expert forum. Diabetes Care 43(12):3117–3128. https://doi.org/10.2337/dci20-0065
Article PubMed PubMed Central Google Scholar
Kilpeläinen TO (2013) Common sources of Bias in gene–lifestyle interaction studies of Cardiometabolic disease. Curr Nutr Rep 2(4):251–257. https://doi.org/10.1007/s13668-013-0056-0
Wong MY, Day NE, Luan JA, Chan KP, Wareham NJ (2003) The detection of gene-environment interaction for continuous traits: should we deal with measurement error by bigger studies or better measurement? Int J Epidemiol 32(1):51–57. https://doi.org/10.1093/ije/dyg002
CAS Article PubMed Google Scholar
Franks PW, Pomares-Millan H (2020) Next-generation epidemiology: the role of high-resolution molecular phenotyping in diabetes research. Diabetologia 63(12):2521–2532. https://doi.org/10.1007/s00125-020-05246-w
Article PubMed PubMed Central Google Scholar
Knowler WC, Pettitt DJ, Saad MF, Bennett PH (1990) Diabetes mellitus in the Pima Indians: incidence, risk factors and pathogenesis. Diabetes Metab Rev 6(1):1–27. https://doi.org/10.1002/dmr.5610060101
CAS Article PubMed Google Scholar
Hanson RL, Elston RC, Pettitt DJ, Bennett PH, Knowler WC (1995) Segregation analysis of non-insulin-dependent diabetes mellitus in Pima Indians: evidence for a major-gene effect. Am J Hum Genet 57(1):160–170
CAS PubMed PubMed Central Google Scholar
Schulz LO, Bennett PH, Ravussin E et al (2006) Effects of traditional and western environments on prevalence of type 2 diabetes in Pima Indians in Mexico and the U.S. Diabetes Care 29(8):1866–1871. https://doi.org/10.2337/dc06-0138
Walter S, Mejía-Guevara I, Estrada K, Liu SY, Glymour MM (2016) Association of a Genetic Risk Score with Body Mass Index across Different Birth Cohorts. Jama 316(1):63–69. https://doi.org/10.1001/jama.2016.8729
CAS Article PubMed Google Scholar
Schrempft S, van Jaarsveld CHM, Fisher A et al (2018) Variation in the heritability of child body mass index by obesogenic home environment. JAMA Pediatr 172(12):1153–1160. https://doi.org/10.1001/jamapediatrics.2018.1508
Article PubMed PubMed Central Google Scholar
McCaffery JM, Papandonatos GD, Bond DS, Lyons MJ, Wing RR (2009) Gene X environment interaction of vigorous exercise and body mass index among male Vietnam-era twins. Am J Clin Nutr 89(4):1011–1018. https://doi.org/10.3945/ajcn.2008.27170
CAS Article PubMed PubMed Central Google Scholar
Silventoinen K, Hasselbalch AL, Lallukka T et al (2009) Modification effects of physical activity and protein intake on heritability of body size and composition. Am J Clin Nutr 90(4):1096–1103. https://doi.org/10.3945/ajcn.2009.27689
CAS Article PubMed PubMed Central Google Scholar
Robinson MR, English G, Moser G et al (2017) Genotype-covariate interaction effects and the heritability of adult body mass index. Nat Genet 49(8):1174–1181. https://doi.org/10.1038/ng.3912
CAS Article PubMed Google Scholar
Ahmad S, Rukh G, Varga TV et al (2013) Gene × physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry. PLoS Genet 9(7):e1003607. https://doi.org/10.1371/journal.pgen.1003607
CAS Article PubMed PubMed Central Google Scholar
Rask-Andersen M, Karlsson T, Ek WE, Johansson Å (2017) Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status. PLoS Genet 13(9):e1006977. https://doi.org/10.1371/journal.pgen.1006977
CAS Article PubMed PubMed Central Google Scholar
Tyrrell J, Wood AR, Ames RM et al (2017) Gene-obesogenic environment interactions in the UK biobank study. Int J Epidemiol 46(2):559–575. https://doi.org/10.1093/ije/dyw337
留言 (0)