Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

References

• Umamaheswaran G, Praveen RG, Damodaran SE, Das AK, Adithan C. Influence of SLC22A1 rs622342 genetic polymorphism on metformin response in South Indian type 2 diabetes mellitus patients. Clin Exp Med. 2015;15(4):511–517. doi:10.1007/s10238-014-0322-5
   PubMed Web of Science ®Google Scholar
• Xiao D, Guo Y, Li X, et al. The Impacts of SLC22A1 rs594709 and SLC47A1 rs2289669 Polymorphisms on Metformin Therapeutic Efficacy in Chinese Type 2 Diabetes Patients. Int J Endocrinol. 2016;2016:4350712. doi:10.1155/2016/4350712
   PubMed Web of Science ®Google Scholar
• Moeez S, Khalid Z, Jalil F, et al. Effects of SLC22A2 (rs201919874) and SLC47A2 (rs138244461) genetic variants on metformin pharmacokinetics in Pakistani T2DM patients. J Pak Med Assoc. 2019;69:155–163.
   PubMedGoogle Scholar
• Song IS, Shin HJ, Shim EJ, et al. Genetic variants of the organic cation transporter 2 influence the disposition of metformin. Clin Pharmacol Ther. 2008;84(5):559–562. doi:10.1038/clpt.2008.61
   PubMed Web of Science ®Google Scholar
• Resendiz-Abarca CA, Flores-Alfaro E, Suarez-Sanchez F, et al. Altered glycemic control associated with polymorphisms in the SLC22A1 (OCT1) gene in a Mexican population with type 2 diabetes mellitus treated with metformin: a cohort study. J Clin Pharmacol. 2019;59:1384–1390. doi:10.1002/jcph.1425
   PubMed Web of Science ®Google Scholar
• Phani NM, Vohra M, Kakar A, et al. Implication of critical pharmacokinetic gene variants on therapeutic response to metformin in type 2 diabetes. Pharmacogenomics. 2018;19:905–911. doi:10.2217/pgs-2018-0041
   PubMed Web of Science ®Google Scholar
• He R, Zhang D, Lu W, et al. SLC47A1 gene rs2289669 G>A variants enhance the glucose-lowering effect of metformin via delaying its excretion in Chinese type 2 diabetes patients. Diabetes Res Clin Pract. 2015;109(1):57–63. doi:10.1016/j.diabres.2015.05.003
   PubMed Web of Science ®Google Scholar
• Choi JH, Yee SW, Ramirez AH, et al. A common 5’-UTR variant in MATE2-K is associated with poor response to metformin. Clin Pharmacol Ther. 2011;90(5):674–684. doi:10.1038/clpt.2011.165
   PubMed Web of Science ®Google Scholar
• Fatehi M, Raja M, Carter C, Soliman D, Holt A, Light PE. The ATP-sensitive K(+) channel ABCC8 S1369A type 2 diabetes risk variant increases MgATPase activity. Diabetes. 2012;61(1):241–249. PMID: 22187380; PMCID: PMC3237651. doi:10.2337/db11-0371
   PubMed Web of Science ®Google Scholar
• Hansen T, Ambye L, Grarup N, et al. Genetic variability of the SUR1 promoter in relation to beta-cell function and Type II diabetes mellitus. Diabetologia. 2001;44:1330–1334. doi:10.1007/s001250100651
   PubMed Web of Science ®Google Scholar
• Pearson ER, Donnelly LA, Kimber C, et al. Variation in TCF7L2 influences therapeutic response to sulfonylureas: a GoDARTs study. Diabetes. 2007;56:2178–2182. doi:10.2337/db07-0440
   PubMed Web of Science ®Google Scholar
• Dawed AY, Donnelly L, Tavendale R, et al.CYP2C8 and SLCO1B1 Variants and Therapeutic Response to Thiazolidinediones in Patients With Type 2 Diabetes. Diabetes Care. 2016;39(11):1902–1908. PMID: 27271184. doi:10.2337/dc15-2464
   PubMed Web of Science ®Google Scholar
• Pei Q, Huang Q, Yang GP, et al. PPAR-γ2 and PTPRD gene polymorphisms influence type 2 diabetes patients’ response to pioglitazone in China. Acta Pharmacol Sin. 2013;34(2):255–261. doi:10.1038/aps.2012.144
   PubMed Web of Science ®Google Scholar
• Hart LM, Fritsche A, Nijpels G, et al.The CTRB1/2 locus affects diabetes susceptibility and treatment via the incretin pathway. Diabetes. 2013;62(9):3275–3281. PMID: 23674605; PMCID: PMC3749354. doi:10.2337/db13-0227
   PubMed Web of Science ®Google Scholar
• Zimdahl H, Ittrich C, Graefe-Mody U, et al. Influence of TCF7L2 gene variants on the therapeutic response to the dipeptidylpeptidase-4 inhibitor linagliptin. Diabetologia. 2014;57(9):1869–1875. PMID: 24906949; PMCID: PMC4119242. doi:10.1007/s00125-014-3276-y
   PubMed Web of Science ®Google Scholar
• de Luis DA, Diaz Soto G, Izaola O, et al. Evaluation of weight loss and metabolic changes in diabetic patients treated with liraglutide, effect of RS 6923761 gene variant of glucagon-like peptide 1 receptor. J Diabetes Complicat. 2015;29(4):595–598. doi:10.1016/j.jdiacomp.2015.02.010
   PubMed Web of Science ®Google Scholar
• Ferreira MC, da Silva MER, Fukui RT, et al. Effect of TCF7L2 polymorphism on pancreatic hormones after exenatide in type 2 diabetes. Diabetol Metab Syndr. 2019;11:10. PMID: 30700996; PMCID: PMC6347826. doi:10.1186/s13098-019-0401-6
   PubMed Web of Science ®Google Scholar
• hou LM, Xu W, Yan XM, Li MXY, Liang H, Weng JP. Association between SORCS1 rs1416406 and therapeutic effect of exenatide. Zhonghua Yi Xue Za Zhi. 2017;97(18):1415–1419. doi:10.3760/cma.j.issn.0376-2491.2017.18.0131
   PubMedGoogle Scholar
• Zimdahl H, Haupt A, Brendel M, et al. Influence of common polymorphisms in the SLC5A2 gene on metabolic traits in subjects at increased risk of diabetes and on response to empagliflozin treatment in patients with diabetes. Pharmacogenet Genomics. 2017;27(4):135–142. PMID: 28134748. doi:10.1097/FPC.0000000000000268
   PubMed Web of Science ®Google Scholar
• Hoeben E, De Winter W, Neyens M, et al. Population Pharmacokinetic Modeling of Canagliflozin in Healthy Volunteers and Patients with Type 2 Diabetes Mellitus. Clin Pharmacokinet. 2016;55(2):209–223. PMID: 26293616. doi:10.1007/s40262-015-0307-x
   PubMed Web of Science ®Google Scholar
• Bonnefond A, Unnikrishnan R, Doria A, et al. Monogenic diabetes. Nat Rev Dis Primers. 2023;9(1):12. doi:10.1038/s41572-023-00421-w
   PubMed Web of Science ®Google Scholar
• Shepherd M, Shields B, Hammersley S, et al. Systematic population screening, using biomarkers and genetic testing, identifies 2·5% of the UK pediatric diabetes population with monogenic diabetes. Diabetes Care. 2016;39:1879–1888. doi:10.2337/dc16-0645
   PubMed Web of Science ®Google Scholar
• Pearson ER, Flechtner I, Njølstad PR, et al.; Neonatal Diabetes International Collaborative Group. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med. 2006; 355(5):467–477. doi:10.1056/NEJMoa061759
   PubMed Web of Science ®Google Scholar
• Gloyn AL, Pearson ER, Antcliff JF, et al. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med. 2004;350(18):1838–1849. doi:10.1056/NEJMoa032922
   PubMed Web of Science ®Google Scholar
• Rafiq M, Flanagan SE, Patch AM, et al. Effective treatment with oral sulfonylureas in patients with diabetes due to sulfonylurea receptor 1 (SUR1) mutations. Diabetes Care. 2008;31(2):204–209. doi:10.2337/dc07-1785
   PubMed Web of Science ®Google Scholar
• Dennis JM. Precision Medicine in Type 2 Diabetes: using Individualized Prediction Models to Optimize Selection of Treatment. Diabetes. 2020;69(10):2075–2085. PMID: 32843566; PMCID: PMC7506836. doi:10.2337/dbi20-0002
   PubMed Web of Science ®Google Scholar
• Gloyn AL, Drucker DJ. Precision medicine in the management of type 2 diabetes. Lancet Diabetes Endocrinol. 2018;6(11):891–900. PMID: 29699867. doi:10.1016/S2213-8587(18)30052-4
   PubMed Web of Science ®Google Scholar
• Morris AP, Voight BF, Teslovich TM, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44(9):981–990. doi:10.1038/ng.2383
   PubMed Web of Science ®Google Scholar
• Sladek R, Rocheleau G, Rung J, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007;445(7130):881–885. doi:10.1038/nature05616
   PubMed Web of Science ®Google Scholar
• Saxena R, Voight BF, et al.; Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, and Novartis Institutes of BioMedical Research. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316(5829):1331–1336. doi:10.1126/science.1142358
   PubMed Web of Science ®Google Scholar
• Scott LJ, Mohlke KL, Bonnycastle LL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316(5829):1341–1345. doi:10.1126/science.1142382
   PubMed Web of Science ®Google Scholar
• Steinthorsdottir V, Thorleifsson G, Reynisdottir I, et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007;39(6):770–775. doi:10.1038/ng2043
   PubMed Web of Science ®Google Scholar
• Zeggini E, Weedon MN, Lindgren CM, et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316(5829):1336–1341. doi:10.1126/science.1142364
   PubMed Web of Science ®Google Scholar
• Chen J, Spracklen CN, Marenne G, et al. The trans-ancestral genomic architecture of glycemic traits. Nat Genet. 2021;53(6):840–860. doi:10.1038/s41588-021-00852-9
   PubMed Web of Science ®Google Scholar
• Scott RA, Scott LJ, Mägi R, et al. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. Diabetes. 2017;66(11):2888–2902. doi:10.2337/db16-1253
   PubMed Web of Science ®Google Scholar
• Laakso M, Fernandes Silva L. Genetics of Type 2 Diabetes: past, Present, and Future. Nutrients. 2022;14(15):3201. doi:10.3390/nu14153201
   PubMed Web of Science ®Google Scholar
• Baca P, Barajas-Olmos F, Mirzaeicheshmeh E, et al. DNA methylation and gene expression analysis in adipose tissue to identify new loci associated with T2D development in obesity. Nutr Diabetes. 2022;12(1):50. PMID: 36535927; PMCID: PMC9763387. doi:10.1038/s41387-022-00228-w
   PubMed Web of Science ®Google Scholar
• Domingo-Relloso A, Gribble MO, Riffo-Campos AL, et al. Epigenetics of type 2 diabetes and diabetes-related outcomes in the Strong Heart Study. Clin Epigenetics. 2022;14(1):177. PMID: 36529747; PMCID: PMC9759920. doi:10.1186/s13148-022-01392-7
   PubMed Web of Science ®Google Scholar
• Eftekharian MM, Sayad A, Omrani MD, et al. Single nucleotide polymorphisms in the FOXP3 gene are associated with increased risk of relapsing-remitting multiple sclerosis. Hum Antibodies. 2016;24(3–4):85–90. doi:10.3233/HAB-160299
   PubMedGoogle Scholar
• Khalifa O, Pers YM, Ferreira R, et al. X-Linked miRNAs Associated with Gender Differences in Rheumatoid Arthritis. Int J Mol Sci. 2016;17(11):1852. doi:10.3390/ijms17111852
   PubMed Web of Science ®Google Scholar
• Wang X, Liu Z, Zhang S, et al. Forkhead box P3 gene polymorphisms predispose to type 2 diabetes and diabetic nephropathy in the Han Chinese populations: a genetic-association and gender-based evaluation study. Hereditas. 2023;160(1):1–2. doi:10.1186/s41065-023-00264-1
   PubMed Web of Science ®Google Scholar
• Liu J, Li L, Li WJ, et al. The role of uncoupling proteins in diabetes mellitus. J Diabetes Res. 2013;2013:1–7.
   Web of Science ®Google Scholar
• Udler MS, Kim J, von Grotthuss M, et al. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis. PLoS Med. 2018;15(9):e1002654. doi:10.1371/journal.pmed.1002654
   PubMed Web of Science ®Google Scholar
• Brand MD, Parker N, Afourtit C, et al. Mitochondrial uncoupling protein 2 in pancreatic beta-cells. Diabetes Obes Metab. 2010;12:134–140. doi:10.1111/j.1463-1326.2010.01264.x
   PubMed Web of Science ®Google Scholar
• Brand MD, Esteves TC. Physiological functions of the mitochondrial uncoupling proteins UCP2 and UCP3. Cell Metab. 2005;2:85–93. doi:10.1016/j.cmet.2005.06.002
   PubMed Web of Science ®Google Scholar
• Sasahara M, Nishi M, Kawashima H, et al. Uncoupling protein 2 promoter polymorphism −866G/A affects its expression in beta-cells and modulates clinical profiles of Japanese type 2 diabetes patients. Diabetes. 2004;53(2):482–485. doi:10.2337/diabetes.53.2.482
   PubMed Web of Science ®Google Scholar
• Gluckman PD, Hanson MA, Buklijas T, Low FM, Beedle AS. Epigenetic mechanisms that underpin metabolic and cardiovascular diseases. Nat Rev Endocrinol. 2009;5(7):401–408. doi:10.1038/nrendo.2009.102
   PubMed Web of Science ®Google Scholar
• Wang S, Se YM, Liu ZQ, et al. Effect of genetic polymorphism of UCP2- 866 G/A on repaglinide response in Chinese patients with type 2 diabetes. Pharmazie. 2012;67(1):74–79.
   PubMed Web of Science ®Google Scholar
• Din I, Majid S, Rashid F, et al. Mitochondrial uncoupling protein 2 (UCP2) gene polymorphism - 866 G/A in the promoter region is associated with type 2 diabetes mellitus among Kashmiri population of Northern India. Mol Biol Rep. 2023;50(1):475–483. doi:10.1007/s11033-022-08055-z
   PubMed Web of Science ®Google Scholar
• Chen YT, Lin WD, Liao WL, Tsai YC, Liao JW, Tsai FJ. NT5C2 methylation regulatory interplay between DNMT1 and insulin receptor in type 2 diabetes [published correction appears in Sci Rep. 2021 Mar 22;11(1):6961]. Sci Rep. 2020;10(1):16087. doi:10.1038/s41598-020-71336-9
   PubMed Web of Science ®Google Scholar
• Lawlor N, George J, Bolisetty M, et al. Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes. Genome Res. 2017;27(2):208–222. doi:10.1101/gr.212720.116
   PubMed Web of Science ®Google Scholar
• Liu J, Liu S, Yu Z, et al. Uncovering the gene regulatory network of type 2 diabetes through multi-omic data integration. J Transl Med. 2022;20(1):604. doi:10.1186/s12967-022-03826-5
   PubMed Web of Science ®Google Scholar
• Clish CB. Metabolomics: an emerging but powerful tool for precision medicine. Cold Spring Harb Mol Case Stud. 2015;1(1)::a000588. doi:10.1101/mcs.a000588
   PubMedGoogle Scholar
• Wang TJ, Larson MG, Vasan RS, et al. Metabolite profiles and the risk of developing diabetes. Nat Med. 2011;17(4):448–453. PMID: 21423183; PMCID: PMC3126616. doi:10.1038/nm.2307
   PubMed Web of Science ®Google Scholar
• Wang TJ, Ngo D, Psychogios N, et al. 2-Aminoadipic acid is a biomarker for diabetes risk. J Clin Invest. 2013;123(10):4309–4317. doi:10.1172/JCI64801
   PubMed Web of Science ®Google Scholar
• Meng J, Huang F, Shi J, et al. Integrated biomarker profiling of the metabolome associated with type 2 diabetes mellitus among Tibetan in China. Diabetol Metab Syndr. 2023;15(1):146. doi:10.1186/s13098-023-01124-8
   PubMed Web of Science ®Google Scholar
• Ben Othman M, Sakamoto K. Effect of inactivated Bifidobacterium longum intake on obese diabetes model mice (TSOD). Food Res Int. 2020;129:108792. PMID: 32036897. doi:10.1016/j.foodres.2019.108792
   PubMed Web of Science ®Google Scholar
• Kwek E, Yan C, Ding H, et al. Effects of hawthorn seed oil on plasma cholesterol and gut microbiota. Nutr Metab (Lond). 2022;19(1):55. PMID: 35962418; PMCID: PMC9373405. doi:10.1186/s12986-022-00690-4
   PubMed Web of Science ®Google Scholar
• Wang H, Shen Q, Fu Y, et al. Effects on Diabetic Mice of Consuming Lipid Extracted from Foxtail Millet (Setaria italica): gut Microbiota Analysis and Serum Metabolomics. J Agric Food Chem. 2023;71(26):10075–10086. doi:10.1021/acs.jafc.3c02179
   PubMed Web of Science ®Google Scholar
• Jin Z, Hu W, Yang Y. Serum metabolomic analysis revealed potential metabolite biomarkers for diabetes mellitus with coronary heart disease. Anal Methods. 2023;15(28):3432–3438. PMID: 37434552. doi:10.1039/d3ay00778b
   PubMed Web of Science ®Google Scholar
• Shi C, Wan Y, He A, et al. Urinary metabolites associate with the presence of diabetic kidney disease in type 2 diabetes and mediate the effect of inflammation on kidney complication. Acta Diabetol. 2023;60(9):1199–1207. PMID: 37184672; PMCID: PMC10359369. doi:10.1007/s00592-023-02094-z
   PubMed Web of Science ®Google Scholar
• Fang J, Wang H, Niu T, et al. Integration of Vitreous Lipidomics and Metabolomics for Comprehensive Understanding of the Pathogenesis of Proliferative Diabetic Retinopathy. J Proteome Res. 2023;22(7):2293–2306. PMID: 37329324. doi:10.1021/acs.jproteome.3c00007
   PubMed Web of Science ®Google Scholar
• Gary-Webb TL, Suglia SF, Tehranifar P. Social epidemiology of diabetes and associated conditions. Curr Diab Rep. 2013;13(6):850–859. doi:10.1007/s11892-013-0427-3
   PubMed Web of Science ®Google Scholar
• Agardh E, Allebeck P, Hallqvist J, et al. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol. 2011;40(3):804–818. doi:10.1093/ije/dyr029
   PubMed Web of Science ®Google Scholar
• NDC Risk Factor Collaboration. Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet. 2016;387:1513–1530. doi:10.1016/S0140-6736(16)00618-8
   PubMed Web of Science ®Google Scholar
• Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet. 2017;389(10085):2239–2251. doi:10.1016/S0140-6736(17)30058-2
   PubMed Web of Science ®Google Scholar
• Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766–781. doi:10.1016/S0140-6736(14)60460-8
   PubMed Web of Science ®Google Scholar
• Ma RC, Chan JC. Type 2 diabetes in East Asians: similarities and differences with populations in Europe and the United States. Ann N Y Acad Sci. 2013;1281::64–91. doi:10.1111/nyas.12098
   PubMed Web of Science ®Google Scholar
• Unnikrishnan R, Anjana RM, Mohan V. Diabetes in South Asians: is the phenotype different? Diabetes. 2014;63:53–55. doi:10.2337/db13-1592
   PubMed Web of Science ®Google Scholar
• Ding C, Chan Z, Magkos F. Lean, but not healthy: the ‘metabolically obese, normal-weight’ phenotype. Curr Opin Clin Nutr Metab Care. 2016;19:408–417. doi:10.1097/MCO.0000000000000317
   PubMed Web of Science ®Google Scholar
• Wang DD, Hu FB. Precision nutrition for prevention and management of type 2 diabetes. Lancet Diabetes Endocrinol. 2018;6(5):416–426. doi:10.1016/S2213-8587(18)30037-8
   PubMed Web of Science ®Google Scholar
• Visseren FLJ, Mach F, Smulders YM, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur J Prev Cardiol. 2022;29(1):5–115. doi:10.1093/eurjpc/zwab154
   PubMed Web of Science ®Google Scholar
• Willett W, Rockström J, Loken B, et al. Food in the Anthropocene: the EAT-Lancet Commission on healthy diets from sustainable food systems [published correction appears in Lancet. 2019 Feb 9;393(10171):530] [published correction appears in Lancet. 2019 Jun 29;393(10191):2590] [published correction appears in Lancet. 2020 Feb 1;395(10221):338] [published correction appears in Lancet. 2020 Oct 3;396(10256):e56]. Lancet. 2019;393(10170):447–492. doi:10.1016/S0140-6736(18)31788-4
   PubMed Web of Science ®Google Scholar
• Ma Y, He FJ, Yin Y, et al. Gradual reduction of sugar in soft drinks without substitution as a strategy to reduce overweight, obesity, and type 2 diabetes: a modelling study. Lancet Diabetes Endocrinol. 2016;4(2):105–114. doi:10.1016/S2213-8587(15)00477-5
   PubMed Web of Science ®Google Scholar
• Kolb H, Martin S. Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes. BMC Med. 2017;15(1):131. doi:10.1186/s12916-017-0901-x
   PubMed Web of Science ®Google Scholar
• Dendup T, Feng X, Clingan S, Astell-Burt T. Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: a Systematic Review. Int. J Environ Res Public Health. 2018;15(1):78. doi:10.3390/ijerph15010078
   Google Scholar
• Jannasch F, Kröger J, Schulze MB. Dietary Patterns and Type 2 Diabetes: a Systematic Literature Review and Meta-Analysis of Prospective Studies. J Nutr. 2017;147(6):1174–1182. doi:10.3945/jn.116.242552
   PubMed Web of Science ®Google Scholar
• Yanai H, Hamasaki H, Katsuyama H, Adachi H, Moriyama S, Sako A. Effects of intake of fish or fish oils on the development of diabetes. J Clin Med Res. 2015;7(1):8–12. PMID: 25368695; PMCID: PMC4217746. doi:10.14740/jocmr1964w
   PubMedGoogle Scholar
• Shin JY, Xun P, Nakamura Y, He K. Egg consumption in relation to risk of cardiovascular disease and diabetes: a systematic review and meta-analysis. Am. J Clin Nutr. 2013;98(1):146–159. doi:10.3945/ajcn.112.051318
   Google Scholar
• Satija A, Bhupathiraju SN, Rimm EB, et al. Plant-Based Dietary Patterns and Incidence of Type 2 Diabetes in US Men and Women: results from Three Prospective Cohort Studies. PLoS Med. 2016;13(6):e1002039. doi:10.1371/journal.pmed.1002039
   PubMed Web of Science ®Google Scholar
• Gardner CD, Landry MJ, Perelman D, et al. Effect of a ketogenic diet versus Mediterranean diet on glycated hemoglobin in individuals with prediabetes and type 2 diabetes mellitus: the interventional Keto-Med randomized crossover trial [published correction appears in Am J Clin Nutr. 2022 Dec 19; 116(6):1904]. Am J Clin Nutr. 2022;116(3):640–652. doi:10.1093/ajcn/nqac154
   PubMed Web of Science ®Google Scholar
• Vitale M, Masulli M, Calabrese I, et al. Impact of a Mediterranean Dietary Pattern and Its Components on Cardiovascular Risk Factors, Glucose Control, and Body Weight in People with Type 2 Diabetes: a Real-Life Study. Nutrients. 2018;10(8):1067. doi:10.3390/nu10081067
   PubMed Web of Science ®Google Scholar
• Alonso-Domínguez R, García-Ortiz L, Patino-Alonso MC, Sánchez-Aguadero N, Gómez-Marcos MA, Recio-Rodríguez JI. Effectiveness of A Multifactorial Intervention in Increasing Adherence to the Mediterranean Diet among Patients with Diabetes Mellitus Type 2: a Controlled and Randomized Study (EMID Study). Nutrients. 2019;11(1):162. doi:10.3390/nu11010162
   PubMed Web of Science ®Google Scholar
• Wilder RMA. The effects of ketonemia on the course of epilepsy. Mayo Clin Bull. 1921;2:307.
   Google Scholar
• Wilson J, Lowery R. The Ketogenic Bible. Las Vegas, NV, USA: Victory Belt Publishing Inc.; 2017. ISBN 13:978-1-628601-04-6.
   Google Scholar
• Rafiullah M, Musambil M, David SK. Effect of a very low-carbohydrate ketogenic diet vs recommended diets in patients with type 2 diabetes: a meta-analysis. Nutr Rev. 2022;80:488–502. doi:10.1093/nutrit/nuab040
   PubMed Web of Science ®Google Scholar
• Li S, Lin G, Chen J, et al. The effect of periodic ketogenic diet on newly diagnosed overweight or obese patients with type 2 diabetes. BMC Endocr Disord. 2022;22:34. CrossRef. doi:10.1186/s12902-022-00947-2
   PubMed Web of Science ®Google Scholar
• Gardner CD, Landry MJ, Perelman D, et al. Effect of a ketogenic diet versus Mediterranean diet on glycated hemoglobin in individuals with prediabetes and type 2 diabetes mellitus: the interventional Keto-Med randomized crossover trial. Am J Clin Nutr. 2022;116:640–652. Erratum in Am. J. Clin. Nutr. 2022 Nov. 09. [CrossRef]. doi:10.1093/ajcn/nqac154
   PubMed Web of Science ®Google Scholar
• Saslow LR, Kim S, Daubenmier JJ, et al. A randomized pilot trial of a moderate carbohydrate diet compared to a very low carbohydrate diet in overweight or obese individuals with type 2 diabetes mellitus or prediabetes. PLoS One. 2014;9:e91027. doi:10.1371/journal.pone.0091027
   PubMed Web of Science ®Google Scholar
• Saslow LR, Daubenmier JJ, Moskowitz JT, et al. Twelve-month outcomes of a randomized trial of a moderate-carbohydrate versus very low-carbohydrate diet in overweight adults with type 2 diabetes mellitus or prediabetes. Nutr Diabetes. 2017;7:304. doi:10.1038/s41387-017-0006-9
   PubMed Web of Science ®Google Scholar
• Landry MJ, Crimarco A, Perelman D, et al. Adherence to Ketogenic and Mediterranean Study Diets in a Crossover Trial: the Keto-Med Randomized Trial. Nutrients.2021;13:967. doi:10.3390/nu13030967
   PubMed Web of Science ®Google Scholar
• Dyńka D, Kowalcze K, Ambrozkiewicz F, Paziewska A. Effect of the Ketogenic Diet on the Prophylaxis and Treatment of Diabetes Mellitus: a Review of the Meta-Analyses and Clinical Trials. Nutrients. 2023;15(3):500. PMID: 36771207; PMCID: PMC9919384. doi:10.3390/nu15030500
   PubMed Web of Science ®Google Scholar
• Sharma SK, Mudgal SK, Kalra S, Gaur R, Thakur K, Agarwal R. Effect of Intermittent Fasting on Glycaemic Control in Patients With Type 2 Diabetes Mellitus: a Systematic Review and Meta-analysis of Randomized Controlled Trials. REV Endocrinol. 2023;19(1):25–32. PMID: 37313231; PMCID: PMC10258621. doi:10.17925/EE.2023.19.1.25
   Google Scholar
• Yang X, Zhou J, Shao H, et al. Effect of an Intermittent Calorie-restricted Diet on Type 2 Diabetes Remission: a Randomized Controlled Trial. J Clin Endocrinol Metab. 2023;108(6):1415–1424. PMID: 36515429. doi:10.1210/clinem/dgac661
   PubMed Web of Science ®Google Scholar
• Cienfuegos S, Gabel K, Kalam F, et al. Effects of 4- and 6-h time-restricted feeding on weight and cardiometabolic health: a randomized controlled trial in adults with obesity. Cell Metab. 2020;32:366–78.e3. doi:10.1016/j.cmet.2020.06.018
   PubMed Web of Science ®Google Scholar
• Carter S, Clifton PM, Keogh JB. Effect of intermittent compared with continuous energy restricted diet on glycemic control in patients with type 2 diabetes: a randomized noninferiority trial. JAMA Netw Open. 2018;1:e180756.
   PubMed Web of Science ®Google Scholar
• Carter S, Clifton PM, Keogh JB. The effects of intermittent compared to continuous energy restriction on glycaemic control in type 2 diabetes; a pragmatic pilot trial. Diabetes Res Clin Pract. 2016;122:106–112. doi:10.1016/j.diabres.2016.10.010
   PubMed Web of Science ®Google Scholar
• Khalfallah M, Elnagar B, Soliman SS, Eissa A, Allaithy A. The Value of Intermittent Fasting and Low Carbohydrate Diet in Prediabetic Patients for the Prevention of Cardiovascular Diseases. Arq Bras Cardiol. 2023. 120(4):e20220606. English, Portuguese. PMID: 37042857. doi:10.36660/abc.20220606
   PubMed Web of Science ®Google Scholar
• Ibrahim M, Barker MM, Ahmad E, et al. Optimizing Ramadan fasting: a randomised controlled trial for people with type 2 diabetes during Ramadan applying the principles of the ADA/EASD consensus. Diabetes Metab Res Rev. 2023;39(3):e3604. PMID: 36547366. doi:10.1002/dmrr.3604
   PubMed Web of Science ®Google Scholar
• Elmajnoun HK, Faris ME, Abdelrahim DN, Haris PI, Abu-Median AB. Effects of Ramadan Fasting on Glycaemic Control Among Patients with Type 2 Diabetes: systematic Review and Meta-analysis of Observational Studies. Diabetes Ther. 2023;14(3):479–496. PMID: 36725794; PMCID: PMC9981835. doi:10.1007/s13300-022-01363-4
   PubMed Web of Science ®Google Scholar
• Franzago M, Santurbano D, Vitacolonna E, Stuppia L. Genes and Diet in the Prevention of Chronic Diseases in Future Generations. Int. J Mol Sci. 2020;21(7):2633. doi:10.3390/ijms21072633
   Google Scholar
• Ortega-Azorín C, Sorlí JV, Asensio EM, et al. Associations of the FTO rs9939609 and the MC4R rs17782313 polymorphisms with type 2 diabetes are modulated by diet, being higher when adherence to the Mediterranean diet pattern is low. Cardiovasc Diabetol. 2012;11(137). doi:10.1186/1475-2840-11-137
   PubMedGoogle Scholar
• Fisher E, Boeing H, Fritsche A, Doering F, Joost HG, Schulze MB. Whole-grain consumption and transcription factor-7-like 2 (TCF7L2) rs7903146: gene-diet interaction in modulating type 2 diabetes risk. Br. J Nutr. 2009;101(4):478–481. doi:10.1017/S0007114508020369
   Web of Science ®Google Scholar
• Bordoni L, Gabbianelli R. Primers on nutrigenetics and nutri(epi)genomics: origins and development of precision nutrition. Biochimie. 2019;160:156–171. doi:10.1016/j.biochi.2019.03.006
   PubMed Web of Science ®Google Scholar
• Kanaley JA, Colberg SR, Corcoran MH, et al. Exercise/Physical Activity in Individuals with Type 2 Diabetes: a Consensus Statement from the American College of Sports Medicine. Med Sci Sports Exerc. 2022;54(2):353–368. PMID: 35029593; PMCID: PMC8802999. doi:10.1249/MSS.0000000000002800
   PubMed Web of Science ®Google Scholar
• Seyedizadeh SH, Cheragh-Birjandi S, Hamedi Nia MR. The Effects of Combined Exercise Training (Resistance-Aerobic) on Serum Kinesin and Physical Function in Type 2 Diabetes Patients with Diabetic Peripheral Neuropathy (Randomized Controlled Trials). J Diabetes Res. 2020;2020(6978128):1–7. doi:10.1155/2020/6978128
   Google Scholar
• Kriska AM, Rockette-Wagner B, Edelstein SL, et al.; DPP Research Group. The Impact of Physical Activity on the Prevention of Type 2 Diabetes: evidence and Lessons Learned From the Diabetes Prevention Program, a Long-Standing Clinical Trial Incorporating Subjective and Objective Activity Measures. Diabetes Care. 2021;44(1):43–49. PMID: 33444158; PMCID: PMC7783946. doi:10.2337/dc20-1129
   PubMed Web of Science ®Google Scholar
• Balducci S, Haxhi J, Sacchetti M, et al. Italian Diabetes and Exercise Study 2 (IDES_2) Investigators. Relationships of Changes in Physical Activity and Sedentary Behavior With Changes in Physical Fitness and Cardiometabolic Risk Profile in Individuals With Type 2 Diabetes: the Italian Diabetes and Exercise Study 2 (IDES_2). Diabetes Care. 2022;45(1):213–221. PMID: 34728529. doi:10.2337/dc21-1505
   PubMed Web of Science ®Google Scholar
• Sattelmair J, Pertman J, Ding EL, et al. Dose response between physical activity and risk of coronary heart disease: a meta-analysis. Circulation. 2011;124(7):789–795. PMID: 21810663; PMCID: PMC3158733. doi:10.1161/CIRCULATIONAHA.110.010710
   PubMed Web of Science ®Google Scholar
• Barakat R, Refoyo I, Coteron J, et al. Exercise during pregnancy has a preventative effect on excessive maternal weight gain and gestational diabetes. A randomized controlled trial. Braz J Phys Ther. 2019;23(2):148–155. PMID: 30470666; PMCID: PMC6428908. doi:10.1016/j.bjpt.2018.11.005
   PubMed Web of Science ®Google Scholar
• Kluding PM, Pasnoor M, Singh R, et al. The effect of exercise on neuropathic symptoms, nerve function, and cutaneous innervation in people with diabetic peripheral neuropathy. J Diabetes Complications. 2012;26(5):424–429. PMID: 22717465; PMCID: PMC3436981. doi:10.1016/j.jdiacomp.2012.05.007
   PubMed Web of Science ®Google Scholar
• Nataraj M, Maiya AG, Nagaraju SP, Shastry BA, Shivashankara KN. Effect of exercise on renal function in diabetic nephropathy-A systematic review and meta-analysis. J Taibah Univ Med Sci. 2022;18(3):526–537. PMID: 36818178; PMCID: PMC9906014. doi:10.1016/j.jtumed.2022.11.002
   PubMed Web of Science ®Google Scholar
• Soleimani A, Soltani P, Karimi H, et al. The effect of moderate-intensity aerobic exercise on non-proliferative diabetic retinopathy in type II diabetes mellitus patients: a clinical trial. Microvasc Res. 2023;149:104556. PMID: 37269942. doi:10.1016/j.mvr.2023.104556
   PubMed Web of Science ®Google Scholar
• Merino J, Guasch-Ferré M, Li J, et al. Polygenic scores, diet quality, and type 2 diabetes risk: an observational study among 35,759 adults from 3 US cohorts. PLoS Med. 2022;19(4):e1003972. doi:10.1371/journal.pmed.1003972
   PubMed Web of Science ®Google Scholar
• Trief PM, Kalichman S, Uschner D, et al. Association of psychosocial factors with medication adherence in emerging adults with youth-onset type 2 diabetes: the iCount study. Pediatr Diabetes. 2022;23(8):1695–1706. doi:10.1111/pedi.13431
   PubMed Web of Science ®Google Scholar
• Roy T, Lloyd CE. Epidemiology of depression and diabetes: a systematic review. J Affect Disord. 2012;142 Suppl:S8–S21. doi:10.1016/S0165-0327(12)70004-6
   PubMed Web of Science ®Google Scholar
• Trief PM, Uschner D, Kalichman S, et al. Psychosocial factors predict medication adherence in young adults with youth-onset type 2 diabetes: longitudinal results from the TODAY2 I Count study. Diabet Med. 2023;40:e15062. PMID: 36751994. doi:10.1111/dme.15062
   PubMed Web of Science ®Google Scholar
• Castañeda SF, Gallo LC, Garcia ML, et al. Effectiveness of an integrated primary care intervention in improving psychosocial outcomes among Latino adults with diabetes: the LUNA-D study. Transl Behav Med. 2022;12(8):825–833. doi:10.1093/tbm/ibac042
   PubMed Web of Science ®Google Scholar
• Marmot M, Allen JJ. Social determinants of health equity. Am J Public Health. 2014;104:Suppl 4(Suppl 4):S517–9. PMID: 25100411; PMCID: PMC4151898. doi:10.2105/AJPH.2014.302200
   Web of Science ®Google Scholar
• Mezuk B, Eaton WW, Albrecht S, et al. Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes Care. 2008;31(12):2383–2390. doi:10.2337/dc08-0985
   PubMed Web of Science ®Google Scholar
• Lin EH, Von Korff M, Alonso J, et al. Mental disorders among persons with diabetes--results from the World Mental Health Surveys. J Psychosom Res. 2008;65(6):571–580. doi:10.1016/j.jpsychores.2008.06.007
   PubMed Web of Science ®Google Scholar
• Gudala K, Bansal D, Schifano F, et al. Diabetes mellitus and risk of dementia: a meta-analysis of prospective observational studies. J Diabetes Investig. 2013;4(6):640–650. doi:10.1111/jdi.12087
   PubMed Web of Science ®Google Scholar
• Cukierman T, Gerstein HC, Williamson JD. Cognitive decline and dementia in diabetes--systematic overview of prospective observational studies. Diabetologia. 2005;48(12):2460–2469. GBD 2019 Diseases and Injuries Collaborators. doi:10.1007/s00125-005-0023-4
   PubMed Web of Science ®Google Scholar
• Vos T, Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204–1222. doi:10.1016/S0140-6736(20)30925-9
   PubMed Web of Science ®Google Scholar
• Mallorquí-Bagué N, Lozano-Madrid M, Toledo E, et al. Type 2 diabetes and cognitive impairment in an older population with overweight or obesity and metabolic syndrome: baseline cross-sectional analysis of the PREDIMED-plus study. Sci Rep. 2018;8(1):16128. doi:10.1038/s41598-018-33843-8
   PubMed Web of Science ®Google Scholar
• Pelle MC, Zaffina I, Giofrè F, Pujia R, Arturi F. Potential Role of Glucagon-like Peptide-1 Receptor Agonists in the Treatment of Cognitive Decline and Dementia in Diabetes Mellitus. Int. J Mol Sci. 2023;24(14):11301. doi:10.3390/ijms241411301
   Google Scholar
• Salvatore T, Pafundi PC, Morgillo F, et al. Metformin: an old drug against old age and associated morbidities. Diabetes Res Clin Pract. 2020;160:108025. doi:10.1016/j.diabres.2020.108025
   PubMed Web of Science ®Google Scholar
• Cukierman-Yaffe T, Gerstein HC, Colhoun HM, et al. Effect of dulaglutide on cognitive impairment in type 2 diabetes: an exploratory analysis of the REWIND trial [published correction appears in Lancet Neurol. 2020 Oct;19(10):e9]. Lancet Neurol. 2020;19(7):582–590. doi:10.1016/S1474-4422(20)30173-3
   PubMed Web of Science ®Google Scholar
• Lee CH, Jeon SJ, Cho KS, et al. Activation of Glucagon-Like Peptide-1 Receptor Promotes Neuroprotection in Experimental Autoimmune Encephalomyelitis by Reducing Neuroinflammatory Responses. Mol Neurobiol. 2018;55(4):3007–3020. doi:10.1007/s12035-017-0550-2
   PubMed Web of Science ®Google Scholar
• Kremers SHM, Wild SH, Elders PJM, et al. The role of mental disorders in precision medicine for diabetes: a narrative review. Diabetologia. 2022;65(11):1895–1906. doi:10.1007/s00125-022-05738-x
   PubMed Web of Science ®Google Scholar
• Galiero R, Pafundi PC, Nevola R, et al. The Importance of Telemedicine during COVID-19 Pandemic: a Focus on Diabetic Retinopathy. J Diabetes Res. 2020;2020:1–8. doi:10.1155/2020/9036847
   Web of Science ®Google Scholar
• Sasso FC, Pafundi PC, Gelso A, et al.; NO BLIND Study Group. Telemedicine for screening diabetic retinopathy: the NO BLIND Italian multicenter study. Diabetes Metab Res Rev. 2019;35(3):e3113. PMID: 30548967. doi:10.1002/dmrr.3113
   PubMed Web of Science ®Google Scholar
• Gómez AM, Henao D, Parra D, et al. Early and sustained increase in time in range 1 year after initiation of hybrid close loop therapy via telemedicine in type 1 diabetes patients. Acta Diabetol. 2023;60(7):943–949. PMID: 37010594; PMCID: PMC10068726. doi:10.1007/s00592-023-02051-w
   PubMed Web of Science ®Google Scholar
• Díaz-Soto G, Ibáñez MS, Del Amo Simón S, et al. Metabolic control and satisfaction in a diabetes education programme in flash glucose monitoring through telemedicine in type 1 diabetes. Endocrinol Diabetes Nutr. 2023;70(6):408–414. PMID: 36456461. doi:10.1016/j.endien.2022.01.009
   Web of Science ®Google Scholar
• Longwitz A, Palokas M. Diabetes self-management education for adults with type 2 diabetes via telehealth in conjunction with remote patient monitoring: a best practice implementation project. JBI Evid Implement. 2023;21(2):156–166. PMID: 36458653. doi:10.1097/XEB.0000000000000360
   PubMedGoogle Scholar
• Zamanillo-Campos R, Fiol-deRoque MA, Serrano-Ripoll MJ, Mira-Martínez S, Ricci-Cabello I. Development and evaluation of DiabeText, a personalized mHealth intervention to support medication adherence and lifestyle change behaviour in patients with type 2 diabetes in Spain: a mixed-methods Phase II pragmatic randomized controlled clinical trial. Int J Med Inform. 2023;176:105103. PMID: 37267809. doi:10.1016/j.ijmedinf.2023.105103
   PubMed Web of Science ®Google Scholar
• van Bastelaar KM, Pouwer F, Cuijpers P, Riper H, Snoek FJ. Web-based depression treatment for type 1 and type 2 diabetic patients: a randomized, controlled trial. Diabetes Care. 2011;34(2):320–325. doi:10.2337/dc10-1248
   PubMed Web of Science ®Google Scholar
• Hill-Briggs F, Adler NE, Berkowitz SA, et al. Social Determinants of Health and Diabetes: a Scientific Review. Diabetes Care. 2020;44(1):258–279. doi:10.2337/dci20-0053
   PubMed Web of Science ®Google Scholar
• Lenzi FR, Filardi T. Social determinants of vulnerabilities in type 2 diabetes: a call to action. J Endocrinol Invest. 2023;46(4):841–844. PMID: 36318450. doi:10.1007/s40618-022-01952-x
   PubMed Web of Science ®Google Scholar
• Bijlsma-Rutte A, Rutters F, Elders PJM, et al. Socio-economic status and HbA1c in type 2 diabetes: a systematic review and meta-analysis. Diabetes Metab Res Rev. 2018;34(6):e3008. PMID: 29633475. doi:10.1002/dmrr.3008
   PubMed Web of Science ®Google Scholar
• Xu X, Yang W, Deng Y, et al. Association of socioeconomic status with glycated haemoglobin level and risk factors for diabetic retinopathy: a cross-sectional study in Sichuan, western China. BMJ Open. 2023;13(2):e067475. PMID: 36797020; PMCID: PMC9936295. doi:10.1136/bmjopen-2022-067475
   PubMed Web of Science ®Google Scholar
• Egnew TR. Suffering, meaning, and healing: challenges of contemporary medicine. Ann Fam Med. 2009;7(2):170–175. PMID: 19273873; PMCID: PMC2653974. doi:10.1370/afm.943
   PubMed Web of Science ®Google Scholar
• ElSayed NA, Aleppo G, Aroda VR, et al. Pharmacologic Approaches to Glycemic Treatment: standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S140–S157. PMID: 36507650; PMCID: PMC9810476. doi:10.2337/dc23-S009
   PubMedGoogle Scholar
• Choi JG, Winn AN, Skandari MR, et al. First-Line Therapy for Type 2 Diabetes With Sodium-Glucose Cotransporter-2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists: a Cost-Effectiveness Study. Ann Intern Med. 2022;175(10):1392–1400. PMID: 36191315; PMCID: PMC10155215. doi:10.7326/M21-2941
   PubMed Web of Science ®Google Scholar
• Zhou K, Pedersen HK, Dawed AY, Pearson ER. Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery. Nat Rev Endocrinol. 2016;12(6):337–346. doi:10.1038/nrendo.2016.51
   PubMed Web of Science ®Google Scholar
• Tsapas A, Karagiannis T, Kakotrichi P, et al. Comparative efficacy of glucose-lowering medications on body weight and blood pressure in patients with type 2 diabetes: a systematic review and network meta-analysis. Diabetes Obes Metab. 2021;23(9):2116–2124. doi:10.1111/dom.14451
   PubMed Web of Science ®Google Scholar
• Caturano A, Galiero R, Pafundi PC. Metformin for Type 2 Diabetes. JAMA. 2019;322(13):1312. PMID: 31573630. doi:10.1001/jama.2019.11489
   PubMedGoogle Scholar
• Zhou K, Donnelly L, Yang J, et al.; Wellcome Trust Case Control Consortium 2; Spencer CC, Groop L, Morris AD, Colhoun HM, Sham PC, McCarthy MI, Palmer CN, Pearson ER. Heritability of variation in glycaemic response to metformin: a genome-wide complex trait analysis. Lancet Diabetes Endocrinol. 2014;2(6):481–487. doi:10.1016/S2213-8587(14)70050-6
   PubMed Web of Science ®Google Scholar
• Wang DS, Jonker JW, Kato Y, Kusuhara H, Schinkel AH, Sugiyama Y. Involvement of organic cation transporter 1 in hepatic and intestinal distribution of metformin. J Pharmacol Exp Ther. 2002;302(2):510–515. doi:10.1124/jpet.102.034140
   PubMed Web of Science ®Google Scholar
• Kimura N, Masuda S, Tanihara Y, et al. Metformin is a superior substrate for renal organic cation transporter OCT2 rather than hepatic OCT1. Drug Metab Pharmacokinet. 2005;20(5):379–386. doi:10.2133/dmpk.20.379
   PubMedGoogle Scholar
• Singh S, Usman K, Banerjee M. Pharmacogenetic studies update in type 2 diabetes mellitus. World J Diabetes. 2016;7(15):5. doi:10.4239/wjd.v7.i15.302
   Google Scholar
• Hou W, Zhang D, Lu W, et al. Polymorphism of organic cation transporter 2 improves glucose-lowering effect of metformin via influencing its pharmacokinetics in Chinese type 2 diabetic patients. Mol Diagn Ther. 2015;19(1):25–33. doi:10.1007/s40291-014-0126-z
   PubMed Web of Science ®Google Scholar
• Tkáč I, Klimčáková L, Javorský M, et al. Pharmacogenomic association between a variant in SLC47A1 gene and therapeutic response to metformin in type 2 diabetes. Diabetes Obes Metab. 2013;15:189–191. doi:10.1111/j.1463-1326.2012.01691.x
   PubMed Web of Science ®Google Scholar
• Florez JC. Pharmacogenetics in type 2 diabetes: precision medicine or discovery tool? Diabetologia. 2017;60(5):800–807. PMID: 28283684. doi:10.1007/s00125-017-4227-1
   PubMed Web of Science ®Google Scholar
• Dennis JM, Henley WE, Weedon MN, et al. MASTERMIND Consortium. Sex and BMI Alter the Benefits and Risks of Sulfonylureas and Thiazolidinediones in Type 2 Diabetes: a Framework for Evaluating Stratification Using Routine Clinical and Individual Trial Data. Diabetes Care. 2018;41(9):1844–1853. PMID: 30072404; PMCID: PMC6591127. doi:10.2337/dc18-0344
   PubMed Web of Science ®Google Scholar
• Vetrano E, Rinaldi L, Mormone A, et al. Non-alcoholic Fatty Liver Disease (NAFLD), Type 2 Diabetes, and Non-viral Hepatocarcinoma: pathophysiological Mechanisms and New Therapeutic Strategies. Biomedicines. 2023;11(2):468. PMID: 36831004; PMCID: PMC9953066. doi:10.3390/biomedicines11020468
   PubMed Web of Science ®Google Scholar
• Lyssenko V, Bianchi C, Del Prato S. Personalized therapy by phenotype and genotype. Diabetes Care. 2016;39(suppl 2):s127–36. doi:10.2337/dcS15-3002
   PubMedGoogle Scholar
• Hamming KS, Soliman D, Matemisz LC, et al. Coexpression of the type 2 diabetes susceptibility gene variants KCNJ11 E23K and ABCC8 S1369A alter the ATP and sulfonylurea sensitivities of the ATP-sensitive K(+) channel. Diabetes. 2009;58(10):2419–2424. PMID: 19587354; PMCID: PMC2750221. doi:10.2337/db09-0143
   PubMed Web of Science ®Google Scholar
• Hanefeld M, Cagatay M, Petrowitsch T, et al. Acarbose reduces the risk for myocardial infarction in Type 2 diabetic patients: meta-analysis of seven long-term studies. Eur Heart J. 2004;25(1):10–16. doi:10.1016/S0195-668X(03)00468-8
   PubMed Web of Science ®Google Scholar
• Wei Y, Xu W. Effect of acarbose on cardiovascular events and new-onset diabetes in patients with coronary heart disease and impaired glucose tolerance. Future Cardiol. 2019;15(2):127–133. PMID: 30793928. doi:10.2217/fca-2018-0062
   PubMed Web of Science ®Google Scholar
• Holman RR, Coleman RL, Chan JCN, et al. Effects of acarbose on cardiovascular and diabetes outcomes in patients with coronary heart disease and impaired glucose tolerance (ACE): a randomised, double-blind, placebo-controlled trial. Lancet Diabetes Endocrinol. 2017;5(11):877–886. doi:10.1016/S2213-8587(17)30309-1
   PubMed Web of Science ®Google Scholar
• Maruthur NM, Gribble MO, Bennett WL, et al. The pharmacogenetics of type 2 diabetes: a systematic review. Diabetes Care. 2014;37:876–886. doi:10.2337/dc13-1276
   PubMed Web of Science ®Google Scholar
• Dennis JM, Shields BM, Hill AV, et al. MASTERMIND Consortium. Precision Medicine in Type 2 Diabetes: clinical Markers of Insulin Resistance Are Associated With Altered Short- and Long-term Glycemic Response to DPP-4 Inhibitor Therapy. Diabetes Care. 2018;41(4):705–712. PMID: 29386249; PMCID: PMC6591121. doi:10.2337/dc17-1827
   PubMed Web of Science ®Google Scholar
• Jones AG, McDonald TJ, Shields BM, et al. Markers of β-Cell Failure Predict Poor Glycemic Response to GLP-1 Receptor Agonist Therapy in Type 2 Diabetes. Diabetes Care. 2016;39(2):250–257. PMID: 26242184; PMCID: PMC4894547. doi:10.2337/dc15-0258
   PubMed Web of Science ®Google Scholar
• Bihan H, Ng WL, Magliano DJ, Shaw JE. Predictors of efficacy of GLP-1 agonists and DPP-4 inhibitors: a systematic review. Diabetes Res Clin Pract. 2016;121:27–34. PMID: 27622682. doi:10.1016/j.diabres.2016.08.011
   PubMed Web of Science ®Google Scholar
• Davis TME, Mulder H, Lokhnygina Y, et al. Effect of race on the glycaemic response to sitagliptin: insights from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS). Diabetes Obes Metab. 2018;20(6):1427–1434. PMID: 29405540. doi:10.1111/dom.13242
   PubMed Web of Science ®Google Scholar
• Palmer SC, Tendal B, Mustafa RA, et al. Sodium-glucose cotransporter protein-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists for type 2 diabetes: systematic review and network meta-analysis of randomised controlled trials. BMJ. 2021;372:m 4573. doi:10.1136/bmj.m4573
   Google Scholar
• Rathmann W, Bongaerts B. Pharmacogenetics of novel glucose-lowering drugs. Diabetologia. 2021;64(6):1201–1212. PMID: 33594477; PMCID: PMC8099830. doi:10.1007/s00125-021-05402-w
   PubMed Web of Science ®Google Scholar
• Yu M, Wang K, Liu H, et al. GLP1R variant is associated with response to exenatide in overweight Chinese Type 2 diabetes patients. Pharmacogenomics. 2019;20(4):273–277. doi:10.2217/pgs-2018-0159
   PubMed Web of Science ®Google Scholar
• de Luis DA, Ovalle HF, Soto GD, et al. Role of genetic variation in the cannabinoid receptor gene (CNR1) (G1359A polymorphism) on weight loss and cardiovascular risk factors after liraglutide treatment in obese patients with diabetes mellitus type 2. J Investig Med. 2014;62(2):324–327. PMID: 24322329. doi:10.2310/JIM.0000000000000032
   PubMed Web of Science ®Google Scholar
• DeFronzo RA, Ferrannini E, Schernthaner G, et al. Slope of change in HbA1c from baseline with empagliflozin compared with sitagliptin or glimepiride in patients with type 2 diabetes. Endocrinol Diabetes Metab. 2018;1(2):e00016. PMID: 30815552; PMCID: PMC6354821. doi:10.1002/edm2.16
   PubMedGoogle Scholar
• Rosenstock J, Hansen L, Zee P, et al. Dual add-on therapy in type 2 diabetes poorly controlled with metformin monotherapy: a randomized double-blind trial of saxagliptin plus dapagliflozin addition versus single addition of saxagliptin or dapagliflozin to metformin. Diabetes Care. 2015;38(3):376–383. PMID: 25352655. doi:10.2337/dc14-1142
   PubMed Web of Science ®Google Scholar
• Dennis JM, Young KG, McGovern AP, et al. Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort study. Lancet Digit Health. 2022;4(12):e873–e883. PMID: 36427949. doi:10.1016/S2589-7500(22)00174-1
   PubMedGoogle Scholar
• Macha S, Mattheus M, Halabi A, et al. Pharmacokinetics, pharmacodynamics and safety of empagliflozin, a sodium glucose cotransporter 2 (SGLT2) inhibitor, in subjects with renal impairment. Diabetes Obes Metab. 2014;16(3):215–222. PMID: 23859488. doi:10.1111/dom.12182
   PubMed Web of Science ®Google Scholar
• Cherney DZI, Cooper ME, Tikkanen I, et al. Pooled analysis of Phase III trials indicate contrasting influences of renal function on blood pressure, body weight, and HbA1c reductions with empagliflozin. Kidney Int. 2018;93(1):231–244. PMID: 28860019. doi:10.1016/j.kint.2017.06.017
   PubMed Web of Science ®Google Scholar
• Shields BM, Dennis JM, Angwin CD, et al. TriMaster Study group. Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study. Nat Med. 2023;29(2):376–383. PMID: 36477733; PMCID: PMC7614216. doi:10.1038/s41591-022-02120-7
   PubMed Web of Science ®Google Scholar
• Salvatore T, Galiero R, Caturano A, et al. An Overview of the Cardiorenal Protective Mechanisms of SGLT2 Inhibitors. Int J Mol Sci. 2022;23(7):3651. PMID: 35409011; PMCID: PMC8998569. doi:10.3390/ijms23073651
   PubMed Web of Science ®Google Scholar
• Coelho FDS, Borges-Canha M, von Hafe M, et al. Effects of sodium-glucose co-transporter 2 inhibitors on liver parameters and steatosis: a meta-analysis of randomized clinical trials. Diabetes Metab Res Rev. 2021;37(6):e3413. PMID: 33010191. doi:10.1002/dmrr.3413
   PubMed Web of Science ®Google Scholar
• Caturano A, Galiero R, Loffredo G, et al. Effects of a Combination of Empagliflozin Plus Metformin vs. Metformin Monotherapy on NAFLD Progression in Type 2 Diabetes: the IMAGIN Pilot Study. Biomedicines. 2023;11(2):322. PMID: 36830859; PMCID: PMC9952909. doi:10.3390/biomedicines11020322
   PubMed Web of Science ®Google Scholar
• Francke S, Mamidi RN, Solanki B, et al. In vitro metabolism of canagliflozin in human liver, kidney, intestine microsomes, and recombinant uridine diphosphate glucuronosyltransferases (UGT) and the effect of genetic variability of UGT enzymes on the pharmacokinetics of canagliflozin in humans. J Clin Pharmacol. 2015;55(9):1061–1072. doi:10.1002/jcph.506
   PubMed Web of Science ®Google Scholar
• Gentile S, Turco S, Guarino G, et al. Comparative efficacy study of atorvastatin vs simvastatin, pravastatin, lovastatin and placebo in type 2 diabetic patients with hypercholesterolaemia. Diabetes Obes Metab. 2000;2(6):355–362. doi:10.1046/j.1463-1326.2000.00106.x
   PubMed Web of Science ®Google Scholar
• Rinaldi L, Nevola R, Franci G, et al. Risk of Hepatocellular Carcinoma after HCV Clearance by Direct-Acting Antivirals Treatment Predictive Factors and Role of Epigenetics. Cancers. 2020;12(6):1351. doi:10.3390/cancers12061351
   PubMed Web of Science ®Google Scholar
• Cozzolino D, Sessa G, Salvatore T, et al. The involvement of the opioid system in human obesity: a study in normal weight relatives of obese people. J Clin Endocrinol Metab. 1996;81(2):713–718. doi:10.1210/jcem.81.2.8636293
   PubMed Web of Science ®Google Scholar
• Ahlqvist E, Storm P, Käräjämäki A, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018;6(5):361–369. PMID: 29503172. doi:10.1016/S2213-8587(18)30051-2
   PubMed Web of Science ®Google Scholar
• Zaharia OP, Strassburger K, Strom A, et al.; German Diabetes Study Group. Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study. Lancet Diabetes Endocrinol. 2019;7(9):684–694. PMID: 31345776. doi:10.1016/S2213-8587(19)30187-1
   PubMed Web of Science ®Google Scholar
• Xiong XF, Yang Y, Wei L, et al. Identification of two novel subgroups in patients with diabetes mellitus and their association with clinical outcomes: a two-step cluster analysis. J Diabetes Investig. 2021;12(8):1346–1358. PMID: 33411406; PMCID: PMC8354513. doi:10.1111/jdi.13494
   PubMed Web of Science ®Google Scholar
• Pafundi PC, Garofalo C, Galiero R, et al. Role of Albuminuria in Detecting Cardio-Renal Risk and Outcome in Diabetic Subjects. Diagnostics (Basel). 2021;11(2):290. PMID: 33673215; PMCID: PMC7918197. doi:10.3390/diagnostics11020290
   PubMedGoogle Scholar
• Salvatore T, Galiero R, Caturano A, et al. Dysregulated Epicardial Adipose Tissue as a Risk Factor and Potential Therapeutic Target of Heart Failure with Preserved Ejection Fraction in Diabetes. Biomolecules. 2022;12(2):176. PMID: 35204677; PMCID: PMC8961672. doi:10.3390/biom12020176
   PubMed Web of Science ®Google Scholar
• Preechasuk L, Khaedon N, Lapinee V, et al. Cluster analysis of Thai patients with newly diagnosed type 2 diabetes mellitus to predict disease progression and treatment outcomes: a prospective cohort study. BMJ Open Diabetes Res Care. 2022;10(6):e003145. PMID: 36581330; PMCID: PMC9806077. doi:10.1136/bmjdrc-2022-003145
   PubMed Web of Science ®Google Scholar
• Naithani N, Atal AT, Tvsvgk T, Vasudevan B, Misra P, Sinha S. Precision medicine: uses and challenges. Med J Armed Forces India. 2021;77(3)::258–265. PMID: 34305277; PMCID: PMC8282516. doi:10.1016/j.mjafi.2021.06.020
   PubMedGoogle Scholar
• Griffin S. Diabetes precision medicine: plenty of potential, pitfalls and perils but not yet ready for prime time. Diabetologia. 2022;65(11):1913–1921. PMID: 35999379; PMCID: PMC9522689. doi:10.1007/s00125-022-05782-7
   PubMed Web of Science ®Google Scholar
• Gaede P, Lund-Andersen H, Parving HH, Pedersen O. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med. 2008;358(6):580–591. PMID: 18256393. doi:10.1056/NEJMoa0706245
   PubMed Web of Science ®Google Scholar
• Gaede P, Vedel P, Larsen N, et al. Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes. N Engl J Med. 2003;348(5):383–393. PMID: 12556541. doi:10.1056/NEJMoa021778
   PubMed Web of Science ®Google Scholar
• Sasso FC, Pafundi PC, Simeon V, et al.; NID-2 Study Group Investigators. Efficacy and durability of multifactorial intervention on mortality and MACEs: a randomized clinical trial in type-2 diabetic kidney disease. Cardiovasc Diabetol. 2021;20(1):145. PMID: 34271948; PMCID: PMC8285851. doi:10.1186/s12933-021-01343-1
   PubMed Web of Science ®Google Scholar
• Sasso FC, Simeon V, Galiero R, et al. NID-2 study group Investigators. The number of risk factors not at target is associated with cardiovascular risk in a type 2 diabetic population with albuminuria in primary cardiovascular prevention. Post-hoc analysis of the NID-2 trial. Cardiovasc Diabetol. 2022;21(1):235. PMID: 36344978; PMCID: PMC9641842. doi:10.1186/s12933-022-01674-7
   PubMed Web of Science ®Google Scholar
• Swen JJ, van der Wouden CH, Manson LE, et al.; Ubiquitous Pharmacogenomics Consortium. A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study. Lancet. 2023;401(10374):347–356. PMID: 36739136. doi:10.1016/S0140-6736(22)01841-4
   PubMed Web of Science ®Google Scholar
• Shah HS, Morieri ML, Marcovina SM, et al. Modulation of GLP-1 Levels by a Genetic Variant That Regulates the Cardiovascular Effects of Intensive Glycemic Control in ACCORD. Diabetes Care. 2018;41(2):348–355. PMID: 29183908; PMCID: PMC5780047. doi:10.2337/dc17-1638
   PubMed Web of Science ®Google Scholar
• Morieri ML, Shah HS, Sjaarda J, et al. PPARA Polymorphism Influences the Cardiovascular Benefit of Fenofibrate in Type 2 Diabetes: findings From ACCORD-Lipid. Diabetes. 2020;69(4):771–783. PMID: 31974142; PMCID: PMC7085251. doi:10.2337/db19-0973
   PubMed Web of Science ®Google Scholar
• Siminerio L, Krall J, Johnson P, et al. Examining a Diabetes Self-Management Education and Support Telemedicine Model With High-Risk Patients in a Rural Community. J Diabetes Sci Technol. 2023;20:19322968231180884. PMID: 37338130. doi:10.1177/19322968231180884
   Google Scholar