Insulin Aspart-szjj: An Insulin Aspart Biosimilar.

How Basal Insulin Analogs Have Changed Diabetes Care

Insulin detemir (Levemir®) is a long-acting insulin analogue indicated for use as basal insulin therapy in patients with type 1 or 2 diabetes mellitus. The protracted action of insulin detemir is explained by increased self-association and reversible binding to albumin, which slows its systemic absorption from the injection site. In glucose-clamp studies, less within-patient variability in glucose-lowering effect was seen with insulin detemir than with neutral protamine Hagedorn (NPH) insulin or insulin glargine in patients with type 1 or 2 diabetes. The beneficial effect of insulin detemir on glycaemic control was shown in numerous randomized, open-label, multicentre trials, including when used as basal-bolus therapy in patients with type 1 or 2 diabetes and as basal therapy in addition to oral antidiabetic drugs in insulin-naive patients with type 2 diabetes. In terms of glycosylated haemoglobin (HbA(1c)).[primary endpoint in most trials], insulin detemir was generally at least as effective as NPH insulin, insulin glargine or insulin lispro protamine suspension in patients with type 1 or 2 diabetes, and at least as effective as biphasic insulin aspart in patients with type 2 diabetes. Less within-patient variability in blood glucose was also generally seen with insulin detemir than with NPH insulin in patients with type 1 or 2 diabetes. Significantly less weight gain was generally seen with insulin detemir than with NPH insulin in patients with type 1 diabetes or with insulin detemir than with NPH insulin, insulin glargine, insulin lispro protamine suspension or biphasic insulin aspart (in one study) in patients with type 2 diabetes (i.e. insulin detemir generally had a weight-sparing effect). The addition of insulin detemir to liraglutide plus metformin improved glycaemic control in insulin-naive patients with type 2 diabetes and inadequate glycaemic control, although a significantly greater reduction in bodyweight was seen in patients receiving liraglutide plus metformin than in those receiving add-on therapy with insulin detemir. Results of two trials in patients aged 2-16 or 6-17 years (and a subgroup analysis in children aged 2-5 years) indicate that a basal-bolus insulin regimen incorporating insulin detemir appears to be a suitable option for use in paediatric patients with type 1 diabetes. Less within-patient variation in self-measured fasting plasma glucose was seen with insulin detemir than with NPH insulin in one of the studies. Insulin detemir was noninferior to NPH insulin in pregnant women with type 1 diabetes in terms of the HbA(1c) value achieved at 36 gestational weeks. In addition, maternal and neonatal outcomes with insulin detemir were similar to those seen with NPH insulin. Subcutaneous insulin detemir was generally well tolerated in the treatment of patients with type 1 or 2 diabetes, including in paediatric patients and pregnant women with type 1 diabetes. The majority of adverse events, including serious adverse events, reported in insulin detemir recipients were not considered to be related to the study drug. Insulin detemir was generally associated with a significantly lower risk of nocturnal hypoglycaemia than NPH insulin in patients with type 1 or 2 diabetes, particularly nocturnal minor hypoglycaemia. In conclusion, insulin detemir is a useful option for use as basal insulin therapy in patients with type 1 or 2 diabetes.

Diabetes mellitus (DM) is a group of metabolic disorders characterized by chronic hyperglycaemia, due to defects in insulin secretion, action activity or both. The prevalence of DM in Kenya is at 3.3% and is reported to be rising. Administration of drugs, healthy eating and exercises are the recommended management of the disease. Combining anti-diabetic drugs with natural remedies including honey has been reported to be more effective than use of drugs alone. However many Kenyans are sceptical about the use of honey in the management of DM on account of its high sugar. The prescription of honey for management of DM by the medical personnel is therefore viewed with cynicism. This study was therefore designed to assess the knowledge and practice of use of honey in diabetes management by the nutritionists working in hospitals. The study was cross-sectional, involving 57 practicing nutritionists drawn from different departments of public and private hospitals within Nairobi County, and the heads of the nutrition departments as key informants. Data was collected by administering a structured questionnaire to the consenting respondents. The study was granted approved by Kenyatta National Hospital (KNH)/ University of Nairobi (UoN) Ethics and Research Committee. Results showed that up to 50.9% of the respondents do not have knowledge on the use of honey in the management of DM, while 42.1% indicated having the knowledge. The gains indicated by the respondents who had knowledge included lowering glycaemic index (7%), control of blood glucose (19.3%), medicinal value (7%), and provision of energy (3.5%), alternative sweetener (1.8%) and antioxidant (1.8%). Only 19.3% of the respondents were aware of studies on use of honey in DM management. Most of the nutritionists recommend unprocessed honey (94.1%) The common forms of usage of the honey were indicated as spreads on bread (41.2%), sweetener of foods such as tea and porridge (17.6%), solution in hot water (11.8%) and direct eating (5.9%). The quantity of honey recommended one teaspoon (41.2%), two teaspoons (29.4%), three teaspoons (23.5%) and four teaspoon (5.9%). Nutritionist who did not recommend honey based their arguments on such reasoning as honey raising blood glucose (60%), lack of knowledge on efficacy (20%), ignorance (17.5%) and patient’s non-acceptance (2.5%). The study concludes that knowledge among nutritionists on the use of honey in management of type-2 DM is very low and therefore prescription/recommendation also very limited. Keywords : Nutritionist, Knowledge and Practice, use of honey, Type-2 Diabetes management DOI : 10.7176/FSQM/91-06 Publication date :October 31 st 2019

Type 1 Diabetes in Children and Adolescents.

Possible Ways to Improve Postprandial Glucose Control in Type 1 Diabetes.

Concept of Diabetes Mellitus: Diabetes mellitus is a group of diseases associated with various metabolic disorders, the main feature of which is chronic hyperglycemia due to insufficient insulin action. Its pathogenesis involves both genetic and environmental factors. The long‐term persistence of metabolic disorders can cause susceptibility to specific complications and also foster arteriosclerosis. Diabetes mellitus is associated with a broad range of clinical presentations, from being asymptomatic to ketoacidosis or coma, depending on the degree of metabolic disorder.

New Medications for the Treatment of Diabetes.

IntroductionAs per the National Diabetes Guideline, auto-antibodies should be tested for all paediatric patients at presentation, to confirm a diagnosis of Type 1 Diabetes Mellitus. It is reported that up...

In Pursuit Of Lower A1c

The incidence of type 2 diabetes (T2D) is on the rise in youth in the US1Dabelea D. Mayer-Davis E.J. Saydah S. Imperatore G. Linder B. Divers J. et al.Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009.JAMA. 2014; 311: 1778-1786Crossref PubMed Scopus (933) Google Scholar,2Mayer-Davis E.J. Dabelea D. Lawrence J.M. Incidence trends of type 1 and type 2 diabetes among youths, 2002-2012.N Engl J Med. 2017; 377: 301Crossref PubMed Scopus (7) Google Scholar and worldwide.3Pinhas-Hamiel O. Zeitler P. The global spread of type 2 diabetes mellitus in children and adolescents.J Pediatr. 2005; 146: 693-700Abstract Full Text Full Text PDF PubMed Scopus (484) Google Scholar T2D is characterized by hyperglycemia from a combination of insulin resistance and relative deficiency of insulin secretion. The contribution of insulin resistance to diabetes pathogenesis explains the clinical association of diabetes with obesity and, subsequently, the coincidence of increasing T2D prevalence with increasing prevalence and severity of obesity in children.4Skinner A.C. Ravanbakht S.N. Skelton J.A. Perrin E.M. Armstrong S.C. Prevalence of obesity and severe obesity in US children, 1999-2016.Pediatrics. 2018; 141: e20173459Crossref PubMed Scopus (783) Google Scholar Differences have been described in the natural history of youth-onset T2D and adult-onset T2D. Compared with adults, T2D in youth appears to progress more rapidly, with higher rates of metformin treatment failure and more rapid rates of beta cell decline.5Zeitler P. Hirst K. Pyle L. Linder B. Copeland K. et al.TODAY Study GroupA clinical trial to maintain glycemic control in youth with type 2 diabetes.N Engl J Med. 2012; 366: 2247-2256Crossref PubMed Scopus (597) Google Scholar, 6Bacha F. Pyle L. Nadeau K. Cuttler L. Goland R. Haymond M. et al.Determinants of glycemic control in youth with type 2 diabetes at randomization in the TODAY study.Pediatr Diabetes. 2012; 13: 376-383Crossref PubMed Scopus (33) Google Scholar, 7Narasimhan S. Weinstock R.S. Youth-onset type 2 diabetes mellitus: lessons learned from the TODAY study.Mayo Clin Proc. 2014; 89: 806-816Abstract Full Text Full Text PDF PubMed Scopus (63) Google ScholarThe presence of diabetes encumbers those affected with a long-term burden of chronic disease and an increased risk of cardiovascular and microvascular complications. This risk increases with the duration of the disease, putting children with T2D at extremely high risk for complications. Follow-up data from both the SEARCH for Diabetes in Youth study and the Treatment Options for Diabetes in Youth (TODAY) trial have found a substantial presence of diabetes complications as early as adolescence and young adulthood.8TODAY Study GroupRapid rise in hypertension and nephropathy in youth with type 2 diabetes: the TODAY clinical trial.Diabetes Care. 2013; 36: 1735-1741Crossref PubMed Scopus (188) Google Scholar, 9TODAY Study GroupLipid and inflammatory cardiovascular risk worsens over 3 years in youth with type 2 diabetes: the TODAY clinical trial.Diabetes Care. 2013; 36: 1758-1764Crossref PubMed Scopus (122) Google Scholar, 10Maahs D.M. Snively B.M. Bell R.A. Dolan L. Hirsch I. Imperatore G. et al.Higher prevalence of elevated albumin excretion in youth with type 2 than type 1 diabetes: the SEARCH for Diabetes in Youth study.Diabetes Care. 2007; 30: 2593-2598Crossref PubMed Scopus (126) Google Scholar, 11Mayer-Davis E.J. Davis C. Saadine J. D'Agostino Jr., R.B. Dabelea D. Dolan L. et al.Diabetic retinopathy in the SEARCH for Diabetes in Youth cohort: a pilot study.Diabet Med. 2012; 29: 1148-1152Crossref PubMed Scopus (55) Google Scholar Moreover, the prevalence of complications and overall mortality are higher in youth with T2D compared with adults with T2D or even youth with type 1 diabetes.12Constantino M.I. Molyneaux L. Limacher-Gisler F. Al-Saeed A. Luo C. Wu T. et al.Long-term complications and mortality in young-onset diabetes: type 2 diabetes is more hazardous and lethal than type 1 diabetes.Diabetes Care. 2013; 36: 3863-3869Crossref PubMed Scopus (268) Google Scholar,13Dabelea D. Stafford J.M. Mayer-Davis E.J. D'Agostino Jr., R. Dolan L. Imperatore G. et al.Association of type 1 diabetes vs type 2 diabetes diagnosed during childhood and adolescence with complications during teenage years and young adulthood.JAMA. 2017; 317: 825-835Crossref PubMed Scopus (2) Google Scholar This burden of disease underscores the need to improve our understanding of diabetes risk, prevention, and optimal treatment in youth.T2D is a complex, multifactorial disease influenced by both environmental factors and genetic variation as well as their interactions.14Barroso I. McCarthy M.I. The genetic basis of metabolic disease.Cell. 2019; 177: 146-161Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar,15Kolb H. Martin S. Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes.BMC Med. 2017; 15: 131Crossref PubMed Scopus (256) Google Scholar The heritability of T2D is demonstrated by both the high concordance rates in identical twins16Barnett A.H. Eff C. Leslie R.D. Pyke D.A. Diabetes in identical twins. A study of 200 pairs.Diabetologia. 1981; 20: 87-93Crossref PubMed Scopus (835) Google Scholar,17Willemsen G. Ward K.J. Bell C.G. Christensen K. Bowden J. Dalgård C. et al.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. 2015; 18: 762-771Crossref PubMed Scopus (82) Google Scholar and the typical presence of a family history of T2D in those with the disease.18Copeland K.C. Zeitler P. Geffner M. Guandalini C. Higgins J. Hirst K. et al.Characteristics of adolescents and youth with recent-onset type 2 diabetes: the TODAY cohort at baseline.J Clin Endocrinol Metab. 2011; 96: 159-167Crossref PubMed Scopus (283) Google Scholar,19Klein B.E. Klein R. Moss S.E. Cruickshanks K.J. Parental history of diabetes in a population-based study.Diabetes Care. 1996; 19: 827-830Crossref PubMed Scopus (100) Google Scholar Investigations of the genetics of diabetes risk have examined both overall T2D risk as well as individual glycemic traits that may predispose to diabetes, such as fasting glucose levels, insulin secretion, insulin resistance, and β-cell function. Understanding the genetic underpinnings of diabetes risk offers an opportunity to improve both our knowledge of the mechanisms contributing to diabetes pathogenesis and our understanding of how best to individualize diabetes treatment and prevent complications. Here we review the current state of T2D genetics, specifically as it pertains to children and adolescents.Monogenic DiabetesDiabetes as a result of a single gene abnormality, or monogenic diabetes, shares clinical overlap with T2D, particularly T2D in youth. There are 3 major subgroups of monogenic diabetes: neonatal diabetes, syndromic diabetes, and maturity-onset diabetes of the young (MODY). Neonatal diabetes presents in infancy, although only a subset of infants develops diabetes in the neonatal period (the first 30 days of life); the majority of patients become symptomatic within the first 6 months of life.20Rubio-Cabezas O. Ellard S. Diabetes mellitus in neonates and infants: genetic heterogeneity, clinical approach to diagnosis, and therapeutic options.Horm Res Paediatr. 2013; 80: 137-146Crossref PubMed Scopus (66) Google Scholar Syndromic diabetes presents with additional extrapancreatic features, typically also in infancy.20Rubio-Cabezas O. Ellard S. Diabetes mellitus in neonates and infants: genetic heterogeneity, clinical approach to diagnosis, and therapeutic options.Horm Res Paediatr. 2013; 80: 137-146Crossref PubMed Scopus (66) Google Scholar MODY is characterized by non–insulin-dependent diabetes diagnosed at a young age (<25 years) demonstrating an autosomal dominant inheritance pattern.21Tattersall R.B. Fajans S.S. A difference between the inheritance of classical juvenile-onset and maturity-onset type diabetes of young people.Diabetes. 1975; 24: 44-53Crossref PubMed Scopus (346) Google Scholar Subtypes of MODY are based on specific genetic defects, with involvement of different genes associated with differences in clinical and physiologic phenotypes.22Hattersley A.T. Maturity-onset diabetes of the young: clinical heterogeneity explained by genetic heterogeneity.Diabet Med. 1998; 15: 15-24Crossref PubMed Scopus (264) Google ScholarMonogenic diabetes can be caused by pathogenic mutations in genes that disrupt glucose sensing, insulin transcription, the potassium–adenosine triphosphate channel that transduces the signal for insulin release, the insulin gene, or pancreatic development. Understanding the genes associated with monogenic forms of diabetes has provided insight into the disease mechanisms of diabetes. Eleven different genes have been identified as causal for MODY in the Online Mendelian Inheritance in Man catalog: HNF4A (MODY 1), GCK (MODY 2), HNF1A (MODY 3), PDX1 (MODY 4), HNF1B (MODY 5), NEUROD1 (MODY 6), CEL (MODY 8), INS (MODY 10), ABCC8 (MODY 12), KCNJ11 (MODY 13), and APPL1 (MODY 14). Note that the genes previously reported as causal for MODY 7, MODY 9, and MODY 11 are absent from this list, owing to the recent proposal to eliminate them from the list of causal MODY genes based on updated genetic evidence.23Laver T.W. Wakeling M.N. Knox O. Colclough K. Wright C.F. Ellard S. et al.Evaluation of evidence for pathogenicity demonstrates that BLK, KLF11, and PAX4 should not be included in diagnostic testing for MODY.Diabetes. 2022; 71: 1128-1136Crossref PubMed Scopus (4) Google Scholar Mutations in the HNF4A and HNF1A genes lead to abnormal insulin secretion, and MODY caused by variants in these genes can be effectively managed with oral sulfonylurea therapy.24Pearson E.R. Pruhova S. Tack C.J. Johansen A. Castleden H.A. Lumb P.J. et al.Molecular genetics and phenotypic characteristics of MODY caused by hepatocyte nuclear factor 4alpha mutations in a large European collection.Diabetologia. 2005; 48: 878-885Crossref PubMed Scopus (178) Google Scholar,25Pearson E.R. Starkey B.J. Powell R.J. Gribble F.M. Clark P.M. Hattersley A.T. Genetic cause of hyperglycaemia and response to treatment in diabetes.Lancet. 2003; 362: 1275-1281Abstract Full Text Full Text PDF PubMed Scopus (461) Google Scholar MODY caused by pathogenic variants in GCK, the gene encoding glucokinase, which phosphorylates glucose to glucose-6-phosphate in pancreatic cells and acts as a glucose sensor, is characterized by a mild, stable hyperglycemia with a low risk of complications that commonly does not require any treatment.26Steele A.M. Shields B.M. Wensley K.J. Colclough K. Ellard S. Hattersley A.T. Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia.JAMA. 2014; 311: 279-286Crossref PubMed Scopus (200) Google ScholarGiven the clinical overlap between T2D and rarer forms of diabetes, a long-held hypothesis is that the genetic underpinnings of both common and rare forms of diabetes might not be entirely distinct. Multiple studies have shown that MODY affects a small but not insignificant subset of youth with diabetes, including those clinically diagnosed with T2D. The SEARCH for Diabetes in Youth Study published the first systematic study of MODY prevalence in US youth, which reported a 1.2% overall prevalence of MODY.27Pihoker C. Gilliam L.K. Ellard S. Dabelea D. Davis C. Dolan L.M. et al.Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: results from the SEARCH for Diabetes in Youth.J Clin Endocrinol Metab. 2013; 98: 4055-4062Crossref PubMed Scopus (219) Google Scholar A genetic sequencing study of participants in the TODAY study found that 4.5% carried a pathogenic variant in a MODY gene.28Kleinberger J.W. Copeland K.C. Gandica R.G. Haymond M.W. Levitsky L.L. Linder B. et al.Monogenic diabetes in overweight and obese youth diagnosed with type 2 diabetes: the TODAY clinical trial.Genet Med. 2018; 20: 583-590Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar A larger genetic study conducted by the Progress in Diabetes Genetics in Youth (ProDiGY) consortium that included the TODAY cohort, a second cohort recruited by the TODAY researchers for genetic studies, and a subset of the SEARCH for Diabetes in Youth study participants identified a 2.8% incidence of MODY.28Kleinberger J.W. Copeland K.C. Gandica R.G. Haymond M.W. Levitsky L.L. Linder B. et al.Monogenic diabetes in overweight and obese youth diagnosed with type 2 diabetes: the TODAY clinical trial.Genet Med. 2018; 20: 583-590Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar,29Todd J.N. Kleinberger J.W. Zhang H. Srinivasan S. Tollefsen S.E. Levitsky L.L. et al.Monogenic diabetes in youth with presumed type 2 diabetes: results from the Progress in Diabetes Genetics in Youth (ProDiGY) collaboration.Diabetes Care. 2021; 44: 2312-2319Crossref Scopus (10) Google Scholar These studies focused on rare, highly penetrant variants in known MODY genes. In adult studies of T2D genetics, there is increasing overlap of common variant associations and genes associated with monogenic diabetes.30Flannick J. Johansson S. Njølstad P.R. Common and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes.Nat Rev Endocrinol. 2016; 12: 394-406Crossref PubMed Scopus (78) Google Scholar Although such associations have not yet been shown in youth with T2D, it is possible that further examination of rarer variants will find associations along a spectrum of disease risk in genes or pathways relevant to diabetes.Candidate Gene StudiesMany efforts to understand the genetic underpinnings of T2D in children have focused on genetic variants with known associations with glycemic traits or T2D risk in adults, examining whether similar associations exist in youth. Individual variants have been shown to have similar associations in children for both fasting glucose31Barker A. Sharp S.J. Timpson N.J. Bouatia-Naji N. Warrington N.M. Kanoni S. et al.Association of genetic Loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children.Diabetes. 2011; 60: 1805-1812Crossref PubMed Scopus (87) Google Scholar,32Kelliny C. Ekelund U. Andersen L.B. Brage S. Loos R.J. Wareham N.J. et al.Common genetic determinants of glucose homeostasis in healthy children: the European Youth Heart Study.Diabetes. 2009; 58: 2939-2945Crossref PubMed Scopus (50) Google Scholar and the homeostasis model assessment of β cell function.31Barker A. Sharp S.J. Timpson N.J. Bouatia-Naji N. Warrington N.M. Kanoni S. et al.Association of genetic Loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children.Diabetes. 2011; 60: 1805-1812Crossref PubMed Scopus (87) Google Scholar Several T2D risk genes have been associated with youth-onset T2D, including TCF7L2,33Dabelea D. Dolan L.M. D'Agostino Jr., R. Hernandez A.M. McAteer J.B. Hamman R.F. et al.Association testing of TCF7L2 polymorphisms with type 2 diabetes in multi-ethnic youth.Diabetologia. 2011; 54: 535-539Crossref PubMed Scopus (42) Google Scholar,34Miranda-Lora A.L. Cruz M. Molina-Díaz M. Gutiérrez J. Flores-Huerta S. Klünder-Klünder M. Associations of common variants in the SLC16A11, TCF7L2, and ABCA1 genes with pediatric-onset type 2 diabetes and related glycemic traits in families: a case-control and case-parent trio study.Pediatr Diabetes. 2017; 18: 824-831Crossref PubMed Scopus (16) Google Scholar SLC16A11, and ABCA1.34Miranda-Lora A.L. Cruz M. Molina-Díaz M. Gutiérrez J. Flores-Huerta S. Klünder-Klünder M. Associations of common variants in the SLC16A11, TCF7L2, and ABCA1 genes with pediatric-onset type 2 diabetes and related glycemic traits in families: a case-control and case-parent trio study.Pediatr Diabetes. 2017; 18: 824-831Crossref PubMed Scopus (16) Google ScholarGenetic risk scores (GRSs), which allow for the assessment of the aggregate genetic risk of a given trait, have demonstrated association of GRSs constructed from variants associated in adults with glycemic traits and/or T2D risk with fasting glucose and measures of β-cell function,35Carayol J. Hosking J. Pinkney J. Marquis J. Charpagne A. Metairon S. et al.Genetic susceptibility determines β-cell function and fasting glycemia trajectories throughout childhood: a 12-year cohort study (EarlyBird 76).Diabetes Care. 2020; 43: 653-660Crossref PubMed Scopus (9) Google Scholar, 36Giannini C. Dalla Man C. Groop L. Cobelli C. Zhao H. Shaw M.M. et al.Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.Diabetes Care. 2014; 37: 475-482Crossref PubMed Scopus (29) Google Scholar, 37Morandi A. Bonnefond A. Lobbens S. Yengo L. Miraglia Del Giudice E. Grandone A. et al.Associations between type 2 diabetes-related genetic scores and metabolic traits, in obese and normal-weight youths.J Clin Endocrinol Metab. 2016; 101: 4244-4250Crossref PubMed Scopus (7) Google Scholar as well as measures of insulin resistance35Carayol J. Hosking J. Pinkney J. Marquis J. Charpagne A. Metairon S. et al.Genetic susceptibility determines β-cell function and fasting glycemia trajectories throughout childhood: a 12-year cohort study (EarlyBird 76).Diabetes Care. 2020; 43: 653-660Crossref PubMed Scopus (9) Google Scholar,36Giannini C. Dalla Man C. Groop L. Cobelli C. Zhao H. Shaw M.M. et al.Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.Diabetes Care. 2014; 37: 475-482Crossref PubMed Scopus (29) Google Scholar,38Graae A.S. Hollensted M. Kloppenborg J.T. Mahendran Y. Schnurr T.M. Appel E.V. et al.An adult-based insulin resistance genetic risk score associates with insulin resistance, metabolic traits and altered fat distribution in Danish children and adolescents who are overweight or obese.Diabetologia. 2018; 61: 1769-1779Crossref PubMed Scopus (9) Google Scholar in youth. Two studies have examined the ability of GRSs to identify children at risk of progressing to T2D; even though the scores were shown to be associated with T2D risk,36Giannini C. Dalla Man C. Groop L. Cobelli C. Zhao H. Shaw M.M. et al.Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.Diabetes Care. 2014; 37: 475-482Crossref PubMed Scopus (29) Google Scholar,39Miranda-Lora A.L. Vilchis-Gil J. Juárez-Comboni D.B. Cruz M. Klünder-Klünder M. A genetic risk score improves the prediction of type 2 diabetes mellitus in Mexican youths but has lower predictive utility compared with non-genetic factors.Front Endocrinol (Lausanne). 2021; 12: 647864Crossref PubMed Scopus (4) Google Scholar in one of the studies clinical factors such as body mass index (BMI) and family history of T2D had higher predictive utility.34Miranda-Lora A.L. Cruz M. Molina-Díaz M. Gutiérrez J. Flores-Huerta S. Klünder-Klünder M. Associations of common variants in the SLC16A11, TCF7L2, and ABCA1 genes with pediatric-onset type 2 diabetes and related glycemic traits in families: a case-control and case-parent trio study.Pediatr Diabetes. 2017; 18: 824-831Crossref PubMed Scopus (16) Google ScholarGenome-Wide Association StudiesSince the first genome-wide association study (GWAS) for T2D in adults was published in 2007,40Sladek R. Rocheleau G. Rung J. Dina C. Shen L. Serre D. et al.A genome-wide association study identifies novel risk loci for type 2 diabetes.Nature. 2007; 445: 881-885Crossref PubMed Scopus (2352) Google Scholar there has been an explosion of genetic discoveries related to adult T2D with extremely well-powered studies and advanced analytic techniques. At the time of this publication, >400 variants have been associated with T2D in adults.41Mahajan A. Taliun D. Thurner M. Robertson N.R. Torres J.M. Rayner N.W. et al.Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.Nat Genet. 2018; 50: 1505-1513Crossref PubMed Scopus (671) Google Scholar In comparison, large scale studies of pediatric T2D have not been conducted, largely due to limited sample sizes. To address this gap, we and colleagues formed the ProDiGY Consortium, which is a collaboration of 3 research groups: the TODAY study,42Zeitler P. Epstein L. Grey M. Hirst K. Kaufman F. et Study for type 2 diabetes in adolescents and a study of the of metformin or in combination with or in adolescents with type 2 Diabetes. 2007; PubMed Scopus Google Scholar SEARCH for Diabetes in Study for Diabetes in a study of the incidence and of diabetes mellitus in Clin Full Text Full Text PDF PubMed Scopus Google Scholar and the 2 Diabetes Genetic by in C. J. T.M. A. K.J. et al.The genetic of type 2 diabetes.Nature. 2016; PubMed Scopus Google Scholar The ProDiGY study is a to understanding of the genetics of T2D in youth by the sample and phenotypic data of 2 pediatric T2D studies with the genetic and of a adult diabetes genetics we conducted the first for T2D in youth to identify genetic variants specifically to youth-onset S. L. J. Divers J. S. S. et al.The first genome-wide association study for type 2 diabetes in the Progress in Diabetes Genetics in Youth (ProDiGY) 2021; PubMed Scopus (10) Google Scholar our genetic in youth with T2D who were for pancreatic and adult years and identified genome-wide including the novel in with an of for T2D, that of the risk a of T2D compared with the A The 6 loci were previously identified in adults and included TCF7L2, and S. L. J. Divers J. S. S. et al.The first genome-wide association study for type 2 diabetes in the Progress in Diabetes Genetics in Youth (ProDiGY) 2021; PubMed Scopus (10) Google the of our ProDiGY our hypothesis was that genetic were in youth with T2D compared with adults, given the T2D with to early age of To this we constructed GRSs in ProDiGY from known T2D variants identified in A. Zhang K.J. T. et meta-analysis insight into the genetic of type 2 diabetes Genet. 2014; PubMed Scopus Google Scholar of the association of the risk score between youth and adult and a higher for T2D in the youth compared with the adult in with our S. L. J. Divers J. S. S. et al.The first genome-wide association study for type 2 diabetes in the Progress in Diabetes Genetics in Youth (ProDiGY) 2021; PubMed Scopus (10) Google Scholar the efforts of the ProDiGY consortium have provided insight into the genetic of T2D in youth and have shown that the genetic of T2D in youth largely with that in adults but with a aggregate genetic risk studies of genes are to understand how the identified genetic variants disease the between and genetic factors are also to T2D risk in of Genetics in has been in our understanding of the genetics of T2D in youth to in sequencing and such as ProDiGY to sample sizes. Here we the of genetics as it pertains to pediatric T2D is a disease of from both environmental and genetic as well as of insulin resistance and β-cell among The of in MODY 3 is a of how genetics can be to disease and Although not as genetics also can be to for the more common of T2D. A approach has been to the heterogeneity of T2D with of loci mechanisms of disease based on β cell insulin resistance, and fat J. M. S. J.B. J. et 2 diabetes genetic loci by associations to disease mechanisms and a Med. 2018; 15: PubMed Scopus Google D. R.B. A. R. M. et association differences of Genet. 2021; PubMed Scopus Google Scholar These efforts to to with the of clinical and the risk of complications in the The of using genetic data to disease is that it over an and can be even a particularly for children who have T2D from the Diabetes Association youth with obesity for T2D based on the presence of additional risk including a family history of T2D, history of diabetes, and associated with insulin resistance, such as Diabetes and of in Care. 2021; 44: PubMed Scopus Google Scholar Although these allow to identify youth diabetes it is not which of these youth will on to T2D. In there is or between clinical as body mass fasting insulin or and the to the early days of T2D studies that a risk score for T2D in adults does not clinical of but to clinical risk genetic may predictive particularly for of adults in risk such as glucose might not have T. B. T. et al.Common genetic variants the from clinically of fasting glucose 2012; PubMed Scopus Google Scholar a risk score of 1 variants and that the of the distribution can identify adults with a to in T2D the of the as the the reported predictive was and the predictive was T. A. et of a risk score for type 2 diabetes in 2022; Scopus Google Scholar Although the current clinical utility of in the more scores from will to improve the predictive of these into can related to T2D with the of pathways related to the genetic the in TCF7L2, which has one of the known for common variants in both youth and adults with D. Dolan L.M. D'Agostino Jr., R. Hernandez A.M. McAteer J.B. Hamman R.F. et al.Association testing of TCF7L2 polymorphisms with type 2 diabetes in multi-ethnic youth.Diabetologia. 2011; 54: 535-539Crossref PubMed Scopus (42) Google R. Rocheleau G. Rung J. Dina C. Shen L. Serre D. et al.A genome-wide association study identifies novel risk loci for type 2 diabetes.Nature. 2007; 445: 881-885Crossref PubMed Scopus (2352) Google S. L. J.

Report of the Committee on the classification and diagnostic criteria of diabetes mellitus

Objective To investigate a community in Taiyuan city of Shanxi Province which carries out the standardized management in elderly patients with 2 diabetes mellitus, summarize its management model, and evaluate its effect in this community, analyze the model, and provide references for the management of diabetes mellitus in communities. Methods Questionnaire survey: all of them were investigated by questionnaire, and fill in the general condition the questionnaire. Training includes six times: self management concept in elderly diabetes; Characteristic and attention in elderly diabetes; Medical nutrition therapy in elderly diabetes; Sport therapy in elderly diabetes; Drug treatment in elderly diabetes; Comprehensive control of blood glucose and metabolism index. It takes 12 weeks for this series of courses ,and fill out the questionnaire second time after 16 weeks. Results 92 patients were included in the analysis, mean age was 66.35±5.07 years (35.9% male) with diabetes duration 8.03±5.74 years. After diabetic health education, blood pressure, blood glucose, blood lipids were significantly lower than before the training. Diabetes knowledge was increase and self-management abilities was increase. Conclusion Community management of diabetes in elderly plays an important role in controlling blood glucose, Blood pressure, and quality of life. Key words: The elderly; Type 2 diabetes mellitus; Community education

New Medications for the Treatment of Diabetes.

Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body’s resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient’s data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-2 diabetes mellitus (T2DM). For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.

There are several guidelines for the management of diabetes mellitus from International Diabetes Federation,American Diabetes Association,Asian-Pacific Type 2 Diabetes Policy Group and Chinese Diabetes Association.These guidelines have individual characteristics.The Clinical Practice Recommendations of the American Diabetes Association are characterized by their abundance of contents and are applicable to persons of profession and scientist.Guideline for Diabetes Prevention and Treatment of the Chinese Diabetes Association,designed for application in China with contents of variety of related subjects,is suitable to persons of variety of profession. Key words: Type 2 diabetes mellitus; Guideline; ADA