{
  "question": [
    "What is the function of the PPAR-gamma gene in diabetes, and how do its variants impact the disease?",
    "How can CRISPR/Cas9 technology be used to study or treat genetic forms of diabetes?",
    "What is the significance of genetic polymorphisms in the GLUT4 gene for Type 2 diabetes?",
    "How do microRNAs regulate gene expression related to diabetes?",
    "What insights have been gained from studying the genetic basis of MODY (Maturity Onset Diabetes of the Young)?"
  ],
  "answer": [
    "The PPAR-gamma gene (PPARG) is a key regulator of adipocyte differentiation and insulin sensitivity, playing a significant role in glucose and lipid metabolism. Variants of this gene can influence the risk of type 2 diabetes (T2D). For instance, loss-of-function (LOF) mutations in PPARG are associated with lipodystrophy and insulin resistance. The common P12A variant is associated with a decreased risk of T2D. However, some rare variants can increase the risk of T2D. Additionally, these genetic variants can influence the effectiveness of antidiabetic medications targeting PPARG, such as thiazolidinediones.",
    "CRISPR/Cas9 technology can be used to study genetic forms of diabetes by editing genes that are associated with the disease. This allows researchers to understand the impact of these genes on cell function, growth, and survival. In terms of treatment, CRISPR/Cas9 might be used to genetically",
    "The text does not provide specific information on the significance of genetic polymorphisms in the GLUT4 gene for Type 2 diabetes.",
    "MicroRNAs (miRNAs) regulate gene expression related to diabetes by binding to the mRNA of target genes, which can inhibit their translation and lead to a decrease in the production of the corresponding proteins. These miRNAs can influence various biological processes such as insulin production and secretion, glucose homeostasis, cell growth and death, and immune response. For example, miR-29 has been shown to inhibit insulin-stimulated glucose uptake and downregulate gluconeogenesis. Other miRNAs like miR-18a and miR-206 can regulate genes like IGF-1, which is involved in glucose metabolism and insulin signaling. Dysregulation of these miRNAs can lead to the development of type 2 diabetes.",
    "Studying the genetic basis of MODY has led to the identification of several genes associated with the disease, including the most common ones: glucokinase, HNF1A, and HNF4A. This has helped in understanding the disease's autosomal dominant inheritance pattern and its onset at a young age due to -cell dysfunction. The genetic subtypes have also aided in identifying patients who will respond to specific therapies, opening the possibility of tailored drug therapy. Furthermore, the genetic research has moved physicians and patients towards precision genomic medicine, taking into account individual genetic data for diagnosis and treatment."
  ],
  "contexts": [
    [
      "\tAt the skeletal muscle level in particular, the total mass\nof muscle and its function as the site of 70% of insulin-mediated glucose disposal\nsuggest physiologically important effects of PPAR (Semple et al 2006). Furthermore, synthetic PPAR agonists, the insulin-sensitizing thiazolidinediones (TZDs),\nare therapeutic agents used in the treatment of type 2 diabetes. However, clinical\nuse of TZDs is limited by the occurrence of fluid retention, haemodilution, and\nheart failure in up to 15% of the patients (Mudaliar et al 2003). By far the most studied PPAR polymorphism is the Pro12Ala in the unique\nPPAR 2 N-terminal domain.\tEndocr Pract\n9:406416\nMuller Y, Bogardus C, Beamer B, Shuldiner A, Baier L 2003 A functional variant in the peroxisome proliferator-activated receptor  2 promoter is associated with predictors of obesity and\ntype 2 diabetes in Pima Indians. Diabetes 52:18641871\nNelson T, Fingerlin T, Moss L, Barmada M, Ferrell R, Norris J 2007 Association of the peroxisome proliferatoractivated receptor  gene with type 2 diabetes mellitus varies by physical\nactivity among non-Hispanic whites from Colorado. Metabolism 56:388393\nNewton-Cheh C, Hirschhorn JN 2005 Genetic association studies of complex traits: design\nand analysis issues.\tPPAR is a fatty acid- and eicosanoiddependent nuclear receptor that binds to specific DNA response elements (PPREs)\nas heterodimer with the retinoid X receptor and, in the presence of ligands, regulates the expression of the target gene. Although the role of PPAR in adipose\ntissue development and function is established, its low levels in tissues important\nto glucose homeostasis, including skeletal muscle, liver, and pancreatic  cells, raise\nthe question of its possible physiological and pharmacological importance at those\nGENEENVIRONMENT INTERACTION AND THE METABOLIC SYNDROME\n\n105\n\nsites (Semple et al 2006).\tPPAR is considered as a strong, if not the strongest, candidate gene for\nthe metabolic syndrome. The PPAR gene is located at 3p25, a region showing\nevidence for linkage with diabetes and obesity susceptibility. Frameshift and missense heterozygous mutations have been liked to insulin resistance and type 2\ndiabetes, obesity, lipodystrophy and hypertension (Ristow et al 1998, Barroso et al\n1999, Hegele et al 2002, Savage et al 2002).",
      "\tInteractions with the peroxisomeproliferator-activated receptors\n\nThe transcription factor peroxisome-proliferatoractivated receptor gamma (PPARg) is known to influence insulin sensitivity, and acts partly via a modulation of the circulating adiponectin level (PPARg agonists increase the adiponectin level) (Ref.38).The PPARgP12A SNP is a wellestablished genetic variant that modulates insulin sensitivity and the risk of type 2 diabetes (Ref.39).In a Chinese family study, Yang et al. demonstrated a genetic interaction between the ADIPOQ exon 2 45TG SNP and the P12A SNP of the PPARg gene with respect to insulin sensitivity (Ref.40).Likewise Tanko et al. reported a similar interaction between the PPARg P12A SNP and the 211377CG SNP of the ADIPOQ gene promoter (Ref.41).Indeed, a significant interaction was detected between the PPARg Ala12 and the ADIPOQ 211377C alleles and higher BMI, and the two alleles were associated with higher insulin sensitivity and displayed interaction with respect to insulin sensitivity.Such associations of 'insulinsensitising' alleles with increased BMI is not uncommon: it was previously reported for the UCP3 and the Isl1 genes in obese subjects ( Refs 42,43) and interpreted as a protective effect that delays the occurrence of type 2 diabetes and thus contributes to the reaching of a higher degree of obesity.",
      "\t\n\nPeroxisome proliferator-activated receptor gamma (PPARG) is a master transcriptional regulator of adipocyte differentiation and a canonical target of antidiabetic thiazolidinedione medications.In rare families, loss-of-function (LOF) mutations in PPARG are known to cosegregate with lipodystrophy and insulin resistance; in the general population, the common P12A variant is associated with a decreased risk of type 2 diabetes (T2D).Whether and how rare variants in PPARG and defects in adipocyte differentiation influence risk of T2D in the general population remains undetermined.By sequencing PPARG in 19,752 T2D cases and controls drawn from multiple studies and ethnic groups, we identified 49 previously unidentified, nonsynonymous PPARG variants (MAF < 0.5%).Considered in aggregate (with or without computational prediction of functional consequence), these rare variants showed no association with T2D (OR = 1.35;P = 0.17).The function of the 49 variants was experimentally tested in a novel high-throughput human adipocyte differentiation assay, and nine were found to have reduced activity in the assay.Carrying any of these nine LOF variants was associated with a substantial increase in risk of T2D (OR = 7.22; P = 0.005).The combination of large-scale DNA sequencing and functional testing in the laboratory reveals that approximately 1 in 1,000 individuals carries a variant in PPARG that reduces function in a human adipocyte differentiation assay and is associated with a substantial risk of T2D.",
      "\tPPARG\n\nPeroxisome proliferator-activated receptor gamma (PPARG) gene, located at 3p25, encodes peroxisome proliferator-activated receptor gamma protein, which is important in the control of insulin sensitivity, glucose homeostasis, and blood pressure (Barroso et al., 1999).Similar to previous meta-analyses, data from a recent meta-analysis involving 32,849 cases and 47,456 controls in 60 studies showed that PPARG polymorphism rs1801282 (Pro12Ala) was associated with a reduction in T2DM risk ( OR  0.86, 95%; CI  0.81  0.90; Gouda et al., 2010).Most recently, other variant genotypes, including rs3856806 (1431C  T), have been associated with T2DM in a Chinese Han population (Lu et al., 2011).\tPPARGC1A\n\nPeroxisome proliferator activated receptor gamma coactivator 1-alpha (PPARGC1A) gene, located at 4p15.1, codes peroxisome proliferator activated receptor gamma coactivator 1 protein.Its expression might infl uence insulin sensitivity as well as energy expenditure, thereby contributing to the development of obesity, a risk factor for diabetes mellitus (Esterbauer, Oberkofl er, Krempler, & Patsch, 1999).The most recent meta-analysis showed that rs8192678 (Gly482Ser) and rs2970847 (Thr394Thr) polymorphisms of PPARGC1A were signifi cantly associated with the risk of T2DM, especially in the Asian Indian population (Yang, Mo, Chen, Lu, & Gu, 2011).Studies on PPARGC1A genetic polymorphisms and GDM are limited.Polymorphisms, rs8192678 and rs2970847, have not been associated with GDM in European Whites living in Vienna (Leipold, Knoefl er, Gruber, Huber, et al., 2006) or Scandinavian women (Shaat et al., 2007).",
      "\tSUMMARY\n\nIn just over a decade, PPARg has evolved from somewhat humble beginnings as a simple regulator of adipogenesis to become a key therapeutic target in the fight against the 21st Century epidemics of obesity, insulin resistance and the metabolic syndrome.Whilst pharmacological and animal studies have yielded a wealth of information regarding the role of this receptor in the regulation of energy, glucose and lipid homeostasis, there can be no doubt that defining the metabolic consequences induced by polymorphisms and mutations in the human PPARg gene has contributed significantly to our understanding of the biology of this receptor.To this end, PPARg has proved to be a fruitful 'hunting ground' with many different genetic variants already identified, each providing novel insights into the role of PPARg in normal physiology and disease.Given the significant species-specific differences that exist in metabolism, particularly in relation to lipid homeostasis, it is critical that we continue to identify and study these human 'experiments of nature' in order to complement the impressive pharmacological and functional genomic approaches that are currently being employed to permit the development of more superior ligands with enhanced therapeutic impact.Given the apparent inexorable rise in the prevalence of obesity, insulin resistance and T2DM, the need for such novel therapies could not be more urgent.",
      "\t\n\nAnother biologic candidate gene that was extensively studied is the peroxisome proliferator -activated receptor  gene ( PPARG ), where mutations that severely decrease the transactivation potential were found to cosegregate with extreme insulin resistance, diabetes and hypertension in two families, with autosomaldominant inheritance [89] .A common amino -acid polymorphism (Pro12Ala) in PPARG has been associated with T2DM; homozygous carriers of the Pro12 allele are more insulin resistant than those having one Ala12 allele and have a 1.25 -fold increased risk of developing diabetes [90] .This common polymorphism has a modest, yet extensively replicated effect on the risk of T2DM.There is also evidence for interaction between this polymorphism and the insulin secretion in response to fatty acids [91] , and BMI [92] ; the protective effect of the alanine allele was lost in subjects with a BMI greater than 35 kg/m 2 .A widespread Gly482Ser polymorphism of PGC1 - (known as PPARGC1 ), a transcriptional coactivator of a series of nuclear receptors including PPARG , has been associated with a 1.34 genotype relative risk of T2DM [93] .In this study, a test for interaction with the Pro12Ala variant in PPARG gave no indication for additive effects on diabetes status.",
      "\t\n\nHere, we report the most relevant PPAR SNPs, mutations, and rare variants, discussing their role on PPAR activity in adipose tissue and their association with T2D and obesity.In addition, we describe the role of alternative splicing and post-translational modifications on PPAR activity, with a specific focus on their impact on human metabolic disorders.Finally, considering PPAR as a pharmacological target, we discuss how nucleotide changes, PTMs, and alternative splicing can affect drug responsiveness in patients.\t\n\nPPAR is the most studied member of the PPAR family due to its primary role in dictating the expression of a network of genes responsible for lipid and glucose homeostasis as well as inflammation [17][18][19][20][21][22].Most importantly, PPAR is sufficient and essential for adipocyte formation and, as such, it is widely considered the master regulator of adipogenesis [9,[23][24][25].Because of its central role in many biological processes, different single-nucleotide polymorphisms (SNPs) and/or rare variants and mutations in the PPARG gene, or posttranslational modifications (PTMs; e.g., phosphorylation and SUMOylation), have been associated with alterations of the metabolic status including insulin resistance, obesity, and type 2 diabetes (T2D) [26][27][28][29][30].In this regard, PPAR has been the focus of intense research as a therapeutic target, and diverse synthetic partial or full agonists targeting this receptor have so far been developed [17,[31][32][33][34][35][36].Thiazolidinediones (TZDs), included in FDA-approved insulin-sensitizing drugs, are used in type 2 diabetes (T2D) treatment due to their positive action on glycemic control, on adipocyte differentiation, and on blood-circulating fatty acids levels [37][38][39][40].Nevertheless, adverse or side effects such as weight gain, edema, and fluid retention [41,42] have been reported, indicating that further knowledge on PPAR activity is needed and that new drugs targeting PPAR should be designed and tested.\tPPARG Genetic Variants and Their Effects on Drug Effectiveness in Metabolic Dysfunctions\n\nThe role of PPARG in the regulation of lipid and glucose homeostasis [20,49,50], inflammatory pathways [21], and its master role in governing the genesis of adipose tissue [19,25] indicate why it is so relevant in the etiology of metabolic diseases.Nucleotide variants in PPARG, alone or in combination (i.e., haplotype), can strongly affect PPAR activity in light of its functioning as a transcription factor.Therefore, its ability to orchestrate gene expression in different tissues can be compromised by nucleotide variations [51].In this regard, only a few studies have addressed the impact of nucleotide variants on the expression of PPAR itself or of its target genes.Instead, most of the effort has focused on identifying single-nucleotide polymorphisms (SNPs) or mutations in the PPARG gene with significant associations with complex traits and/or metabolic disorders [52][53][54][55][56][57][58][59][60][61][62].Moreover, as PPAR is targeted by synthetic agonists, (TZDs or glitazones) used in T2D treatment, different studies in the era of personalized medicine have attempted to demonstrate whether and how pharmacological efficacy can be affected by the presence of such variations in patients with diabetes [63].\tGain-and Loss-of-Function Mutations Affecting Metabolic Phenotype\n\nPPARG low frequency (~1:500) variants and rare point mutations, mostly associated with metabolic dysfunctions by independent studies, have also been extensively tested for their ability to affect PPAR activity, adipocyte differentiation, and TZD efficacy [54,58,61,[107][108][109][110][111][112][113].Among them, a very rare heterozygous PPAR mutation, P113Q (in PPAR2), has been identified in a German cohort [110,113,114] but not detected in French and American individuals or in Icelandic children [115][116][117].Ristow and colleagues [113] reported marked obesity (BMI 37.9-47.3)and T2D in patients carrying this mutation, also showing that it reduces PPAR phosphorylation in Ser112, in turn inducing PPAR transactivation capacity, adipocyte differentiation, and triglycerides accumulation [113].Subsequently, this gain-offunction mutation has been related to a marked reduction of body glucose uptake, suggesting it to be a rare cause of severe insulin resistance [114].However, insulin resistance and T2D have been mostly associated with loss-of-function (LOF) PPAR mutations [54,61,111], frequently identified as causing familial partial lipodystrophy type 3 (FPLD3).This autosomal dominant-inherited disorder is characterized by gradual loss of subcutaneous adipose tissue from limbs and the gluteal region, and is accompanied by dramatic metabolic complications, such as severe insulin resistance and early onset of T2D [108,112].A group of FPLD3-associated mutations resides within PPAR LBD and affects the protein structure to variable degrees.In particular, the heterozygous mutation in PPARG exon 6 R425C (in PPAR2) was identified in a patient who developed diabetes mellitus and hypertriglyceridemia at a young age and lipodystrophy of the extremities and face in adulthood [112].Interestingly, R425 is a wellconserved amino acid residue involved in the formation and stabilization of the tertiary structure, falling in a domain that is crucial for the interaction with RXR [112].Therefore, the R425C substitution strongly modifies receptor activity by altering the ability of the protein to form a functional heterodimer [112].Consequently, the mutated receptor strongly reduces the capacity of precursor cells to differentiate in mature adipocytes, also reducing rosiglitazone responsiveness, even at high doses [110].\t\nPurpose of Review Full and partial synthetic agonists targeting the transcription factor PPAR are contained in FDA-approved insulin-sensitizing drugs and used for the treatment of metabolic syndrome-related dysfunctions.Here, we discuss the association between PPARG genetic variants and drug efficacy, as well as the role of alternative splicing and post-translational modifications as contributors to the complexity of PPAR signaling and to the effects of synthetic PPAR ligands.Recent Findings PPAR regulates the transcription of several target genes governing adipocyte differentiation and glucose and lipid metabolism, as well as insulin sensitivity and inflammatory pathways.These pleiotropic functions confer great relevance to PPAR in physiological regulation of whole-body metabolism, as well as in the etiology of metabolic disorders.Accordingly, PPARG gene mutations, nucleotide variations, and post-translational modifications have been associated with adipose tissue disorders and the related risk of insulin resistance and type 2 diabetes (T2D).Moreover, PPAR alternative splicing isoformsgenerating dominant-negative isoforms mainly expressed in human adipose tissue-have been related to impaired PPAR activity and adipose tissue dysfunctions.Thus, multiple regulatory levels that contribute to PPAR signaling complexity may account for the beneficial as well as adverse effects of PPAR agonists.Further targeted analyses, taking into account all these aspects, are needed for better deciphering the role of PPAR in human pathophysiology, especially in insulin resistance and T2D.Summary The therapeutic potential of full and partial PPAR synthetic agonists underlines the clinical significance of this nuclear receptor.PPARG mutations, polymorphisms, alternative splicing isoforms, and post-translational modifications may contribute to the pathogenesis of metabolic disorders, also influencing the responsiveness of pharmacological therapy.Therefore, in the context of the current evidence-based trend to personalized diabetes management, we highlight the need to decipher the intricate regulation of PPAR signaling to pave the way to tailored therapies in patients with insulin resistance and T2D.Keywords PPARG genetic variants .Dominant-negative isoforms .Post-tranlational modifications .Adipose tissue dysfunctions .Drug responsiveness .Type 2 diabetes This article is part of the Topical Collection on Genetics * Alfredo Ciccodicola\t\n\nPurpose of Review Full and partial synthetic agonists targeting the transcription factor PPAR are contained in FDA-approved insulin-sensitizing drugs and used for the treatment of metabolic syndrome-related dysfunctions.Here, we discuss the association between PPARG genetic variants and drug efficacy, as well as the role of alternative splicing and post-translational modifications as contributors to the complexity of PPAR signaling and to the effects of synthetic PPAR ligands.Recent Findings PPAR regulates the transcription of several target genes governing adipocyte differentiation and glucose and lipid metabolism, as well as insulin sensitivity and inflammatory pathways.These pleiotropic functions confer great relevance to PPAR in physiological regulation of whole-body metabolism, as well as in the etiology of metabolic disorders.Accordingly, PPARG gene mutations, nucleotide variations, and post-translational modifications have been associated with adipose tissue disorders and the related risk of insulin resistance and type 2 diabetes (T2D).Moreover, PPAR alternative splicing isoformsgenerating dominant-negative isoforms mainly expressed in human adipose tissue-have been related to impaired PPAR activity and adipose tissue dysfunctions.Thus, multiple regulatory levels that contribute to PPAR signaling complexity may account for the beneficial as well as adverse effects of PPAR agonists.Further targeted analyses, taking into account all these aspects, are needed for better deciphering the role of PPAR in human pathophysiology, especially in insulin resistance and T2D.Summary The therapeutic potential of full and partial PPAR synthetic agonists underlines the clinical significance of this nuclear receptor.PPARG mutations, polymorphisms, alternative splicing isoforms, and post-translational modifications may contribute to the pathogenesis of metabolic disorders, also influencing the responsiveness of pharmacological therapy.Therefore, in the context of the current evidence-based trend to personalized diabetes management, we highlight the need to decipher the intricate regulation of PPAR signaling to pave the way to tailored therapies in patients with insulin resistance and T2D.Keywords PPARG genetic variants .Dominant-negative isoforms .Post-tranlational modifications .Adipose tissue dysfunctions .Drug responsiveness .Type 2 diabetes This article is part of the Topical Collection on Genetics * Alfredo Ciccodicola",
      "\t\n\nThere is substantial evidence that PPAR- contributes to the risk for type 2 diabetes by influencing insulin sensitivity, insulin secretion and susceptibility to obesity [6].The 12Ala allele of the PPAR-2 gene, that has been shown to have a decreased transcriptional activity, is also associated with improved insulin sensitivity and lower risk for diabetes [17].This finding is in agreement with results from heterozygous PPAR- null mice exhibiting increased insulin sensitivity compared with wild-type mice [46].The 12Ala allele was associated with a higher reduction in the 2-h serum insulin level, probably indicating an increase in insulin sensitivity.However, it cannot be excluded that a decrease in insulin levels could also be due to impaired insulin secretion, because the 12Ala allele has been associated with reduced insulin secretion capacity in previous studies [20,47].\t\n\nPPAR is a ligand-activated transcription factor, a member of the nuclear hormone receptor superfamily, that functions as a heterodimer with a retinoid X receptor (RXR) to promote transcription of numerous target genes [5,6].PPAR-2, an isoform of PPAR- with 28 additional amino acids at its N-terminus, is expressed almost exclusively in adipose tissue [7].It plays a key role in adipogenesis [8,9,10,11], is involved in the regulation of insulin sensitivity [12,13], and is the major functional receptor for the thiazolidinedione class of insulin-sensitising drugs [11,14].Therefore, the PPAR- gene has been viewed as a \"thrifty gene\", with an important role in the development of type 2 diabetes and diabetes-related traits [7,15].Additionally, the Pro12Ala substitution in exon B of the PPAR-2 gene, first reported in Caucasians [16], has been associated with diabetes mellitus [17,18,19,20,21,22,23,24,25,26,27,28].Although not all associations have been consistent, a meta-analysis of published studies has confirmed a modest (1.25-fold), but statistically significant, increase in diabetes risk for the Pro12Pro genotype [4,19].\t\n\nIn summary, we have demonstrated that the Pro12Pro genotype of the PPAR-2 gene and the 482Ser allele of the PGC-1 gene predict the conversion from IGT to type 2 diabetes.Our study also shows that the interaction between drug treatment (acarbose) and genetic variation may be significant with respect to the conversion from impaired glucose tolerance to type 2 diabetes.\t\n\nPPAR- plays a key role in adipocyte differentiation [10,11], and can therefore influence body fat mass and obesity.In our study subjects, those with the 12Ala allele had a somewhat higher BMI at baseline, and tended to lose more weight.This finding is in accordance with our results from the Finnish Diabetes Prevention Study [48].In that study, subjects belonging to the intervention group (lifestyle changes) and who had the Ala12 allele lost significantly more weight (and were protected from type 2 diabetes) than subjects with the Pro12Pro genotype, although in the control group the 12Ala allele did not confer protection against diabetes.In the present study, the effect of the Pro12Pro genotype in increasing the risk for diabetes was independent of baseline weight change and other OR=odds ratio.Smoking was coded as 0 = never smokers and ex-smokers and 1 = current smokers at baseline.PPAR-2 genotypes were coded as 0 = the 12Ala allele and 1 = the Pro12Pro genotype confounding factors in women in the acarbose group, indicating that women possessing the Pro12Pro genotype were less responsive to acarbose treatment.This implies that the effect of acarbose treatment was modified by the Pro12Ala polymorphism.Several mechanisms could explain why the Gly482Ser polymorphism of the PGC-1 gene regulates the conversion from IGT to diabetes.PGC-1 increases and coordinates the expression of different genes that stimulate mitochondrial biogenesis, adaptive thermogenesis, fibre-type switching [32], expression of GLUT-4 in skeletal muscle [33], and regulation of gluconeogenesis in the liver [34].Thus, a reduction in the activity of PGC-1, possibly also as a result of the Gly482Ser mutation, might lead to insulin resistance in skeletal muscle.Additionally, a quantitative trait linkage analysis in Pima Indians suggested a link between basal insulin concentrations and chromosome 4p15. 1 [49] in cases where the PGC-1 gene has been mapped [50].In the present study the Gly482Ser variant was not related to fasting and 2-h plasma glucose, serum insulin, or their changes, or to BMI and weight change.However, compared to the Gly482Gly genotype, the 482Ser allele was associated with a 1.6-fold higher risk for diabetes in the placebo group but not in the acarbose group.The 482Ser allele had a significant interaction with treatment and acarbose treatment was able to reduce the risk of diabetes particularly among carriers of the 482Ser allele."
    ],
    [
      "\t\n\nThe advancements in both differentiation protocols and genome-editing technologies make it now possible to study the effect of genetic perturbations on human -cell development.\tA measure of -cell exocytosis based on electrical current. the scalability of such studies.Moreover, a genome-wide CRISPR loss-of-function screen performed in 2019 identified 373 potential regulators of insulin production in the mouse insulinoma-derived Min6 -cell line 178 .Extending genome-wide screens to human -cell models and increasing the diversity of cellular read-outs will provide orthogonal data sets for integration with existing genetic and genomic resources, in order to elucidate downstream biology.As the current protocols for hiPSC differentiation are expensive, are time-consuming and have variability in differentiation efficiency, continued advancements in differentiation protocols will enable similar approaches in these cell models.",
      "\tRegulation of GWAS diabetes genes by glucose in pancreatic islets\n\nMany of the recently discovered type 2 diabetes genes have been suggested to affect the development and/or function of pancreatic islets [6].The function, growth and survival of -cells can be regulated acutely and chronically by glucose [34].Thus, we examined whether the new type 2 diabetes susceptibility genes are regulated by overnight incubation in low (5 mM) or high (25 mM) glucose (Figure 5).Most genes were significantly or tended to be downregulated under conditions of high glucose.Cdkal1, Cdkn2a (Arf, P = 0.07), Ide, Jazf1, Camk1d, and Tspan8 (P = 0.06) expression levels were decreased ~50-60%.Meanwhile, the expression of Cdkn2b, Hhex (P = 0.10), Cdc123, Adamts9 (P = 0.09), and Thada were reduced 30-40%.To ensure the islets incubated in high glucose did not have globally decreased expression, we examined the expression of Txnip, which has been shown to be highly upregulated by glucose [35] and found that its expression was still significantly elevated in the islets cultured in high glucose (Figure 5).Mouse islets consist of -cells and other cell types.Thus, the MIN6 -cell line was also examined.We found that all the genes were expressed in this cell line (not shown), although this does not preclude that they also are expressed in other cell types within the islet.",
      "\tEmploying hPSCs and genome editing tools to study diabetes and metabolic syndromes\n\nIn general, the strategy to carry out in vitro disease modeling of diabetes and related metabolic syndromes with hPSCs and genome editing tools would be to 1) derive hiPSCs from patients with these conditions, 2) generate \"repaired/corrected\" isogenic controls [53] and then 3) differentiate them into pancreatic cells or target cells of relevance, such as immune cells in the case of T1D or myocytes, adipocytes and hepatocytes in the case of T2D (Figure 2).If patient material is inaccessible, one could introduce (naturally occurring) mutations or gene variants into hESCs and differentiate them accordingly to study disease mechanisms.Since excellent reviews have been published recently, we will provide a brief overview to familiarize the reader with the classification of diabetes and metabolic disorders.\tCONCLUSIONS\n\nhPSCs and the advancing genome editing tools appear to be a timely and potent combination for probing molecular mechanism(s) underlying diseases such as diabetes and metabolic syndromes.Studying monogenic forms of diabetes and syndromes of insulin resistance using these tools would be extremely useful given the lack of an autoimmune attack and confounding effects of insulin resistance and obesity.One caveat of this methodology at the moment is the \"low\" efficiency of deriving human beta cells in vitro [75,76], possibly due to our incomplete knowledge on human pancreatic development.Another explanation would be the lack of in vivo environmental cues emanating from proximal tissues such as the vasculature.Nonetheless, successful disease modeling of MODY2 [7] and Wolfram Syndrome [8] already suggests a high possibility of success.These technologies have the potential to elucidate the underlying pathophysiology that stem from defects in 1) beta cell development, metabolism or survival or 2) development of adipocyte.For instance in the case of MODY2, it is now clear that GCK mutation affects glucose-stimulated insulin secretion but not insulin synthesis or beta cell proliferation [7].With the latest advances in the derivation of mature and functional human pancreatic beta-like cells from hPSCs in vitro [75e77], eventually circumventing the requirement for in vivo maturation, disease modeling of diabetes is expected to progress exponentially.The knowledge gained from these hiPSC-based disease modeling studies can potentially be translated into the clinics by guiding clinicians on the appropriate type of medication to use for each condition based on the mechanism of action of the disease.Findings from these proposed studies could also offer clues to the pathophysiology of the \"garden variety\" of type 2 diabetes which is known to manifest defects in each of these tissues.hPSCs and genome editing tools may also provide an opportunity to better understand the relevance of gene variants identified from GWAS studies, in causing T1D, T2D, obesity and metabolic syndromes, given that they exhibit only modest effects and w85% of the variants map onto noncoding regions such as enhancers or regulatory elements [104].Investment into hPSCs and genome editing would allow a better mechanistic understanding of the pathophysiology of monogenic and complex diseases relevant for organismal homeostasis and therefore an improved approach to stratified personalized medicine.By identifying the impact of gene variants on disease predisposition, prophylactic measures in the form of lifestyle alterations or medication could be adopted early on in life to delay or even prevent the onset of diabetes and/or metabolic diseases.It is also likely that these hiPSCbased disease modeling studies would provide insights into approaches to predict the susceptibility of disease.Henceforth, the translational potential of studying human diabetes and metabolic syndrome disease mechanisms is huge, with opportunities for early prophylactic intervention that could have long-term implications for global health care and reduction of economic burden.While the derivation of hiPSCs from human tissues is relatively easier and gaining popularity compared to just a few years ago [2], it is likely that the modern technology of generating site-specific nucleases will also rapidly mature to make in vitro disease modeling a routine approach.\tEmploying hPSCs and genome editing tools to study type 1 diabetes (T1D)\n\nPatients with T1D are unable to secrete insulin due to near complete destruction of their pancreatic beta cells.More than 50 risk variants/ susceptibility alleles have been found to be associated with susceptibility to this disease [71] (https://www.niddkrepository.org/studies/t1dgc/) (Table 1).The strongest association is with the human leukocyte antigens (HLAs), which accounts for a large proportion of the genetic risk for T1D [71].Most of the T1D genes affect adaptive and innate autoimmunity leading to incomplete self-tolerance to beta cell antigens and immune-mediated destruction of beta cells [71].T1D-hiPSCs can be differentiated into T lymphocytes [72e74] and pancreatic beta cells [75e77] to allow co-culture experiments aimed at progressively evaluating their interactions in vitro (Figure 2) [78].A similar strategy can be applied to hiPSCs derived from T1D-susceptible patients to examine the impact of susceptible gene variants (Table 1) on the vulnerability of pancreatic beta cells to immune attack.For instance, hiPSCs derived from patients with a gene variant in PTPN22 can be differentiated into lymphocytes to study lymphocyte function [79e81].hiPSCs from subjects with gene variants in ERBB3, which is expressed in monocytes and dendritic cells, and may affect antigen presenting cell (APC) function [82], can be differentiated into selective immune cells to study how they affect APC function.hiPSCs from patients with gene variants in UBASH3A (also known as STS2), which is specifically expressed in lymphocytes [83], are well suited for differentiation into lymphocytes to study the function of this gene.\t\n\nBackground: Diabetes and metabolic syndromes are chronic, devastating diseases with increasing prevalence.Human pluripotent stem cells are gaining popularity in their usage for human in vitro disease modeling.With recent rapid advances in genome editing tools, these cells can now be genetically manipulated with relative ease to study how genes and gene variants contribute to diabetes and metabolic syndromes.Scope of review: We highlight the diabetes and metabolic genes and gene variants, which could potentially be studied, using two powerful technologies e human pluripotent stem cells (hPSCs) and genome editing tools e to aid the elucidation of yet elusive mechanisms underlying these complex diseases.Major conclusions: hPSCs and the advancing genome editing tools appear to be a timely and potent combination for probing molecular mechanism(s) underlying diseases such as diabetes and metabolic syndromes.The knowledge gained from these hiPSC-based disease modeling studies can potentially be translated into the clinics by guiding clinicians on the appropriate type of medication to use for each condition based on the mechanism of action of the disease.\t\n\nOne strategy to study these monogenic syndromes would be to derive hiPSCs from these patients, differentiate them into pancreatic progenitors and then transplant these progenitors into immunocompromised (SCID-Beige or NSG) mice for in vivo maturation (Figure 2).This methodology has been recently used to successfully model MODY2, demonstrating that beta cells derived from hiPSCs with GCK mutation are indeed less sensitive to glucose levels [7].Endoplasmic reticulum (ER) stress-related diabetes in patients with Wolfram syndrome has also been modeled using hiPSC-derived beta cells, demonstrating that WFS1 protein maintains ER function in beta cells by acting upstream of the unfolded protein response (UPR) pathways [8].phenotypes occurring in humans.Likewise, the stepwise analysis of human pancreatic development with this strategy would likely provide mechanistic insights into the ability of a single gene mutation (PDX1, PTF1A, HNF1B, GATA6 and GATA4) to promote pancreatic agenesis/ atrophy.Further, studying mutations in KCNJ11 and ABCC8 using hiPSC-derived beta cells may elucidate the mechanistic differences between permanent and transient neonatal diabetes [64].Overall, insulin production and secretion could be compared between diseased and gene-corrected pancreatic cells to understand the underlying cause of each type of monogenic diabetes (Figure 2).",
      "\t\n\nMoving beyond cancer phenotypes, indirect in vivo screens are beginning to be used in other disease models.A genome-scale knockout screen in pancreatic beta-cells transplanted into a mouse model for Type 1 Diabetes identified genetic factors preventing autoimmune clearance of transplants.Inhibition of an identified gene hit, Rnls , with pargyline [101] prevented an autoimmune reaction and confirmed that the screen was able to identify candidates of therapeutic relevance [11] .",
      "\t\n\nunderstand each cell type's genomic architecture and better characterize their roles in islet resilience and failure.Experimental manipulation of the regulatory elements and/or the target genes identified by (epi)genomic approaches described above and modeling the putative pathways and processes they implicate in human islet cell lines (e.g., EndoC-bH1-H3) is essential to progress from correlation to causation.Similarly, transitioning from \"the\" mouse (C57BL/6) to multiple mouse models for insights into the effects of naturally occurring genetic variation on islet function and physiology [61] and for manipulation of key genomic elements should also help characterize the dynamic range of islet behavior and response.T2D is a heterogeneous, complex, and progressive disorder, as multiple subtypes have been identified and associated with different genetic risk and clinical outcome profiles.Future islet genomics studies that focus on identifying the distinct subgroups of individuals with distinct genes/pathways that are disrupted and/or contributing to islet (dys)function at basal and/or responsive states are needed.Furthermore, priority should be given to profiling more islets from pre-diabetic and T2D individuals to characterize the transition between basal to stressed to T2D state and determine if there are intermediate signatures for islet failure and T2D onset.Together, this multi-pronged approach toward studying T2D genetics and islet pathophysiology will help identify additional targets and opportunities for intervention that can be exploited for more precise and effective preventative, treatment, and management options for T2D.",
      "\t\n\nIn addition, knock-out and transgenic mice have become powerful tools in elucidating the influence of specific genes in glucose metabolism and the pathogenesis of diabetes.This includes understanding which transcription factors are involved in pancreas development (Habener et al., 2005) and elucidation of insulin signalling pathways (Kahn, 2003;Wang and Jin, 2009).Tissue-specific knockouts have proven to be particularly useful in studying insulin signalling (Neubauer and Kulkarni, 2006) as the global insulin receptor knock-out is non-viable (Accili et al., 1996).",
      "\t\n\nA recent sequencing study provides an example of detection of rare variants in type 1 diabetes.Targeted sequencing in a series of candidate coding regions resulted in IFIH1 being identified as the causal gene in a region associated with type 1 diabetes by GWA studies (58).IFIH1 encodes a cytoplasmic helicase that mediates induction of the interferon response to viral RNA.The discovery of IFIH1 as a contributor to susceptibility to type 1 diabetes has strengthened the hypothesis (70) about a mechanism of disease pathogenesis involving virusgenetic interplay and raised type 1 interferon levels as a cofactor in -cell destruction.Nonetheless, it should be recognized that a component of the missing heritability (familial aggregation) in type 1 diabetes could well be due to unrecognized intra-familial environmental factors.Disease pathogenesis.Contemporary models of pathogenesis of type 1 diabetes support the involvement of two primary dramatis personae: the immune system and the -cell.The known and newly identified genetic risk factors for type 1 diabetes present exciting opportunities to build on to the current cast of disease mechanisms and networks.Most of the listed genes of interest (Table 2) and those in extended regions are assumed to regulate immune function.Some of these genes, however, may also have roles in the -cell (insulin being the most obvious example).Another gene, PTPN2, encoding a protein tyrosine phosphatase, was identified as affecting the risk for type 1 diabetes as well as for Crohn disease (47,71).PTPN2 is expressed in immune cells, and its expression is highly regulated by cytokines.However, PTPN2 is expressed also in -cells, where it modulates interferon (IFN)- signal transduction and has been shown to regulate cytokineinduced apoptosis (72).Other candidate genes, such as NOS2A, IL1B, reactive oxygen species scavengers, and candidate genes, identified in large GWA studies of type 2 diabetes, have not been found to be significant contributors to the susceptibility of type 1 diabetes (73).",
      "\t\n\nHuman genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D).However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS).We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks.We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant.At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants.The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.",
      "\tGene Therapy in Diabetes\n\nThe series of experiments leading to cloning and expression of insulin in the cultures cells in the 1970s was a tremendous revolution in the field of medicine and application of gene therapy in the treatment of diabetes was suggested as a possible cure.Regulating the sugar levels is the most important aspect in the treatment which also reduces the complications associated with the disease.Somatic gene therapy involving the somatic cells of the body includes two methods of gene delivery.The first one known as ex vivo gene therapy is described as the one in which the tissues are removed from the body; the therapeutic gene is inserted in vitro and then reimplanted back in the body while the in vivo therapy involves the insertion of gene therapy vectors directly to the patients by subcutaneous, intravenous, or intrabronchial routes, or by local injection [57].The application of ex vivo therapy aims at the generation of cells which possess the properties of  cells, for example, insulin producing cells [58].This therapy has also been used to generate  cells for transplantation.However, the concern lies in the aspect of surgically removing the tissue from the patient and reimplantation of the genetically modified tissues back into the body of the patients [57].Furthermore, type 1 diabetes results from autoimmune destruction of insulin synthesizing pancreatic  cells and islet transplantation has been explored as a possible solution for the treatment.The invention of insulin gene therapy substitutes  cell function by generating insulin secretory non- cells, not vulnerable to autoimmune reactions, offering a prospective therapeutic approach for type 1 diabetes [59].",
      "\t\nThe inheritance of variants that lead to coding changes in, or the mis-expression of, genes critical to pancreatic beta cell function can lead to alterations in insulin secretion and increase the risk of both type 1 and type 2 diabetes.Recently developed clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) gene editing tools provide a powerful means of understanding the impact of identified variants on cell function, growth, and survival and might ultimately provide a means, most likely after the transplantation of genetically \"corrected\" cells, of treating the disease.Here, we review some of the disease-associated genes and variants whose roles have been probed up to now.Next, we survey recent exciting developments in CRISPR/Cas9 technology and their possible exploitation for b cell functional genomics.Finally, we will provide a perspective as to how CRISPR/Cas9 technology may find clinical application in patients with diabetes.\t\n\nThe inheritance of variants that lead to coding changes in, or the mis-expression of, genes critical to pancreatic beta cell function can lead to alterations in insulin secretion and increase the risk of both type 1 and type 2 diabetes.Recently developed clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) gene editing tools provide a powerful means of understanding the impact of identified variants on cell function, growth, and survival and might ultimately provide a means, most likely after the transplantation of genetically \"corrected\" cells, of treating the disease.Here, we review some of the disease-associated genes and variants whose roles have been probed up to now.Next, we survey recent exciting developments in CRISPR/Cas9 technology and their possible exploitation for b cell functional genomics.Finally, we will provide a perspective as to how CRISPR/Cas9 technology may find clinical application in patients with diabetes.\tGWAS-Identified Genes\n\nFollowing the successful identification of genetic loci by GWAS, several candidate genes within or surrounding genetic loci which are thought to play roles in b cell function, in particular, in proinsulin processing and secretion, have been examined in mechanistic studies.Gene editing tools have quickly replaced techniques such as shRNA-based silencing and HDR-mediated deletion to become a mainstream technique in studies of gene function.For example, the critical b cell-enriched NEUROD1 and SLC30A8 genes were deleted in EndoC-bH1 cells using these approaches in recent studies (243).Similarly, pancreatic duodenum homeobox-1 (PDX1), an important regulator of the INS gene, was also mutated by CRISPR-Cas9 resulting in a line with defective glucose-induced Ca 2+ influx and insulin secretion (244).Our laboratory has inactivated the type 2 diabetes-related STARD10 and FCHSD2 genes in EndoC-bH1 cells using a lentiviral approach and demonstrated effects on insulin secretion (and see above) (117).Furthermore, Fang et al. used CRISPR screening technology and identified several genes involved in insulin regulation in mouse MIN6 cells (172).\t\n\nIn vivo delivery of CRISPR editing tools into pancreatic b cells in people with diabetes is likely to face enormous challenges for two main reasons: 1. b cells are postmitotic, thus disfavouring HDR-mediated CRISPR editing.2. Selective targeting to these cells will be required, likely involving cell type-tropic viruses (272), raising evident concerns over off-target effects and toxicity.Hence, the most likely and feasible way of CRISPR editing has to be an ex vivo system where b cells can first be engineered by CRISPR editing and then transplanted into patients (Figure 2).\t\n\ninsulin secretion.We begin by providing examples of genes and loci associated with altered T2D risk.Finally, we review the CRISPR tools that may offer the potential to correct these variants in the human b cell.\tIn Vitro and In Vivo b Cell Models for Studying Genetic Variants\n\nIn order to understand the pathogenic role of diabetes-associated genetic variants, tractable b cell models are essential.Mouse models, either transgenic or knock-out, are valuable for examining the roles of single genes, but their use is more limited in studies of intergenic regions given more substantial inter-species (mouse versus human) differences in these regions.As sources of human b cells, there are currently three possibilities.Firstly, primary islets isolated from organ donors: This source is, however, limited in terms of the availability and quality of islets (226).Secondly, clonal human b cells.Immortalized human EndoC-bH1 cells were developed in recent years after infection of foetal islets with large T antigen and further inoculation of islets in immunocompromised mice (227).Later generation EndoC-bH2 (228) and EndoC-bH3 (229) cell lines were subsequently established with more advanced features including regulated deletion of the immortalizing gene.The limitation of these cell lines, however, is their extremely slow growth rate which hampers their use.Given this slow growth rate -and the fact that these lines poorly tolerate expansion from a single cell-it is virtually impossible to modify them by HDR via CRISPR editing.A third possibility are therefore islet-like cells differentiated from human embryonic stem cells (hESC) or patient-derived induced pluripotent stem cells (iPSC).In light of the limitations of the above cellular models, laboratories are now focusing on hESC or iPSC in studies of gene function throughout b cell development by differentiating hESC/iPSC cells into mature b cells (230,231).Such directed differentiation protocols have recently been improved (21,159)."
    ],
    [
      "\t\n\nThe insulin receptor substrate 1 (IRS-1) expressed in tissues sensitive to insulin is crucial to glucose transporter 4 translocation (GLUT-4).IRS-1 polymorphism has been found related to insulin resistance, obesity and type 2 diabetes mellitus.In a study on GDM, the frequency of IRS-1 gene polymorphism was significantly higher in women with GDM than in pregnant women with a normal glucose tolerance, suggesting a role for this polymorphism in the onset of GDM as well as type 2 diabetes mellitus (17).The switch on IRS-1 of the amino acid GLY972 Arg (rs1801278) impairs insulin secretion, and a study on 1306 GDM patients and 1973 pregnant women without GDM found a significant association between the presence of this polymorphism and the risk of GDM (18).",
      "\t\n\nAssociation of ADIPOQ gene polymorphisms with Type 2 diabetes.",
      "\t\n\nThese six variants of PGC-1 gene were first studied to be associated with changes in insulin/glucose levels among Danish Caucasians (Ek et al. 2001).In the present study, genetic association analysis revealed increased risk of the A-allele (2.7-fold risk) and AA genotype (3.78-fold risk) of rs3736265 polymorphism towards T2D susceptibility in Jat Sikhs only, which can be attributed to ethnic heterogeneity.In contrast, a study on Danish Caucasians (Ek et al. 2001) revealed protective role of this allele while Han Chinese population (Zhu et al. 2009) showed no association.The AA genotype of rs3755863 polymorphism tends to pose 2.7-fold T2D risk in Jat Sikh group.On the other hand, studies on Caucasians showed protective effect whereas Chinese population failed to report any association with T2D (Barroso et al. 2003;Zhang et al. 2007).",
      "\t\n\nType 2 diabetes (T2DM) is a complex disease resulting from the contribution of both environmental and genetic factors.Recently, the list of genes implicated in the susceptibility to T2DM has substantially grown, also as a consequence of the great development of the genome-wide association studies in the last decade.Common polymorphisms in TCF7L2 gene have shown to have a strong effect with respect to many other involved genes.The aims of our study were to confirm the role of TCF7L2 in the susceptibility to T2DM in the Italian population and to investigate whether TCF7L2 genotypes also contribute to the clinical phenotypes variability and to diabetic complications development.Three TCF7L2 polymorphisms (rs7903146, rs7901695 and rs12255372) have been analyzed by allelic discrimination assays in a cohort of 154 Italian patients with T2DM and 171 healthy controls.A case-control association study and a genotype-phenotype correlation study have been carried out.Consistent with previous studies, all three SNPs showed a strong association with susceptibility to T2DM, both at genotypic (P = 0.003, P = 0.004 and P = 0.012) and at allelic level (P = 0.0004, P = 0.0004 and P = 0.003).Moreover, we observed associations between TCF7L2 variants and the following diabetic complications: diabetic retinopathy, cardiovascular disease and coronary artery disease.We also found a strong correlation between the rs7903146 and the presence of cardiovascular autonomic neuropathy (P = 0.02 with a high OR = 8.28).",
      "\t\n\nIn a GWAS of the French population, polymorphism rs13266634 of SLC30A8 gene has been associated with T2DM (Sladek et al., 2007).In a large meta-analysis including 42,609 cases and 69,564 controls from various ethnic groups from Europe, Asia, and Africa, polymorphism rs13266634 was also associated with T2DM in both Europeans and Asians (Jing, Sun, Bi, Shen, & Zhu, 2011).",
      "\t\n\nGene polymorphisms affecting drug response for some commonly used antidiabetic agents.",
      "\t\n\nIn fact, only two of the many candidate-gene associations claimed for T2D have stood the test of time.The Pro12Ala variant in the peroxisome proliferator-activated receptor gamma (PPARG) gene (encoding the target for the thiazolidinedione class of drugs used to treat T2D) [11] and the Glu23Lys variant in KCNJ11 (the potassium inwardly rectifying channel, subfamily J, member 11, which encodes part of the target for another class of diabetes drug, the sulphonylureas) [12] are both common polymorphisms shown in multiple studies to influence risk of T2D.Their effect sizes are only modest, each copy of the susceptibility allele increasing risk of disease by 15-20%.Interestingly, rare mutations in both KCNJ11 and PPARG are also known to be causal for certain rare monogenic syndromes (neonatal diabetes and lipodystrophies) characterized by severe metabolic disturbance of b-cell function and insulin resistance, respectively [13,14].",
      "\t\n\nNo other recent associations of polymorphisms with T2D have been replicated to date (Table 5).However, a recent meta-analysis (106) identified some early reproducibility of an association between variation in GLUT1 and T2D, originally reported in 1988 (104).It is likely that this association has not been pursued further for several reasons, but one possibility is a study that reported the rejection of linkage to GLUT1 at high levels of significance (46).However, linkage has limited power to assess associations with common variants and modest effect (and hence low  S ); complete evaluation of this association would require comprehensive testing of variation in this gene in large samples.",
      "\t\n\nbutions of these four common polymorphisms in type 2 diabetes patients were similar to those of normal nondiabetic controls.However, these four common polymorphisms were variably associated with several diabetes-related phenotypes, such as high-density lipoprotein (HDL) cholesterol, fasting plasma glucose, and homeostasis model assessment of insulin resistance.In particular, subjects harboring g.1062C were associated with a lower serum HDL cholesterol level after adjusting for other variables (P  0.0004 or 0.01 after Bonferroni correction for 24 tests).",
      "\t\n\nHowever, there have been some successes.In T2D, the presence of common polymorphisms in known diabetes drug targets has presented obvious candidates for pharmacogenetic analysis.Evidence of a relationship between ABCC8/KCNJ11 genotype and sulfonylurea response is encouraging.Recent analyses in large cohorts have reported, for example, a 45% increased risk of glibenclamide treatment failure amongst risk compared to non-risk allele homozygotes (Sesti et al. 2006) and a greater decrease in fasting plasma glucose following gliclazide treatment amongst risk allele carriers (Feng et al. 2008).An effect upon gliclazide response is consistent with functional data which demonstrates that the risk variant K ATP channel has 3.5 times increased sensitivity to gliclazide inhibition (Hamming et al. 2009).",
      "\tDNA polymorphisms associated with type 2 diabetes\n\nWe found 7 known genes (GPC1, ATSV, AGXT, HDLBP, NEDD5, PPP1R7 and serine/threonine (S/T) kinase-like), none of which were obvious candidates, and 15 ESTs in the NIDDM1 interval (Fig. 1).We identified single-nucleotide polymorphisms (SNPs) and other types of DNA polymorphism in the 7 known genes and in 4 of the 15 ESTs (Fig. 1).We carried out the initial analyses, examining association of alleles and haplotypes comprised of alleles at adjacent polymorphisms with type 2 diabetes, using just the random sample and the two groups of patients described above.There was a nominally significant difference (P=0.003,uncorrected for the 44-haplotype/group comparisons) in the haplotype frequency distribution of markers UCSNP-1, -2 and -19 between the group of patients with evidence for linkage at NIDDM1 and the random sample (Table A, see http://genetics.nature.com/supplementary_info/). The characterization of additional SNPs in the interval between UCSNP-19 and UCSNP-1 and -2 (Figs 1 and 2) revealed a cluster of four SNPs having significant differences in allele frequencies between the random sample and patients: UCSNP-26, P=0.02; UCSNP-25, P=0.03; UCSNP-23, P=0.02; and UCSNP-22, P=0.01 (Table 1).These results, however, cannot be considered independent observations of association due to linkage disequilibrium among the four SNPs.We also observed significant differences in allele frequencies at UCSNP-29, -35, -37, -38 and -40 between patient and random samples.These results suggested there might be a diabetes-susceptibility gene in the vicinity of these SNPs, thus prompting us to examine this region in more detail.We therefore resequenced this region in ten diabetic Mexican American subjects to gain a better understanding of all of the genetic variation that was present and the relationship between each polymorphism and type 2 diabetes (Fig. 2; and Table B, see http://genetics.nature.com/supplementary_info/).",
      "\t\n\nwww.nature.com/clinicalpractice/endmetPPARG (peroxisome proliferator-activated receptor  gene; this encodes the target for thiazolidinediones) 11 and the Glu32Lys variant in KCNJ11 (which encodes part of another diabetes therapeutic target, this time for sulfonyl ureas) 4 are both common single-nucleotide polymorphisms (SNPs) that have been shown to influence risk of diabetes in multiple studies.Their effect sizes are modest (each extra copy of a susceptibility allele increases the risk of disease by about 15-20%), however, and their contribution to the observed familial aggregation of diabetes limited. ][14] The harvest of equivalent efforts in obesity has been even more limited.The only locus contributing to a respectable proportion of cases of severe adult obesity is the one that includes MC4R (melanocortin 4 receptor gene). 6The variants responsible are themselves rare, however, and have limited impact on variation in weight within the wider population. 5,6",
      "\tConclusions\n\nIn this Review, we have summarized the available evidence on the role of polymorphisms in the genes encoding for insulin-signaling inhibitors molecules in determining genetic predisposition to T2D and related diseases.Overall, solid evidence seems to exist only for rs1044498 of the ENPP1 gene and for rs2295490 of the TRIB3 gene, whose association with T2D risk and insulin resistance, even if not confirmed (for ENPP1) [33] or not yet investigated (for TRIB3) [33] by GWAS studies, has been consistently reported by several original studies [16-20, 22-33, 38-43, 100, 101, 103, 104] and large meta-analyses [32,104].It is worth underlining that both rs1044498 and rs2295490 have been reported to be associated not only with defective insulin action in peripheral target tissues but also with impaired insulin secretion and decreased beta-cell homeostasis [14,15,101,103,104].These observations suggest that the two major pathogenic defects of T2D share common genetic causes and support the hypothesis that they should be seen as different aspects of the same process rather than as separate events [105].In addition, several studies have shown that the effect of rs1044498 and rs2295490 is more evident on early-onset T2D [26,28,104]; notably similar data have been obtained for rs1801278 of IRS1 gene [106]; these data hint to the possibility that focusing on early-onset cases may represent a successful strategy to study the contribution of insulin-signaling gene variants to T2D pathogenesis.Interestingly, a very recent study [107] has investigated the combined role of rs1044498 of the ENPP1 gene and for rs2295490 of the TRIB3 gene together with rs1801278 of IRS1 gene, on CVD, age at MI, and in vivo insulin sensitivity reporting a significant additive effect among the risk variants; notably the joint predictive power of ENPP1 rs1044498, IRS1 rs1801278, and TRIB3 rs 2295490 SNPs was even more evident among obese individuals [107].These results not only further reinforce the importance of rs1044498 and rs2295490 in determining the risk of insulin resistance and related diseases but further underlie that in any single individual the effect of each specific variant is also significantly influenced by the interaction with other variants as well as by environmental factors [108,109].Indeed T2D, CVD, IR, obesity, and related metabolic disorders are characterized by extremely heterogeneous phenotypes; thus some of the earlier positive findings reported in this Review that were not confirmed in subsequent, larger studies may have been \"real\" associations, even if limited to a specific subset of subjects in a definite environmental and genetic setting.In fact the extreme hetereogeneity of T2D and related diseases may represent one of the main reasons for the apparent discrepancy between the results of GWAS and those of classical \"candidate-gene\" studies, as the design of GWAS does not take into account several factors, including sexual dimorphism, age at disease onset, and obesity status, that have been shown to have an important role in the pathogenesis of metabolic diseases.In recent years, several methods for screening gene-environment interaction have been proposed [110] and their wider implementation is likely to shed further light on the genetics of metabolic diseases.Furthermore, novel technologies, such as next generation sequencing, that allow to address the role of relatively rare variants, will significantly contribute to obtain a clearer picture of the genetics basis of T2D and related diseases [111].Finally, the data on the genetics of insulin-signaling inhibitors molecules, recapitulated in this Review article, may supply useful elements to interpret the results of novel, more technically advanced, genetic studies; indeed it is becoming increasingly evident that genetic information on complex metabolic diseases should be interpreted taking into account the composite biological pathways underlying their pathogenesis [112].In addition, as suggested by recent studies on ENPP1 rs1044498 [35][36][37], a deeper knowledge of the genetic variants affecting the pathogenesis of T2D and related metabolic diseases may have important implications also for the implementation of tailored therapeutical approaches.\t\n\nA small Iranian study evaluated the specific contribution of seven polymorphisms found in the 2 Kb at the 3  extension of PTPN1 (plausibly, the promoter region) to the development of T2D [84].Only rs6126029A/C (g.-1023) showed nominal association with T2D, but this association was not confirmed after correction for established T2D risk factors [84].Functional analyses in HepG2 cell lines also showed that rs6126029A/C did not influence PTPN1 expression [84].The IVS5+3666del-/T SNP was only found in one study, and it was associated with morbid obesity in a French cohort, with no effects on T2D development or on glucose/insulin parameters [80].",
      "\t\n\nTaken together, it seems therefore reasonable to believe that minor changes in a single enzyme or protein function due to a single nucleotide polymorphism are unlikely to generate defects in blood glucose and insulin concentrations across a population as a major clinical outcome.This is in contrast to insulin secretion where relatively minor effects due to gene polymorphism on b-cell viability, survival or function would, over time, have a measurable effect on the rate of insulin secretion from pancreatic islets, and present clinically as hyperglycemia.",
      "\t\n\nWe recognize that our study has limitations as the limited size of the sample in the groups of study.The functional effect of the polymorphisms only was determined by informatics tools, so experimental designs are needed in order to corroborate this functional effect.In spite of these limitations, our study contributes to a new argument in which the 5UTR 44 C/G polymorphism may have a role as a risk factor for T2DM.",
      "\tDiscussion\n\nThe main result of our study shows that, among lean individuals, carriers of polymorphism Gly972Arg of the IRS1 gene are at 3 times greater odds of having T2D, as compared with noncarriers.This association with T2D exists independently of potentially associated environmental factors like BMI, family history of diabetes, and sex.This observation suggests a possible relationship of polymorphism Gly972Arg in the pathogenesis of T2D.The other 3 tested SNPs on this gene were not associated with the presence of T2D.The SNP-SNP and SNP-environment interactions were not significant.\t\n\nBased on our previous observation suggesting a greater genetic predisposition among lean diabetics [20], in the present analysis, we aimed to evaluate the association of the Gly972Arg polymorphism and other polymorphic variants on the IRS1 gene with T2D in a representative sample of the Mexican population with body mass index (BMI) less than 25 kg/m 2 .",
      "\t\n\nPrevious attempts to relate the Gly482Ser polymorphism to type 2 diabetes have shown an 1.34-fold increase in risk among Danish Caucasians [38] and a significant association among Japanese subjects [39].In contrast, the 482Ser allele did not predict diabetes in French Caucasians or Pima Indians [40,41].These studies were carried out in single populations.Because several different populations were used in the STOP-NIDDM trial, our data provides strong evidence that the Gly482Ser polymorphism of the PGC-1 gene contributes to the risk of type 2 diabetes.In agreement with this, the reduced expression of PGC-1 in adipose tissue has been associated with insulin resistance [51].Moreover, recent studies have reported that down-regulation of the PGC-1 gene and coordinated changes in other genes involved in oxidative phosphorylation in man are associated with IGT, diabetes mellitus [35] and insulin resistance [37].",
      "\tCONCLUsION\n\nTo conclude, rs7903146 and rs680 polymorphisms were found independently to be significantly associated with T2DM risk in Indian adults.MDR identified the gene-gene interaction between TCF7L2 and SLC30A8 polymorphisms in confirming T2DM risk.Further studies should address the biological mechanisms affecting glucose homeostasis."
    ],
    [
      "\tDISCUSSION\n\nIn this study, we employed high throughput sequencing to identify differentially expressed miRNAs associated with IGT and untreated diabetes in whole blood of South African mixed ancestry women, which in an earlier study we had established a high prevalence of undiagnosed IGT and DM [18).We observed evidence for differential expression of 61 in IGT, 109 in screendetected diabetes both when compared to individuals with normal glucose tolerance, of which 25 were common in both conditions.Although several of these dysregulated miRNAs have been linked to diabetic and non-diabetic hyperglycaemia, we also uncovered 57 novel miRNAs.Of note is hsa-miR-novel-chr2_50989 which had the highest fold change in screen-detected DM and remained in the top ten differentially expressed miRNAs in IGT.Functional annotation of genes that are potentially regulated by the miRNAs implicated showed that signal transduction pathways (PI3K-Akt, MAPK, HIF-1, cAMP, FoxO, ErbB, Ras, Rap1 and insulin resistance); carbohydrate metabolism; glycan biosynthesis and metabolism, cell communication, cell growth and death; immune system; endocrine system and metabolic diseases are likely involved in the development of hyperglycaemia in this population.\t\n\nA number of miRNAs such as the let-7 family, 30ep-5p [26,31,32] found in this study and others have been shown to be involved in these pathways.These miRNAs have be reported to exert their function by suppressing the expression of insulin receptor genes [17,32].Although many similarities were found between this study and others, our study is unique for uncovering that some of these miRNAs were differentially expressed between diabetic and non-diabetic dysglycaemia.Indeed, using OGTT to characterise asymptomatic participants, we identified three miRNAs that potentially distinguish between diabetic and non-diabetic hyperglycaemia.For example, miR-126-3p, and miR-28-3p were upregulated in IGT when compared to screen-detected DM, whilst miR-486-5p was down-regulated in screen-detected DM in comparison to either IGT or NGT.miR-126 is expressed by cells that modulate inflammatory response and vascular homeostasis through enhanced production of anti-inflammatory chemokines, and has been shown to be reduced in T2DM [33][34][35][36][37].The downgrelation of miR-126 has been shown to be mostly pronounced in poorly controlled T2DM and in T2DM with complications when compared to sujects with T2DM without complication [38].Similarly, in a study that investigated miR-126 in serum of DM patients with varying degrees of retinopathy, miR-126 was reduced in patients versus the controls, but lowest in patients with proliferative diabetic retinopathy [39].Taken together, our findings of upregulated miR-126 and others in IGT versus screen-detected DM most probably point towards a cascading reduction with respect to diabetes related complications suggesting a potential role for miR-126 in distinguishing prediabetes from diabetes.Indeed, Liu et al [40]), examined the usefulness of miR-126 in predicting prediabetes and T2DM and reported lower levels in T2DM compared to prediabetes, even though both were significanlty lower than in healthy controls.It is important to note that a number of miRNAs including novel ones with potential to distinguish between hyperglycaemia and normal glucose tolerance were uncovered in the current study.For example, miR-hsa-miR-1299 had the highest fold change in IGT versus controls and was not detected in individuals with DM, whilst mir-novel-chr2_55842 was amongst the 10 th most differentially expressed in IGT only.In hepato-hepatocellular carcinoma, miR-1299 inhibits cell proliferation by targeting cyclin-dependent kinase 6, [41] however there is limited information about miR-1299 in diabetes.Therefore, further studies are needed to elucidate the molecular mechanisms of miR-1299 and other novel miRNAs identified in this study.\t\n\nSome of the dysregulated miRNAs found in our study corroborate findings of many other studies that have aimed to characterize miRNAs in different tissue types of individuals with DM and/or prediabetes.A recent systematic study of dysregulated miRNAs in T2DM identified a total of 158 dysregulated miRNAs in adipose, islet, skeletal muscle, whole blood, PBMC, plasma and serum [26].Similarly we found 36 (23%) of these miRNAs dysregulated in T2DM and IGT (Supplementary Table 4).Furthermore, three additional miRNAs (miR-27b, miR-98, and miR-21) previously reported to be dysregulated in mixed ethnic ancestry women with IGT or T2DM [27] were also differentially expressed in screen-detected DM in our sample.The miRNAs found in the current study and others have been shown to play a direct role in insulin production and secretion [21][22][23][24][25]28].This was confirmed by bioinformatics techniques we applied to identify the potential biological functions affected by the miRNA signatures.p53 signaling, PI3K/ Akt, p53 signaling and MAPK were respectively the 2 nd , 3 rd and 6 th targeted significant pathways in enrichment analysis by KEGG.The PI3K/Akt/ and MAPK pathways plays a major signaling role in the cellular response to extracellular stimuli, including glucose homeostasis, cell proliferation and survival [29].In glucose homeostasis,   the activation of these pathways is directly under the control of insulin receptors upon insulin stimulation [30].\t\nEarly identification of individuals with elevated risk of developing diabetes mellitus, followed by the implementation of effective prevention interventions can delay the onset of the disease and related complications.In this regard, recent studies have shown that miRNAs are useful as early markers of certain disease types, including diabetes.We used high throughput sequencing to assess miRNA expression profiles from whole blood of 12 individuals with screen-detected diabetes, 12 with prediabetes and 12 with normal glucose tolerance, matched for age, blood pressure, smoking and body mass index.We identified a total of 261 (57 novel) differentially expressed miRNA profiles between the study groups.Comparison of the miRNA expression profiles between prediabetess and diabetes revealed 25 common miRNA, but highlighted some interesting differences.For instance, three miRNAs (miR-126-3p, miR-28-3p miR-486-5p) were dysregulated in prediabetes compared to screen-detected diabetes.Target gene analysis showed thousands of potential genes and KEGG pathway analysis revealed 107 significant pathways of which some are involved signal transduction, cell-cell communications, cell growth and death, immune response, endocrine system and metabolic diseases.This first detailed African study has shown both known and novel differentially expressed miRNAs in relation to glucose tolerance.\t\n\nEarly identification of individuals with elevated risk of developing diabetes mellitus, followed by the implementation of effective prevention interventions can delay the onset of the disease and related complications.In this regard, recent studies have shown that miRNAs are useful as early markers of certain disease types, including diabetes.We used high throughput sequencing to assess miRNA expression profiles from whole blood of 12 individuals with screen-detected diabetes, 12 with prediabetes and 12 with normal glucose tolerance, matched for age, blood pressure, smoking and body mass index.We identified a total of 261 (57 novel) differentially expressed miRNA profiles between the study groups.Comparison of the miRNA expression profiles between prediabetess and diabetes revealed 25 common miRNA, but highlighted some interesting differences.For instance, three miRNAs (miR-126-3p, miR-28-3p miR-486-5p) were dysregulated in prediabetes compared to screen-detected diabetes.Target gene analysis showed thousands of potential genes and KEGG pathway analysis revealed 107 significant pathways of which some are involved signal transduction, cell-cell communications, cell growth and death, immune response, endocrine system and metabolic diseases.This first detailed African study has shown both known and novel differentially expressed miRNAs in relation to glucose tolerance.\t\n\nOverall, in addition to complementing earlier studies on miRNAs in prediabetes and diabetes, our findings provide evidence of known and novel differentially expressed miRNAs in African mixed ancestry individuals with IGT and screen-detected DM.We further observed that the aberrant expression profiles of miRNAs were linked to several biological processes, such as signal transduction, cell-cell communications, cell growth and death, immune response, endocrine system and metabolic diseases.Larger prospective studies in this and other racial populations from Africa are needed to characterize the molecular mechanisms of African-specific differentially expressed miRNAs, as well as assess their potential to predict worsening of glucose tolerance status.\t\n\nDespite the growing evidence of the important role and potential diagnostic value of miRNAs in dysglycaemia, such properties are yet to be demonstrated in the African setting.Therefore, in the present study we aimed to identify dysregulated miRNA in a South African mixed ancestry population previously reported to be at high risk of diabetes [18].To avoid potential bias from treatment induced alterations in miRNA expression, we focused on individuals with normal glucose tolerance (NGT), prediabetes individuals with IGT only and those with screen-detected diabetes who had not initiated glucose lowering drug treatment.",
      "\t\n\nSome recently-identified miRNAs have been associated with insulin secretion, insulin resistance, and inflammation, and differences have emerged in some circulating miRNA levels between individuals with and without type 2 diabetes (40).Zhao and others (41) examined some miRNAs in pregnant women at 16-19 weeks of gestation (WG), finding a significantly lower expression of 3 miRNAs (miR-29a, miR-132 and miR222) in women who went on to develop GDM at 24-28 WG than in those who did not develop GDM.MiR-29 plays a part in glucose homeostasis: its overexpression inhibits insulinstimulated glucose uptake and downregulates gluconeogenesis (42).MiR-132 targets the insulin-mediated regulation of cytochrome P450 (which is involved in hepatic metabolism), and it has a role in trophoblast expansion (its reduced expression impairs normal trophoblast development) (42,43).MiR-222 is involved in regulating the cell cycle (controlling the cyclindependent kinase inhibitor).",
      "\t\n\nUpon further epigenetic regulatory elements in diabetes, micro-RNAs, such as miR-15a and miR-29b, were found to be downregulated in type 2 diabetes, whereas miR-27a and miR-320a were upregulated and might open the possibility for new diagnostic markers [187, [231][232][233].",
      "\t\n\nIn addition to predicting targets of the differentially expressed miRNAs in T2DMED based on a literature review, IGF-1, as one of the target genes of miR-18a or miR-206, was confirmed via luciferase assay.T2DMED rats with downregulation of IGF-1 in their CCs have been reported (El-Sakka et al. 1999).In experiments with human diabetic erectile tissue, researchers also found a decreased expression of IGF-1, which was mainly located in the layers of smooth muscle cells (Castela et al. 2012).In this study, we also verified this reduction via ELISA.IGF-1 is essential to the regeneration of NOS-containing nerve fibres in the dorsal and intracavernosal nerves (Jung et al. 1999).Intervention of IGF-1 expression in the penis could ameliorate ED in T2DMED rats (Pu et al. 2007).Thus, miR-18a and/or miR-206 suppression of IGF-1 may be an interesting research direction for T2DMED.\t\n\nThe genes regulated by the four miRNAs relate to several KEGG pathways which might be involved in the mechanisms of T2DMED\t\n\nexpression of miR-18a, miR-206, miR-122, and miR-133   were confirmed by qRT-PCR (p < 0.05 and FDR <5 %).According to bioinformatic analysis, the four miRNAs were speculated to play potential roles in the mechanisms of T2DMED via regulating 28 different genes and several pathways, including apoptosis, fibrosis, eNOS/cGMP/ PKG, and vascular smooth muscle contraction processes, which mainly focused on influencing the functions of the endothelium and smooth muscle in the CC.IGF-1, as one of the target genes, was verified to decrease in the CCs of T2DMED animals via ELISA and was confirmed as the target of miR-18a or miR-206 via luciferase assay.Finally, these four miRNAs deserve further confirmation as biomarkers of T2DMED in larger studies.Additionally, miR-18a and/or miR-206 may provide new preventive/therapeutic targets for ED management by targeting IGF-1.\t\nexpression of miR-18a, miR-206, miR-122, and miR-133   were confirmed by qRT-PCR (p < 0.05 and FDR <5 %).According to bioinformatic analysis, the four miRNAs were speculated to play potential roles in the mechanisms of T2DMED via regulating 28 different genes and several pathways, including apoptosis, fibrosis, eNOS/cGMP/ PKG, and vascular smooth muscle contraction processes, which mainly focused on influencing the functions of the endothelium and smooth muscle in the CC.IGF-1, as one of the target genes, was verified to decrease in the CCs of T2DMED animals via ELISA and was confirmed as the target of miR-18a or miR-206 via luciferase assay.Finally, these four miRNAs deserve further confirmation as biomarkers of T2DMED in larger studies.Additionally, miR-18a and/or miR-206 may provide new preventive/therapeutic targets for ED management by targeting IGF-1.\t\n\nIn conclusion, for the first time, we reported the differentially expressed miRNAs in a classical murine model of T2DMED.Four differentially expressed miRNAs (miR-18a, miR-206, miR-122 and miR-133) were confirmed by qRT-PCR and are speculated to play crucial roles in influencing the functions of the endothelium and smooth muscle via regulating 28 different genes and several pathways, including apoptosis, fibrosis, eNOS/cGMP/PKG, and vascular smooth muscle contraction processes.IGF-1, as one of the target genes, was verified to decrease in the CCs of T2DMED animals and was confirmed as the target of miR-18a or miR-206 via luciferase assay.These four miRNAs deserve further confirmation as biomarkers of T2DMED in larger studies and may provide new perspectives for understanding the molecular aetiology of T2DMED in the future.Particularly, miR-18a and/or miR-206 may provide new preventive/therapeutic targets for ED management by targeting IGF-1.",
      "\t\n\nRecent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell.MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis.We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility.We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescenceactivated cell sorting.In total, 366 miRNAs were found to be expressed (i.e..100cumulative reads) in islets and 346 in betacells; of the total of 384 unique miRNAs, 328 were shared.A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e..50% of all reads seen across the tissues) in islets.Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g.miR-27b-3p, miR-192-5p)  have not previously been described in the context of islet biology.As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites.We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values ,0.01, q-values ,0.1).At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants.In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis.\t\nRecent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell.MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis.We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility.We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescenceactivated cell sorting.In total, 366 miRNAs were found to be expressed (i.e..100cumulative reads) in islets and 346 in betacells; of the total of 384 unique miRNAs, 328 were shared.A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e..50% of all reads seen across the tissues) in islets.Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g.miR-27b-3p, miR-192-5p)  have not previously been described in the context of islet biology.As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites.We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values ,0.01, q-values ,0.1).At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants.In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis.",
      "\t\n\nFigure 4. Candidate miRNA regulatory hubs in a type 2 diabetes gene network. (A) Each data point represents a 59-reference miRNA or a 59-shifted isomiR from primary human beta cells, and the y-axis shows the negative Log2 of the p-value of the predicted miRNA targeting score among genes in a type 2 diabetes (T2D) network.The dashed red line denotes the significance threshold (empirical P = 0.05). (B) Effects of miR-29 mimic and inhibitor in MIN6 cells on the mRNA levels of four T2D genes are shown.The x-axis lists the gene symbols for each of four predicted miR-29 target genes and the y-axis depicts the relative quantitative value (RQV; expression determined by RT-qPCR and normalized to Rps9) in response to the miR-29 mimic (blue) or the miR-29 inhibitor (red) relative to mock transfection.The data shown represent at least two independent experiments, each conducted in triplicate.P-values were calculated based on Student's t-tests. *, P,0.05; **, P,0.01.doi:10.1371/journal.pone.0073240.g004\tCandidate 59-shifted isomiR Regulatory Hubs in Type 2 Diabetes\n\nGenome-wide association studies for type 2 diabetes (T2D) have primarily (though not exclusively) implicated genes with critical function in the pancreatic beta cell [45,46].Therefore, we sought to determine if any of the highly expressed human beta cell miRNAs, including 59-shifted isomiRs, serve as regulatory hubs in T2D.We first assembled a list of genes (n = 92) implicated in T2D and related conditions including maturing onset diabetes of the young (MODY) (Methods).We then implemented a Monte Carlo simulation strategy (Methods) to determine for each miRNA whether the predicted regulatory impact on T2D genes is significantly (uncorrected P,0.05) greater than expected by chance (such miRNAs are termed ''candidate regulatory hubs'').We identified 10 candidate miRNA regulatory hubs (Fig. 4A; Table S3 in File S2).The top two were the 59-reference miRNAs miR-29 and let-7, both of which have been implicated in beta cell function and glucose homeostasis [47][48][49].Though miR-29 has been shown to regulate glucose-stimulated insulin secretion, its target genes in the beta cell are largely unknown.To validate the in silico approach, we selected several predicted targets (Camk1d, Glis3, and Jazf1), and one previously validated target (Slc16a1 [48]), of miR-29 from among the T2D gene list for evaluation in MIN6 cells.Specifically, we transiently transfected MIN6 cells with a miR-29 mimic or inhibitor (antagomiR) and measured the mRNA levels of each of the four genes by real-time quantitative PCR (RT-qPCR).Three of the four genes were significantly (p,0.05) down regulated by the over-expression of miR-29 and three genes were significantly (p,0.05) up regulated by the antagomiR-mediated inhibition of miR-29 (Fig. 4B).These findings are consistent with previous reports that miR-29 is involved in the regulation of beta cell function [48,50], and they serve as a validation of the in silico regulatory hub analysis.",
      "\t\n\nFigure 2. miRNA expression profile changes in T2D compared with control subjects using the Exiqon chip platform and TaqMan confirmation (FDR <10%). (a) Data are plotted to show the pattern of change of these significantly up-/down-regulated miRNA.Black lines represent those miRNA that increase/decrease progressively with IGT and T2D (DM), green lines represent miRNAs that are increased/decreased with IGT and then revert with T2D, while orange lines show miRNAs increased/decreased only in the T2D state. (b) miRNAs that show the expression profile during myocyte differentiation (cell data derived from Chen et al. [55]) is the opposite pattern to that observed in the muscle of patients with T2D (green = down-regulated probe sets, red = up-regulated probe sets; the color range is from -3-fold to +3-fold change).MG refers to the data produced by Chen et al. during myogenesis. (c) Expression level of miR-1, miR-133a, miR-133b and miR-206 in muscle biopsies from healthy individuals (NGT, n = 10, white bars), individuals with impaired glucose tolerance (IGT, n = 10, grey bars) and individuals with type 2 diabetes (T2D, n = 10, black bars).miR-133a (P < 0.001) and miR-206 (P = 0.04) were significantly reduced in T2D patients when compared with expression levels in healthy controls.Data are expressed as fold change from NGT and shown as mean  standard error. **P < 0.001, *P < 0.05. (d) Expression level of miR-133a in muscle versus indices of glucose homeostasis in subjects with and without T2D.Expression of miR-133a is positively correlated with fasting glucose, R 2 = 0.41 (P < 0.001, n = 30).Data are shown as Ct levels normalized to RNU48 and plotted versus fasting glucose levels (mmol/L).",
      "\t\n\nT2D loci were also identified at clusters of noncoding RNAs with roles in islet  cell function.One locus includes a set of microRNAs specifically expressed in islet  cells, the maternally expressed noncoding RNA MEG3, and the paternally expressed gene DLK1.Targets of these microRNAs increase  cell apoptosis 40 , and reduced Meg3 expression impairs insulin secretion 41 .DLK1 inhibits adipocyte differentiation, thereby protecting against obesity 3 , and promotes pancreatic ductal cell differentiation into  cells, increasing insulin secretion 42,43 .Other variants near MEG3 have been associated with type 1 diabetes 44 (EAS and EUR LD r 2 = 0 with EAS lead variant).The other noncoding RNA locus is the MIR17HG cluster of miRNAs, which regulate glucose-stimulated insulin secretion and pancreatic  cell proliferation stress 45 ; one of these microRNAs, miR-19a, affects hepatic gluconeogenesis 46 .Yet another T2D locus is located near TRAF3, which is a direct target of the MIR17HG microRNA cluster and promotes hyperglycaemia by increasing hepatic glucose production 47,48 .The T2D association results suggest that these noncoding RNAs influence disease susceptibility."
    ],
    [
      "\tConclusion\n\nIn our sequencing study involving 6888 individuals, 2.2% of individuals with early onset diabetes and 0.7% of individuals with late onset diabetes harbored a likely pathogenic mutation in monogenic diabetes genes.Our results confirm previous reports that MODY is under-diagnosed [19,75], particularly in individuals presenting with early onset diabetes and clinically labeled as T2D and, in such cases, genetic testing can provide an etiological diagnosis.With the continuing reduction in costs of DNA sequencing, genetic screening of all known monogenic diabetes genes in individuals with early onset diabetes should be routinely considered since it can identify individuals with undiagnosed MODY as well as atypical forms of monogenic diabetes.Knowledge of mutations in monogenic diabetes genes has the potential to influence diagnosis and therapy for individuals with diabetes as well as to enable the genetic testing of relatives.",
      "\tConclusions\n\nGenomics research in monogenic diabetes and the implementation of NGS-based approaches for precision diagnosis of MODY subtypes undoubtedly move the physicians and patients towards the era of precision genomic medicine that takes into account the individual genetic data.Specific issues are emerging such as the right estimate of variant pathogenicity and age-dependent penetrance, the multi-genic causality, and the composite phenotypes.Lessons learned from MD with recent findings in common T2D genetic architecture support a continuum of diabetes phenotypes from rare monogenic to common adult-onset diabetes which impacts the strategies for both diagnosis and longitudinal investigation of diverse clinical subtypes along the life course.Beyond facing youngonset diabetes, practitioners should systematically promote a comprehensive genetic testing of MD-MODY subtypes, with benefits of optimal patient care and of strong reduction of global medical costs.\t\nPurpose of Review Non-autoimmune monogenic diabetes (MD) in young people shows a broad spectrum of clinical presentations, which is largely explained by multiple genetic etiologies.This review discusses how the application of state-of-the-art genomics research to precision diagnosis of MD, particularly the various subtypes of maturity-onset diabetes of the young (MODY), has increasingly informed diabetes precision medicine and patient care throughout life.Recent Findings Due to extended genetic and clinical heterogeneity of MODY, diagnosis approaches based on next-generation sequencing have been worthwhile to better ascribe a specific subtype to each patient with young-onset diabetes.This guides the best appropriate treatment and clinical follow-up.Summary Early etiological diagnosis of MD and individualized treatment are essential for achieving metabolic targets and avoiding long-term diabetes complications, as well as for drastically decreasing the financial and societal burden of diabetesrelated healthcare.Genomic medicine-based practices help to optimize long-term clinical follow-up and patient care management.\t\n\nPurpose of Review Non-autoimmune monogenic diabetes (MD) in young people shows a broad spectrum of clinical presentations, which is largely explained by multiple genetic etiologies.This review discusses how the application of state-of-the-art genomics research to precision diagnosis of MD, particularly the various subtypes of maturity-onset diabetes of the young (MODY), has increasingly informed diabetes precision medicine and patient care throughout life.Recent Findings Due to extended genetic and clinical heterogeneity of MODY, diagnosis approaches based on next-generation sequencing have been worthwhile to better ascribe a specific subtype to each patient with young-onset diabetes.This guides the best appropriate treatment and clinical follow-up.Summary Early etiological diagnosis of MD and individualized treatment are essential for achieving metabolic targets and avoiding long-term diabetes complications, as well as for drastically decreasing the financial and societal burden of diabetesrelated healthcare.Genomic medicine-based practices help to optimize long-term clinical follow-up and patient care management.\tIntroduction\n\nMaturity-onset diabetes of the young (MODY), a dominantly inherited familial form of diabetes typically diagnosed before 25 years of age in non-obese subjects, represents the most frequent subgroup of early-onset non-autoimmune diabetes [1,2].MODY is a monogenic disease but with a high clinical and genetic heterogeneity, although always caused by a primary inherited or de novo genetically induced defect in insulin secretion responsible for chronic hyperglycemia.This pathophysiological feature common to all MODY cases arises from a functional impairment of one of the diverse pancreatic -cell expressed key regulators of insulin biosynthesis and secretion [2,3].More than fifteen MODY genetic subtypes have been characterized raising the issue of an accurate etiological genetic diagnosis at an early age enabling a genuine personalized medicine of diabetes.MODY patients are usually diagnosed under the age of 25-30 years, but overt diabetes or moderate chronic hyperglycemia can happen at any age from childhood to young adulthood or at later age.The broad range of phenotypic features and variability in the clinical presentations are largely dependent on the underlying genetic defect that actually determines both pathophysiology and long-term progression of diabetes.\t\n\nIn this review, we highlight the recent advances in the field of genomics of monogenic diabetes (MD) with the current challenges of accurately defining and recognizing the various MODY subtypes and of translating molecular diagnosis into personalized care over the lifetime.\t\n\nThe known genetic causes of MODY have pointed out major pancreatic -cell expressed genes regulating insulin secretion, such as alterations in GCK and a network of transcription factors important for the control of -cell function.Recent works have further provided new clues for better understanding specific functional mechanisms related to MODY genetic defects.\tA Global View on MODY Genetics\n\nClinical Heterogeneity and Genetic Subtypes of MODY More than 25 years of comprehensive investigation of MODY genetic components, through the study of patient cohorts and multiplex families, have provided great advances in the knowledge and functional characterization of major MODY genes with mostly various protein-coding changes.So far, at least 15 genes causing MODY, involving different mutation types, have been formally identified (details on these genes are given in Table 1).In these genes, a single, mostly highly penetrant, rare mutation is sufficient to cause a MODY phenotype.The major MODY genes encode pancreatic -cell expressed proteins involved in developmental processes, in the maturation and maintenance of cell function (through transcription factors regulating the transcriptional network of pancreatic -cells), in the control of -cell glucose sensing (through the glucokinase enzyme), in -cell signaling, and in insulin production and secretion [2].From our current knowledge of the underlying pathogenic mechanisms, it is well substantiated that MODY-causing mutations cluster into key genes and interconnected biological pathways that represent core regulatory networks for pancreatic -cell identity and function (as for -cell transcriptional network, or regulatory proteins of reticulum endoplasmic homeostasis) [14].Along the same line, -cell dysfunction is the main driver of MODY, together with decreased -cell mass and cellular death.",
      "\tU N C O R R E C T E D A C C E P T E D A R T I C L E BACKGROUND\n\nMaturity-onset diabetes of the young (MODY) is a monogenic form of diabetes mellitus characterised by autosomal dominant inheritance, a young age of onset (often diagnosed before 25 years of age) and pancreatic -cell dysfunction (MODY; MIM# 606391) (Fajans and Bell, 2011;Hattersley, 1998;Molven and Njolstad, 2011;Tattersall, 1974).Heterozygous mutations in the genes encoding the glycolytic enzyme glucokinase (Froguel, et al., 1992;Hattersley, et al., 1992) and the transcription factors, hepatocyte nuclear factor (HNF)-1 alpha (HNF1A; MIM# 142410) (HNF1A MODY, formerly MODY3) (Yamagata, et al., 1996a), HNF-4 alpha (HNF4A; MIM# 600281) (HNF4A MODY, formerly MODY1) (Yamagata, et al., 1996b) and HNF1B (formerly MODY5) (Horikawa, et al., 1997) have been shown to cause MODY.A distinct clinical phenotype is associated with each genetic aetiology (Edghill, et al., 2006;Stride and Hattersley, 2002).Mutations in the genes pancreatic and duodenal homeobox 1 (PDX1) (Stoffers, et al., 1997), NEUROD1 (Malecki, et al., 1999), CEL (Torsvik, et al., 2010), KCNJ11 (Yorifuji, et al., 2005) INS (Edghill, et al., 2008), and ABCC8 (Bowman, et al., 2012) are rare causes of autosomal dominant diabetes.Other potential forms of MODY include mutations in the transcription factor genes KLF11 (Neve, et al., 2005), PAX4 (Plengvidhya, et al., 2007) and BLK (Borowiec, et al., 2009), but the identification of additional families showing co-segregation of mutations with diabetes is required to confirm these as \"MODY genes\".",
      "\tIntroduction\n\nMaturity onset diabetes of the young (MODY) is the most common monogenic subtype of diabetes that is characterized by an early-onset of diabetes, no requirement for insulin at diagnosis, and no signs of autoimmunity or insulin resistance [1] .MODY is inherited in an autosomal dominant manner.It is a clinically heterogeneous group of disorders caused by -cell dysfunction.It is estimated that MODY accounts for up to 1.8% of patients with diabetes [2] .Mutations in 13 genes are known to cause MODY; the most prevalent are HNF1A , GCK and HNF4A [3,4] .The MODY subtypes differ in age of onset of diabetes, the pattern of hyperglycemia, response to treatment, and associated extrapancreatic manifestations [5] .As compared to type 2 diabetes, the clinical symptoms present often at a relatively young age in patients without overweight, who have a positive family history.As compared to type 1 diabetes, progression may be less severe, and the required dosage of insulin low.",
      "\tCANDIDATE GENES IDENTIFIED IN HUMAN AND RODENT MODELS OF T2D\n\nMaturity onset diabetes of the young Foremost among the monogenic forms of T2D is MODY.The early age of onset and autosomal dominant pattern of inheritance have facilitated gene identication in the majority of MODY families through classical Mendelian positional cloning approaches, as described in Chapter 4.",
      "\tMaturity Onset Diabetes of the Young (MODY)\n\nIn 1960, Fajans & Conn (50) first described maturity-onset diabetes of the young (MODY).MODY is characterized clinically by autosomal dominant transmission, early onset (usually before the age of 25 years), the correction of fasting hyperglycemia without insulin for at least two years following diagnosis, and nonketotic disease (49).Thus, the main distinguishing features compared to more typical cases of T2D include a strong family history (typically spanning several generations), a younger age of onset, and the absence of obesity.The familial pattern of inheritance and lack of requirement for insulin therapy to prevent ketosis distinguish MODY clinically from T1D. MODY usually presents as asymptomatic hyperglycemia in young adults and often has a mild course.Some patients, however, progress rapidly and require insulin therapy, and microvascular and renal complications can ensue.",
      "\t\n\n1 Genetic causes of maturity-onset diabetes of the young A BLK, PAX4 and KLF11, although classified as MODY genes (#11, #9, and #7 respectively) in OMIM, are not listed as MODY-causing because of recently disputed or refuted gene-disease relationships (see section \"Rare types of MODY\").APPL1 was proposed as MODY14 based on two families reported in 201533, but evidence is otherwise limited.RFX6 does not have a MODY number in OMIM, but is included here as multiple loss-of-function variants were recently implicated in a phenotype very similar to that of other MODY genes but with lower penetrance 11 .OHA: Oral Hypoglycemia Agents",
      "\tMaturity\n\n-onset diabetes of the young (MODY) is a heterogeneous single gene disorder characterized by non-insulin-dependent diabetes, an early onset and autosomal dominant inheritance.Mutations in six genes have been shown to cause MODY.Approximately 15-20% of families fitting MODY criteria do not have mutations in any of the known genes.These families provide a rich resource for the identification of new MODY genes.This will potentially enable further dissection of clinical heterogeneity and bring new insights into mechanisms of -cell dysfunction.To facilitate the identification of novel MODY loci, we combined the results from three genome-wide scans on a total of 23 families fitting MODY criteria.We used both a strict parametric model of inheritance with heterogeneity and a model-free analysis.We did not identify any single novel locus but provided putative evidence for linkage to chromosomes 6 (nonparametric linkage [NPL]score 2.12 at 71 cM) and 10 (NPL score 1.88 at 169 -175 cM), and to chromosomes 3 (heterogeneity LOD [HLOD] score 1.27 at 124 cM) and 5 (HLOD score 1.22 at 175 cM) in 14 more strictly defined families.Our results provide evidence for further heterogeneity in MODY.Diabetes 52:872-881, 2003 M aturity-onset diabetes of the young (MODY) is characterized by -cell dysfunction, no requirement for insulin in the first years of the disease, an autosomal dominant mode of inheritance, and an early age at onset of diabetes (25 years) ( 1).The identification of MODY genes has helped explain the phenotypic heterogeneity associated with the disorder.MODY is a genetically diverse subgroup of diabetes, and to date six distinct MODY genes have been identified: these encode the glycolytic enzyme glucokinase (GCK) (2,3), hepatocyte nuclear factor (HNF)-1 (4), HNF-1 (5), HNF-4 (6), insulin promoter factor (IPF)-1 (7), and NeuroD1/BETA2 (8).The relative distribution of MODY1-6 depends on the population investigated, although in all studies mutations in GCK and HNF1 are the two most prevalent forms (9 -11).Mutations in each gene result in distinct clinical and physiological characteristics (12).Glucokinase mutations present with stable mild fasting hyperglycemia throughout life as a result of reduced glucose sensing in the -cell (13).In contrast, mutations in the transcription factors (HNF-1, HNF-4, HNF-1, and IPF-1) cause a progressive -cell failure that may become severe (14).",
      "\tTypes of monogenic diabetes\n\nMaturity-onset diabetes of the young MODY comprises most monogenic diabetes cases, with classical characteristics of young diagnosis age, family history of diabetes in an autosomal dominant pattern of transmission, and insulin independence, with some types having additional features (Table 1).While 14 genes have now been designated as MODY genes in OMIM and/or the literature, three of these (BLK, PAX4, and KLF11) have been proposed for elimination based on a recent study (10) (see Table 1 for the remaining 11 along with RFX6, recently proposed as an additional MODY gene; ref . 11).Variants in GCK, HNF1A, and HNF4A are responsible for most MODY cases, followed by HNF1B (12).Given the known genetic etiology of  (42), but evidence is otherwise limited.RFX6 does not have a MODY number in OMIM, but is included here as multiple loss-of-function variants were recently implicated in a phenotype very similar to that of other MODY genes but with lower penetrance (11).OHA, oral hypoglycemia agents.",
      "\t\n\nThere is now clear evidence of a strong genetic component to the disease due to prevalence differences between racial groups, a higher concordance rate among monozygotic than dizygotic twins and a sibling risk ratio of approximately 3.5 [119].Maturity-onset diabetes of the young (MODY) is the autosomal dominantly inherited form of diabetes without insulin dependency, characterized by -cell dysfunction and is diagnosed at a relatively young age (<25 years) [120,121].MODY is made up of subtypes defined on the basis of genetic etiology.These genetic subtypes have aided the identification of patients who will respond to a given therapy from those who are unlikely to respond.As such, this opens the possibility of tailored drug therapy both at the individual level for MODY and for the general treatment of T1D and T2D as a whole.Identifying further forms of this monogenic diabetes will provide crucial insights into patterns of -cell dysfunction and the associated therapeutic response.Of the seven MODY genes identified to date, the most common forms present as a consequence of mutations in the genes encoding the glycolytic enzyme, glucokinase, and the transcription factor, hepatic nuclear factor-1 (HNF1) [122,123].",
      "\t\n\nMaturity-onset diabetes of the young (MODY) is a rare, autosomal dominant form of diabetes.There are six primary forms of MODY, each a consequence of mutations in six different genes [37].In addition to the autosomal dominant inheritance, MODY is characterized by onset before the age of 25 and -cell dysfunction typically in the absence of insulin resistance or obesity.MODY3 arises from mutations in the hepatocyte nuclear factor 1 homeobox A gene (HNF1A), and patients with this disease are hyper-sensitive to the hypoglycemic effects of sulfonylureas [38].In an early case study, Pearson et al. [39] identified three MODY3 patients with HNF1A mutations, in whom cessation and reintroduction of sulfonylureas caused dramatic changes in HbA1c levels, or severe hypoglycemia, in response to introduction of sulfonylureas into the treatment regimen.A subsequent study found that MODY3 patients had a 5.2-fold or 3.9-fold greater response to gliclazide compared to metformin or patients with T2D, respectively [40].These patients also had a stronger insulin secretory response to tolbutamide and were more insulin-sensitive compared to individuals with common T2D [40].",
      "\t\n\nBoth genetic susceptibility and environmental drivers, notably obesity and sedentary lifestyles, determine the overall risk of T2D (4)(5)(6).Supporting a genetic component, rare monogenic forms of the disease exist with Mendelian inheritance (7,8).Thus, maturity onset of diabetes of the young (MODY) is a rare form of diabetes with mutations often residing in exons encoding the functional domains of transcription factors such as hepatocyte nuclear factor hepatocyte nuclear factor 1 homeobox A (HNF1A) (9) and HNF4A (10), or of proteins involved in b cell glucose metabolism such as glucokinase (GCK) (11) (Table 1).",
      "\tIntroduction\n\nThe maturity onset diabetes of the young (MODY) is a monogenic form of diabetes characterized by an autosomal dominant inheritance; the onset usually happens before the 25 years of age and is characterized by an impaired insulin secretion with minimal or no defect of the insulin action (Fajans and Bell 2001).Some studies suggest that 1-2% of patients with type 2 diabetes (T2D) may in fact have MODY (Shields et al. 2010).Data available suggest that people carrying one mutated allele are born with completely normal physiological and biochemical functions of the pancreatic b-cells, and diabetes will occur at some stage during adolescence (Bell and Polonsky 2001;Fajans and Bell 2001).Penetrance of diabetes in patients with mutations in MODY is quite high (more than 95% by the age of 55 years) (Frayling et al. 2001;Murphy et al. 2008).Recent studies have demonstrated heterozygous mutations in genes encoding 11 forms of MODY, including the hepatocyte nuclear factor-4a encoding the gene (HNF4A)(MODY 1), the glucokinase gene or GCK (MODY 2), the hepatocyte nuclear factor-1a that encodes HNF1A (MODY 3), the pancreas/duodenum homeobox protein 1 (PDX1, also known as IPF-1) (MODY 4), the hepatocyte nuclear factor-1b encoding the gene HNF1B (MODY 5), the neurogenic differentiation 1 that encodes the gene (NEUROD1)(MODY 6), the Kruppel-like factor 11 (KLF11) (MODY 7), the carboxylester lipase encoding the gene (CEL) (MODY 8), the paired box gene 4 (PAX4) (MODY 9), insulin gene (INS) (MODY 10), the tyrosine kinase B-lymphocyte specific gene (BLK) (MODY 11), the potassium voltage-gated channel subfamily J member 11 (KCNJ11 gene) (MODY13), and the adapter protein containing PH domain, PTB domain and leucine zipper motif 1, also known as DCC-interacting protein 13-a encoded by the APPL1 gene (MODY14).Those cases of as yet unknown genetic derangement have been classified as MODYX (Online Mendelian Inheritance in Man [OMIM], MIM entry 606391).",
      "\t\n\nIn contrast, maturity-onset diabetes of the young (MODY) is a rare monogenic form of type 2 diabetes that has an autosomal dominant mode of inheritance.At least five different genes, located on chromosomes 20, 7, 12, 13, and 17, independently cause MODY within single pedigrees (5)(6)(7)(8)(9).MODY genes may also play a minor role in the common form of type 2 diabetes (10)."
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