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+{
+  "question": [
+    "How do genetic mutations in the insulin gene affect glucose metabolism?",
+    "What are the most common genetic loci associated with an increased risk of Type 2 diabetes?",
+    "How does genome-wide association studies (GWAS) help in identifying diabetes-related genes?",
+    "What is the role of the HLA region in the genetic predisposition to Type 1 diabetes?",
+    "How do genetic differences contribute to variations in diabetes prevalence among different populations?",
+    "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)?",
+    "What genes are most commonly associated with an increased risk of developing diabetes?",
+    "How can genetic testing help predict a person's risk for diabetes?",
+    "What role do family genetics play in the likelihood of getting diabetes?",
+    "Can lifestyle changes affect genetic risk factors for diabetes?",
+    "What recent breakthroughs have been made in understanding the genetic causes of diabetes?",
+    "How do genes influence how our bodies respond to sugar and insulin?",
+    "Are there specific genetic markers that can indicate a higher risk for Type 1 versus Type 2 diabetes?",
+    "How can new gene therapies potentially cure or treat diabetes?",
+    "What is the difference between monogenic and polygenic diabetes?",
+    "How does studying the DNA of people with diabetes help scientists find better treatments or cures?"
+  ],
+  "answer": [
+    "Genetic mutations in the insulin gene can significantly affect glucose metabolism in several ways:  1. Mutations that result in mutant insulin or the inability to convert proinsulin to insulin can lead to glucose intolerance. This is because the proper conversion and function of insulin are crucial for maintaining normal glucose levels in the blood [1].  2. Insulin gene mutations can cause early-onset diabetes, with marked differences in clinical presentation and metabolic status. These mutations can lead to the retention of insulin in the endoplasmic reticulum, causing stress and potentially leading to beta-cell apoptosis, which reduces insulin production and secretion [2], [10].  3. Insulin-deficient conditions, such as those caused by certain mutations, can lead to severe hyperglycemia, as insulin is a central hormone for maintaining glucose homeostasis. Without sufficient insulin, glucose cannot be effectively taken up by cells, leading to elevated blood glucose levels [5].  4. Some mutations may result in abnormal proinsulin folding, leading to an accumulation of misfolded proteins in the endoplasmic reticulum. This accumulation can cause endoplasmic reticulum stress and beta-cell apoptosis, further impairing insulin production and secretion [10].  Overall, genetic mutations in the insulin gene can disrupt normal insulin synthesis and function, leading to impaired glucose metabolism and conditions such as diabetes.",
+    "The most common genetic loci associated with an increased risk of Type 2 diabetes include:  1. **TCF7L2** [2], [5], [7] 2. **KCNJ11** [2], [5] 3. **PPARG** [2], [5] 4. **CDKAL1** [2], [5], [7] 5. **CDKN2A/CDKN2B** [2], [5], [7] 6. **IGF2BP2** [2], [5], [7] 7. **SLC30A8** [2], [5], [7] 8. **FTO** [2], [5] 9. **HHEX** [2], [5], [7]  These loci have been identified and replicated in multiple studies as being associated with an increased susceptibility to Type 2 diabetes.",
+    "Genome-wide association studies (GWAS) help in identifying diabetes-related genes by examining associations between a large number of single-nucleotide polymorphisms (SNPs) and the disease, such as type 2 diabetes mellitus (T2DM) [1]. GWAS have successfully identified genetic loci associated with T2DM, providing insights into the genetic risk factors and biological pathways underlying the disease [2], [4]. These studies have identified hundreds of SNPs associated with T2DM, which can uncover previously unexpected disease pathways and contribute significantly to our understanding of the genetics of diabetes [5], [9]. Additionally, meta-analyses of GWAS data have improved the ability to detect new loci by combining findings from multiple studies, thereby increasing statistical power [2], [10]. Despite challenges such as the modest effect sizes of individual variants and stringent significance thresholds, GWAS remain a powerful tool for identifying genetic loci for complex diseases like diabetes [7], [10].",
+    "The HLA region plays a significant role in the genetic predisposition to Type 1 diabetes. The major genetic susceptibility determinants for Type 1 diabetes have been mapped to the MHC class II genes, specifically HLA-DQB1 and HLA-DRB1 [7]. These genes are part of the highly polymorphic HLA class II genes, which play the most important single role in susceptibility to Type 1 diabetes [3]. The class II genes encoding HLA-DR and HLA-DQ, along with one or more additional genes within the HLA region, confer most of the genetic risk for Type 1 diabetes [4]. The contribution of HLA genes to Type 1 diabetes susceptibility accounts for about 44% of the genetic risk [6]. However, variation at these loci alone cannot explain all of the genetic association and linkage of the MHC with Type 1 diabetes, indicating that other genes within the MHC region may also affect Type 1 diabetes risk [3].",
+    "Genetic differences contribute to variations in diabetes prevalence among different populations in several ways:  1. **Genetic Heterogeneity**: Different genes may be responsible for the development of type 2 diabetes mellitus (T2DM) in different populations, indicating genetic heterogeneity. Even within the same ethnic group, different genes might be responsible for different subtypes of diabetes, such as those with predominating failure in insulin secretion or insulin resistance [3].  2. **Ethnicity-Specific Genetic Variants**: The pathogenesis of T2DM involves genetic variants in candidate genes, and these variants can show ethnicity-specific differences. The interactions between genes involved in insulin signaling and secretory pathways play a crucial role in determining an individual's susceptibility to T2DM [4].  3. **Single Nucleotide Polymorphisms (SNPs) and Haplotypes**: Minute genetic differences, such as SNPs and haplotypes, are used to explain patterns of disease between populations. These genetic markers are understood as the basis for biological differences between populations, which can affect diabetes prevalence [5].  4. **Risk Allele Frequencies**: Human populations exhibit substantial variation in risk allele frequencies, which contributes to different susceptibilities to diseases, including diabetes, among populations [7].  5. **Insulin Secretion Capacity**: In some populations, such as the Asian population, genetic influences on the prevalence of type 2 diabetes are mainly related to insulin secretion capacity. This suggests that genes associated with insulin secretion capacity are particularly relevant in contributing to ethnic differences in diabetes prevalence [10].  Overall, genetic differences, including variations in specific genes, SNPs, and risk allele frequencies, contribute to the observed variations in diabetes prevalence among different populations. These genetic factors interact with environmental and lifestyle factors to influence diabetes risk.",
+    "The PPAR-gamma gene encodes a transcription factor that plays a crucial role in regulating insulin sensitivity and lipid metabolism, which are important in the context of diabetes [4]. PPAR-gamma influences insulin sensitivity partly by modulating circulating adiponectin levels, with PPAR-gamma agonists known to increase these levels [1]. This gene is a target for the thiazolidinedione class of oral antidiabetic agents, which are used to improve insulin sensitivity in patients with type 2 diabetes [4].  Variants of the PPAR-gamma gene can significantly impact the risk and progression of type 2 diabetes. The Pro12Ala variant, for example, is a well-established genetic variant that modulates insulin sensitivity and increases the risk of type 2 diabetes [1], [4]. Other pathogenic PPARG variants, such as R194Q, A417V, R212W, P387S, M203I, and T356R, have been identified in patients with partial lipodystrophy and are associated with an increased risk of type 2 diabetes [7]. These variants can affect the gene's function in adipocyte differentiation and metabolism, thereby influencing the development of insulin resistance and type 2 diabetes [10].",
+    "CRISPR/Cas9 technology can be used to study or treat genetic forms of diabetes in several ways:  1. **Genome and Epigenome Editing**: CRISPR/Cas9 has revolutionized the ability to modify genomes and epigenomes, allowing researchers to target specific genes associated with Type 2 Diabetes (T2D) and manipulate cis-regulatory elements related to beta cell function and glucose homeostasis [1].  2. **Gene Knockout Studies**: CRISPR has been used to knock out genes by introducing frameshift mutations, which result in protein depletion. This approach has been adopted to study several genes in beta cell lines and human embryonic stem cell-derived beta cells, providing insights into the genetic basis of diabetes [4].  3. **Correction of Point Mutations**: CRISPR technology has been used to correct point mutations in patient-derived induced pluripotent stem cells (iPSCs) targeting diabetes-related gene defects. The most efficient method for this is CRISPR/Cas9-based homology-directed repair (HDR), which involves generating a Cas9-mediated cut near the mutation site and using a homologous donor template to introduce the intended nucleotide change [5].  4. **Disease Modeling**: CRISPR/Cas9 can be employed in human pluripotent stem cells (hPSCs) to model diabetes and metabolic syndromes in vitro. This allows researchers to study the disease mechanisms and test potential treatments in a controlled environment [3].  5. **Animal Models**: CRISPR/Cas9 has been used to create knockout and knock-in mouse models, such as leptin and leptin receptor knockout mice, which serve as tools for diabetes and obesity research. These models help in understanding the genetic factors contributing to diabetes and testing therapeutic interventions [7].  Overall, CRISPR/Cas9 technology provides a powerful platform for both studying the genetic underpinnings of diabetes and developing potential gene therapies to treat the disease.",
+    "Genetic polymorphisms in the GLUT4 gene have been studied to determine their significance in relation to Type 2 diabetes. However, according to the provided context, none of the identified polymorphisms in the GLUT4 gene have been linked to or found to be associated with Type 2 diabetes across various populations [1]. This suggests that, despite investigations, there is no established connection between GLUT4 gene polymorphisms and the susceptibility to Type 2 diabetes.",
+    "MicroRNAs (miRNAs) regulate gene expression related to diabetes by acting at the post-transcriptional level to control their target genes. They are involved in several crucial pathways associated with diabetes, including insulin secretion, cholesterol biosynthesis, fat metabolism, and adipogenesis [2]. miRNAs also play significant roles in pancreatic islet development, beta-cell dysfunction, insulin synthesis and secretion, and insulin resistance, which are key factors in the pathology of both Type 1 and Type 2 Diabetes Mellitus (T1DM and T2DM) [6]. Additionally, specific miRNAs have been implicated in the pathogenesis of diabetic complications, such as diabetic nephropathy, where miRNAs like miR-192, miR-216a, miR-217, and miR-377 are up-regulated [2]. These miRNAs can modulate the actions of growth factors and inflammatory factors, further influencing diabetic complications [5].",
+    "Studying the genetic basis of MODY (Maturity Onset Diabetes of the Young) has provided several important insights:  1. **Genetic Heterogeneity**: MODY is caused by mutations in multiple genes, with at least 13 known genes implicated. The most prevalent mutations occur in the genes HNF1A, GCK, and HNF4A [3]. This genetic diversity leads to different subtypes of MODY, each with distinct clinical characteristics such as age of onset, pattern of hyperglycemia, response to treatment, and associated extrapancreatic manifestations [3].  2. **Inheritance Pattern**: MODY is inherited in an autosomal dominant manner, which means that it can be passed down through families. This inheritance pattern allows for the collection of multigenerational pedigrees, making MODY an attractive model for genetic studies [2].  3. **Clinical Presentation**: MODY typically presents in young adults, often before the age of 25, and is characterized by primary insulin secretion defects. It is not related to obesity or autoimmune processes, distinguishing it from other forms of diabetes like type 1 and type 2 diabetes [5].  4. **Pathogenic Mechanisms**: Despite advances in understanding the molecular pathogenesis of MODY, there remain unknown genetic determinants in many patients with a MODY-like phenotype, suggesting additional locus heterogeneity and new pathogenic mechanisms yet to be discovered [4].  5. **Impact on Treatment and Diagnosis**: Genetic testing for MODY can lead to more accurate diagnoses and tailored treatment plans. Many patients with MODY are currently undiagnosed or misdiagnosed with type 1 or type 2 diabetes, highlighting the importance of genetic testing in identifying this condition [7].  These insights underscore the complexity and variability of MODY, as well as the importance of genetic research in improving diagnosis and treatment strategies for this form of diabetes.",
+    "The genes most commonly associated with an increased risk of developing diabetes, particularly type 2 diabetes, include:  1. **CDKAL1, CDKN2A, CDKN2B** - These genes are linked to reduced insulin secretion via reduced beta-cell mass [1]. 2. **MTNR1B, TCF7L2, KCNJ11** - These genes are associated with beta-cell dysfunction [1]. 3. **FTO** - This gene is related to increased insulin resistance associated with obesity [1]. 4. **IRS1, PPARG** - These genes are related to increased insulin resistance unrelated to obesity [1]. 5. **IGF2BP2, HHEX, SLC30A8, WFS1** - These genes have been shown to increase susceptibility to type 2 diabetes in reproducible studies [3]. 6. **JAZF1, CDC123/CAMK1D, TSPAN8/LGR5, THADA, ADAMTS9, NOTCH2** - These are additional variants identified in a recent meta-analysis as being associated with type 2 diabetes [3]. 7. **KCNQ1** - This gene is associated with susceptibility to type 2 diabetes in East Asian and European populations [6].  These genes have been identified through various genome-wide association studies (GWAS) and other genetic research efforts.",
+    "Genetic testing can help predict a person's risk for diabetes in several ways:  1. **Tailored Interventions**: Knowing an individual's genotype can allow for the development of personalized lifestyle intervention programs aimed at preventing or significantly delaying the onset of type 2 diabetes [1].  2. **Role of Genetic Factors**: Genetic factors play a role in determining an individual's risk of developing diabetes, suggesting that genetic testing can help identify those at higher risk [2].  3. **Genetic Risk Scores**: A genotype risk score can predict type 2 diabetes from a young age, as demonstrated in studies like the CARDIA study [6]. This score can help identify individuals who are at increased risk due to their genetic makeup.  4. **Heritability and Risk Assessment**: Type 2 diabetes is heritable, and genetic testing can help identify individuals with a familial risk, which is increased by a factor of 2 to 6 compared to those without familial diabetes [7].  5. **Improved Prediction and Stratification**: Genetic testing offers the potential for improved prediction and stratification of patients according to their risk, which can aid in selecting possible therapeutic targets [8].  6. **Identification of Genetic Variants**: By genotyping specific single nucleotide polymorphisms (SNPs) associated with diabetes, genetic testing can improve the ability to detect who will ultimately develop the disease [9].  Overall, genetic testing provides valuable insights into an individual's risk for diabetes, enabling more targeted prevention and management strategies.",
+    "Family genetics play a significant role in the likelihood of developing diabetes. Several studies and observations highlight this connection:  1. Genetic factors are important in determining an individual's risk of developing diabetes [1]. 2. A family history of diabetes, particularly in first-degree relatives such as parents or siblings, is associated with a two- to fourfold increased risk of developing diabetes [3]. 3. Type 2 diabetes is strongly influenced by genetics, as evidenced by high concordance rates in identical twins, with studies showing a 58-75% concordance rate [5]. In some studies, the concordance rate is reported to be nearly 100% [6]. 4. The risk of developing type 2 diabetes is approximately 70% if both parents have the disease and about 40% if one parent is affected [7], [9]. 5. Type 2 diabetes clusters in families, and having a first-degree relative with the disease increases the lifetime risk significantly, up to 40% or more [9].  Overall, these findings underscore the strong genetic component in the susceptibility to diabetes, particularly type 2 diabetes.",
+    "Yes, lifestyle changes can affect genetic risk factors for diabetes. Evidence from both observational studies and clinical trials suggests that lifestyle factors can modify the genetic effects on the risk of developing type 2 diabetes mellitus (T2DM) [1]. Lifestyle modifications, such as improvements in dietary quality and increased physical activity, have been shown to be particularly effective in preventing and managing type 2 diabetes, even in individuals with a high genetic risk [6]. Furthermore, behavioral changes can substantially mitigate the diabetogenic effects of individual or multiple risk alleles, indicating that the adverse effects of some established T2D-associated loci may be greatly attenuated by appropriate lifestyle changes [9].",
+    "Recent breakthroughs in understanding the genetic causes of diabetes include several key advancements:  1. The number of genetic regions causally implicated in both type 1 and type 2 diabetes has increased to 11 each, marking significant progress in identifying genetic factors associated with these conditions [1].  2. Genome-wide association studies have been particularly successful in uncovering genetic determinants of complex diseases like diabetes. These studies have identified a number of novel disease-associated variants, which have been largely replicated by independent research groups, highlighting their reliability and significance [2].  3. Advances in technology, such as the use of single nucleotide polymorphism (SNP) chips, have enabled the analysis of up to a million genetic variations. This technological leap has greatly enhanced our understanding of the genetic basis of complex, multifactorial forms of diabetes, bringing it closer to the understanding of rarer, single-gene disorders [5].  4. Recent studies have yielded six new replicating gene regions associated with type 2 diabetes, providing new insights into the genetic architecture of the disease and suggesting potential directions for future research [8].  These breakthroughs represent a significant leap forward in the genetic understanding of diabetes, driven by technological advancements and collaborative research efforts.",
+    "Genes influence how our bodies respond to sugar and insulin in several ways:  1. **Insulin Secretion and Resistance**: Genes are directly related to insulin secretion and indirectly influence insulin resistance by interacting with other genes. This interaction supports the idea that environmentally triggered insulin resistance can interact with genetically programmed beta-cell dysfunction, leading to diabetes [1].  2. **Beta-Cell Function**: Many genetic variants primarily affect beta-cell function, development, or survival, rather than insulin sensitivity. This suggests that genetic factors play a significant role in how beta cells respond to sugar and insulin [2].  3. **Expression in Metabolically Relevant Tissues**: Genes affecting insulin sensitivity are often expressed in peripheral insulin-sensitive tissues, such as the liver and adipose tissue, and their expression can be responsive to metabolic status. For instance, a high-fat diet can decrease the expression of several of these genes, indicating a genetic influence on how the body responds to dietary changes [3].  4. **Regulation by Metabolic Conditions**: The expression of certain genes can be altered by conditions such as fasting and feeding, which are known to affect peripheral insulin sensitivity. This suggests that genetic regulation can influence how the body responds to changes in sugar and insulin levels [4].  5. **Genetic Variation and Insulin Response**: Specific genetic variations, such as those in the GIPR gene, can influence glucose and insulin responses to an oral glucose challenge, highlighting the role of genetic differences in individual responses to sugar intake [9].  Overall, genetic factors can influence both the secretion of insulin and the body's sensitivity to it, affecting how we metabolize sugar and respond to dietary changes.",
+    "Yes, there are specific genetic markers that can indicate a higher risk for Type 1 versus Type 2 diabetes.  For Type 1 diabetes, genome-wide association studies have identified over 50 loci associated with an increased genetic risk. Several candidate genes within these regions have been suggested or identified, although the exact molecular mechanisms by which they contribute to islet cell inflammation and beta cell destruction are not fully understood [1].  For Type 2 diabetes, specific genetic markers have also been identified. Some of the loci associated with an increased risk include TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX [9]. Additionally, markers such as TCF7L2 and CAPN10 have been strongly associated with the risk of developing Type 2 diabetes [8].  These findings indicate that while both types of diabetes have genetic components, the specific markers and loci associated with each type differ, reflecting their distinct pathophysiological mechanisms.",
+    "New gene therapies have the potential to cure or treat diabetes through several innovative approaches:  1. **Gene-Based Therapies**: Advances in understanding the biological mechanisms that maintain glucose homeostasis and the molecular defects leading to chronic hyperglycemia could lead to the development of gene-based therapies. These therapies aim to target specific genetic factors involved in diabetes, potentially offering more precise treatment options [3].  2. **In Vivo Gene Therapy**: This approach involves directly inserting a vector containing the desired gene into the patient. It is considered a promising therapeutic strategy for type 1 diabetes, although challenges remain in developing safe and effective vectors [9].  3. **Inducing Islet Neogenesis**: Gene therapy techniques, such as betacellulin gene therapy, have been shown to induce islet neogenesis in the liver and reverse diabetes in mice. This suggests that gene therapy can stimulate the body to produce insulin-producing cells, offering a potential cure for diabetes [10].  These strategies highlight the potential of gene therapies to address the underlying genetic causes of diabetes and restore normal insulin production and glucose regulation.",
+    "Monogenic and polygenic diabetes are distinct forms of diabetes with different genetic underpinnings:  1. **Monogenic Diabetes**: This form of diabetes results from a mutation in a single gene that is highly penetrant, meaning it has a strong effect on the individual who carries it [1], [6]. Monogenic diabetes is often associated with defects in beta-cell function, leading to a decrease in the number or function of these cells [2]. It is typically characterized by early onset, often before the age of 25, and can include conditions like Maturity-Onset Diabetes of the Young (MODY) [5]. Monogenic diabetes is relatively rare, representing about 2%-5% of diabetes cases [2].  2. **Polygenic Diabetes**: In contrast, polygenic diabetes results from the combined effect of multiple genetic variants, each contributing a small effect, along with environmental and lifestyle factors [1], [6]. This form of diabetes is more common and is the predominant mode of inheritance in type 2 diabetes [7]. The genetic variants involved in polygenic diabetes do not have as strong an effect individually as those in monogenic diabetes, but together they contribute to the disease risk in the presence of other factors like obesity and sedentary lifestyle [3].  In summary, monogenic diabetes is caused by a single gene mutation with a strong effect, while polygenic diabetes involves multiple genes with smaller effects combined with environmental influences.",
+    "Studying the DNA of people with diabetes helps scientists find better treatments or cures in several ways:  1. **Identification of Genetic Determinants**: By performing genetic profiling on diabetic patients, scientists can identify genetic determinants that define the targets of current and future therapies. This leads to the development of therapies that are more specific to the genetic makeup of individuals with diabetes [1].  2. **Understanding Disease Mechanisms**: Genetic studies improve our understanding of the biological mechanisms that maintain glucose homeostasis and reveal molecular defects leading to chronic hyperglycemia. This knowledge can lead to the development of more specifically targeted antidiabetic drugs or even gene-based therapies [4].  3. **Pharmacogenetics**: Pharmacogenetic testing can be used to predict therapeutic responses to different classes of drugs for each patient, allowing for more personalized treatment plans [4].  4. **Discovery of New Therapeutic Targets**: A greater understanding of the genetic and epigenetic basis of diabetes can enable the discovery of new therapeutic targets, potentially leading to novel treatments for diabetes and its complications [3].  5. **Stratification of Diabetes Subclasses**: By analyzing DNA variations and their interactions with environmental factors, scientists can stratify type 2 diabetes into subclasses. This stratification allows for more effective treatment strategies tailored to specific genetic and lifestyle interactions [8].  6. **Identification of Key Genetic Elements**: Genetic studies can identify key genetic elements that determine susceptibility to diabetes, disease progression, and responsiveness to specific therapies. This information helps in identifying novel targets for future interventions [9].  Overall, studying the DNA of people with diabetes provides critical insights that drive the development of more effective and personalized treatments."
+  ],
+  "contexts": [
+    [
+      "Mutations that result in mutant insulin or the  inability to convert proinsulin to insulin result in gl ucose  intolerance in some of these cases. Genetic defects  in the insulin receptor or in the signal transduction  pathway of insulin have been demonstrated to result in  hyperinsulinemia and modest hyperglycemia to severe  diabetes[1].  Disease of the exocrine pancreas Damage of the  cells of the pancreas due to diffused  injury of the pancreas can cause diabetes. This damage",
+      "A, et al. Insulin gene mutations resulting in early-onset diabetes: marked differences in clinical presentation, metabolic status, and pathogenic effect through endoplasmic reticulum retention. Diabetes. 2010;59:653 61. 21. Steele AM, Shields BM, Wensley KJ, Colclough K, Ellard S, Hattersley AT. Prevalence of vascular complications among pa- tients with glucokinase mutations and prolonged, mild hyperglyce- mia. JAMA. 2014;311:279 86.22. Chakera AJ, Spyer G, Vincent N, Ellard S, Hattersley AT, Dunne FP.",
+      "presumed glucose toxicity (34). The finding that a mutation of a single nucleotide in the gene encoding the glucokinase enzyme can result in NIDDM lends credibility to the hypoth- esis that inherited defects in insulin production contribute to NIDDM (6). Increased insulin demand of obesity and insulin resistance is accompanied by enhanced insulin biosynthesis,",
+      "insulin synthesis and function while mutations in the insulin gene ( INS) obviously affect the key hormone made by pancreatic beta cells [62]. ATP synthesis defect (mitochondrial diabetes) and mutations in ATP- sensitive potassium channel subunits (channel-building Kir6.2 [po- tassium inwardly-rectifying channel, subfamily J, member 11;KCNJ11 ] and regulatory SUR1 [ATP-binding cassette transporter subfamily C member 8], ABCC8 ) all affect insulin secretion [63].",
+      "Insulin gene mutations  Insulin is synthesized in 13-cells of the islets of Langerhans and is a  central honnone that maintains glucose homeostasis. Insulin-deficient mice  die shortly after birth due to severe hyperglycemia.53 All cell types of the  endocrine pancreas are present in insulin deficient mice suggesting that  insulin is not required for development and differentiation of the endocrine  pancreas. 53  Naturally occurring mutations in the insulin gene that result in the",
+      "Theprevalenceofgeneticmutationsaffectingthestructure oftheinsulinmoleculeinthegeneralpopulationisunknown. Uptothepresent,onlythosepatientsmanifestingthemutant insulinsyndrome(5-8,36)withunusualorfamilialTypeII diabeteshavebeenscreenedanddiscovered.Thus,mutantin- sulinspecieswithnormalorrelativelywell-preservedbinding andbiologicalactivitycharacteristics,andthereforenormal metabolicclearances,areunlikelytobediscoveredbythisap- proachsincehyperinsulinemiawillbeabsentorsubtle.Future",
+      "at various steps, resulting in an impaired insulin action and potential  development of extreme insulin resistant clinical conditions. Many mutations  have been identified in the insulin receptor gene. These mutations may lead  to:   Decreased insulin receptor biosynthesis   Premature chain termination in extracellular or intracellular domain   Accelerated receptor degradation   Defect in the receptor transport to plasma membranes   Decreased insulin binding affinity   Impaired tyrosine kinase activity",
+      "15. Steiner DF, Tager HS, Chan SJ, et al . Lessons learned from molecular biology of insulin-gene mutations. Diabetes Care 1990; 13: 600609. 16. Vionnet N, Stoffel M, Takeda J, et al . Nonsense mutation in the glucokinase gene causes early-onset non-insulin-dependent diabetes mellitus. Nature 1992; 356 : 721722. 17. Sakagashira S, Sanke T, Hanabusa T, et al . Missense mutation of amylin gene (S20G) in Japanese NIDDM patients. Diabetes 1996; 45: 12791281.",
+      "vating mutations in the gene encoding Kir6.2 alter fetal and postnatal growthand also cause neonatal diabetes. J Clin Endocrinol Metab 2006; 91(7): 27822788. 93. Stoy J, Edghill EL, Flanagan SE, et al. Insulin gene mutations as a cause of permanent neonatal diabetes. Proc Natl Acad Sci U S A 2007; 104(38): 1504015044. 94. Pulizzi N, Lyssenko V, Jonsson A, et al. Interaction between prenatal growth and high-risk genotypes in the devel-opment of type 2 diabetes. Diabetolo- gia2009; 52(5): 825829.",
+      "(Edghill et al., 2008; Garin et al., 2010; Stoy et al., 2007). Hyperglycemia occurs due to decreased insulin biosynthe-sis, in which most of the reported missense heterozygous mutations are expected to cause an abnormal proinsulin folding. An accumulation of the misfolded protein in the en-doplasmic reticulum (ER) consequently occurs, resulting in ER stress and betacell apoptosis (Liu, Hodish, Rhodes, & Arvan, 2007). Our identified de novo novel variant in INS is expected to result in aberrant proinsulin"
+    ],
+    [
+      "novel risk loci for type 2 diabetes. Nature 2007, 445(7130) :881-885.5. Gaulton KJ, Willer CJ, Li Y, Scott LJ, Conneely KN, Jackson AU, Duren WL, Chines PS, Narisu N, Bonnycastle LL, et al:Comprehensive association study of type 2 diabetes and related quantitative traits with 222 candidate genes. Diabetes 2008, 57(11) :3136-3144. 6. Hu C, Zhang R, Wang C, Wang J, Ma X, Lu J, Qin W, Hou X, Bao Y, Xiang K, et al:PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX,",
+      "ly associated with type 2 diabetes: TCF7L2, KCNJ11,   and PPARG . 5-7 However, in 2007, a number of novel  genetic variants ( CDKAL1, IGF2BP2,  the locus on  chromosome 9 close to CDKN2A/CDKN2B, FTO,  HHEX, SLC30A8,  and WFS1)8-14 were shown to in - crease susceptibility to type 2 diabetes in repro - ducible studies. Furthermore, a recent meta-analy - sis identified six novel variants ( JAZF1, CDC123/ CAMK1D, TSPAN8/LGR5, THADA, ADAMTS9, and NOTCH2 ) that are associated with type 2 dia - betes. 15",
+      "2009. There are now at least 19 loci containing genes that increase risk of T2D, including PPARG [27], KCNJ11 [27], KCNQ1 [28,29], PLoS Genetics | www.plosgenetics.org 1 February 2010 | Volume 6 | Issue 2 | e1000847",
+      "et al. Association between type 2 diabetes loci and measures of fatness. PLoS One 5, e8541 (2010). 22 Ng, M. C., Park, K. S., Oh, B., Tam, C. H., Cho, Y. M., Shin, H. D. et al. Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 57,22262233 (2008). 23 Thorsby, P. M., Midthjell, K., Gjerlaugsen, N., Holmen, J., Hanssen, K. F., Birkeland, K. I.",
+      "Genome-wide association studies validated these old culprits of T2D and expanded them to include hundreds of single-nucleotide variants (SNVs) that represent more than 150 genomic loci that are associated with T2D, insulin secretion, and insulin resistance [ 11]. Besides TCF7L2 ,PP ARG , and KCNJ11 loci, the most replicated T2D susceptibility variants identied in GWASs were found in and around CDKN2A/2B ,IGF2BP2 ,SLC30A8 ,CDKAL1 and FTO genes [ 1215]. The variants that are most",
+      "Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 2008;40:638-45. 20. Dupuis J, Langenberg C, Prokopenko  I, et al. New genetic loci implicated in fasting glucose homeostasis and their im - pact on type 2 diabetes risk. Nat Genet 2010;42:105-16. 21. Qi L, Cornelis MC, Kraft P, et al. Ge - netic variants at 2q24 are associated with susceptibility to type 2 diabetes. Hum Mol Genet 2010;19:2706-15.",
+      "multiple loci associated with susceptibility to type 2 diabetes, includ- ingTCF7L2 (transcription factor 7-like 2), which had been originally identied by a large-scale association mapping prompted by prior evidence of linkage in that area2,SLC30A8 (solute carrier family 30 member 8), HHEX (haematopoietically expressed homeobox), CDKAL1 (CDK5 regulatory subunit associated protein 1-like 1), CDKN2A/B (cyclin-dependent kinase inhibitor 2A/B) and IGF2BP2 (insulin-like growth factor 2 mRNA-binding protein 2)37.",
+      "associated with susceptibility to type 2 diabetes mellitus. Nat Genet 2008; 40: 109297 . 74 Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are  associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genet 2008; 40: 1098102. 75 Lyssenko V, Lupi R, Marchetti P, et al. Mechanisms by which  common variants in the TCF7L2 gene increase risk of type 2 diabetes. J Clin Invest 2007; 117: 215563.  76 Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA",
+      "type 2 diabetes or the inability to replicate linkage withdened loci. However, at least one susceptibility gene, namelyCAPN10, was found using a genome-wide scan approach [3]. Obesity is the greatest risk factor for type 2 diabetes mellitus, as it is known to induce insulin resistance via variousmechanisms ( TNF     release, free fatty acids, etc.). Both",
+      "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes n engl j med 359;21 www.nejm.org november 20, 2008 2231MPP subjects (P = 0.001) and from 0.79 to 0.83 in  the Botnia subjects (P = 0.006). Of the 16 loci that have been associated with  type 2 diabetes previously,8-15 we showed that 11   TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1,  CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX    were associated with an enhanced risk of future"
+    ],
+    [
+      "BMC Medical Genomics  2009, 2:72 http://www.biomedcentral.com/1755-8794/2/72 Page 2 of 8 (page number not for citation purposes)Background Genome-wide association study (GWAS) offers unbiased ways to examine association of more than a million singlenucleotide polymorphisms (SNPs) with disease [1]. Sev-eral GWAS have indentified novel genomic regions influ-encing risk for type 2 diabetes mellitus (T2DM) [2-6].However, the challenge remains to prioritize SNPs from",
+      "GWAS have successfully identified genetic loci associ- ated with a variety of conditions such as type 2 diabetes2 and coronary disease.35The large number of statistical tests required in GWAS poses a special challenge because few studies that have DNA and high-quality phenotypedata are sufficiently large to provide adequate statisticalpower for detecting small to modest effect sizes. 6Meta- analyses combining previously published findings have im-proved the ability to detect new loci.",
+      "diabetes mellitus6,7. However, the traditional GWAS ignored a large number of loci with moderate effects, because of the strin-gent signi cance thresholds used. Gene-based analysis takes a gene as a basic unit for association analysis. As this method can combine genetic information given by all the SNPs in a gene to obtain moreinformative results 8, it is being used as a novel method com- plementing SNP-based GWAS to identify disease susceptibilitygenes. Notably, this method can increase our chance of nd-",
+      "1. Genome-wide association studies (GW AS) have made considerable progress in identifying genetic risk  factors and in providing evidence for more in-depth understanding of the biological and pathological pathways underlying T2D. A recent study performed a meta-analysis of T2D across 32 GW AS of European ancestry par - ticipants and identified 243 genome-wide significant loci (403 distinct genetic variants) associated with T2D risk",
+      "that a genome-wide approach could uncover  previously unexpected disease pathways. In early 2007, GW AS provided by far the  biggest increment to date in our knowledge of  the genetics of this common health problem. Six new gene regions identified Together, the six recent GW AS papers  provide convincing evidence for six new  gene regions involved in type   2 diabetes1621;  a seventh publication describes how one  of these variants alters BMI and represents by far the best example of an association",
+      "Abstract Genome-wide association studies (GWASs) have discovered association of several loci with Type 2 diabetes (T2D), a common complex disease characterized by impaired insulin secretion by pancreatic bcells and insulin signaling in target tissues. However, effect of genetic risk variants on continuous glycemic measures in nondiabetic subjects mainly elucidatesperturbation of insulin secretion. Also, the disease associated genes do not clearly converge on functional categories",
+      "mechanisms of DR remain poorly understood. A genome-wide association study (GWAS) is a powerful tool to identify genetic loci for complex diseases, and a large number of genetic loci for the susceptibility to various diseases, such astype 2 diabetes, have been successfully identified through GWAS (69). GWAS for DR have been performed, but most of the studies only reported suggestive signals with no replication ( 5)b e c a u s e of their limited sample sizes. Recently, several loci with genome-",
+      "kidney disease, several loci have been identi ed and validated, but the results were quite heterogenic across different popula- tions and depended on the type of diabetes and stage of disease. The major bene t of GWAS results is to be found in the in- creased understanding of disease mechanism and identi ca- tion of novel pathways and possibly new therapeutic targets.Follow-up studies are important in order to identify variants with speci c biological effect and may provide important",
+      "Abstract Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D) and coronary artery disease (CAD), respectively. Nevertheless, these studies were generally per -",
+      "linkage or association data. But, none of these studies include in the analysis existing data from GWAs. Finally, a recent study identied additional susceptibility loci for type 2 diabetes by performing a meta-analysis of three published GWAs.21As acknowledged by the authors, GWAs are limited by the modest effect sizes of individual common variants and the need for stringent statistical thresholds. Thus, by combining data involving 10,128 samples, the authors found"
+    ],
+    [
+      "conferred by specic alleles, genotypes, and haplotypes ofthe HLA class II (and class I) genes. There are currentlyabout 50 non-HLA region loci that also affect the type 1diabetes risk. Many of the assumed functions of thenon-HLA genes of interest suggest that variants at theseloci act in concert on the adaptive and innate immunesystems to initiate, magnify, and perpetuate /H9252-cell destruc-",
+      "II HLA gene associated with type 1 diabetes maps to the 240-kbregion near HLA-B. Diabetes 49: 22172221, 2000. 303. Nejentsev S, Howson JM, Walker NM, Szeszko J, Field SF. Localization of type 1 diabetes susceptibility to the MHC class Igenes HLA-B and HLA-A. Nature 450: 887892, 2007. 304. Nejentsev S, Walker N, Riches D, Egholm M, Todd JA. Rare variants of IFIH1, a gene implicated in antiviral responses, protectagainst type 1 diabetes. Science 324: 387389, 2009.",
+      "Although the highly polymorphic HLA class II genesclearly play the most important single role in susceptibilityto type 1 diabetes, variation at these loci alone cannotexplain all of the evidence of genetic association andlinkage of the MHC with type 1 diabetes. To better denegenes within the MHC that may affect type 1 diabetes riskand would therefore merit further studies, the T1DGCundertook a comprehensive study of the genetics of theclassic 4-Mb MHC region. More than 3,000 SNPs and 66microsatellite",
+      "age to type 1 diabetes in the HLA region and suggestive evidence at a small number of other regions in the genome. In general, the emerging picture from linkage studies is that the class II genes encoding HLA-DR and HLA-DQ, as well as one or more additional genes within the HLA re - gion, confer most of the genetic risk for type 1 dia - betes. Genes outside the HLA region also con - tribute to the risk of type 1 diabetes, but their individual contributions are much smaller than that of HLA.",
+      "Benkalha and Polychronakos, 2008 ). Other genetic loci ( Table 1) are believed to in uence population-level risk for T1D, although it is poorly understood how these non-HLA loci contribute to disease susceptibility (Ram et al., 2016a ). 2.1. Human leukocyte antigen (HLA) The association between T1D and the HLA complex was rst de- monstrated in 1973 following observation of an increased frequency ofHL-W15 (HLA antigen) in T1D patients compared to controls ( Singal",
+      "cyte Antigen (HLA) gene region in immune regulation, and ready availability of serologic markers, led investigators to discover the association between certainHLAalleles and T1D in the early 1970s (33,130,158). The global importance of theHLAonT1Dhassincebeenconrmedingenome-widescansforlinkage:All suchscansperformedtodateshowamajorlocusatthe HLA(28,32,36,78,119). Thefractionofallgeneticrisk,whichcanbeattributedtothecontributionof HLA genes to T1D susceptibility, is about 44%, with a  Sof3.4 (160).",
+      "The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all dis- orders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 andHLA-DRB1 (refs 13), but these genes cannot completely explain the association between type 1 diabetes and the MHC region411.Owing to the regions",
+      "The HLA class I A locus a ects susceptibility to type 1 diabetes. Hum. Immunol. 63, 657 664. pii). https://doi.org/S0198885902004214 . Noble, J.A., Valdes, A.M., Cook, M., Klitz, W., Thomson, G., Erlich, H.A., 1996. The role of HLA class II genes in insulin-dependent diabetes mellitus: molecular analysis of 180 Caucasian, multiplex families. Am. J. Hum. Genet. 59, 1134 1148 . Noble, J.A., Valdes, A.M., Thomson, G., Erlich, H.A., 2000. The HLA class II locus DPB1",
+      "to type 1diabetes susceptibility, including within the MHC itself.Currently, there are over 50 non-HLA regions that signi-cantly affect the risk for type 1 diabetes (http://www.t1dbase.org). Many of these regions contain interesting,but previously unrecognized, candidate genes. A few re-gions contain genes of unknown function or no knownannotated genes, suggesting roles for long-distance generegulatory effects, noncoding RNAs, or unknown mecha-nisms. Against a background of ever-improving knowledgeof the",
+      "the 240-kb region near HLA-B. Diabetes 49,22172221 (2000). 6. Lie, B. A. et al. The predisposition to type 1 diabetes linked to the human leukocyte antigen complex includes at least one non-class II gene. Am. J. Hum. Genet. 64, 793800 (1999). 7. Valdes, A. M. et al. Extended DR3 D6S273-HLA-B haplotypes are associated with increased susceptibility to type 1 diabetes in US Caucasians. Tissue Antigens 65,115119 (2005). 8. Valdes, A. M., Erlich, H. A. & Noble, J. A. Human leukocyte antigen class I B and C"
+    ],
+    [
+      "of diabetes when compared to the native population while not necessar-ily different from populations where they origi-nate from. Risk factors for diabetes appear to be similar between populations, mostly insulin resistance, obesity, and sedentary lifestyle with possible genetic differences contributing to the increased susceptibility. Some data suggest a greater prevalence of microvascular complica-",
+      "nants of type 2 diabetes between immigrant and native populations. Some studies in South Asian (Indian) populations suggest that genetic differ-ences may exist [  17 ,  30 ], but larger studies are  needed to get better insight into this issue.       Prevalence Estimates   The prevalence of diabetes in minorities is affected by ethnicity and country of residence. In one study in the UK [  59 ], standardized preva-",
+      "majority of cases it is difficult to replicate the findingsin other populations. One of the major problems in thesearch for genes responsible for common forms ofdiabetes is the genetic heterogeneity of the diseasewith different genes responsible for the developmentof T2DM in different populations. Furthermore, evenwithin the same ethnic group, different genes may beresponsible for different subtypes of diabetes (for in-stance with predominating failure in insulin secretionor insulin resistance). This is",
+      "across different races or populations but show ethnicity- specific differences. The pathogenesis of T2D involves  genetic variants in the candidate genes. The interactions  between the genes involved in insulin signaling and secre - tory pathways are believed to play an important role in  determining an individuals susceptibility towards T2D.  Therefore, the present study was initiated to examine the  differences, if any, in the contribution of polymorphisms",
+      "That is, the minute genetic differences discernable with SNPs, patterns of single nu-cleotides (A,G,T ,C), and other mutation analysis technologies are now used to explainpatterns of disease between populations, which are in turn understood as the basisfor biological differences between the populations themselves. The case of diabetesgenetics research affords a more nuanced look at what is labeled genetic determinism.It is evident in diabetes research that SNPs and haplotypes, (an inherited pattern of 99",
+      "- tion for disease classification. This genetic component may be specifically important when understanding the pathogenesis of diabetes in ethnic groups, when BMI [14, 15] and HbA1c [16] show distinct differences between ethnicities. Though applying patient-matched, genomic information is currently unrealistic for disease diagnosis, it may hold the key for revealing commonalities across ethnic and demographic groups when classifying diabetic onset, progression, and severity.",
+      "particularly useful for understanding differences in dis-ease prevalence and drug response among differentpopulations. There is ample evidence that human popu-lations have different susceptibility to diseases, exhibit-ing substantial variation in risk allele frequencies [1].For example, genetic predisposition to asthma differsamong the differentially-admixed Hispanic populations of the United States, with the highest prevalence observed in Puerto Ricans. Ge netic variants responsible",
+      "populations and across countries. World-wide differences in prevalence of theforms of diabetes necessitates inclusion of currently understudied populationsfor the development of precision diag-nostics and therapeutics. As a result, theprecise subtype of diabetes a particularindividual is diagnosed with may vary indifferent populations based on subtypefrequency or genetic or dietary or life-style differences. The communication strategy used by the interventionalist and the patient s",
+      "were  positively  associated  with  country  level  income  [49]. However,  the  drivers  for  the  observed  pattern  with  geographi- cal  differences  and  varying  time  trends  are  still  unclear. Susceptibility  to  type  1  diabetes  denitely  has  a  strong  genetic component  (HLA  genotype)  [50],  but  the  heterogeneity  of  type 1  diabetes  cannot  be  explained  solely  by  the  prevalence  of susceptibility  genes  [5153] .  Thus,  the  reasons  for  changes  in",
+      "twice higher than that of 2010  [3] .   The genetic influences on the prevalence of type 2 diabetes i n the Asian population are  mainly related to insulin secretion capacity  [4] ; other genes involved in the risk of type 2  diabetes are not substantially different in other ethnic groups   [5] . The most relevant genes  contributing to ethnic differences are associated with insulin secretion capacity, and they are"
+    ],
+    [
+      "The transcription factor peroxisome-proliferator- activated receptor gamma (PPAR g) is known to inuence insulin sensitivity, and acts partly via amodulation of the circulating adiponectin level (PPAR gagonists increase the adiponectin level) (Ref. 38). The PPAR gP12A SNP is a well- established 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",
+      "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 Introduction Peroxisome proliferator activated receptor gamma (PPAR ) is a ligand-activated transcription factor belonging to the nu-",
+      "2 . A widespread  Gly482Ser polymorphism of PGC1 -    (known as  PPARGC1  ), a  transcriptional coactivator of a series of nuclear receptors includ-ing  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.   Other genes have been shown to be implicated in the genetic",
+      "PPARG Peroxisome proliferator-activated receptor- gene. This gene is located on chromosome 3p25, and has been studied as a candidate genefor type 2 diabetes based on its role in adipocyte and lipid metabolism. The Pro12Ala variant in particular has been associated with adecrease in insulin sensitivity and a several-fold increased risk of type 2 diabetes. PPAR is a target for the thiazolidinedione class of oralantidiabetic agents",
+      "Genetic variation in the peroxisome proliferator-activated receptor (PPAR) and peroxisome proliferator-activated receptor gamma co-activator 1 (PGC1) gene families and type 2 diabetes. Ann Hum Genet 78:2332 Vimaleswaran KS, Radha V, Ghosh S, Majumder PP, Deepa R, Babu  HN etal (2005) Peroxisome proliferator-activated receptor-gamma  co-activator-1alpha (PGC-1alpha) gene polymorphisms and their  relationship to type 2 diabetes in Asian Indians. Diabetic Med 22:15161521",
+      "Dali-Youcef N, et al. The Pro12Ala PPARgamma2 variant deter- mines metabolism at the gene-environment interface. Cell Metab. 2009;9:88 98. 53. Agostini M, Schoenmakers E, Mitchell C, Szatmari I, Savage D, Smith A, et al. Non-DNA binding, dominant-negative, human PPARgamma mutations cause lipodystrophic insulin resistance. Cell Metab. 2006;4:303 11. 54. Agostini M, Gurnell M, Savage DB, Wood EM, Smith AG, Rajanayagam O, et al. Tyrosine agonists reverse the molecular",
+      "associated with a marked increase in T2D risk in the general population, schematized in Fig. 1. The latter systematically tested all the possible PPAR protein variants by using a large-scale pooled functional assay based on a human macro- phage cell line. Using these in vitro data to train a classifier by supervised machine learning, they identified six pathogenic PPARG variants (R194Q, A417V, R212W, P387S, M203I, and T356R) in patients with partial lipodystrophy [ 109].",
+      "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 isoforms",
+      "the PPARgamma locus. Diabetes 2001;50:686 689 12. Kahara T, Takamura T, Hayakawa T, et al. PPARgamma gene polymorphism is as-sociated with exercise-mediated changes of insulin resistance in healthy men. Me- tabolism 2003;52:209 212 13. Franks PW, Luan J, Browne PO, et al. Does peroxisome proliferator-activated receptor gamma genotype (Pro12ala) modify the association of physical activityand dietary fat with fasting insulin level? Metabolism 2004;53:11 16 14. Memisoglu A, Hu FB, Hankinson SE, et al.",
+      "30. Majithia, A. R. et al. Rare variants in PPARG  with decreased activity in  adipocyte differentiation are associated with increased risk of type 2 diabetes.  Proc Natl Acad Sci USA 111, 1312713132 (2014).  31. Majithia, A. R. et al. Prospective functional classification of all   possible missense variants in PPARG . Nat. Genet.  48, 15701575 (2016).  32. Claussnitzer, M. et al. Leveraging cross-species transcription factor binding"
+    ],
+    [
+      "A variety of cellular and animal models have been developed and applied over the past few years to experimentally manipulate cis-regulatory elements and their target gene function as it related to beta cell/isletfunction, glucose homeostasis, and T2D pathogenesis. CRISPR/Cas9 hasrevolutionized our ability to modify genomes and epigenomes almost at will. Unsurprisingly, CRISPR (epi)genome editing tools can and have been used to target putative T2D target genes [54] orcis-REs[55] in beta",
+      "to how CRISPR/Cas9 technology may nd clinical application in patients with diabetes. Keywords: genome editing, beta cell, genome-wide association studies, maturity onset of diabetes of the young, stem cells, mouse models INTRODUCTION Type 2 diabetes (T2D) affects an estimated 425 million people worldwide, a number predicted to rise to 629 million by 2045 ( 1). The disease usually involves insulin resistance but is ultimately the result",
+      "hPSCs [48,49] for correcting the COL7A1 [50] anda1-antitrypsin genes [51]. Given the superior cutting ef ciency, CRISPR/Cas9 is increasingly becoming the favored choice for genome editing inhPSCs [16,52] . 3.2. Employing hPSCs and genome editing tools to study diabetes and metabolic syndromes In general, the strategy to carry out in vitro disease modeling of dia-",
+      "Due to its simplicity and adaptability, CRISPR has rapidly become the most popular genome editing tool available for the mammalian genome ( 50,63). Because NHEJ DNA repair often introduces unwanted indels at the Cas9 cutting site, CRISPR hasbeen used to knock-out genes by introducing frameshiftmutations, resulting in protein depletion ( 156,157). In the diabetes eld, CRISPR has also been adopted to study several genes in bcell lines and in human ES-derived bcells ( 21,151,",
+      "samples ( 236). CRISPR technology has been used recently to correct point mutations in patient-derived iPSCs to target diabetes-relatedgene defects. To date, the most ef cient method used in iPSC is CRISPR/Cas9-based homology-directed repair (HDR). Here, a Cas9-mediated cut is generated adjacent to the site of interest. A homologous donor template with the intended nucleotidechange containing silent mutations in the gRNA sequence(167) can then be recombined by HDR. This approach has",
+      "in response to various stimuli including glucose aftertransplantation in an immunocompromised mouse model (230,231). However, the use of iPSC is controversial and there are some concerns over genetic and epigenetic variations iniPSCs which might affect cell function after differentiation ( 275). Manipulation of hESC/iPSC cells via CRISPR-Cas9 technology provides a platform for the correction of genomic mutations not only in diabetes but in other disease elds as well",
+      "RNP and single strand edDNA (ssDNA) donor which carriesdesired changes such as insertion of loxP site ( 255,259265). Using CRISPR-Cas9, leptin and leptin receptor knockout mice have been established as tools in diabetes and obesity research ( 160,255,256). Knock-in mouse models have also been established via HDR to achieve cell-speci c deletion of the gene ( 266). Genome Editing: Clinical Application in Diabetes An important goal in genetic research is to identify the genetic",
+      "CRISPR-Cas9 epigenome editing enables high-throughput screening for functionalregulatory elements in the human genome. Nature Biotechnology 35(6):561 e568. [58] Hodson, D.J., Mitchell, R.K., Marselli, L., Pullen, T.J., Gimeno Brias, S., Semplici, F., et al., 2014. ADCY5 couples glucose to insulin secretion in humanislets. Diabetes 63(9):3009 e3021 . [59] Zhou, Y., Park, S.-Y., Su, J., Bailey, K., Ottosson-Laakso, E., Shcherbina, L.,",
+      "free IPSCs from Human Pancreatic Cells Using the CRISPR-Cas9 System. J Vis Exp JoVE (2017). doi: 10.3791/56260 277. Millette K, Georgia S. Gene Editing and Human Pluripotent Stem Cells: Tools for Advancing Diabetes Disease Modeling and Beta-Cell Development. Curr Diabetes Rep (2017) 17:116. doi: 10.1007/s11892-017-0947-3Hu et al. Genome Editing of Pancreatic Beta Cells Frontiers in Endocrinology | www.frontiersin.org October 2020 | Volume 11 | Article 576632 19",
+      "DNA donors as templates, it is possible the nCas9-RT will beable to convert all variants at once. This new technique, however,is still in early development, and its editing ef ciency and side- effects remain to be seen.FUTURE PROSPECTIVES Recent technological developments around CRISPR-Cas9 and itsderivative technologies, combined with advances in humancellular models, should accelerate our understanding of theinterplay between diabetes risk-associated genetic variants and"
+    ],
+    [
+      "Effectors  Glucose transporters. A number of polymorphisms have been identified in  the GLUT4 gene. None of them have been linked to or found to be  associated with type 2 diabetes in a variety of populations. 5960 Interestingly,  an association was found between a polymorphism in the human GLUT!  gene and type 2 diabetes60 that was significant for obese women. Regulation  of GLUT4 protein expression in diabetes occurs in a strongly tissue-specific",
+      "M,XiangKS,etal.1996.Geneticcontri-bution of polymorphism of the GLUT1and GLUT4 genes to the susceptibilityto type 2 (non-insulin-dependent) dia-betes mellitus in different populations.Acta Diabetologica 33:19397 141. Poulsen P, Kyvik KO, Vaag A, Beck- Nielsen H. 1999. Heritability of type II(non-insulin-dependent) diabetes melli-tus and abnormal glucose toleranceapopulation-basedtwinstudy. Diabetolo- gia42:13945 142. Pugliese A, Zeller M, Fernandez AJ,",
+      "A mutation in the Glut2 glucose transporter gene of a diabetic patientabolishes transport activity. J Biol Chem 269: 1776517767, 1994. 36.Patel P, Bell GI, Cook JT, Turner RC, Wainscoat JS. Multiple restriction fragment length polymorphisms at the GLUT2 locus: GLUT2haplotypes for genetic analysis of type 2 (non-insulin-dependent) diabetesmellitus. Diabetologia 34: 817821, 1991. 37.Pereira MA, FitzerGerald SJ, Gregg EW, Joswiak ML, Ryan WJ, Suminski RR, Utter AC, Zmuda JM. A collection of Physical Activity",
+      "NootherrecentassociationsofpolymorphismswithT2Dhavebeenreplicated to date (Table 5). However, a recent meta-analysis (106) identied some earlyreproducibilityofanassociationbetweenvariationin GLUT1andT2D,originally reportedin1988(104).Itislikelythatthisassociationhasnotbeenpursuedfurtherfor several reasons, but one possibility is a study that reported the rejection oflinkageto GLUT1athighlevelsofsignicance(46).However,linkagehaslimited",
+      "mechanism by which type 2 diabetes is influenced remains to be identified. There have been several attempts to clarify the role of the polymorphism in SLC30A8 in the development of type 2 diabetes and the focus has been set on insulin secretion dueto the importance of ZnT-8 for insulin storage in the granulaof pancreatic cells. The results are controversial, but there appears to be an association between the risk variant of rs13266634 and reduced insulin secretion. Interestingly, decreased insulin",
+      "glucose tolerance, suggesting a r ole 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 insulinsecretion, and a study on 1306 GDM patients and 1973 pregnantwomen without GDM found a signi cant association between the presence of this polymorphism and the risk of GDM ( 18). Intriguing results were generated by a study on the genetic",
+      "tients the EUGENE2 study. Diabetologia 2008;51:816 820 32. Kirchhoff K, Machicao F, Haupt A, et al. Polymorphisms in the TCF7L2, CDKAL1 and SLC30A8 genes are associated with impaired proinsulinconversion. Diabetologia 2008;51:597 601 33. Nicolson TJ, Bellomo EA, Wijesekara N, et al. Insulin storage and glucose homeostasis in mice null for the granule zinc transporter ZnT8 and studies of the type 2 diabetes-associated variants. Diabetes 2009;58:2070 2083",
+      "is markedly reduced in glucose-unresponsive islets from ani-mal models of type 2 diabetes (51). In a previous study in PimaIndians, we found that ~5% of this population carries a mis-sense polymorphism in exon 3 of the GLUT2 gene (52), but this polymorphism was not associated with the residual fast-ing plasma insulin concentration in the present study.Despite the fact that GLUT2 is an attractive candidate, it",
+      "polymorphisms in 24 DNA samples. Common variants were thengenotyped in 760 type 2 diabetic patients and 641 nondiabetic sub-jects. Genetic associations with diabetes-related phenotypes werealso analyzed. Results: Nine polymorphisms were identified, and four common poly- morphisms [g. /H110021500C /H11022G, g./H110021062G /H11022C, g./H11002994C/H11022T, g./H11001408C/H11022A (Leu72Met)] were genotyped in a larger study. The genotype distri-butions of these four common polymorphisms in type 2 diabetes pa-",
+      "in turn, result in a defective or poorly expressed glucagonprotein and lead to decreased insulin secretion and conse- quently hyperglycaemia [ 48]. The current study identified, for the first time, several type 2 diabetes-associated risk alleles associated with a higher riskof GDM, namely rs7957197 ( HNF1A ), rs10814916 ( GLIS3 ), rs3802177 ( SLC30A8 ) and rs7041847 ( GLIS3 ). These SNPs"
+    ],
+    [
+      "MicroRNAs (miRNA) ar e single -stranded, small RNA molecules that act at the post - transcriptional standard to regulate their target or source genes. Many biological processes  are regulated by this Micro RNA. Since its discovery about two decades ago. It is correlated  with a com prehensive set of diseases and described by numerous miRNAs, including T2DM  and cardiovascular diseases. Specifically, with respect to T2DM, micro RNA plays a",
+      "they can act as oncogenes or tumor suppressors  (8, 29, 72). miRs are associated with the 341  regulation of genes relevant to insulin secre tion, cholesterol biosynthesis, fat metabolism and 342  adipogenesis, crucial pathways in the pathogene sis of diabetes (53, 114, 115). miRs have also 343  been implicated in TGF-  signaling related to th e pathogenesis of diabetic nephropathy with key 344  miRs such as miR-192, miR-216a, miR-217 and miR-377 being up-regula ted in glomerular 345",
+      "Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM et al (2005) Microarray analysis shows that some microRNAs down-regulate large numbers of target mRNAs. Nature 433:769773 Lovis P, Roggli E, Laybutt DR, Gattesco S, Yang JY et al (2008) Alterations in microRNA expression contribute to fatty acid-induced pancreatic beta-cell dysfunction. Diabetes 57:27282736 Nadler ST, Stoehr JP, Schueler KL, Tanimoto G, Yandell BS et al",
+      "Abstract Recent 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",
+      "evidence demonstrates that miRNAs and lncRNAs can alsoregulate the expression of genes and modulate the actions of growth factors and inflammatory factors related to diabetic complications [ 8]. These reports have been described in sev- eral reviews [ 8,8791] and are only briefly discussed here. Numerous recent reports have demonstrated abnormal ex- pression of various miRNAs in renal, vascular and retinal cellsunder diabetic conditions, and in vivo models of related",
+      "In addition, miRNAs have been shown to be involved in T2DM. For example, miRNAs play major roles  in pancreatic islet development,  cell dysfunction, insulin synthesis and secretion and insulin   resistance [148] . Studies based on miRNA microarray analysis have identified many different miRNAs  involved in the pathology of both T1DM and T2DM; these miRNAs include mi R-375, miR -29, miR -9,  miR-124a, miR -195, miR -222, miR -126, miR -133a, miR -296, miR -96, miR -34a, miR -146b, miR -657,",
+      "26. He Y , Ding Y , Liang B, Lin J, Kim TK, Yu H, Hang H,  Wang K. A Systematic Study of Dysregulated MicroRNA in  Type 2 Diabetes Mellitus. Int J Mol Sci. 2017:18. 27. Dias S, Hemmings S, Muller C, Louw J, Pheiffer C. MicroRNA Expression Varies according to Glucose  Tolerance, Measurement Platform, and Biological Source.  Biomed Res Int. 2017;2017:1080157. 28. El Ouaamari A, Baroukh N, Martens GA, Lebrun P, Pipeleers D, van Obberghen E. miR-375 targets  3'-phosphoinositide-dependent protein kinase-1 and",
+      "nucleotide RNA molecules that potentially regulate the expression of thousands of genes. To understand therelationship between miRNA regulation and obesity- induced diabetes, we quantitatively proled approximately220 miRNAs in pancreatic islets, adipose tissue, and liver from diabetes-resistant (B6) and diabetes-susceptible (BTBR) mice. More than half of the miRNAs proled wereexpressed in all three tissues, with many miRNAs in each tissue showing signicant changes in response to genetic",
+      "11. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281 97. 12. Pirola L, Balcerczyk A, Tothill RW, et al. Genome-wide analysis distinguishes hyperglycemia regulated epigenetic signatures of pri- mary vascular cells. Genome Res. 2011;21(10):1601 15. 13.Cooper ME, El-Osta A. Epigenetics: mechanisms and implications for diabetic complications. Circ Res. 2010;107(12):1403 13.Thispaper also provides a review of evidence pertaining to the role",
+      "128. Diao X, Shen E, Wang X, Hu B. Differentially expressed microRNAs and their target genes in the hearts of streptozotocin-induced diabetic mice. Mol Med Rep (2011) 4:63340. doi:10.3892/mmr.2011.489  129. La Sala L, Cattaneo M, De Nigris V , Pujadas G, Testa R, Bonfigli AR,   et al. Oscillating glucose induces microRNA-185 and impairs an efficient antioxidant response in human endothelial cells. Cardiovasc Diabetol  (2016)  15:71. doi:10.1186/s12933-016-0390-9"
+    ],
+    [
+      "studying the highly familial MODY form of young - onset diabetes or other rare forms of monogenic diabetes.     Table 12.2    The different subtypes of maturity - onset diabetes of the young ( MODY ).     MODY  type     Gene  locus     Gene name     Year of  discovery     Distribution     Onset of  diabetes     Primary  defect     Severity of  diabetes     Complications     OMIM     MODY1    20q     HNF4A   ( TCF14  )    1996    Rare (2  3%)    Adolescence/",
+      "penetrance and early - onset diabetes, allows the collection of multigenerational pedigrees, making MODY an attractive model for genetic studies. MODY usually develops in thin young adults (usually before 25 years of age; in childhood, adolescence or young adulthood), and is associated with primary insulin - secretion defects  [4,5] . The prevalence of MODY is estimated to be less than 1  2% of patients with T2DM, although it could represent as many as 5% of European cases of diabetes  [4,25] . MODY is not",
+      "[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 manifesta-tions   [5] . As compared to type 2 diabetes, the clinical  Key Words   Best practice  Genetic testing  Healthcare providers  Interview study  Maturity onset diabetes of the young   Abstract",
+      "causal for MODY , although genetic or functional evidence of obvious pathogenicity is not fully compelling (Table 1). Despite these important advances in understanding the mo- lecular pathogenesis of MODY , the genetic determinants in many patients with young-onset diabetes resembling a MODY-like phenotype remain unknown, suggesting addi- tional locus heterogeneity and new pathogenic mechanismsto be yet discovered. This has particularly been observed in",
+      "MODY Maturity Onset Diabetes of the Young. This is an uncommon form of diabetes, inherited as an autosomal dominant condition, and displaysa slow onset of symptoms. It generally presents before 25 years of age, is not related to obesity, and appears to have no autoi mmune basis. Multiple forms of MODY have been characterised based on mutations affecting different genes involved in the control of -cellfunction, and display different degrees of disease severity Continued over page",
+      "Genetic Testing for MODY  Public Health Genomics 2015;18:5259  DOI: 10.1159/00036796359  1 Singh R, Pearson ER: The importance of mak- ing a genetic diagnosis of diabetes. Can J Dia-betes 2006;    30:   183190.    2 Ledermann HM: Is maturity onset diabetes at  young age (MODY) more common in Europe than previously assumed? Lancet 1995;    345:    648.",
+      "Genetic Testing for MODY  Public Health Genomics 2015;18:5259  DOI: 10.1159/00036796353symptoms present often at a relatively young age in pa- tients without overweight, who have a positive family his-tory. As compared to type 1 diabetes, progression may be less severe, and the required dosage of insulin low.   Many patients with MODY are currently undiagnosed  or misdiagnosed with type 1 or 2 diabetes mellitus  [4] . In",
+      "in 1992, through familial linkage analysis of French pedigreeswith early-onset, non-auto-immune, non-obese diabetes thatwas also called maturity-onset diabetes of the young (MODY) (Froguel et al., 1992 ). Mutations in GCK (encoding glucokinase) were shown to cause a relatively benign form of MODY. Inciden-tally, it was the rst time that the direct causative effect of rela- tive insulin deciency was demonstrated in T2D, when insulin",
+      "gene studies were under powered. However, studies of  monogenic forms of diabetes, specifically maturity onset  diabetes of the young 2 (MODY2), provided some of the  first insights into the contribution of genetic variation to  hyperglycemia observed during pregnancy and fetal  outcomes. MODY2 is an autosomal dominant form of  MODY due to mutations in glucokinase ( GCK ) [2527]. Table 1. Characteristics and treatment modalities of different forms of diabetes mellitus Characteristics Treatment modalities",
+      "is variable, underlining that this disorder is genetically heterogeneous.  Table 1. Definition of MODY   Impaired glucose tolerance   Age of onset <25 years   Autosomal-dominant inheritance  Using genetic linkage and candidate gene approaches, mutations in  genes on chromosomes 2, 7, 12, 13, 19, and 20 have been linked to MODY  and collectively may represent up to 3% of all patients with type 2 diabetes  (Table 2). The gene on chromosome 7 (MODY2) encodes the glycolytic"
+    ],
+    [
+      "of Diabetes   Results of several genome-wide association stud- ies (GWAS) have linked the following common gene variants with a 1520% increased risk of diabetes: reduced insulin secretion via reduce beta-cell mass (CDKAL1, CDKN2A, CDKN2B) and beta-cell dysfunction (MTNR1B, TCF7L2, KCNJ11) and increased insulin resistance related to obesity (FTO) and unrelated to obesity (IRS1, PPARG) [  11 ]. While most of the early studies",
+      "gene are associated with NIDDM in Caucasians. Diabetes 1996 , 45, 825-831.  46.  Tarasov, A.I.; Nicolson, T.J. ; Riveline, J.P.; Taneja, T.K. ; Baldwin, S.A.; Baldwin, J.M.;  Charpentier, G.; Gautier, J.F. ; Froguel, P.; Vaxillaire, M.; et al.  A rare mutation in ABCC8/SUR1  leading to altered ATP-sensitive K+ channel activ ity and beta-cell glucose sensing is associated  with type 2 diabetes in adults. Diabetes 2008 , 57, 1595-1604.",
+      "ly associated with type 2 diabetes: TCF7L2, KCNJ11,   and PPARG . 5-7 However, in 2007, a number of novel  genetic variants ( CDKAL1, IGF2BP2,  the locus on  chromosome 9 close to CDKN2A/CDKN2B, FTO,  HHEX, SLC30A8,  and WFS1)8-14 were shown to in - crease susceptibility to type 2 diabetes in repro - ducible studies. Furthermore, a recent meta-analy - sis identified six novel variants ( JAZF1, CDC123/ CAMK1D, TSPAN8/LGR5, THADA, ADAMTS9, and NOTCH2 ) that are associated with type 2 dia - betes. 15",
+      "CDKAL1 in  uences insulin response and risk of type 2 diabetes. Nat Genet 2007; 39: 77075. 69 Wu Y , Li H, Loos RJ, et al. Common variants in CDKAL1, CDKN2A/ B, IGF2BP2, SLC30A8, and HHEX/IDE genes are associated with type 2 diabetes and impaired fasting glucose in a Chinese Han population. Diabetes 2008; 57: 283442. 70 Sandhu MS, Weedon MN, Fawcett KA, et al. Common variants in  WFS1 confer risk of type 2 diabetes. Nat Genet 2007; 39: 95153.",
+      "Genes signifying increased risk for both type 1 and type 2 dia-betes have been identified. Genomewide association studies have identified over 50 loci associated with an increased genetic risk of type 1 diabetes. Several T1D candidate genes for increased risk of developing type 1 diabetes have been sug-gested or identified within these regions, but the molecular basis by which they contribute to islet cell inflammation and beta cell destruction is not fully understood. 12 Also, several",
+      "associated with susceptibility to type 2 diabetes mellitus. Nat Genet 2008; 40: 109297 . 74 Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are  associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genet 2008; 40: 1098102. 75 Lyssenko V, Lupi R, Marchetti P, et al. Mechanisms by which  common variants in the TCF7L2 gene increase risk of type 2 diabetes. J Clin Invest 2007; 117: 215563.  76 Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA",
+      "type 2 diabetes or the inability to replicate linkage withdened loci. However, at least one susceptibility gene, namelyCAPN10, was found using a genome-wide scan approach [3]. Obesity is the greatest risk factor for type 2 diabetes mellitus, as it is known to induce insulin resistance via variousmechanisms ( TNF     release, free fatty acids, etc.). Both",
+      "50 most cases of type 2 diabetes are thought to be  due to genetic variations that are more common but exert less e  ect. In early studies, genetic variants in the peroxisome proliferator-activated receptor- gene (PPARG) 51 and the ATP-sensitive potassium channel  Kir62 (KCNJ11) were reproducibly associated with type 2 diabetes. 52 In Asian populations, the protective e  ect of  the PPARG*A12Ala allele on insulin resistance and risk of type 2 diabetes was not consistently seen. 53",
+      "49. Cornelis MC, Qi L, Zhang C, et al. Joint e ects of common genetic variants on the risk for type 2 diabetes in U.S. men and women ofEuropean ancestry. Ann Intern Med . 2009;150:541 550(in eng). 50. Hu C, Zhang R, Wang C, et al. PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8are associated with type 2 diabetes in a Chinese population. PLoS One. 2009;4:e7643 (in eng). 51. Lin X, Song K, Lim N, et al. Risk prediction of prevalent diabetes in",
+      "46. Sladek R, Rocheleau G, Rung J et al (2007) A genome-wide asso- ciation study identifies novel risk loci for type 2 diabetes. Nature 445:881 885 47. Lauenborg J, Grarup N, Damm P et al (2009) Common type 2 diabetes risk gene variants associate with gestational diabetes. J Clin Endocrinol Metab 94:145 150 48. Florez JC, Jablonski KA, Bayley N et al (2006) TCF7L2 polymor- phisms and progression to diabetes in the Diabetes Prevention Program. N Engl J Med 355:241 250"
+    ],
+    [
+      "genetic knowledge beyond its use for predic-tion of the individuals type 2 diabetes risk?One major advantage of knowing an at-riskpersons genotype could be to offer an individ-ually tailored lifestyle intervention program to prevent or, at least, to significantly retard the",
+      "Genetic factors appear to play a role in determining an individuals risk of developing diabetes. It is hoped",
+      "(35). If genetic tests are not helpful in the prediction and prevention of diabetes,they could have a role in discriminatingbetween type 1 and type 2 diabetes. Theepidemic of obesity (36) has made it moredifcult to distinguish diabetes type be- cause many children and young adultswith type 1 diabetes are also obese (37).Misclassi cation poses signi cant risks; an incorrect diagnosis of type 2 diabetes",
+      "geted at specific genetic mutations, it is likely that accompa-nying diagnostic tests for biomarkers will also become available to confirm whether the target biomarker is present. Genomic Analyses for Diabetes Risk",
+      "genes improves prediction of type 1 diabetes[published correction appears in Diabetologia. 2015; 58(1):206]. Diabetologia . 2014; 57(12):2521 2529. 57. Oram RA, Patel K, Hill A, Shields B, McDonald TJ, Jones A, Hattersley AT, Weedon MN. A type 1 diabetes genetic risk score can aid discrimination between type 1 and type 2 diabetes in young adults.Diabetes Care . 2016; 39(3):337 344. 58. Redondo MJ, Oram RA, Steck AK. Genetic risk",
+      "10.2337/db13-1663.  20. Vassy JL, et al. A genotype risk score predicts type 2 diabetes from young  adulthood: the CARDIA study. Diabetologia. 2012;55:26042612. doi:  10.1007/s00125-012-2637-7.  21. Vassy JL, et al. Is genetic testing useful to predict type 2 diabe-tes? Best Pract Res Clin Endocrinol Metab. 2012;26:189201. doi:  10.1016/j.beem.2011.09.002.  22. Khera AV, et al. Genome-wide polygenic score to identify a monogenic  risk-equivalent for coronary disease. bioRxiv. 2017. doi: 10.1101/218388.",
+      "Genotype Score for Prediction of Type 2 Diabetes n engl j med 359;21 www.nejm.org november 20, 2008 2209Type 2 diabetes mellitus is a m ajor  health problem worldwide.1 Fortunately,  its development can be prevented in many  instances,2 and persons at risk can be readily  identified with the measurement of a few com - mon risk factors.3-5 Type 2 diabetes is heritable,  with a risk for people with familial diabetes as  compared with those without familial diabetes that is increased by a factor of 2 to 6.",
+      "risk of type 1 diabetes offers the potential for improved prediction, stratification of patients according to risk, and selection of possible therapeutic targets. As germ-line factors, genetic risk variants are present and amenable to study at all times  be -",
+      "offers the opportunity to test whetherknowledge of these genetic loci canimprove our ability to detect who willultimately develop diabetes. To answerthis question, we genotyped 18 well-validated single nucleotide polymorph-isms that had previously been associat- ed with diabetes in large genetics",
+      "Comprehension of Genomic Risk for  Diabetes  Public Health Genomics 2014;17:95104  DOI: 10.1159/000358413101their results in-person from a genetic counselor were able  to correctly indicate their genomic or lifetime risk score for T2DM and interpret their genomic risk, compared to 50% of participants receiving their results online. This finding aligns with reports that suggest genetic counsel-ing (though limited to reporting of test results in this study) improves patients accuracy of risk perception"
+    ],
+    [
+      "Genetic factors appear to play a role in determining an individuals risk of developing diabetes. It is hoped",
+      "Metabolic Syndrome and Family History  of Diabetes Public Health Genomics 2010;13:353359 357able difference in the odds between these 2 risk levels.  This table indicates that, compared with the average fa-milial risk, a moderate or high familial risk of diabetes increases the odds for each single component of the met-a b o l i c  s y n d r o m e .  T h e s e  o d d s  v a r y  f r o m  1 . 1 9  ( 9 5 %  C I :  0.881.61) to 1.53 (95% CI: 1.301.81).   C o n c l u s i o n",
+      "For type 2 diabetes, there have been a few  studies utilising a candidate-gene approach as well as genome-wide association studies, although some argue that genetic factors play only a minor role among Caribbean populations [  90 ]. A family history of diabetes in any   rst-  degree relative (parent, sibling) or in a grandpar-ent is associated with a two- to fourfold increased risk of diabetes [  10 ,  91 ]. A family history of dia-",
+      "evidenced by a very high positive rate of family history of diabetes, and  drastically different prevalence in various ethnic groups. Therefore, there is  no doubt that type 2 diabetes is a disease with a strong genetic influence.  However, the prediction of the relative contribution of genetic influence and  number of genes involved in the pathogenesis of the disease has changed in  the past few years. Initially, enthusiastic searches of diabetes genes were",
+      "can decrease risk of diabetes.22 Diet may also play a role. High calorie diets,  including those high in fat, and especially saturated fat, have been implicated  in the development of type 2 diabetes?4-26 Family history is a very strong risk  factor for type 2 diabetes. A strong genetic component is suggested by the  58-75% concordance rates for type 2 diabetes observed in identical twins  (Table 3).3  Table 3. Estimated risk of developing type 2 diabetes by family history  One parent with type 2 diabetes",
+      "The fact that type 2 diabetes is a genetic disease is well known to clinicians by how it occurs in families, and by there being ethnic populations who are particularly high risk. The genetic link was clearly shown more than two decades ago by a famous study of identical twins in the U.K. that found essentially a 100% concordance rate for this disease if one twin developed type 2 diabetes, then the other one invariably developed it (9). However, this kind of study",
+      "genetic factors play an important role in the susceptibility to T2D. The risk of the disease developing at some point of life is ~70% when both parents are diabetic and ~40% when one parent has T2D [ 4]. Furthermore, latest data show that more than 400 genetic risk variants at 250 loci for T2D have been Genes 2018 ,9, 374; doi:10.3390/genes9080374 www.mdpi.com/journal/genes",
+      "36 Herder C, Roden M. Genetics of type 2 diabetes: pathophysiologic  and clinical relevance. Eur J Clin Invest 2011; 41: 67992. 37 Dabelea D, Hanson RL, Lindsay RS, et al. Intrauterine exposure  to diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes 2000; 49: 220811. 38 Voight BF, Scott LJ, Steinthorsdottir V, et al. Twelve type 2 diabetes  susceptibility loci identi  ed through large-scale association analysis. Nat Genet 2010; 42: 57989.",
+      "long follow-up. Type 2 diabetes and impaired glucose tolerance (IGT)  cluster in families. Thus, most patients have a positive family history, and  the lifetime risk for developing type 2 diabetes is increased up to 40% (more  than five times the background rate) by having a first degree relative with the  disease. If both parents have type 2 diabetes the risk to the offspring may be  as high as 70%. Available evidence supports a polygenic mode of  inheritance with a considerable environmental input. 1",
+      "Genetic factors Type 2 diabetes has a strong genetic component and most Asian patients have a   rst-degree relative with diabetes. 48,49 Much progress has been made in our  understanding of the genetics of this disease. Importantly, most of the loci originally associated with diabetes in European populations have been replicated in Asian populations. Whereas monogenic forms of diabetes result from rare genetic mutations with large e  ects,  such as those seen in maturity-onset diabetes of young people,"
+    ],
+    [
+      "of a given genetic variant is modified by the environ - mental milieu (and vice versa). Evidence that lifestyle factors modify the genetic effects on T2DM risk has been  generated from both observational studies and clinical  trials82. However, genetic background might also affect  the individuals response to lifestyle interventions83. In  addition, replication data are sparse, and comprehensive,  large-scale studies have failed to provide a compelling",
+      "genetic risk for diabetes may not moti-vate improvements in lifestyle behaviors.Indeed, knowledge of increased geneticrisk for diabetes may decrease motiva-tion to modify behavior in genetic fatal-ists (83). Diet recommendations optimized to the individual have been shown to re-duce postprandial glycemic excursionsto a greater extent than standard approaches in healthy individuals (84).Meal compositions that induce the most favorable glycemic pro les have been",
+      "diabetes regardless of the underlying genetic risk. This contrasts with theextensive epidemiological evidence sug-gesting that the relationship of lifestylewith obesity is dependent on genetic risk(7881); however, with few exceptions (e.g., [74]), analyses in large randomizedcontrolled trials have failed to show thatthese same genetic variants modifyweight loss in response to lifestyle in-tervention (82). It is also important to recognize that knowledge of increased",
+      "Genetic factors appear to play a role in determining an individuals risk of developing diabetes. It is hoped",
+      "suggested to attenuate its negative e  ect on metabolic pro  le,  body weight, and diabetes risk (   Franks et al., 2007   ;    Kilpelainen et al., 2008   ;    Lindi et al., 2002   ;    Ruchat et al., 2010   ) (             Table 1   ).  The notion that lifestyle modi  cation can eliminate the increased  risk for development of T2DM in subjects with genetic suscepti-bility is also supported by  ndings of    Barwell et al. (2008)    who",
+      "proven particularly effective for preven-tion and management of type 2 diabetes.For example, improvement in dietaryquality, in conjunction with other lifestylemodications like increased physical ac-tivity, was shown to be more effectivethan pharmacological treatment in pre-vention of diabetes in individuals at highrisk (1). Further, lifestyle modicationmay mitigate the risk associated with thestrongest known diabetes risk loci (2).While the existence of environmental in-uences on genetic risk (and vice",
+      "who is lean, genetic risk factors are more likely to be present than in someone who is obese and develops the disease or that weight loss enhances the genetic risk ofdiabetes. Genetic analyses performed in clinical trials involving intensive lifestyle modi - cation provide an important adjunct to the epidemiological literature on gene- lifestyle interactions in type 2 diabetes.On one hand, a major advantage of ran- domized controlled trials is that interac-",
+      "Lifestyle behaviors and genetic loci have clear and distinguishable effects on  T2D risk; however, the pattern of disease occurrence within and between popula-tions that differ in their genetic and environmental underpinnings suggests T2D is caused in part by the interaction between adverse lifestyle behaviors and the genetic profile of an individual. For many, this seems a reasonable assumption, but there is little robust empirical evidence supporting the presence of such interactions.",
+      "this occurs. Findings to date, however, indicate that behavioral changes can substantially mitigate diabetogenic and obesogenic effects of individual or multiple risk alleles, which has much broader clinical and public health implications.We have seen considerable progress in our understanding of the role that both environ- ment and genetics play in the development of T2D. Recent work suggests that the adverse effect of some established T2D-associated loci may be greatly attenuated by appropriate",
+      "Susceptibility to obesity and diabetes is deter- mined by both genetic and lifestyle factors.Suggestive evidence of genelifestyle interac- tion (Box 33.3) in the development of common diseases such as obesity and type 2 diabetes wasrst provided by descriptive epidemiological studies such as migration studies that compare the disease risk between genetically related pop-ulations who live different lifestyles. A classicalexample is the comparison of the risk of obesity"
+    ],
+    [
+      "understanding of the genetic basis of diabetes, and the advances of recent months are arguably the most important made since the role of the HLA region was recognised in type1 diabetes. The number of genetic regions causally implicated is now 11 each for type 1 and type 2 diabetes [ 19], and is set to rise further. The bewildering pace of new discovery standsin stark contrast to the slow progress that characterised the previous two decades, with a total combined output of three",
+      "It has proven to be challenging to isolate the genes underlying the genetic components conferring susceptibility to type 1 and type 2 diabetes. Unlike previous approaches, genome-wide association studies have extensively delivered on the promise of uncovering genetic determinants of complexdiseases, with a number of novel disease-associated variants being largelyreplicated by independent groups. This review provides an overview of these recent breakthroughs in the context of type 1 and type 2 diabetes, and",
+      "The history of diabetes genetics traces human genetic research more broadly.Initially, only a few polymorphic genetic markers were known, and these werestudiedinpopulation-basedassociationstudies.Withthedevelopmentofgenome-wide maps for family-based linkage analysis and of positional cloning, attentionturned to monogenic forms of disease. The application of family-based linkagemethods to common forms of diabetes, however, met with less clear success.More recently, with progress in genome sequencing and",
+      "the elucidation of the wide spectrum of genes that  played a role in the molecular mechanism of diabetes  development[142-144]. However , despite the vast flow of  genetic information including the identification of many  gene mutations and a large array of single nucleotide  polymorphisms (SNPs) in many genes involved in the  metabolic pathways that affect blood glucose levels,  the exact genetic mechanism of diabetes remains  elusive[145,146]. Evidently, a major complication is the",
+      "confirmed genes for type 2 diabetes and six for type 1(Fig. 1). At last, it seems, our understanding of the genetic basis of complex, multifactorial forms of diabetes is catching up with that of rarer, single-gene disorders. This leap in knowledge is the result of major advances in technology plus an improved understanding of patterns of human genetic variation. Using single nucleotide polymor- phism (SNP) chips it is now possible to analyse up to a million",
+      "make dissection of the black box of genetics of diabetespossible in the near future, but at this point, apart fromthe pro les that distinguish between type 1 and type 2 diabetes and a limited number of speci c variants that identify small subgroups of patients (MODY), genetics has not been successful in further differentiating subclasses ofdiabetes. Research Gaps After consideration of the known genetic associations with diabetes risk, consensus developed that the eld is",
+      "studies provide new insights into type 2diabetes aetiology. Nat Rev Genet 2007;8:657662 11. Grant RW, Moore AF, Florez JC. Genetic architecture of type 2 diabetes: recentprogress and clinical implications. Diabe-tes Care 2009;32:11071114 12. Dupuis J, Langenberg C, Prokopenko I,",
+      "early results have been excellent, yielding six  new replicating gene regions. Here I discuss the insights into type   2  diabetes genetics that have been provided by  these new findings. I consider where diabe - tes genetic studies might go from here, and  present a perspective that may be applicable  to other common traits. I also briefly discuss  the wider implications that surround the  identification of a common gene that predis - poses to type",
+      "that genetic studies will ultimately identify key genetic elements that help determine susceptibility to diabetes,disease progression, and responsiveness to specific therapies, as well as help identify novel targets for futureintervention. A substantial number of genetic loci, gene polymorphisms, and mutations have already beenreported as having variable degrees of association with one or other type of diabetes (type 1, type 2, maturityonset diabetes of the young [MODY]), while others appear to be involved",
+      "24. Varshney, A. et al. Genetic regulatory signatures underlying islet gene expression and type 2 diabetes. Proc. Natl. Acad. Sci. USA 114,   23012306 (2017).  25. Thurner, M. et al. Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 diabetes susceptibility loci. eLife  7,   e31977 (2018).  26. Gaulton, K. J. et al. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nat. Genet.  47,  14151425 (2015)."
+    ],
+    [
+      "genes relate directly to insulin secretion and indirectly, through collaborating with other genes, to insulin resistance. Thisseems to support the epidemiological evidence that environmentally triggered insulin resistance interacts with geneticallyprogrammed bcell dysfunction to precipitate diabetes. Citation: Jain P, Vig S, Datta M, Jindel D, Mathur AK, et al. (2013) Systems Biology Approach Reveals Genome to Phenome Correlation in Type 2 Diabetes. PLoS ONE 8(1): e53522. doi:10.1371/journal.pone.0053522",
+      "have been the subject of most follow-up studies to date.Specifically, we examined acute changes in expression of these genes in response to feeding and fasting and longer term changes in the expression of these genes inresponse to a diet high in fat and sugar, recognized as a critical environmental risk factor for type 2 diabetes. It has been hypothesized that most of the new genetic variants affect -cell function, development or survival but not insulin sensitivity [6]. Consistent with this,",
+      "or survival. However, we also found evidence that most of the genes could have potential roles in other metabolically-relevant tissues. Genes affecting insulinsensitivity may be expected to be expressed in peripheralinsulin sensitive tissues, such as liver and adipose tissue, and be responsive to metabolic status. Consumption of a high fat diet was associated with a tendency for the ex- pression of several of these genes to be decreased. Simi-larly, many of the genes were regulated by feeding and",
+      "secretion versus insulin sensitivity). We also sought todetermine whether any of these genes are regulated by conditions known to alter the expression of metabolic- ally relevant genes. We examined the expression of thesegenes under fasting and non-fasting conditions (e.g. in response to insulin), which might be altered if they affect peripheral insulin sensitivity. Consumption of diets high in fats and sugars is associated with risk of developing type 2 diabetes [34] and many genes that are critical for",
+      "regulating sugar metabolism. Moreover, genes that were",
+      "Figure 2: The role of type 2 diabetes genes in insulin secretion Pancreatic -cell genes associated with type 2 diabetes are in italics. G6P=glucose-6-phosphate. Adapted from Florez JC. Newly identi  ed loci highlight beta cell dysfunction as a key cause of type 2 diabetes: where are the insulin resistance genes? Diabetologia 2008; 51: 110010, by kind permission of the author and Springer Science + Business Media.  Positive calorie balance Cycle A++ Cycle B Liver fat  Insulin suppression of",
+      "tive Glis3  expression, which in turn drive increased levels of beta cell  apoptosis and senescence. Genetic susceptibility could be replicated  by elevated levels of dietary fat. Transcriptional analysis of human  islets identified the same genetic networks at play. Together, these  findings demonstrate both the important role of genetic variation in  beta cells for diabetes susceptibility and a mechanism by which the  Western diet may contribute to the growing diabetes epidemic. RESULTS",
+      "associated with fasting proinsulin levels and provides new insights into the  pathophysiology of type 2 diabetes. Diabetes 60, 26242634 (2011). 65. Saxena, R. etal. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat. Genet. 42, 142148 (2010). 66. Tobacco and Genetics Consortium. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat. Genet. 42, 441447 (2010).",
+      "38. Saxena R, Hivert M, Langenberg C, Tanaka T, Pankow JS, et al. (2010) Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet 42: 142148. doi:10.1038/ng.521. 39. Neale BM, Sham PC (2004) The future of association studies: gene-based analysis and replication. Am J Hum Genet 75: 353362. doi:10.1086/423901. 40. Saccone SF, Hinrichs AL, Saccone NL, Chase GA, Konvicka K, et al. (2007)",
+      "Nature Reviews | EndocrinologyFactors that aect insulin secretion and action  Body weight  Level of physical activity Smoking Heavy alcohol consumption Genetic predisposition Geneenvironment interaction Positive risk prole Negative risk prole Normoglycaemia/uni03B2-cell dysfunction and insulin resistanceAdipose tissue Skeletal muscle LiverInsulin-mediated  glucose production /uni2191Insulin-mediated glucose uptake /uni2193 Insulin-mediated glucose uptake /uni2193 Hyperglycaemia  Epigenetics"
+    ],
+    [
+      "Genes signifying increased risk for both type 1 and type 2 dia-betes have been identified. Genomewide association studies have identified over 50 loci associated with an increased genetic risk of type 1 diabetes. Several T1D candidate genes for increased risk of developing type 1 diabetes have been sug-gested or identified within these regions, but the molecular basis by which they contribute to islet cell inflammation and beta cell destruction is not fully understood. 12 Also, several",
+      "Genetics of Type 2 Diabetes Chapter 12 197400 multiallelic markers (short tandem repeats or microsatellites,  with a density of   1 marker/10   cmol) allows identi  cation of  polymorphic markers showing strong allele identity by descent in diabetic family members (i.e. allele sharing in sibships is signi  - cantly higher than 50%). Once identi  ed, such susceptibility  genes for diabetes may then be positionally cloned in the intervals of linkage.",
+      "3. Katsarou, A. etal. Type 1 diabetes mellitus. Nat. Rev. Dis. Primers 3, 17016 (2017). 4. Onengut-Gumuscu, S. etal. Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers. Nat. Genet.  47, 381386 (2015). 5. Barrett, J. C. etal. Genome-wide association study and meta-analysis find that over 40  loci affect risk of type 1 diabetes. Nat. Genet. 41, 703707 (2009).",
+      "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes n engl j med 359;21 www.nejm.org november 20, 2008 2229(Fig. 3). An increase in the BMI and a concomi - tant decrease in insulin sensitivity during the  8-year period were consistent findings, with no differences between subjects at high and low genetic risk (Fig. 3A and 3B). However, subjects with a high genetic risk did not increase their insulin secretion (disposition index) to compen -",
+      "and genetic markers to improve the prediction of type 2 diabetes: theEPIC-Potsdam Study. Diabetes Care . 2009;32:2116 2119 (in eng). 56. Cauchi S, Meyre D, Durand E, et al. Post genome-wide association studies of novel genes associated with type 2 diabetes show gene-gene interaction and high predictive value. PLoS One . 2008;3(5): e2031 . 57. Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med . 2008;359:2220 2232 (in eng).",
+      "etically expressed homeobox variant (rs1111875) on type 2 diabetes risk.  Molecular Genetics  and Metabolism  ,  102 (2), 194199.   Watanabe, R. M., Black, M. H., Xiang, A. H., Allayee, H., Lawrence, J. M., & Buchanan, T. A. (2007).  Genetics of gestational diabetes mellitus and type 2 diabetes.  Diabetes Care  ,  30 (Suppl. 2),  S134S140.   Williams, M. A., Qiu, C., Dempsey , J. C., & Luthy , D. A. (2003). Familial aggregation of type 2",
+      "markers, genetic markers do not change with disease progression.Dimas and collaborators examined the association of 37 establishedT2D susceptibility loci and indices of proinsulin processing, insulin secretion, and insulin sensitivity in 58,614 nondiabetic subjects [6]. Cluster analysis classi ed the risk loci into ve major categories on the basis of their association with glycemic phenotypes. The rst cluster was characterized by the effects of the risk alleles of PPARG ,KLF14 ,",
+      "recently, meta-analysis of GWAS data involving African  American type 2 diabetes patients identified similar loci  to the previous studies with the addition of two novel  loci, HLA-B and INS-IGF[157]. These results provide  strong evidence of common genetic determinants  including common specific genes that are linked to  diabetes. A small list of specific genetic markers seem  strongly associated with the risk of developing type 2  diabetes including the TCF7L2[158] and CAPN10[159,160]",
+      "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes n engl j med 359;21 www.nejm.org november 20, 2008 2231MPP subjects (P = 0.001) and from 0.79 to 0.83 in  the Botnia subjects (P = 0.006). Of the 16 loci that have been associated with  type 2 diabetes previously,8-15 we showed that 11   TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1,  CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX    were associated with an enhanced risk of future",
+      "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes n engl j med 359;21 www.nejm.org november 20, 2008 2227(Fig. 1B), whereas impaired fasting glucose or  impaired glucose tolerance developed in 313 of 2039 subjects (15.4%). Clinical Factors Predicting Incidence   of Diabetes In both the MPP and Botnia studies, a family his - tory of diabetes, an increased BMI, and increased levels of blood pressure and serum levels of tri -"
+    ],
+    [
+      "unraveling the pathophysiological mechanisms of this disease, identifying  candidate diabetic genes, and discovering and testing new therapeutic agents.  The classical rodent models of diabetes allow unbiased discovery, while the  new models made by genetic manipulation allow testing of the role of  specific genes and tissues. Experimental animal models are an irreplaceable  resource for diabetes research and are hastening the progress towards the  goals of better treatment, prevention, and cure.",
+      "is absence of reliable methods for generating specific celltypes,immunologicalrejectionofthetransplantedcells,anddifficulty in purification of specific lineages [55]. Furtherconcernsincludetheuncontrolledproliferationofthetrans-planted embryonic stem cells into a specific type, once theyaretransplanted[56].Still,despiteofitsmanifoldlimitationsboth scientific and ethical, the application of stem cell tech-nologyholdsimmenseprospectsintreatmentofdiabetes. 6. Gene Therapy in Diabetes",
+      "T ogether, these discoveries will continue to improve our  understanding of the biologic mechanisms that maintain glucose homeostasis, and of still hidden  molecular defects leading to  chronic hyperglycemia, and could also lead to the development of more speci  cally targeted antidiabetic drugs or even gene -  based therapies. Moreover, pharmacogenetic testing might then be used to predict, for each patient, the therapeutic response to different classes of drugs. The identi  cation of T2DM genes will",
+      "Greatstrideshavebeenmadeclinicallyintheprevention, development,andtreatmentofthediseasebutnotherapeuticmethod have been completely successful till date. With newtechnologies revolutionizing the treatment possibilities, thesearch for an effective medication is not far ahead. Theextensive research leading to the discovery of the pathwaygenes contributing to the development of the disease andthe sequencing of complete genomes have revolutionized the diabetes research. The development of the techniques",
+      "into different genetic levels of disease categories, from which pre- vention or treatment methods could be provided accordingly [ 4]. For example, some forms of diabetes are directly related to a change in a single gene [ 34]. Some patients who are diagnosed with type 1 diabetes can now be tested for one of monogenic diabetes. The appropriate treatment for these patients is not injecting insulin, but giving oral sulfonylureas [ 34]. Moreover, it is now well understood",
+      "pp .430435,2003. [58] M. Zalzman, S. Gupta, R. K. Giri et al., Reversal of hyperglycemia in mice by using human expandable insulin- producing cells differentiated from fetal liver progenitor cells,Proceedings of the National Academy of Sciences of the United StatesofAmerica ,vol.100,no .12,pp .72537258,2003. [59] H.-S. Jun and J.-W. Yoon, Approaches for the cure of type 1 diabetes by cellular and gene therapy, Current Gene Therapy , vol.5,no.2,pp.249262,2005.",
+      "transgenics. It is likely that animal models will play an importantrole in the eventual cure of human diabetes mellitus.  Competing interests  None declared.  References  1Sima AAF, Shafrir E, eds.   Animal Models of Diabetes: A Primer.  Amsterdam: Harwood Academic Publishers, 2000. 2British Union for the Abolition of Vivisection. Home page. Available from: http://www.buav.org. 3Patterson C.   Eternal Treblinka. Our Treatment of Animals and the Holocaust  . New York: Lantern Books, 2002. 4Regan T.",
+      "Third, this view of diabetes pathogenesis is consistent with the growing portfolio of available therapies. We have agents and interventions that can prevent or ameliorate diabetesthrough, for example, beneficial effects on islet function (e.g. sulfonylureas), obesity (weight loss), insulin resistance (e.g. exercise), fuel partitioning (e.g. thiazolidinediones) andmicrobiome content (metformin, possibly). Just as diabetes risk alleles influence metabolic phenotype through pushing",
+      "aprospectivetherapeuticapproachfortype1diabetes[59]. Thein vivogene therapy is the method of choice as a therapeutic strategy because it is simpler and the vectorcontaining the desired gene is directly inserted into thepatient, but the development of safe (not toxic to host)and effective vectors remains as a challenging task for genetherapist. Presently, the strategies for in vivotherapy involve",
+      "betacellulin gene therapy induces islet neogenesis in the liver a n dr e v e r s e sd i a b e t e si nm i c e ,  Nature Medicine ,v o l .9 ,n o .5 , pp.596603,2003. [73] S. Ferber, A. Halkin, H. Cohen et al., Pancreatic and duode- nal homeobox gene 1 induces expression of insulin genes inliver and ameliorates streptozotocin-induced hyperglycemia, Nature Medicine ,vol.6,no .5,pp .568572,2000. [74] P.A.Halban,S.E.Kahn, A.Lernmark,andC.J.Rhodes,Gene andcell-replacementtherapyinthetreatmentoftype1diabetes."
+    ],
+    [
+      "to improve diagnosis. Monogenic vs. polygenic diabetes   Monogenic and polygenic diabetes are traditionally considered distinct, with  monogenic diabetes resulting from one highly penetrant variant in one gene in a given  individual, and polygenic diabetes resulting from the contribution of several variants with  smaller effects in the context of environmental/lifestyle factors.  In T1D, autoimmune  dysfunction is the prominent mechanism, with variation in the major histocompatibility",
+      "represent about 2%-5% of diabetes patients. Mono - genic diabetes results primarily from gene defects that  lead to a decrease in beta cell number or function.  Monogenic diabetes genes were identified using linkage  studies or code for proteins that directly affected  glucose homeostasis. The majority of genes responsible  for monogenetic diabetes code for either transcription  factors that participate in the control of nuclear gene  expression or proteins that are located on the cell",
+      "diabetic patients inwhom rare, highly penetrant mutations ofasingle gene cause their diabetes (13). While com - mon variants ofthese genes that make a small contribution topolygenic diabetes may also exist (13), thevariants causing monogenic diabetes have limited util- ityinpharmacogenetics duetotheir low allele frequency. Thevast majority oftype 2diabetes patients have polygenetic forms ofthedisease that typically also require a permissive environment (e.g., obesity, sed-",
+      "diabetes exist along more of a continuum than previously appre - ciated. Therefore, knowledge about monogenic diabetes not only  provides opportunities for etiology-based treatment of the minori- ty of individuals with highly penetrant variants, but also informs  broader understanding of diabetes etiology. Types of monogenic diabetes Maturity-onset diabetes of the young MODY comprises most monogenic diabetes cases, with classical  characteristics of young diagnosis age, family history of diabe -",
+      "Monogenic Diabetes   Monogenic diabetes is a class of diabetes associated with genetic defects in beta - cell function. They are frequently associated with early onset of hyperglycemia (typically before 25 years of age). Three common forms of mono-genic diabetes include maturity - onset diabetes of the",
+      "HNF4A-MODY  and requires genetic testing to diagnose. Here  we will describe monogenic diabetes types, etiologies, diagnosis,  management, and strategies to improve diagnosis. Monogenic versus polygenic diabetes Monogenic and polygenic diabetes are traditionally considered  distinct, with monogenic diabetes resulting from one highly pene - trant variant in one gene in a given individual and polygenic diabe - tes resulting from the contribution of several variants with smaller",
+      "Monogenic inheritance is caused by mutation of a single gene. There are  some well-defined monogenic rodent models. In humans, monogenic obesity  and diabetes exist as well, but are extremely rare.  Polygenic inheritance is the result of multiple contributing genes and  is the predominant mode of inheritance in human type 2 diabetes. Multiple  polygenic animal models are also available. However, even in monogenic  animal models, genetic background plays an important influence. For",
+      "(Mendelian) that may also cause type 2 diabetes (Yang & Chan, 2016). More than twenty genes highly expressed in pancreatic cells have been identified within these mono-genic subtypes (AlkortaAranburu et al., 2014). Recently, two national surveys revealed that most patients with mono-genic diabetes are likely to be unrecognized and misdiag-nosed as type 1 or type 2 diabetes (Delvecchio et al., 2017; Johansson et al., 2017). Genetic diagnosis leads to improved treatment, better prediction of disease",
+      "Key words: diabetes, gene, polygenic, monogenic Introduction Diabetes is one of the most common metabolic disor - ders. It is estimated that the number of diabetes pa - tients worldwide has already exceeded 200 million [92]. This creates a need to understand the etiology ofthe disease, genetic and enviromental factors influ - encing development of diabetes. Diabetes is a group of metabolic diseases that are characterized by ele - vated glucose level. Poorly controlled or undiagnosed",
+      "2   1.1.2 Introduction  Monogenic diabetes is caused by a single defect in one of over 40 genes1,2. Since  MODY (maturity onset diabetes of the young) was named by Fajans for the T2D -like  presentation in young people with an autosomal dominant pattern of inheritance3,4, our  understanding of phenotypic and genetic heterogeneity in monogenic diabetes has  increased. The major monogenic diabetes categories are MODY, neon atal diabetes"
+    ],
+    [
+      "by performing a genetic profile on diabetic patients (pharmacogenetics).  Furthermore, identification of genetic determinants of diabetic patients will  better define the targets of current and future therapies, and will lead to  therapies that are more specific for their genetic constitutes.  SUMMARY  With the advancement of the Human Genome Project, we enter the  era of a sequence-based biology. Some progress has been made in the",
+      "Todate,studiesofdiabeteshaveplayedamajorroleinshapingthinkingabout thegeneticanalysisofcomplexdiseases.Basedontrendsingenomicinformationandtechnology,combinedwiththegrowingpublichealthimportanceofdiabetes,diabetes will likely continue to be an important arena in which methods will bepioneeredandlessonslearned.Itiswithgreatenthusiasmthatwelookforwardtothis effort, and with avid curiosity we await to see whether the lessons of todaywill be supported by the data of tomorrow.",
+      "DNA code. Therefore, greater unders tanding of the epigenetic basis of disease could enable the 576  discovery new therapeutic targets for the treat ment of numerous human diseases including 577  diabetes and its complications. 578   579  580",
+      "T ogether, these discoveries will continue to improve our  understanding of the biologic mechanisms that maintain glucose homeostasis, and of still hidden  molecular defects leading to  chronic hyperglycemia, and could also lead to the development of more speci  cally targeted antidiabetic drugs or even gene -  based therapies. Moreover, pharmacogenetic testing might then be used to predict, for each patient, the therapeutic response to different classes of drugs. The identi  cation of T2DM genes will",
+      "research will contribute positive ly to the life of people living with T1D . Being able pinpoint  mutations, and then discover how they contribute to the genetic  cause  of a condition, can help  to open up path s for pharmaceutical treatments. Currently, m ost treatment strategies for genetic  disorders do not alter the underlying genetic mutation;  but are designed to improve particular  signs and symptoms associated with the disorder. For instance, T1D  is managed by",
+      "Epigenomic approaches: applications in diabetic complications research Epigenetic studies in human disease have been greatly accel- erated as a result of advances in whole-genome and epige- nome profiling technologies as well as bioinformatics andgenomic data analysis platforms [ 99,100]. DNAme is analysed using bisulfite conversion of genomic DNA, immu- noprecipitation of methylated DNA, followed byhybridisation to arrays or next-generation sequencing to ob-",
+      "new therapeutic targets and identify potential diabetic neuropathy biomarkers. The genes identied in the current study conrm datagathered from experimental models of diabetes and provide a comprehensive picture of the expression of multiple targets in asingle human tissue sample. Our initial analyses of this data set classied the patient samples based on myelinated bre density and found that two large groups emerged; those with a loss of myelinated bre density 5500 bres/mm",
+      "DNA variation with disease processes in a range of settings, from cell lines to human populations, and major advances have been made in coupling these complex datasets with information about extrinsic environmental exposures including drug prescription in ways that allowthe logical interrogation of gene-drug and gene-lifestyle interactions. Doing so may teach us about disease etiology and help stratify type 2 diabetes (T2D) into subclasses that can be treated more effectively, with",
+      "that genetic studies will ultimately identify key genetic elements that help determine susceptibility to diabetes,disease progression, and responsiveness to specific therapies, as well as help identify novel targets for futureintervention. A substantial number of genetic loci, gene polymorphisms, and mutations have already beenreported as having variable degrees of association with one or other type of diabetes (type 1, type 2, maturityonset diabetes of the young [MODY]), while others appear to be involved",
+      "the onset and progression of diabetic neuropathy is of primeimportance. The current study takes an important rst step towards this goal by identifying specic sets of genes whose expression accurately classies patient samples with regard to diabetic neuropathy pro- gression and by analysing their interactions within known cellularpathways. Identifying common elements in these complex net-works will yield novel insights into disease pathogenesis, provide"
+    ]
+  ],
+  "task_id": [1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9,10]
+}
\ No newline at end of file