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              "content": "Genetic mutations in the insulin gene can significantly affect glucose metabolism in several ways:\n\n1. 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].\n\n2. 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].\n\n3. 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].\n\n4. 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].\n\nOverall, genetic mutations in the insulin gene can disrupt normal insulin synthesis and function, leading to impaired glucose metabolism and conditions such as diabetes.",
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              "text": "Mutations that result in mutant insulin or the \ninability to convert proinsulin to insulin result in gl ucose \nintolerance in some of these cases. Genetic defects \nin the insulin receptor or in the signal transduction \npathway of insulin have been demonstrated to result in \nhyperinsulinemia and modest hyperglycemia to severe \ndiabetes[1]. \nDisease of the exocrine pancreas\nDamage of the  cells of the pancreas due to diffused \ninjury of the pancreas can cause diabetes. This damage",
              "title": "2015 - Diabetes mellitus The epidemic of the century.pdf",
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              "text": "A, et al. Insulin gene mutations resulting in early-onset diabetes:\nmarked differences in clinical presentation, metabolic status, and\npathogenic effect through endoplasmic reticulum retention.\nDiabetes. 2010;59:653 61.\n21. Steele AM, Shields BM, Wensley KJ, Colclough K, Ellard S,\nHattersley AT. Prevalence of vascular complications among pa-\ntients with glucokinase mutations and prolonged, mild hyperglyce-\nmia. JAMA. 2014;311:279 86.22. Chakera AJ, Spyer G, Vincent N, Ellard S, Hattersley AT, Dunne FP.",
              "title": "2019 - How Recent Advances in Genomics Improve Precision Diagnosis.pdf",
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              "text": "presumed glucose toxicity (34). The finding that a mutation\nof a single nucleotide in the gene encoding the glucokinase\nenzyme can result in NIDDM lends credibility to the hypoth-\nesis that inherited defects in insulin production contribute to\nNIDDM (6). Increased insulin demand of obesity and insulin\nresistance is accompanied by enhanced insulin biosynthesis,",
              "title": "1994 - Isolation of the Human LIMTHomeodomain Gene Islet-1.pdf",
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              "text": "insulin synthesis and function while mutations in the insulin gene ( INS)\nobviously affect the key hormone made by pancreatic beta cells [62].\nATP synthesis defect (mitochondrial diabetes) and mutations in ATP-\nsensitive potassium channel subunits (channel-building Kir6.2 [po-\ntassium inwardly-rectifying channel, subfamily J, member 11;KCNJ11 ] and regulatory SUR1 [ATP-binding cassette transporter\nsubfamily C member 8], ABCC8 ) all affect insulin secretion [63].",
              "title": "2016 - Dissecting diabetes metabolic disease.pdf",
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              "text": "Insulin gene mutations \nInsulin is synthesized in 13-cells of the islets of Langerhans and is a \ncentral honnone that maintains glucose homeostasis. Insulin-deficient mice \ndie shortly after birth due to severe hyperglycemia.53 All cell types of the \nendocrine pancreas are present in insulin deficient mice suggesting that \ninsulin is not required for development and differentiation of the endocrine \npancreas. 53 \nNaturally occurring mutations in the insulin gene that result in the",
              "title": "2004 - Diabetes Genes a.pdf",
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              "text": "Theprevalenceofgeneticmutationsaffectingthestructure\noftheinsulinmoleculeinthegeneralpopulationisunknown.\nUptothepresent,onlythosepatientsmanifestingthemutant\ninsulinsyndrome(5-8,36)withunusualorfamilialTypeII\ndiabeteshavebeenscreenedanddiscovered.Thus,mutantin-\nsulinspecieswithnormalorrelativelywell-preservedbinding\nandbiologicalactivitycharacteristics,andthereforenormal\nmetabolicclearances,areunlikelytobediscoveredbythisap-\nproachsincehyperinsulinemiawillbeabsentorsubtle.Future",
              "title": "1986 - Diabetes due to secretion of a structurally abnormal insulin.pdf",
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              "text": "at various steps, resulting in an impaired insulin action and potential \ndevelopment of extreme insulin resistant clinical conditions. Many mutations \nhave been identified in the insulin receptor gene. These mutations may lead \nto: \n Decreased insulin receptor biosynthesis \n Premature chain termination in extracellular or intracellular domain \n Accelerated receptor degradation \n Defect in the receptor transport to plasma membranes \n Decreased insulin binding affinity \n Impaired tyrosine kinase activity",
              "title": "2004 - Diabetes Genes a.pdf",
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              "text": "15. Steiner DF, Tager HS, Chan SJ, et al . Lessons learned from\nmolecular biology of insulin-gene mutations. Diabetes Care\n1990; 13: 600609.\n16. Vionnet N, Stoffel M, Takeda J, et al . Nonsense mutation in the\nglucokinase gene causes early-onset non-insulin-dependent\ndiabetes mellitus. Nature 1992; 356 : 721722.\n17. Sakagashira S, Sanke T, Hanabusa T, et al . Missense mutation of\namylin gene (S20G) in Japanese NIDDM patients. Diabetes\n1996; 45: 12791281.",
              "title": "2001 - Genomic variation in pancreatic ion channel genes in Japanese type 2 diabetic patients.pdf",
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              "text": "vating mutations in the gene encoding\nKir6.2 alter fetal and postnatal growthand also cause neonatal diabetes. J\nClin Endocrinol Metab 2006; 91(7):\n27822788.\n93. Stoy J, Edghill EL, Flanagan SE, et al.\nInsulin gene mutations as a cause\nof permanent neonatal diabetes. Proc\nNatl Acad Sci U S A 2007; 104(38):\n1504015044.\n94. Pulizzi N, Lyssenko V, Jonsson A, et al.\nInteraction between prenatal growth\nand high-risk genotypes in the devel-opment of type 2 diabetes. Diabetolo-\ngia2009; 52(5): 825829.",
              "title": "2011 - Genome-wide association studies (GWAS) impact.pdf",
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              "text": "(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",
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              "content": "The most common genetic loci associated with an increased risk of Type 2 diabetes include:\n\n1. **TCF7L2** [2], [5], [7]\n2. **KCNJ11** [2], [5]\n3. **PPARG** [2], [5]\n4. **CDKAL1** [2], [5], [7]\n5. **CDKN2A/CDKN2B** [2], [5], [7]\n6. **IGF2BP2** [2], [5], [7]\n7. **SLC30A8** [2], [5], [7]\n8. **FTO** [2], [5]\n9. **HHEX** [2], [5], [7]\n\nThese loci have been identified and replicated in multiple studies as being associated with an increased susceptibility to Type 2 diabetes.",
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              "text": "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,\nChines PS, Narisu N, Bonnycastle LL, et al:Comprehensive association\nstudy of type 2 diabetes and related quantitative traits with 222\ncandidate genes. Diabetes 2008, 57(11) :3136-3144.\n6. Hu C, Zhang R, Wang C, Wang J, Ma X, Lu J, Qin W, Hou X, Bao Y, Xiang K,\net al:PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX,",
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              "text": "ly associated with type 2 diabetes: TCF7L2, KCNJ11,  \nand PPARG .\n5-7 However, in 2007, a number of novel \ngenetic variants ( CDKAL1, IGF2BP2,  the locus on \nchromosome 9 close to CDKN2A/CDKN2B, FTO, \nHHEX, SLC30A8,  and WFS1)8-14 were shown to in -\ncrease susceptibility to type 2 diabetes in repro -\nducible studies. Furthermore, a recent meta-analy -\nsis identified six novel variants ( JAZF1, CDC123/\nCAMK1D, TSPAN8/LGR5, THADA, ADAMTS9, and NOTCH2 ) that are associated with type 2 dia -\nbetes.\n15",
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              "text": "2009. There are now at least 19 loci containing genes that increase\nrisk of T2D, including PPARG [27], KCNJ11 [27], KCNQ1 [28,29],\nPLoS Genetics | www.plosgenetics.org 1 February 2010 | Volume 6 | Issue 2 | e1000847",
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              "text": "et al. Association between type 2 diabetes loci and measures of fatness. PLoS One 5,\ne8541 (2010).\n22 Ng, M. C., Park, K. S., Oh, B., Tam, C. H., Cho, Y. M., Shin, H. D. et al. Implication of\ngenetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and\nFTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 57,22262233 (2008).\n23 Thorsby, P. M., Midthjell, K., Gjerlaugsen, N., Holmen, J., Hanssen, K. F., Birkeland, K. I.",
              "title": "2012 - Association between type 2 diabetes genetic susceptibility loci and visceral and subcutaneous fat area as determined by computed tomography.pdf",
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              "text": "Genome-wide association studies validated these old culprits of T2D and expanded them to include\nhundreds of single-nucleotide variants (SNVs) that represent more than 150 genomic loci that are\nassociated with T2D, insulin secretion, and insulin resistance [ 11]. Besides TCF7L2 ,PP ARG , and\nKCNJ11 loci, the most replicated T2D susceptibility variants identied in GWASs were found in and\naround CDKN2A/2B ,IGF2BP2 ,SLC30A8 ,CDKAL1 and FTO genes [ 1215]. The variants that are most",
              "title": "2018 - High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes.pdf",
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              "text": "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.\n20. Dupuis J, Langenberg C, Prokopenko \nI, et al. New genetic loci implicated in fasting glucose homeostasis and their im -\npact on type 2 diabetes risk. Nat Genet 2010;42:105-16.\n21. Qi L, Cornelis MC, Kraft P, et al. Ge -\nnetic variants at 2q24 are associated with susceptibility to type 2 diabetes. Hum Mol Genet 2010;19:2706-15.",
              "title": "2010 - Genomics, Type 2 Diabetes, and Obesity.pdf",
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              "text": "multiple loci associated with susceptibility to type 2 diabetes, includ-\ningTCF7L2 (transcription factor 7-like 2), which had been originally\nidentied by a large-scale association mapping prompted by prior\nevidence of linkage in that area2,SLC30A8 (solute carrier family 30\nmember 8), HHEX (haematopoietically expressed homeobox),\nCDKAL1 (CDK5 regulatory subunit associated protein 1-like 1),\nCDKN2A/B (cyclin-dependent kinase inhibitor 2A/B) and IGF2BP2\n(insulin-like growth factor 2 mRNA-binding protein 2)37.",
              "title": "2008 - SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes.pdf",
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              "text": "associated with susceptibility to type 2 diabetes mellitus. Nat Genet 2008; 40: 109297 .\n74 Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are \nassociated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genet 2008; 40: 1098102.\n75 Lyssenko V, Lupi R, Marchetti P, et al. Mechanisms by which \ncommon variants in the TCF7L2 gene increase risk of type 2 diabetes. J Clin Invest 2007; 117: 215563. \n76 Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA",
              "title": "2010 - Diabetes in Asia.pdf",
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              "text": "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].\nObesity is the greatest risk factor for type 2 diabetes\nmellitus, as it is known to induce insulin resistance via variousmechanisms ( TNF \n \n release, free fatty acids, etc.). Both",
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              "text": "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes\nn engl j med 359;21 www.nejm.org november 20, 2008 2231MPP subjects (P = 0.001) and from 0.79 to 0.83 in \nthe Botnia subjects (P = 0.006).\nOf the 16 loci that have been associated with \ntype 2 diabetes previously,8-15 we showed that 11 \n TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, \nCDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX   \nwere associated with an enhanced risk of future",
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              "content": "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].",
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              "text": "BMC Medical Genomics  2009, 2:72 http://www.biomedcentral.com/1755-8794/2/72\nPage 2 of 8\n(page number not for citation purposes)Background\nGenome-wide association study (GWAS) offers unbiased\nways 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",
              "title": "2009 - Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus.pdf",
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              "text": "GWAS have successfully identified genetic loci associ-\nated with a variety of conditions such as type 2 diabetes2\nand coronary disease.35The large number of statistical\ntests required in GWAS poses a special challenge because\nfew studies that have DNA and high-quality phenotypedata are sufficiently large to provide adequate statisticalpower for detecting small to modest effect sizes.\n6Meta-\nanalyses combining previously published findings have im-proved the ability to detect new loci.",
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              "text": "diabetes mellitus6,7. However, the traditional GWAS ignored a\nlarge number of loci with moderate effects, because of the strin-gent signi cance thresholds used.\nGene-based analysis takes a gene as a basic unit for\nassociation analysis. As this method can combine genetic\ninformation given by all the SNPs in a gene to obtain moreinformative results\n8, it is being used as a novel method com-\nplementing SNP-based GWAS to identify disease susceptibilitygenes. Notably, this method can increase our chance of nd-",
              "title": "2014 - Identification of novel risk genes associated with type 1 diabetes mellitus.pdf",
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              "text": "1. Genome-wide association studies (GW AS) have made considerable progress in identifying genetic risk \nfactors 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 -\nticipants and identified 243 genome-wide significant loci (403 distinct genetic variants) associated with T2D risk",
              "title": "2020 - Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study.pdf",
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              "text": "that a genome-wide approach could uncover \npreviously unexpected disease pathways.\nIn early 2007, GW AS provided by far the \nbiggest increment to date in our knowledge of \nthe genetics of this common health problem.\nSix new gene regions identified\nTogether, the six recent GW AS papers \nprovide convincing evidence for six new \ngene regions involved in type\n \n2 diabetes1621; \na seventh publication describes how one \nof these variants alters BMI and represents by far the best example of an association",
              "title": "2007 - Genome\u2013wide association studies provide new insights into type 2 diabetes aetiology..pdf",
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              "text": "Abstract\nGenome-wide association studies (GWASs) have discovered association of several loci with Type 2 diabetes (T2D), a\ncommon complex disease characterized by impaired insulin secretion by pancreatic bcells and insulin signaling in target\ntissues. 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",
              "title": "2013 - Systems Biology Approach Reveals Genome to Phenome Correlation in Type 2 Diabetes.pdf",
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              "text": "mechanisms of DR remain poorly understood.\nA genome-wide association study (GWAS) is a powerful tool\nto identify genetic loci for complex diseases, and a large number\nof genetic loci for the susceptibility to various diseases, such astype 2 diabetes, have been successfully identified through GWAS\n(69). GWAS for DR have been performed, but most of the studies\nonly reported suggestive signals with no replication ( 5)b e c a u s e\nof their limited sample sizes. Recently, several loci with genome-",
              "title": "2021 - Genome-wide association studies identify two novel loci.pdf",
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              "text": "kidney disease, several loci have been identi ed and validated,\nbut the results were quite heterogenic across different popula-\ntions and depended on the type of diabetes and stage of disease.\nThe major bene t of GWAS results is to be found in the in-\ncreased understanding of disease mechanism and identi ca-\ntion of novel pathways and possibly new therapeutic targets.Follow-up studies are important in order to identify variants\nwith speci c biological effect and may provide important",
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              "text": "Abstract\nGenome-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 -",
              "title": "2020 - Identification of novel functional CpG-SNPs associated with type 2 diabetes and coronary artery disease..pdf",
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              "text": "linkage or association data. But, none of these studies include in\nthe analysis existing data from GWAs.\nFinally, a recent study identied additional susceptibility loci\nfor type 2 diabetes by performing a meta-analysis of three\npublished GWAs.21As acknowledged by the authors, GWAs\nare limited by the modest effect sizes of individual common\nvariants and the need for stringent statistical thresholds. Thus,\nby combining data involving 10,128 samples, the authors found",
              "title": "2009 - Gene prioritization based on biological plausibility over genome wide association studies renders new loci associated with type 2 diabetes.pdf",
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              "content": "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].",
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              "text": "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-",
              "title": "2010 - Genetics of Type 1 Diabetes What\u2019s Next.pdf",
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              "text": "II HLA gene associated with type 1 diabetes maps to the 240-kbregion near HLA-B. Diabetes 49: 22172221, 2000.\n303. Nejentsev S, Howson JM, Walker NM, Szeszko J, Field SF.\nLocalization of type 1 diabetes susceptibility to the MHC class Igenes HLA-B and HLA-A. Nature 450: 887892, 2007.\n304. Nejentsev S, Walker N, Riches D, Egholm M, Todd JA. Rare\nvariants of IFIH1, a gene implicated in antiviral responses, protectagainst type 1 diabetes. Science 324: 387389, 2009.",
              "title": "2011 - Type 1 Diabetes Etiology, Immunology.pdf",
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              "text": "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",
              "title": "2010 - Genetics of Type 1 Diabetes What\u2019s Next.pdf",
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              "text": "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 -\ngion, confer most of the genetic risk for type 1 dia -\nbetes. Genes outside the HLA region also con -\ntribute to the risk of type 1 diabetes, but their individual contributions are much smaller than that of HLA.",
              "title": "2009 - Genetics of Type 1A Diabetes.pdf",
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              "text": "Benkalha and Polychronakos, 2008 ). Other genetic loci ( Table 1) are\nbelieved to in uence population-level risk for T1D, although it is poorly\nunderstood how these non-HLA loci contribute to disease susceptibility\n(Ram et al., 2016a ).\n2.1. Human leukocyte antigen (HLA)\nThe association between T1D and the HLA complex was rst de-\nmonstrated in 1973 following observation of an increased frequency ofHL-W15 (HLA antigen) in T1D patients compared to controls ( Singal",
              "title": "2018 - The genetic architecture of type 1 diabetes mellitus.pdf",
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              "text": "cyte Antigen (HLA) gene region in immune regulation, and ready availability of\nserologic markers, led investigators to discover the association between certainHLAalleles and T1D in the early 1970s (33,130,158). The global importance of\ntheHLAonT1Dhassincebeenconrmedingenome-widescansforlinkage:All\nsuchscansperformedtodateshowamajorlocusatthe HLA(28,32,36,78,119).\nThefractionofallgeneticrisk,whichcanbeattributedtothecontributionof HLA\ngenes to T1D susceptibility, is about 44%, with a \nSof3.4 (160).",
              "title": "2003 - The Inherited Basis of Diabetes Mellitus.pdf",
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              "text": "The major histocompatibility complex (MHC) on chromosome 6\nis associated with susceptibility to more common diseases than\nany other region of the human genome, including almost all dis-\norders classified as autoimmune. In type 1 diabetes the major\ngenetic susceptibility determinants have been mapped to the\nMHC class II genes HLA-DQB1 andHLA-DRB1 (refs 13), but\nthese genes cannot completely explain the association between\ntype 1 diabetes and the MHC region411.Owing to the regions",
              "title": "2007 - Localization of type 1 diabetes susceptibility to the MHC Class 1 Genes.pdf",
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              "text": "The HLA class I A locus a ects susceptibility to type 1 diabetes. Hum. Immunol. 63,\n657 664. pii). https://doi.org/S0198885902004214 .\nNoble, J.A., Valdes, A.M., Cook, M., Klitz, W., Thomson, G., Erlich, H.A., 1996. The role of\nHLA class II genes in insulin-dependent diabetes mellitus: molecular analysis of 180\nCaucasian, multiplex families. Am. J. Hum. Genet. 59, 1134 1148 .\nNoble, J.A., Valdes, A.M., Thomson, G., Erlich, H.A., 2000. The HLA class II locus DPB1",
              "title": "2018 - The genetic architecture of type 1 diabetes mellitus.pdf",
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              "text": "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",
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              "text": "the 240-kb region near HLA-B. Diabetes 49,22172221 (2000).\n6. Lie, B. A. et al. The predisposition to type 1 diabetes linked to the human leukocyte\nantigen complex includes at least one non-class II gene. Am. J. Hum. Genet. 64,\n793800 (1999).\n7. Valdes, A. M. et al. Extended DR3 D6S273-HLA-B haplotypes are associated\nwith increased susceptibility to type 1 diabetes in US Caucasians. Tissue Antigens\n65,115119 (2005).\n8. Valdes, A. M., Erlich, H. A. & Noble, J. A. Human leukocyte antigen class I B and C",
              "title": "2007 - Localization of type 1 diabetes susceptibility to the MHC Class 1 Genes.pdf",
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              "content": "Genetic differences contribute to variations in diabetes prevalence among different populations in several ways:\n\n1. **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].\n\n2. **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].\n\n3. **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].\n\n4. **Risk Allele Frequencies**: Human populations exhibit substantial variation in risk allele frequencies, which contributes to different susceptibilities to diseases, including diabetes, among populations [7].\n\n5. **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].\n\nOverall, 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.",
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              "text": "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-",
              "title": "2017 - diabetes-mellitus-in-developing-countries-and-underserved-commun-2017.pdf",
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              "text": "nants of type 2 diabetes between immigrant and native populations. Some studies in South Asian (Indian) populations suggest that genetic differ-ences may exist [ \n17 ,  30 ], but larger studies are \nneeded to get better insight into this issue.  \n    Prevalence Estimates \n The prevalence of diabetes in minorities is affected by ethnicity and country of residence. In one study in the UK [ \n59 ], standardized preva-",
              "title": "2017 - diabetes-mellitus-in-developing-countries-and-underserved-commun-2017.pdf",
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              "text": "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",
              "title": "2005 - Type 2 diabetes mellitus from genes to disease.pdf",
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              "text": "across different races or populations but show ethnicity-\nspecific differences. The pathogenesis of T2D involves \ngenetic variants in the candidate genes. The interactions \nbetween the genes involved in insulin signaling and secre -\ntory pathways are believed to play an important role in \ndetermining an individuals susceptibility towards T2D. \nTherefore, the present study was initiated to examine the \ndifferences, if any, in the contribution of polymorphisms",
              "title": "2016 - Association of genetic variants in INS (rs689), INSR (rs1799816) and PP1G.G (rs1799999) with type 2 diabetes (T2D) a case\u2013control study in three ethnic groups from N.pdf",
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              "text": "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\n99",
              "title": "2007 - Bioethnic Conscription Genes, Race.pdf",
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              "text": "-\ntion 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.",
              "title": "2019 - Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics.pdf",
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              "text": "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\nof the United States, with the highest prevalence\nobserved in Puerto Ricans. Ge netic variants responsible",
              "title": "2011 - Dating the age of admixture via wavelet.pdf",
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              "text": "populations and across countries. World-wide differences in prevalence of theforms of diabetes necessitates inclusion\nof 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.\nThe communication strategy used by\nthe interventionalist and the patient s",
              "title": "2020 - Precision Medicine in Diabetes.pdf",
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              "text": "were  positively  associated  with  country  level  income  [49].\nHowever,  the  drivers  for  the  observed  pattern  with  geographi-\ncal  differences  and  varying  time  trends  are  still  unclear.\nSusceptibility  to  type  1  diabetes  denitely  has  a  strong  genetic\ncomponent  (HLA  genotype)  [50],  but  the  heterogeneity  of  type\n1  diabetes  cannot  be  explained  solely  by  the  prevalence  of\nsusceptibility  genes  [5153] .  Thus,  the  reasons  for  changes  in",
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              "text": "twice higher than that of 2010  [3] .\n  The genetic influences on the prevalence of type 2 diabetes i n the Asian population are \nmainly related to insulin secretion capacity  [4] ; other genes involved in the risk of type 2 \ndiabetes are not substantially different in other ethnic groups   [5] . The most relevant genes \ncontributing to ethnic differences are associated with insulin secretion capacity, and they are",
              "title": "2016 - TRPV1 Gene Polymorphisms Are Associated with Type 2 Diabetes by Their Interaction with Fat Consumption in the Korean Genome Epidemiology Study.pdf",
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              "content": "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].\n\nVariants 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].",
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              "text": "The transcription factor peroxisome-proliferator-\nactivated receptor gamma (PPAR g) is known to\ninuence insulin sensitivity, and acts partly via amodulation of the circulating adiponectin level\n(PPAR gagonists increase the adiponectin level)\n(Ref. 38). The PPAR gP12A SNP is a well-\nestablished genetic variant that modulates\ninsulin sensitivity and the risk of type 2 diabetes\n(Ref. 39). In a Chinese family study, Yang et al.demonstrated a genetic interaction between the",
              "title": "2006 - Adiponectin, type 2 diabetes and the metabolic syndrome.pdf",
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              "text": "intricate regulation of PPAR signaling to pave the way to tailored therapies in patients with insulin resistance and T2D.\nKeywords PPARG genetic variants .Dominant-negative isoforms .Post-tranlational modifications .Adipose tissue\ndysfunctions .Drug responsiveness .Type 2 diabetes\nIntroduction\nPeroxisome proliferator activated receptor gamma (PPAR )\nis a ligand-activated transcription factor belonging to the nu-",
              "title": "2021 - PPAR\u03b3 and Diabetes Beyond the Genome and Towards Personalized Medicine.pdf",
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              "text": "2 . A widespread \nGly482Ser polymorphism of PGC1 -    (known as  PPARGC1  ), a \ntranscriptional coactivator of a series of nuclear receptors includ-ing  PPARG  , has been associated with a 1.34 genotype relative risk \nof T2DM  [93] . In this study, a test for interaction with the Pro12Ala variant in  PPARG   gave no indication for additive effects \non diabetes status. \n Other genes have been shown to be implicated in the genetic",
              "title": "2010 - The Genetics of Type 2 Diabetes.pdf",
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              "text": "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",
              "title": "2008 - Glossary of Genetics Genomics Terms.pdf",
              "version": "v0",
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              "text": "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\nVimaleswaran KS, Radha V, Ghosh S, Majumder PP, Deepa R, Babu \nHN etal (2005) Peroxisome proliferator-activated receptor-gamma \nco-activator-1alpha (PGC-1alpha) gene polymorphisms and their \nrelationship to type 2 diabetes in Asian Indians. Diabetic Med 22:15161521",
              "title": "2018 - Association of PGC-1\u03b1 gene with type 2 diabetes in three unrelated endogamous groups of North-West India (Punjab) a case-control and meta-analysis study.pdf",
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              "text": "Dali-Youcef N, et al. The Pro12Ala PPARgamma2 variant deter-\nmines metabolism at the gene-environment interface. Cell Metab.\n2009;9:88 98.\n53. Agostini M, Schoenmakers E, Mitchell C, Szatmari I, Savage D,\nSmith A, et al. Non-DNA binding, dominant-negative, human\nPPARgamma mutations cause lipodystrophic insulin resistance.\nCell Metab. 2006;4:303 11.\n54. Agostini M, Gurnell M, Savage DB, Wood EM, Smith AG,\nRajanayagam O, et al. Tyrosine agonists reverse the molecular",
              "title": "2021 - PPAR\u03b3 and Diabetes Beyond the Genome and Towards Personalized Medicine.pdf",
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              "text": "associated with a marked increase in T2D risk in the general\npopulation, schematized in Fig. 1. The latter systematically\ntested all the possible PPAR protein variants by using a\nlarge-scale pooled functional assay based on a human macro-\nphage cell line. Using these in vitro data to train a classifier by\nsupervised machine learning, they identified six pathogenic\nPPARG variants (R194Q, A417V, R212W, P387S, M203I,\nand T356R) in patients with partial lipodystrophy [ 109].",
              "title": "2021 - PPAR\u03b3 and Diabetes Beyond the Genome and Towards Personalized Medicine.pdf",
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              "text": "lipid metabolism, as well as insulin sensitivity and inflammatory pathways. These pleiotropic functions confer great relevance to\nPPAR in physiological regulation of whole-body metabolism, as well as in the etiology of metabolic disorders. Accordingly,\nPPARG gene mutations, nucleotide variations, and post-translational modifications have been associated with adipose tissue\ndisorders and the related risk of insulin resistance and type 2 diabetes (T2D). Moreover, PPAR alternative splicing isoforms",
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              "text": "the PPARgamma locus. Diabetes 2001;50:686 689\n12. Kahara T, Takamura T, Hayakawa T, et al.\nPPARgamma gene polymorphism is as-sociated with exercise-mediated changes\nof insulin resistance in healthy men. Me-\ntabolism 2003;52:209 212\n13. Franks PW, Luan J, Browne PO, et al.\nDoes peroxisome proliferator-activated\nreceptor gamma genotype (Pro12ala)\nmodify the association of physical activityand dietary fat with fasting insulin level?\nMetabolism 2004;53:11 16\n14. Memisoglu A, Hu FB, Hankinson SE, et al.",
              "title": "2013 - Gene-Environment and Gene-Treatment.pdf",
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              "text": "30. Majithia, A. R. et al. Rare variants in PPARG  with decreased activity in \nadipocyte differentiation are associated with increased risk of type 2 diabetes. \nProc Natl Acad Sci USA 111, 1312713132 (2014).\n 31. Majithia, A. R. et al. Prospective functional classification of all  \npossible missense variants in PPARG . Nat. Genet.  48, 15701575 (2016).\n 32. Claussnitzer, M. et al. Leveraging cross-species transcription factor binding",
              "title": "2018 - Refining the accuracy of validated target identification through coding variant.pdf",
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              "content": "CRISPR/Cas9 technology can be used to study or treat genetic forms of diabetes in several ways:\n\n1. **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].\n\n2. **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].\n\n3. **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].\n\n4. **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].\n\n5. **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].\n\nOverall, CRISPR/Cas9 technology provides a powerful platform for both studying the genetic underpinnings of diabetes and developing potential gene therapies to treat the disease.",
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              "text": "A variety of cellular and animal models have been developed and applied\nover the past few years to experimentally manipulate cis-regulatory\nelements 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\nwill. Unsurprisingly, CRISPR (epi)genome editing tools can and have\nbeen used to target putative T2D target genes [54] orcis-REs[55] in beta",
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              "text": "to how CRISPR/Cas9 technology may nd clinical application in patients with diabetes.\nKeywords: genome editing, beta cell, genome-wide association studies, maturity onset of diabetes of the young,\nstem cells, mouse models\nINTRODUCTION\nType 2 diabetes (T2D) affects an estimated 425 million people worldwide, a number predicted to rise\nto 629 million by 2045 ( 1). The disease usually involves insulin resistance but is ultimately the result",
              "title": "2020 - Functional Genomics in Pancreatic \u03b2 Cells Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research.pdf",
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              "text": "hPSCs [48,49] for correcting the COL7A1 [50] anda1-antitrypsin\ngenes [51]. Given the superior cutting ef ciency, CRISPR/Cas9 is\nincreasingly becoming the favored choice for genome editing inhPSCs [16,52] .\n3.2. Employing hPSCs and genome editing tools to study diabetes\nand metabolic syndromes\nIn general, the strategy to carry out in vitro disease modeling of dia-",
              "title": "2016 - Dissecting diabetes metabolic disease.pdf",
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              "text": "Due to its simplicity and adaptability, CRISPR has rapidly\nbecome the most popular genome editing tool available for the\nmammalian genome ( 50,63). Because NHEJ DNA repair often\nintroduces 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\ndiabetes eld, CRISPR has also been adopted to study several\ngenes in bcell lines and in human ES-derived bcells ( 21,151,",
              "title": "2020 - Functional Genomics in Pancreatic \u03b2 Cells Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research.pdf",
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              "text": "samples ( 236).\nCRISPR technology has been used recently to correct point\nmutations in patient-derived iPSCs to target diabetes-relatedgene defects. To date, the most ef cient method used in iPSC\nis CRISPR/Cas9-based homology-directed repair (HDR). Here, a\nCas9-mediated cut is generated adjacent to the site of interest. A\nhomologous donor template with the intended nucleotidechange containing silent mutations in the gRNA sequence(167) can then be recombined by HDR. This approach has",
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              "text": "in response to various stimuli including glucose aftertransplantation in an immunocompromised mouse model\n(230,231). However, the use of iPSC is controversial and there\nare some concerns over genetic and epigenetic variations iniPSCs which might affect cell function after differentiation ( 275).\nManipulation of hESC/iPSC cells via CRISPR-Cas9\ntechnology provides a platform for the correction of genomic\nmutations not only in diabetes but in other disease elds as well",
              "title": "2020 - Functional Genomics in Pancreatic \u03b2 Cells Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research.pdf",
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              "text": "RNP and single strand edDNA (ssDNA) donor which carriesdesired changes such as insertion of loxP site ( 255,259265).\nUsing CRISPR-Cas9, leptin and leptin receptor knockout mice\nhave been established as tools in diabetes and obesity research ( 160,255,256). Knock-in mouse models have also been established via\nHDR to achieve cell-speci c deletion of the gene ( 266).\nGenome Editing: Clinical Application\nin Diabetes\nAn important goal in genetic research is to identify the genetic",
              "title": "2020 - Functional Genomics in Pancreatic \u03b2 Cells Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research.pdf",
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              "text": "CRISPR-Cas9 epigenome editing enables high-throughput screening for functionalregulatory elements in the human genome. Nature Biotechnology 35(6):561 e568.\n[58] Hodson, D.J., Mitchell, R.K., Marselli, L., Pullen, T.J., Gimeno Brias, S.,\nSemplici, F., et al., 2014. ADCY5 couples glucose to insulin secretion in humanislets. Diabetes 63(9):3009 e3021 .\n[59] Zhou, Y., Park, S.-Y., Su, J., Bailey, K., Ottosson-Laakso, E., Shcherbina, L.,",
              "title": "2019 - (Epi)genomic heterogeneity of pancreatic islet function and failure in type 2 diabetes.pdf",
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              "text": "free IPSCs from Human Pancreatic Cells Using the CRISPR-Cas9 System.\nJ Vis Exp JoVE (2017). doi: 10.3791/56260\n277. Millette K, Georgia S. Gene Editing and Human Pluripotent Stem Cells:\nTools for Advancing Diabetes Disease Modeling and Beta-Cell Development.\nCurr Diabetes Rep (2017) 17:116. doi: 10.1007/s11892-017-0947-3Hu et al. Genome Editing of Pancreatic Beta Cells\nFrontiers in Endocrinology | www.frontiersin.org October 2020 | Volume 11 | Article 576632 19",
              "title": "2020 - Functional Genomics in Pancreatic \u03b2 Cells Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research.pdf",
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              "text": "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-\neffects remain to be seen.FUTURE PROSPECTIVES\nRecent 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",
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              "content": "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.",
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              "text": "Effectors \nGlucose transporters. A number of polymorphisms have been identified in \nthe GLUT4 gene. None of them have been linked to or found to be \nassociated with type 2 diabetes in a variety of populations. 5960 Interestingly, \nan association was found between a polymorphism in the human GLUT! \ngene and type 2 diabetes60 that was significant for obese women. Regulation \nof GLUT4 protein expression in diabetes occurs in a strongly tissue-specific",
              "title": "2004 - Diabetes Genes a.pdf",
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              "text": "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\n141. Poulsen P, Kyvik KO, Vaag A, Beck-\nNielsen H. 1999. Heritability of type II(non-insulin-dependent) diabetes melli-tus and abnormal glucose toleranceapopulation-basedtwinstudy. Diabetolo-\ngia42:13945\n142. Pugliese A, Zeller M, Fernandez AJ,",
              "title": "2003 - The Inherited Basis of Diabetes Mellitus.pdf",
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              "text": "A mutation in the Glut2 glucose transporter gene of a diabetic patientabolishes transport activity. J Biol Chem 269: 1776517767, 1994.\n36.Patel P, Bell GI, Cook JT, Turner RC, Wainscoat JS. Multiple\nrestriction fragment length polymorphisms at the GLUT2 locus: GLUT2haplotypes for genetic analysis of type 2 (non-insulin-dependent) diabetesmellitus. Diabetologia 34: 817821, 1991.\n37.Pereira MA, FitzerGerald SJ, Gregg EW, Joswiak ML, Ryan WJ,\nSuminski RR, Utter AC, Zmuda JM. A collection of Physical Activity",
              "title": "2007 - Physical activity modifies the effect of SNPs in the SLC2A2 (GLUT2).pdf",
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              "text": "NootherrecentassociationsofpolymorphismswithT2Dhavebeenreplicated\nto date (Table 5). However, a recent meta-analysis (106) identied some earlyreproducibilityofanassociationbetweenvariationin GLUT1andT2D,originally\nreportedin1988(104).Itislikelythatthisassociationhasnotbeenpursuedfurtherfor several reasons, but one possibility is a study that reported the rejection oflinkageto GLUT1athighlevelsofsignicance(46).However,linkagehaslimited",
              "title": "2003 - The Inherited Basis of Diabetes Mellitus.pdf",
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              "text": "mechanism by which type 2 diabetes is influenced remains to\nbe identified.\nThere have been several attempts to clarify the role of the\npolymorphism in SLC30A8 in the development of type 2\ndiabetes and the focus has been set on insulin secretion dueto the importance of ZnT-8 for insulin storage in the granulaof pancreatic cells.\nThe results are controversial, but there appears to be an\nassociation between the risk variant of rs13266634 and\nreduced insulin secretion. Interestingly, decreased insulin",
              "title": "2009 - Zinc and Diabetes - clinical links and molecular mechanisms.pdf",
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              "text": "glucose tolerance, suggesting a r ole for this polymorphism in the\nonset of GDM as well as type 2 diabetes mellitus ( 17). The switch on\nIRS-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\npresence of this polymorphism and the risk of GDM ( 18).\nIntriguing results were generated by a study on the genetic",
              "title": "2020 - Genetics and Epigenetics New Insight on Gestational Diabetes Mellitus.pdf",
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              "text": "tients the EUGENE2 study. Diabetologia 2008;51:816 820\n32. Kirchhoff K, Machicao F, Haupt A, et al. Polymorphisms in the TCF7L2,\nCDKAL1 and SLC30A8 genes are associated with impaired proinsulinconversion. Diabetologia 2008;51:597 601\n33. Nicolson TJ, Bellomo EA, Wijesekara N, et al. Insulin storage and glucose\nhomeostasis in mice null for the granule zinc transporter ZnT8 and studies\nof the type 2 diabetes-associated variants. Diabetes 2009;58:2070 2083",
              "title": "2012 - Reduced Insulin Exocytosis in Human Pancreatic b-Cells.pdf",
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              "text": "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\nthis 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",
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              "text": "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.\nResults: Nine polymorphisms were identified, and four common poly-\nmorphisms [g. /H110021500C /H11022G, g./H110021062G /H11022C, g./H11002994C/H11022T, g./H11001408C/H11022A\n(Leu72Met)] were genotyped in a larger study. The genotype distri-butions of these four common polymorphisms in type 2 diabetes pa-",
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              "text": "in turn, result in a defective or poorly expressed glucagonprotein and lead to decreased insulin secretion and conse-\nquently hyperglycaemia [ 48].\nThe current study identified, for the first time, several type\n2 diabetes-associated risk alleles associated with a higher riskof GDM, namely rs7957197 ( HNF1A ), rs10814916 ( GLIS3 ),\nrs3802177 ( SLC30A8 ) and rs7041847 ( GLIS3 ). These SNPs",
              "title": "2018 - Genetic variants of gestational diabetes mellitus a study of 112 SNPs among 8722 women in two independent populations.pdf",
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              "content": "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].",
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              "text": "MicroRNAs (miRNA) ar e single -stranded, small RNA molecules that act at the post -\ntranscriptional standard to regulate their target or source genes. Many biological processes \nare regulated by this Micro RNA. Since its discovery about two decades ago. It is correlated \nwith a com prehensive set of diseases and described by numerous miRNAs, including T2DM \nand cardiovascular diseases. Specifically, with respect to T2DM, micro RNA plays a",
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              "text": "they can act as oncogenes or tumor suppressors  (8, 29, 72). miRs are associated with the 341 \nregulation of genes relevant to insulin secre tion, cholesterol biosynthesis, fat metabolism and 342 \nadipogenesis, crucial pathways in the pathogene sis of diabetes (53, 114, 115). miRs have also 343 \nbeen implicated in TGF-  signaling related to th e pathogenesis of diabetic nephropathy with key 344 \nmiRs such as miR-192, miR-216a, miR-217 and miR-377 being up-regula ted in glomerular 345",
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              "text": "Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM et al\n(2005) Microarray analysis shows that some microRNAs down-regulate large numbers of target mRNAs. Nature 433:769773\nLovis P, Roggli E, Laybutt DR, Gattesco S, Yang JY et al (2008)\nAlterations in microRNA expression contribute to fatty acid-induced pancreatic beta-cell dysfunction. Diabetes 57:27282736\nNadler ST, Stoehr JP, Schueler KL, Tanimoto G, Yandell BS et al",
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              "text": "Abstract\nRecent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the\nregulation of transcriptional activity within the pancreatic beta-cell. MicroRNAs (miRNAs) represent an important\ncomponent of regulatory control, and have proven roles in the development of human disease and control of glucose",
              "title": "2013 - The miRNA Profile of Human Pancreatic Islets and BetaCells and Relationship to Type 2 Diabetes Pathogenesis.pdf",
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              "text": "evidence demonstrates that miRNAs and lncRNAs can alsoregulate the expression of genes and modulate the actions of\ngrowth factors and inflammatory factors related to diabetic\ncomplications [ 8]. These reports have been described in sev-\neral reviews [ 8,8791] and are only briefly discussed here.\nNumerous recent reports have demonstrated abnormal ex-\npression of various miRNAs in renal, vascular and retinal cellsunder diabetic conditions, and in vivo models of related",
              "title": "2015 - Epigenetic mechanisms in diabetic complications and metabolic memory.pdf",
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              "text": "In addition, miRNAs have been shown to be involved in T2DM. For example, miRNAs play major roles \nin pancreatic islet development,  cell dysfunction, insulin synthesis and secretion and insulin  \nresistance [148] . Studies based on miRNA microarray analysis have identified many different miRNAs \ninvolved in the pathology of both T1DM and T2DM; these miRNAs include mi R-375, miR -29, miR -9, \nmiR-124a, miR -195, miR -222, miR -126, miR -133a, miR -296, miR -96, miR -34a, miR -146b, miR -657,",
              "title": "2014 - Nutrigenetics and Nutrigenomics Insights into Diabetes Etiopathogenesis.pdf",
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              "text": "26. He Y , Ding Y , Liang B, Lin J, Kim TK, Yu H, Hang H, \nWang K. A Systematic Study of Dysregulated MicroRNA in \nType 2 Diabetes Mellitus. Int J Mol Sci. 2017:18.\n27. Dias S, Hemmings S, Muller C, Louw J, Pheiffer C. MicroRNA Expression Varies according to Glucose \nTolerance, Measurement Platform, and Biological Source. \nBiomed Res Int. 2017;2017:1080157.\n28. El Ouaamari A, Baroukh N, Martens GA, Lebrun P, Pipeleers D, van Obberghen E. miR-375 targets \n3'-phosphoinositide-dependent protein kinase-1 and",
              "title": "2018 - MicroRNA profiling and their pathways in South African.pdf",
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              "text": "nucleotide RNA molecules that potentially regulate the\nexpression of thousands of genes. To understand therelationship between miRNA regulation and obesity-\ninduced diabetes, we quantitatively proled approximately220 miRNAs in pancreatic islets, adipose tissue, and liver\nfrom diabetes-resistant (B6) and diabetes-susceptible\n(BTBR) mice. More than half of the miRNAs proled wereexpressed in all three tissues, with many miRNAs in each\ntissue showing signicant changes in response to genetic",
              "title": "2009 - Obesity and genetics regulate microRNAs in islets, liver, and adipose of diabetic mice.pdf",
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              "text": "11. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and\nfunction. Cell. 2004;116(2):281 97.\n12. Pirola L, Balcerczyk A, Tothill RW, et al. Genome-wide analysis\ndistinguishes hyperglycemia regulated epigenetic signatures of pri-\nmary vascular cells. Genome Res. 2011;21(10):1601 15.\n13.Cooper ME, El-Osta A. Epigenetics: mechanisms and implications\nfor diabetic complications. Circ Res. 2010;107(12):1403 13.Thispaper also provides a review of evidence pertaining to the role",
              "title": "2016  - Epigenetic Mechanisms in Diabetic Kidney Disease.pdf",
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              "text": "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 \n129. La Sala L, Cattaneo M, De Nigris V , Pujadas G, Testa R, Bonfigli AR,  \net al. Oscillating glucose induces microRNA-185 and impairs an efficient antioxidant response in human endothelial cells. Cardiovasc Diabetol  (2016) \n15:71. doi:10.1186/s12933-016-0390-9",
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              "content": "Studying the genetic basis of MODY (Maturity Onset Diabetes of the Young) has provided several important insights:\n\n1. **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].\n\n2. **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].\n\n3. **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].\n\n4. **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].\n\n5. **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].\n\nThese 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.",
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              "text": "studying the highly familial MODY form of young - onset diabetes or other rare forms of monogenic diabetes.  \n  Table 12.2    The different subtypes of maturity - onset diabetes of the young ( MODY ). \n   MODY \ntype     Gene \nlocus     Gene name     Year of \ndiscovery     Distribution     Onset of \ndiabetes     Primary \ndefect     Severity of \ndiabetes     Complications     OMIM  \n  MODY1    20q     HNF4A   ( TCF14  )    1996    Rare (2  3%)    Adolescence/",
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              "text": "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",
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              "text": "[2] . Mutations in 13 genes are known \nto cause MODY; the most prevalent are  HNF1A  ,  GCK   \nand  HNF4A   [3, 4]  . The MODY subtypes differ in age of \nonset of diabetes, the pattern of hyperglycemia, response to treatment, and associated extrapancreatic manifesta-tions  \n[5] . As compared to type 2 diabetes, the clinical  Key Words \n Best practice  Genetic testing  Healthcare providers  Interview study  Maturity onset diabetes of the young \n Abstract",
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              "text": "causal for MODY , although genetic or functional evidence of\nobvious pathogenicity is not fully compelling (Table 1).\nDespite these important advances in understanding the mo-\nlecular pathogenesis of MODY , the genetic determinants in\nmany patients with young-onset diabetes resembling a\nMODY-like phenotype remain unknown, suggesting addi-\ntional locus heterogeneity and new pathogenic mechanismsto be yet discovered. This has particularly been observed in",
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              "text": "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\nbasis. 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\nContinued over page",
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              "text": "Genetic Testing for MODY  Public Health Genomics 2015;18:5259 \nDOI: 10.1159/00036796359  1 Singh R, Pearson ER: The importance of mak-\ning a genetic diagnosis of diabetes. Can J Dia-betes 2006; \n  30:   183190. \n  2 Ledermann HM: Is maturity onset diabetes at \nyoung age (MODY) more common in Europe than previously assumed? Lancet 1995; \n  345:  \n 648.",
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              "text": "Genetic Testing for MODY  Public Health Genomics 2015;18:5259 \nDOI: 10.1159/00036796353symptoms present often at a relatively young age in pa-\ntients 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.\n  Many patients with MODY are currently undiagnosed \nor misdiagnosed with type 1 or 2 diabetes mellitus  [4] . In",
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              "text": "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)\n(Froguel et al., 1992 ). Mutations in GCK (encoding glucokinase)\nwere shown to cause a relatively benign form of MODY. Inciden-tally, it was the rst time that the direct causative effect of rela-\ntive insulin deciency was demonstrated in T2D, when insulin",
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              "text": "gene studies were under powered. However, studies of \nmonogenic forms of diabetes, specifically maturity onset \ndiabetes of the young 2 (MODY2), provided some of the \nfirst insights into the contribution of genetic variation to \nhyperglycemia observed during pregnancy and fetal \noutcomes. MODY2 is an autosomal dominant form of \nMODY due to mutations in glucokinase ( GCK ) [2527]. Table 1. Characteristics and treatment modalities of different forms of diabetes mellitus\nCharacteristics Treatment modalities",
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              "text": "is variable, underlining that this disorder is genetically heterogeneous. \nTable 1. Definition of MODY \n Impaired glucose tolerance \n Age of onset <25 years \n Autosomal-dominant inheritance \nUsing genetic linkage and candidate gene approaches, mutations in \ngenes on chromosomes 2, 7, 12, 13, 19, and 20 have been linked to MODY \nand collectively may represent up to 3% of all patients with type 2 diabetes \n(Table 2). The gene on chromosome 7 (MODY2) encodes the glycolytic",
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              "content": "The genes most commonly associated with an increased risk of developing diabetes, particularly type 2 diabetes, include:\n\n1. **CDKAL1, CDKN2A, CDKN2B** - These genes are linked to reduced insulin secretion via reduced beta-cell mass [1].\n2. **MTNR1B, TCF7L2, KCNJ11** - These genes are associated with beta-cell dysfunction [1].\n3. **FTO** - This gene is related to increased insulin resistance associated with obesity [1].\n4. **IRS1, PPARG** - These genes are related to increased insulin resistance unrelated to obesity [1].\n5. **IGF2BP2, HHEX, SLC30A8, WFS1** - These genes have been shown to increase susceptibility to type 2 diabetes in reproducible studies [3].\n6. **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].\n7. **KCNQ1** - This gene is associated with susceptibility to type 2 diabetes in East Asian and European populations [6].\n\nThese genes have been identified through various genome-wide association studies (GWAS) and other genetic research efforts.",
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              "text": "of Diabetes \n Results of several genome-wide association stud-\nies (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) [ \n11 ]. While most of the early studies",
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              "text": "gene are associated with NIDDM in Caucasians. Diabetes 1996 , 45, 825-831. \n46.  Tarasov, A.I.; Nicolson, T.J. ; Riveline, J.P.; Taneja, T.K. ; Baldwin, S.A.; Baldwin, J.M.; \nCharpentier, G.; Gautier, J.F. ; Froguel, P.; Vaxillaire, M.; et al.  A rare mutation in ABCC8/SUR1 \nleading to altered ATP-sensitive K+ channel activ ity and beta-cell glucose sensing is associated \nwith type 2 diabetes in adults. Diabetes 2008 , 57, 1595-1604.",
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              "text": "ly associated with type 2 diabetes: TCF7L2, KCNJ11,  \nand PPARG .\n5-7 However, in 2007, a number of novel \ngenetic variants ( CDKAL1, IGF2BP2,  the locus on \nchromosome 9 close to CDKN2A/CDKN2B, FTO, \nHHEX, SLC30A8,  and WFS1)8-14 were shown to in -\ncrease susceptibility to type 2 diabetes in repro -\nducible studies. Furthermore, a recent meta-analy -\nsis identified six novel variants ( JAZF1, CDC123/\nCAMK1D, TSPAN8/LGR5, THADA, ADAMTS9, and NOTCH2 ) that are associated with type 2 dia -\nbetes.\n15",
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              "text": "CDKAL1 in  uences insulin response and risk of type 2 diabetes. Nat Genet 2007; 39: 77075.\n69 Wu Y , Li H, Loos RJ, et al. Common variants in CDKAL1, CDKN2A/\nB, 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.\n70 Sandhu MS, Weedon MN, Fawcett KA, et al. Common variants in \nWFS1 confer risk of type 2 diabetes. Nat Genet 2007; 39: 95153.",
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              "text": "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.\n12 Also, several",
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              "text": "associated with susceptibility to type 2 diabetes mellitus. Nat Genet 2008; 40: 109297 .\n74 Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are \nassociated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genet 2008; 40: 1098102.\n75 Lyssenko V, Lupi R, Marchetti P, et al. Mechanisms by which \ncommon variants in the TCF7L2 gene increase risk of type 2 diabetes. J Clin Invest 2007; 117: 215563. \n76 Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA",
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              "text": "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].\nObesity is the greatest risk factor for type 2 diabetes\nmellitus, as it is known to induce insulin resistance via variousmechanisms ( TNF \n \n release, free fatty acids, etc.). Both",
              "title": "2003 - Genome-wide screen in obese pedigrees with type 2 diabetes.pdf",
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              "text": "50 most cases of type 2 diabetes are thought to be \ndue 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)\n51 and the ATP-sensitive potassium channel \nKir62 (KCNJ11) were reproducibly associated with type 2 diabetes.\n52 In Asian populations, the protective e  ect of \nthe PPARG*A12Ala allele on insulin resistance and risk of type 2 diabetes was not consistently seen.\n53",
              "title": "2010 - Diabetes in Asia.pdf",
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              "text": "49. Cornelis MC, Qi L, Zhang C, et al. Joint e ects of common genetic\nvariants on the risk for type 2 diabetes in U.S. men and women ofEuropean ancestry. Ann Intern Med . 2009;150:541 550(in eng).\n50. Hu C, Zhang R, Wang C, et al. PPARG, KCNJ11, CDKAL1,\nCDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8are associated with type 2 diabetes in a Chinese population. PLoS\nOne. 2009;4:e7643 (in eng).\n51. Lin X, Song K, Lim N, et al. Risk prediction of prevalent diabetes in",
              "title": "2018 - Quantitative Relationship Between Cumulative Risk Alleles Based.pdf",
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              "text": "46. Sladek R, Rocheleau G, Rung J et al (2007) A genome-wide asso-\nciation study identifies novel risk loci for type 2 diabetes. Nature\n445:881 885\n47. Lauenborg J, Grarup N, Damm P et al (2009) Common type 2\ndiabetes risk gene variants associate with gestational diabetes. J\nClin Endocrinol Metab 94:145 150\n48. Florez JC, Jablonski KA, Bayley N et al (2006) TCF7L2 polymor-\nphisms and progression to diabetes in the Diabetes Prevention\nProgram. N Engl J Med 355:241 250",
              "title": "2018 - Genetic variants of gestational diabetes mellitus a study of 112 SNPs among 8722 women in two independent populations.pdf",
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              "content": "Genetic testing can help predict a person's risk for diabetes in several ways:\n\n1. **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].\n\n2. **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].\n\n3. **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.\n\n4. **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].\n\n5. **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].\n\n6. **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].\n\nOverall, genetic testing provides valuable insights into an individual's risk for diabetes, enabling more targeted prevention and management strategies.",
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              "text": "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\nprevent or, at least, to significantly retard the",
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              "text": "(35).\nIf genetic tests are not helpful in the\nprediction 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-\ncause many children and young adultswith type 1 diabetes are also obese (37).Misclassi cation poses signi cant risks;\nan incorrect diagnosis of type 2 diabetes",
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              "text": "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.\nGenomic Analyses for Diabetes Risk",
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              "text": "genes improves prediction of type 1 diabetes[published correction appears in Diabetologia. 2015;\n58(1):206]. Diabetologia . 2014; 57(12):2521 2529.\n57. Oram RA, Patel K, Hill A, Shields B, McDonald TJ,\nJones A, Hattersley AT, Weedon MN. A type 1\ndiabetes genetic risk score can aid discrimination\nbetween type 1 and type 2 diabetes in young adults.Diabetes Care . 2016; 39(3):337 344.\n58. Redondo MJ, Oram RA, Steck AK. Genetic risk",
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              "text": "10.2337/db13-1663.\n 20. Vassy JL, et al. A genotype risk score predicts type 2 diabetes from young \nadulthood: the CARDIA study. Diabetologia. 2012;55:26042612. doi: \n10.1007/s00125-012-2637-7.\n 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: \n10.1016/j.beem.2011.09.002.\n 22. Khera AV, et al. Genome-wide polygenic score to identify a monogenic \nrisk-equivalent for coronary disease. bioRxiv. 2017. doi: 10.1101/218388.",
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              "text": "Genotype Score for Prediction of Type 2 Diabetes\nn engl j med 359;21 www.nejm.org november 20, 2008 2209Type 2 diabetes mellitus is a m ajor \nhealth problem worldwide.1 Fortunately, \nits development can be prevented in many \ninstances,2 and persons at risk can be readily \nidentified with the measurement of a few com -\nmon risk factors.3-5 Type 2 diabetes is heritable, \nwith a risk for people with familial diabetes as \ncompared with those without familial diabetes that is increased by a factor of 2 to 6.",
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              "text": "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 -",
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              "text": "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-\ned with diabetes in large genetics",
              "title": "2010 - Cardiovascular Disease Risk Factors, Type 2 Diabetes Mellitus, and the Framingham Heart Study.pdf",
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              "text": "Comprehension of Genomic Risk for \nDiabetes  Public Health Genomics 2014;17:95104 \nDOI: 10.1159/000358413101their results in-person from a genetic counselor were able \nto 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",
              "title": "2014 -  Impact of Delivery Models on Understanding Genomic Risk for Type 2 Diabetes.pdf",
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              "content": "Family genetics play a significant role in the likelihood of developing diabetes. Several studies and observations highlight this connection:\n\n1. Genetic factors are important in determining an individual's risk of developing diabetes [1].\n2. 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].\n3. 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].\n4. 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].\n5. 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].\n\nOverall, these findings underscore the strong genetic component in the susceptibility to diabetes, particularly type 2 diabetes.",
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              "text": "Genetic factors appear to play a role in determining an individuals risk of developing diabetes. It is hoped",
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              "text": "Metabolic Syndrome and Family History \nof Diabetes Public Health Genomics 2010;13:353359 357able difference in the odds between these 2 risk levels. \nThis 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).\n  C o n c l u s i o n",
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              "text": "For type 2 diabetes, there have been a few \nstudies 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 [ \n90 ]. A family history of diabetes in any   rst- \ndegree relative (parent, sibling) or in a grandpar-ent is associated with a two- to fourfold increased risk of diabetes [ \n10 ,  91 ]. A family history of dia-",
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              "text": "evidenced by a very high positive rate of family history of diabetes, and \ndrastically different prevalence in various ethnic groups. Therefore, there is \nno doubt that type 2 diabetes is a disease with a strong genetic influence. \nHowever, the prediction of the relative contribution of genetic influence and \nnumber of genes involved in the pathogenesis of the disease has changed in \nthe past few years. Initially, enthusiastic searches of diabetes genes were",
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              "text": "can decrease risk of diabetes.22 Diet may also play a role. High calorie diets, \nincluding those high in fat, and especially saturated fat, have been implicated \nin the development of type 2 diabetes?4-26 Family history is a very strong risk \nfactor for type 2 diabetes. A strong genetic component is suggested by the \n58-75% concordance rates for type 2 diabetes observed in identical twins \n(Table 3).3 \nTable 3. Estimated risk of developing type 2 diabetes by family history \nOne parent with type 2 diabetes",
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              "text": "The fact that type 2 diabetes is a genetic disease is well\nknown to clinicians by how it occurs in families, and by\nthere being ethnic populations who are particularly high risk.\nThe genetic link was clearly shown more than two decades\nago by a famous study of identical twins in the U.K. that\nfound essentially a 100% concordance rate for this disease\nif one twin developed type 2 diabetes, then the other one\ninvariably developed it (9). However, this kind of study",
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              "text": "genetic factors play an important role in the susceptibility to T2D. The risk of the disease developing\nat some point of life is ~70% when both parents are diabetic and ~40% when one parent has T2D [ 4].\nFurthermore, latest data show that more than 400 genetic risk variants at 250 loci for T2D have been\nGenes 2018 ,9, 374; doi:10.3390/genes9080374 www.mdpi.com/journal/genes",
              "title": "2018 - High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes.pdf",
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              "text": "36 Herder C, Roden M. Genetics of type 2 diabetes: pathophysiologic \nand clinical relevance. Eur J Clin Invest 2011; 41: 67992.\n37 Dabelea D, Hanson RL, Lindsay RS, et al. Intrauterine exposure \nto diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes 2000; 49: 220811.\n38 Voight BF, Scott LJ, Steinthorsdottir V, et al. Twelve type 2 diabetes \nsusceptibility loci identi  ed through large-scale association analysis. Nat Genet 2010; 42: 57989.",
              "title": "2011 - Type 2 diabetes across generations from pathophysiology to prevention and management.pdf",
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              "text": "long follow-up. Type 2 diabetes and impaired glucose tolerance (IGT) \ncluster in families. Thus, most patients have a positive family history, and \nthe lifetime risk for developing type 2 diabetes is increased up to 40% (more \nthan five times the background rate) by having a first degree relative with the \ndisease. If both parents have type 2 diabetes the risk to the offspring may be \nas high as 70%. Available evidence supports a polygenic mode of \ninheritance with a considerable environmental input. 1",
              "title": "2004 - Diabetes Genes a.pdf",
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              "text": "Genetic factors\nType 2 diabetes has a strong genetic component and most Asian patients have a   rst-degree relative with diabetes.\n48,49 Much progress has been made in our \nunderstanding 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, \nsuch as those seen in maturity-onset diabetes of young people,",
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              "content": "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].",
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              "text": "of a given genetic variant is modified by the environ -\nmental milieu (and vice versa). Evidence that lifestyle factors modify the genetic effects on T2DM risk has been \ngenerated from both observational studies and clinical \ntrials82. However, genetic background might also affect \nthe individuals response to lifestyle interventions83. In \naddition, replication data are sparse, and comprehensive, \nlarge-scale studies have failed to provide a compelling",
              "title": "2018 - Global aetiology and epidemiology of type 2 diabetes mellitus and its complications.pdf",
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              "text": "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).\nDiet recommendations optimized to\nthe individual have been shown to re-duce postprandial glycemic excursionsto a greater extent than standard\napproaches in healthy individuals (84).Meal compositions that induce the most\nfavorable glycemic pro les have been",
              "title": "2020 - Precision Medicine in Diabetes.pdf",
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              "text": "diabetes regardless of the underlying\ngenetic 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\n(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\nrecognize that knowledge of increased",
              "title": "2020 - Precision Medicine in Diabetes.pdf",
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              "text": "Genetic factors appear to play a role in determining an individuals risk of developing diabetes. It is hoped",
              "title": "2008 - Glossary of Genetics Genomics Terms.pdf",
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              "text": "suggested to attenuate its negative e  ect on metabolic pro  le, \nbody weight, and diabetes risk (   Franks et al., 2007   ;    Kilpelainen et al., 2008   ;    Lindi et al., 2002   ;    Ruchat et al., 2010   ) (     \n       Table 1   ). \nThe notion that lifestyle modi  cation can eliminate the increased \nrisk for development of T2DM in subjects with genetic suscepti-bility is also supported by  ndings of    Barwell et al. (2008)    who",
              "title": "2011 - Lifestyle and Genetics in Obesity and type 2 Diabetes.pdf",
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              "text": "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",
              "title": "2010 - Interactions of Dietary Whole-Grain Intake.pdf",
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              "text": "who is lean, genetic risk factors are more\nlikely to be present than in someone who\nis obese and develops the disease or that\nweight loss enhances the genetic risk ofdiabetes.\nGenetic analyses performed in clinical\ntrials involving intensive lifestyle modi -\ncation provide an important adjunct to\nthe epidemiological literature on gene-\nlifestyle interactions in type 2 diabetes.On one hand, a major advantage of ran-\ndomized controlled trials is that interac-",
              "title": "2013 - Gene-Environment and Gene-Treatment.pdf",
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              "text": "Lifestyle behaviors and genetic loci have clear and distinguishable effects on \nT2D 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.",
              "title": "2011 - Interaction Between Exercise and Genetics.pdf",
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              "text": "this occurs. Findings to date, however, indicate\nthat behavioral changes can substantially\nmitigate diabetogenic and obesogenic effects\nof individual or multiple risk alleles, which\nhas much broader clinical and public health\nimplications.We have seen considerable progress in our\nunderstanding of the role that both environ-\nment and genetics play in the development of\nT2D. Recent work suggests that the adverse\neffect of some established T2D-associated\nloci may be greatly attenuated by appropriate",
              "title": "2012 - Gene-Environment Interactions in the Development of Type 2 Diabetes.pdf",
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              "text": "Susceptibility to obesity and diabetes is deter-\nmined by both genetic and lifestyle factors.Suggestive evidence of genelifestyle interac-\ntion (Box 33.3) in the development of common\ndiseases such as obesity and type 2 diabetes wasrst provided by descriptive epidemiological\nstudies such as migration studies that compare\nthe disease risk between genetically related pop-ulations who live different lifestyles. A classicalexample is the comparison of the risk of obesity",
              "title": "2010 - Candidate Gene and Genome-Wide Association Studies in Behavioral Medicine.pdf",
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              "content": "Recent breakthroughs in understanding the genetic causes of diabetes include several key advancements:\n\n1. 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].\n\n2. 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].\n\n3. 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].\n\n4. 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].\n\nThese breakthroughs represent a significant leap forward in the genetic understanding of diabetes, driven by technological advancements and collaborative research efforts.",
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              "text": "understanding of the genetic basis of diabetes, and the\nadvances of recent months are arguably the most important\nmade since the role of the HLA region was recognised in type1 diabetes. The number of genetic regions causally implicated\nis now 11 each for type 1 and type 2 diabetes [ 19], and is set\nto rise further. The bewildering pace of new discovery standsin stark contrast to the slow progress that characterised the\nprevious two decades, with a total combined output of three",
              "title": "2007 - Genetic studies of diabetes following the advent of the genome-wide association study where do we go from here.pdf",
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              "text": "It has proven to be challenging to isolate the genes underlying the genetic\ncomponents conferring susceptibility to type 1 and type 2 diabetes. Unlike\nprevious approaches, genome-wide association studies have extensively\ndelivered 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\nrecent breakthroughs in the context of type 1 and type 2 diabetes, and",
              "title": "2011 - Genome-wide association studies (GWAS) impact.pdf",
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              "text": "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",
              "title": "2003 - The Inherited Basis of Diabetes Mellitus.pdf",
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              "text": "the elucidation of the wide spectrum of genes that \nplayed a role in the molecular mechanism of diabetes \ndevelopment[142-144]. However , despite the vast flow of \ngenetic information including the identification of many \ngene mutations and a large array of single nucleotide \npolymorphisms (SNPs) in many genes involved in the \nmetabolic pathways that affect blood glucose levels, \nthe exact genetic mechanism of diabetes remains \nelusive[145,146]. Evidently, a major complication is the",
              "title": "2015 - Diabetes mellitus The epidemic of the century.pdf",
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              "text": "confirmed genes for type 2 diabetes and six for type 1(Fig. 1). At last, it seems, our understanding of the genetic\nbasis of complex, multifactorial forms of diabetes is catching\nup with that of rarer, single-gene disorders.\nThis leap in knowledge is the result of major advances in\ntechnology plus an improved understanding of patterns of\nhuman genetic variation. Using single nucleotide polymor-\nphism (SNP) chips it is now possible to analyse up to a million",
              "title": "2007 - Genetic studies of diabetes following the advent of the genome-wide association study where do we go from here.pdf",
              "version": "v0",
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              "text": "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\ndiabetes and a limited number of speci c variants that\nidentify small subgroups of patients (MODY), genetics has\nnot been successful in further differentiating subclasses ofdiabetes.\nResearch Gaps\nAfter consideration of the known genetic associations\nwith diabetes risk, consensus developed that the eld is",
              "title": "2017 - Differentiation of Diabetes by Pathophysiology.pdf",
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              "text": "studies provide new insights into type 2diabetes aetiology. Nat Rev Genet 2007;8:657662\n11. Grant RW, Moore AF, Florez JC. Genetic\narchitecture of type 2 diabetes: recentprogress and clinical implications. Diabe-tes Care 2009;32:11071114\n12. Dupuis J, Langenberg C, Prokopenko I,",
              "title": "2010 - Interactions of Dietary Whole-Grain Intake.pdf",
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              "text": "early results have been excellent, yielding six \nnew replicating gene regions.\nHere I discuss the insights into type\n \n2 \ndiabetes genetics that have been provided by \nthese new findings. I consider where diabe -\ntes genetic studies might go from here, and \npresent a perspective that may be applicable \nto other common traits. I also briefly discuss \nthe wider implications that surround the \nidentification of a common gene that predis -\nposes to type",
              "title": "2007 - Genome\u2013wide association studies provide new insights into type 2 diabetes aetiology..pdf",
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              "text": "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",
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              "text": "24. Varshney, A. et al. Genetic regulatory signatures underlying islet gene expression and type 2 diabetes. Proc. Natl. Acad. Sci. USA 114,  \n23012306 (2017).\n 25. Thurner, M. et al. Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 diabetes susceptibility loci. eLife  7,  \ne31977 (2018).\n 26. Gaulton, K. J. et al. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nat. Genet.  47, \n14151425 (2015).",
              "title": "2018 - Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.pdf",
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              "content": "Genes influence how our bodies respond to sugar and insulin in several ways:\n\n1. **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].\n\n2. **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].\n\n3. **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].\n\n4. **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].\n\n5. **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].\n\nOverall, 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.",
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              "text": "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.\nCitation: 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\nONE 8(1): e53522. doi:10.1371/journal.pone.0053522",
              "title": "2013 - Systems Biology Approach Reveals Genome to Phenome Correlation in Type 2 Diabetes.pdf",
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              "text": "have been the subject of most follow-up studies to date.Specifically, we examined acute changes in expression of\nthese genes in response to feeding and fasting and\nlonger term changes in the expression of these genes inresponse to a diet high in fat and sugar, recognized as a\ncritical environmental risk factor for type 2 diabetes.\nIt has been hypothesized that most of the new genetic\nvariants affect -cell function, development or survival\nbut not insulin sensitivity [6]. Consistent with this,",
              "title": "2013 - Diabetes genes identified by genome-wide association studies are regulated in mice by nutritional factors in metabolically relevant tissues and by glucose concentrations in islets.pdf",
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              "text": "or survival. However, we also found evidence that most\nof the genes could have potential roles in other\nmetabolically-relevant tissues. Genes affecting insulinsensitivity may be expected to be expressed in peripheralinsulin sensitive tissues, such as liver and adipose tissue,\nand be responsive to metabolic status. Consumption of a\nhigh fat diet was associated with a tendency for the ex-\npression of several of these genes to be decreased. Simi-larly, many of the genes were regulated by feeding and",
              "title": "2013 - Diabetes genes identified by genome-wide association studies are regulated in mice by nutritional factors in metabolically relevant tissues and by glucose concentrations in islets.pdf",
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              "text": "secretion versus insulin sensitivity). We also sought todetermine whether any of these genes are regulated by\nconditions known to alter the expression of metabolic-\nally relevant genes. We examined the expression of thesegenes under fasting and non-fasting conditions (e.g. in\nresponse to insulin), which might be altered if they affect\nperipheral insulin sensitivity. Consumption of diets high\nin fats and sugars is associated with risk of developing\ntype 2 diabetes [34] and many genes that are critical for",
              "title": "2013 - Diabetes genes identified by genome-wide association studies are regulated in mice by nutritional factors in metabolically relevant tissues and by glucose concentrations in islets.pdf",
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              "text": "regulating sugar metabolism. Moreover, genes that were",
              "title": "2015 - Gestational Diabetes Alters Offspring DNA.pdf",
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              "text": "Figure 2: The role of type 2 diabetes genes in insulin secretion\nPancreatic -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. \nPositive calorie balance\nCycle A++\nCycle B Liver fat\n Insulin suppression of",
              "title": "2010 - Diabetes in Asia.pdf",
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              "text": "tive Glis3  expression, which in turn drive increased levels of beta cell \napoptosis and senescence. Genetic susceptibility could be replicated \nby elevated levels of dietary fat. Transcriptional analysis of human \nislets identified the same genetic networks at play. Together, these \nfindings demonstrate both the important role of genetic variation in \nbeta cells for diabetes susceptibility and a mechanism by which the \nWestern diet may contribute to the growing diabetes epidemic.\nRESULTS",
              "title": "2016 - Genetic predisposition for beta cell fragility underlies type 1 and type 2 diabetes.pdf",
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              "text": "associated with fasting proinsulin levels and provides new insights into the \npathophysiology of type 2 diabetes. Diabetes 60, 26242634 (2011).\n65. Saxena, R. etal. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat. Genet. 42, 142148 (2010).\n66. Tobacco and Genetics Consortium. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat. Genet. 42, 441447 (2010).",
              "title": "2021 - Interpreting type 1 diabetes risk.pdf",
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              "text": "38. Saxena R, Hivert M, Langenberg C, Tanaka T, Pankow JS, et al. (2010) Genetic\nvariation in GIPR influences the glucose and insulin responses to an oral glucose\nchallenge. Nat Genet 42: 142148. doi:10.1038/ng.521.\n39. Neale BM, Sham PC (2004) The future of association studies: gene-based\nanalysis and replication. Am J Hum Genet 75: 353362. doi:10.1086/423901.\n40. Saccone SF, Hinrichs AL, Saccone NL, Chase GA, Konvicka K, et al. (2007)",
              "title": "2010 - Common Inherited Variation in Mitochondrial Genes.pdf",
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              "text": "Nature Reviews | EndocrinologyFactors that aect insulin secretion and action\n Body weight\n Level of physical activity Smoking Heavy alcohol consumption Genetic predisposition Geneenvironment interaction\nPositive risk prole Negative risk prole\nNormoglycaemia/uni03B2-cell dysfunction and insulin resistanceAdipose tissue Skeletal muscle LiverInsulin-mediated \nglucose production /uni2191Insulin-mediated glucose uptake /uni2193 Insulin-mediated glucose uptake /uni2193\nHyperglycaemia\n Epigenetics",
              "title": "2018 - Global aetiology and epidemiology of type 2 diabetes mellitus and its complications.pdf",
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              "content": "Yes, there are specific genetic markers that can indicate a higher risk for Type 1 versus Type 2 diabetes.\n\nFor 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].\n\nFor 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].\n\nThese 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.",
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              "text": "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.\n12 Also, several",
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              "text": "Genetics of Type 2 Diabetes Chapter 12\n197400 multiallelic markers (short tandem repeats or microsatellites, \nwith a density of   1 marker/10   cmol) allows identi  cation of \npolymorphic markers showing strong allele identity by descent in diabetic family members (i.e. allele sharing in sibships is signi  -\ncantly higher than 50%). Once identi  ed, such susceptibility \ngenes for diabetes may then be positionally cloned in the intervals of linkage.",
              "title": "2010 - The Genetics of Type 2 Diabetes.pdf",
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              "text": "3. Katsarou, A. etal. Type 1 diabetes mellitus. Nat. Rev. Dis. Primers 3, 17016 (2017).\n4. 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. \n47, 381386 (2015).\n5. Barrett, J. C. etal. Genome-wide association study and meta-analysis find that over 40 \nloci affect risk of type 1 diabetes. Nat. Genet. 41, 703707 (2009).",
              "title": "2021 - Interpreting type 1 diabetes risk.pdf",
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              "text": "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes\nn engl j med 359;21 www.nejm.org november 20, 2008 2229(Fig. 3). An increase in the BMI and a concomi -\ntant decrease in insulin sensitivity during the \n8-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 -",
              "title": "2008 - Clinical Risk Factors, DNA Variants.pdf",
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              "text": "and genetic markers to improve the prediction of type 2 diabetes: theEPIC-Potsdam Study. Diabetes Care . 2009;32:2116 2119 (in eng).\n56. Cauchi S, Meyre D, Durand E, et al. Post genome-wide association\nstudies of novel genes associated with type 2 diabetes show gene-gene interaction and high predictive value. PLoS One . 2008;3(5):\ne2031 .\n57. Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA\nvariants, and the development of type 2 diabetes. N Engl J Med .\n2008;359:2220 2232 (in eng).",
              "title": "2018 - Quantitative Relationship Between Cumulative Risk Alleles Based.pdf",
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              "text": "etically expressed homeobox variant (rs1111875) on type 2 diabetes risk.  Molecular Genetics \nand Metabolism  ,  102 (2), 194199. \n Watanabe, R. M., Black, M. H., Xiang, A. H., Allayee, H., Lawrence, J. M., & Buchanan, T. A. (2007). \nGenetics of gestational diabetes mellitus and type 2 diabetes.  Diabetes Care  ,  30 (Suppl. 2), \nS134S140. \n Williams, M. A., Qiu, C., Dempsey , J. C., & Luthy , D. A. (2003). Familial aggregation of type 2",
              "title": "2011 - Shared Genomics of Type 2 and Gestational Diabetes Mellitus.pdf",
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              "text": "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\nsecretion, and insulin sensitivity in 58,614 nondiabetic subjects [6].\nCluster analysis classi ed the risk loci into ve major categories on the\nbasis of their association with glycemic phenotypes. The rst cluster\nwas characterized by the effects of the risk alleles of PPARG ,KLF14 ,",
              "title": "2019 - Biomarkers for type 2 diabetes.pdf",
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              "text": "recently, meta-analysis of GWAS data involving African \nAmerican type 2 diabetes patients identified similar loci \nto the previous studies with the addition of two novel \nloci, HLA-B and INS-IGF[157]. These results provide \nstrong evidence of common genetic determinants \nincluding common specific genes that are linked to \ndiabetes. A small list of specific genetic markers seem \nstrongly associated with the risk of developing type 2 \ndiabetes including the TCF7L2[158] and CAPN10[159,160]",
              "title": "2015 - Diabetes mellitus The epidemic of the century.pdf",
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              "text": "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes\nn engl j med 359;21 www.nejm.org november 20, 2008 2231MPP subjects (P = 0.001) and from 0.79 to 0.83 in \nthe Botnia subjects (P = 0.006).\nOf the 16 loci that have been associated with \ntype 2 diabetes previously,8-15 we showed that 11 \n TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, \nCDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX   \nwere associated with an enhanced risk of future",
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              "text": "Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes\nn engl j med 359;21 www.nejm.org november 20, 2008 2227(Fig. 1B), whereas impaired fasting glucose or \nimpaired glucose tolerance developed in 313 of 2039 subjects (15.4%).\nClinical Factors Predicting Incidence  \nof Diabetes\nIn both the MPP and Botnia studies, a family his -\ntory of diabetes, an increased BMI, and increased levels of blood pressure and serum levels of tri -",
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              "content": "New gene therapies have the potential to cure or treat diabetes through several innovative approaches:\n\n1. **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].\n\n2. **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].\n\n3. **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].\n\nThese strategies highlight the potential of gene therapies to address the underlying genetic causes of diabetes and restore normal insulin production and glucose regulation.",
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              "text": "unraveling the pathophysiological mechanisms of this disease, identifying \ncandidate diabetic genes, and discovering and testing new therapeutic agents. \nThe classical rodent models of diabetes allow unbiased discovery, while the \nnew models made by genetic manipulation allow testing of the role of \nspecific genes and tissues. Experimental animal models are an irreplaceable \nresource for diabetes research and are hastening the progress towards the \ngoals of better treatment, prevention, and cure.",
              "title": "2004 - Diabetes Genes a.pdf",
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              "text": "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.\n6. Gene Therapy in Diabetes",
              "title": "2015 - Recent Trends in Therapeutic Approaches for Diabetes Management  A Comprehensive Updat.pdf",
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              "text": "T ogether, these discoveries will continue to improve our \nunderstanding of the biologic mechanisms that maintain glucose homeostasis, and of still hidden  molecular defects leading to \nchronic hyperglycemia, and could also lead to the development of more speci  cally targeted antidiabetic drugs or even gene -\n 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",
              "title": "2010 - The Genetics of Type 2 Diabetes.pdf",
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              "text": "Greatstrideshavebeenmadeclinicallyintheprevention,\ndevelopment,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\nthe diabetes research. The development of the techniques",
              "title": "2015 - Recent Trends in Therapeutic Approaches for Diabetes Management  A Comprehensive Updat.pdf",
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              "text": "into different genetic levels of disease categories, from which pre-\nvention or treatment methods could be provided accordingly [ 4].\nFor example, some forms of diabetes are directly related to a change\nin a single gene [ 34]. Some patients who are diagnosed with type 1\ndiabetes can now be tested for one of monogenic diabetes. The\nappropriate treatment for these patients is not injecting insulin, but\ngiving oral sulfonylureas [ 34]. Moreover, it is now well understood",
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              "text": "pp .430435,2003.\n[58] M. Zalzman, S. Gupta, R. K. Giri et al., Reversal of\nhyperglycemia in mice by using human expandable insulin-\nproducing cells differentiated from fetal liver progenitor cells,Proceedings of the National Academy of Sciences of the United\nStatesofAmerica ,vol.100,no .12,pp .72537258,2003.\n[59] H.-S. Jun and J.-W. Yoon, Approaches for the cure of type 1\ndiabetes by cellular and gene therapy, Current Gene Therapy ,\nvol.5,no.2,pp.249262,2005.",
              "title": "2015 - Recent Trends in Therapeutic Approaches for Diabetes Management  A Comprehensive Updat.pdf",
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              "text": "transgenics. It is likely that animal models will play an importantrole in the eventual cure of human diabetes mellitus. \nCompeting interests \nNone declared. \nReferences \n1Sima AAF, Shafrir E, eds.  \nAnimal Models of Diabetes: A Primer. \nAmsterdam: Harwood Academic Publishers, 2000.\n2British Union for the Abolition of Vivisection. Home page. Available\nfrom: http://www.buav.org.\n3Patterson C.  \nEternal Treblinka. Our Treatment of Animals and the\nHolocaust \n. New York: Lantern Books, 2002.\n4Regan T.",
              "title": "2005  - Animal models of diabetes mellitus.pdf",
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              "text": "Third, this view of diabetes pathogenesis is consistent with\nthe growing portfolio of available therapies. We have agents\nand interventions that can prevent or ameliorate diabetesthrough, for example, beneficial effects on islet function\n(e.g. sulfonylureas), obesity (weight loss), insulin resistance\n(e.g. exercise), fuel partitioning (e.g. thiazolidinediones) andmicrobiome content (metformin, possibly). Just as diabetes\nrisk alleles influence metabolic phenotype through pushing",
              "title": "2017 - Painting a new picture of personalised medicine for diabetes.pdf",
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              "text": "aprospectivetherapeuticapproachfortype1diabetes[59].\nThein vivogene therapy is the method of choice as\na 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",
              "title": "2015 - Recent Trends in Therapeutic Approaches for Diabetes Management  A Comprehensive Updat.pdf",
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              "text": "betacellulin gene therapy induces islet neogenesis in the liver\na 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 ,\npp.596603,2003.\n[73] S. Ferber, A. Halkin, H. Cohen et al., Pancreatic and duode-\nnal homeobox gene 1 induces expression of insulin genes inliver and ameliorates streptozotocin-induced hyperglycemia,\nNature Medicine ,vol.6,no .5,pp .568572,2000.\n[74] P.A.Halban,S.E.Kahn, A.Lernmark,andC.J.Rhodes,Gene\nandcell-replacementtherapyinthetreatmentoftype1diabetes.",
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              "content": "Monogenic and polygenic diabetes are distinct forms of diabetes with different genetic underpinnings:\n\n1. **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].\n\n2. **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].\n\nIn 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.",
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              "text": "to improve diagnosis. Monogenic vs. polygenic diabetes  \nMonogenic and polygenic diabetes are traditionally considered distinct, with \nmonogenic diabetes resulting from one highly penetrant variant in one gene in a given \nindividual, and polygenic diabetes resulting from the contribution of several variants with \nsmaller effects in the context of environmental/lifestyle factors.  In T1D, autoimmune \ndysfunction is the prominent mechanism, with variation in the major histocompatibility",
              "title": "2021 - Genomic Medicine in Diabetes Improving the Diagnostic Rate of Monogenic Diabetes.pdf",
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              "text": "represent about 2%-5% of diabetes patients. Mono -\ngenic diabetes results primarily from gene defects that \nlead to a decrease in beta cell number or function. \nMonogenic diabetes genes were identified using linkage \nstudies or code for proteins that directly affected \nglucose homeostasis. The majority of genes responsible \nfor monogenetic diabetes code for either transcription \nfactors that participate in the control of nuclear gene \nexpression or proteins that are located on the cell",
              "title": "2015 - Diabetes mellitus The epidemic of the century.pdf",
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              "text": "diabetic patients inwhom rare, highly\npenetrant mutations ofasingle gene\ncause their diabetes (13). While com -\nmon variants ofthese genes that make a\nsmall contribution topolygenic diabetes\nmay also exist (13), thevariants causing\nmonogenic diabetes have limited util-\nityinpharmacogenetics duetotheir low\nallele frequency. Thevast majority oftype\n2diabetes patients have polygenetic forms\nofthedisease that typically also require a\npermissive environment (e.g., obesity, sed-",
              "title": "2007 - Pharmacogenetics of metformin response a step in the path toward personalized medicine.pdf",
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              "text": "diabetes exist along more of a continuum than previously appre -\nciated. Therefore, knowledge about monogenic diabetes not only \nprovides opportunities for etiology-based treatment of the minori-\nty of individuals with highly penetrant variants, but also informs \nbroader understanding of diabetes etiology.\nTypes of monogenic diabetes\nMaturity-onset diabetes of the young\nMODY comprises most monogenic diabetes cases, with classical \ncharacteristics of young diagnosis age, family history of diabe -",
              "title": "2021 -  Monogenic diabetes a gateway to precision medicine.pdf",
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              "text": "Monogenic Diabetes \n 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",
              "title": "2012 - Systems Biology Approaches to Nutrition.pdf",
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              "text": "HNF4A-MODY  and requires genetic testing to diagnose. Here \nwe will describe monogenic diabetes types, etiologies, diagnosis, \nmanagement, and strategies to improve diagnosis.\nMonogenic versus polygenic diabetes\nMonogenic and polygenic diabetes are traditionally considered \ndistinct, with monogenic diabetes resulting from one highly pene -\ntrant variant in one gene in a given individual and polygenic diabe -\ntes resulting from the contribution of several variants with smaller",
              "title": "2021 -  Monogenic diabetes a gateway to precision medicine.pdf",
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              "text": "Monogenic inheritance is caused by mutation of a single gene. There are \nsome well-defined monogenic rodent models. In humans, monogenic obesity \nand diabetes exist as well, but are extremely rare. \nPolygenic inheritance is the result of multiple contributing genes and \nis the predominant mode of inheritance in human type 2 diabetes. Multiple \npolygenic animal models are also available. However, even in monogenic \nanimal models, genetic background plays an important influence. For",
              "title": "2004 - Diabetes Genes a.pdf",
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              "text": "(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",
              "title": "2019 - HDAC4 mutations cause diabetes and induce  \u2010cell FoxO1 nuclear exclusion.pdf",
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              "text": "Key words:\ndiabetes, gene, polygenic, monogenic\nIntroduction\nDiabetes is one of the most common metabolic disor -\nders. It is estimated that the number of diabetes pa -\ntients worldwide has already exceeded 200 million\n[92]. This creates a need to understand the etiology ofthe disease, genetic and enviromental factors influ -\nencing development of diabetes. Diabetes is a group\nof metabolic diseases that are characterized by ele -\nvated glucose level. Poorly controlled or undiagnosed",
              "title": "2005 - Type 2 diabetes mellitus from genes to disease.pdf",
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              "text": "2 \n 1.1.2 Introduction \nMonogenic diabetes is caused by a single defect in one of over 40 genes1,2. Since \nMODY (maturity onset diabetes of the young) was named by Fajans for the T2D -like \npresentation in young people with an autosomal dominant pattern of inheritance3,4, our \nunderstanding of phenotypic and genetic heterogeneity in monogenic diabetes has \nincreased. The major monogenic diabetes categories are MODY, neon atal diabetes",
              "title": "2021 - Genomic Medicine in Diabetes Improving the Diagnostic Rate of Monogenic Diabetes.pdf",
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              "content": "Studying the DNA of people with diabetes helps scientists find better treatments or cures in several ways:\n\n1. **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].\n\n2. **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].\n\n3. **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].\n\n4. **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].\n\n5. **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].\n\n6. **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].\n\nOverall, studying the DNA of people with diabetes provides critical insights that drive the development of more effective and personalized treatments.",
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              "text": "by performing a genetic profile on diabetic patients (pharmacogenetics). \nFurthermore, identification of genetic determinants of diabetic patients will \nbetter define the targets of current and future therapies, and will lead to \ntherapies that are more specific for their genetic constitutes. \nSUMMARY \nWith the advancement of the Human Genome Project, we enter the \nera of a sequence-based biology. Some progress has been made in the",
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              "text": "Todate,studiesofdiabeteshaveplayedamajorroleinshapingthinkingabout\nthegeneticanalysisofcomplexdiseases.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.",
              "title": "2003 - The Inherited Basis of Diabetes Mellitus.pdf",
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              "text": "DNA code. Therefore, greater unders tanding of the epigenetic basis of disease could enable the 576 \ndiscovery new therapeutic targets for the treat ment of numerous human diseases including 577 \ndiabetes and its complications. 578 \n 579 \n580",
              "title": "2010 - The Role of Epigenetics in the Pathology of Diabetic Complications.pdf",
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              "text": "T ogether, these discoveries will continue to improve our \nunderstanding of the biologic mechanisms that maintain glucose homeostasis, and of still hidden  molecular defects leading to \nchronic hyperglycemia, and could also lead to the development of more speci  cally targeted antidiabetic drugs or even gene -\n 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",
              "title": "2010 - The Genetics of Type 2 Diabetes.pdf",
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              "text": "research will contribute positive ly to the life of people living with T1D . Being able pinpoint \nmutations, and then discover how they contribute to the genetic  cause  of a condition, can help \nto open up path s for pharmaceutical treatments. Currently, m ost treatment strategies for genetic \ndisorders do not alter the underlying genetic mutation;  but are designed to improve particular \nsigns and symptoms associated with the disorder. For instance, T1D  is managed by",
              "title": "2016 - The Genomics of Type 1 Diabetes.pdf",
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              "text": "Epigenomic approaches: applications in diabetic\ncomplications research\nEpigenetic studies in human disease have been greatly accel-\nerated as a result of advances in whole-genome and epige-\nnome profiling technologies as well as bioinformatics andgenomic data analysis platforms [ 99,100]. DNAme is\nanalysed using bisulfite conversion of genomic DNA, immu-\nnoprecipitation of methylated DNA, followed byhybridisation to arrays or next-generation sequencing to ob-",
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              "text": "new therapeutic targets and identify potential diabetic neuropathy\nbiomarkers. The genes identied in the current study conrm datagathered from experimental models of diabetes and provide a\ncomprehensive picture of the expression of multiple targets in asingle human tissue sample.\nOur initial analyses of this data set classied the patient samples\nbased on myelinated bre density and found that two large\ngroups emerged; those with a loss of myelinated bre density\n5500 bres/mm",
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              "text": "DNA variation with disease processes in a range of settings, from cell\nlines to human populations, and major advances have been made in\ncoupling these complex datasets with information about extrinsic\nenvironmental exposures including drug prescription in ways that allowthe logical interrogation of gene-drug and gene-lifestyle interactions.\nDoing so may teach us about disease etiology and help stratify type 2\ndiabetes (T2D) into subclasses that can be treated more effectively, with",
              "title": "2016 - Putting the Genome in Context Gene-Environment Interactions.pdf",
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              "text": "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",
              "title": "2008 - Glossary of Genetics Genomics Terms.pdf",
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              "text": "the onset and progression of diabetic neuropathy is of primeimportance.\nThe current study takes an important rst step towards this goal\nby identifying specic sets of genes whose expression accurately\nclassies patient samples with regard to diabetic neuropathy pro-\ngression and by analysing their interactions within known cellularpathways. Identifying common elements in these complex net-works will yield novel insights into disease pathogenesis, provide",
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