{
    "created_at": "2024-04-18T18:45:53.040778Z",
    "data": {
        "amplify": false,
        "answer": "The varying efficacy of diabetes treatments among individuals can be attributed to genetic variants present in drug receptors or drug metabolizers, such as OCT genes, KCNJ11, ABCC8, and CYP2C9. These genetic variants can influence the metabolism, transportation, and therapeutic mechanisms of antidiabetic drugs, leading to differences in drug disposition, glycemic response, tolerability, and incidence of adverse effects. Additionally, gene-gene, gene-environment, and gene-treatment interactions may also contribute to the variation in disease progression and response to therapy.",
        "context": {
            "063a0254-1d1b-4caa-b782-6a1fe4ebca0d": [
                {
                    "document_id": "063a0254-1d1b-4caa-b782-6a1fe4ebca0d",
                    "text": "Genetics and pharmacogenomics\n\nWe are at the dawn of the age of pharmacogenomics and personalized medicine and ever closer to achieving the \"$1,000 genome. \"What does this mean for diabetes?Forward genetic approaches (i.e., starting from phenotype and identifying the genetic cause) to dissecting mendelian forms of diabetes have been hugely successful in identifying a small subset of diabetic patients in whom rare, highly penetrant mutations of a single gene cause their diabetes (13).While common variants of these genes that make a small contribution to polygenic diabetes may also exist (13), the variants causing monogenic diabetes have limited utility in pharmacogenetics due to their low allele frequency.The vast majority of type 2 diabetes patients have polygenetic forms of the disease that typically also require a permissive environment (e.g., obesity, sedentary lifestyle, advancing age, etc.) to be penetrant.Each locus contributes a small amount of risk (odds ratios typically ranging from 1.1- to 1.5-fold), so large cohorts are needed to identify the at-risk alleles.Some of the loci identified to date include transcription factor 7-like 2 (TCF7L2) (14), calpain 10 (CAPN10) (15), peroxisome proliferator-activated receptor γ (PPARG) (16), and potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) (17).However, the pace of gene identification is increasing due to the availability of large-scale databases of genetic variation and advances in genotyping technology.A recent genome-wide study identified solute carrier family 30, member 8 (SLC30A8), a β cell Zn transporter, and two other genomic regions as additional diabetes risk loci (18)."
                }
            ],
            "08858a32-d736-4d8d-a135-f86568152a81": [
                {
                    "document_id": "08858a32-d736-4d8d-a135-f86568152a81",
                    "text": "\n\nWith further progress in unravelling the pathogenic roles of genes and epigenomic phenomena in type 2 diabetes, pharmacogenomic and pharmacoepigenomic studies might eventually yield treatment choices that can be personalised for individual patients."
                }
            ],
            "183f165e-4d5c-4580-9aff-4e6b2e5a6463": [
                {
                    "document_id": "183f165e-4d5c-4580-9aff-4e6b2e5a6463",
                    "text": "Pharmacogenomics of Type 2 Diabetes\n\nWith the advent of GWAS, studies on the roles of inherited and acquired genetic variations in drug response have undergone an evolution from pharmacogenetics into pharmacogenomics, with a shift from the focus on individual candidate genes to GWAS [147].Clinically, it is often observed that even patients who receive similar antidiabetic regimens demonstrate large variability in drug disposition, glycemic response, tolerability, and incidence of adverse effects [148].This interindividual variability can be attributed to specific gene polymorphisms involved in the metabolism, transportation, and therapeutic mechanisms of oral antidiabetic drugs.Pharmacogenomics is on the agenda to explore feasible genetic testing to predict treatment outcome, so that appropriate steps could be taken to treat type 2 diabetes more efficiently."
                }
            ],
            "277be46c-4307-4738-972d-eb6efd9b175a": [
                {
                    "document_id": "277be46c-4307-4738-972d-eb6efd9b175a",
                    "text": "Future directions\n\nDelays in identifying genetic variants that are robustly associated with differences in individual predisposition to the complications of diabetes, have constrained progress towards a mechanistic understanding of these conditions.Some approaches to overcome these limitations are outlined in Figure 4."
                }
            ],
            "4d3330eb-acd0-4f72-aadf-b056d3c8b389": [
                {
                    "document_id": "4d3330eb-acd0-4f72-aadf-b056d3c8b389",
                    "text": "Genomics of T2D\n\nDiet, lifestyle, environment, and even genetic variation influence an individual's response to disease therapy.Like GWAS which identify genetic variants conferring risk for a disease, studies have been carried out for identifying genetic variants responsible for patient differences in drug response.Pharmacogenomics in diabetes focuses on the study of gene polymorphisms which influence an individual's response to antidiabetic drugs.Such genetic variants influence the pharmacodynamics and/or pharmacokinetics of the drug, thus affecting its efficacy or toxicity in an individual.The difference in response to treatments and therapies across individuals on account of these factors strengthens the case for personalized medicine in diabetes."
                },
                {
                    "document_id": "4d3330eb-acd0-4f72-aadf-b056d3c8b389",
                    "text": "Genetics & genomics of T2D\n\n• Genome-wide association studies (GWAS) have been helpful in identifying a large number of genetic variants conferring risk to T2D.However, only close to 10% heritability is explained by these variants.Other genetic variants, particularly those which are rare but with significant effects need to be identified.• Genetic variability is responsible for the difference in response to antidiabetic drugs seen across individuals."
                }
            ],
            "4feda561-1914-404d-9092-3c629d5251bd": [
                {
                    "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                    "text": "\nThe aim of this study was to summarize current knowledge and provide perspectives on the relationships between human genetic variants, type 2 diabetes, antidiabetic treatment, and disease progression.Type 2 diabetes is a complex disease with clear-cut diagnostic criteria and treatment guidelines.Yet, the interindividual response to therapy and slope of disease progression varies markedly among patients with type 2 diabetes.Gene-gene, gene-environment, and gene-treatment interactions may explain some of the variation in disease progression.Several genetic variants have been suggested to be associated with response to antidiabetic drugs.Some are present in drug receptors or drug metabolizers (OCT genes, KCNJ11, ABCC8, and CYP2C9).Numerous type 2 diabetes risk variants have been identified, but genetic risk score models applying these variants have failed to identify 'disease progressors' among patients with diabetes.Although genetic risk scores are based on a few known loci and only explain a fraction of the heritability of type 2 diabetes, it seems that the genes responsible for the development of diabetes may not be the same driving disease progression after the diagnosis has been made.Pharmacogenetic interactions explain some of the interindividual variation in responses to antidiabetic treatment and may provide the foundation for future genotype-based treatment standards.Pharmacogenetics and Genomics 25:475-484"
                },
                {
                    "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                    "text": "\n\nDiabetes progression is a multifactorial process; however, pharmacogenetics seems to play an important role in understanding the different phenotypes and progression rates among diabetic patients.Genetic variants associated with decreased effect of a certain drug might explain why some individuals are more likely to experience glycemic deterioration on a given treatment.In the following sections, different genetic variants and their impact on treatment efficacy and outcome will be addressed."
                },
                {
                    "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                    "text": "\n\nThe aim of this study was to summarize current knowledge and provide perspectives on the relationships between human genetic variants, type 2 diabetes, antidiabetic treatment, and disease progression.Type 2 diabetes is a complex disease with clear-cut diagnostic criteria and treatment guidelines.Yet, the interindividual response to therapy and slope of disease progression varies markedly among patients with type 2 diabetes.Gene-gene, gene-environment, and gene-treatment interactions may explain some of the variation in disease progression.Several genetic variants have been suggested to be associated with response to antidiabetic drugs.Some are present in drug receptors or drug metabolizers (OCT genes, KCNJ11, ABCC8, and CYP2C9).Numerous type 2 diabetes risk variants have been identified, but genetic risk score models applying these variants have failed to identify 'disease progressors' among patients with diabetes.Although genetic risk scores are based on a few known loci and only explain a fraction of the heritability of type 2 diabetes, it seems that the genes responsible for the development of diabetes may not be the same driving disease progression after the diagnosis has been made.Pharmacogenetic interactions explain some of the interindividual variation in responses to antidiabetic treatment and may provide the foundation for future genotype-based treatment standards.Pharmacogenetics and Genomics 25:475-484"
                },
                {
                    "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                    "text": "\n\nTo date, a number of genetic variants have been identified to be associated with response to antidiabetic drugs.Of these, some variants are present in either drug receptors or drug metabolizers as for OCT genes, KCNJ11, ABCC8, and CYP2C9.Other variants are known T2D susceptibility variants such as TCF7L2.To identify variants of importance for antiglycemic drug response, GWAS in large cohorts of patients with diabetes with detailed measures of pharmacotherapy are lacking.The pharmacologic management of patients with diabetes often involves drug classes other than antidiabetics.Pharmacogenetic studies on statin and antihypertensive treatment have reported several genetic variants associated with treatment response and adverse drug reactions [101,102].It therefore seems natural to conclude that the future perspectives in pharmacogenetics is to conduct genetic studies in large cohorts with wellphenotyped individuals, thorough data collection on baseline treatment, concomitant treatment, adherence to therapy as well as data collection on comorbidity and additional disease diagnoses.These types of pharmacogenetic studies may provide unique opportunities for future genotype-based treatment standards and may help in delaying or changing the slope of disease progression among patients with T2D."
                }
            ],
            "50c72e55-b5fe-42a6-b837-64c28620a4c0": [
                {
                    "document_id": "50c72e55-b5fe-42a6-b837-64c28620a4c0",
                    "text": "\n\nGenetic determinants of diabetes and metabolic syndromes."
                }
            ],
            "516de7be-3cef-47ee-8338-199fb922bc6f": [
                {
                    "document_id": "516de7be-3cef-47ee-8338-199fb922bc6f",
                    "text": "\n\nThus, specific answers are lacking as to the genetic basis for type 2 diabetes.Still, speculations can be made about what eventually will be found.It is almost certain the genetic basis for type 2 diabetes and other common metabolic diseases will be extremely complex-that a predisposition for the disease will require several genetic hits as opposed to just one.Also, it is generally assumed there will be many susceptibility genes for type 2 diabetes, with enormous variability in different families and ethnic groups.Not known is whether there will be a common form of type 2 diabetes, with any one or even a few susceptibility genes accounting for a sizeable percentage of affected persons.As such, identifying diabetes genes will be slow and difficult."
                }
            ],
            "5d1d5baa-75f4-42d5-8e4c-fb038a71bbec": [
                {
                    "document_id": "5d1d5baa-75f4-42d5-8e4c-fb038a71bbec",
                    "text": "Ta rge ted T r e atmen t a nd Pr e v en t ion\n\n4][75] In monogenic forms of diabetes, at least, genetic testing already drives the choice of therapy.For example, in patients who have maturity-onset diabetes of the young due to mutations in the gene encoding glucokinase (GCK), the hyperglycemia is mild and stable, the risk of complications is low, and dietary management is often sufficient.In contrast, in patients who have maturity-onset diabetes of the young due to mutations in HNF1A, the disease follows a more aggressive course, with a greater risk of severe complications, but is particularly responsive to the hypoglycemic effects of sulfonylureas. 62,73Most children with neonatal diabetes have mutations in KCNJ11 or ABCC8, adjacent genes that jointly encode the beta-cell ATP-sensitive potassium channel that mediates glucose-stimulated insulin secretion and is the target of sulfonylureas.In such children, treatment with sulfonylureas has proved more effective and convenient than the lifelong insulin therapy previously considered the default option. 74,75n children with severe obesity due to profound leptin deficiency, exogenous leptin therapy is lifesaving. 76s yet, there are insufficient genetic data to support management decisions for common forms of type 2 diabetes and obesity. 77Although the TCF7L2 genotype is associated with variation in the response to sulfonylurea treatment, 78 the effect is too modest to guide the care of individual patients.For the time being, the contribution of genetic information to therapy is most likely to come through the drug-discovery pipeline.Information from genetic studies could be used to identify new targets for pharmaceutical intervention that have validated effects on physiological characteristics, to provide information about new and existing targets (e.g., clues about the long-term safety of pathway intervention), 32 and to characterize high-risk groups to enable more efficient clinical trials of agents designed to reduce the progression of type 2 diabetes or obesity or the risk of complications."
                }
            ],
            "9c9cc0b3-5dde-4077-ae41-1410db9aeb24": [
                {
                    "document_id": "9c9cc0b3-5dde-4077-ae41-1410db9aeb24",
                    "text": "Type 2 Diabetes\n\nWhile a subset of genetic variants are linked to both type 1 and type 2 diabetes (42,43), the two diseases have a largely distinct genetic basis, which could be leveraged toward classification of diabetes (44).Genome-wide association studies have identified more than 130 genetic variants associated with type 2 diabetes, glucose levels, or insulin levels; however, these variants explain less than 15% of disease heritability (45)(46)(47).There are many possibilities for explaining the majority of type 2 diabetes heritability, including disease heterogeneity, gene-gene interactions, and epigenetics.Most type 2 variants are in noncoding genomic regions.Some variants, such as those in KCNQ1, show strong parent-of-origin effects (48).It is possible that children of mothers carrying KCNQ1 are born with a reduced functional b-cell mass and thereby are less able to increase their insulin secretion when exposed to insulin resistance (49).Another area of particular interest has been the search for rare variants protecting from type 2 diabetes, such as loss-of-function mutations in SLC30A8 (50), which could offer potential new drug targets for type 2 diabetes."
                },
                {
                    "document_id": "9c9cc0b3-5dde-4077-ae41-1410db9aeb24",
                    "text": "Research Gaps\n\nAfter consideration of the known genetic associations with diabetes risk, consensus developed that the field is not yet at a place where genetics has provided actionable information to guide treatment decisions, with a few notable exceptions, namely in MODY.The experts agreed there is a need to use the increasingly accessible and affordable technologies to further refine our understanding of how genetic variations affect the rate of progression of diabetes and its complications.The expert committee also highlighted the importance of determining categorical phenotypic subtypes of diabetes in order to link specific genetic associations to these phenotypic subtypes.These types of information are necessary to develop the tools to predict response to-and side effects of-therapeutic approaches for diabetes in patient populations."
                }
            ],
            "ad88aed6-75ba-469d-b96b-7be4a65be8fc": [
                {
                    "document_id": "ad88aed6-75ba-469d-b96b-7be4a65be8fc",
                    "text": "\nGenome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c).At the end of 2011, established loci (P < 5 × 10 −8 ) totaled 55 for T2D and 32 for glycemic traits.Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05]variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations.Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF ≤ 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci.Established published loci now total ∼88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered.Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes."
                }
            ],
            "b00b9753-c198-4f8a-a8b9-dd5e94dc5896": [
                {
                    "document_id": "b00b9753-c198-4f8a-a8b9-dd5e94dc5896",
                    "text": "\n\nTogether, the findings from these studies were among the first to demonstrate that the genetic etiology of hyperglycemia may modulate response to hypoglycemia agents.Such results yielded strong implications for patient management and paved the way toward elucidating additional genetic factors that might influence drug response in the treatment of T2D."
                }
            ],
            "c8c58fdf-06e3-4da4-a920-d5bcbcd18289": [
                {
                    "document_id": "c8c58fdf-06e3-4da4-a920-d5bcbcd18289",
                    "text": "A\n\nnumber of studies have implicated a genetic basis for type 2 diabetes (1).The discovery of monogenic forms of the disease underscored the phenotypic and genotypic heterogeneity, although monogenic forms account for only a few percent of the disease (1).Defining the genetic basis of the far more common polygenic form of the disease presents more difficulties (2,3).Nevertheless, some interesting results have recently emerged.A genome scan of Hispanic-American families (330 affected sib-pairs [ASPs]) found linkage to chromosome 2q37 (logarithm of odds [LOD] 4.15) (4), and the causative gene has been recently reported (5).A number of other genome scans in various racial groups have identified other putative susceptibility loci (6 -8).The largest genome-wide scan for type 2 diabetes loci reported to date studied 477 Finnish families (716 ASPs) and found evidence for linkage to chromosome 20q12-13.1(LOD 2.06 at D20S107) (9).Interestingly, similar results have been reported by at least three other groups (10 -12)."
                }
            ],
            "f7072d9b-4e07-4541-bac7-13a25761f460": [
                {
                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
                    "text": "\n\nBecause more than one genetic mutation contributes to T1D, the differences that occur between individuals of different backgrounds (for instance, race and locality) may need to be considered in the design of treatments.Personalized medicine is about the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or in their response to a specific treatment (Blau and Liakopoulou, 2013;Timmeman, 2013).This will allow for a more accurate diagnosis per individual, and design of specific treatment plans including gene therapy."
                }
            ],
            "fcf8fb37-20cf-491c-96f8-04a5621812a2": [
                {
                    "document_id": "fcf8fb37-20cf-491c-96f8-04a5621812a2",
                    "text": "\n\nGenetic predisposition to diabetes mellitus type 2: will large collaborative efforts be able to overcome the geneticist's nightmare?"
                }
            ]
        },
        "data_source": [
            {
                "document_id": "4d3330eb-acd0-4f72-aadf-b056d3c8b389",
                "section_type": "main",
                "text": "Genomics of T2D\n\nDiet, lifestyle, environment, and even genetic variation influence an individual's response to disease therapy.Like GWAS which identify genetic variants conferring risk for a disease, studies have been carried out for identifying genetic variants responsible for patient differences in drug response.Pharmacogenomics in diabetes focuses on the study of gene polymorphisms which influence an individual's response to antidiabetic drugs.Such genetic variants influence the pharmacodynamics and/or pharmacokinetics of the drug, thus affecting its efficacy or toxicity in an individual.The difference in response to treatments and therapies across individuals on account of these factors strengthens the case for personalized medicine in diabetes."
            },
            {
                "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                "section_type": "abstract",
                "text": "\nThe aim of this study was to summarize current knowledge and provide perspectives on the relationships between human genetic variants, type 2 diabetes, antidiabetic treatment, and disease progression.Type 2 diabetes is a complex disease with clear-cut diagnostic criteria and treatment guidelines.Yet, the interindividual response to therapy and slope of disease progression varies markedly among patients with type 2 diabetes.Gene-gene, gene-environment, and gene-treatment interactions may explain some of the variation in disease progression.Several genetic variants have been suggested to be associated with response to antidiabetic drugs.Some are present in drug receptors or drug metabolizers (OCT genes, KCNJ11, ABCC8, and CYP2C9).Numerous type 2 diabetes risk variants have been identified, but genetic risk score models applying these variants have failed to identify 'disease progressors' among patients with diabetes.Although genetic risk scores are based on a few known loci and only explain a fraction of the heritability of type 2 diabetes, it seems that the genes responsible for the development of diabetes may not be the same driving disease progression after the diagnosis has been made.Pharmacogenetic interactions explain some of the interindividual variation in responses to antidiabetic treatment and may provide the foundation for future genotype-based treatment standards.Pharmacogenetics and Genomics 25:475-484"
            },
            {
                "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                "section_type": "main",
                "text": "\n\nDiabetes progression is a multifactorial process; however, pharmacogenetics seems to play an important role in understanding the different phenotypes and progression rates among diabetic patients.Genetic variants associated with decreased effect of a certain drug might explain why some individuals are more likely to experience glycemic deterioration on a given treatment.In the following sections, different genetic variants and their impact on treatment efficacy and outcome will be addressed."
            },
            {
                "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                "section_type": "main",
                "text": "\n\nThe aim of this study was to summarize current knowledge and provide perspectives on the relationships between human genetic variants, type 2 diabetes, antidiabetic treatment, and disease progression.Type 2 diabetes is a complex disease with clear-cut diagnostic criteria and treatment guidelines.Yet, the interindividual response to therapy and slope of disease progression varies markedly among patients with type 2 diabetes.Gene-gene, gene-environment, and gene-treatment interactions may explain some of the variation in disease progression.Several genetic variants have been suggested to be associated with response to antidiabetic drugs.Some are present in drug receptors or drug metabolizers (OCT genes, KCNJ11, ABCC8, and CYP2C9).Numerous type 2 diabetes risk variants have been identified, but genetic risk score models applying these variants have failed to identify 'disease progressors' among patients with diabetes.Although genetic risk scores are based on a few known loci and only explain a fraction of the heritability of type 2 diabetes, it seems that the genes responsible for the development of diabetes may not be the same driving disease progression after the diagnosis has been made.Pharmacogenetic interactions explain some of the interindividual variation in responses to antidiabetic treatment and may provide the foundation for future genotype-based treatment standards.Pharmacogenetics and Genomics 25:475-484"
            },
            {
                "document_id": "183f165e-4d5c-4580-9aff-4e6b2e5a6463",
                "section_type": "main",
                "text": "Pharmacogenomics of Type 2 Diabetes\n\nWith the advent of GWAS, studies on the roles of inherited and acquired genetic variations in drug response have undergone an evolution from pharmacogenetics into pharmacogenomics, with a shift from the focus on individual candidate genes to GWAS [147].Clinically, it is often observed that even patients who receive similar antidiabetic regimens demonstrate large variability in drug disposition, glycemic response, tolerability, and incidence of adverse effects [148].This interindividual variability can be attributed to specific gene polymorphisms involved in the metabolism, transportation, and therapeutic mechanisms of oral antidiabetic drugs.Pharmacogenomics is on the agenda to explore feasible genetic testing to predict treatment outcome, so that appropriate steps could be taken to treat type 2 diabetes more efficiently."
            },
            {
                "document_id": "4d3330eb-acd0-4f72-aadf-b056d3c8b389",
                "section_type": "main",
                "text": "Genetics & genomics of T2D\n\n• Genome-wide association studies (GWAS) have been helpful in identifying a large number of genetic variants conferring risk to T2D.However, only close to 10% heritability is explained by these variants.Other genetic variants, particularly those which are rare but with significant effects need to be identified.• Genetic variability is responsible for the difference in response to antidiabetic drugs seen across individuals."
            },
            {
                "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                "section_type": "main",
                "text": "\n\nTo date, a number of genetic variants have been identified to be associated with response to antidiabetic drugs.Of these, some variants are present in either drug receptors or drug metabolizers as for OCT genes, KCNJ11, ABCC8, and CYP2C9.Other variants are known T2D susceptibility variants such as TCF7L2.To identify variants of importance for antiglycemic drug response, GWAS in large cohorts of patients with diabetes with detailed measures of pharmacotherapy are lacking.The pharmacologic management of patients with diabetes often involves drug classes other than antidiabetics.Pharmacogenetic studies on statin and antihypertensive treatment have reported several genetic variants associated with treatment response and adverse drug reactions [101,102].It therefore seems natural to conclude that the future perspectives in pharmacogenetics is to conduct genetic studies in large cohorts with wellphenotyped individuals, thorough data collection on baseline treatment, concomitant treatment, adherence to therapy as well as data collection on comorbidity and additional disease diagnoses.These types of pharmacogenetic studies may provide unique opportunities for future genotype-based treatment standards and may help in delaying or changing the slope of disease progression among patients with T2D."
            },
            {
                "document_id": "516de7be-3cef-47ee-8338-199fb922bc6f",
                "section_type": "main",
                "text": "\n\nThus, specific answers are lacking as to the genetic basis for type 2 diabetes.Still, speculations can be made about what eventually will be found.It is almost certain the genetic basis for type 2 diabetes and other common metabolic diseases will be extremely complex-that a predisposition for the disease will require several genetic hits as opposed to just one.Also, it is generally assumed there will be many susceptibility genes for type 2 diabetes, with enormous variability in different families and ethnic groups.Not known is whether there will be a common form of type 2 diabetes, with any one or even a few susceptibility genes accounting for a sizeable percentage of affected persons.As such, identifying diabetes genes will be slow and difficult."
            },
            {
                "document_id": "b00b9753-c198-4f8a-a8b9-dd5e94dc5896",
                "section_type": "main",
                "text": "\n\nTogether, the findings from these studies were among the first to demonstrate that the genetic etiology of hyperglycemia may modulate response to hypoglycemia agents.Such results yielded strong implications for patient management and paved the way toward elucidating additional genetic factors that might influence drug response in the treatment of T2D."
            },
            {
                "document_id": "fcf8fb37-20cf-491c-96f8-04a5621812a2",
                "section_type": "main",
                "text": "\n\nGenetic predisposition to diabetes mellitus type 2: will large collaborative efforts be able to overcome the geneticist's nightmare?"
            },
            {
                "document_id": "50c72e55-b5fe-42a6-b837-64c28620a4c0",
                "section_type": "main",
                "text": "\n\nGenetic determinants of diabetes and metabolic syndromes."
            },
            {
                "document_id": "08858a32-d736-4d8d-a135-f86568152a81",
                "section_type": "main",
                "text": "\n\nWith further progress in unravelling the pathogenic roles of genes and epigenomic phenomena in type 2 diabetes, pharmacogenomic and pharmacoepigenomic studies might eventually yield treatment choices that can be personalised for individual patients."
            },
            {
                "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
                "section_type": "main",
                "text": "\n\nBecause more than one genetic mutation contributes to T1D, the differences that occur between individuals of different backgrounds (for instance, race and locality) may need to be considered in the design of treatments.Personalized medicine is about the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or in their response to a specific treatment (Blau and Liakopoulou, 2013;Timmeman, 2013).This will allow for a more accurate diagnosis per individual, and design of specific treatment plans including gene therapy."
            },
            {
                "document_id": "5d1d5baa-75f4-42d5-8e4c-fb038a71bbec",
                "section_type": "main",
                "text": "Ta rge ted T r e atmen t a nd Pr e v en t ion\n\n4][75] In monogenic forms of diabetes, at least, genetic testing already drives the choice of therapy.For example, in patients who have maturity-onset diabetes of the young due to mutations in the gene encoding glucokinase (GCK), the hyperglycemia is mild and stable, the risk of complications is low, and dietary management is often sufficient.In contrast, in patients who have maturity-onset diabetes of the young due to mutations in HNF1A, the disease follows a more aggressive course, with a greater risk of severe complications, but is particularly responsive to the hypoglycemic effects of sulfonylureas. 62,73Most children with neonatal diabetes have mutations in KCNJ11 or ABCC8, adjacent genes that jointly encode the beta-cell ATP-sensitive potassium channel that mediates glucose-stimulated insulin secretion and is the target of sulfonylureas.In such children, treatment with sulfonylureas has proved more effective and convenient than the lifelong insulin therapy previously considered the default option. 74,75n children with severe obesity due to profound leptin deficiency, exogenous leptin therapy is lifesaving. 76s yet, there are insufficient genetic data to support management decisions for common forms of type 2 diabetes and obesity. 77Although the TCF7L2 genotype is associated with variation in the response to sulfonylurea treatment, 78 the effect is too modest to guide the care of individual patients.For the time being, the contribution of genetic information to therapy is most likely to come through the drug-discovery pipeline.Information from genetic studies could be used to identify new targets for pharmaceutical intervention that have validated effects on physiological characteristics, to provide information about new and existing targets (e.g., clues about the long-term safety of pathway intervention), 32 and to characterize high-risk groups to enable more efficient clinical trials of agents designed to reduce the progression of type 2 diabetes or obesity or the risk of complications."
            },
            {
                "document_id": "9c9cc0b3-5dde-4077-ae41-1410db9aeb24",
                "section_type": "main",
                "text": "Type 2 Diabetes\n\nWhile a subset of genetic variants are linked to both type 1 and type 2 diabetes (42,43), the two diseases have a largely distinct genetic basis, which could be leveraged toward classification of diabetes (44).Genome-wide association studies have identified more than 130 genetic variants associated with type 2 diabetes, glucose levels, or insulin levels; however, these variants explain less than 15% of disease heritability (45)(46)(47).There are many possibilities for explaining the majority of type 2 diabetes heritability, including disease heterogeneity, gene-gene interactions, and epigenetics.Most type 2 variants are in noncoding genomic regions.Some variants, such as those in KCNQ1, show strong parent-of-origin effects (48).It is possible that children of mothers carrying KCNQ1 are born with a reduced functional b-cell mass and thereby are less able to increase their insulin secretion when exposed to insulin resistance (49).Another area of particular interest has been the search for rare variants protecting from type 2 diabetes, such as loss-of-function mutations in SLC30A8 (50), which could offer potential new drug targets for type 2 diabetes."
            },
            {
                "document_id": "c8c58fdf-06e3-4da4-a920-d5bcbcd18289",
                "section_type": "main",
                "text": "A\n\nnumber of studies have implicated a genetic basis for type 2 diabetes (1).The discovery of monogenic forms of the disease underscored the phenotypic and genotypic heterogeneity, although monogenic forms account for only a few percent of the disease (1).Defining the genetic basis of the far more common polygenic form of the disease presents more difficulties (2,3).Nevertheless, some interesting results have recently emerged.A genome scan of Hispanic-American families (330 affected sib-pairs [ASPs]) found linkage to chromosome 2q37 (logarithm of odds [LOD] 4.15) (4), and the causative gene has been recently reported (5).A number of other genome scans in various racial groups have identified other putative susceptibility loci (6 -8).The largest genome-wide scan for type 2 diabetes loci reported to date studied 477 Finnish families (716 ASPs) and found evidence for linkage to chromosome 20q12-13.1(LOD 2.06 at D20S107) (9).Interestingly, similar results have been reported by at least three other groups (10 -12)."
            },
            {
                "document_id": "277be46c-4307-4738-972d-eb6efd9b175a",
                "section_type": "main",
                "text": "Future directions\n\nDelays in identifying genetic variants that are robustly associated with differences in individual predisposition to the complications of diabetes, have constrained progress towards a mechanistic understanding of these conditions.Some approaches to overcome these limitations are outlined in Figure 4."
            },
            {
                "document_id": "9c9cc0b3-5dde-4077-ae41-1410db9aeb24",
                "section_type": "main",
                "text": "Research Gaps\n\nAfter consideration of the known genetic associations with diabetes risk, consensus developed that the field is not yet at a place where genetics has provided actionable information to guide treatment decisions, with a few notable exceptions, namely in MODY.The experts agreed there is a need to use the increasingly accessible and affordable technologies to further refine our understanding of how genetic variations affect the rate of progression of diabetes and its complications.The expert committee also highlighted the importance of determining categorical phenotypic subtypes of diabetes in order to link specific genetic associations to these phenotypic subtypes.These types of information are necessary to develop the tools to predict response to-and side effects of-therapeutic approaches for diabetes in patient populations."
            },
            {
                "document_id": "063a0254-1d1b-4caa-b782-6a1fe4ebca0d",
                "section_type": "main",
                "text": "Genetics and pharmacogenomics\n\nWe are at the dawn of the age of pharmacogenomics and personalized medicine and ever closer to achieving the \"$1,000 genome. \"What does this mean for diabetes?Forward genetic approaches (i.e., starting from phenotype and identifying the genetic cause) to dissecting mendelian forms of diabetes have been hugely successful in identifying a small subset of diabetic patients in whom rare, highly penetrant mutations of a single gene cause their diabetes (13).While common variants of these genes that make a small contribution to polygenic diabetes may also exist (13), the variants causing monogenic diabetes have limited utility in pharmacogenetics due to their low allele frequency.The vast majority of type 2 diabetes patients have polygenetic forms of the disease that typically also require a permissive environment (e.g., obesity, sedentary lifestyle, advancing age, etc.) to be penetrant.Each locus contributes a small amount of risk (odds ratios typically ranging from 1.1- to 1.5-fold), so large cohorts are needed to identify the at-risk alleles.Some of the loci identified to date include transcription factor 7-like 2 (TCF7L2) (14), calpain 10 (CAPN10) (15), peroxisome proliferator-activated receptor γ (PPARG) (16), and potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) (17).However, the pace of gene identification is increasing due to the availability of large-scale databases of genetic variation and advances in genotyping technology.A recent genome-wide study identified solute carrier family 30, member 8 (SLC30A8), a β cell Zn transporter, and two other genomic regions as additional diabetes risk loci (18)."
            },
            {
                "document_id": "ad88aed6-75ba-469d-b96b-7be4a65be8fc",
                "section_type": "abstract",
                "text": "\nGenome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c).At the end of 2011, established loci (P < 5 × 10 −8 ) totaled 55 for T2D and 32 for glycemic traits.Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05]variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations.Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF ≤ 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci.Established published loci now total ∼88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered.Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes."
            },
            {
                "document_id": "ce63119a-9a7b-4946-b1f5-bc8bfc4c10da",
                "section_type": "main",
                "text": "\n\nGenetic factors appear to play a role in determining an individual's risk of developing diabetes.It is hoped 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 future intervention.A substantial number of genetic loci, gene polymorphisms, and mutations have already been reported as having variable degrees of association with one or other type of diabetes (type 1, type 2, maturity onset diabetes of the young [MODY]), while others appear to be involved in response to antihyperglycemic agents.We have compiled the following glossary of genetic and genomic terms relating to diabetes, which we hope will prove a useful reference to researchers and clinicians with an interest in this disease.This is by no means an exhaustive list, but includes many of the genetic loci and variants that have been studied in association with diabetes.Gene encoding insulin-like growth factor 2 mRNA binding protein 2 (also known as IMP-2).SNPs in the gene have been associated with type 2 diabetes IFIH1"
            },
            {
                "document_id": "e2c1cfb0-9cfc-4a59-9df6-8599708b25ed",
                "section_type": "main",
                "text": "\n\nc With increasing efforts to map patients with T2D in etiological space using clinical and molecular phenotype, physiology, and genetics, it is likely that this increasingly granular view of T2D will lead to increasing precision therapeutic paradigms requiring evaluation and potential implementation.Genetic variation not only can capture etiological variation (i.e., genetic variants associated with diabetes risk) but also variation in drug pharmacokinetics (absorption, distribution, metabolism, and excretion [ADME]) and in drug action (pharmacodynamics)."
            },
            {
                "document_id": "d978c09f-53e0-4a69-bfa6-e15537f32ffb",
                "section_type": "main",
                "text": "Genomics and gene-environment interactions\n\nEven though many cases of T2DM could be prevented by maintaining a healthy body weight and adhering to a healthy lifestyle, some individuals with prediabetes mellitus are more susceptible to T2DM than others, which suggests that individual differences in response to lifestyle interventions exist 76 .Substantial evidence from twin and family studies has suggested a genetic basis of T2DM 77 .Over the past decade, successive waves of T2DM genome-wide association studies have identified >100 robust association signals, demonstrating the complex polygenic nature of T2DM 5 .Most of these loci affect T2DM risk through primary effects on insulin secretion, and a minority act through reducing insulin action 78 .Individually, the common variants (minor allele frequency >5%) identified in these studies have only a modest effect on T2DM risk and collectively explain only a small portion (~20%) of observed T2DM heritability 5 .It has been hypothesized that lower-frequency variants could explain much of the remaining heritability 79 .However, results of a large-scale sequencing study from the GoT2D and T2D-GENES consortia, published in 2016, do not support such a hypothesis 5 .Genetic variants might help reveal possible aetiological mechanisms underlying T2DM development; however, the variants identified thus far have not enabled clinical prediction beyond that achieved with common clinical measurements, including age, BMI, fasting levels of glucose and dyslipidaemia.A study published in 2014 linked susceptibility variants to quantitative glycaemic traits and grouped these variants on the basis of their potential intermediate mechanisms in T2DM pathophysiology: four variants fitted a clear insulin resistance pattern; two reduced insulin secretion with fasting hyperglycaemia; nine reduced insulin secretion with normal fasting glycaemia; and one altered insulin processing 80 .Considering such evidence, the genetic architecture of T2DM is highly polygenic, and thus, substantially larger association studies are needed to identify most T2DM loci, which typically have small to modest effect sizes 81 ."
            },
            {
                "document_id": "3548bb7f-727c-4ccb-acc7-a97553b89992",
                "section_type": "main",
                "text": "\n\nRecent advances in GWAS have substantially improved our understanding of the pathophysiology of diabetes, but the currently identified genetic susceptibility loci are insufficient to explain differences in diabetes risk across different ethnic groups or the rapid rise in diabetes prevalence over the past several decades.Clinical utility of these loci in predicting future risk of diabetes is also limited."
            },
            {
                "document_id": "183f165e-4d5c-4580-9aff-4e6b2e5a6463",
                "section_type": "abstract",
                "text": "\nWith rapidly increasing prevalence, diabetes has become one of the major causes of mortality worldwide.According to the latest studies, genetic information makes substantial contributions towards the prediction of diabetes risk and individualized antidiabetic treatment.To date, approximately 70 susceptibility genes have been identified as being associated with type 2 diabetes (T2D) at a genome-wide significant level ( < 5×10 −8 ).However, all the genetic loci identified so far account for only about 10% of the overall heritability of T2D.In addition, how these novel susceptibility loci correlate with the pathophysiology of the disease remains largely unknown.This review covers the major genetic studies on the risk of T2D based on ethnicity and briefly discusses the potential mechanisms and clinical utility of the genetic information underlying T2D."
            },
            {
                "document_id": "a49c4251-7a66-44f1-9f95-0d6e8191a2ad",
                "section_type": "main",
                "text": "\n\nThe molecular mechanisms involved in the development of type 2 diabetes are poorly understood.Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia.We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8.Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect.The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes."
            },
            {
                "document_id": "b29b3621-cdb5-4723-b771-8b48546241a5",
                "section_type": "main",
                "text": "\n\nThe molecular mechanisms involved in the development of type 2 diabetes are poorly understood.Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia.We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8.Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect.The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes."
            },
            {
                "document_id": "f3b925cc-2556-4f30-809b-6bfe63a805b8",
                "section_type": "main",
                "text": "\n\nThe molecular mechanisms involved in the development of type 2 diabetes are poorly understood.Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia.We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8.Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect.The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes."
            },
            {
                "document_id": "b00b9753-c198-4f8a-a8b9-dd5e94dc5896",
                "section_type": "main",
                "text": "Conclusions\n\nPharmacogenetics research provides a means to better understand and improve on pharmacotherapy.However, pharmacogenetic studies of T2D therapies lag behind those for other complex diseases, despite the fact that pharmacologic interventions for T2D have been studied extensively at both the clinical and epidemiologic levels.Among the studies that have been conducted, several have identified variants that are potentially associated with differential response to anti-diabetes medications; these preliminary results are promising and warrant investigations in larger, well-designed cohorts to assess their potential roles in optimal drug selection and individualized pharmacotherapy in patients with T2D.At this time, larger, well-powered studies with clearly defined outcomes and utilizing a global approach are needed, as they will not only be more informative than extant candidate gene investigations, but will also be necessary to define the array of genetic variants that may underlie drug response.Such results will likely enable achievement of optimal glucose control, improvement of therapeutic efficacy, and reduction in risk of adverse drug events in at-risk patients, which together will lead to personalized treatment strategies for all individuals with T2D."
            },
            {
                "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                "section_type": "main",
                "text": "Pharmacogenetics in disease progression\n\nOver the recent years, more than 90 susceptibility genes have been identified by genome-wide association studies (GWAS) [55][56][57][58].However, the knowledge of the potential interactions between T2D predisposing genetic variants and the efficacy of treatment of T2D is sparse.Identification of gene-treatment interactions is challenging and requires large sample sizes and sophisticated analytical methods.Furthermore, detailed information on lifestyle and compliance to treatment as well as a long follow-up period are necessary for analysis of pharmacogenomics in T2D."
            },
            {
                "document_id": "ad88aed6-75ba-469d-b96b-7be4a65be8fc",
                "section_type": "main",
                "text": "\n\nGenome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c).At the end of 2011, established loci (P < 5 × 10 −8 ) totaled 55 for T2D and 32 for glycemic traits.Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05]variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations.Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF ≤ 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci.Established published loci now total ∼88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered.Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes."
            },
            {
                "document_id": "15524ac0-da3c-4c01-8ae2-1b8c901105ad",
                "section_type": "abstract",
                "text": "\nThe development of type 2 diabetes (T2DM) is determined by two factors: genetics and environment.The genetic background of T2DM is undoubtedly heterogeneous.Most patients with T2DM exhibit two different defects: the impairment of insulin secretion and decreased insulin sensitivity.This means that there are at least two pathophysiological pathways and at least two groups of genes that may be involved in the pathogenesis of T2DM.As far as genetic bacground of T2DM is concerned, the disease may be divided into two large groups: monogenic and polygenic forms.In this review, we present genes known to cause rare monogenic forms of diabetes with predominant insulin deficiency (MODY -maturity-onset diabetes of the young, MIDD -maternally inherited diabetes with deafness) and uncommon syndromes of severe insulin resistance.We also describe some of the main approaches used to identify genes involved in the more common forms of T2D and the reasons for the lack of spectacular success in this field.Although major genes for T2DM still await to be discovered, we have probably established a \"road map\" that we should follow."
            },
            {
                "document_id": "dcd88798-0248-45e0-8d45-8614c7697266",
                "section_type": "main",
                "text": "\n\ndiabetes (DoD) and poor glycemic control (2).Genetic factors are also implicated, with heritability of 52% for proliferative DR (PDR) (3,4).Several candidate gene and genome-wide association studies (GWAS) have been conducted (5)(6)(7)(8)(9)(10)(11).Although several polymorphisms have been suggested to be associated with DR, few have been convincingly replicated (10,(12)(13)(14)(15).There are several reasons why studies have not yielded consistent findings.The genetic effects are likely modest, and identification requires large sample sizes.Previous studies have not consistently accounted for the strongest two covariates, DoD and glycemic control.Liability threshold (LT) modeling is one way to incorporate these covariates while also increasing statistical power (16).Finally, previous genetic studies have largely examined individual variants.Techniques that examine top GWAS findings collectively for variants that cluster in biological networks based on known protein-protein interactions have the potential to identify variants where there is insufficient power to detect their individual effects."
            },
            {
                "document_id": "516de7be-3cef-47ee-8338-199fb922bc6f",
                "section_type": "main",
                "text": "Genetic Predisposition\n\nThe fact that type 2 diabetes is a genetic disease is well known to clinicians by how it occurs in families, and by there being ethnic populations who are particularly high risk.The genetic link was clearly shown more than two decades ago by a famous study of identical twins in the U.K. that found essentially a 100% concordance rate for this diseaseif one twin developed type 2 diabetes, then the other one invariably developed it (9).However, this kind of study provides no insight into how genetics act in the disease.Is there a defective gene that directly impairs the glucose homeostasis system?Alternatively, does it cause insulin resistance or some other defect that acts indirectly by exceeding the capacity of an otherwise normal glucose homeostasis system to compensate?Also, are there one or many genetic defects that predispose to this disease?"
            },
            {
                "document_id": "2a71b781-89fe-4055-bbb1-15aa226e1e3a",
                "section_type": "main",
                "text": "\n\nDiabetes is a genetically complex multifactorial disease that requires sophisticated consideration of multigenic and phenotypic influences.As well as standard nonpara-  metric methods, we used novel approaches to evaluate and identify locus heterogeneity.It has also proved productive to consider phenotypes such as age at type 2 diabetes onset and obesity, which may define a more homogeneous subgroup of families.A genome-wide scan of 247 African-American families has identified a locus on chromosome 6q and a region of 7p that apparently interacts with early-onset type 2 diabetes and low BMI, as target regions in the search for African-American type 2 diabetes susceptibility genes."
            },
            {
                "document_id": "2a94ec9f-6fb6-4ce3-8e33-1a8859470be9",
                "section_type": "main",
                "text": "\n\nAn individual's risk of developing T2D is influenced by a combination of lifestyle, environmental, and genetic factors.Uncovering the genetic contributors to diabetes holds promise for clinical impact by revealing new therapeutic targets aimed at the molecular and cellular mechanisms that lead to disease.Genome-wide association studies performed during the past decade have uncovered more than 100 regions associated with T2D (5)(6)(7)(8)(9)(10)(11)(12).Although these studies have provided a better understanding of T2D genetics, the majority of identified variants fall outside protein-coding regions, leaving the molecular mechanism by which these variants confer altered disease risk obscure.Consequently, T2D genome-wide association studies have identified few loci with clear therapeutic potential."
            },
            {
                "document_id": "4feda561-1914-404d-9092-3c629d5251bd",
                "section_type": "main",
                "text": "\n\nThe purpose of this review is to summarize current knowledge of pharmacogenetics in T2D and provide a perspective on the relationships between human genetic variants, antidiabetic treatment, and disease progression.This topic is of utmost importance as an improved understanding of gene-treatment interactions may provide a basis for development of future individualized therapies and treatment guidelines."
            },
            {
                "document_id": "183f165e-4d5c-4580-9aff-4e6b2e5a6463",
                "section_type": "main",
                "text": "\n\nWith rapidly increasing prevalence, diabetes has become one of the major causes of mortality worldwide.According to the latest studies, genetic information makes substantial contributions towards the prediction of diabetes risk and individualized antidiabetic treatment.To date, approximately 70 susceptibility genes have been identified as being associated with type 2 diabetes (T2D) at a genome-wide significant level ( < 5×10 −8 ).However, all the genetic loci identified so far account for only about 10% of the overall heritability of T2D.In addition, how these novel susceptibility loci correlate with the pathophysiology of the disease remains largely unknown.This review covers the major genetic studies on the risk of T2D based on ethnicity and briefly discusses the potential mechanisms and clinical utility of the genetic information underlying T2D."
            },
            {
                "document_id": "3e53b34f-5bdf-43d5-9594-736cf83071db",
                "section_type": "main",
                "text": "\n\nTo extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent.We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association.Genomewide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D.Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis."
            },
            {
                "document_id": "a7bad429-5f6a-464f-a666-f9cb1be60338",
                "section_type": "main",
                "text": "DIABETES AND GENETICS\n\nDiabetes is a complex disease that involves a wide range of genetic and environmental factors.Over the past several years, many studies have focused on the elucidation of the wide spectrum of genes that played a role in the molecular mechanism of diabetes development [142][143][144] .However, despite the vast flow of genetic information including the identification of many gene mutations and a large array of single nucleotide polymorphisms (SNPs) in many genes involved in the metabolic pathways that affect blood glucose levels, the exact genetic mechanism of diabetes remains elusive [145,146] .Evidently, a major complication is the fact that a single gene mutation or polymorphism will not impose the same effect among different individuals within a population or different populations.This variation is directly or indirectly affected by the overall genetic background at the individual, family or population levels that are potentially further complicated by interaction with highly variable environmental modifier factors [147,148] ."
            }
        ],
        "document_id": "C4C12C6896F2957844079BC4AFF8FF4B",
        "engine": "gpt-4",
        "first_load": false,
        "focus": "api",
        "keywords": [
            "type&2&diabetes",
            "pharmacogenetics",
            "pharmacogenomics",
            "GWAS",
            "genetic&variants",
            "OCT&genes",
            "KCNJ11",
            "ABCC8",
            "CYP2C9",
            "TCF7L2"
        ],
        "metadata": [
            {
                "object": "The intrinsic clearance Vmax/Km values of all variants, with the exception of CYP2C9*2, CYP2C9*11, CYP2C9*23, CYP2C9*29, CYP2C9*34, CYP2C9*38, CYP2C9*44, CYP2C9*46 and CYP2C9*48, were significantly different from CYP2C9*1. CYP2C9*27, *40, *41, *47, *49, *51, *53, *54, *56 and N418T variant exhibited markedly larger values than CYP2C9*1.",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab827642"
            },
            {
                "object": "genetic association studies in pediatric population in Japan: Data confirm that mutations in KCNJ11 or ABCC8 are associated with neonatal diabetes mellitus. Novel mutations were identified; 2 in KCNJ11 V64M, R201G and 6 in ABCC8 R216C, G832C, F1176L, A1263V, I196N, T229N. KCNJ11 = ATP-sensitive inward rectifier potassium channel-11; ABCC8 = ATP-binding cassette subfamily C member-8",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab316321"
            },
            {
                "object": "rs2059806 of INSR was associated with both type 2 diabetes mellitus and type 2 diabetic nephropathy, while rs7212142 of mTOR was associated with type 2 diabetic nephropathy but not type 2 diabetes mellitus in a Chinese Han population.",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab687817"
            },
            {
                "object": "genetic association studies in population in Scotland: data suggest, in type 2 diabetes treated with sulfonylureas, 2 SNPs in CYP2C9 CYP2C9*2, R144C, rs1799853; CYP2C9*3, I359L, rs1057910 are associated with drug-induced hypoglycemia; an SNP in POR POR*28, A503V, rs1057868 is associated with better response to sulfonylureas. CYP2C9 = cytochrome P450 family 2 subfamily C member 9; POR = cytochrome p450 oxidoreductase",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab316392"
            },
            {
                "object": "Novel mutations were detected in ABCC8 and KCNJ11 gene in Chinese patients with congenital hyperinsulinism CHI. Hotspot mutations such as T1042Qfs*75, I1511K, E501K, G111R in ABCC8 gene, and R34H in KCNJ11 gene are predominantly responsible for Chinese CHI patients.",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab535847"
            },
            {
                "object": "he aim of this study was to ascertain the polymorphic markers profile of ADIPOQ, KCNJ11 and TCF7L2 genes in Kyrgyz population and to analyze the association of polymorphic markers and combinations of ADIPOQ gene's G276T locus, KCNJ11 gene's Glu23Lys locus and TCF7L2 gene's VS3C>T locus with type two diabetes T2D in Kyrgyz population",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab334669"
            },
            {
                "object": "genetic variants in TCF7L2 confer a strong risk of future type 2 diabetes possibly mediated by altering expression of TCF7L2 in pancreatic islets [review]",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab318653"
            },
            {
                "object": "Considering that CYP2C9*2 and CYP2C9*3 alleles have altered catalytic activities relative to CYP2C9*1, the present data suggest the need for pharmacogenetic studies to optimize drug dosages in different populations.",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab155248"
            },
            {
                "object": "The association of variants in IRS1 with type 2 diabetes and type 2 diabetes-related phenotypes and the differential expression of IRS1 in adipocytes and skeletal muscle suggest a role of this gene in the pathogenesis of type 2 diabetes in Pima Indians.",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab782328"
            },
            {
                "object": "trend for augmented exercise-induced IL6 release in type 2 diabetics; results also suggest that neither type 2 diabetic nor healthy skeletal muscle releases IL6 at rest,indicating that other organs contribute to elevated basal IL6 in type 2 diabetics",
                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
                "subject": "ndd791caee50643ad90a986f563d2a0dab971647"
            }
        ],
        "question": "What are the genetic bases for the varying efficacy of diabetes treatments among individuals?",
        "subquestions": null,
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