{
  "question": [
    "What genes are most commonly associated with an increased risk of developing diabetes?",
    "How can genetic testing help predict a person's risk for diabetes?",
    "What role do family genetics play in the likelihood of getting diabetes?",
    "Can lifestyle changes affect genetic risk factors for diabetes?",
    "What recent breakthroughs have been made in understanding the genetic causes of diabetes?"
  ],
  "answer": [
    "The genes most commonly associated with an increased risk of developing diabetes include TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX.",
    "Genetic testing can help predict a person's risk for diabetes by identifying specific genetic variants or risk alleles associated with the disease. These genetic markers, when combined into a polygenic score, can provide information on individual patterns of disease predisposition. This can be particularly useful if measured early in life, as it can enable early interventions for preventing diabetes. However, the predictive value of these genetic factors is currently considered to be small compared to traditional risk factors like obesity and fasting glucose levels.",
    "Family genetics play a significant role in the likelihood of getting diabetes. Studies have shown that siblings of individuals with diabetes have a significantly higher risk of developing the disease compared to the general population. Genetic factors account for a substantial fraction of susceptibility to type 1 diabetes. In type 2 diabetes, the risk is higher if one or both parents have the disease. However, the presence of certain genetic factors does not guarantee the development of diabetes, as environmental factors also play a significant role.",
    "Yes, lifestyle changes can affect genetic risk factors for diabetes. Studies suggest that a healthy lifestyle or lifestyle modification can partially or totally control genetic predisposition to obesity and Type 2 Diabetes Mellitus (T2DM). However, the effectiveness of these changes can vary among individuals due to genetic influences.",
    "Recent breakthroughs in understanding the genetic causes of diabetes include the identification of many genes that predispose to both major types of diabetes, thanks to advances in genetics. Genome-wide association studies have been particularly effective in uncovering genetic determinants of complex diseases like diabetes. More recent approaches have used genotyping arrays of more densely spaced markers, imputation of ungenotyped variants based on improved reference haplotype panels, and sequencing of protein-coding exomes and whole genomes. These methods have led to the identification of novel variants and loci contributing to trait variation and disease risk."
  ],
  "contexts": [
    [
      "\t\n\nIn the past 10 years, geneticists have devoted a large amount of effort to finding type 2 diabetes genes.These efforts have included many candidate-gene studies, extensive efforts to fine map linkage signals 3 , and an international linkage consortium that was perhaps the best example of a multi-centre collaboration in common-disease genetics.Of these efforts, only the candidate-gene studies produced unequivocal evidence for common variants involved in type 2 diabetes.These are the E23K variant in the potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) gene [4][5][6] , the P12A variant in the peroxisome proliferatoractivated receptor- (PPARG) gene 7 , and common variation in the transcription factor 2, hepatic (TCF2) 8,9 and the Wolfram syndrome 1 (WFS1) 10 genes.All of these genes encode proteins that have strong biological links to diabetes.Rare, severe mutations in all four cause monogenic forms of diabetes [11][12][13][14] , and two are targets of anti-diabetic therapies: KCNJ11 encodes a component of a potassium channel with a Genome-wide association studies provide new insights into type 2 diabetes aetiology Timothy M. Frayling Abstract | Human geneticists are currently in the middle of a race.Thanks to a new technology in the form of 'genome-wide chips', investigators can potentially find many novel disease genes in one large experiment.Type 2 diabetes has been hot out of the blocks with six recent publications that together provide convincing evidence for six new gene regions involved in the condition.Together with candidate approaches, these studies have identified 11 confirmed genomic regions that alter the risk of type 2 diabetes in the European population.One of these regions, the fat mass and obesity associated gene (FTO), represents by far the best example of an association between common variation and fat mass in the general population.key role in -cell physiology that is a target for the sulphonylurea class of drugs, and PPARG encodes a transcription factor involved in adipocyte differentiation that is a target for the thiazolodinedione class of drugs.\tSix new gene regions identified\n\nTogether, the six recent GWAS papers provide convincing evidence for six new gene regions involved in type 2 diabetes [16][17][18][19][20][21] ; a seventh publication describes how one of these variants alters BMI and represents by far the best example of an association between common genetic variation and obesity 22 .There are now 11 gene regions in which common variation alters type 2 diabetes risk with the levels of statistical confidence that are required by genetic association studies (FIGS 2,3).This progress is all the more remarkable in view of the weak genetic component to type 2 diabetes risk, as compared with many other common diseases that are currently being studied using GWAS.The sibling relative risk is 3-4 at the most for type 2 diabetes, in contrast with 5-10 for rheumatoid arthritis, 15 for type 1 diabetes, 7-10 for bipolar disorder, 17-35 for Crohn disease, 2-7 for early myocardial infarction and 2.5-3.5 for hypertension 21 .",
      "\t\n\nGenes whose variants are commonly associated with both type 2 diabetes mellitus and cardiovascular disease.",
      "\tGenomic Analyses for Diabetes Risk\n\nGenes signifying increased risk for both type 1 and type 2 diabetes 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 suggested 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. 12Also, several candidate genes for increased risk of developing type 2 diabetes have been identified, including peroxisome proliferatoractivated receptor gamma (PPAR2), angiotensin converting enzyme (ACE), methylene tetrahydrofolate reductase (MTHR), fatty acid binding protein-2 (FABP2), and fat mass and obesity associated gene (FTO). 13he conclusions of a \"Workshop on Metformin Pharmacogenomics,\" sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases, were published in 2014. 14The meeting was intended to review metformin pharmacogenomics and identify both novel targets and more effective agents for diabetes.The idea behind the meeting was that understanding the genes and pathways that determine the response to metformin has the potential to reveal new drug targets for the treatment of diabetes.The group noted that there have been few genes associated with glycemic control by metformin, and the most reproducible associations have been in metformin transporter genes.They acknowledged that nongenetic factors also contribute to response to metformin and that broader system biology approaches will be required to model the combined effects of multiple gene variants and their interaction with nongenetic factors.They concluded that the overall challenge to the field of precision medicine as it relates to antidiabetes treatment is to identify the individualized factors that can lead to improved glycemic control.",
      "\tIntroduction\n\nIt is well recognized that type II diabetes mellitus has a substantial genetic component (Barnett et al. 1981;Knowler et al. 1981;Hanson et al. 1995a).Genes that predispose to some types of diabetes have been identi-fied; these include several loci for type I diabetes (Davies et al. 1994) and for maturity-onset diabetes of the young (Froguel et al. 1992;Yamagata et al. 1996aYamagata et al. , 1996b;;Stoffers et al. 1997).However, the genes that cause the most common forms of diabetes remain unknown, and it is, therefore, likely that additional important diabetessusceptibility loci remain to be identified.Moreover, the specific risk factors through which such genes influence the development of type II diabetes are also unknown.Obesity, as quantified by body-mass index (BMI) (kg/ m 2 ), is a strong risk factor for type II diabetes (Knowler et al. 1981) and is also likely to have genetic determinants (Price et al. 1994).The present study represents a genomewide search for loci linked to diabetes and BMI in Pima Indians, a Native American population with a high prevalence of type II diabetes and obesity (Bennett et al. 1971;Knowler et al. 1978Knowler et al. , 1991)).",
      "\tGENETIC SUSCEPTIBILITY AND GENE-ENVIRONMENT INTERACTIONS-\n\nThe recent advent of genome-wide association studies (GWAS) has led to major advances in the identification of common genetic variants contributing to diabetes susceptibility (40).To date, at least 40 genetic loci have been convincingly associated with type 2 diabetes, but these loci confer only a modest effect size and do not add to the clinical prediction of diabetes beyond traditional risk factors, such as obesity, physical inactivity, unhealthy diet, and family history of diabetes.Many diabetes genes recently discovered through GWAS in Caucasian populations have been replicated in Asians; however, there were significant interethnic differences in the location and frequency of these risk alleles.For example, common variants of the TCF7L2 gene that are significantly associated with diabetes risk are present in 20-30% of Caucasian populations but only 3-5% of Asians (41,42).Conversely, a variant in the KCNQ1 gene associated with a 20-30% increased risk of diabetes in several Asian populations (43,44) is common in East Asians, but rare in Caucasians.It is intriguing that most diabetes susceptibility loci that have been identified are related to impaired b-cell function, whereas only a few (e.g., peroxisome proliferator-activated receptor-g, insulin receptor substrate 1, IGF-1, and GCKR) are associated with insulin resistance or fasting insulin, which points toward b-cell dysfunction as a primary defect for diabetes pathogenesis.It should be noted that most of the single nucleotide polymorphisms uncovered may not be the actual causal variants, which need to be pinpointed through fine-mapping, sequencing, and functional studies.",
      "\t\n\nInitial linkage studies in affected families indentified CAPN10 and TCF7L2 as risk-conferring genes in T2D [27].Association studies using candidate gene approach identified additional risk genes -PPARG and KCNJ11 (the targets of many current diabetes medications), IRS1, WFS1, HNF1A, HNF1B and HNF4A, among others [28].The more recent GWAS have added a plethora of genetic risk variants, but with small indifuture science group Genetics, genomics & personalized medicine in Type 2 diabetes: a perspective on the Arab region Review vidual effect size.To date, GWAS for T2D have identified over 50 genetic risk variants, but their causal relationship in the etiology of the disease remains elusive.However, it is important to note that most loci harboring disease-causing variants have been found to be associated with defective functioning of the -cells of the pancreatic islets, thus implicating this pathway as a major factor in the pathology of T2D [29].So far, the strongest association signal for T2D has been found for the TCF7L2 gene, which has been replicated across GWAS of different ethnic groups.Other important genes which have been replicated across GWAS of different populations include HHEX, SLC30A8, CDKN2A/B, IGF2BP2, HMGA2, KCNQ11 and NOTCH2-ADAM30 [28].",
      "\t\n\nGenetic determinants of diabetes and metabolic syndromes.",
      "\t\n\nAmong type 2 diabetes susceptibility genes few, if any, individual loci are expected to carry alleles of major effect explaining a substantial proportion of cases, although a few genes could have a substantial population effect but not give a strong genetic signal if the causal alleles were common and the increase in risk were modest [6,7].Such genes have proven hard to detect using linkage-based approaches, although recent rapid advances in genetic association methodologies have led to some successes.The P12A polymorphism in the gene encoding the peroxisome proliferator-activated receptor-g (PPARG) [7], the E23K polymorphism in the gene encoding the islet ATPdependent potassium channel Kir6.2 (ABCC8-KCNJ11) [8][9][10] and common variants in the gene encoding the transcription factor 7-like 2 gene (TCF7L2) [11,12] were all found using well-powered association mapping, and all have been reproducibly associated with diabetes in diverse samples at highly significant p-values.",
      "\t\n\nIn support of our focus on developmental genes, pathway analysis of recent genome-wide association studies, which so far have yielded few T2D candidate genes, provided an integrated interpretation of the highest ranked risk genes for T2D [97].This analysis found that lipid metabolism and developmental genes were significantly over-represented in the upper ranked genes of the T2D genome-wide association studies, an observation based on thousands of samples, and one strongly consistent with the present independent analysis.Combined, we believe this presents strong evidence that developmental genes may play a role in setting or regulating the long-term responses of skeletal muscle to diabetes.",
      "\tResults\n\nStrong predictors of diabetes were a family history of the disease, an increased body-mass index, elevated liver-enzyme levels, current smoking status, and reduced measures of insulin secretion and action.Variants in 11 genes (TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX) were significantly associated with the risk of type 2 diabetes independently of clinical risk factors; variants in 8 of these genes were associated with impaired beta-cell function.",
      "\t\n\nRecently, spectacular advance was made in identifying susceptible genes involved in T2D through genome-wide association strategy (GWAS) [10,11].Consequently, a number of novel genetic variants (PPARG, KCNJ11, IGF2BP2, KCNQ1, TCF7L2, CDKAL1, and MTNR1B) were shown to increase the risk of T2D in reproducible studies.Therefore, several studies have examined the association of these newly identified loci using a candidate gene approach for GDM.It has been reported that the pathophysiological changes of GDM are similar to those observed in T2D, which is characterized by peripheral insulin resistance accompanied by an insulin secretory defect [12,13].Functional studies showed that these new diabetogenic genes took part in many steps of the process, for instance, impaired b-cell function (CDKAL1, IGF2BP2, KCNQ1, KCNJ11, MTNR1B), insulin resistance (PPARG, TCF7L2), and abnormal utilization of glucose (GCK) [14][15][16][17][18][19][20][21][22][23].",
      "\t\n\nGenome-wide association studies (GWAS) have discovered germline genetic variation associated with type 2 diabetes risk (1)(2)(3)(4).One of the largest GWAS, involving DNA taken from individuals of European descent and conducted by the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) consortium, identified 65 loci associated with type 2 diabetes risk (1).However, for most of these loci, the precise identity of the affected gene and the molecular mechanisms underpinning the altered risk are not known.",
      "\t\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",
      "\t\n\nNearly all of the recent discoveries have used genome wide association study (GWAS) techniques to identify single nucleotide polymorphisms (SNPs) that exist at higher frequency in DNA from people with established T2DM (''cases'') than in non-diabetic individuals (''controls'').Where the physiological roles of these variants have so far been determined, the majority encode proteins linked with the b-cell.For example, of 19 validated T2DM genes, 14 have been shown to influence glucose or incretin stimulated insulin secretion (reviewed in [6]).In addition, these variants have relatively large effects on diabetes risk compared with other variants, with the seven variants with the greatest association with diabetes risk (TCF7L2, CDKAL1, HHEX, CDKNA/2B, IGF2BP2, SLC30A8, JAZF1) all affecting b-cell insulin secretion.The rapid rise in prevalence of type 2 diabetes mellitus (T2DM) has been driven by changes in environmental factors -primarily increased caloric intake and reduced energy expenditure -resulting in reduced whole body insulin sensitivity (often termed insulin resistance).Insulin resistance has been proposed to be a major driver of progression to T2DM.However, of 38 individual susceptibility loci for T2DM recently identified by genome wide association studies, by far the majority code for proteins involved in b-cell function.In this review, we discuss the possible reasons for the paucity of insulin resistance genes and ask whether the new genetic susceptibility data should focus attention on b-cell targets in the development of therapies for T2DM.",
      "\t\n\nMore than 65 loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D).Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notably TCF7L2 and ZnT8/SLC30A8, have to date been examined in mouse models.We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics.\t\nMore than 65 loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D).Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notably TCF7L2 and ZnT8/SLC30A8, have to date been examined in mouse models.We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics.",
      "\t\n\nGenomic information associated with Type 2 diabetes.",
      "\tBackground\n\nMultiple genetic loci have been convincingly associated with the risk of type 2 diabetes mellitus.We tested the hypothesis that knowledge of these loci allows better prediction of risk than knowledge of common phenotypic risk factors alone.",
      "\t\n\nAs 80% of type 2 diabetes patients are obese, a further research focus is the identification of genes encoding 'diabesity', predisposing the carrier to both pathological conditions.Philippe Froguel (Lille, France) found in a French population with a BMI of 40, as well in Germans with early onset obesity, a linkage with markers on chromosome 2p, 8 and around D10S1781.Leptin gene polymorphisms on chromosome 7 were only associated with blood leptin levels and diet success in the extremely obese.Stephen Rich (Winston-Salem, NC) showed how quantitative trait linkage (QTL) can greatly increase the accuracy of genetic studies.Rich found a clustering for type 2 diabetes candidate genes in families with diabetic nephropathy (Caucasians s 52.7 and African Americans s 58.1) as well as a correlation with arterial-wall width.Takashi Kadowaki (Tokyo, Japan) illustrated the important role of animal models in the understanding of diabetes.Using glucokinase-, IRS2-and PPAR-knockout mice, he was able to measure the effect of different dietary fats on insulin resistance, -cell hyperplasia, overt diabetes and arterial hypertension."
    ],
    [
      "\t\n\nResearchers are expanding our understanding of genetic risk factors for diabetes through ongoing discoveries.Genetic variants associated with increased susceptibility to type 2 diabetes, a disease that affects more than 200 million people worldwide, have been identified (NHGRI & NIDDK, 2007).Such discoveries accelerate efforts to understand genetic contributions to chronic illness, as well as facilitate greater investigation of how these genetic factors interact with each other and with lifestyle factors.Ultimately, once the association of these variants with diabetes are confirmed, genetic tests may be utilized to identify (even before escalating blood sugars) those individuals, like Vanessa, who may be able to delay or prevent diabetes with healthy lifestyle decisions and behaviors.Information to assist nurses in this challenge is available in a toolkit \"Your Game Plan for Preventing Type 2 Diabetes\" (Your Game Plan, n.d.).Would you have known whether or not genetic testing was available for Vanessa?If you had said no to this question but could have explained the progress currently being made in understanding diabetes, Vanessa would have had access to the best care possible today.",
      "\t\n\nProgress toward wider use of genetic testing in the prediction of type 2 diabetes and its complications will require three developments.The first involves identification of a growing number of risk variants that, collectively, deliver greater predictive and discriminative performance than the subset thus far known.The second involves understanding how genetic information can be combined with other conventional risk factors (and possibly with non-DNA-based biomarkers, as these emerge) to provide a more accurate assessment of individual risk.It should be kept in mind that susceptibility genotype information will not be orthogonal to those traditional factors, since several of them (such as ethnicity, family history, and BMI) capture overlapping genetic information.The third development will be evidence that imparting such information results in clinically meaningful differences in individual behavior or provides a more rational basis for therapeutic or preventative interventions.\t\n\nOf course, individual small effects can amount to more when considered collectively, and it is true that genetic testing (for the 17 known genes, for example) can identify subsets of individuals who have inherited particularly high or low numbers of risk alleles and therefore have marked differences in individual risk (87).However, the numbers of individuals in these \"extreme\" high-and low-risk groups are comparatively small, and for many, their risk will already be obvious through conventional factors (family history, BMI, and previous gestational diabetes, for example).When the information from the known type 2 diabetes-susceptibility variants is examined using approaches such as receiver-operating curve analysis, which are better suited for evaluating the performance of diagnostic tests at the population level, the results look far less spectacular (72,87).",
      "\tClinical Utility of Genetic Information: Prediction of Type 2 Diabetes\n\nOne of most important clinical utilities of genetic information is to predict the risk of developing T2D among nondiabetic individuals.This will facilitate the early interventional strategies to prevent or delay the onset of the disease.A vast number of recent studies have constructed genetic risk score models by summing up numerous independently inherited susceptible variants for T2D to evaluate the predictive ability from the current genetic information.For example, the area under the receiver operating characteristic (ROC) curves (AUCs) is used to assess discriminative accuracy of this approach.The AUC value can range from 0.5 to 1.0, where the AUC of 0.5 stands for the lack of discrimination and AUC of 1 stands for perfect discrimination.An AUC value of greater than 0.75 is considered to be clinically useful [140].\t\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 ( < 510 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.",
      "\tGENOMICS IN THE PREDICTION, PREVENTION, AND DIAGNOSIS OF DIABETES\n\nThe incidence and prevalence of diabetes have doubled over the past two decades (13), and there are now about 30 million adults in the U.S. living with this condition, 95% of whom have type 2 diabetes (14).Genome-wide association (GWA) studies test hundreds of thousands or even millions of common (minor allele frequency [MAF] .5%)and lowfrequency (MAF 1-5%) variants across both protein coding (exonic) and noncoding (intronic) regions of the genome.Large GWA studies have identified more than 50 genetic loci associated with various glycemic traits and at least 90 loci associated with type 2 diabetes (15)(16)(17)(18).These genetic variants, which may explain as much as 10% of the variance in disease susceptibility, have advanced our understanding of the biology of diabetes, but each genetic locus confers only a small increase in risk.For example, the common variant from these GWA studies most strongly associated with type 2 diabetes, an intronic variant in TCF7L2 (rs7903146), is associated with a 37% increased relative risk per copy of the variant allele (19).Rare variants (MAF ,1%) and variants that are common only in specific ancestral populations have been associated with a greater increase in diabetes risk, but they account for less of the overall burden of diabetes (20)(21)(22).",
      "\t\n\nThe promise of genetic risk scoring for diabetes can be evaluated in the framework of three perspectives.First is the potential for robust prediction of diabetes risk.Second is the prospect of designing targeted preventive and therapeutic interventions (personalized medicine).Thirdly, increased knowledge could provide genomic clues to ethnic disparities in diabetes.Regarding robustness of prediction, results from the Framingham Offspring Study showed that clinical risk assessment (using age, sex, family history, BMI, fasting glucose level, systolic blood pressure, high-density lipoprotein cholesterol level, and triglyceride level) performed as well as cumulative genotype score at 18 loci in predicting incident type 2 diabetes during 28 years of follow-up of initially normoglycemic subjects (14).Also, cumulative genotype score at 34 loci did not add significantly to clinical risk factors in predicting progression from impaired glucose tolerance to type 2 diabetes among the multiethnic cohort enrolled in the Diabetes Prevention Program (15).One current limitation is the incomplete framework from which GRS is constructed.For example, the 17 SNPs studied in the present report (17) represent just about half of the .30diabe-toSNPs identified to date.Even the latter do not represent all possible risk loci, and important information on structural variants that might increase diabetes risk is often lacking.Thus, current experience renders the promise of robust genetic prediction and personalized diabetes intervention a distant hope.",
      "\t\n\nRegardless, one expects many of the important susceptibility genes for type 2 diabetes will be uncovered in the next 10 years.Once that occurs, intense effort will be focused on developing targeted therapies.Also, medical care will shift to genetic testing of persons with type 2 diabetes, followed by giving them the most effective proven therapy for that genetic form of the disease.Also, their family members will undergo genetic testing while still normally glucose tolerant to determine if they carry a genetic predisposition.If so, specific treatment plans will be developed for prevention of the disease, again based on proven efficacy for each genetic defect.",
      "\t\n\nTwo more recent population -based studies using a longitudinal design with prospectively investigated cohorts have examined the predictive value of a genotype score in addition to common risk factors for prediction of T2DM [194,195] .Meigs et al. [194] reported that a genotype score based on 18 risk alleles predicted new cases of diabetes in the community but provided only a slightly better prediction of risk than knowledge of common clinical risk factors alone [195] .A similar conclusion was drawn in the paper by Lyssenko et al. [196] , along with an improved value of genetic factors with an increasing duration of follow -up, suggesting that assessment of genetic risk factors is clinically more meaningful the earlier in life they are measured.They also showed that  -cell function adjusted for insulin resistance (using the disposition index) was the strongest predictor of future diabetes, although subjects in the prediabetic stage presented with many features of insulin resistance.It is also noteworthy that many of the variants that were genotyped appear to infl uence  -cell function.The addition of DNA data to the clinical model improved not only the discriminatory power, but also the reclassifi cation of the subjects into different risk strategies.Identifying subgroups of the population at substantially different risk of disease is important to target these subgroups of individuals with more effective preventative measures.As more genetic variants are now identifi ed, tests with better predictive performance should become available with a valuable addition to clinical practice.",
      "\t\n\nPredicting T2DM in healthy individuals has been attempted using a diabetes risk score that is derived from common clinical information, such as adiposity, blood pressure, and family history of T2DM.However, using the risk score is inevitably limited in predicting T2DM because T2DM has a strong genetic basis; concordance of T2DM is about 70% for monozygotic twins, compared to about 20-30% for dizygotic twins. 2 Limitations in predicting T2DM have driven researchers to employ genetic risk assessments.Moreover, unlike clinical markers, genetic markers do not change with time, so they possess the advantage of identifying high-risk individuals long before disease onset, which could enable early interventions for preventing T2DM.Conventionally, family-based linkage studies have played an important role in identifying genes having a large effect in monogenic disorders, such as maturity-onset diabetes of the young. 3However, linkage studies have low power for polygenic diseases that are influenced by multiple genes, as is the case with the majority of those with T2DM.Therefore, using monogenic mutations would have very limited value for predicting risk of disease in the general population because of their low frequency.",
      "\tDiscussion\n\nOur study provides insight into the relative importance of clinical risk factors and those that are related to a panel of DNA variants associated with type 2 diabetes.Obesity was a strong risk factor for future diabetes, a risk that almost doubled in subjects with a family history of diabetes.However, the addition of data from genotyping of the known DNA variants to clinical risk factors (including a family history of diabetes) had a minimal, albeit statistically significant, effect on the prediction of future type 2 diabetes.Notably, the ability of genetic risk factors to predict future type 2 diabetes improved with an increasing duration of follow-up, suggesting that assessment of genetic risk factors is clinically more meaningful the earlier in life they are measured.\t\n\nIn conclusion, the inclusion of common genetic variants that are associated with type 2 diabetes very slightly improved the prediction of future type 2 diabetes, as compared with the inclusion of clinical risk factors alone.Although this effect might be too small to allow for individual risk prediction, it could be useful in reducing the number of subjects who would need to be included in intervention studies aimed at the prevention of type 2 diabetes.Supported by grants from the Swedish Research Council (including Linn grant 31475113580), the Heart and Lung Foundation, the Swedish Diabetes Research Society, a Nordic Center of Excellence Grant in Disease Genetics, the Diabetes Program at the Lund University, the Finnish Diabetes Research Society, the Sigrid Juselius Foundation, the Phlsson Foundation, the Crafoord Foundation, the Folkhlsan Research Foundation, the Novo Nordisk Foundation, the European Network of Genomic and Genetic Epidemiology, the Wallenberg Foundation, and the European Foundation for the Study of Diabetes.\t\nA bs tr ac t\nBackgroundType 2 diabetes mellitus is thought to develop from an interaction between environmental and genetic factors.We examined whether clinical or genetic factors or both could predict progression to diabetes in two prospective cohorts. MethodsWe genotyped 16 single-nucleotide polymorphisms (SNPs) and examined clinical factors in 16,061 Swedish and 2770 Finnish subjects.Type 2 diabetes developed in 2201 (11.7%) of these subjects during a median follow-up period of 23.5 years.We also studied the effect of genetic variants on changes in insulin secretion and action over time. ResultsStrong predictors of diabetes were a family history of the disease, an increased body-mass index, elevated liver-enzyme levels, current smoking status, and reduced measures of insulin secretion and action.Variants in 11 genes (TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX) were significantly associated with the risk of type 2 diabetes independently of clinical risk factors; variants in 8 of these genes were associated with impaired beta-cell function.The addition of specific genetic information to clinical factors slightly improved the prediction of future diabetes, with a slight increase in the area under the receiveroperating-characteristic curve from 0.74 to 0.75; however, the magnitude of the increase was significant (P = 1.010 4 ).The discriminative power of genetic risk factors improved with an increasing duration of follow-up, whereas that of clinical risk factors decreased. ConclusionsAs compared with clinical risk factors alone, common genetic variants associated with the risk of diabetes had a small effect on the ability to predict the future development of type 2 diabetes.The value of genetic factors increased with an increasing duration of follow-up.",
      "\t\n\nGenetic variants can also identify patients at higher risk, predict rates of C-peptide decline, and predict response to various therapies (41).With a better understanding of inheritance profiles, it may become possible to realize new targets for individualized intervention.",
      "\t\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",
      "\t\nDuring the last decade, there have been substantial advances in the identification and characterization of DNA sequence variants associated with individual predisposition to type 1 and type 2 diabetes.As well as providing insights into the molecular, cellular, and physiological mechanisms involved in disease pathogenesis, these risk variants, when combined into a polygenic score, capture information on individual patterns of disease predisposition that have the potential to influence clinical management.In this review, we describe the various opportunities that polygenic scores provide: to predict diabetes risk, to support differential diagnosis, and to understand phenotypic and clinical heterogeneity.We also describe the challenges that will need to be overcome if this potential is to be fully realized.\t\n\nDuring the last decade, there have been substantial advances in the identification and characterization of DNA sequence variants associated with individual predisposition to type 1 and type 2 diabetes.As well as providing insights into the molecular, cellular, and physiological mechanisms involved in disease pathogenesis, these risk variants, when combined into a polygenic score, capture information on individual patterns of disease predisposition that have the potential to influence clinical management.In this review, we describe the various opportunities that polygenic scores provide: to predict diabetes risk, to support differential diagnosis, and to understand phenotypic and clinical heterogeneity.We also describe the challenges that will need to be overcome if this potential is to be fully realized.",
      "\t\n\nTwo trials in the field of T2D have assessed weight change in response to genetic testing.In the Genetic Counseling and Lifestyle Change for Diabetes Prevention Study (107), 177 patients with metabolic syndrome were randomized to receive genetic testing for T2D susceptibility based on 36 T2D-associated SNPs plus brief genetic counseling versus no genetic testing.Diabetes risk for genotyped  participants was summarized with a risk score categorizing their genetic risk as low, average, high.All patients were then enrolled in a 12-week lifestyle medication program modeled on the evidencebased DPP (108).The lifestyle intervention was effective: the group overall lost a mean of 8.5 6 10.1 pounds, with 31% losing at least 5% of their body weight.Communicating genetic risk did not change this effectiveness, however.The genotyped and control arms did not differ with respect to weight loss, attendance at the 12 DPP sessions, or motivation or confidence to make health behavior changes (107).In a second randomized trial, 601 patients with obesity or overweight received T2D risk estimates based on family history, BMI, and fasting plasma glucose, followed by either T2D genetic susceptibility results from four T2D-associated SNPs or eye disease counseling as a control (109).All participants received brief lifestyle counseling but were not otherwise enrolled in a weight loss program.Although the group receiving genetic risk information reported lower calorie and fat intake after 3 months, the two groups did not differ in these behaviors or in physical activity, weight loss, insulin resistance, or perceived risk after 6 months.",
      "\t\n\nConclusions and Future Directions GWAS and GWAS meta-analyses have by far been the most efficient way to identify new T2D genes (Figure 2), but their predictive value for future occurrence of T2D has been very limited compared to classic risk factors such as obesity and fasting glucose levels (Walford et al., 2014).Although it might be good news that our genome does not fully dictate our future, the knowledge of its specificities may help us to improve our health.Early genetic studies showed that the higher risk for T2D conferred by TCF7L2 variant can be reversed by lifestyle intervention (Florez et al., 2006), opening avenues for strategies targeted on genetically selected individuals with pre-diabetes.TCF7L2 has also been shown to be associated with a lower efficiency of oral sulfonylureas in newly diagnosed T2D patients (Pearson et al., 2007), but a more recent Danish study suggested that in contrast to clinical markers, all known T2D-associated variants do not significantly affect the time to prescription of the first drug after disease onset (Hornbak et al., 2014).In other words, frequent SNPs are not helpful to predict patients' futures, though the good use of genetic data may contribute to provide better care to newly diagnosed T2D patients who are currently all treated the same (with metformin).",
      "\tBackground\n\nMultiple genetic loci have been convincingly associated with the risk of type 2 diabetes mellitus.We tested the hypothesis that knowledge of these loci allows better prediction of risk than knowledge of common phenotypic risk factors alone."
    ],
    [
      "\tA. Genetic Screening\n\nWe have discussed above the genetic component of T1D.The genetic susceptibility to T1D is determined by genes related to immune function with the potential exception of the insulin gene (434).The genetic susceptibility component of T1D allows some targeting of primary preventive care to family members of diagnosed T1D patients, but there is no complete inheritance of the disease.Nevertheless, the risk for developing T1D compared with people with no family history is 10 -15 times greater.Although 70% of individuals with T1D carry defined risk-associated genotypes at the HLA locus, only 3-7% of the carriers of such genetic risk markers develop diabetes (3).",
      "\tGenes\n\n2][43][44][45][46][47] Twin studies need to be considered carefully, however, as the intrauterine environments of dizygotic-twin (separate placentas), monozygotic-twin (60-70% share one placenta), and singleton pregnancies (one placenta without competition for maternal nutrients) will all be diff erent, and this can be a confounder in the inter pretation of eff ects. 44A large study from Sweden on familial risk of type 2 diabetes showed that the relative risks were highest in individuals with at least two aff ected siblings, irrespective of parental diabetes status. 42This fi nding suggests that a recessive pattern of inheritance from uncommon genetic defects, the sharing of similar intrauterine, postnatal, or both environments by siblings (eg, breastfeeding or bottle feeding or childhood nutrition), or a combination of these factors is important.9][50] A greater number of these loci are associated with impaired -cell function (KCNJ11, TCF7L2, WFS1, HNF1B, SLC30A8, CDKAL1, IGF2BP2, CDKN2A, CDKN2B, NOTCH2, CAMK1D, THADA, KCNQ1, MTNR1B, GCKR, GCK, PROX1, SLC2A2, G6PC2, GLIS3, ADRA2A, and GIPR) than impaired insulin sensitivity (PPARG, IRS1, IGF1, FTO, and KLF14) or obesity (FTO). 38,48,50Of these, TCF7L2 is the strongest susceptibility locus for type 2 diabetes, being associated with -cell dysfunction. 48Most patients with monogenic forms of diabetes also have gene defects that aff ect islet -cell function. 51,52Nevertheless, only around 10% of the heritability of type 2 diabetes can be explained by susceptibility loci identifi ed so far, with each locus having a low eff ect size. 36The remaining heritability might be related to a large number of less common variants (allele frequency <5%) that are diffi cult to fi nd with current approaches of genome-wide association studies, and/or epigenetic phenomena.",
      "\t\n\nObserved increased risk in African Americans is likely to result from a combination of shared environmental and genetic factors.Although there are few published studies specifically investigating familial aggregation of type 2 diabetes in African-American families, Rotimi et al. (10) found that relatives of African-American probands with type 2 diabetes had a 2.95-fold (95% CI 1.55-5.62)higher prevalence of diabetes when compared with relatives of unaffected individuals.In the GENNID (Genetics of Noninsulin Dependent Diabetes Mellitus) African-American families, the majority of first-degree relatives of African-American individuals with type 2 diabetes had abnormal glucose tolerance (11), with 27% found to have undiagnosed diabetes and 31% impaired fasting glucose and/or impaired glucose tolerance.",
      "\t\n\nmore frequently than by chance alone among siblings who share the phenotype of type 1 diabetes.Nuclear families, or even just the affected sibling pairs themselves, are genotyped with panels of markers spanning the genome at a modest density.Linkage between a marker and a susceptibility locus for type 1 diabetes is determined by accumulating evidence across families.Since affected sibling pairs are relatively rare in type 1 diabetes, data from linkage studies are collected from a rather unique subgroup of families with type 1 diabetes.In general, linkage studies are the method of choice when the risk factors being sought have large effect sizes but are relatively rare.As risk factors become more common and have smaller effect sizes, association methods emerge as a potentially more powerful approach (Fig. 1).Since the genetic basis of type 1 diabetes is probably a complex mixture of small, moderate, and large genetic effects, multiple strategies are needed and vary according to the population being studied and their exposure to unknown environmental factors.",
      "\tEvidence from family and twin studies\n\nThe obvious familial aggregation of T2D is clearly consistent with a genetic component to disease susceptibility, although a shared environment may also contribute.The extent of familial aggregation is often summarised in terms of the sibling relative risk (l s , the ratio of disease prevalence in the siblings of aected individuals compared with that in the general population).l s for T2D in European populations is approximately 3.5 (35% versus 10%) 4 , a modest value compared with the equivalent gure of around 15 for type 1 diabetes.The patterns of segregation in families with T2D are (with rare exceptions, such as maturity onset diabetes of the young  MODY  see below) consistent with a complex, multifactorial inheritance. 5orts to estimate the heritability of T2D by a comparison of the concordance rates in mono-and dizygotic twins have varied greatly as a result of dierences in ascertainment scheme, diagnostic criteria and follow-up duration.69 Concordance for diabetes is generally higher in identical twins (supporting a genetic basis for disease), although the extremely high concordance rates in some early studies 6 were undoubtedly inated by ascertainment bias.",
      "\tThe genetics of type 1 diabetes\n\nThere is a strong genetic risk to T1D.This is exemplified by (Redondo et al., 2001) who demonstrated a strong concordance of genetic inheritance (65%) and T1D susceptibility in monozygotic twin pairs.That is, when one sibling is afflicted, there is a high probability that the other twin will develop T1D by the age of 60 years.Additionally, autoantibody positivity and islet destruction was observed after a prospective long-term follow-up of monozygotic twins of patients with T1D, despite initial disease-discordance among the twins (Redondo et al., 2008).",
      "\tHeritability\n\nFamily history is an important risk factor for the development of T1D and T2D.In rare cases, there are families in which diabetes is inherited as a monogenic disease.More generally, the sibling of a patient with T1D has a 15-fold higher risk of developing the disease (6%) than does an unrelated individual (0.4%) (53).In T2D, the absolute risk to siblings is 30%-40%, as compared to a population prevalence of 7%, providing a relative risk to siblings of four to sixfold.In T1D and T2D, rates of concordance are much higher for monozygotic twins as compared to dizygotic twins.Specifically, in T1D, the concordance rate for monozygotic twins is estimated to range from 21%-70%, higher than the 0%-13% range reported for dizygotic twins (145).For T2D, Barnett et al. (8) found that 48 of 53 identical twin pairs were concordant for T2D if followed for long enough, and Poulsen et al. (141) described a concordance rate of 43% in Danish dizygotic twins as compared to 63% in monozygotic twins.Interestingly, while the relative risk to a sibling ( S , which tracks with power in a linkage study) is higher in T1D than T2D, the absolute risk and concordance in monozygotic twins are higher in T2D than in T1D.",
      "\tType 1 diabetes is a genetic disease\n\nFamily studies have indicated that genetic factors are important determinants of type 1 diabetes risk.First, the risk to a sibling of an affected individual is approximately 6%, as compared with an average risk of 0.4% (depending on the population), or a relative increased risk of 15-fold (17).The increased risk to siblings is referred to as l s (18) and is one measure of the degree of familial clustering of the disease.\t\nFamily and twin studies indicate that a substantial fraction of susceptibility to type 1 diabetes is attributable to genetic factors.These and other epidemiologic studies also implicate environmental factors as important triggers.Although the specific environmental factors that contribute to immune-mediated diabetes remain unknown, several of the relevant genetic factors have been identified using two main approaches: genome-wide linkage analysis and candidate gene association studies.This article reviews the epidemiology of type 1 diabetes, the relative merits of linkage and association studies, and the results achieved so far using these two approaches.Prospects for the future of type 1 diabetes genetics research are considered.\t\n\nFamily and twin studies indicate that a substantial fraction of susceptibility to type 1 diabetes is attributable to genetic factors.These and other epidemiologic studies also implicate environmental factors as important triggers.Although the specific environmental factors that contribute to immune-mediated diabetes remain unknown, several of the relevant genetic factors have been identified using two main approaches: genome-wide linkage analysis and candidate gene association studies.This article reviews the epidemiology of type 1 diabetes, the relative merits of linkage and association studies, and the results achieved so far using these two approaches.Prospects for the future of type 1 diabetes genetics research are considered.\tType 1 diabetes has unusual epidemiological features related to gender\n\nType 1 diabetes also displays unusual patterns of inheritance that may yield insights into etiology and provide clues to the best methods for analyzing genetic studies.The risk to the offspring is generally greater from a mother or father who was diagnosed at an early age (again suggesting that early-onset cases are more heavily genetically 'loaded').However, the risk of diabetes is approximately two to four times higher for a child whose father has type 1 diabetes than one whose mother is affected [see (52,53) and references therein].This parental difference is largely due to a low risk for offspring of mothers who were diagnosed at a later age (53).The difference could be explained by at least three different factors.First, the risk alleles could only be active when transmitted by the father (such as is seen in imprinting, where only one of the parental alleles is expressed).Alternatively, a maternal environmental factor during pregnancy could be protective.However, it is difficult to see how this protective effect would be restricted to mothers diagnosed at a later age, especially since the protective effect was unrelated to the mother's duration of diabetes or even diabetic status at delivery (53).Finally, mothers who are diagnosed at a later age could represent more 'environmental' cases of diabetes, and thus be less likely to pass on risk genes to their offspring.",
      "\t\n\nCopyright  2008 Massachusetts Medical Society.All rights reserved.Panel A shows the incidence of type 2 diabetes in four quartiles (Q) of body-mass index (BMI) among Malm subjects who had a family history of diabetes and those without such a history.An increase in the quartile of the BMI gradually increased the risk of diabetes, as compared with the lowest quartile, with an odds ratio of 1.50 for the second quartile (95% confidence interval [CI], 1.26 to 1.78; P = 6.710 6 ), of 2.36 for the third quartile (95% CI, 2.00 to 2.78; P = 1.510 24 ), and of 4.96 for the fourth quartile (95% CI, 4.25 to 5.79; P = 1.110 90 ).Panel B shows the incidence of type 2 diabetes in relation to insulin secretion (disposition index) among subjects with a family history of diabetes and those without such a history.Subjects with a disposition index below the median of 23,393 (26.1% of highrisk subjects and 9.4% of low-risk subjects) had an increase in the risk of type 2 diabetes by a factor of 3.23 (95% CI, 2.41 to 4.34; P = 5.810 15 ), as compared with those above the median.A family history of diabetes significantly increased the risk of diabetes in subjects with impaired insulin secretion (35.5% vs. 9.9%), with an odds ratio of 4.86 (3.12 to 7.56, P = 2.310 12 ).Panel C shows the incidence of type 2 diabetes in carriers of an increasing number of risk alleles in 11 genes, which individually predicted future risk of type 2 diabetes, in relation to quartiles of BMI.There was a stepwise increase in diabetes risk with an increasing number of risk alleles and increasing quartiles of BMI so that participants carrying more than 12 risk alleles showed a doubling of the risk conferred by BMI alone.In the highest quartile of BMI (31.8% vs. 5.1%), this yielded an odds ratio of 8.0 (95% CI, 5.71 to 11.19; P = 9.110 34 ).Panel D shows the incidence of type 2 diabetes in carriers of an increasing number of risk alleles in the 11 genes, which individually predicted future risk of type 2 diabetes, in relation to low insulin secretion.Carriers of more than 12 risk alleles and a low disposition index (37.9%vs. 10.1%) had an odds ratio of 5.81 (95% CI, 3.18 to 10.61; P = 1.110 8 ).",
      "\tEvidence for a genetic basis: family and twin studies of Type I diabetes\n\nWhat is the evidence that Type I diabetes has a genetic basis?The simplest evidence comes from the fact that the frequency of the disorder is higher in close relatives of diabetic patients than in the general population (note: the reference population in the discussion which follows are people of European ancestry, who have the highest prevalence of Type I diabetes).For example, the frequency of Type I diabetes in siblings of diabetics is about 6 % by age 30 [1], while the frequency in the general population is about 0.4 % by age 30 [2].Thus, Type I diabetes is about 6/0.4,i. e. 15 times more common in siblings of diabetic patients than in the general population.This ratio between frequency in siblings compared with the general population is referred to as l sib [3].",
      "\tType 1 Diabetes\n\nThe higher type 1 diabetes prevalence observed in relatives implies a genetic risk, and the degree of genetic identity with the proband correlates with risk (22)(23)(24)(25)(26). Gene variants in one major locus, human leukocyte antigen (HLA) (27), confer 50-60% of the genetic risk by affecting HLA protein binding to antigenic peptides and antigen presentation to T cells (28).Approximately 50 additional genes individually contribute smaller effects (25,29).These contributors include gene variants that modulate immune regulation and tolerance (30)(31)(32)(33), variants that modify viral responses (34,35), and variants that influence responses to environmental signals and endocrine function (36), as well as some that are expressed in pancreatic b-cells (37).Genetic influences on the triggering of islet autoimmunity and disease progression are being defined in relatives (38,39).Together, these gene variants explain ;80% of type 1 diabetes heritability.Epigenetic (40), gene expression, and regulatory RNA profiles (36) may vary over time and reflect disease activity, providing a dynamic readout of risk.\tGenetics\n\nBoth type 1 and type 2 diabetes are polygenic diseases where many common variants, largely with small effect size, contribute to overall disease risk.Disease heritability (h 2 ), defined as sibling-relative risk, is 3 for type 2 diabetes and 15 for type 1 diabetes (17).The lifetime risk of developing type 2 diabetes is ;40% if one parent has type 2 diabetes and higher if the mother has the disease (18).The risk for type 1 diabetes is ;5% if a parent has type 1 diabetes and higher if the father has the disease (19).Maturity-onset diabetes of the young (MODY) is a monogenic disease and has a high h 2 of ;50 (20).Mutations in any 1 of 13 different individual genes have been identified to cause MODY (21), and a genetic diagnosis can be critical for selecting the most appropriate therapy.For example, children with mutations in KCJN11 causing MODY should be treated with sulfonylureas rather than insulin.",
      "\t\n\nGenetic factors have an important role in the development of diabetes, with some forms of the disease resulting from mutations in a single gene.Others are multifactorial in origin.The monogenic forms of diabetes account for approximately 5% of cases and are caused by mutations in genes encoding insulin 3 , the insulin receptor 4 , the glycolytic enzyme glucokinase 5 , and the transcription factors hepatocyte nuclear factor-1 (HNF-1), HNF-1, HNF-4, insulin promoter factor-1 and NeuroD1/BETA2 (refs  6-10).Mutations in maternally inherited mitochondrial genes can also cause diabetes, often in association with hearing loss 11 .",
      "\t\n\nStudies [71][72][73][74] in Mexican and Asian populations have identified several mutations associated with type 2 diabetes in young people.The high prevalence of type 2 diabetes in the parents of young people diagnosed with type 2 diabetes could reflect a stronger genetic predisposition, even when monogenic diabetes is excluded.This hypothesis suggests that efforts to define genes that cause type 2 diabetes by linkage might be more powerful if focused on young adults with diabetes, raising the question of whether type 2 diabetes in older populations has a relatively smaller genetic contribution and a stronger environmental contribution. 66",
      "\tFamily studies\n\nThe 29 index patients had 130 first-degree relatives (58 parents, 63 siblings, and nine children).Ten families were negative for fasting hyperglycaemia except for one sibling with juvenile-onset diabetes mellitus only.However, a family history of maturity-onset diabetes was present in seven families in members other than first-degree relatives.No relative had a history of psychiatric illness on direct questioning.There was no maternal history of diabetes or deafness.The parents of three index patients were consanguineous: one family was English, one Pakistani, and one of mixed Arabic/African descent.All the other index patients were caucasians.",
      "\t\n\nWe found that the presence or absence of parental diabetes and the genotype score were independently associated with the risk of diabetes.This suggests that family history as a risk factor for diabetes conveys more than heritable genetic information; it probably includes nongenetic familial behaviors and norms.The lower relative risks for diabetes associated with observed parental diabetes as compared with those associated with self-reported family history (approximately 1.8 vs. approximately 2.2) support the contention that family history contains more risk information than is implied by inheritance of the diabetes phenotype alone.One of the limitations of our study is that the 18 SNPs we included are probably insufficient to account for the familial risk of diabetes.They account for a minority of diabetes heritability, and the SNP array platforms from which they were chosen capture only approximately 80% of common variants in Europeans.In addition, we have not considered structural variants that might confer a risk of diabetes.It is possible that the addition of rare risk alleles with large effects, or a much larger number of common risk alleles with small individual effects, could improve discrimination. 36Indeed, as many as 500 loci may underlie the genetic risk of type 2 diabetes. 16Also, we did not study interactions among genes or between genes and the environment that might alter the genetic risk in exposed persons.As more diabetes risk variants become known, their incorporation into the genotype score may explain more of the genetic risk implied by parental diabetes.",
      "\t\n\nGenetics is one example of the 'other risk factors' involved in the pathogenesis of DR.Twin and epidemiological studies have strongly suggested a genetic component in the etiology of DR (6 -10), with heritability scores ranging from 27 to 52% in both type 1 and type 2 diabetes (7 -10).There is an increased risk of severe DR among family members of DR subjects (8,9) and in siblings of affected subjects (8,9).Furthermore, several studies have also shown a discrepant rate of the prevalence of DR among different racial ethnic groups in the US population, with a significantly higher prevalence observed among Hispanic, African-American and Chinese-American when compared with Caucasian populations (11).While these differences may partially be attributed to lifestyle factors, evidence from familial aggregation, ethnic differences and heritability clearly supports a genetic contribution in the etiology of DR."
    ],
    [
      "\t\n\nIn addition to lifestyle factors, it is known that type 2 diabetes has a strong genetic component.Recent genomewide association studies have identified >60 genetic variants that are associated with type 2 diabetes but individual effects of genetic variants are considered to be small [139,140].",
      "\t\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.",
      "\t\n\nThe notion that lifestyle modifi cation can eliminate the increased risk for development of T2DM in subjects with genetic susceptibility is also supported by fi ndings of Barwell et al. (2008) who reported that women with family history of T2DM experience greater improvement in insulin sensitivity following an exercise intervention than women with no family history.Although lifestyle modifi cation has been found effi cient in obesity and T2DM prevention even among genetically susceptible individuals, considerable heterogeneity in intervention responses has been observed.Genetic infl uences have been suggested to contribute to this heterogeneity.Risk allele carriers in several obesity-and T2DM-associated genes, for instance, have been found to experience suppressed weight reduction and improvement in various metabolic parameters in response to exercise or combined lifestyle interventions ( Franks et   preference for foods of high energy density ( Haupt et al., 2009b ;Speakman et al., 2008 ;Timpson et al., 2008 ).In summary, healthy lifestyle or lifestyle modifi cation may keep genetic predisposition to obesity and T2DM under control.Genetics has, however, been suggested to infl uence the outcome of a lifestyle intervention or even to determine individual PA level, food intake, and motivation for lifestyle change.\tLifestyle and Genetics in Obesity and Type 2 Diabetes \n\nRecent advancement in human genetics has led to the identifi cation of a relatively big number of obesity-and T2DM-associated loci.Their contribution to disease risk has, however, been shown to be small and their predictive value low, suggesting that lifestyle plays crucial role in obesity and T2DM development ( Vimaleswaran and Loos, 2010 ).Indeed, studies investigating the gene-lifestyle interactions in obesity and T2DM have suggested that the biological eff ect of genetic predisposition may be partially or totally abolished by healthy lifestyle or lifestyle modifi cation and vice versa.Epidemiological studies have reported that the negative eff ect of several obesity-and T2DM-associated genes may be attenuated in individuals with higher PA levels or healthy lifestyle, whereas low PA and western dietary pattern have been found to accentuate it. ( 1 ).\t\n\nGene-lifestyle interaction studies supporting the protective role of diet, exercise or combined lifestyle interventions in individuals genetically susceptible to obesity and type 2 diabetes.This document was downloaded for personal use only.Unauthorized distribution is strictly prohibited.\tConclusions \n\nObesity and T2DM are clearly the results of a complex interplay between inherited factors and the environment.Recent advancements made through the GWA approach have substantially contributed to our understanding of obesity and T2DM genetics, however, most of the loci identifi ed to date have modest eff ect on disease risk.Hence, lifestyle factors, namely physical inactivity and food overconsumption seem to have major importance for the development of both diseases.Healthy lifestyle and lifestyle modifi cation, on the other hand, appear to be the most effi cient tools for obesity and T2DM prevention.In addition, gene-lifestyle interaction studies suggest that lifestyle determines whether an individual is likely to develop the disease and that genetic susceptibility may be partially or totally kept under control by lifestyle modifi cation.Since genetics seems to infl uence individual response to a lifestyle intervention and even the motivation for lifestyle change, personalized interventions according to genotype may be considered in the future.By then lifestyle modifi cation targeting dietary change and increased physical activity may be recommended for successful obesity and T2DM prevention irrespectively of genetic susceptibility.\tLifestyle and Genetics in Obesity and type 2 Diabetes\n\nvaluable insights into the interactions between genetic predisposition and lifestyle factors, namely physical activity (PA) and food consumption.This current progress may have essential contribution to our understanding of the pathophysiology of both diseases, as well as, to the development and implementation of future treatment and prevention strategies.It is, therefore, the aim of the present review to summarize the available literature on the eff ect of the interactions between lifestyle and genetics on obesity and T2DM.",
      "\t\n\nLifestyle behaviors and genetic loci have clear and distinguishable effects on T2D risk; however, the pattern of disease occurrence within and between populations 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.\t\n\nNotwithstanding the important role lifestyle factors play in the etiology of T2D, persons living similar lifestyles can vary considerably in their susceptibility to the disease, with the variance being least among biologically related individuals, suggesting a genetic basis to the disease.In the past 4 years, major advances have been made in unraveling the genetic architecture of T2D.This search has cumulated in the discovery and confirmation of more than 30 common predisposing loci [10], but the variance in disease risk explained by these variants is much lower than predicted from heritability studies [11].Thus, the genetic associations discovered to date are likely to represent no more than the tip of the iceberg with respect to the genetic landscape of T2D.\t\n\nThe availability of detailed information on gene  environment interactions may enhance our understanding of the molecular basis of T2D, elucidate the mechanisms through which lifestyle exposures influence diabetes risk, and possibly help to refine strategies for diabetes prevention or treatment.The ultimate hope is genetics might one day be used in primary care to inform the targeting of interventions that comprise exercise regimes and other lifestyle therapies for individuals most likely to respond well to them.",
      "\t\n\nAt 1-week follow-up, 44% of participants indicated that the primary risk factor for them was genes/family history, followed by diet (26%) and lifestyle (19%).There was not a significant difference in the proportion of participants at increased genomic risk who indicated genes/ family history as the primary cause (p = 0.5144).In addition, no statistically significant difference in IPQ-R subscales and risk perception between those at increased and nonincreased genomic risk for T2DM or between those with and without a family history for other factors related to illness perception was observed.",
      "\tDiscussion\n\nOur study provides insight into the relative importance of clinical risk factors and those that are related to a panel of DNA variants associated with type 2 diabetes.Obesity was a strong risk factor for future diabetes, a risk that almost doubled in subjects with a family history of diabetes.However, the addition of data from genotyping of the known DNA variants to clinical risk factors (including a family history of diabetes) had a minimal, albeit statistically significant, effect on the prediction of future type 2 diabetes.Notably, the ability of genetic risk factors to predict future type 2 diabetes improved with an increasing duration of follow-up, suggesting that assessment of genetic risk factors is clinically more meaningful the earlier in life they are measured.",
      "\t\n\nAlthough the expected range of effects that are realistic for gene-lifestyle interactions in type 2 diabetes remains unclear, a doubling of the genetic risk estimate in the group exposed to adverse lifestyle factors compared with those who are unexposed (b GE = 2) is at the upper end of the interaction effect estimate ranges reported for common variants and common exposures (10).It is reasonable to conclude, therefore, that most of the interaction studies published to date report \"lucky\" true-positive results or false-positive results that may be underpinned by analytical and reporting biases.The replication of few examples of genelifestyle interactions in type 2 diabetes suggests that the literature is composed largely of the latter.Despite this, recent developments in the ways genetic association studies are performed, such as adoption of hypothesis-free approaches, the availability of comprehensive genotype arrays in large sample collections, global collaborations, and more rigorous analysis and reporting of data, have led to the emergence of many reproducible genetic association signals for type 2 diabetes and related glycemic traits, which has spurred a number of large-scale studies of gene-lifestyle interactions.",
      "\t\n\nGenetic and epigenetic factors determine cell fate and function.Recent breakthroughs in genotyping technology have led to the identification of more than 20 loci associated with the risk of type 2 diabetes (Sambuy 2007;Zhao et al. 2009).However, all together these loci explain <5% of the genetic risk for diabetes.Epigenetic events have been implicated as contributing factors for metabolic diseases (Barker 1988;Kaput et al. 2007).Unhealthy diet and a sedentary lifestyle likely lead to epigenetic changes that can, in turn, contribute to the onset of diabetes (Kaput et al. 2007).At present, the underlying molecular mechanisms for disease progression remain to be elucidated.",
      "\t\n\nThird, there is the issue as to whether early diagnosis can be shown to result in beneficial outcomes, for example by motivating improvements in lifestyle or treatments that reduce the risk of disease.In the case of TD, the potential for lifestyle modification and/or pharmaceutical intervention (e.g., with metformin) to reduce diabetes progression is clear (, ), and these benefits seem to accrue irrespective of genetic risk.In the Diabetes Prevention Program, for example, lifestyle intervention was effective at reducing diabetes incidence compared with placebo even among those with the highest quartile of TD rsPS ().However, there is limited evidence to date that the communication of genetic risk is sufficient to motivate most individuals to undertake the kind of long-term behavioral modification required for sustained benefit (-).There is also some (at least theoretical) risk of harm if the communication of risk information is mishandled.This could arise through failure to use ethnically appropriate scores, or to incorporate other relevant health information.For example, an overweight person with a low TD polygenic score may be at far greater risk of disease than the polygenic score alone would suggest.Some individuals may be liable to interpret high genetic risk in a deterministic and fatalistic way, failing to appreciate that remediation of risk through lifestyle modification is no less likely to be effective in their case.",
      "\t\n\nTwo trials in the field of T2D have assessed weight change in response to genetic testing.In the Genetic Counseling and Lifestyle Change for Diabetes Prevention Study (107), 177 patients with metabolic syndrome were randomized to receive genetic testing for T2D susceptibility based on 36 T2D-associated SNPs plus brief genetic counseling versus no genetic testing.Diabetes risk for genotyped  participants was summarized with a risk score categorizing their genetic risk as low, average, high.All patients were then enrolled in a 12-week lifestyle medication program modeled on the evidencebased DPP (108).The lifestyle intervention was effective: the group overall lost a mean of 8.5 6 10.1 pounds, with 31% losing at least 5% of their body weight.Communicating genetic risk did not change this effectiveness, however.The genotyped and control arms did not differ with respect to weight loss, attendance at the 12 DPP sessions, or motivation or confidence to make health behavior changes (107).In a second randomized trial, 601 patients with obesity or overweight received T2D risk estimates based on family history, BMI, and fasting plasma glucose, followed by either T2D genetic susceptibility results from four T2D-associated SNPs or eye disease counseling as a control (109).All participants received brief lifestyle counseling but were not otherwise enrolled in a weight loss program.Although the group receiving genetic risk information reported lower calorie and fat intake after 3 months, the two groups did not differ in these behaviors or in physical activity, weight loss, insulin resistance, or perceived risk after 6 months.",
      "\t\n\nThe missing heritability of T2DM could be accounted for by the interactions between susceptibility loci and various environmental determinants, whereby the impact of a given genetic variant is modified by the environmental milieu (and vice versa).Evidence that lifestyle factors modify the genetic effects on T2DM risk has been generated from both observational studies and clinical trials 82 .However, genetic background might also affect the individual's response to lifestyle interventions 83 .In addition, replication data are sparse, and comprehensive, large-scale studies have failed to provide a compelling basis for the significant interaction effect 84,85 .This failure might have occurred because the interaction effects are of small magnitude or might be due to the limited statistical power and multiple sources of bias and confounding factors in the current research methods 86 .\tGenomics 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 .",
      "\t\n\nAlthough precision diabetes medicine is much more than genetics, the majority of relevant research has focused on evaluating the role of genetic variants in precision prevention.Large epidemiological studies (75) and intervention trials (76,77) strongly suggest that standard approaches for lifestyle modification are equally efficacious in preventing diabetes regardless of the underlying genetic risk.This contrasts with the extensive epidemiological evidence suggesting that the relationship of lifestyle with obesity is dependent on genetic risk (78-81); however, with few exceptions (e.g., [74]), analyses in large randomized controlled trials have failed to show that these same genetic variants modify weight loss in response to lifestyle intervention (82).It is also important to recognize that knowledge of increased genetic risk for diabetes may not motivate improvements in lifestyle behaviors.Indeed, knowledge of increased genetic risk for diabetes may decrease motivation to modify behavior in genetic fatalists (83).",
      "\t\n\nOther aspects that have been overlooked in large GWAS on T2DM relate to environmental effects such as diet, physical activity, and stresses, which may affect gene expression.For example, fish oil may stimulate PPARG in much the same fashion as the thiazolidinedione class of drugs; however, studies on the interaction of the PPARG variant with dietary components have not been performed.The spectacular rise in the incidence of diabetes among Pima Indians and other populations as they adopt Western diets and lifestyles dramatically demonstrates the key role of the environment [12].Consequently, it could be expected that the effect of a common gene variant among populations that have very different diets and exercise habits might be totally different, thus explaining some instances of lack of replication. [4].Another variable that influences the statistical and real association of an SNP with a disease or response to a diet is epigenetic interaction.Epigenesis is the study of heritable changes in gene function that occur without a change in the DNA sequence, such as DNA methylation and chromatin remodeling.Both mechanisms can affect gene expression by altering the accessibility of DNA to regulatory proteins or complexes such as transcription factors, and they can be influenced by certain nutrients and by overall caloric intake.Thus, it can be expected that long-term exposure to certain diets could produce permanent epigenetic changes in the genome [7]."
    ],
    [
      "\tConcluding remarks\n\nFor the past two decades, genetics has been widely advocated as a tool for unravelling the pathogenesis of common forms of diabetes, but the complexity of the problem defied easy solutions.Recent advances have made it possible to find many of the genes that predispose to both major types of diabetes.Much work is still needed to translate knowledge of these genes into benefits for patients.The greatest benefit is likely to come from new\tIntroduction\n\nWe are all witnesses to a period of astonishing progress in our understanding of the genetic basis of diabetes, and the advances of recent months are arguably the most important made since the role of the HLA region was recognised in type 1 diabetes.The number of genetic regions causally implicated is now 11 each for type 1 and type 2 diabetes [1][2][3][4][5][6][7][8][9], and is set to rise further.The bewildering pace of new discovery stands in stark contrast to the slow progress that characterised the previous two decades, with a total combined output of three confirmed genes for type 2 diabetes and six for type 1 (Fig. 1).At last, it seems, our understanding of the genetic basis of complex, multifactorial forms of diabetes is catching up with that of rarer, single-gene disorders.",
      "\t\n\nThis technology recently facilitated rapid progress in type 2 diabetes genetic research.This is all the more remarkable because type 2 diabetes does not have a strong genetic component compared with some other common traits, and was previously described as 'a geneticist's nightmare' 1,2 .Nevertheless, early results have been excellent, yielding six new replicating gene regions.",
      "\tFuture 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.",
      "\t\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.",
      "\t\n\nGenetic factors are known to play a role in T2D and an understanding of the genetic basis of T2D could lead to the development of new treatments (Frayling, 2007a,b;Frayling & Mccarthy, 2007;Frayling, 2008).With the increased prevalence of diabetes worldwide, the need for intensive research is of high priority.Sequencing of the human genome and development of a set of powerful tools has made it possible to find the genetic contributions to common complex diseases (Donnelly, 2011).Genome-wide association studies (GWAS) have been used to search for genetic risk factors for complex disease (Hindorff, Junkins et al., 2009;Hindorff, Sethupathy et al., 2009).Used in combination with the scaffold data of the human genome courtesy of the HUGO Project (2003) and the International HapMap Project (Thorisson et al., 2005), it is now possible to analyse the whole genome to identify genetic variants that contribute to common disease in a fast and efficient manner.",
      "\t\n\nAll of these genetic research efforts of the last decade have led to the identification of at least 27 (confirmed and potential) type 2 diabetes susceptibility genes, and their time-course of discovery or initial publication is depicted in Fig. 1.",
      "\t\n\nUnfortunately, these questions are not yet answered.The early 1990s was the beginning of the era of molecular biol- ogy, and it was generally assumed that within a few years this powerful new technology would identify the genetic defects in type 2 diabetes.Indeed, the genetic basis for many monogenic forms of diabetes has been discovered such as mitochondrial genome defects and the association with diabetes and deafness, Wolfram's syndrome, several rare syndromes of extreme insulin resistance and obesity, and many of the MODY syndromes (maturity onset diabetes of youth).Still, these account for only a small proportion of diabetes.",
      "\tNew d iscoveries in the g enetic e tiology of T 2 DM\n\nImportant advances in T2DM genetics have been made with the completion of GWA studies based on HapMap -selected common SNPs.This has become reality with the outstanding breakthroughs made in the knowledge and assessment of human genome variations, their mapping and their links with the genetic background of common diseases [167] , and in the development and accessibility to very high throughput genotyping techniques based on microarray technology and to biostatistical tools for large cohort data analyses.",
      "\t\n\nOver the past two years, there has been a spectacular change in the capacity to identify common genetic variants that contribute to predisposition to complex multifactorial phenotypes such as type 2 diabetes (T2D).The principal advance has been the ability to undertake surveys of genome-wide association in large study samples.Through these and related efforts, $20 common variants are now robustly implicated in T2D susceptibility.Current developments, for example in high-throughput resequencing, should help to provide a more comprehensive view of T2D susceptibility in the near future.Although additional investigation is needed to define the causal variants within these novel T2Dsusceptibility regions, to understand disease mechanisms and to effect clinical translation, these findings are already highlighting the predominant contribution of defects in pancreatic b-cell function to the development of T2D.",
      "\t\n\nTo date, studies of diabetes have played a major role in shaping thinking about the genetic analysis of complex diseases.Based on trends in genomic information and technology, combined with the growing public health importance of diabetes, diabetes will likely continue to be an important arena in which methods will be pioneered and lessons learned.It is with great enthusiasm that we look forward to this effort, and with avid curiosity we await to see whether the lessons of today will be supported by the data of tomorrow.",
      "\t\n\nIn recent years tremendous changes had occurred in the field of molecular genetics and personalized medicine especially on exploring novel genetic factors associated with complex diseases like T2D with the advancement of new and improved genetic techniques including the next generation sequencing (NGS).In this review, we summarize recent developments from studies on the genetic factors associated with the development of T2D in the Arab world published between 2015 and 2018, which were based on the latest available genetic technologies.Few such studies have been conducted in this region of the world.Therefore, our study will provide valuable contributions to advanced genetic research and a personalized approach to diabetes management.",
      "\t\nIt has proven to be challenging to isolate the genes underlying the genetic components conferring susceptibility to type 1 and type 2 diabetes.Unlike previous approaches, 'genome-wide association studies' have extensively delivered on the promise of uncovering genetic determinants of complex diseases, with a number of novel disease-associated variants being largely replicated by independent groups.This review provides an overview of these recent breakthroughs in the context of type 1 and type 2 diabetes, and outlines strategies on how these findings will be applied to impact clinical care for these two highly prevalent disorders.\t\n\nIt has proven to be challenging to isolate the genes underlying the genetic components conferring susceptibility to type 1 and type 2 diabetes.Unlike previous approaches, 'genome-wide association studies' have extensively delivered on the promise of uncovering genetic determinants of complex diseases, with a number of novel disease-associated variants being largely replicated by independent groups.This review provides an overview of these recent breakthroughs in the context of type 1 and type 2 diabetes, and outlines strategies on how these findings will be applied to impact clinical care for these two highly prevalent disorders.",
      "\t\nGenome wide association studies (GWAS) have transformed the study of heritable factors influencing complex diseases such as type 2 diabetes (T2D), with the current tally of established risk loci approaching 70.Each of these loci has the potential to offer novel insights into the biology of this disease, and opportunities for clinical exploitation.However, the complexity of this condition has often frustrated efforts to achieve these functional and translational advances.This review describes progress made over the past year to expand genome wide association studies, to characterize the mechanisms through which diabetes risk loci operate, and to define the processes involved in diabetes predisposition.",
      "\t\nA new generation of genetic studies of diabetes is underway.Following from initial genome-wide association (GWA) studies, more recent approaches have used genotyping arrays of more densely spaced markers, imputation of ungenotyped variants based on improved reference haplotype panels, and sequencing of protein-coding exomes and whole genomes.Experimental and statistical advances make possible the identification of novel variants and loci contributing to trait variation and disease risk.Integration of sequence variants with functional analysis is critical to interpreting the consequences of identified variants.We briefly review these methods and technologies and describe how they will continue to expand our understanding of the genetic risk factors and underlying biology of diabetes.\t\n\nA new generation of genetic studies of diabetes is underway.Following from initial genome-wide association (GWA) studies, more recent approaches have used genotyping arrays of more densely spaced markers, imputation of ungenotyped variants based on improved reference haplotype panels, and sequencing of protein-coding exomes and whole genomes.Experimental and statistical advances make possible the identification of novel variants and loci contributing to trait variation and disease risk.Integration of sequence variants with functional analysis is critical to interpreting the consequences of identified variants.We briefly review these methods and technologies and describe how they will continue to expand our understanding of the genetic risk factors and underlying biology of diabetes.",
      "\t\n\nMuch has been made over the past decade of the potential for genetics to advance our understanding of the pathogenesis of type 2 diabetes and to 'revolutionise' management of this condition [1].Others have argued that these claims are premature [2]; indeed, some have questioned the contribution of genetic predisposition to the pathogenesis of common forms of type 2 diabetes [3].",
      "\t\n\n During the last decade, there have been major advances in our understanding of the genetic basis of the most common subtypes of type 1 (T1D) and type 2 diabetes (T2D), with .500robust associations identified  Although individual variants typically have only a modest effect on risk, when combined into a polygenic score, they offer increasing power to capture information on individual patterns of disease predisposition with the potential to influence clinical management",
      "\tTHE GENETICS OF TYPE 1 DIABETES\n\nThe study of the genome to map disease-susceptibility regions for T1D and other multifactorial diseases has been facilitated by recent advances in next generation DNA sequencing methods."
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