Download PDF Diabetes (Genes and Disease)

Free download. Book file PDF easily for everyone and every device. You can download and read online Diabetes (Genes and Disease) file PDF Book only if you are registered here. And also you can download or read online all Book PDF file that related with Diabetes (Genes and Disease) book. Happy reading Diabetes (Genes and Disease) Bookeveryone. Download file Free Book PDF Diabetes (Genes and Disease) at Complete PDF Library. This Book have some digital formats such us :paperbook, ebook, kindle, epub, fb2 and another formats. Here is The CompletePDF Book Library. It's free to register here to get Book file PDF Diabetes (Genes and Disease) Pocket Guide.
Donate Today to Fight Diabetes
  1. Genetics of Diabetes
  2. Subscribe to addiction research updates
  3. Study identifies new diabetes genes | European Bioinformatics Institute
  4. DNA sequence alterations linked to type 2 diabetes genes and mechanisms
  5. Type 1 diabetes and genetics - average risks

IMPC researchers create computational models of disease in the mouse that anyone can use to explore how diseases arise and develop in humans. In this study, the team of researchers used computational models of mice to identify genes that are implicated in metabolic disease. They compared their results with genome data collected from human patients.

Genetics of Diabetes

By measuring physiological activities in these mice, we can see what biological systems are affected when a specific gene is not functioning. This gives us clues about how genetics is linked to disease, both in mice and humans. The team identified hundreds of genes associated with metabolism in mice. In 51 of them, the link with disease had been completely unknown to scientists. It is only by deciphering cause and effect — the causal genetic links — that researchers can understand how diseases arise, develop therapeutic interventions or even prevent an outbreak.

The newly identified diabetes genes discovered in this study could be used as biomarkers for predicting the risk of diabetes in an individual, early diagnosis of the disease, or personalised approaches for treatment. Your gift today will help us get closer to curing diabetes and better treatments for those living with diabetes. You've probably wondered how you developed diabetes. You may worry that your children will develop it too.

Subscribe to addiction research updates

Unlike some traits, diabetes does not seem to be inherited in a simple pattern. Yet clearly, some people are born more likely to develop diabetes than others. Type 1 and type 2 diabetes have different causes. Yet two factors are important in both. You inherit a predisposition to the disease then something in your environment triggers it. Genes alone are not enough. One proof of this is identical twins. Identical twins have identical genes. Yet when one twin has type 1 diabetes, the other gets the disease at most only half the time.

In most cases of type 1 diabetes, people need to inherit risk factors from both parents. We think these factors must be more common in whites because whites have the highest rate of type 1 diabetes. Because most people who are at risk do not get diabetes, researchers want to find out what the environmental triggers are. One trigger might be related to cold weather. Type 1 diabetes develops more often in winter than summer and is more common in places with cold climates.

Another trigger might be viruses. Perhaps a virus that has only mild effects on most people triggers type 1 diabetes in others. Early diet may also play a role. Type 1 diabetes is less common in people who were breastfed and in those who first ate solid foods at later ages. In many people, the development of type 1 diabetes seems to take many years. In experiments that followed relatives of people with type 1 diabetes, researchers found that most of those who later got diabetes had certain autoantibodies in their blood for years before.

Antibodies are proteins that destroy bacteria or viruses. The traditional method of mapping disease genes is to use the long stretches of linkage disequilibrium LD in affected families by performing linkage analysis. By genotyping about — genetic markers, disease loci can be mapped on a genomewide level. Finding that affected family members share a certain marker that is identical by descent, i. Although this strategy has been very successful for mapping genetic diseases with strong penetrance and a known inheritance mode, it has been less useful for identifying genes that cause complex diseases, such as T2D.

Study identifies new diabetes genes | European Bioinformatics Institute

This region was later fine-mapped in the Icelandic population by use of microsatellite markers covering a The association between T2D and a number of single-nucleotide polymorphisms SNPs in the TCF7L2 gene has since been confirmed in numerous studies in different ethnic groups. The risk allele confers a relative risk of approximately 1. The mechanisms by which TCF7L2 affects diabetes susceptibility are still not completely understood. In a study of Scandinavian individuals, we showed that the T-allele of SNP rs is associated with risk of T2D, impaired insulin secretion, incretin effects, and an enhanced rate of hepatic glucose production In addition, TCF7L2 has been suggested to regulate proglucagon gene expression, and thus glucagon-like peptide 1 GLP-1 synthesis, from intestinal endocrine L cells The other gene mapped by linkage analysis is a locus on chromosome 2 that was first mapped in by Hanis et al.

In the locus was fine mapped and the causative gene shown to be CAPN10 , the gene for calpain 10, a cysteine protease with largely unknown functions in glucose metabolism Despite a number of negative replication studies, several metaanalyses have shown consistent association of CAPN10 with T2D 19 , Identification of disease genes can also be made on the basis of association testing in populations rather than in families.

Because of the short LD stretches in unrelated individuals, a very large number of markers are needed to perform mapping on a genomewide level. Until recently, the only feasible strategy was to study candidate genes that had high probability of affecting the studied trait based on the known function of the gene. Although the initial report was followed by a number of negative studies, in a family-based study, with the use of a transmission disequilibrium test, we observed excess transmission of the Pro allele to affected offspring It soon became clear that most negative studies had been underpowered, and that combining the data from all published studies in a metaanalysis yielded strong support for association between the Pro12Ala variant and T2D 22 — IRS1 encodes a protein that is phosphorylated by insulin receptor tyrosine kinase and is essential to insulin function.

The association between a GlyArg polymorphism and T2D was reported in 25 but could not be replicated consistently by subsequent studies. It was, however, found to be strongly associated with T2D in a recent GWAS that also showed an association with reduced basal concentrations of IRS1 protein and decreased insulin induction of IRS1-associated phosphatidylinositolOH kinase activity in human skeletal muscle biopsies KCNJ11 encodes a protein, Kir6.

Activating mutations in this gene cause severe neonatal diabetes A Glu23Lys polymorphism has been associated with modest impairment of insulin secretion and T2D Large-scale studies and metaanalyses have confirmed the association and shown that the lysine variant increases activation of the channel by 2-fold, resulting in a 1. The association has also been confirmed in GWAS 32 — WFS1 encodes Wolframin, a protein that is defective in individuals suffering from the Wolfram syndrome, characterized by diabetes insipidus, juvenile diabetes, optic atrophy, and deafness.

WFS1 was first suggested to be associated with T2D in a small family-based association study The gene was later included as a candidate in a study of SNPs in 84 candidate genes. Of these 84 genes only WFS1 was associated with T2D and could be replicated in cases and 11 controls The association has also been confirmed in a large metaanalysis comprising 14 cases and 16 controls Mutations in the HNF1B gene cause MODY5, which in affected individuals is associated with early-onset diabetes and also urogenital and renal pathology.

Rapid improvement in high-throughput technology for SNP genotyping, which has allowed simultaneous genotyping of hundreds of thousands of SNPs, has opened new possibilities for association studies. A few months later this study was followed by another 4 studies, all performed in European populations with a case-control setup, including the Wellcome Trust Case Control Consortium study in cases and controls from the UK 45 ; the Diabetes Genetics Initiative study in cases and controls from Sweden and Finland 32 ; the FUSION Finland—United States Investigation of NIDDM [non—insulin-dependent diabetes mellitus] genetics study in cases and controls from Finland 33 ; and a study by Steinthorsdottir et al.

The first 3 studies shared results before publication and considered only positive results that were seen and replicated in all 4 studies. About the same time, the fat mass and obesity associated FTO gene was identified as a major susceptibility locus for obesity, and therefore indirectly also for T2D 46 , Results of the first GWAS on T2D in non-European populations were published in ; both of these studies used multistage approaches 48 , Yasuda et al.

In total 19 individuals of Asian and European descent were genotyped for the strongest signals.

Genomic Variation and the Inherited Basis of Common Disease

Unoki et al. The risk allele of the SNP rs has also been found to be associated with reduced insulin secretion in Swedish and Finnish cross-sectional and prospective cohorts, conferring a T2D risk of 1. Another study in an Asian population was performed by Tsai et al. In Kong et al. The marker rs was only weakly associated with T2D in a standard case-control analysis. However, when parental origin was taken into account the paternally inherited allele increased risk of T2D with genome-wide significance. Interestingly, the maternally inherited allele showed nominally significant evidence of a protective effect on T2D.

Qi et al. The loci recently identified by GWAS and metaanalysis can be subgrouped on the basis of their association with phenotypes with a key role in T2D etiology. Melatonin works as a chronobiotic factor, adjusting the timing of the biological clock 59 , Its receptors are present in the pancreas, and melatonin is proposed to contribute to the nocturnal lowering of insulin in humans. Recently Lyssenko et al. Mulder et al. In addition, the insulinotropic pressure e. Lyssenko et al. Grarup et al. The CDKAL1 gene is expressed both in skeletal muscle and pancreatic islets but has a largely unknown function 33 , Rosengren et al.

It is well known that epinephrine excess can suppress insulin secretion and cause diabetes. Pretreatment of human islets with the ADRA2-blocking agent yohimbine normalized insulin secretion in risk genotype carriers. Insulin resistance is a condition in which peripheral tissues fail to respond adequately to insulin. In a metaanalysis study by Orho-Melander et al.

IGF1 codes for insulin-like growth factor 1, and a null mutation for IGF1 has previously been correlated with improper glucose homeostasis with resistance to insulin and high concentrations of circulating insulin KLF14 a widely expressed, intronless member of the Kruppel-like family of transcription factors is maternally expressed, and the variant at this locus appears to have a primary effect on insulin action Obesity is an important predictor and cause of T2D and cardiovascular disease.

Genes increasing susceptibility to obesity are thus important candidates for T2D risk as well. Increased free fatty acid concentrations are often seen in obese individuals, in whom they cause defective glucose metabolism through insulin resistance development 69 — Subsequently, new GWAS have identified many novel obesity-associated loci in both children and adults. However, results have been variable for replication in other ethnic populations such as Hispanics 79 , Asians, Oceanics 80 , and blacks The FTO gene encodes for a protein 2-oxoglutarate-dependent nucleic acid demethylase involved in fatty acid metabolism, DNA repair, and posttranslational modifications Studies in mice suggest that Fto might affect neuropeptide Y expression in the hypothalamus, which in turn is known to impact feeding behavior Fto —knock-out mice have a reduced size and body weight with improved insulin sensitivity and increased adrenaline concentrations in blood, suggesting that their energy expenditure occurs in the presence of increased sympathetic activation so they are lean even after hyperphagia Olszewski et al.

The second most important obesity gene, MC4R , is expressed in the hypothalamus and regulates energy expenditure, insulin sensitivity, and energy intake Leptin, an anorexogenic adipokine, stimulates the production of proopiomelanocortin products, which bind to MC4R, resulting in decreased food intake and increased energy expenditure Chambers et al. Although a considerable number of variants have been found to affect the risk of T2D, these variants still account for only a small proportion of the total heritability.

DNA sequence alterations linked to type 2 diabetes genes and mechanisms

Most of the identified variants have very modest effect sizes in the range of 1. Some of these effect sizes may even be overestimated owing to winner's curse, i. The key question is thus, what can explain the missing heritability? One possibility is of course that the heritability estimates are wrong. This error would not be surprising for T2D, for which the familial risk of 3 has been derived from family studies, but most GWAS studies have not requested that study participants have another family member with T2D. Other possible explanations include a much larger number of variants of even smaller effects that remain to be identified, low frequency minor allele frequency 0.

Many of these effects could possibly be identified by the currently used strategies by increasing genotyping coverage and sample sizes even further. However, it is likely that many variants escape detection owing to mechanisms such as parental-origin—specific effects, gene—gene interactions, gene—environment interactions, and epigenetic effects, among others. The hunt for these variants will benefit from the development of new detection strategies and methods. In the years to come, next-generation sequencing in families in which the heritability has been estimated should be able to answer some of these questions.

It is plausible that some of the genetic variance is explained by relatively rare variants, some of which could have larger effect sizes than the common variants identified so far. A substantial part of the missing heritability could be due to variants with large or intermediate effect sizes and relatively low frequencies that are likely to have escaped detection by current methods, having too low penetrance to allow linkage analysis and being too rare to detect in GWAS.

The strategies to identify such variants largely depend on the frequency of the variants. However, detection of many of these rare or intermediate variants will require next-generation sequencing rather than traditional GWAS or genotyping Variants that are relatively rare in the European population could also be identified by studying other ethnic groups where the variant is more common.

Gene—gene interactions with nonadditive effects are another potential source of missing heritability.

Type 1 diabetes and genetics - average risks

How much such epistatic effects contribute to the genetic variation in the predisposition to T2D is unknown, and so far there is little evidence in human studies 91 — 93 that epistatic changes contribute to disease pathology. In contrast, epistatic effects seem to be very common in animal models, in which they can be identified by using selective breeding strategies.

For example, Shao et al. This finding suggests that nonlinear effects is a rule rather than an exception if all effects were additive the sum of effects would equal the parental difference Studies of gene—gene interactions in outbred populations are difficult because the number of tests required usually exceeds our calculation and power capacity Therefore, a common strategy to limit the number of tests is to restrict the analysis to loci with significant main effects 45 , 96 However, it is well known from studies in plants and animals that epistatic effects are often detected in the absence of main effects 97 , An illustrative study was performed by Carlborg et al.

In spite of the large genetic variance, only 1 significant locus, with a minor effect, was identified in standard quantitative-trait loci analysis. Similar networks have been shown to determine obesity in mice There are no reasons to assume that the genetics of human metabolism will be less complex.

  1. Is type 1 diabetes hereditary?.
  2. related stories.
  3. Diabetes and genetic risk?
  4. Genetics of Type 2 Diabetes | Clinical Chemistry;
  5. Is Type 1 Diabetes Genetic/Hereditary? | Causes & Treatment - dLife.

Gene—environment interactions are another potential source of missing heritability that could have effects similar to those of gene—gene interactions, but these are also poorly investigated in humans owing to the fact that the potentially relevant environmental factors are huge in number and by their nature difficult to measure in a standardized fashion to allow analysis in adequately large sample sizes.

Epigenetics has been defined as heritable changes in gene function that occur without a change in the nucleotide sequence. Epigenetic modifications can be passed from one cell generation to the next mitotic inheritance or between generations of individuals meiotic inheritance. Although meiotic inheritance is well established in plants, there is only limited information about the inheritance of epigenetic traits between generations in animals and humans so far , Epigenetic effects can also occur during life, stochastically or in response to environmental stimuli, thereby influencing the effects of genetic variants and thus acting as a mechanism of gene—environment interaction.

Both DNA methylation and histone modifications can change the response of our genome to the environment during life. DNA methylation often results in decreased expression of a gene, which in its extreme form becomes completely suppressed imprinted. Posttranslational modifications on the N-terminal histone tails in the chromatin also play an essential role in regulation of gene expression and function. Modification of the chromatin structure can allow access or prevent access of proteins to binding with a transcription factor, which has been shown for TCF7L2 In the pathogenesis of T2D, special attention has been given to the role of intrauterine DNA methylation and imprinting for the programming of diabetogenic effects later in life An interesting study by Dabelea et al.

However, the exact mechanism for this maternal effect remains to be determined. Intrauterine growth retardation has also been associated with increased DNA methylation of the Pdx1 promoter in islets from experimental animals A few additional epigenetic studies have been carried out in target tissues from individuals with T2D — One such study describes hypermethylation of the PPRG1A gene promoter in islets from T2D patients, resulting in decreased gene expression, and glucose-stimulated insulin secretion Methylation of the insulin gene promoter also seems to affect insulin secretion Several studies have investigated the predictive value of genetic markers in comparison with clinical risk factors with similar results 62 , — The largest study was performed by our own group in 2 Scandinavian cohorts.

Inclusion of genetic information from 16 genotyped risk variants increased the area under the ROC curve from 0. Notably the difference in predictive value increased the earlier the genetic analyses were performed The use of genetic markers in diagnosis of T2D is thus not very useful so far, although identification of new variants with larger effects could change this rapidly. It should also be noted that the effect size of a locus is not at all correlated with the potential for the involved pathway as a target for clinical therapy.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 re-quirements: a significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; b drafting or revising the article for intellectual content; and c final approval of the published article.