Genetics of Type 2 Diabetes - Pitfalls and Possibilities

Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult.Peer reviewe

Clusters provide a better holistic view of type 2 diabetes than simple clinical features

Non peer reviewe

Ethnic differences in the contribution of insulin action and secretion to type 2 diabetes in immigrants from the Middle East compared to native Swedes.

We investigated insulin action (insulin sensitivity index, ISI) and insulin secretion (oral disposition indices, DIo) and studied metabolic, demographic and lifestyle-related risk factors for type 2 diabetes and insulin action, in the largest non-European immigrant group to Sweden, immigrants from Iraq and native Swedes

Common variants in CNDP1 and CNDP2, and risk of nephropathy in type 2 diabetes.

AIMS/HYPOTHESIS: Several genome-wide linkage studies have shown an association between diabetic nephropathy and a locus on chromosome 18q harbouring two carnosinase genes, CNDP1 and CNDP2. Carnosinase degrades carnosine (β-alanyl-L-: histidine), which has been ascribed a renal protective effect as a scavenger of reactive oxygen species. We investigated the putative associations of genetic variants in CNDP1 and CNDP2 with diabetic nephropathy (defined either as micro- or macroalbuminuria) and estimated GFR in type 2 diabetic patients from Sweden. METHODS: We genotyped nine single nucleotide polymorphisms (SNPs) and one trinucleotide repeat polymorphism (D18S880, five to seven leucine repeats) in CNDP1 and CNDP2 in a case-control set-up including 4,888 unrelated type 2 diabetic patients (with and without nephropathy) from Sweden (Scania Diabetes Registry). RESULTS: Two SNPs, rs2346061 in CNDP1 and rs7577 in CNDP2, were associated with an increased risk of diabetic nephropathy (rs2346061 p = 5.07 × 10(-4); rs7577 p = 0.021). The latter was also associated with estimated GFR (β = -0.037, p = 0.014), particularly in women. A haplotype including these SNPs (C-C-G) was associated with a threefold increased risk of diabetic nephropathy (OR 2.98, 95% CI 2.43-3.67, p < 0.0001). CONCLUSIONS/INTERPRETATION: These data suggest that common variants in CNDP1 and CNDP2 play a role in susceptibility to kidney disease in patients with type 2 diabetes

Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying susceptibility loci associated with polygenetic diseases such as type 2 diabetes mellitus (T2DM). However, it is still a daunting task to prioritize single nucleotide polymorphisms (SNPs) from GWAS for further replication in different population. Several recent studies have shown that genetic variation often affects gene-expression at proximal (<it>cis</it>) as well as distal (<it>trans</it>) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability.</p> <p>Methods</p> <p>To prioritize SNPs from GWAS, we combined results from two GWAS related to T2DM, the Diabetes Genetics Initiative (DGI) and the Wellcome Trust Case Control Consortium (WTCCC), with genome-wide expression data from pancreas, adipose tissue, liver and skeletal muscle of individuals with or without T2DM or animal models thereof to identify T2DM susceptibility loci.</p> <p>Results</p> <p>We identified 1,170 SNPs associated with T2DM with <it>P </it>< 0.05 in both GWAS and 243 genes that were located in the vicinity of these SNPs. Out of these 243 genes, we identified 115 differentially expressed in publicly available gene expression profiling data. Notably five of them, <it>IGF2BP2</it>, <it>KCNJ11</it>, <it>NOTCH2</it>, <it>TCF7L2 </it>and <it>TSPAN8</it>, have subsequently been shown to be associated with T2DM in different populations. To provide further validation of our approach, we reversed the approach and started with 26 known SNPs associated with T2DM and related traits. We could show that 12 (57%) (<it>HHEX</it>, <it>HNF1B</it>, <it>IGF2BP2</it>, <it>IRS1</it>, <it>KCNJ11</it>, <it>KCNQ1</it>, <it>NOTCH2</it>, <it>PPARG</it>, <it>TCF7L2</it>, <it>THADA</it>, <it>TSPAN8 </it>and <it>WFS1</it>) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies.</p> <p>Conclusions</p> <p>Utilizing of gene expression profiling data from different tissues of individuals with or without T2DM or animal models thereof is a powerful tool for prioritizing SNPs from WGAS for further replication studies.</p

Role of the FOXC2 -512C&gt;T polymorphism in type 2 diabetes: possible association with the dysmetabolic syndrome.

OBJECTIVE: Overexpression of the human transcription factor FOXC2 gene ( FOXC2) protects against insulin resistance in mice and a common FOXC2 polymorphism (-512C > T) has been suggested to be associated with insulin resistance in humans. Here, we addressed the potential role for FOXC2 as a candidate gene for type 2 diabetes and associated phenotypes. MATERIALS AND METHODS: A case-control study was performed in 390 type 2 diabetic patients and 307 control subjects. The number of patients was increased to a total of 768 subjects for further study of phenotypic differences relating to the dysmetabolic syndrome relative to genetic variation. The FOXC2 -512C > T polymorphism was genotyped by a restriction fragment length polymorphism PCR assay. RESULTS: FOXC2 -512C > T allele and genotype distribution did not differ between patients with type 2 diabetes and control subjects, but the C/C genotype was associated with increased body mass index (BMI, kg/m(2)) (P-a = 0.03) among type 2 diabetic patients. The FOXC2 -512C > T polymorphism was a significant independent predictor of BMI (P = 0.001) in a multiple regression model including age, gender and affection status. We found no significant association with type 2 diabetes-related metabolic parameters but that the C-allele (P = 0.01) and C/C and C/T genotypes (P = 0.03) were significantly over-represented in type 2 diabetic males with a concomitant diagnosis of dysmetabolic syndrome. CONCLUSION: We conclude that FOXC2 is associated with obesity and metabolic deterioration but does not contribute to an increased risk for type 2 diabetes

1-Hour Post-OGTT Glucose Improves the Early Prediction of Type 2 Diabetes by Clinical and Metabolic Markers

Context: Early prediction of dysglycemia is crucial to prevent progression to type 2 diabetes. The 1-hour postload plasma glucose (PG) is reported to be a better predictor of dysglycemia than fasting plasma glucose (FPG), 2-hour PG, or glycated hemoglobin (HbA1c). Objective: To evaluate the predictive performance of clinical markers, metabolites, HbA1c, and PG and serum insulin (INS) levels during a 75-g oral glucose tolerance test (OGTT). Design and Setting: We measured PG and INS levels at 0, 30, 60, and 120 minutes during an OGTT in 543 participants in the Botnia Prospective Study, 146 of whom progressed to type 2 diabetes within a 10-year follow-up period. Using combinations of variables, we evaluated 1527 predictive models for progression to type 2 diabetes. Results: The 1-hour PG outperformed every individual marker except 30-minute PG or mannose, whose predictive performances were lower but not significantly worse. HbA1c was inferior to 1-hour PG according to DeLong test P value but not false discovery rate. Combining the metabolic markers with PG measurements and HbA1c significantly improved the predictive models, and mannose was found to be a robust metabolic marker. Conclusions: The 1-hour PG, alone or in combination with metabolic markers, is a robust predictor for determining the future risk of type 2 diabetes, outperforms the 2-hour PG, and is cheaper to measure than metabolites. Metabolites add to the predictive value of PG and HbA1c measurements. Shortening the standard 75-g OGTT to 1 hour improves its predictive value and clinical usability.Peer reviewe

Genome editing of human pancreatic beta cell models : problems, possibilities and outlook

Understanding the molecular mechanisms behind beta cell dysfunction is essential for the development of effective and specific approaches for diabetes care and prevention. Physiological human beta cell models are needed for this work. We review the possibilities and limitations of currently available human beta cell models and how they can be dramatically enhanced using genome-editing technologies. In addition to the gold standard, primary isolated islets, other models now include immortalised human beta cell lines and pluripotent stem cell-derived islet-like cells. The scarcity of human primary islet samples limits their use, but valuable gene expression and functional data from large collections of human islets have been made available to the scientific community. The possibilities for studying beta cell physiology using immortalised human beta cell lines and stem cell-derived islets are rapidly evolving. However, the functional immaturity of these cells is still a significant limitation. CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9) has enabled precise engineering of specific genetic variants, targeted transcriptional modulation and genome-wide genetic screening. These approaches can now be exploited to gain understanding of the mechanisms behind coding and non-coding diabetes-associated genetic variants, allowing more precise evaluation of their contribution to diabetes pathogenesis. Despite all the progress, genome editing in primary pancreatic islets remains difficult to achieve, an important limitation requiring further technological development.Peer reviewe

The insertion/deletion variation in the α(2B)-adrenoceptor does not seem to modify the risk for acute myocardial infarction, but may modify the risk for hypertension in sib-pairs from families with type 2 diabetes

BACKGROUND: An insertion/deletion polymorphism in the α(2B)-adrenoceptor (AR) has been associated with the risk for acute myocardial infarction (AMI) and sudden cardiac death. In this study we tested whether this polymorphism is associated with the risk for AMI among members of families with type 2 diabetes. METHODS: 154 subjects with a history of AMI were matched for age and sex with one of their siblings who did not have a history of AMI. The prevalence of the genotypes of the α(2B)-AR insertion/deletion polymorphism was compared between the siblings using McNemar's test. We also explored the data to see whether this genetic variation affects the risk for hypertension by using logistic regression models in the two subpopulations of subjects, with and without a history of AMI. RESULTS: Among all study subjects, 73 (24%) carried the α(2B)-AR deletion/deletion genotype, 103 (33%) carried the insertion/insertion genotype, and 132 (43%) were heterozygous. The distribution of genotypes of the α(2B)-AR insertion/deletion variation in the group of subjects with a history of AMI and their phenotype-discordant siblings did not statistically significantly differ from that expected by random distribution (p = 0.52): the deletion/deletion genotype was carried by 34 subjects with AMI (22%), and by 39 subjects without AMI (25%). Neither did we observe any significant difference in deletion allele frequencies of the α(2B)-AR insertion/deletion polymorphism between patients with a history of AMI (0.44) and their sib-pair controls (0.46, p = 0.65). In an exploratory analysis, the α(2B)-AR deletion/deletion genotype was associated with increased odds for hypertension compared with subjects carrying any of the other genotypes. CONCLUSIONS: The deletion/deletion genotype of the α(2B)-AR does not emerge in this study as a risk factor for AMI among members of families with type 2 diabetes; however, it might be involved in the development of hypertension