Physiologic characterization of type 2 diabetes-related loci

Applications of genomic research in pediatric endocrine diseases

Recent advances in molecular genetics have advanced our understanding of the molecular mechanisms involved in pediatric endocrine disorders and now play a major role in mainstream medical practice. The spectrum of endocrine genetic disorders has 2 extremes: Mendelian and polygenic. Mendelian or monogenic diseases are caused by rare variants of a single gene, each of which exerts a strong effect on disease risk. Polygenic diseases or common traits are caused by the combined effects of multiple genetic variants in conjunction with environmental and lifestyle factors. Testing for a single gene is preferable if the disease is phenotypically and/or geneically homogeneous. Next-generation sequencing (NGS) can be applied to phenotypically and genetically heterogeneous conditions. Genome-wide association studies (GWASs) have examined genetic variants across the entire genome in a large number of individuals who have been matched for population ancestry and assessed for a disease or trait of interest. Common endocrine diseases or traits, such as type 2 diabetes mellitus, obesity, height, and pubertal timing, result from the combined effects of multiple variants in various genes that are frequently found in the general population, each of which contributes a small individual effect. Isolated founder mutations can result from a true founder effect or an extreme reduction in population size. Studies of founder mutations offer powerful advantages for efficiently localizing the genes that underlie Mendelian disorders. The Korean population has settled in the Korean peninsula for thousands of years, and several recurrent mutations have been identified as founder mutations. The application of molecular technology has increased our understanding of endocrine diseases, which have impacted on the practice of pediatric endocrinology related to diagnosis and genetic counseling. This review focuses on the application of genomic research to pediatric endocrine diseases using GWASs and NGS technology for diagnosis and treatment.

Gene-environment interactions in the associations of PFAS exposure with insulin sensitivity and beta-cell function in a Faroese cohort followed from birth to adulthood

BACKGROUND

Exposure to perfluoroalkyl substances (PFAS) has been associated with changes in insulin sensitivity and pancreatic beta-cell function in humans. Genetic predisposition to diabetes may modify these associations; however, this hypothesis has not been yet studied.

OBJECTIVES

To evaluate genetic heterogeneity as a modifier in the PFAS association with insulin sensitivity and pancreatic beta-cell function, using a targeted gene-environment (GxE) approach.

METHODS

We studied 85 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes, in 665 Faroese adults born in 1986-1987. Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were measured in cord whole blood at birth and in participants' serum from age 28 years. We calculated the Matsuda-insulin sensitivity index (ISI) and the insulinogenic index (IGI) based on a 2 h-oral glucose tolerance test performed at age 28. Effect modification was evaluated in linear regression models adjusted for cross-product terms (PFAS*SNP) and important covariates.

RESULTS

Prenatal and adult PFOS exposures were significantly associated with decreased insulin sensitivity and increased beta-cell function. PFOA associations were in the same direction but attenuated compared to PFOS. A total of 58 SNPs were associated with at least one PFAS exposure variable and/or Matsuda-ISI or IGI in the Faroese population and were subsequently tested as modifiers in the PFAS-clinical outcome associations. Eighteen SNPs showed interaction p-values (PGxE) < 0.05 in at least one PFAS-clinical outcome association, five of which passed False Discovery Rate (FDR) correction (PGxE-FDR<0.20). SNPs for which we found stronger evidence for GxE interactions included ABCA1 rs3890182, FTO rs9939609, FTO rs3751812, PPARG rs170036314 and SLC12A3 rs2289116 and were more clearly shown to modify the PFAS associations with insulin sensitivity, rather than with beta-cell function.

DISCUSSION

Findings from this study suggest that PFAS-associated changes in insulin sensitivity could vary between individuals as a result of genetic predisposition and warrant replication in independent larger populations.

Genetic Ablation of the Nutrient Sensor Ogt in Endocrine Progenitors Is Dispensable for β-Cell Development but Essential for Maintenance of β-Cell Mass

Previously we utilized a murine model to demonstrate that Ogt deletion in pancreatic progenitors (OgtKOPanc) causes pancreatic hypoplasia, partly mediated by a reduction in the Pdx1-expressing pancreatic progenitor pool. Here, we continue to explore the role of Ogt in pancreas development by deletion of Ogt in the endocrine progenitors (OgtKOEndo). At birth OgtKOEndo, were normoglycemic and had comparable pancreas weight and α-cell, and β-cell mass to littermate controls. At postnatal day 23, OgtKOEndo displayed wide ranging but generally elevated blood glucose levels, with histological analyses showing aberrant islet architecture with α-cells invading the islet core. By postnatal day 60, these mice were overtly diabetic and showed significant loss of both α-cell and β-cell mass. Together, these results highlight the indispensable role of Ogt in maintenance of β-cell mass and glucose homeostasis.

Association of depression and parasympathetic activation with glycemic control in type 2 diabetes mellitus

AIM

Patients with type 2 diabetes mellitus exhibited autonomic nervous system (ANS) dysfunction and comorbidities with depressive or anxiety symptoms were related to poor glycemic control. Heart rate variability (HRV) converted from electrocardiogram (ECG) has been used as the ANS index. The study aimed to explore the associations between depression, anxiety, HRV, and glycemic control in patients with type 2 diabetes mellitus.

METHODS

The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) questionnaires were used to assess depressive and anxiety symptoms in 647 patients with type 2 diabetes mellitus (mean age was 63 ± 10 years, 56 % males). The ECG raw signals were collected from a 5-min sitting and resting baseline and then transformed to HRV indices referring ANS activation. Blood glucose and lipid profiles including glycated hemoglobin (HbA1c), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglyceride were obtained from the electronic medical records.

RESULTS

Ninety-nine (15 %) participants had depressive symptoms and 59 (9 %) had anxiety symptoms. Depression and HbA1c were negatively correlated with parasympathetic activation. Depression and anxiety were positively correlated with sympathetic activation. After controlling for demographic data and lipid profiles, depression was a significant positive predictor for HbA1c levels; and HRV indices (lnLF and lnHF) were the significant negative predictors for HbA1c levels. Mediation effect analysis showed that depression was a mediator between parasympathetic activation and glycemic control.

CONCLUSIONS

Lower parasympathetic activation and higher depressive symptoms may affect glycemic control in patients with type 2 diabetes mellitus. Intervention programs targeting to increase parasympathetic activities and reducing depression could be further tested for their effects on glycemic outcomes for potential clinical use.

Deep Resequencing of 9 Candidate Genes Identifies a Role for ARAP1 and IGF2BP2 in Modulating Insulin Secretion Adjusted for Insulin Resistance in Obese Southern Europeans

Type 2 diabetes is characterized by impairment in insulin secretion, with an established genetic contribution. We aimed to evaluate common and low-frequency (1–5%) variants in nine genes strongly associated with insulin secretion by targeted sequencing in subjects selected from the extremes of insulin release measured by the disposition index. Collapsing data by gene and/or function, the association between disposition index and nonsense variants were significant, also after adjustment for confounding factors (OR = 0.25, 95% CI = 0.11–0.59, p = 0.001). Evaluating variants individually, three novel variants in ARAP1, IGF2BP2 and GCK, out of eight reaching significance singularly, remained associated after adjustment. Constructing a genetic risk model combining the effects of the three variants, only carriers of the ARAP1 and IGF2BP2 variants were significantly associated with a reduced probability to be in the lower, worst, extreme of insulin secretion (OR = 0.223, 95% CI = 0.105–0.473, p < 0.001). Observing a high number of normal glucose tolerance between carriers, a regression posthoc analysis was performed. Carriers of genetic risk model variants had higher probability to be normoglycemic, also after adjustment (OR = 2.411, 95% CI = 1.136–5.116, p = 0.022). Thus, in our southern European cohort, nonsense variants in all nine candidate genes showed association with better insulin secretion adjusted for insulin resistance, and we established the role of ARAP1 and IGF2BP2 in modulating insulin secretion.

Predictive effect of GIPR SNP rs10423928 on glucose metabolism liver fat and adiposity in prediabetic and diabetic subjects

The gastric inhibitory polypeptide receptor (GIPR) regulates postprandial metabolism. In this context GIPR SNP rs10423928 seems toplay an important role in modulating glucose metabolism and insulinsensitivity. However, evidence regarding thisparticular SNP is still vague. In this study, we collected baseline data from four different dietaryintervention studies. We genotyped 424 subjects with prediabetes and 73with diabetes for GIPR SNP rs10423928 and examined its impact on glucosemetabolism, insulin sensitivity and body fat accumulation. We extended previous data by showing that carriers of the A allele withprediabetes displayed increased fasting glucose (p = 0.015). Unexpectedly,A allele carriers showed lower glucose levels 2 h (p = 0.021) after anoral glucose challenge compared to T/T homozygous individuals. A allelecarriers also showed significantly higher insulin sensitivity (p < 0.001)(assessed by Cederholm Index), indicating an enhanced ß-cell response. This study points to a potential protective role for rs10423928 inglucose metabolism and insulin sensitivity in subjects with prediabetes.Further studies are necessary to confirm these results.

Effects of variants of 50 genes on diabetes risk among the Chinese population born in the early 1960s

BACKGROUND

Genome-wide association studies have identified loci that significantly increase diabetes risk. This study explored the genetic susceptibility in relation to diabetes risk in adulthood among a Chinese population born in the early 1960s.

METHODS

In all, 2129 subjects (833 males, 1296 females) were selected from the cross-sectional 2010 to 2012 China National Nutrition and Health Survey. Fifty diabetes-related single nucleotide polymorphisms (SNPs) were detected. Two diabetes genetic risk scores (GRSs) based on the 50 diabetes-predisposing variants were developed to examine the association of these SNPs with diabetes risk.

RESULTS

Associations were found between diabetes risk and SNPs in the MTNR1B (rs10830963), KLHDC5 (rs10842994), GRK5 (rs10886471), cyclindependentkinase 5 regulatory subunit associated protein 1 (rs10946398), adaptorrelated protein complex 3 subunit sigma 2 (rs2028299), diacylglycerol kinase beta/transmembrane protein 195 (rs2191349), SREBF chaperone (rs4858889), ankyrin1 (rs516946), RAS guanyl releasing protein 1 (rs7403531), and zinc finger AN1-type containing 3 (rs9470794) genes. As a continuous variable, with a 1-point increase in the GRS or weighted (w) GRS, fasting plasma glucose (FPG) increased 0.045 and 0.044 mM, respectively (P < 0.001 for both), after adjusting for confounders. Both GRS and wGRS showed an association with diabetes, with a multivariable-adjusted odds ratio (95% confidence interval) of 1.09 (1.00-1.19) and 1.12 (1.03-1.22), respectively, among all subjects. No significant associations were found between the GRS or wGRS and impaired fasting glucose or impaired glucose tolerance.

CONCLUSIONS

The data suggest the association of 10 SNPs and the GRS or wGRS with diabetes risk. Genetic susceptibility to diabetes may synergistically affect the risk of diabetes in adulthood.

Cell- and tissue-specific epigenetic changes associated with chronic inflammation in insulin resistance and type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by hyperglycaemia, which can cause micro- and macrovascular complications. Chronic inflammation may be the cause and result of T2DM, and its related complications as an imbalance between pro- and anti-inflammatory cytokines can affect immune functions. Apart from genetic changes occurring within the body resulting in inflammation in T2DM, epigenetic modifications can modify gene expression in response to environmental cues such as an unhealthy diet, lack of exercise and obesity. The most widely studied epigenetic modification, DNA methylation (DNAm), regulates gene expression and may manipulate inflammatory genes to increase or decrease inflammation associated with T2DM. This review explores the studies related to epigenetic changes, more specifically DNAm, associated with chronic inflammation in T2DM, at both the cell and tissue levels. Studying epigenetic alterations during inflammatory response, as a result of genetic and environmental signals, creates opportunities for the development of "early detection/relative risk" tests to aid in prevention of T2DM. Understanding inflammation in T2DM at the gene level in inflammation-associated cells and tissues may provide further insight for the development of specific therapeutic targets for the disorder.

Autonomic Regulation of Glucose Homeostasis: a Specific Role for Sympathetic Nervous System Activation

PURPOSE OF REVIEW

Cardiometabolic disorders such as obesity, metabolic syndrome and diabetes are increasingly common and associated with adverse cardiovascular outcomes. The mechanisms driving these developments are incompletely understood but likely to include autonomic dysregulation. The latest evidence for such a role is briefly reviewed here.

RECENT FINDINGS

Recent findings highlight the relevance of autonomic regulation in glucose metabolism and identify sympathetic activation, in concert with parasympathetic withdrawal, as a major contributor to the development of metabolic disorders and an important mediator of the associated adverse cardiovascular consequences. Methods targeting sympathetic overactivity using pharmacological and device-based approaches are available and appear as logical additional approaches to curb the burden of metabolic disorders and alleviate the associated morbidity from cardiovascular causes. While the available data are encouraging, the role of therapeutic inhibition of sympathetic overdrive in the prevention of the metabolic disorders and the associated adverse outcomes requires adequate testing in properly sized randomised controlled trials.

A genetic risk score that includes common type 2 diabetes risk variants is associated with gestational diabetes

OBJECTIVE

Gestational diabetes (GDM) is characterized by maternal glucose intolerance that manifests during pregnancy. Because GDM resembles type 2 diabetes (T2DM), shared genetic predisposition is likely but has not been established. We tested the hypothesis that a genetic risk score (GRS) that included variants known to be associated with T2DM is associated with GDM.

STUDY DESIGN

We conducted a case-control study using the Vanderbilt Medical Center biobank (BioVU) and calculated a simple-count GRS using 34 variants previously associated with T2DM or fasting glucose in the general population, or with GDM or glucose intolerance in pregnancy. We assessed the association of the GRS with GDM adjusting for maternal age, parity, and body mass index (BMI) and calculated the area under the curve for the receiver-operating characteristic curve (c-statistic).

STUDY POPULATION

Among Caucasian women, we identified 458 cases of GDM and 1538 pregnant controls with normal glucose tolerance.

RESULTS

Cases of GDM had a higher number of risk alleles compared to controls (38.9±4.0 vs 37.4±4.0 risk alleles, P=1.6×10-11 ). The GRS was significantly associated with GDM; the adjusted odds ratio associated with each additional risk allele was 1.10 (95% CI: 1.07-1.13, P=6×10-11 ). Clinical variables predicted the risk of GDM (c-statistic 0.67, 95% CI: 0.64-0.70), and adding the GRS modestly improved prediction (0.70, 95% CI: 0.67-0.73).

CONCLUSIONS

Among Caucasian women, a GRS that included common T2DM genetic risk variants was associated with increased risk of GDM but showed limited utility in the identification of GDM cases.

Identification of Candidate Gene Variants in Korean MODY Families by Whole-Exome Sequencing

AIMS

To date, 13 genes causing maturity-onset diabetes of the young (MODY) have been identified. However, there is a big discrepancy in the genetic locus between Asian and Caucasian patients with MODY. Thus, we conducted whole-exome sequencing in Korean MODY families to identify causative gene variants.

METHODS

Six MODY probands and their family members were included. Variants in the dbSNP135 and TIARA databases for Koreans and the variants with minor allele frequencies >0.5% of the 1000 Genomes database were excluded. We selected only the functional variants (gain of stop codon, frameshifts and nonsynonymous single-nucleotide variants) and conducted a case-control comparison in the family members. The selected variants were scanned for the previously introduced gene set implicated in glucose metabolism.

RESULTS

Three variants c.620C>T:p.Thr207Ile in PTPRD, c.559C>G:p.Gln187Glu in SYT9, and c.1526T>G:p.Val509Gly in WFS1 were respectively identified in 3 families. We could not find any disease-causative alleles of known MODY 1-13 genes. Based on the predictive program, Thr207Ile in PTPRD was considered pathogenic.

CONCLUSIONS

Whole-exome sequencing is a valuable method for the genetic diagnosis of MODY. Further evaluation is necessary about the role of PTPRD, SYT9 and WFS1 in normal insulin release from pancreatic beta cells.

Genetic variants primarily associated with type 2 diabetes are related to coronary artery disease risk

BACKGROUND

The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well.

METHODS AND RESULTS

We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p < 5*10(-8)) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p < 0.05), more than expected by chance (p = 5.0*10(-5)). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973-1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p = 7.2*10(-10) vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD.

CONCLUSIONS

Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting.

Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium

Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D.

The type 2 diabetes risk allele of TMEM154-rs6813195 associates with decreased beta cell function in a study of 6,486 Danes

OBJECTIVES

A trans-ethnic meta-analysis of type 2 diabetes genome-wide association studies has identified seven novel susceptibility variants in or near TMEM154, SSR1/RREB1, FAF1, POU5F1/TCF19, LPP, ARL15 and ABCB9/MPHOSPH9. The aim of our study was to investigate associations between these novel risk variants and type 2 diabetes and pre-diabetic traits in a Danish population-based study with measurements of plasma glucose and serum insulin after an oral glucose tolerance test in order to elaborate on the physiological impact of the variants.

METHODS

Case-control analyses were performed in up to 5,777 patients with type 2 diabetes and 7,956 individuals with normal fasting glucose levels. Quantitative trait analyses were performed in up to 5,744 Inter99 participants naïve to glucose-lowering medication. Significant associations between TMEM154-rs6813195 and the beta cell measures insulinogenic index and disposition index and between FAF1-rs17106184 and 2-hour serum insulin levels were selected for further investigation in additional Danish studies and results were combined in meta-analyses including up to 6,486 Danes.

RESULTS

We confirmed associations with type 2 diabetes for five of the seven SNPs (TMEM154-rs6813195, FAF1-rs17106184, POU5F1/TCF19-rs3130501, ARL15-rs702634 and ABCB9/MPHOSPH9-rs4275659). The type 2 diabetes risk C-allele of TMEM154-rs6813195 associated with decreased disposition index (n=5,181, β=-0.042, p=0.012) and insulinogenic index (n=5,181, β=-0.032, p=0.043) in Inter99 and these associations remained significant in meta-analyses including four additional Danish studies (disposition index n=6,486, β=-0.042, p=0.0044; and insulinogenic index n=6,486, β=-0.037, p=0.0094). The type 2 diabetes risk G-allele of FAF1-rs17106184 associated with increased levels of 2-hour serum insulin (n=5,547, β=0.055, p=0.017) in Inter99 and also when combining effects with three additional Danish studies (n=6,260, β=0.062, p=0.0040).

CONCLUSION

Studies of type 2 diabetes intermediary traits suggest the diabetogenic impact of the C-allele of TMEM154-rs6813195 is mediated through reduced beta cell function. The impact of the diabetes risk G-allele of FAF1-rs17106184 on increased 2-hour insulin levels is however unexplained.

Diabetes mellitus: influences on cancer risk

Diabetes mellitus and cancer are common conditions, and their co-diagnosis in the same individual is not infrequent. The relative risks associated with type 2 diabetes are greater than twofold for hepatic, pancreatic, and endometrial cancers. The relative risk is somewhat lower, at 1.2-1.5-fold for colorectal, breast, and bladder cancers. In comparison, the relative risk of lung cancer is less than 1. The evidence for other malignancies (e.g. kidney, non-Hodgkin lymphoma) is inconclusive, whereas prostatic cancer occurs less frequently in male patients with diabetes. The potential biologic links between the two diseases are incompletely understood. Evidence from observational studies suggests that some medications used to treat hyperglycemia are associated with either increased or reduced risk of cancer. Whereas anti-diabetic drugs have a minor influence on cancer risk, drugs used to treat cancer may either cause diabetes or worsen pre-existing diabetes. If hyperinsulinemia acts as a critical link between the observed increased cancer risk and type 2 diabetes, one would predict that patients with type 1 diabetes would have a different cancer risk pattern than patients with type 2 diabetes because the former patients are exposed to lower levels of exogenous administered insulin. Obtained results showed that patients with type 1 diabetes had elevated risks of cancers of the stomach, cervix, and endometrium. Type 1 diabetes is associated with a modest excess cancer risk overall and risks of specific cancers that differ from those associated with type 2 diabetes.

A novel model enhances HbA1c-based diabetes screening using simple anthropometric, anamnestic, and demographic information

BACKGROUND

The sensitivity of HbA1c is not optimal for the screening of patients with latent diabetes. We hypothesize that simple healthcare information could improve accuracy.

METHODS

We retrospectively analyzed data, including HbA1c, from multiple years from the National Health and Nutrition Examination Survey (NHANES) database (2005-2010). The data were used to create a logistic regression classification model for screening purposes.

RESULTS

The study evaluated data for 5381 participants, including 404 with undiagnosed diabetes. The HbA1c screening data were supplemented with information about age, waist circumference, and physical activity in the HbA1c+ model. Alone, HbA1c alone had a receiver operating characteristics (ROC) curve for the area under the curve (AUC) of 0.808 (95% confidence interval [CI] 0.792-0.834). The HbA1c+ model had an ROC AUC of 0.851 (95% CI 0.843-0.872). There was a significant difference in the AUC between our model and using HbA1c without supplementary information (P < 0.05).

CONCLUSIONS

We have developed a novel screening model that could help improve screening for type 2 diabetes with HbA1c. It seems beneficial to systematically add additional patient healthcare information in the process of screening with HbA1c.

Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond

During the past 7 years, genome-wide association studies have shed light on the contribution of common genomic variants to the genetic architecture of type 2 diabetes, obesity and related intermediate phenotypes. The discoveries have firmly established more than 175 genomic loci associated with these phenotypes. Despite the tight correlation between type 2 diabetes and obesity, these conditions do not appear to share a common genetic background, since they have few genetic risk loci in common. The recent genetic discoveries do however highlight specific details of the interplay between the pathogenesis of type 2 diabetes, insulin resistance and obesity. The focus is currently shifting towards investigations of data from targeted array-based genotyping and exome and genome sequencing to study the individual and combined effect of low-frequency and rare variants in metabolic disease. Here we review recent progress as regards the concepts, methodologies and derived outcomes of studies of the genetics of type 2 diabetes and obesity, and discuss avenues to be investigated in the future within this research field.

Novel approaches to drug discovery for the treatment of type 2 diabetes

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a chronic, complex and multifactorial metabolic disorder, which has become a serious global health problem. The side effects of known drugs and the deficiency of long-term safety data, in addition to the already determined adverse effects for the current preclinical drugs against T2DM, have largely called upon the urgent exploration of novel therapeutic and preventative strategies against this disease.

AREAS COVERED

The authors highlight the potential approaches for anti-T2DM drug discovery by focusing on: the restoration of pancreatic β-cell mass, the promotion of insulin secretion, the regulation of oxidative stress and endoplasmic reticulum (ER) stress and the modulation of autophagy.

EXPERT OPINION

T2DM is based on the gradual development of insulin resistance and β-cell dysfunction. Thus, the restoration of β-cell function is considered as one of the promising therapeutic strategies against T2DM. The stress factors, such as oxidative stress, ER stress and autophagy, play potent roles in the regulation of β-cell apoptosis, insulin secretion and sensitivity in the development of T2DM involving complicated cross-talks. Based on multiplex stress-involved regulatory networks, more and more novel potential targets have been discovered and the multi-targeted drug leads are expected to help develop more effective clinical agents for the treatment of T2DM.

A computational approach to chemical etiologies of diabetes

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals, and offers thus promising guidance for future research in regard to the etiology and pathogenesis of complex diseases.

Improved diabetes screening using an extended predictive feature search

BACKGROUND

Screening entire populations for diabetes is not cost-effective. Hence, an efficient screening process must select those people who are at high risk for diabetes. In this study, we investigated whether screening procedures could be improved using an extended predictive feature search.

MATERIALS AND METHODS

In order to develop our model and identify persons with diabetes (prevalence) we used data from years of the National Health and Nutrition Examination Survey (2005-2010), which has not been explored for this purpose before. We calculated all combinations of predictors in order to identify the optimal subset, and we used a linear logistic classification model to predict diabetes. V-fold cross-validation was used for the process of including variables and for validating the final models. This new model was compared with two established models.

RESULTS

In total, 5,398 participants were included in this study. Among these, 478 participants had unidentified diabetes. The established models had a receiver operating characteristics curve for the area under the curve (AUC) of 0.74 and 0.71 compared with an AUC of 0.78 for the new model, showing a significant difference (P<0.05). A proposed cutoff point for the established models yielded respective sensitivities/specificities of 63%/72% and 40%/72% compared with the new model, which had a sensitivity/specificity of 70%/72%.

CONCLUSIONS

Our data indicate that simple healthcare and economic information such as ratio of family income to poverty can add value in deciding who is at risk of unknown diabetes by using extended investigations of predictor combinations.

The future for genetic studies in reproduction

Genetic factors contribute to risk of many common diseases affecting reproduction and fertility. In recent years, methods for genome-wide association studies (GWAS) have revolutionized gene discovery for common traits and diseases. Results of GWAS are documented in the Catalog of Published Genome-Wide Association Studies at the National Human Genome Research Institute and report over 70 publications for 32 traits and diseases associated with reproduction. These include endometriosis, uterine fibroids, age at menarche and age at menopause. Results that pass appropriate stringent levels of significance are generally well replicated in independent studies. Examples of genetic variation affecting twinning rate, infertility, endometriosis and age at menarche demonstrate that the spectrum of disease-related variants for reproductive traits is similar to most other common diseases. GWAS 'hits' provide novel insights into biological pathways and the translational value of these studies lies in discovery of novel gene targets for biomarkers, drug development and greater understanding of environmental factors contributing to disease risk. Results also show that genetic data can help define sub-types of disease and co-morbidity with other traits and diseases. To date, many studies on reproductive traits have used relatively small samples. Future genetic marker studies in large samples with detailed phenotypic and clinical information will yield new insights into disease risk, disease classification and co-morbidity for many diseases associated with reproduction and infertility.

Studies of association of AGPAT6 variants with type 2 diabetes and related metabolic phenotypes in 12,068 Danes

Background

Type 2 diabetes, obesity and insulin resistance are characterized by hypertriglyceridemia and ectopic accumulation of lipids in liver and skeletal muscle. AGPAT6 encodes a novel glycerol-3 phosphate acyltransferase, GPAT4, which catalyzes the first step in the de novo triglyceride synthesis. AGPAT6-deficient mice show lower weight and resistance to diet- and genetically induced obesity. Here, we examined whether common or low-frequency variants in AGPAT6 associate with type 2 diabetes or related metabolic traits in a Danish population.

Methods

Eleven variants selected by a candidate gene approach capturing the common and low-frequency variation of AGPAT6 were genotyped in 12,068 Danes from four study populations of middle-aged individuals. The case–control study involved 4,638 type 2 diabetic and 5,934 glucose-tolerant individuals, while studies of quantitative metabolic traits were performed in 5,645 non-diabetic participants of the Inter99 Study.

Results

None of the eleven AGPAT6 variants were robustly associated with type 2 diabetes in the Danish case–control study. Moreover, none of the AGPAT6 variants showed association with measures of obesity (waist circumference and BMI), serum lipid concentrations, fasting or 2-h post-glucose load levels of plasma glucose and serum insulin, or estimated indices of insulin secretion or insulin sensitivity.

Conclusions

Common and low-frequency variants in AGPAT6 do not significantly associate with type 2 diabetes susceptibility, or influence related phenotypic traits such as obesity, dyslipidemia or indices of insulin sensitivity or insulin secretion in the population studied.

Genetic risk score of 46 type 2 diabetes risk variants associates with changes in plasma glucose and estimates of pancreatic β-cell function over 5 years of follow-up

More than 40 genetic risk variants for type 2 diabetes have been validated. We aimed to test whether a genetic risk score associates with the incidence of type 2 diabetes and with 5-year changes in glycemic traits and whether the effects were modulated by changes in BMI and lifestyle. The Inter99 study population was genotyped for 46 variants, and a genetic risk score was constructed. During a median follow-up of 11 years, 327 of 5,850 individuals developed diabetes. Physical examinations and oral glucose tolerance tests were performed at baseline and after 5 years (n = 3,727). The risk of incident type 2 diabetes was increased with a hazard ratio of 1.06 (95% CI 1.03-1.08) per risk allele. While the population in general had improved glucose regulation during the 5-year follow-up period, each additional allele in the genetic risk score was associated with a relative increase in fasting, 30-min, and 120-min plasma glucose values and a relative decrease in measures of β-cell function over the 5-year period, whereas indices of insulin sensitivity were unaffected. The effect of the genetic risk score on 5-year changes in fasting plasma glucose was stronger in individuals who increased their BMI. In conclusion, a genetic risk score based on 46 variants associated strongly with incident type 2 diabetes and 5-year changes in plasma glucose and β-cell function. Individuals who gain weight may be more susceptible to the cumulative impact of type 2 diabetes risk variants on fasting plasma glucose.

Effects of common genetic variants associated with type 2 diabetes and glycemic traits on α- and β-cell function and insulin action in humans

Although meta-analyses of genome-wide association studies have identified >60 single nucleotide polymorphisms (SNPs) associated with type 2 diabetes and/or glycemic traits, there is little information on whether these variants also affect α-cell function. The aim of the current study was to evaluate the effects of glycemia-associated genetic loci on islet function in vivo and in vitro. We studied 43 SNPs in 4,654 normoglycemic participants from the Finnish population-based Prevalence, Prediction, and Prevention of Diabetes-Botnia (PPP-Botnia) Study. Islet function was assessed, in vivo, by measuring insulin and glucagon concentrations during oral glucose tolerance test, and, in vitro, by measuring glucose-stimulated insulin and glucagon secretion from human pancreatic islets. Carriers of risk variants in BCL11A, HHEX, ZBED3, HNF1A, IGF1, and NOTCH2 showed elevated whereas those in CRY2, IGF2BP2, TSPAN8, and KCNJ11 showed decreased fasting and/or 2-h glucagon concentrations in vivo. Variants in BCL11A, TSPAN8, and NOTCH2 affected glucagon secretion both in vivo and in vitro. The MTNR1B variant was a clear outlier in the relationship analysis between insulin secretion and action, as well as between insulin, glucose, and glucagon. Many of the genetic variants shown to be associated with type 2 diabetes or glycemic traits also exert pleiotropic in vivo and in vitro effects on islet function.

Diabetes genetic predisposition score and cardiovascular complications among patients with type 2 diabetes

OBJECTIVE

To examine the association between genetic predisposition to type 2 diabetes (T2D) and risk of cardiovascular disease (CVD) among patients with T2D.

RESEARCH DESIGN AND METHODS

The current study included 1,012 men and 1,310 women with T2D from the Health Professionals Follow-up Study and Nurses' Health Study, including 677 patients with CVD and 1,645 non-CVD control subjects. A genetic predisposition score (GPS) was calculated on the basis of 36 established independent diabetes-predisposing variants.

RESULTS

Each additional diabetes-risk allele in the GPS was associated with a 3% increased risk of CVD (odds ratio [OR] 1.03 [95% CI 1.00-1.06]). The OR was 1.47 (1.11-1.95) for CVD risk by comparing extreme quartiles of the GPS (P for trend = 0.01). We also found that the GPS was positively associated with hemoglobin A(1c) levels (P = 0.009).

CONCLUSIONS

Genetic predisposition to T2D is associated with an increased risk of cardiovascular complications in patients with T2D.

Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes

AIMS/HYPOTHESIS

Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes.

METHODS

The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans.

RESULTS

Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)).

CONCLUSIONS/INTERPRETATION

We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits.

Association of type 2 diabetes susceptibility variants with advanced prostate cancer risk in the Breast and Prostate Cancer Cohort Consortium

Observational studies have found an inverse association between type 2 diabetes (T2D) and prostate cancer (PCa), and genome-wide association studies have found common variants near 3 loci associated with both diseases. The authors examined whether a genetic background that favors T2D is associated with risk of advanced PCa. Data from the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium, a genome-wide association study of 2,782 advanced PCa cases and 4,458 controls, were used to evaluate whether individual single nucleotide polymorphisms or aggregations of these 36 T2D susceptibility loci are associated with PCa. Ten T2D markers near 9 loci (NOTCH2, ADCY5, JAZF1, CDKN2A/B, TCF7L2, KCNQ1, MTNR1B, FTO, and HNF1B) were nominally associated with PCa (P < 0.05); the association for single nucleotide polymorphism rs757210 at the HNF1B locus was significant when multiple comparisons were accounted for (adjusted P = 0.001). Genetic risk scores weighted by the T2D log odds ratio and multilocus kernel tests also indicated a significant relation between T2D variants and PCa risk. A mediation analysis of 9,065 PCa cases and 9,526 controls failed to produce evidence that diabetes mediates the association of the HNF1B locus with PCa risk. These data suggest a shared genetic component between T2D and PCa and add to the evidence for an interrelation between these diseases.

Genetic variant SLC2A2 [corrected] Is associated with risk of cardiovascular disease – assessing the individual and cumulative effect of 46 type 2 diabetes related genetic variants

Aim

To assess the individual and combined effect of 46 type 2 diabetes related risk alleles on incidence of a composite CVD endpoint.

Methods

Data from the first Danish MONICA study (N = 3523) and the Inter99 study (N = 6049) was used. Using Cox proportional hazard regression the individual effect of each risk allele on incident CVD was analyzed. Risk was presented as hazard ratios (HR) per risk allele.

Results

During 80,859 person years 1441 incident cases of CVD (fatal and non-fatal) occurred in the MONICA study. In Inter99 942 incident cases were observed during 61,239 person years.

In the Danish MONICA study four gene variants were significantly associated with incident CVD independently of known diabetes status at baseline; SLC2A2 rs11920090 (HR 1.147, 95% CI 1.027–1.283 , P = 0.0154), C2CD4A rs7172432 (1.112, 1.027–1.205 , P = 0.0089), GCKR rs780094 (1.094, 1.007–1.188 , P = 0.0335) and C2CD4B rs11071657 (1.092, 1.007–1.183 , P = 0.0323). The genetic score was significantly associated with increased risk of CVD (1.025, 1.010–1.041, P = 0.0016). In Inter99 two gene variants were associated with risk of CVD independently of diabetes; SLC2A2 (HR 1.180, 95% CI 1.038–1.341 P = 0.0116) and FTO (0.909, 0.827–0.998, P = 0.0463). Analysing the two populations together we found SLC2A2 rs11920090 (HR 1.164, 95% CI 1.070–1.267, P = 0.0004) meeting the Bonferroni corrected threshold for significance. GCKR rs780094 (1.076, 1.010–1.146, P = 0.0229), C2CD4B rs11071657 (1.067, 1.003–1.135, P = 0.0385) and NOTCH2 rs10923931 (1.104 (1.001 ; 1.217 , P = 0.0481) were found associated with CVD without meeting the corrected threshold. The genetic score was significantly associated with increased risk of CVD (1.018, 1.006–1.031, P = 0.0043).

Conclusions

This study showed that out of the 46 genetic variants examined only the minor risk allele of SLC2A2 rs11920090 was significantly (P = 0.0005) associated with a composite endpoint of incident CVD below the threshold for statistical significance corrected for multiple testing. This potential pathway needs further exploration.

The Danish Centre for Strategic Research in Type 2 Diabetes (DD2) Project: rationale and planned nationwide studies of genetic predictors, physical exercise, and individualized pharmacological treatment

Here we provide an overview of the rationale and methods of a series of planned population based studies within the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) Project. The project aims to support and evaluate ongoing political and administrative efforts to implement nationwide guidelines for maintaining metabolic control in newly diagnosed type 2 diabetes (T2D) patients to prevent diabetic complications and improve quality of life. The DD2 is designed as a prospective cohort study (collection of epidemiological data) supplemented by randomized clinical intervention trials (on physical exercise and individualized pharmacological treatment) and the establishment of a biobank comprised of material from a large number of newly diagnosed T2D patients. Inclusion of the majority of newly diagnosed T2D patients as they are diagnosed at their general practitioner or diabetes hospital outpatient clinics and entered into the DD2 cohort will establish a nationwide database comprising a large number of future incident cases of T2D in Denmark. These cases will form the project cohort of the DD2. Within the first 6 months of diagnosis, all patients will be invited to contribute to a biobank of DNA, plasma, urine, and tissue sampling. The DNA biobank will enable future studies of the effect of pharmacological treatment and outcome in subsets of patients with specific genetic risk profiles covering disease etiology and specific drug kinetics and metabolism. We will also perform two clinical intervention trials examining: the effectiveness of physical exercise on diabetes-related outcomes and the impact of trial outcomes on individualized pharmacological treatment. Moreover, the DD2 will serve as a platform for testing and developing new antidiabetic drugs. All together, we expect this study to contribute to substantially improved diabetes care in T2D patients locally and abroad.

'Omics'-driven discoveries in prevention and treatment of type 2 diabetes

Eur J Clin Invest 2012; 42 (6): 579-588 ABSTRACT: Glucose-based methods are currently gold standards for identifying individuals at risk of type 2 diabetes. Obviously, these methods only consider one of many pathologies of impaired glucose metabolism and they all suffer from a poor specificity as type 2 diabetes risk assessment tools. Recently, however, panels of multiple biomarkers reflecting several pre-diabetic pathologies have been developed. Their specificity and potentials for future risk stratification are discussed. As a multifactorial disorder type 2 diabetes calls for a multifactorial treatment approach targeting multiple but modifiable vascular risk factors. The same holds for pre-diabetic states and prevention hereof. In addition, type 2 diabetes and pre-diabetes show major heterogeneity between affected individuals in pathology, risk of organ damages, progression rate and responsiveness to treatment or prevention. Despite the heterogeneity and uniqueness of type 2 diabetes and pre-diabetes most affected individuals are currently offered interventions as if they all have the same disease or risk of disease and will respond similarly. The complex origin and course of type 2 diabetes combined with uniformity and non-specificity of current interventions may explain the high rate of treatment failures and the relative poor prognosis of many diabetes patients. Given this situation, the present review also explores the perspectives of selected examples within applied genomics and metagenomics for improving patient care by facilitating interventions tailored to specific subpopulations.

Exome sequencing and genetic testing for MODY

CONTEXT

Genetic testing for monogenic diabetes is important for patient care. Given the extensive genetic and clinical heterogeneity of diabetes, exome sequencing might provide additional diagnostic potential when standard Sanger sequencing-based diagnostics is inconclusive.

OBJECTIVE

The aim of the study was to examine the performance of exome sequencing for a molecular diagnosis of MODY in patients who have undergone conventional diagnostic sequencing of candidate genes with negative results.

RESEARCH DESIGN AND METHODS

We performed exome enrichment followed by high-throughput sequencing in nine patients with suspected MODY. They were Sanger sequencing-negative for mutations in the HNF1A, HNF4A, GCK, HNF1B and INS genes. We excluded common, non-coding and synonymous gene variants, and performed in-depth analysis on filtered sequence variants in a pre-defined set of 111 genes implicated in glucose metabolism.

RESULTS

On average, we obtained 45 X median coverage of the entire targeted exome and found 199 rare coding variants per individual. We identified 0-4 rare non-synonymous and nonsense variants per individual in our a priori list of 111 candidate genes. Three of the variants were considered pathogenic (in ABCC8, HNF4A and PPARG, respectively), thus exome sequencing led to a genetic diagnosis in at least three of the nine patients. Approximately 91% of known heterozygous SNPs in the target exomes were detected, but we also found low coverage in some key diabetes genes using our current exome sequencing approach. Novel variants in the genes ARAP1, GLIS3, MADD, NOTCH2 and WFS1 need further investigation to reveal their possible role in diabetes.

CONCLUSION

Our results demonstrate that exome sequencing can improve molecular diagnostics of MODY when used as a complement to Sanger sequencing. However, improvements will be needed, especially concerning coverage, before the full potential of exome sequencing can be realized.

Genetic determinants of glucose homeostasis

Type 2 diabetes is a complex metabolic disorder characterised by varying degrees of impairment in insulin secretion and resistance to the action of insulin. Considerable progress has been made recently in understanding the genetic determinants of diabetes. A logical next step is to describe how these variants relate to the underlying pathophysiological processes that lead to diabetes as this may provide insights into pathways to disease. These quantitative traits are, of course, of direct interest in themselves and a growing literature is now emerging on the genetic determinants of insulin secretion and insulin resistance. This review article focuses on describing the complex associations between type 2 diabetes risk variants and quantitative glycaemic traits and the relationship between variants initially discovered in association studies of these traits and risk of type 2 diabetes.

Common variation in oxidative phosphorylation genes is not a major cause of insulin resistance or type 2 diabetes

AIMS/HYPOTHESIS

There is substantial evidence that mitochondrial dysfunction is linked to insulin resistance and is present in several tissues relevant to the pathogenesis of type 2 diabetes. Here, we examined whether common variation in genes involved in oxidative phosphorylation (OxPhos) contributes to type 2 diabetes susceptibility or influences diabetes-related metabolic traits.

METHODS

OxPhos gene variants (n = 10) that had been nominally associated (p < 0.01) with type 2 diabetes in a recent genome-wide meta-analysis (n = 10,108) were selected for follow-up in 3,599 type 2 diabetic and 4,956 glucose-tolerant Danish individuals. A meta-analysis of these variants was performed in 11,729 type 2 diabetic patients and 43,943 non-diabetic individuals. The impact on OGTT-derived metabolic traits was evaluated in 5,869 treatment-naive individuals from the Danish Inter99 study.

RESULTS

The minor alleles of COX10 rs9915302 (p = 0.02) and COX5B rs1466100 (p = 0.005) showed nominal association with type 2 diabetes in our Danish cohort. However, in the meta-analysis, none of the investigated variants showed a robust association with type 2 diabetes after correction for multiple testing. Among the alleles potentially associated with type 2 diabetes, none negatively influenced surrogate markers of insulin sensitivity in non-diabetic participants, while the minor alleles of UQCRC1 rs2228561 and COX10 rs10521253 showed a weak (p < 0.01 to p < 0.05) negative influence on indices of glucose-stimulated insulin secretion.

CONCLUSIONS/INTERPRETATION

We cannot rule out the possibility that common variants in or near OxPhos genes may influence beta cell function in non-diabetic individuals. However, our quantitative trait studies and a sufficiently large meta-analysis indicate that common variation in proximity to the examined OxPhos genes is not a major cause of insulin resistance or type 2 diabetes.

The TALLYHO mouse as a model of human type 2 diabetes

The TALLYHO/Jng (TH) mouse is an inbred polygenic model for type 2 diabetes (T2D) with moderate obesity. Both male and female TH mice are characterized by increased body and fat pad weights, hyperleptinemia, hyperinsulinemia, and hyperlipidemia. Glucose intolerance and hyperglycemia are exhibited only in males. Reduced 2-deoxy-glucose uptake occurs in adipose tissue and skeletal muscle of male TH mice. While both sexes of TH mice exhibit enlarged pancreatic islets, only males have degranulation and abnormal architecture in islets. Endothelial dysfunction and considerably decreased bone density are also observed in male TH mice. The blood pressure of male TH mice is normal. Genetic outcross experiments with non-diabetic strains revealed multiple susceptibility loci (quantitative trait loci) for obesity, hypertriglyceridemia, hypercholesterolemia, and hyperglycemia. In conclusion, TH mice encompass many aspects of polygenic human diabetes and are a very useful model for T2D.

Central insulin and leptin-mediated autonomic control of glucose homeostasis

Largely as a result of rising obesity rates, the incidence of type 2 diabetes is escalating rapidly. Type 2 diabetes results from multi-organ dysfunctional glucose metabolism. Recent publications have highlighted hypothalamic insulin- and adipokine-sensing as a major determinant of peripheral glucose and insulin responsiveness. The preponderance of evidence indicates that the brain is the master regulator of glucose homeostasis, and that hypothalamic insulin and leptin signaling in particular play a crucial role in the development of insulin resistance. This review discusses the neuronal crosstalk between the hypothalamus, autonomic nervous system, and tissues associated with the pathogenesis of type 2 diabetes, and how hypothalamic insulin and leptin signaling are integral to maintaining normal glucose homeostasis.

Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile

Genome-wide association studies have identified 32 loci influencing body mass index, but this measure does not distinguish lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ∼2.5 million SNPs and body fat percentage from 36,626 individuals and followed up the 14 most significant (P < 10(-6)) independent loci in 39,576 individuals. We confirmed a previously established adiposity locus in FTO (P = 3 × 10(-26)) and identified two new loci associated with body fat percentage, one near IRS1 (P = 4 × 10(-11)) and one near SPRY2 (P = 3 × 10(-8)). Both loci contain genes with potential links to adipocyte physiology. Notably, the body-fat-decreasing allele near IRS1 is associated with decreased IRS1 expression and with an impaired metabolic profile, including an increased visceral to subcutaneous fat ratio, insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.