This 24-week trial assessed the efficacy and safety of saxagliptin as add-on therapy in patients with type 2 diabetes with inadequate glycemic control with metformin alone.

OBJECTIVE Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action. RESEARCH DESIGN AND METHODS We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084). RESULTS The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 x 10(-71)). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction. CONCLUSIONS Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.

The RETN gene encodes the adipokine resistin. Associations of RETN with plasma resistin levels, type 2 diabetes, and related metabolic traits have been inconsistent. Using comprehensive linkage disequilibrium mapping, we genotyped tag single nucleotide polymorphisms (SNPs) in RETN and tested associations with plasma resistin levels, risk of diabetes, and glycemic traits.

Ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) inhibits insulin-receptor (IR) signaling and, when over-expressed, induces insulin resistance in vitro and in vivo. Understanding the regulation of ENPP1 expression may, thus, unravel new molecular mechanisms of insulin resistance. Recent data point to a pivotal role of the ENPP1 3'UTR, in modulating ENPP1 mRNA stability and expression. We sought to identify trans-acting proteins binding the ENPP1-3'UTR and to investigate their role on ENPP1 expression and on IR signaling. By RNA electrophoresis mobility shift analysis and tandem mass spectrometry, we demonstrated the binding of heat shock protein 70 (HSP70) to ENPP1-3'UTR. Through this binding, HSP70 stabilizes ENPP1 mRNA and increases ENPP1 transcript and protein levels. This positive modulation of ENPP1 expression is paralleled by a reduced insulin-induced IR and IRS-1 phosphorylation. Taken together these data suggest that HSP70, by affecting ENPP1 expression, may be a novel mediator of altered insulin signaling.

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.

Epigenetic modifications such as DNA methylation play a key role in gene regulation and disease susceptibility. However, little is known about the genome-wide frequency, localization, and function of methylation variation and how it is regulated by genetic and environmental factors. We utilized the Multiple Tissue Human Expression Resource (MuTHER) and generated Illumina 450K adipose methylome data from 648 twins. We found that individual CpGs had low variance and that variability was suppressed in promoters. We noted that DNA methylation variation was highly heritable (h(2)median = 0.34) and that shared environmental effects correlated with metabolic phenotype-associated CpGs. Analysis of methylation quantitative-trait loci (metQTL) revealed that 28% of CpGs were associated with nearby SNPs, and when overlapping them with adipose expression quantitative-trait loci (eQTL) from the same individuals, we found that 6% of the loci played a role in regulating both gene expression and DNA methylation. These associations were bidirectional, but there were pronounced negative associations for promoter CpGs. Integration of metQTL with adipose reference epigenomes and disease associations revealed significant enrichment of metQTL overlapping metabolic-trait or disease loci in enhancers (the strongest effects were for high-density lipoprotein cholesterol and body mass index [BMI]). We followed up with the BMI SNP rs713586, a cg01884057 metQTL that overlaps an enhancer upstream of ADCY3, and used bisulphite sequencing to refine this region. Our results showed widespread population invariability yet sequence dependence on adipose DNA methylation but that incorporating maps of regulatory elements aid in linking CpG variation to gene regulation and disease risk in a tissue-dependent manner.

Plasma adiponectin levels are reduced in type 2 diabetes mellitus (T2DM) and other insulin-resistant states. We examined whether plasma adiponectin levels at baseline and after pioglitazone treatment in impaired glucose tolerance (IGT) subjects were associated with improved insulin sensitivity (SI) and glucose tolerance status.

Despite their nearly identical genomes, males and females differ in risk, incidence, prevalence, severity and age-at-onset of many diseases. Sexual dimorphism is also seen in human autosomal gene expression, and has largely been explored by examining the contribution of genotype-by-sex interactions to variation in gene expression.

The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data.

Emerging evidence suggests that TLR (Toll-like receptor) 4 and downstream pathways [MAPKs (mitogen-activated protein kinases) and NF-κB (nuclear factor κB)] play an important role in the pathogenesis of insulin resistance. LPS (lipopolysaccharide) and saturated NEFA (non-esterified fatty acids) activate TLR4, and plasma concentrations of these TLR4 ligands are elevated in obesity and Type 2 diabetes. Our goals were to define the role of TLR4 on the insulin resistance caused by LPS and saturated NEFA, and to dissect the independent contribution of LPS and NEFA to the activation of TLR4-driven pathways by employing TAK-242, a specific inhibitor of TLR4. LPS caused robust activation of the MAPK and NF-κB pathways in L6 myotubes, along with impaired insulin signalling and glucose transport. TAK-242 completely prevented the inflammatory response (MAPK and NF-κB activation) caused by LPS, and, in turn, improved LPS-induced insulin resistance. Similar to LPS, stearate strongly activated MAPKs, although stimulation of the NF-κB axis was modest. As seen with LPS, the inflammatory response caused by stearate was accompanied by impaired insulin action. TAK-242 also blunted stearate-induced inflammation; yet, the protective effect conferred by TAK-242 was partial and observed only on MAPKs. Consequently, the insulin resistance caused by stearate was only partially improved by TAK-242. In summary, TAK-242 provides complete and partial protection against LPS- and NEFA-induced inflammation and insulin resistance, respectively. Thus, LPS-induced insulin resistance depends entirely on TLR4, whereas NEFA works through TLR4-dependent and -independent mechanisms to impair insulin action.

Using an integrative approach in which genetic variation, gene expression, and clinical phenotypes are assessed in relevant tissues may help functionally characterize the contribution of genetics to disease susceptibility. We sought to identify genetic variation influencing skeletal muscle gene expression (expression quantitative trait loci [eQTLs]) as well as expression associated with measures of insulin sensitivity. We investigated associations of 3,799,401 genetic variants in expression of >7,000 genes from three cohorts (n = 104). We identified 287 genes with cis-acting eQTLs (false discovery rate [FDR] <5%; P < 1.96 × 10(-5)) and 49 expression-insulin sensitivity phenotype associations (i.e., fasting insulin, homeostasis model assessment-insulin resistance, and BMI) (FDR <5%; P = 1.34 × 10(-4)). One of these associations, fasting insulin/phosphofructokinase (PFKM), overlaps with an eQTL. Furthermore, the expression of PFKM, a rate-limiting enzyme in glycolysis, was nominally associated with glucose uptake in skeletal muscle (P = 0.026; n = 42) and overexpressed (Bonferroni-corrected P = 0.03) in skeletal muscle of patients with T2D (n = 102) compared with normoglycemic controls (n = 87). The PFKM eQTL (rs4547172; P = 7.69 × 10(-6)) was nominally associated with glucose uptake, glucose oxidation rate, intramuscular triglyceride content, and metabolic flexibility (P = 0.016-0.048; n = 178). We explored eQTL results using published data from genome-wide association studies (DIAGRAM and MAGIC), and a proxy for the PFKM eQTL (rs11168327; r(2) = 0.75) was nominally associated with T2D (DIAGRAM P = 2.7 × 10(-3)). Taken together, our analysis highlights PFKM as a potential regulator of skeletal muscle insulin sensitivity.

Insulin replacement therapy is essential in type 1 diabetic individuals and is required in ~40- 50% of type 2 diabetics during their lifetime. Prior attempts at beta cell regeneration have relied upon pancreatic injury to induce beta cell proliferation, dedifferentiation and activation of the embryonic pathway, or stem cell replacement. We report an alternative method to transform adult non-stem (somatic) cells into pancreatic beta cells. The Cellular Networking, Integration and Processing (CNIP) approach targets cellular mechanisms involved in pancreatic function in the organ's adult state and utilizes a synergistic mechanism that integrates three important levels of cellular regulation to induce beta cell formation: (i) glucose metabolism, (ii) membrane receptor function, and (iii) gene transcription. The aim of the present study was to induce pancreatic beta cell formation in vivo in adult animals without stem cells and without dedifferentiating cells to recapitulate the embryonic pathway as previously published (1-3). Our results employing CNIP demonstrate that: (i) insulin secreting cells can be generated in adult pancreatic tissue in vivo and circumvent the problem of generating endocrine (glucagon and somatostatin) cells that exert deleterious effects on glucose homeostasis, and (ii) longterm normalization of glucose tolerance and insulin secretion can be achieved in a wild type diabetic mouse model. The CNIP cocktail has the potential to be used as a preventative or therapeutic treatment or cure for both type 1 and type 2 diabetes.

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

Type 2 diabetes (T2D) is a common, multifactorial disease that is influenced by genetic and environmental factors and their interactions. However, common variants identified by genome wide association studies (GWAS) explain only about 10% of the total trait variance for T2D and less than 5% of the variance for obesity, indicating that a large proportion of heritability is still unexplained. The transcriptomic approach described here uses quantitative gene expression and disease-related physiological data (deep phenotyping) to measure the direct correlation between the expression of specific genes and physiological traits. Transcriptomic analysis bridges the gulf between GWAS and physiological studies. Recent GWAS studies have utilized very large population samples, numbering in the tens of thousands (or even hundreds of thousands) of individuals, yet establishing causal functional relationships between strongly associated genetic variants and disease remains elusive. In light of the findings described below, it is appropriate to consider how and why transcriptomic approaches in small samples might be capable of identifying complex disease-related genes which are not apparent using GWAS in large samples.

Small RNAs are functional molecules that modulate mRNA transcripts and have been implicated in the aetiology of several common diseases. However, little is known about the extent of their variability within the human population. Here, we characterise the extent, causes, and effects of naturally occurring variation in expression and sequence of small RNAs from adipose tissue in relation to genotype, gene expression, and metabolic traits in the MuTHER reference cohort. We profiled the expression of 15 to 30 base pair RNA molecules in subcutaneous adipose tissue from 131 individuals using high-throughput sequencing, and quantified levels of 591 microRNAs and small nucleolar RNAs. We identified three genetic variants and three RNA editing events. Highly expressed small RNAs are more conserved within mammals than average, as are those with highly variable expression. We identified 14 genetic loci significantly associated with nearby small RNA expression levels, seven of which also regulate an mRNA transcript level in the same region. In addition, these loci are enriched for variants significant in genome-wide association studies for body mass index. Contrary to expectation, we found no evidence for negative correlation between expression level of a microRNA and its target mRNAs. Trunk fat mass, body mass index, and fasting insulin were associated with more than twenty small RNA expression levels each, while fasting glucose had no significant associations. This study highlights the similar genetic complexity and shared genetic control of small RNA and mRNA transcripts, and gives a quantitative picture of small RNA expression variation in the human population.

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 × 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 × 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-β1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 × 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Non-alcoholic fatty liver disease (NAFLD) is characterized by accumulation of triglycerides (TG) in hepatocytes, which may also trigger cirrhosis. The mechanisms of NAFLD are not fully understood, but insulin resistance has been proposed as a key determinant.

The sequence of Ciona savignyi was determined using a whole-genome shotgun strategy, but a high degree of polymorphism resulted in a fractured assembly wherein allelic sequences from the same genomic region assembled separately. We designed a multistep strategy to generate a nonredundant reference sequence from the original assembly by reconstructing and aligning the two 'haplomes' (haploid genomes). In the resultant 174 megabase reference sequence, each locus is represented once, misassemblies are corrected, and contiguity and continuity are dramatically improved.

A recent meta-analysis demonstrated a nominal association of the ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) K-->Q missense single nucleotide polymorphism (SNP) at position 121 with type 2 diabetes. We set out to confirm the association of ENPP1 K121Q with hyperglycemia, expand this association to insulin resistance traits, and determine whether the association stems from K121Q or another variant in linkage disequilibrium with it.