Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium.

AIMS/HYPOTHESIS: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). METHODS: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. RESULTS: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants' clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. CONCLUSIONS/INTERPRETATION: The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes.

Empagliflozin compared with glimepiride in metformin-treated patients with type 2 diabetes: 208-week data from a masked randomized controlled trial.

AIM: To report results at week 208, including a 104-week masked extension, of the EMPA-REG H2H-SU trial in patients with type 2 diabetes with inadequate glycaemic control on metformin, in which empagliflozin 25 mg given for 104 weeks provided a sustained reduction in glycated haemoglobin (HbA1c) with a small but statistically significant benefit vs glimepiride, sustained reductions in weight and blood pressure, and low risk of hypoglycaemia. RESEARCH DESIGN AND METHODS: Patients with type 2 diabetes and HbA1c 53-86 mmol/mol (7% to 10%) were randomized to empagliflozin 25 mg or glimepiride 1 to 4 mg for 104 weeks as add-on to metformin. Patients who completed the randomized treatment period could participate in a 104-week extension in which they continued the double-blind treatment allocated at randomization. RESULTS: Of 765 and 780 patients treated with empagliflozin and glimepiride, 576 and 549 patients, respectively, entered the extension period of the study. At week 208, the adjusted mean difference in change from baseline in HbA1c with empagliflozin vs glimepiride was -1.96 mmol/mol, 95% CI -3.57, -0.35 (-0.18%, 95% CI -0.33, -0.03); P = 0.0172. Rescue therapy was given to 23% of patients on empagliflozin and 34% on glimepiride (odds ratio 0.56 [95% CI 0.45, 0.71]; P < 0.0001). Confirmed hypoglycaemic adverse events (plasma glucose ≤3.9 mmol/L and/or requiring assistance) occurred in 3% of patients on empagliflozin and 28% on glimepiride (odds ratio 0.08 [95% CI 0.05, 0.13]; P < 0.0001). CONCLUSIONS: In patients with type 2 diabetes, empagliflozin 25 mg as add-on to metformin for 208 weeks reduced HbA1c with a significantly lower risk of hypoglycaemia and a significantly smaller proportion of patients receiving rescue therapy compared with glimepiride.

Estimating the impact of changes in HbA1c, body weight and insulin injection regimen on health related quality-of-life: a time trade off study.

BACKGROUND: There are limited data on the potential short-term benefits associated with reductions in HbA1c levels, and understanding any immediate improvements in health related quality-of-life (HRQoL) through better glycaemic control may help inform diabetes management decisions. This time-trade-off (TTO) study investigated the short-term impact on HRQoL associated with three different aspects of diabetes management; HbA1c change, body weight change, and the complexity of treatment regimen. METHODS: The study was designed in three stages: Stage 1) Qualitative telephone interviews with people with type 2 diabetes (T2D) in Denmark who had experienced a decrease in their HbA1c level. Stage 2) A validation survey with people with T2D in Denmark to obtain quantifiable knowledge on the short-term effects of a change in HbA1c levels. Stage 3) TTO survey using health states based on results from stage 2. Respondents were either adults with T2D (Sweden) or from the general public (UK and Denmark) and were separately asked to evaluate seven health states through an internet-based survey. RESULTS: Results from 4060 respondents were available for the TTO analysis (UK n = 1777; Denmark n = 1799, Sweden n = 484). 'Well-controlled diabetes' was associated with utilities of 0.85-0.91 and 'not well-controlled diabetes' with utilities of 0.71-0.80 in all countries. Difference in utilities per HbA1c percentage point was smallest in Sweden and largest in Denmark (between 0.025-0.034 per HbA1c percentage point respectively). The treatment management health state associated with the lowest disutility was the once-daily insulin regimen. The disutility associated with per kg of weight change ranged from 0.0041-0.0073. CONCLUSIONS: Changes in HbA1c levels, insulin regimen and body weight are all likely to affect HRQoL for patients with T2D. A change in HbA1c is likely to have a short-term impact in addition to the effect on the development of long term diabetes complications. A treatment which has a simple regimen with fewer injections, and/or the need for less planning, and that causes weight loss or less weight gain, compared with other treatments, will have a positive impact on HRQoL.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium.

AIMS/HYPOTHESIS: The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT. METHODS: Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size ~1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MRI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires. CONCLUSIONS/INTERPRETATION: DIRECT will yield an unprecedented array of biomaterials and data. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes.

Coordinate changes in histone modifications, mRNA levels, and metabolite profiles in clonal INS-1 832/13 ß-cells accompany functional adaptations to lipotoxicity.

Lipotoxicity is a presumed pathogenetic process whereby elevated circulating and stored lipids in type 2 diabetes cause pancreatic ß-cell failure. To resolve the underlying molecular mechanisms, we exposed clonal INS-1 832/13 ß-cells to palmitate for 48 h. We observed elevated basal insulin secretion but impaired glucose-stimulated insulin secretion in palmitate-exposed cells. Glucose utilization was unchanged, palmitate oxidation was increased, and oxygen consumption was impaired. Halting exposure of the clonal INS-1 832/13 ß-cells to palmitate largely recovered all of the lipid-induced functional changes. Metabolite profiling revealed profound but reversible increases in cellular lipids. Glucose-induced increases in tricarboxylic acid cycle intermediates were attenuated by exposure to palmitate. Analysis of gene expression by microarray showed increased expression of 982 genes and decreased expression of 1032 genes after exposure to palmitate. Increases were seen in pathways for steroid biosynthesis, cell cycle, fatty acid metabolism, DNA replication, and biosynthesis of unsaturated fatty acids; decreases occurred in the aminoacyl-tRNA synthesis pathway. The activity of histone-modifying enzymes and histone modifications of differentially expressed genes were reversibly altered upon exposure to palmitate. Thus, Insig1, Lss, Peci, Idi1, Hmgcs1, and Casr were subject to epigenetic regulation. Our analyses demonstrate that coordinate changes in histone modifications, mRNA levels, and metabolite profiles accompanied functional adaptations of clonal ß-cells to lipotoxicity. It is highly likely that these changes are pathogenetic, accounting for loss of glucose responsiveness and perturbed insulin secretion.

Personalized Intervention Based on Early Detection of Atherosclerosis: JACC State-of-the-Art Review.

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide and challenges the capacity of health care systems globally. Atherosclerosis is the underlying pathophysiological entity in two-thirds of patients with CVD. When considering that atherosclerosis develops over decades, there is potentially great opportunity for prevention of associated events such as myocardial infarction and stroke. Subclinical atherosclerosis has been identified in its early stages in young individuals; however, there is no consensus on how to prevent progression to symptomatic disease. Given the growing burden of CVD, a paradigm shift is required-moving from late management of atherosclerotic CVD to earlier detection during the subclinical phase with the goal of potential cure or prevention of events. Studies must focus on how precision medicine using imaging and circulating biomarkers may identify atherosclerosis earlier and determine whether such a paradigm shift would lead to overall cost savings for global health.

The association of cardiometabolic, diet and lifestyle parameters with plasma glucagon-like peptide-1: An IMI DIRECT study.

CONTEXT: The role of glucagon-like peptide-1(GLP-1) in Type 2 diabetes (T2D) and obesity is not fully understood. OBJECTIVE: We investigate the association of cardiometabolic, diet and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. METHOD: We analysed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1(n=2127) individuals at risk of diabetes; cohort 2 (n=789) individuals with new-onset of T2D. RESULTS: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin resistant phenotype and observe a strong independent relationship with male sex, increased adiposity and liver fat particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycaemia, higher adiposity, liver fat, male sex and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit and vegetables inpeople with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. CONCLUSION: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

Rationale, design and baseline characteristics of a 4-year (208-week) phase III trial of empagliflozin, an SGLT2 inhibitor, versus glimepiride as add-on to metformin in patients with type 2 diabetes mellitus with insufficient glycemic control.

BACKGROUND: Sulfonylureas (SUs) are commonly used in the treatment of type 2 diabetes (T2DM), usually as second-line treatment after the failure of metformin. However, SUs are associated with poor durability, hypoglycemia and weight gain. Empagliflozin is a sodium glucose cotransporter 2 (SGLT2) inhibitor in development for the treatment of T2DM. In Phase II/III trials, empagliflozin reduced hyperglycemia, body weight and blood pressure, with a low incidence of hypoglycemia. The aim of this Phase III study is to compare the effects of empagliflozin and the SU glimepiride as second-line therapy in patients with T2DM inadequately controlled with metformin immediate release (IR) and diet/exercise. METHOD: After a 2-week placebo run-in, patients were randomized to receive empagliflozin 25 mg once daily (qd) or glimepiride 1-4 mg qd double-blind for 2 years, in addition to metformin IR. Patients who participate in the initial 2-year randomization period will be eligible for a 2-year double-blind extension. The primary endpoint is change from baseline in HbA1c. Secondary endpoints are change from baseline in body weight, the incidence of confirmed hypoglycemia and changes in systolic and diastolic blood pressure. Exploratory endpoints include markers of insulin secretion, body composition and responder analyses. Safety endpoints include the incidence of adverse events (AEs) (including macro- and microvascular adverse events) and changes from baseline in clinical laboratory parameters. RESULTS: Between August 2010 and June 2011, 1549 patients were randomized and 1545 patients were treated. At baseline, mean (SD) age was 55.9 (10.4) years, HbA1c was 7.92 (0.84)%, body mass index was 30.11 (5.59) kg/m², systolic blood pressure was 133.5 (15.9) mmHg and diastolic blood pressure was 79.5 (9.4) mmHg. DISCUSSION: This is the largest study to compare the efficacy and safety of an SGLT2 inhibitor with an SU in patients with T2DM inadequately controlled on metformin to date. In addition to determining the effects of these treatments on glycemic control over the long term, this study will investigate effects on beta-cell function, cardiovascular risk factors and markers of renal function/damage. The results will help to inform the choice of second-line treatment in patients with T2DM who have failed on metformin. TRIAL REGISTRATION: Clinicaltrials.gov NCT01167881.

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

Precision medicine for cardiometabolic disease: a framework for clinical translation.

Cardiometabolic disease is a major threat to global health. Precision medicine has great potential to help to reduce the burden of this common and complex disease cluster, and to enhance contemporary evidence-based medicine. Its key pillars are diagnostics; prediction (of the primary disease); prevention (of the primary disease); prognosis (prediction of complications of the primary disease); treatment (of the primary disease or its complications); and monitoring (of risk exposure, treatment response, and disease progression or remission). To contextualise precision medicine in both research and clinical settings, and to encourage the successful translation of discovery science into clinical practice, in this Series paper we outline a model (the EPPOS model) that builds on contemporary evidence-based approaches; includes precision medicine that improves disease-related predictions by stratifying a cohort into subgroups of similar characteristics, or using participants' characteristics to model treatment outcomes directly; includes personalised medicine with the use of a person's data to objectively gauge the efficacy, safety, and tolerability of therapeutics; and subjectively tailors medical decisions to the individual's preferences, circumstances, and capabilities. Precision medicine requires a well functioning system comprised of multiple stakeholders, including health-care recipients, health-care providers, scientists, health economists, funders, innovators of medicines and technologies, regulators, and policy makers. Powerful computing infrastructures supporting appropriate analysis of large-scale, well curated, and accessible health databases that contain high-quality, multidimensional, time-series data will be required; so too will prospective cohort studies in diverse populations designed to generate novel hypotheses, and clinical trials designed to test them. Here, we carefully consider these topics and describe a framework for the integration of precision medicine in cardiometabolic disease.

Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity.

CONTEXT: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity. OBJECTIVE: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies. DESIGN: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models. RESULTS: Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity. CONCLUSION: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.

Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study.

OBJECTIVE: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), ß-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS: Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R 2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS: Deteriorating insulin sensitivity and ß-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, ß-cell function, and insulin clearance may be relevant to prevent progression.

Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). ß-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.

Prediction of non-alcoholic fatty liver disease and liver fat using metabolic and genetic factors.

BACKGROUND & AIMS: Our aims were to develop a method to accurately predict non-alcoholic fatty liver disease (NAFLD) and liver fat content based on routinely available clinical and laboratory data and to test whether knowledge of the recently discovered genetic variant in the PNPLA3 gene (rs738409) increases accuracy of the prediction. METHODS: Liver fat content was measured using proton magnetic resonance spectroscopy in 470 subjects, who were randomly divided into estimation (two thirds of the subjects, n = 313) and validation (one third of the subjects, n = 157) groups. Multivariate logistic and linear regression analyses were used to create an NAFLD liver fat score to diagnose NAFLD and liver fat equation to estimate liver fat percentage in each individual. RESULTS: The presence of the metabolic syndrome and type 2 diabetes, fasting serum (fS) insulin, fS-aspartate aminotransferase (AST), and the AST/alanine aminotransferase ratio were independent predictors of NAFLD. The score had an area under the receiver operating characteristic curve of 0.87 in the estimation and 0.86 in the validation group. The optimal cut-off point of -0.640 predicted increased liver fat content with sensitivity of 86% and specificity of 71%. Addition of the genetic information to the score improved the accuracy of the prediction by only <1%. Using the same variables, we developed a liver fat equation from which liver fat percentage of each individual could be estimated. CONCLUSIONS: The NAFLD liver fat score and liver fat equation provide simple and noninvasive tools to predict NAFLD and liver fat content.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

BACKGROUND: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. METHODS: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. RESULTS: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. CONCLUSIONS: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study.

AIM: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. METHODS: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. RESULTS: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. CONCLUSIONS: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.

Genetic dissection of type 2 diabetes.

Compared to the successful probing of genetic causes of monogenic disorders, dissecting the genetics of complex polygenic diseases has until recently been a fairly slow and cumbersome process. With the introduction of whole genome wide association studies (WGAS) the situation dramatically changed in 2007. The results from several recent WGAS on type 2 diabetes (T2D) and obesity have identified at least eighteen genes consistently associated with T2D. Many of the genes implicate pancreatic beta-cell function in the pathogenesis of T2D whereas only one clearly associate with insulin resistance. The identified genes most likely merely represent the tip of the iceberg in the explanation behind T2D. Refined tools will have to provide a more complete picture of the genetic complexity of T2D over the next few years. In addition to common variants increasing susceptibility for the disease, rare variants with stronger effects, copy number variations, and epigenetic effects like DNA methylation and histone acetylation will become important. Nevertheless, today we are able for the first time to anticipate that the genetics of a complex disease like T2D really can be dissected.

Using metabolite profiling to construct and validate a metabolite risk score for predicting future weight gain.

BACKGROUND: Excess weight gain throughout adulthood can lead to adverse clinical outcomes and are influenced by complex factors that are difficult to measure in free-living individuals. Metabolite profiling offers an opportunity to systematically discover new predictors for weight gain that are relatively easy to measure compared to traditional approaches. METHODS AND RESULTS: Using baseline metabolite profiling data of middle-aged individuals from the Framingham Heart Study (FHS; n = 1,508), we identified 42 metabolites associated (p < 0.05) with longitudinal change in body mass index (BMI). We performed stepwise linear regression to select 8 of these metabolites to build a metabolite risk score (MRS) for predicting future weight gain. We replicated the MRS using data from the Mexico City Diabetes Study (MCDS; n = 768), in which one standard deviation increase in the MRS corresponded to ~0.03 increase in BMI (kg/m2) per year (i.e. ~0.09 kg/year for a 1.7 m adult). We observed that none of the available anthropometric, lifestyle, and glycemic variables fully account for the MRS prediction of weight gain. Surprisingly, we found the MRS to be strongly correlated with baseline insulin sensitivity in both cohorts and to be negatively predictive of T2D in MCDS. Genome-wide association study of the MRS identified 2 genome-wide (p < 5 × 10-8) and 5 suggestively (p < 1 × 10-6) significant loci, several of which have been previously linked to obesity-related phenotypes. CONCLUSIONS: We have constructed and validated a generalizable MRS for future weight gain that is an independent predictor distinct from several other known risk factors. The MRS captures a composite biological picture of weight gain, perhaps hinting at the anabolic effects of preserved insulin sensitivity. Future investigation is required to assess the relationships between MRS-predicted weight gain and other obesity-related diseases.