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Aims/hypothesis: The euglycaemic–hyperinsulinaemic clamp (EIC) is the reference standard for the measurement of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-throughput plasma proteomic profiling in developing signatures correlating with the M value derived from the EIC. Methods: We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M value variance explained (R2). Results: A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M value R2 from 0.237 (95% CI 0.178, 0.303) to 0.456 (0.372, 0.536) in RISC. A similar pattern was observed in ULSAM, in which the M value R2 increased from 0.443 (0.360, 0.530) to 0.632 (0.569, 0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R2 despite differences in baseline cohort characteristics and clamp methodology (RISC to ULSAM: 0.491 [0.433, 0.539] for 51 proteins; ULSAM to RISC: 0.369 [0.331, 0.416] for 67 proteins). A randomised LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins), which improved R2 but to a lesser degree than in standard LASSO models: 0.352 (0.266, 0.439) in RISC and 0.495 (0.404, 0.585) in ULSAM. Reductions in improvements of R2 with randomised LASSO and stability selection were less marked in cross-cohort analyses (RISC to ULSAM R2 0.444 [0.391, 0.497]; ULSAM to RISC R2 0.348 [0.300, 0.396]). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomised LASSO. The single most consistently selected protein across all analyses and models was IGF-binding protein 2. Conclusions/interpretation: A plasma proteomic signature identified using a standard LASSO approach improves the cross-sectional estimation of the M value over routine clinical variables. However, a small subset of these proteins identified using a stability selection algorithm affords much of this improvement, especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin-resistant individuals at risk of insulin resistance-related adverse health consequences. [ABSTRACT FROM AUTHOR]

Aim/hypothesis: The risk of progressing from autoantibody positivity to type 1 diabetes is inversely related to age. Separately, whether age influences patterns of C-peptide loss or changes in insulin sensitivity in autoantibody-positive individuals who progress to stage 3 type 1 diabetes is unclear. Methods: Beta cell function and insulin sensitivity were determined by modelling of OGTTs performed in 658 autoantibody-positive participants followed longitudinally in the Diabetes Prevention Trial–Type 1 (DPT-1). In this secondary analysis of DPT-1 data, time trajectories of beta cell function and insulin sensitivity were analysed in participants who progressed to type 1 diabetes (progressors) to address the impact of age on patterns of metabolic progression to diabetes. Results: Among the entire DPT-1 cohort, the highest discriminant age for type 1 diabetes risk was 14 years, with participants aged <14 years being twice as likely to progress to type 1 diabetes as those aged ≥14 years. At study entry, beta cell glucose sensitivity was impaired to a similar extent in progressors aged <14 years and progressors aged ≥14 years. From study entry to stage 3 type 1 diabetes onset, beta cell glucose sensitivity and insulin sensitivity declined in both progressor groups. However, there were no significant differences in the yearly rate of decline in either glucose sensitivity (−13.7 [21.2] vs −11.9 [21.5] pmol min−1 m−2 [mmol/l]−1, median [IQR], p=0.52) or insulin sensitivity (−22 [37] vs −14 [40] ml min−1 m−2, median [IQR], p=0.07) between progressors aged <14 years and progressors aged ≥14 years. Conclusions/interpretation: Our data indicate that during progression to stage 3 type 1 diabetes, rates of change in declining glucose and insulin sensitivity are not significantly different between progressors aged <14 years and progressors aged ≥14 years. These data suggest there is a predictable course of declining metabolic function during the progression to type 1 diabetes that is not influenced by age. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Endoplasmic reticulum (ER) stress and beta cell dedifferentiation both play leading roles in impaired insulin secretion in overt type 2 diabetes. Whether and how these factors are related in the natural history of the disease remains, however, unclear. Methods: In this study, we analysed pancreas biopsies from a cohort of metabolically characterised living donors to identify defects in in situ insulin synthesis and intra-islet expression of ER stress and beta cell phenotype markers. Results: We provide evidence that in situ altered insulin processing is closely connected to in vivo worsening of beta cell function. Further, activation of ER stress genes reflects the alteration of insulin processing in situ. Using a combination of 17 different markers, we characterised individual pancreatic islets from normal glucose tolerant, impaired glucose tolerant and type 2 diabetic participants and reconstructed disease progression. Conclusions/interpretation: Our study suggests that increased beta cell workload is accompanied by a progressive increase in ER stress with defects in insulin synthesis and loss of beta cell identity. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Experimental studies suggest that the fatty acid palmitoleate may act as an adipocyte-derived lipid hormone (or 'lipokine') to regulate systemic metabolism. We investigated the relationship of circulating palmitoleate with insulin sensitivity, beta cell function and glucose tolerance in humans. Methods: Plasma NEFA concentration and composition were determined in non-diabetic individuals from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study cohort at baseline (n = 1234) and after a 3 year follow-up (n = 924). Glucose tolerance, insulin secretion and beta cell function were assessed during an OGTT. Whole-body insulin sensitivity was measured by a hyperinsulinaemic–euglycaemic clamp (M/I) and OGTT (oral glucose insulin sensitivity index [OGIS]). The liver insulin resistance index was calculated using clinical and biochemical data. Body composition including fat mass was determined by bioelectrical impedance. Results: Circulating palmitoleate was proportional to fat mass (r = 0.21, p < 0.0001) and total NEFA levels (r = 0.19, p < 0.0001). It correlated with whole-body insulin sensitivity (M/I: standardised regression coefficient [std. β] = 0.16, p < 0.0001), liver insulin resistance (std. β = −0.14, p < 0.0001), beta cell function (potentiation: std. β = 0.08, p = 0.045) and glucose tolerance (2 h glucose: std. β = −0.24, p < 0.0001) after adjustment for age, sex, BMI, adiposity and other NEFA. High palmitoleate concentrations prevented the decrease in insulin sensitivity associated with excess palmitate (p = 0.0001). In a longitudinal analysis, a positive independent relationship was observed between changes in palmitoleate and insulin sensitivity over time (std. β = 0.07, p = 0.04). Conclusions/interpretation: We demonstrated that plasma palmitoleate is an independent determinant of insulin sensitivity, beta cell function and glucose tolerance in non-diabetic individuals. These results support the role of palmitoleate as a beneficial lipokine released by adipose tissue to prevent the negative effects of adiposity and excess NEFA on systemic glucose metabolism. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Postprandial hypoglycaemia (PPHG) is a complication of Roux-en-Y gastric bypass (RYGB) surgery in normoglycaemic individuals. In type 2 diabetes, RYGB improves glucose metabolism, but whether this improvement is related to the later development of PPHG is not known. We investigated the presence and mechanisms of PPHG in individuals with type 2 diabetes undergoing RYGB.Methods: A total of 35 obese individuals with type 2 diabetes underwent an OGTT before and 24 months after surgery. PPHG was defined as a plasma glucose level of ≤3.3 mmol/l when not taking glucose-lowering agents. Insulin sensitivity was assessed by oral glucose insulin sensitivity index and beta-cell function by mathematical modelling of the plasma glucose, insulin and C-peptide concentrations.Results: After surgery, PPHG occurred in 11 of 35 individuals who underwent RYGB. Before surgery, BMI was lower, glycaemic control less good and time of glucose peak earlier in the PPHG vs No PPHG group, and the duration of diabetes was shorter with PPHG (all p ≤ 0.05). In addition, insulin sensitivity was greater in the PPHG than No PPHG group (p = 0.03). After surgery, BMI and fasting glucose and insulin levels decreased similarly in the two groups; insulin secretion during the first hour of the OGTT increased more in the PPHG than No PPHG group (p = 0.04). Beta-cell glucose sensitivity increased more in individuals with PPHG than those without (p = 0.002). Over the same time interval, the glucagon-like peptide 1 (GLP-1) response was lower in individuals with PPHG before surgery (p = 0.05), and increased more after surgery. At 2 h after glucose ingestion in the OGTT, postsurgery plasma glucagon level was significantly lower in the PPHG than No PPHG group.Conclusions/interpretation: In morbidly obese individuals with type 2 diabetes, spontaneous PPHG may occur after bariatric surgery independently of a remission of diabetes. Before surgery, individuals had a shorter duration and were more insulin sensitive. Two years after surgery, these individuals developed greater beta-cell glucose sensitivity, and showed greater insulin and GLP-1 release early in the OGTT. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: The hyperglycaemic clamp technique and the frequently sampled IVGTT are unsuitable techniques to assess beta cell function (BCF) in large cohorts. Therefore, the aim of this study was to evaluate the discriminatory ability of simple OGTT-based BCF indices for prediction of prediabetes (meaning impaired fasting glucose and/or impaired glucose tolerance) and type 2 diabetes. Methods: Glucose metabolism status was assessed by 2 h 75 g OGTT at baseline ( n = 476, mean age 59.2 years, 38.7% women) and after 7 years of follow-up ( n = 416) in the Cohort on Diabetes and Atherosclerosis Maastricht (CODAM) study (1999-2009). Baseline plasma glucose, insulin and C-peptide values during OGTTs were used to calculate 21 simple indices of BCF. Disposition indices (BCF index × Matsuda index), to compensate for the prevailing level of insulin resistance, were calculated for the BCF indices with the best discriminatory abilities. The discriminatory ability of the BCF indices was estimated by the area under the receiver operating characteristics curve (ROC AUC) with an outcome of incident prediabetes ( n = 73) or type 2 diabetes ( n = 60 and n = 18 cases, respectively, in individuals who were non-diabetic or had normal glucose metabolism at baseline). Results: For incident prediabetes ( n = 73), all ROC AUCs were less than 70%, whereas for incident type 2 diabetes, I/I, CP/CP, ΔI/ΔG, ΔCP/ΔG (where I, CP and G are the plasma concentrations of insulin, C-peptide and glucose, respectively, at the times indicated), and corrected insulin response at 30 min had ROC AUCs over 70%. In at-baseline non-diabetic individuals, disposition indices ΔI/ΔG, ΔCP/ΔG and corrected insulin response at 30 min had ROC AUCs of over 80% for incident type 2 diabetes. Moreover, these BCF disposition indices had significantly better discriminatory abilities for incident type 2 diabetes than the Matsuda index alone. Conclusions/interpretation: BCF indices reflecting early-phase insulin secretion have the best ability to discriminate individuals who will develop prediabetes and type 2 diabetes. Of these, ΔCP/ΔG, often referred to as the C-peptidogenic index, performed consistently well. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Sodium glucose co-transporter 2 (SGLT2) inhibitors lower glycaemia by inducing glycosuria, but raise endogenous glucose production (EGP). Metformin lowers glycaemia mainly by suppressing EGP. We compared the effects of the SGLT2 inhibitor empagliflozin in treatment-naive (TN) and metformin pretreated (Met) patients with type 2 diabetes. Methods: A total of 32 TN and 34 patients on a stable dose of metformin, two subgroups of a study that we previously reported, received a mixed meal with double-tracer glucose administration and indirect calorimetry at baseline, after a single 25 mg dose of empagliflozin, and after 4 weeks of treatment with empagliflozin 25 mg/day. Results: At baseline, compared with the TN group, the Met group had higher fasting glycaemia (9.1 ± 1.7 vs 8.2 ± 1.3 mmol/l), lower fasting and postmeal insulin secretion, lower beta cell glucose sensitivity (37 [18] vs 58 [43] pmol min m [mmol/l], median [interquartile range]) and insulin:glucagon ratio, and higher fasting EGP (15.9 [4.3] vs 12.1 [2.7] μmol kg min). Change from baseline in fasting EGP after single dose and 4 weeks of treatment with empagliflozin was similar in the Met and TN groups (19.6 [4.2] and 19.0 [2.3] in Met vs 16.2 [3.6] and 15.5 [3.2] μmol kg min in TN for acute and chronic dosing, respectively). Beta cell glucose sensitivity increased less in Met than TN patients, whereas substrate utilisation shifted from carbohydrate to fat more in Met than TN patients. Conclusions/interpretation: At baseline, Met patients with type 2 diabetes had more advanced disease than TN patients, featuring worse beta cell function and higher EGP. Empagliflozin induced similar glycosuria and metabolic and hormonal responses in Met and TN patients. Trial registration:: ClinicalTrials.gov NCT01248364; European Union Clinical Trials Register 2010-018708-99 [ABSTRACT FROM AUTHOR]

Unfortunately, 'Present address' was omitted from one of the addresses provided for Mark I. McCarthy (#26). [ABSTRACT FROM AUTHOR]

The affiliation details for Geltrude Mingrone are corrected below. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes., Methods: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively., Results: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA 1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes., Conclusions/interpretation: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions., (© 2024. The Author(s).)

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/m 2 ; 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/m 2 ; 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.

Aims/hypothesis: The hyperglycaemic clamp technique and the frequently sampled IVGTT are unsuitable techniques to assess beta cell function (BCF) in large cohorts. Therefore, the aim of this study was to evaluate the discriminatory ability of simple OGTT-based BCF indices for prediction of prediabetes (meaning impaired fasting glucose and/or impaired glucose tolerance) and type 2 diabetes., Methods: Glucose metabolism status was assessed by 2 h 75 g OGTT at baseline (n = 476, mean age 59.2 years, 38.7% women) and after 7 years of follow-up (n = 416) in the Cohort on Diabetes and Atherosclerosis Maastricht (CODAM) study (1999-2009). Baseline plasma glucose, insulin and C-peptide values during OGTTs were used to calculate 21 simple indices of BCF. Disposition indices (BCF index × Matsuda index), to compensate for the prevailing level of insulin resistance, were calculated for the BCF indices with the best discriminatory abilities. The discriminatory ability of the BCF indices was estimated by the area under the receiver operating characteristics curve (ROC AUC) with an outcome of incident prediabetes (n = 73) or type 2 diabetes (n = 60 and n = 18 cases, respectively, in individuals who were non-diabetic or had normal glucose metabolism at baseline)., Results: For incident prediabetes (n = 73), all ROC AUCs were less than 70%, whereas for incident type 2 diabetes, I 30 /I 0 , CP 30 /CP 0 , ΔI 30 /ΔG 30 , ΔCP 30 /ΔG 30 (where I, CP and G are the plasma concentrations of insulin, C-peptide and glucose, respectively, at the times indicated), and corrected insulin response at 30 min had ROC AUCs over 70%. In at-baseline non-diabetic individuals, disposition indices ΔI 30 /ΔG 30 , ΔCP 30 /ΔG 30 and corrected insulin response at 30 min had ROC AUCs of over 80% for incident type 2 diabetes. Moreover, these BCF disposition indices had significantly better discriminatory abilities for incident type 2 diabetes than the Matsuda index alone., Conclusions/interpretation: BCF indices reflecting early-phase insulin secretion have the best ability to discriminate individuals who will develop prediabetes and type 2 diabetes. Of these, ΔCP 30 /ΔG 30 , often referred to as the C-peptidogenic index, performed consistently well.

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.