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

Abstract

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.

Keywords: Diet; Ectopic fat; Genome; Glycaemic control; Insulin secretion; Insulin sensitivity; Personalised medicine; Physical activity; Prediabetes; Type 2 diabetes.

Fig. 1

Participant flow of cohorts 1 and 2. DanFunD, Danish Functional Disability study; GGG, Gut, Grain and Greens study; HMS, Hoorn Meal Study; METSIM, Metabolic Syndrome in Men study; NHS, New Hoorn Study; RISC, Relationship between Insulin Sensitivity and Cardiovascular disease cohort

Fig. 2

Pairwise correlation matrix. Fill colour indicates Pearson correlation coefficient (r), where positive is denoted by red fill, inverse by blue fill and magnitude by intensity. Cohorts 1 and 2 are separate, above and below the diagonal, respectively. All continuous variables were normally transformed and adjusted for age, sex and study centre. ActGLP1min0, fasting intact GLP-1 concentration; BasalISR, fasting insulin secretion; CHOI, carbohydrate intake; Chol, total cholesterol; DBP, diastolic blood pressure; FatI, fat intake; FibreI, fibre intake; Glucagonmin0, fasting glucagon; Glucose, fasting glucose; GlucoseSens, glucose sensitivity; HDL, fasting HDL-cholesterol; IncGLP1min60, 1 h GLP-1 increment; IncGlucagonmin60, 1 h glucagon increment; Insulin, fasting insulin; LDL, fasting LDL-cholesterol; LiverFat, liver fat; LiverIron, liver iron content; LPA, light physical activity (% of time); Matsuda, Matsuda insulin sensitivity index; MeanGlucose, mean 2 h glucose; MeanInsulin, mean 2 h insulin; MPA, moderate physical activity (% of time); MUFatI, monounsaturated fat intake; OGIS, 2 h insulin sensitivity; PA, mean physical activity intensity; hpfVM; PancFat, pancreatic fat; PancIron, pancreatic iron content; PFR, potentiation factor ratio; ProInsmin60, 1 h intact proinsulin; ProteinI, protein intake; PUFatI, polyunsaturated fat intake; RateSens, rate sensitivity; SatFatI, saturated fat intake; SBP, systolic blood pressure; SPA, sedentary (% of time); Stumvoll, Stumvoll insulin sensitivity index; SugarI, sugar intake; TEI, total energy intake; TG, fasting triacylglycerol; TotalISR, integral of total insulin secretion; TotGLP1min0, fasting total GLP-1 concentration; TwoGlucose, 2 h glucose; TwoInsulin, 2 h insulin; VPA, vigorous physical activity (% of time)

Fig. 3

Pairwise correlation matrix of follow-up Δ (difference between 48 month follow-up assessment and baseline visit). Fill colour indicates Pearson correlation coefficient (r), where positive is denoted by red fill, inverse by blue fill and magnitude by intensity. Cohorts 1 and 2 are separate, above and below diagonal, respectively. All continuous variables were normally transformed and adjusted for age, sex and study centre. BasalISR, fasting insulin secretion; DBP, diastolic blood pressure; Glucose, fasting glucose; GlucoseSens, glucose sensitivity; Insulin, fasting insulin; Matsuda, Matsuda insulin sensitivity index; MeanGlucose, mean 2 h glucose; MeanInsulin, mean 2 h insulin; OGIS, insulin sensitivity (2 h OGIS); PFR, potentiation factor ratio; RateSens, rate sensitivity; SBP, systolic blood pressure; Stumvoll, Stumvoll insulin sensitivity index; TotalISR, integral of total insulin secretion; TwoGlucose, 2 h glucose; TwoInsulin, 2 h insulin.

Fig. 4

Genetic population structure within the cohorts. A statistical summary of genetic data from cohorts 1 and 2 (combined) based on principal component axis one (PC1) and axis two (PC2). Points are coloured according to recruitment centre