Background
Why was the cohort set up?
Subphenotypes of DM
Complications and diagnosis of early manifestations
Individualized intervention strategies
Classical and novel risk factors
Study design and methods
Who is in the cohort?
Key inclusion criteria | Key exclusion criteria | Exclusion criteria for specific examinations |
---|---|---|
Diagnosis of type 1 DM and type 2 DM including maturity onset diabetes of the young (MODY) and latent autoimmune diabetes of the adult (LADA) based on current ADA recommendationsa
Onset of DM within the last 12 months Diagnosis of type 1 DM based on diabetes manifestation with ketoacidosis or immediate insulin requirement along with the presence of at least one islet cell directed autoantibody or C-peptide levels below detection limita
Age of 18–69 years | Secondary DM according to ADA criteria (Type 3 B-H, e.g. pancreoprive DM) Type 4 (gestational) DM, pregnancy Poor glycemic control (HbA1c > 9.0 %) Hyperlipidemia (triglycerides and low-density lipoproteins ≥double upper reference limit) Heart, renal, liver failure (NYHA ≥II, serum creatinine ≥1.6 mg/dl, Aspartate-Aminotransferase/Alanine-Aminotransferase/Gamma-Glutamyltransferase Peripheral artery occlusive disease IV Venous thromboembolic events Anemia, blood donation or participation in a clinical study within the past 3 months Acute infection, leukocytosis, immunosuppressive therapy, autoimmune diseases, infection with human immunodeficiency virus, other severe diseases (e.g. active cancer disease) Psychiatric disorders, limited cooperation ability | Neurologic examination: corneal disorders, and neuropathy from causes other than diabetes Spiroergometry: electrocardiogram abnormalities (alterations of the ST segment, higher-grade arrhythmia), unstable angina pectoris, uncontrolled hypertonia Magnetic resonance spectroscopy/imaging: metallic implants (cardiac pacemaker or defibrillator, cochlear implants, implanted catheters, clips, prosthetic valves), metallic fragments (metal removed from eye, ever worked as metal worker), larger tattoos, waist circumference > 135 cm, claustrophobia Tissue biopsies: effective anticoagulation therapy, platelet aggregation inhibitors >100 mg acetylsalicylate |
How often will they be followed up?
What is measured?
Type 1 DM | Type 2 DM | |
---|---|---|
Age | (%) | (%) |
15–19 | 5.4 | 0.2 |
20–24 | 15.0 | 1.1 |
25–29 | 16.7 | 1.7 |
30–34 | 18.0 | 3.1 |
35–39 | 10.0 | 4.6 |
40–44 | 9.6 | 8.5 |
45–49 | 8.7 | 15.3 |
50–54 | 10.4 | 16.2 |
55–59 | 2.5 | 17.2 |
60–64 | 3.0 | 18.8 |
65–69 | 0.8 | 13.1 |
70–74 | 0 | 0.2 |
Sex | ||
Male | 62.5 | 67.0 |
Female | 37.5 | 33.0 |
Marital status | ||
Single | 55.0 | 21.8 |
Co-habiting/married | 40.8 | 61.6 |
Separated/divorced | 3.7 | 12.4 |
Widowed | 0.4 | 4.1 |
Higher education | ||
Up to class 8 | 9.6 | 27.1 |
Junior high school | 20.0 | 22.5 |
Up to class 10 | 0.0 | 5.0 |
Advanced technical college | 13.3 | 12.2 |
Secondary school examination | 55.0 | 30.6 |
No education | 0.4 | 0.7 |
Other types of education | 1.2 | 1.7 |
No response* | 0.4 | 0.2 |
Employment | ||
Laborer | 9.2 | 16.2 |
Employee | 54.6 | 61.3 |
Official | 5.4 | 5.0 |
Business man | 7.2 | 10.0 |
Farmer | 0 | 0.2 |
Self-employed worker | 2.1 | 3.5 |
Non-employed | 0.8 | 0 |
Other professions | 5.4 | 1.5 |
No response/advanced educationa
| 1.2 | 0.2 |
Medical insurance | ||
Private | 15.8 | 12.4 |
Government/public | 77.9 | 81.9 |
Other insurance | 5.8 | 4.6 |
No insurance | 0 | 0 |
No response | 0.5 | 1.1 |
Regular medical checks | ||
Yes | 35.8 | 56.1 |
No | 63.7 | 42.8 |
No responsea
| 0.4 | 0.9 |
Family history of diabetes | ||
Mother | 16.1 | 32.7 |
Father | 17.3 | 26.3 |
Children | 0.8 | 1.7 |
Brothers and sisters | 7.6 | 18.4 |
Grandparents | 37.3 | 35.2 |
Uncles and aunts | 15.8 | 20.0 |
Other diseases/risk factors/comorbidities | ||
Hypertension | 18.5 | 63.3 |
History of myocardial infarction | 0.4 | 2.8 |
Retinopathy | 0.8 | 1.3 |
History of or current smoking | 73.3 | 88.9 |
Subclinical DSPN | 9.8 | 6.9 |
Confirmed asymptomatic DSPN | 0.4 | 2.6 |
Confirmed symptomatic DSPN | 2.2 | 4.0 |
Possible DSPN | 7.2 | 23.2 |
Probable DSPN | 0.5 | 5.3 |
Subclinical/borderline CAN | 0.9 | 2.1 |
Definite CAN | 1.4 | 2.4 |
Medication | ||
Glucose lowering therapy | ||
Insulin, short acting | 87.9 | 5.9 |
Insulin, long acting | 54.2 | 4.8 |
Metformin | 14.6 | 56.1 |
Sulfonylurea | 1.3 | 3.5 |
Dipeptidyl-peptidase-4 inhibitors | 1.3 | 6.6 |
GLP-1-Agonists | 0.4 | 2.0 |
Other therapies | ||
Acetylsalicylic acid | 1.7 | 11.1 |
Statins | 2.5 | 17.5 |
Fibrates | 0.0 | 0.7 |
Any antihypertensive therapy | ||
Blockers of the renin-angiotensin system | 2.1 | 15.9 |
Beta blockers | 2.9 | 25.3 |
Calcium channel blockers | 0.8 | 13.8 |
Diuretics | 0.4 | 8.3 |
N | M ± SD | LQ/UQ | Med | |
---|---|---|---|---|
Panel a
| ||||
Age (years) | 240 | 36.0 ± 11.8 | 26.3/45.4 | 34.0 |
Body mass index (kg/m2) | 240 | 24.8 ± 4.1 | 22.0/26.6 | 24.0 |
Waist circumference (cm) | 239 | 86.1 ± 12.6 | 76.2/94.0 | 85.0 |
Hemoglobin A1c (%) | 237 | 6.5 ± 1.2 | 5.8/6.9 | 6.3 |
Glucose (mg/dl) | 232 | 133.4 ± 48.0 | 106.0/150.5 | 121.0 |
Total cholesterol (mg/dl) | 238 | 184.9 ± 38.6 | 160.5/207.5 | 180.5 |
HDL cholesterol (mg/dl) | 236 | 60.5 ± 17.3 | 48.5/70.5 | 59 |
LDL cholesterol (mg/dl) | 236 | 108.9 ± 33.5 | 87.0/126.5 | 105.0 |
Triglycerides (mg/dl) | 238 | 89.6 ± 58.2 | 56.0/102.0 | 74.0 |
ASAT (U/l) | 238 | 22.4 ± 8.5 | 17.0/25.0 | 20.2 |
ALAT (U/l) | 238 | 25.2 ± 18.5 | 15.9/28.0 | 20.9 |
GGT (U/l) | 238 | 22.1 ± 21.7 | 11.1/26.0 | 16.0 |
hsCRP (mg/dl) | 237 | 0.2 ± 0.3 | 0.1/0.2 | 0.1 |
C-peptide (ng/ml) | 236 | 1.2 ± 0.9± | 0.5/1.4/ | 1.0 |
SBP (mmHg) | 237 | 129.5 ± 14.9 | 120.5/138.0 | 129.0 |
DBP (mmHg) | 237 | 78.0 ± 9.8 | 71.0/84.0 | 77.0 |
VO2max (ml min.−1 kg−1) | 203 | 27.0 ± 7.8 | 22.1/31.3 | 25.7 |
FMD (%) | 201 | 6.8 ± 6.6 | 2.2/10.6 | 5.6 |
NMD (%) | 196 | 16.4 ± 9.5 | 9.3/22.1 | 15.8 |
Panel b
| ||||
Age (years) | 458 | 53.5 ± 10.4 | 47.1/62.4 | 54.8 |
Body mass index (kg/m2) | 456 | 31.7 ± 6.0 | 27.1/35.4 | 31.1 |
Waist circumference (cm) | 455 | 105.9 ± 14.7 | 95.0/115.5 | 105.5 |
Hemoglobin A1c (%) | 452 | 6.4 ± 0.8 | 5.8/6.8 | 6.2 |
Fasting glucose (mg/dl) | 438 | 125.0 ± 28.6 | 107.0/137.0 | 122.0 |
Total cholesterol (mg/dl) | 451 | 206.2 ± 42.0 | 180.0/234.0 | 203.0 |
HDL cholesterol (mg/dl) | 448 | 46.4 ± 12.8 | 37.0/53.0 | 45.0 |
LDL cholesterol (mg/dl) | 448 | 130.5 ± 36.1 | 105.2/153.5 | 129.0 |
Triglycerides (mg/dl) | 451 | 176.0 ± 165.2 | 98.0/203.8 | 137.0 |
ASAT (U/l) | 451 | 25.4 ± 11.0 | 19.0/29.0 | 23.0 |
ALAT (U/l) | 451 | 34.5 ± 19.5 | 21.9/41.8 | 29.0 |
GGT (U/l) | 451 | 43.0 ± 51.0 | 21.4/48.0 | 31.6 |
hsCRP (mg/dl) | 446 | 0.4 ± 0.7 | 0.1/0.5 | 0.3 |
C-peptide (ng/ml) | 445 | 3.3 ± 1.6 | 2.2/4.2 | 3.0 |
SBP (mmHg) | 447 | 141.6 ± 17.1 | 129.5/152.0 | 141.5 |
DBP (mmHg) | 447 | 85.1 ± 10.5 | 78.0/91.5 | 84.5 |
VO2max (ml min.−1 kg−1) | 317 | 19.1 ± 4.9 | 15.6/21.8 | 18.7 |
FMD (%) | 332 | 5.6 ± 5.3 | 1.9/8.25 | 4.5 |
NMD (%) | 338 | 12.2 ± 7.3 | 6.6/16.2 | 11.5 |
Baseline | 5-year follow-up | 10-year follow-up | Telephone interview | |
---|---|---|---|---|
Demographics | ||||
Age | Y | N | N | N |
Sex | Y | N | N | N |
Marital status | Y | Y | Y | Y |
Retardation/physical disabilities | Y | Y | Y | Y |
Diabetes | ||||
Time of diagnosis | Y | N | N | N |
Symptoms at time of diagnosis | Y | N | N | N |
Diabetes treatment regime | Y | Y | Y | Y |
Diet plan and advice | Y | Y | Y | Y |
Diabetes education for the patients | Y | Y | Y | Y |
Ophthalmological complications | Y | Y | Y | Y |
Kidney complications | Y | Y | Y | Y |
Cardiovascular complications | Y | Y | Y | Y |
Neurological complications | Y | Y | Y | Y |
Cerebrovascular complications | Y | Y | Y | Y |
Radiation exposure in last 10 years | Y | Y | Y | Y |
Family history of diabetes and other diseases | Y | Y | Y | Y |
Socio-economic status | ||||
Household composition | Y | Y | Y | Y |
Education | Y | Y | Y | Y |
Health insurance | Y | Y | Y | Y |
Employment | Y | Y | Y | Y |
Net household income | Y | Y | Y | Y |
Personal health behavior, life style | ||||
Smoking | Y | Y | Y | Y |
Alcohol | Y | Y | Y | Y |
Physical activity | Y | Y | Y | Y |
Food frequency questionnaire | Y | Y | Y | Y |
Regular medical checks | Y | Y | Y | Y |
Personal health history | ||||
Other diseases | Y | Y | Y | Y |
Food supplement intake | Y | Y | Y | Y |
Other medication | Y | Y | Y | Y |
Self reported weight and weight change | Y | Y | Y | Y |
Mental health | Y | Y | Y | Y |
Reproductive history | Y | Y | Y | Y |
Health-related quality of life | ||||
WHO-5, SF-36 | Y | Y | Y | Y |
WHOQUOL-Bref, SCL-14 | Y | Y | Y | N |
Depression | ||||
PHQ, PAID, ADS-L | Y | Y | Y | Y |
Information needs, patient time | ||||
CPS, API |
Discussion
What has it found? key findings and publications
Baseline characteristics
Summary of the results obtained so far
Standardization of experimental protocols
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The measures of insulin sensitivity derived from the Botnia clamp were validated against the standard hyperinsulinemic-euglycemic clamps in patients with type 2 DM [64].
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Post-calorimetric individual calibration procedures have been developed to increase the accuracy and comparability of indirect calorimetry assessed in different centers [66].
-
Blood glucose measuring instruments were validated against gold-standard method and the method with the highest accuracy was selected [107].
Establishment of novel methods for metabolic imaging
-
At DDZ, noninvasive phosphorous (31P) MRS of liver was established and optimized with short examination time on a 3-T clinical magnet [75]. With this method, GDS started to employ quantifying absolute concentrations of hepatic adenosine triphosphate (ATP) and inorganic phosphate (Pi) as measures of liver energy metabolism [112].
Development of comorbidities
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Immune cell phenotyping showed distinct occurrence of certain white blood cell subtypes and associations with insulin sensitivity, glycemia and lipidemia in patients with type 1 and type 2 DM [106].
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The sensitivity of an indicator test for sudomotor dysfunction on the foot (Neuropad) for detecting small fiber dysfunction was relatively high in recently diagnosed type 1 DM (80 %) and somewhat lower in type 2 DM (68 %) (64). Thus, early sudomotor dysfunction may be demonstrated by screening in recent-onset diabetes.
-
Using novel methods to quantify small nerve fiber density (NFD) including corneal confocal microscopy and skin biopsy early nerve pathology was detected in up to 20 % of subgroups with type 2 DM participating in the GDS [69‐71]. However, the vast majority of patients with abnormal corneal NFD showed concomitantly normal intraepidermal NFD and vice versa. Thus, both techniques detect early nerve fiber loss in recently diagnosed type 2 DM, but largely in different patients, suggesting a patchy manifestation pattern of small fiber neuropathy. Recently diagnosed type 2 DM patients also demonstrate a marked reduction of cutaneous Langerhans cell density, which relates to insulin resistance in women [69]. Prospective data will establish whether the initial Langerhans cell decline could promote a cutaneous immunogenic imbalance toward inflammation predisposing to polyneuropathy and foot ulcers. Moreover, dermal expression of mitochondrial superoxide dismutase (SOD2) expression in the lower limbs was augmented by ≈60 % and correlated with increasing diabetes duration, cardiac sympathetic predominance, and diminished vagal activity, while subepidermal endothelial cell area was not altered. The SOD2 overexpression points to an early enhanced, presumably compensatory, cutaneous anti-oxidative defence in type 2 DM [111]. Whether cutaneous SOD2 levels can predict the development of diabetic neuropathy will be determined during the prospective GDS follow-up.
-
Assessing various single nucleotide polymorphisms (SNPs) in the transketolase gene, we observed associations of genetic variability in transketolase enzyme with neuropathic symptoms and reduced thermal sensation in the GDS baseline cohort, suggesting a role of pathways metabolizing glycolytic intermediates in early diabetic neuropathy.
-
Using the diagnostic criteria for diabetic sensorimotor polyneuropathy (DSPN) based on the Toronto Consensus (85), the prevalence of DSPN was relatively high, achieving 20 % in individuals with type 1 DM and 42 % in those with type 2 DM (Table 3). DSPN was subclinical in 10 % of the type 1 DM subjects and possible in 23 % of those with type 2 DM. The prevalence of confirmed DSPN was relatively low, with 3 % in individuals with type 1 DM and 7 % in those with type 2 DM, similar to the prevalence of cardiovascular autonomic neuropathy (CAN) at 2 % in type 1 DM and 5 % in type 2 DM patients. The rate of DSPN strongly depends on the definition of DSPN and is considerably lower, if both clinical and electrodiagnostic criteria are combined. The prevalence of definite CAN in GDS participants with type 2 DM (2.4 %) is similar to the rate of 1.8 % observed by the Verona Newly Diagnosed Type 2 Diabetes Study (VNDS) [113]. Likewise, the prevalence of DSPN found in the present study is compatible with the percentages of 4–39 % depending on the different definition criteria for DSPN used in cohorts of newly diagnosed DM patients [114].
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Biomarkers of subclinical inflammation are associated with DSPN and both motor and sensory nerve conduction velocity (NCV). High serum IL-6 was associated with the presence of DSPN and reduced motor NCV in type 2 DM. In addition, higher levels of high-molecular weight (HMW) and total adiponectin were consistently associated with DSPN and both reduced motor and sensory NCV in individuals with type 2 DM. In participants with type 1 DM however, associations between high adiponectin and higher motor NCV were found. Thus, our data support the hypothesis that the pathomechanisms leading to DSPN may only partially overlap between type 1 and type 2 DM [115].
Cellular mechanisms of insulin resistance
-
In a subgroup of type 2 DM patients, we assessed cellular mechanisms of insulin resistance in skeletal muscle [35]. These data provided evidence that specific diacylglycerol species underlie activation of protein kinase C, which impairs insulin signaling.
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In a subgroup of type 2 DM participants, we analysed effect of low-caloric interventions on insulin sensitivity and found that energy restriction per se seems to be key for improving insulin action in phases of active weight loss in obese type 2 DM, with a potential improvement of subclinical inflammation with a diet free of red meat [108].
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Higher levels of biomarkers of subclinical and vascular inflammation were found associated with the deterioration of glycemic control and decreases in beta-cell function in study participants with recently diagnosed type 1 and type 2 DM [94].