Original investigation

Network of vascular diseases, death and biochemical characteristics in a set of 4,197 patients with type 1 diabetes (The FinnDiane Study)

Ville-Petteri Mäkinen^1,2,3 , Carol Forsblom^1,2 , Lena M Thorn^1,2 , Johan Wadén^1,2 , Kimmo Kaski³ , Mika Ala-Korpela^4,5 and Per-Henrik Groop^1,2,6

¹  Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Finland

²  Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Finland

³  Department of Biomedical Engineering and Computational Science, Helsinki University of Technology, Finland

⁴  Computational Medicine Research Group, Institute of Clinical Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Finland

⁵  Department of Internal Medicine and Biocenter Oulu, Clinical Research Center, University of Oulu, Finland

⁶  The Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia

author email corresponding author email

Cardiovascular Diabetology 2009, 8:54doi:10.1186/1475-2840-8-54

Published:	6 October 2009

Abstract

Background

Cardiovascular disease is the main cause of premature death in patients with type 1 diabetes. Patients with diabetic kidney disease have an increased risk of heart attack or stroke. Accurate knowledge of the complex inter-dependencies between the risk factors is critical for pinpointing the best targets for research and treatment. Therefore, the aim of this study was to describe the association patterns between clinical and biochemical features of diabetic complications.

Methods

Medical records and serum and urine samples of 4,197 patients with type 1 diabetes were collected from health care centers in Finland. At baseline, the mean diabetes duration was 22 years, 52% were male, 23% had kidney disease (urine albumin excretion over 300 mg/24 h or end-stage renal disease) and 8% had a history of macrovascular events. All-cause mortality was evaluated after an average of 6.5 years of follow-up (25,714 patient years). The dataset comprised 28 clinical and 25 biochemical variables that were regarded as the nodes of a network to assess their mutual relationships.

Results

The networks contained cliques that were densely inter-connected (r > 0.6), including cliques for high-density lipoprotein (HDL) markers, for triglycerides and cholesterol, for urinary excretion and for indices of body mass. The links between the cliques showed biologically relevant interactions: an inverse relationship between HDL cholesterol and the triglyceride clique (r < -0.3, P < 10^-16), a connection between triglycerides and body mass via C-reactive protein (r > 0.3, P < 10^-16) and intermediate-density cholesterol as the connector between lipoprotein metabolism and albuminuria (r > 0.3, P < 10^-16). Aging and macrovascular disease were linked to death via working ability and retinopathy. Diabetic kidney disease, serum creatinine and potassium, retinopathy and blood pressure were inter-connected. Blood pressure correlations indicated accelerated vascular aging in individuals with kidney disease (P < 0.001).

Conclusion

The complex pattern of links between diverse characteristics and the lack of a single dominant factor suggests a need for multifactorial and multidisciplinary paradigms for the research, treatment and prevention of diabetic complications.