Metabolic Phenotypes, Vascular Complications, and Premature Deaths in a Population of 4,197 Patients With Type 1 Diabetes - Mäkinen, Ville-Petteri; Forsblom, Carol; Thorn, Lena M.; Wadén, Johan; Gordin, Daniel; Heikkilä, Outi; Hietala, Kustaa; Kyllönen, Laura; Kytö, Janne; Rosengård-Bärlund, Milla; Saraheimo, Markku; Tolonen, Nina; et al. (Diabetes (New York, N.Y.), 2008)
Metabolic Phenotypes, Vascular Complications, and Premature Deaths in a Population of 4,197 Patients With Type 1 Diabetes Ville-Petteri Mäkinen 1 2 3 , Carol Forsblom 2 3 , Lena M. Thorn 2 3 , Johan Wadén 2 3 , Daniel Gordin 2 3 , Outi Heikkilä 2 3 , Kustaa Hietala 2 3 , Laura Kyllönen 2 3 , Janne Kytö 2 3 , Milla Rosengård-Bärlund 2 3 , Markku Saraheimo 2 3 , Nina Tolonen 2 3 , Maija Parkkonen 2 3 , Kimmo Kaski 1 , Mika Ala-Korpela 1 2 3 , Per-Henrik Groop 2 3 and on behalf of the FinnDiane Study Group * 1 Department of Biomedical Engineering and Computational Science, Helsinki University of Technology, Helsinki, Finland 2 Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland 3 Division of Nephrology, Department of Medicine, Helsinki University Hospital, Helsinki, Finland Corresponding authors: Ville-Petteri Mäkinen, ville-petteri.makinenatcomputationalmedicine.fi ; and Per-Henrik Groop, per-henrik.groopathelsinki.fi Abstract OBJECTIVE— Poor glycemic control, elevated triglycerides, and albuminuria are associated with vascular complications in diabetes. However, few studies have investigated combined associations between metabolic markers, diabetic kidney disease, retinopathy, hypertension, obesity, and mortality. Here, the goal was to reveal previously undetected association patterns between clinical diagnoses and biochemistry in the FinnDiane dataset. RESEARCH DESIGN AND METHODS— At baseline, clinical records, serum, and 24-h urine samples of 2,173 men and 2,024 women with type 1 diabetes were collected. The data were analyzed by the self-organizing map, which is an unsupervised pattern recognition algorithm that produces a two-dimensional layout of the patients based on their multivariate biochemical profiles. At follow-up, the results were compared against all-cause mortality during 6.5 years (295 deaths). RESULTS— The highest mortality was associated with advanced kidney disease. Other risk factors included 1 ) a profile of insulin resistance, abdominal obesity, high cholesterol, triglycerides, and low HDL 2 cholesterol, and 2 ) high adiponectin and high LDL cholesterol for older patients. The highest population-adjusted risk of death was 10.1-fold (95% CI 7.3–13.1) for men and 10.7-fold (7.9–13.7) for women. Nonsignificant risk was observed for a profile with good glycemic control and high HDL 2 cholesterol and for a low cholesterol profile with a short diabetes duration. CONCLUSIONS— The self-organizing map analysis enabled detailed risk estimates, described the associations between known risk factors and complications, and uncovered statistical patterns difficult to detect by classical methods. The results also suggest that diabetes per se, without an adverse metabolic phenotype, does not contribute to increased mortality. Footnotes Published ahead of print at http://diabetes.diabetesjournals.org on 19 June 2008. * * A complete listing of the FinnDiane Study Group can be found in the online appendix available at http://dx.doi.org/10.2337/db08-0332 . Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Accepted May 22, 2008. Received March 7, 2008. DIABETES