1
|
Schöttker B, Rathmann W, Herder C, Thorand B, Wilsgaard T, Njølstad I, Siganos G, Mathiesen EB, Saum KU, Peasey A, Feskens E, Boffetta P, Trichopoulou A, Kuulasmaa K, Kee F, Brenner H. HbA1c levels in non-diabetic older adults - No J-shaped associations with primary cardiovascular events, cardiovascular and all-cause mortality after adjustment for confounders in a meta-analysis of individual participant data from six cohort studies. BMC Med 2016; 14:26. [PMID: 26867584 PMCID: PMC4751667 DOI: 10.1186/s12916-016-0570-1] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 01/26/2016] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND To determine the shape of the associations of HbA1c with mortality and cardiovascular outcomes in non-diabetic individuals and explore potential explanations. METHODS The associations of HbA1c with all-cause mortality, cardiovascular mortality and primary cardiovascular events (myocardial infarction or stroke) were assessed in non-diabetic subjects ≥50 years from six population-based cohort studies from Europe and the USA and meta-analyzed. Very low, low, intermediate and increased HbA1c were defined as <5.0, 5.0 to <5.5, 5.5 to <6.0 and 6.0 to <6.5% (equals <31, 31 to <37, 37 to <42 and 42 to <48 mmol/mol), respectively, and low HbA1c was used as reference in Cox proportional hazards models. RESULTS Overall, 6,769 of 28,681 study participants died during a mean follow-up of 10.7 years, of whom 2,648 died of cardiovascular disease. Furthermore, 2,493 experienced a primary cardiovascular event. A linear association with primary cardiovascular events was observed. Adjustment for cardiovascular risk factors explained about 50% of the excess risk and attenuated hazard ratios (95 confidence interval) for increased HbA1c to 1.14 (1.03-1.27), 1.17 (1.00-1.37) and 1.19 (1.04-1.37) for all-cause mortality, cardiovascular mortality and cardiovascular events, respectively. The six cohorts yielded inconsistent results for the association of very low HbA1c levels with the mortality outcomes and the pooled effect estimates were not statistically significant. In one cohort with a pronounced J-shaped association of HbA1c levels with all-cause and cardiovascular mortality (NHANES), the following confounders of the association of very low HbA1c levels with mortality outcomes were identified: race/ethnicity; alcohol consumption; BMI; as well as biomarkers of iron deficiency anemia and liver function. Associations for very low HbA1c levels lost statistical significance in this cohort after adjusting for these confounders. CONCLUSIONS A linear association of HbA1c levels with primary cardiovascular events was observed. For cardiovascular and all-cause mortality, the observed small effect sizes at both the lower and upper end of HbA1c distribution do not support the notion of a J-shaped association of HbA1c levels because a certain degree of residual confounding needs to be considered in the interpretation of the results.
Collapse
Affiliation(s)
- Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany. .,Network Aging Research, University of Heidelberg, Bergheimer Straße 20, 69115, Heidelberg, Germany.
| | - W Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf`m Hennekamp 65, 40225, Düsseldorf, Germany
| | - C Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf`m Hennekamp 65, 40225, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, München-Neuherberg, Germany
| | - B Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Postfach 1129, Neuherberg, Germany
| | - T Wilsgaard
- Epidemiology of Chronic Diseases Research Group, Department of Community Medicine, UiT The Arctic University of Norway, 9037, Tromsø, Norway
| | - I Njølstad
- Epidemiology of Chronic Diseases Research Group, Department of Community Medicine, UiT The Arctic University of Norway, 9037, Tromsø, Norway
| | - G Siganos
- Brain and Circulation Research Group, Department of Clinical Medicine, UiT The Arctic University of Norway, 9037, Tromsø, Norway
| | - E B Mathiesen
- Brain and Circulation Research Group, Department of Clinical Medicine, UiT The Arctic University of Norway, 9037, Tromsø, Norway
| | - K U Saum
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - A Peasey
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK
| | - E Feskens
- Division of Human Nutrition, Wageningen University, PO Box 8129, 6700 EV, Wageningen, The Netherlands
| | - P Boffetta
- Institute for Translational Epidemiology and The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Hellenic Health Foundation, Kaisareias 13 and Alexandroupoleos, Athens, 11527, Greece
| | - A Trichopoulou
- Hellenic Health Foundation, Kaisareias 13 and Alexandroupoleos, Athens, 11527, Greece
| | - K Kuulasmaa
- National Institute for Health and Welfare (THL), PO Box 30, FI-00271, Helsinki, Finland
| | - F Kee
- UKCRC Centre of Excellence for Public Health, Queen's University Belfast, Belfast, Northern Ireland
| | - H Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | | |
Collapse
|
2
|
Yang Q, Siganos G, Faloutsos M, Lonardi S. Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet. Comput Syst Bioinformatics Conf 2006:299-310. [PMID: 17369648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.
Collapse
Affiliation(s)
- Q Yang
- Department of Computer Science and Engineering, University of California-Riverside, Riverside, CA 92521, USA
| | | | | | | |
Collapse
|