Dietary effects on type 2 diabetes risk – Using metabolomics networks to elucidate the underlying mechanisms
Final Report Abstract
The scientific community is still trying to figure out why certain foods and eating habits increase the risk of type 2 diabetes. In this project, we aimed to learn more by looking at how different foods affect the body's biochemical processes. We used a technique called metabolomics to measure small molecules, the metabolites, in the blood. I other projects we employed lipidomics, a variant to measure lipid metabolites. Then, we used advanced statistics to examine metabolomics profiles in large human populations as potential factor connecting diet to diabetes risk. We hypothesized that the influence of diet on metabolomics profiles captures the biological processes underlying the link between long-term dietary habits and future risk of developing cardiometabolic diseases. We used data from prospective human cohort studies with information on the habitual diet, metabolomics and lipidomics profiles, and prospective disease incidence. The main research projects relied on data from the Nurses’ Health Study, the Prevencion con Dieta Mediterranea (PREDIMED) trial, and the European Investigation into Diet and Cancer (EPIC)-Potsdam study. Within these studies, we examined metabolomics and lipidomics as potential link between diet and the risk of type 2 diabetes, myocardial infarction, stroke, and heart failure. Three projects that I have led can illustrate the main aspect of this approach.Project I. Heart failure is a major public health issue and a leading cause of morbidity and mortality worldwide. We used lipidomics as a tool to understand the role of lipid metabolism as a determinant of the risk to suffer from this chronic condition later in life. In the PREDIMED trial, we discovered novel associations of specific lipid metabolites and lipid network clusters with future risk of heart failure incidence. These associations were replicated in the EPIC-Potsdam study. These findings suggest that lipidomic profiling could be a useful tool in identifying individuals at risk of heart failure and developing personalized prevention and treatment strategies. Project II. In this study, we conducted a targeted analysis of dihydroceramides and ceramides lipidomics profiles in the EPIC-Potsdam study. We applied the in-house NetCoupler-algorithm to link a data-driven (dihydro)ceramide network to type 2 diabetes and cardiovascular disease risk and found strong associations that were robust against adjustment for other ceramides from the network. In addition, causal mediation analyses suggested, for example, that the influence of high red meat consumption on specific long-chain fatty acid-containing ceramides may explain how red meat consumption can contribute to higher diabetes risk. Project III. Here, we use repeated metabolomics profiling after ten years in the Nurses’ Health Study and provide evidence that long-term changes in several plasma metabolite levels are associated with subsequent type 2 diabetes risk, independent of the baseline metabolite levels. Our observations indicate that high-throughput metabolic profiling captures progressive perturbations of amino acid and lipid metabolism underlying early type 2 diabetes etiology. These novel findings suggest potential metabolomics profiling applications for tracking type 2 diabetes risk change over time. These examples illustrate the substantial contributions to nutritional metabolomics and primary cardiometabolic risk prevention that resulted from this individual research fellowship, during which I have contributed to over thirty peer-reviewed scientific publications. In addition, we have published open-source software packages for the integrated analysis of diet, metabolomics, and disease risk data in human population studies. The three-year research stay was centered at the Harvard T.H. Chan School of Public Health.
Publications
- Lipid Profiles and Heart Failure Risk: Results From Two Prospective Studies. Circ Res, 128(3): p. 309-320.
Wittenbecher, C., F. Eichelmann, E. Toledo, M. Guasch-Ferré, M. Ruiz-Canela, J. Li, F. Arós, C.H. Lee, L. Liang, J. Salas-Salvadó, C.B. Clish, M.B. Schulze, M. Martínez-González, and F.B. Hu
(See online at https://doi.org/10.1161/circresaha.120.317883) - Changes in metabolomics profiles over ten years and subsequent risk of developing type 2 diabetes: Results from the Nurses' Health Study. EBioMedicine. 75: p. 103799.
Wittenbecher, C., M. Guasch-Ferré, D.E. Haslam, C. Dennis, J. Li, S.N. Bhupathiraju, C.H. Lee, Q. Qi, L. Liang, A.H. Eliassen, C. Clish, Q. Sun, and F.B. Hu
(See online at https://doi.org/10.1016/j.ebiom.2021.103799) - Dihydroceramide- and ceramide-profiling provides insights into human cardiometabolic disease etiology. Nat Commun, 13(1): p. 936.
Wittenbecher, C., R. Cuadrat, L. Johnston, F. Eichelmann, S. Jäger, O. Kuxhaus, M. Prada, M.F. Del Greco, A.A. Hicks, P. Hoffman, J. Krumsiek, F.B. Hu, and M.B. Schulze
(See online at https://doi.org/10.1038/s41467-022-28496-1) - Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease. Diabetes Care, 45(11): p. 2729-2736.
Birukov, A., B. Plavša, F. Eichelmann, O. Kuxhaus, R.A. Hoshi, N. Rudman, T. Štambuk, I. Trbojević-Akmačić, C. Schiborn, J. Morze, M. Mihelčić, A. Cindrić, Y. Liu, O. Demler, M. Perola, S. Mora, M.B. Schulze, G. Lauc, and C. Wittenbecher
(See online at https://doi.org/10.2337/dc22-0833) - Metabolomics and Type 2 Diabetes Risk: An Updated Systematic Review and Meta-analysis of Prospective Cohort Studies. Diabetes Care, 45(4): p. 1013-1024.
Morze, J., C. Wittenbecher, L. Schwingshackl, A. Danielewicz, A. Rynkiewicz, F.B. Hu, and M. Guasch-Ferré
(See online at https://doi.org/10.2337/dc21-1705) - Retinol and Retinol Binding Protein 4 Levels and Cardiometabolic Disease Risk. Circ Res.131(7): p. 637-649.
Schiborn, C., D. Weber, T. Grune, R. Biemann, S. Jäger, N. Neu, M. Müller von Blumencron, A. Fritsche, C. Weikert, M.B. Schulze, and C. Wittenbecher
(See online at https://doi.org/10.1161/circresaha.122.321295)
