TY - JOUR A1 - Wittenbecher, Clemens A1 - Kuxhaus, Olga A1 - Boeing, Heiner A1 - Stefan, Norbert A1 - Schulze, Matthias Bernd T1 - Associations of short stature and components of height with incidence of type 2 diabetes BT - mediating effects of cardiometabolic risk factors JF - Diabetologia : journal of the European Association for the Study of Diabetes (EASD) N2 - Aims/hypothesis This study aimed to evaluate associations of height as well as components of height (sitting height and leg length) with risk of type 2 diabetes and to explore to what extent associations are explainable by liver fat and cardiometabolic risk markers. Methods A case-cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study comprising 26,437 participants who provided blood samples was designed. We randomly selected a subcohort of 2500 individuals (2029 diabetes-free at baseline and with anamnestic, anthropometrical and metabolic data for analysis). Of the 820 incident diabetes cases identified in the full cohort during 7 years of follow-up, 698 remained for analyses after similar exclusions. Results After adjustment for age, potential lifestyle confounders, education and waist circumference, greater height was related to lower diabetes risk (HR per 10 cm, men 0.59 [95% CI 0.47, 0.75] and women 0.67 [0.51, 0.88], respectively). Leg length was related to lower risk among men and women, but only among men if adjusted for total height. Adjustment for liver fat and triacylglycerols, adiponectin and C-reactive protein substantially attenuated associations between height and diabetes risk, particularly among women. Conclusions/interpretation We observed inverse associations between height and risk of type 2 diabetes, which was largely related to leg length among men. The inverse associations may be partly driven by lower liver fat content and a more favourable cardiometabolic profile. KW - Adult height KW - Blood pressure KW - Diabetes incidence KW - Leg length KW - Liver fat KW - Short stature KW - Trunk length Y1 - 2019 U6 - https://doi.org/10.1007/s00125-019-04978-8 SN - 0012-186X SN - 1432-0428 VL - 62 IS - 12 SP - 2211 EP - 2221 PB - Springer CY - New York ER - TY - JOUR A1 - Eichelmann, Fabian A1 - Schulze, Matthias Bernd A1 - Wittenbecher, Clemens A1 - Menzel, Juliane A1 - Weikert, Cornelia A1 - di Giuseppe, Romina A1 - Biemann, Ronald A1 - Isermann, Berend A1 - Fritsche, Andreas A1 - Boeing, Heiner A1 - Aleksandrova, Krasimira T1 - Association of Chemerin Plasma Concentration With Risk of Colorectal Cancer JF - JAMA network open N2 - IMPORTANCE Inflammatory processes have been suggested to have an important role in colorectal cancer (CRC) etiology. Chemerin is a recently discovered inflammatory biomarker thought to exert chemotactic, adipogenic, and angiogenic functions. However, its potential link with CRC has not been sufficiently explored. OBJECTIVE To evaluate the prospective association of circulating plasma chemerin concentrations with incident CRC. DESIGN, SETTING, AND PARTICIPANTS Prospective case-cohort study based on 27 548 initially healthy participants from the European Prospective Investigation Into Cancer and Nutrition (EPIC)-Potsdam cohort who were followed for up to 16 years. Baseline study information and samples were collected between August 23, 1994, and September 25, 1998. Recruitment was according to random registry sampling from the geographical area of Potsdam, Germany, and surrounding municipalities. The last date of study follow-up was May 10, 2010. Statistical analysis was conducted in 2018. MAIN OUTCOMES AND MEASURES Incident CRC, colon cancer, and rectal cancer. Baseline chemerin plasma concentrations were measured by enzyme-linked immunosorbent assay. CONCLUSIONS AND RELEVANCE This study found that the association between chemerin concentration and the risk of incident CRC was linear and independent of established CRC risk factors. Further studies are warranted to evaluate chemerin as a novel immune-inflammatory agent in colorectal carcinogenesis. Y1 - 2019 U6 - https://doi.org/10.1001/jamanetworkopen.2019.0896 SN - 2574-3805 VL - 2 IS - 3 PB - American Veterinary Medical Association CY - Chicago ER - TY - JOUR A1 - Wittenbecher, Clemens A1 - Ouni, Meriem A1 - Kuxhaus, Olga A1 - Jähnert, Markus A1 - Gottmann, Pascal A1 - Teichmann, Andrea A1 - Meidtner, Karina A1 - Kriebel, Jennifer A1 - Grallert, Harald A1 - Pischon, Tobias A1 - Boeing, Heiner A1 - Schulze, Matthias Bernd A1 - Schürmann, Annette T1 - Insulin-Like Growth Factor Binding Protein 2 (IGFBP-2) and the Risk of Developing Type 2 Diabetes JF - Diabetes : a journal of the American Diabetes Association N2 - Recent studies suggest that insulin-like growth factor binding protein 2 (IGFBP-2) may protect against type 2 diabetes, but population-based human studies are scarce. We aimed to investigate the prospective association of circulating IGFBP-2 concentrations and of differential methylation in the IGFBP-2 gene with type 2 diabetes risk. Y1 - 2019 U6 - https://doi.org/10.2337/db18-0620 SN - 0012-1797 SN - 1939-327X VL - 68 IS - 1 SP - 188 EP - 197 PB - American Diabetes Association CY - Alexandria ER - TY - THES A1 - Wittenbecher, Clemens T1 - Linking whole-grain bread, coffee, and red meat to the risk of type 2 diabetes T1 - Der Einfluss von Vollkornbrot, Kaffee, und rotem Fleisch auf das Typ 2 Diabetesrisiko BT - using metabolomics networks to infer potential biological mechanisms BT - Verwendung von Metabolomics-Netzwerken, um auf biologische Mechanismen zu schließen N2 - Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles. Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations. Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years. Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect. Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication. Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified. Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk. Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures. Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes. N2 - Hintergrund: Evidenz aus prospektiven Kohortenstudien belegt, dass der gewohnheitsmäßige Verzehr von Vollkorn, Kaffee und rotem Fleisch mit dem Risiko an Typ 2 Diabetes zu erkranken assoziiert ist. Dieser Risikobeziehung eventuell zugrunde liegende Mechanismen sind allerdings noch weitgehend unklar. Des Weiteren wurde gezeigt, dass Metabolitenprofile im Blut durch die oben genannten Ernährungs-expositionen beeinflusst werden und außerdem in Zusammenhang mit dem Typ 2 Diabetesrisiko stehen. Zusätzlich wurde beschrieben, dass grafische Netzwerkmodelle von Metabolitenprofilen die zugrunde liegenden Stoffwechselprozesse gut abbilden. Zielstellung: Das Ziel dieser Arbeit war es, Hypothesen bezüglich biologischer Mechanismen zu generieren, die die Assoziationen des Vollkornverzehrs, des Kaffeekonsums und des Fleischverzehrs mit dem Typ 2 Diabetesrisiko erklären könnten. Im speziellen sollten Aminosäure- und Lipidprofile als mögliche Mediatoren des Risikozusammenhangs untersucht werden. Studienpopulation: Analysen wurden auf Grundlage von Daten aus der prospektiven EPIC-Potsdam Kohortenstudie (n=27,548) durchgeführt, wobei ein Fall-Kohorten-Design verwendet wurde (n=2317, darunter 692 inzidente Typ 2 Diabetesfälle). Ernährungsgewohnheiten wurden mit einem validierten, semiquantitativen Verzehrshäufigkeitsfragebogen erfasst. Die Konzentrationen von 126 Metaboliten (Aminosäuren, Acylcarnitine, Sphingomyeline und Phosphatidylcholine) wurden zur Basiserhebung genommen Blutproben gemessen. Inzidente Typ 2 Diabetesfälle wurden im Rahmen einer aktiven Folgeerhebung detektiert und verifiziert. Die mediane Dauer des berücksichtigten prospektiven Erhebungszeitraums lag für diese Studie bei 6,6 Jahren. Aufbau der Analysen: Die theoretische Grundlage für den methodischen Ansatz dieser Arbeit bildete die kontrafaktische Theorie der Kausalinferenz. Die in Netzwerken kodierte konditionale Unabhängigkeitsstruktur wurde genutzt, um den Raum möglicher Modelle zu begrenzen, die die beobachteten Zusammenhänge zwischen den Metaboliten erklären könnten. Unter Annahme weniger grundlegender Effektrichtungen (von der Ernährung auf die Netzwerke gerichtete Effekte; von den Netzwerken auf das Diabetesrisiko gerichtete Effekte) genügt die Adjustierung für eine Teilmenge der direkten Nachbarn im Netzwerk, um netzwerkunabhängige direkte Effekte konsistent zu schätzen. Eine weitere Spezifizierung der Modelle war allerdings aufgrund fehlender Richtungsinformationen zu den Metaboliten-abhängigkeiten nicht möglich. Deshalb wurde ein Multi-Modellierungsansatz gewählt, um die Grenzen möglicher Effekte zu schlussfolgern. Alle möglichen Ernährungs-Metaboliten-Beziehungen und Metaboliten-Typ 2 Diabetesrisiko-Beziehungen wurden dadurch in eine der folgenden drei Kategorien klassifiziert: Direkter Effekt, Unklar, Kein Effekt. Querschnittsbeziehungen wurden in multivariabel adjustierten linearen Regressionsmodellen untersucht. Longitudinale Zusammenhänge wurden mit Cox-Regressionsmodellen geschätzt. Alle Modelle wurden für Alter, Geschlecht, Body-Mass-Index, prävalente Hypertonie, Ernährungs- und Lebensstilfaktoren und die Einnahme von Medikamenten adjustiert. Ergebnisse: Der Verzehr von Vollkornbrot stand im Zusammenhang mit niedrigeren Konzentrationen gesättigter und einfach ungesättigter Fettsäuren. Kaffee stand in Beziehung zu niedrigeren Konzentrationen verzweigtkettiger und aromatischer Aminosäuren und hatte potentielle Effekte auf das Fettsäureprofil in den Lipidmetaboliten. Rotes Fleisch zeigte einen Zusammenhang mit niedrigeren Glyzinspiegeln und mit höheren Konzentrationen verzweigtkettiger Aminosäuren. Außerdem stand das Fettsäureprofil in den verschieden Gruppen von Lipidmetaboliten in Zusammenhang mit dem Fleischverzehr. Des Weiteren wurden potentielle Effekte der Metabolite auf das Typ 2 Diabetesrisiko gefunden. Aromatische Aminosäuren und Lipidmetabolite mit geradzahligen, gesättigten (C14-C16) und mit spezifischen mehrfach ungesättigten Fettsäureseitenketten standen mit einem erhöhten Typ 2 Diabetesrisiko in Beziehung. Glyzin, Glutamin und Lipidmetabolite mit einfach ungesättigten und anderen mehrfach ungesättigten Fettsäureseitenketten zeigten einen günstigen Zusammenhang mit dem Diabetesrisiko. Mögliche Mediatoren der Beziehung der Ernährungsexpositionen wurden identifiziert, indem diese Informationen in gemeinsamen grafischen Modellen integriert wurden. Mediationsanalysen zeigten, dass die möglichen Effekte von Vollkornverzehr auf die Lipidmetabolite ungefähr ein Viertel des günstigen Einflusses von Vollkornverzehr auf das Diabetesrisikos erklären könnten. Die möglichen Effekte von Kaffeekonsum und von Fleischverzehr auf Aminosäuren und Lipidmetabolite könnten jeweils ungefähr zwei Drittel der Zusammenhänge mit dem Diabetesrisiko erklären. Schlussfolgerung: Grundlage für die Ergebnisse dieser Arbeit war die Entwicklung eines Algorithmus, der externe Faktoren (kontinuierlich Expositionsvariablen, Ereigniszeit-Daten) und hochdimensionale Metabolitenprofile in einem gemeinsamen grafischen Modell integriert. Die Anwendung dieses Algorithmus auf Daten aus der EPIC-Potsdam Kohortenstudie hat gezeigt, dass die beobachteten konditionalen Unabhängigkeitsstrukturen mit der a priori Mediationshypothese konsistent waren. Der frühe Einfluss auf den Aminosäure- und Lipidstoffwechsel könnte die beobachteten Zusammenhänge zwischen drei wichtigen Ernährungsfaktoren und dem Risiko an Typ 2 Diabetes zu erkranken zu großen Teilen erklären. KW - type 2 diabetes KW - nutrition KW - lipid metabolism KW - metabolomics KW - epidemiology KW - networks KW - graphical models KW - mediation analysis KW - red meat KW - whole-grain KW - Diabetes mellitus Typ 2 KW - Ernährung KW - Fettstoffwechsel KW - Metabolomics KW - Epidemiologie KW - Netzwerke KW - grafische Modelle KW - Mediationsanalyse KW - rotes Fleisch KW - Vollkorn KW - Kaffee KW - coffee Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-404592 ER - TY - JOUR A1 - Eichelmann, Fabian A1 - Sellem, Laury A1 - Wittenbecher, Clemens A1 - Jäger, Susanne A1 - Kuxhaus, Olga A1 - Prada, Marcela A1 - Cuadrat, Rafael A1 - Jackson, Kim G. A1 - Lovegrove, Julie A. A1 - Schulze, Matthias Bernd T1 - Deep lipidomics in human plasma: cardiometabolic disease risk and effect of dietary fat modulation JF - Circulation N2 - Background: In blood and tissues, dietary and endogenously generated fatty acids (FAs) occur in free form or as part of complex lipid molecules that collectively represent the lipidome of the respective tissue. We assessed associations of plasma lipids derived from high-resolution lipidomics with incident cardiometabolic diseases and subsequently tested if the identified risk-associated lipids were sensitive to dietary fat modification. Methods: The EPIC Potsdam cohort study (European Prospective Investigation into Cancer and Nutrition) comprises 27 548 participants recruited within an age range of 35 to 65 years from the general population around Potsdam, Germany. We generated 2 disease-specific case cohorts on the basis of a fixed random subsample (n=1262) and all respective cohort-wide identified incident primary cardiovascular disease (composite of fatal and nonfatal myocardial infarction and stroke; n=551) and type 2 diabetes (n=775) cases. We estimated the associations of baseline plasma concentrations of 282 class-specific FA abundances (calculated from 940 distinct molecular species across 15 lipid classes) with the outcomes in multivariable-adjusted Cox models. We tested the effect of an isoenergetic dietary fat modification on risk-associated lipids in the DIVAS randomized controlled trial (Dietary Intervention and Vascular Function; n=113). Participants consumed either a diet rich in saturated FAs (control), monounsaturated FAs, or a mixture of monounsaturated and n-6 polyunsaturated FAs for 16 weeks. Results: Sixty-nine lipids associated (false discovery rate<0.05) with at least 1 outcome (both, 8; only cardiovascular disease, 49; only type 2 diabetes, 12). In brief, several monoacylglycerols and FA16:0 and FA18:0 in diacylglycerols were associated with both outcomes; cholesteryl esters, free fatty acids, and sphingolipids were largely cardiovascular disease specific; and several (glycero)phospholipids were type 2 diabetes specific. In addition, 19 risk-associated lipids were affected (false discovery rate<0.05) by the diets rich in unsaturated dietary FAs compared with the saturated fat diet (17 in a direction consistent with a potential beneficial effect on long-term cardiometabolic risk). For example, the monounsaturated FA-rich diet decreased diacylglycerol(FA16:0) by 0.4 (95% CI, 0.5-0.3) SD units and increased triacylglycerol(FA22:1) by 0.5 (95% CI, 0.4-0.7) SD units. Conclusions: We identified several lipids associated with cardiometabolic disease risk. A subset was beneficially altered by a dietary fat intervention that supports the substitution of dietary saturated FAs with unsaturated FAs as a potential tool for primary disease prevention. KW - cardiovascular diseases KW - cholesterol KW - diabetes mellitus KW - type 2 KW - diet KW - food KW - and nutrition KW - epidemiology KW - lipids Y1 - 2022 U6 - https://doi.org/10.1161/CIRCULATIONAHA.121.056805 SN - 0009-7322 SN - 1524-4539 VL - 146 IS - 1 SP - 21 EP - 35 PB - Lippincott Williams & Wilkins CY - Philadelphia ER -