Sharma S, Dong Q, Haid M, Adam J, Bizzotto R, Fernandez-Tajes JJ, Jones AG, Tura A, Artati A, Prehn C, Kastenmüller G, Koivula RW, Franks PW, Walker M, Forgie IM, Giordano G, Pavo I, Ruetten H, Dermitzakis M, McCarthy MI, Pedersen O, Schwenk JM, Tsirigos KD, De Masi F, Brunak S, Viñuela A, Mari A, McDonald TJ, Kokkola T, Adamski J, Pearson ER, and Grallert H
Aims/hypothesis: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes., Methods: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively., Results: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA 1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes., Conclusions/interpretation: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions., Competing Interests: Acknowledgements: We extend our gratitude to the IMI-DIRECT study participants who willingly participated in phenotyping as well as to the clinical and technical staff across European study centres for their contributions to participant recruitment and clinical assessment. This publication’s development has been supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement 115317 (DIRECT), with resources derived from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in-kind contributions. Special thanks go to the study centre team, L. M. 't Hart, F. Rutters, J. Vangipurapu and T. H. Hansen, for providing internal review on this manuscript. Data availability: Access to the molecular and clinical raw data, as well as the processed data, is restricted. This is in accordance with the informed consent provided by study participants, the various national ethical approvals obtained for the study, and compliance with the European General Data Protection Regulation (GDPR). Individual-level clinical and molecular data cannot be transferred from the centralised IMI-DIRECT repository. Requests for access will receive guidance on accessing data through the DIRECT secure analysis platform after submitting an appropriate application. The IMI-DIRECT data access policy and additional information about the IMI-DIRECT research consortium’s initiatives and activities can be found at https://directdiabetes.org . Code used for MR in the study is included as ESM. Funding: Open Access funding enabled and organized by Projekt DEAL. We would like to thank Helmholtz Munich, German Diabetes Center (DZD) for their support in current research and China Research Council (CRC) funding for a PhD student hosted by Helmholtz Munich. Authors’ relationships and activities: The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: SS, QD, MH, JA and HG conceptualised the analysis plan. RWK, PWF, MW, IF, GG, IP, HR, MD, MM, OP, JS, KT, FDM, SB, AV, AM, TM, TK, JA, EP and HG were involved in conception and design of the DIRECT study. SS, QD, MH, JA, GK, AA, CP, RB, JFT, AJ and AT were involved in the data acquisition, pre-processing and interpretation of data. SS organised inclusion of outlined sections and, along with QD, wrote the original draft of the manuscript. All authors contributed to drafting the article or critically revising it for significant intellectual content and have provided approval to the final version to be published. SS and HG are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis., (© 2024. The Author(s).)