Dihydroceramide- and ceramide-profiling provides insights into human cardiometabolic disease etiology

Metabolic alterations precede cardiometabolic disease onset. Here we present ceramide- and dihydroceramide-profiling data from a nested case-cohort (type 2 diabetes [T2D, n = 775]; cardiovascular disease [CVD, n = 551]; random subcohort [n = 1137]) in the prospective EPIC-Potsdam study. We apply the novel NetCoupler-algorithm to link a data-driven (dihydro)ceramide network to T2D and CVD risk. Controlling for confounding by other (dihydro)ceramides, ceramides C18:0 and C22:0 and dihydroceramides C20:0 and C22:2 are associated with higher and ceramide C20:0 and dihydroceramide C26:1 with lower T2D risk. Ceramide C16:0 and dihydroceramide C22:2 are associated with higher CVD risk. Genome-wide association studies and Mendelian randomization analyses support a role of ceramide C22:0 in T2D etiology. Our results also suggest that (dh)ceramides partly mediate the putative adverse effect of high red meat consumption and benefits of coffee consumption on T2D risk. Thus, (dihydro)ceramides may play a critical role in linking genetic predisposition and dietary habits to cardiometabolic disease risk.


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Data
Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection. Yavorska OO, Burgess S. MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46:1734-1739 The data that support the findings of this study are not publicly available due to data protection regulations. In accordance with German Federal and State data protection regulations, epidemiological data analyses of EPIC-Potsdam may be initiated upon an informal inquiry addressed to the PI of the EPIC-Potsdam study, who is the corresponding author of this manuscript [MBS]. EPIC-Potsdam study data is stored (in SAS data files) and analyzed on servers of the German Institute of Human Nutrition Potsdam-Rehbruecke, and analyses requests are discussed in monthly meetings and usually approved when concerns regarding data privacy can be ruled out. Metabolite sets for enrichment analysis were obtained from the MSigDB C2.CP database together with GSA-SNP2 tool (https://sourceforge.net/ projects/gsasnp2/files/data/popular_pathway_data-20170227T151601Z-001.zip).
The sample size does not rely primarily on power calculations. The observational analyses were based on two case-cohort samples nested within the prospective EPIC-Potsdam study (775 participants with incident T2D among 1886 at-risk participants, and 551 participants with incident CVD among 1707 at-risk participants). The sample size of the case cohort was determined by the number of incident disease cases in the EPIC-Potsdam cohort at the time of study construction. For T2D, the censoring date was the 31st of August 2005; for CVD the censoring date was the 30th of November 2006. The subcohort (n=1,137) included participants randomly selected from all participants with available baseline blood samples and free of T2D at baseline.
For T2D, the censoring date was the 31st of August 2005 (820 incident cases). After excluding participants with missing follow-up information, prevalent diabetes at recruitment, insufficient blood specimens, or non-verifiable information on diabetes incidence, the analytical sample comprised 1886 participants (1000 women and 886 men), including 775 participants with incident T2D from whom 70 were part of the subcohort. The median follow-up time for T2D was 6.5 years (interquartile range 6.0 to 8.6 years).
For CVD, the censoring date was the 30th of November 2006, with 583 incident primary cardiovascular events occurring during the study. After equivalent exclusions (using prevalent and non-verifiable CVD instead of diabetes as exclusion criterion), the CVD sample comprised 1707 participants (910 women and 797 men), including 551 participants with incident CVD (283 only myocardial infarction, 257 only stroke, 11 both) from whom 30 were part of the subcohort. The median follow-up time for CVD was 8.4 years (interquartile range 7.6 to 9.2 years).
No experiments were performed. The observational associations between (dh)ceramides and cardiometabolic disease incidence were not externally validated.
For the EPIC-Potsdam GWAS on Cer18:0, Cer20:0, and Cer22:0, we performed lookup studies in two independent, first with partly unpublished results from EUROSPAN (European special populations research network: quantifying and harnessing genetic variation for gene discovery) consortium, and second with published SNP-Cer22:0 associations from the Framingham Heart Study Offspring Cohort (n=2217, Cer18:0 and Cer20:0 not available). The other (dh)ceramides associated with cardiometabolic risk in EPIC-Potsdam were not available in the Framingham Heart Study Offspring Cohort. These resources were also used to replicate Mendelian randomization analyses for Cer 22:0. No other replications were attempted.

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Blinding
Behavioural & social sciences study design All studies must disclose on these points even when the disclosure is negative. The laboratory personnel that generated the (dh)ceramide measurements was blinded to the case status and all other phenotypical characteristics of the blood specimen donors. As usual, the epidemiological data analysts were not blinded.
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