Identification of circulating sphingosine kinase-related metabolites for prediction of type 2 diabetes

Abstract

Background Sphingosine Kinase (SphK) that catalyzes sphingosine (Sph) to sphingosine 1-phosphate (S1P), plays a key role in both sphingolipid metabolism and cellular signaling. While SphK has been implicated in type 2 diabetes mellitus (T2DM), it is unexplored in humans. Herein, we investigated whether circulating SphK-related metabolites are associated with T2DM incidence in an established prospective cohort. Methods Levels of SphK-related sphingolipid metabolites, including Sph, S1P, dihydrosphingosine (dhSph) and dihydro-S1P (dhS1P) in serum were measured by targeted-lipidomic analyses. By accessing to an established prospective cohort that involves a total of 2486 non-diabetic adults at baseline, 100 subjects who developed T2DM after a mean follow-up of 4.2-years, along with 100 control subjects matched strictly with age, sex, BMI and fasting glucose, were randomly enrolled for the present study. Results Comparison with the control group, medians of serum dhS1P and dhS1P/dhSph ratio at baseline were elevated significantly prior to the onset of T2DM. Each SD increment of dhS1P and dhS1P/dhSph ratio was associated with 53.5% and 54.1% increased risk of incident diabetes, respectively. The predictive effect of circulating dhS1P and dhS1P/dhSph ratio on T2DM incidence was independent of conventional risk factors in multivariate regression models. Furthermore, combination of serum dhS1P and dhS1P/dhSph ratio with conventional clinical indices significantly improved the accuracy of T2DM prediction (AUROC, 0.726), especially for normoglycemic subjects (AUROC, 0.859). Conclusion Circulating levels of dhS1P and dhS1P/dhSph ratio are strongly associated with increased risk of T2DM, and could serve as a useful biomarker for prediction of incident T2DM in normoglycemic populations.

Longitudinal analysis of epigenome-wide DNA methylation reveals novel loci associated with BMI change in East Asians

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DNA methylation age acceleration contributes to the development and prediction of non-alcoholic fatty liver disease

“…The inclusion criteria were age 45 years or older, and the exclusion criteria included refusal to participate in the study or refusal to sign an informed consent form. Initially, genome-wide DNA methylation profiles were measured in the whole blood of 100 participants with new-onset type 2 diabetes at follow-up examination (Cohort 1) as described previously [ 16 ] and a randomly sampled representative cohort of 407 participants (Cohort 2), who were selected using SPSS software by a computer. After excluding the participants with missing liver ultrasound examination, excessive alcohol consumption, or other known chronic liver diseases, 95 participants from Cohort 1 and 356 participants from Cohort 2 were included for further analysis.…”

A one-health approach to identifying and mitigating the impact of endocrine disorders on human and equine athletes

“…On the most basic level, metabolomics can differentiate between healthy individuals and diseased individuals. 170,171 Studies [172][173][174][175] in humans have identified characteristic metabolic signatures of type II diabetes mellitus, obesity, and fatty liver disease. A consistent pattern of reduced glycine and acylcarnitines [176][177][178] with increased concentrations of valine, isoleucine, and α-hydroxybuterate 179,180 has been associated with both basal and dynamic measures of insulin resistance.…”