Plasma deoxysphingolipids: a novel class of biomarkers for the metabolic syndrome?
Othman, A. ; Rütti, M. ; Ernst, D. ; Saely, C. ; Rein, P. ; Drexel, H. ; Porretta-Serapiglia, C. ; Lauria, G. ; Bianchi, R. ; von Eckardstein, A. ; Hornemann, T.
In: Diabetologia, 2012, vol. 55, no. 2, p. 421-431
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- Aims/hypothesis: Sphingolipid synthesis is typically initiated by the conjugation of l-serine and palmitoyl-CoA, a reaction catalysed by serine palmitoyltransferase (SPT). SPT can also metabolise other acyl-CoAs (C12 to C18) and other amino acids such as l-alanine and glycine, giving rise to a spectrum of atypical sphingolipids. Here, we aimed to identify changes in plasma levels of these atypical sphingolipids to explore their potential as biomarkers in the metabolic syndrome and diabetes. Methods: We compared the plasma profiles of ten sphingoid bases in healthy individuals with those of patients with the metabolic syndrome but not diabetes, and diabetic patients (n = 25 per group). The results were verified in a streptozotocin (STZ) rat model. Univariate and multivariate statistical analyses were used. Results: Deoxysphingolipids (dSLs) were significantly elevated ( $$ p = {5} \times {1}{0^{{ - {6}}}} $$ ) in patients with the metabolic syndrome (0.11 ± 0.04μmol/l) compared with controls (0.06 ± 0.02μmol/l) but did not differ between the metabolic syndrome and diabetes groups. Levels of C16-sphingosine-based sphingolipids were significantly lowered in diabetic patients but not in patients with the metabolic syndrome but without diabetes (p = 0.008). Significantly elevated dSL levels were also found in the plasma and liver of STZ rats. A principal component analysis revealed a similar or even closer association of dSLs with diabetes and the metabolic syndrome in comparison with the established biomarkers. Conclusions/interpretation: We showed that dSLs are significantly elevated in patients with type 2 diabetes mellitus and non-diabetic metabolic syndrome compared with healthy controls. They may, therefore, be useful novel biomarkers to improve risk prediction and therapy monitoring in these patients