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Diabetologia. 2012 Feb;55(2):421-31. doi: 10.1007/s00125-011-2384-1. Epub 2011 Nov 29.

Plasma deoxysphingolipids: a novel class of biomarkers for the metabolic syndrome?

Author information

1
Institute for Clinical Chemistry, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland.

Abstract

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 (C(12) to C(18)) 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 × 10⁻⁶) in patients with the metabolic syndrome (0.11 ± 0.04 μmol/l) compared with controls (0.06 ± 0.02 μmol/l) but did not differ between the metabolic syndrome and diabetes groups. Levels of C(16)-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.

PMID:
22124606
DOI:
10.1007/s00125-011-2384-1
[Indexed for MEDLINE]

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