Serum Metabolic Fingerprinting Identified Putatively Annotated Sphinganine Isomer as a Biomarker of Wolfram Syndrome.
Agnieszka ZmyslowskaMichal CiborowskiMaciej BorowiecWojciech FendlerKarolina PietrowskaEwa ParfieniukKarolina AntosikAleksandra PyziakArleta WaszczykowskaAdam KretowskiWojciech MlynarskiPublished in: Journal of proteome research (2018)
Wolfram syndrome (WFS) is an example of a rare neurodegenerative disease with coexisting endocrine symptoms including diabetes mellitus as the first clinical symptom. Treatment of WFS is still only symptomatic and associated with poor prognosis. Potential markers of disease progression that could be useful for possible intervention trials are not available. Metabolomics has potential to identify such markers. In the present study, serum fingerprinting by LC-QTOF-MS was performed in patients with WFS (n = 13) and in patients with T1D (n = 27). On the basis of the obtained results, aminoheptadecanediol (17:0 sphinganine isomer) (+50%, p = 0.02), as the most discriminatory metabolite, was selected for validation. The 17:0 sphinganine isomer level was determined using the LC-QQQ method in the samples from WFS patients at two time points and compared with samples obtained from patients with T1D (n = 24) and healthy controls (n = 24). Validation analysis showed higher 17:0 sphinganine isomer level in patients with WFS compared to patients with T1D (p = 0.0097) and control group (p < 0.0001) with progressive reduction of its level after two-year follow-up period. Patients with WFS show a unique serum metabolic fingerprint, differentiating them from patients with T1D. Sphinganine derivate seems to be a marker of the ongoing process of neurodegeneration in WFS patients.
Keyphrases
- poor prognosis
- mass spectrometry
- long non coding rna
- multiple sclerosis
- ms ms
- end stage renal disease
- randomized controlled trial
- ejection fraction
- chronic kidney disease
- newly diagnosed
- case report
- simultaneous determination
- prognostic factors
- magnetic resonance imaging
- depressive symptoms
- risk assessment
- climate change
- computed tomography
- insulin resistance
- tandem mass spectrometry