Summary of Study ST002243
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001432. The data can be accessed directly via it's Project DOI: 10.21228/M8MQ5M This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST002243 |
| Study Title | Lipidomics analysis of Friedreich's ataxia (FRDA) (part II) |
| Study Type | Untargeted and targeted (PRM) analysis |
| Study Summary | Friedreich’s Ataxia (FRDA) is an autosomal neurodegenerative disease caused by the deficiency of protein frataxin. Frataxin functions in the assembly of iron-sulfur clusters that are important for iron homeostasis and metabolic functions. To identify metabolic features that can be used for potential biomarkers in FRDA plasma, we performed a targeted multi-omics (metabolomics, lipidomics, and proteomics) analysis using discovery-validation cohort design. Muti-omics analysis revealed that FRDA patients had dysregulated sphingolipid metabolism, phospholipid metabolism, citric acid cycle, amino acid metabolism, and apolipoprotein metabolism. Sphingolipid dysfunctions were revealed by decreased very long chain ceramides but unchanged long chain ceramides in FRDA plasma, which resulted in the increased ratio of long chain ceramides to very long chain ceramides. Decreased very long chain ceramides distinguished FRDA patients from healthy controls and showed good predictive capacities with AUC values from 0.75 to 0.85. Furthermore, by performing lipidomic and stable isotope tracing experiment in induced pluripotent stem cell differentiated cardiomyocytes (iPSC-CMs, we demonstrated that frataxin deficiency affected ceramide synthase (CerS2), and preferentially enriched long chain ceramides and depleted very long chain ceramides. Moreover, ceramide metabolism was differentially regulated in a tissue-specific manner. Finally, machine learning model increased the prediction of FRDA using the combination of three metabolites (AUC > 0.9). In conclusion, decreased very long chain ceramides are potential biomarkers and therapeutic target in FRDA patients. |
| Institute | University of Pennsylvania |
| Last Name | Wang |
| First Name | Dezhen |
| Address | 421 Curie Blvd, Philadelphia, PA, 19104, USA |
| dezhen.wang@pennmedicine.upenn.edu | |
| Phone | 5312185610 |
| Submit Date | 2022-07-29 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2022-08-22 |
| Release Version | 1 |
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Collection:
| Collection ID: | CO002322 |
| Collection Summary: | Venous blood was drawn in 8.5 mL purple cap Vacutainer EDTA tubes and gently invert to mix. Plasma was collected after centrifugation at 1000 g for 15 min. All samples were immediately aliquoted to Eppendorf tubes and frozen at -80 ºC until analysis. |
| Sample Type: | Blood (plasma) |
| Storage Conditions: | -80℃ |
