MSACL 2019 US Abstract

Spatial Metabolomics Identifies a Glomerular Sphingomyelin as a Potential Therapeutic Target for the Treatment of Diabetic Kidney Disease

Guanshi Zhang (1,2), Dusan Velikovic (3), Viktor Drel (1,2), Shweta Bansal (1,2), Manjeri A. Venkatachalam (4), Evren Azeloglu (5), Ljiljana Pasa-Tolic (3), Theodore Alexandrov (6,7), Christopher Anderton (1,3), Kumar Sharma (1,2)
(1) Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health San Antonio, TX (2) Audie L. Murphy Memorial VA Hospital, South Texas Veterans Health Care System, San Antonio, TX (3) Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA (4) Department of Pathology, University of Texas Health San Antonio, TX (5) Division of Nephrology, Icahn School of Medicine at Mount Sinai, NY (6) Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany (7) Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA

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Guanshi Zhang (Presenter) UT Health San Antonio

Presenter Bio: I am an Assistant Professor/Research at The Center for Renal Precision Medicine, UT Health San Antonio (UTHSA). I have more than six years’ experience in MS based metabolomics studies. My initial metabolomics training in MS- and NMR- based equipment and bioinformatics tools was during my PhD in The Metabolomics Innovation Centre, University of Alberta (09/2012-08/2016), Canada with Drs. Ametaj and Wishart (09/2016-12/2016: Postdoc Fellow). During that time, I ran several MS and NMR instruments and became familiar with MetaboAnalyst for data interpretation. Upon joining the Institute of Metabolomic Medicine at UC San Diego (01/2017-06/2017) with Dr. Sharma, I had intensive training with the lab of Dr. Dorrestein at UCSD for MSI. With Dr. Sharma’s move to San Antonio, I helped set up the MSI platform with him at UTHSA (07/2017-10/2018: Postdoc Fellow; 10/2018-present: Assistant Professor).

Relevant Financial Disclosures (within past 24 months) No relevant financial relationship(s) to disclose. Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

The current study is a part of the NIDDK Kidney Precision Medicine Project (KPMP). The study was designed to optimize untargeted and targeted mass spectrometry imaging (MSI) based spatial metabolomics analysis of tissues (human kidney biopsy and nephrectomy) from normal and diseased kidneys. Our major goal was to contribute metabolite data in discrete renal compartments to generate metabolite atlases of the kidney from normal, acute kidney injury, chronic kidney disease, and disease subgroups. In addition, major metabolic pathways involved in the disease development and novel therapeutic targets for the treatment of different kidney diseases can be identified.