Literature DB >> 29602396

Lipidomics and Biomarker Discovery in Kidney Disease.

Farsad Afshinnia1, Thekkelnaycke M Rajendiran2, Stefanie Wernisch1, Tanu Soni3, Adil Jadoon1, Alla Karnovsky4, George Michailidis5, Subramaniam Pennathur6.   

Abstract

Technological advances in mass spectrometry-based lipidomic platforms have provided the opportunity for comprehensive profiling of lipids in biological samples and shown alterations in the lipidome that occur in metabolic disorders. A lipidomic approach serves as a powerful tool for biomarker discovery and gaining insight to molecular mechanisms of disease, especially when integrated with other -omics platforms (ie, transcriptomics, proteomics, and metabolomics) in the context of systems biology. In this review, we describe the workflow commonly applied to the conduct of lipidomic studies including important aspects of study design, sample preparation, biomarker identification and quantification, and data processing and analysis, as well as crucial considerations in clinical applications. We also review some recent studies of the application of lipidomic platforms that highlight the potential of lipid biomarkers and add to our understanding of the molecular basis of kidney disease.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Lipidomics; biomarkers; mass spectrometry; metabolomics

Mesh:

Substances:

Year:  2018        PMID: 29602396      PMCID: PMC5881936          DOI: 10.1016/j.semnephrol.2018.01.004

Source DB:  PubMed          Journal:  Semin Nephrol        ISSN: 0270-9295            Impact factor:   5.299


  61 in total

Review 1.  Shotgun lipidomics: electrospray ionization mass spectrometric analysis and quantitation of cellular lipidomes directly from crude extracts of biological samples.

Authors:  Xianlin Han; Richard W Gross
Journal:  Mass Spectrom Rev       Date:  2005 May-Jun       Impact factor: 10.946

2.  Lipidomics profiling by high-resolution LC-MS and high-energy collisional dissociation fragmentation: focus on characterization of mitochondrial cardiolipins and monolysocardiolipins.

Authors:  Susan S Bird; Vasant R Marur; Matthew J Sniatynski; Heather K Greenberg; Bruce S Kristal
Journal:  Anal Chem       Date:  2010-12-30       Impact factor: 6.986

3.  Automated identification and quantification of glycerophospholipid molecular species by multiple precursor ion scanning.

Authors:  Christer S Ejsing; Eva Duchoslav; Julio Sampaio; Kai Simons; Ron Bonner; Christoph Thiele; Kim Ekroos; Andrej Shevchenko
Journal:  Anal Chem       Date:  2006-09-01       Impact factor: 6.986

Review 4.  Sphingolipidomics: methods for the comprehensive analysis of sphingolipids.

Authors:  Christopher A Haynes; Jeremy C Allegood; Hyejung Park; M Cameron Sullards
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2008-12-31       Impact factor: 3.205

5.  Elucidation of the double-bond position of long-chain unsaturated fatty acids by multiple-stage linear ion-trap mass spectrometry with electrospray ionization.

Authors:  Fong-Fu Hsu; John Turk
Journal:  J Am Soc Mass Spectrom       Date:  2008-07-16       Impact factor: 3.109

Review 6.  Electrospray mass spectrometry of phospholipids.

Authors:  Melissa Pulfer; Robert C Murphy
Journal:  Mass Spectrom Rev       Date:  2003 Sep-Oct       Impact factor: 10.946

7.  Dichloromethane as a solvent for lipid extraction and assessment of lipid classes and fatty acids from samples of different natures.

Authors:  Elena Cequier-Sánchez; Covadonga Rodríguez; Angel G Ravelo; Rafael Zárate
Journal:  J Agric Food Chem       Date:  2008-05-28       Impact factor: 5.279

8.  Identification of molecular species of glycerophospholipids and sphingomyelin using electrospray mass spectrometry.

Authors:  J L Kerwin; A R Tuininga; L H Ericsson
Journal:  J Lipid Res       Date:  1994-06       Impact factor: 5.922

Review 9.  Net reclassification indices for evaluating risk prediction instruments: a critical review.

Authors:  Kathleen F Kerr; Zheyu Wang; Holly Janes; Robyn L McClelland; Bruce M Psaty; Margaret S Pepe
Journal:  Epidemiology       Date:  2014-01       Impact factor: 4.822

10.  A systems biology strategy reveals biological pathways and plasma biomarker candidates for potentially toxic statin-induced changes in muscle.

Authors:  Reijo Laaksonen; Mikko Katajamaa; Hannu Päivä; Marko Sysi-Aho; Lilli Saarinen; Päivi Junni; Dieter Lütjohann; Joél Smet; Rudy Van Coster; Tuulikki Seppänen-Laakso; Terho Lehtimäki; Juhani Soini; Matej Oresic
Journal:  PLoS One       Date:  2006-12-20       Impact factor: 3.240

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  16 in total

Review 1.  New insights into the mechanisms of diabetic complications: role of lipids and lipid metabolism.

Authors:  Stephanie Eid; Kelli M Sas; Steven F Abcouwer; Eva L Feldman; Thomas W Gardner; Subramaniam Pennathur; Patrice E Fort
Journal:  Diabetologia       Date:  2019-07-25       Impact factor: 10.122

2.  Early pregnancy prediction of gestational diabetes mellitus risk using prenatal screening biomarkers in nulliparous women.

Authors:  Brittney M Snyder; Rebecca J Baer; Scott P Oltman; Jennifer G Robinson; Patrick J Breheny; Audrey F Saftlas; Wei Bao; Andrea L Greiner; Knute D Carter; Larry Rand; Laura L Jelliffe-Pawlowski; Kelli K Ryckman
Journal:  Diabetes Res Clin Pract       Date:  2020-04-06       Impact factor: 5.602

3.  Increased lipogenesis and impaired β-oxidation predict type 2 diabetic kidney disease progression in American Indians.

Authors:  Farsad Afshinnia; Viji Nair; Jiahe Lin; Thekkelnaycke M Rajendiran; Tanu Soni; Jaeman Byun; Kumar Sharma; Patrice E Fort; Thomas W Gardner; Helen C Looker; Robert G Nelson; Frank C Brosius; Eva L Feldman; George Michailidis; Matthias Kretzler; Subramaniam Pennathur
Journal:  JCI Insight       Date:  2019-11-01

4.  Lipidomic analysis reveals disturbances in glycerophospholipid and sphingolipid metabolic pathways in benzene-exposed mice.

Authors:  Linling Yu; Rongli Sun; Kai Xu; Yunqiu Pu; Jiawei Huang; Manman Liu; Minjian Chen; Juan Zhang; Lihong Yin; Yuepu Pu
Journal:  Toxicol Res (Camb)       Date:  2021-06-15       Impact factor: 2.680

5.  Association Between Increased Lipid Profiles and Risk of Diabetic Retinopathy in a Population-Based Case-Control Study.

Authors:  Zhenzhen Liu; Mingxi Shao; Jun Ren; Yichao Qiu; Shengjie Li; Wenjun Cao
Journal:  J Inflamm Res       Date:  2022-06-10

Review 6.  Lipidomic approaches to dissect dysregulated lipid metabolism in kidney disease.

Authors:  Judy Baek; Chenchen He; Farsad Afshinnia; George Michailidis; Subramaniam Pennathur
Journal:  Nat Rev Nephrol       Date:  2021-10-06       Impact factor: 42.439

7.  Modulation of Lipid Metabolism by Celastrol.

Authors:  Ting Zhang; Qi Zhao; Xuerong Xiao; Rui Yang; Dandan Hu; Xu Zhu; Frank J Gonzalez; Fei Li
Journal:  J Proteome Res       Date:  2019-02-12       Impact factor: 4.466

Review 8.  Metabolomics of Type 1 and Type 2 Diabetes: Insights into Risk Prediction and Mechanisms.

Authors:  Daniel Gonzalez Izundegui; Matthew Nayor
Journal:  Curr Diab Rep       Date:  2022-02-03       Impact factor: 4.810

9.  PathBank: a comprehensive pathway database for model organisms.

Authors:  David S Wishart; Carin Li; Ana Marcu; Hasan Badran; Allison Pon; Zachary Budinski; Jonas Patron; Debra Lipton; Xuan Cao; Eponine Oler; Krissa Li; Maïlys Paccoud; Chelsea Hong; An C Guo; Christopher Chan; William Wei; Miguel Ramirez-Gaona
Journal:  Nucleic Acids Res       Date:  2020-01-08       Impact factor: 16.971

10.  Renin-angiotensin system inhibition reverses the altered triacylglycerol metabolic network in diabetic kidney disease.

Authors:  Kelli M Sas; Jiahe Lin; Chih-Hong Wang; Hongyu Zhang; Jharna Saha; Thekkelnaycke M Rajendiran; Tanu Soni; Viji Nair; Felix Eichinger; Matthias Kretzler; Frank C Brosius; George Michailidis; Subramaniam Pennathur
Journal:  Metabolomics       Date:  2021-07-04       Impact factor: 4.747

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