Commentary For reprint orders, please contact: reprints@future-science.com Understanding neurodegenerative disorders by MS-based lipidomics Cosima D Calvano 1 , Francesco Palmisano 1 & Tommaso RI Cataldi* ,1 1 Dipartimento di Chimica, Universit ` a degli Studi di Bari Aldo Moro, via Orabona 4, 70126 Bari, Italy *Author for correspondence: tommaso.cataldi@uniba.it First draft submitted: 25 January 2018; Accepted for publication: 21 March 2018; Published online: 4 June 2018 Keywords: biomarkers • lipidomics • MS • neurodegenerative diseases • neurolipidomics Lipids in neurodegenerative disorders Lipidomics has been literally revolutionized by recent developments in MS [1] and comprehensive databases, such as LIPID Metabolites And Pathways Strategy (LipidMAPS) [2]. Depending on the MS platform used, hundreds to thousands of lipids have been characterized at different molecular levels. Apart from the most obvious roles of ensuring energy storage and structural integrity of membranes, lipids serve many other specific functions in cellular homeostasis, being involved in the regulation of membrane trafficking and in signal transduction as well. Consequently, dysfunction of lipid signaling and metabolism is widely recognized to play a significant role in many metabolic diseases, such as obesity, atherosclerosis, stroke, hypertension and diabetes (collectively referred to as the ‘metabolic syndrome’) and neurological disorders (e.g., Alzheimer’s, Parkinson’s, amyotrophic lateral sclerosis, Huntington’s and multiple sclerosis). Alzheimer’s disease (AD) is the most common cause of dementia among neurodegenerative disorders; about 46.8 million people living worldwide with dementia have been estimated in 2015 and this number is believed to rise to 75 million in 2030 and 131.5 million in 2050 [3]. AD remains a major health issue that will gain even more ethical and economical concern as the pharmacological management is still an open issue. Research efforts have been heavily focused to improve early detection strategies and diagnostic criteria [4]. The large body of evidence, gathered so far, about the association between AD and abnormal lipid metabolism provides a strong incentive to move from early protein- and gene-centric approaches toward a lipidomics one. This last should provide understanding of AD pathogenesis from a previously unexplored perspective and hold the promises to be a powerful tool for identifying potential biomarkers of AD onset, progression and severity. Lipidomics could also shed light on the temporal and spatial changes of cellular lipidomes, the subcellular organizations among different lipidomes, as well as interactions of lipids with other metabolic partners. The uniqueness and complexity of the neurolipidome make neurolipidomics particularly challenging for various reasons as outlined by Han in an excellent review [5]. Indeed the (central plus peripheral) nervous system (NS) is anatomically very intricate and displays an extraordinarily high degree of interconnectivity and interaction within and between regions. The diversity of functions performed by each structure/region could explain why, compared with other organs, NS contains the largest diversity of lipid classes and species. For instance, apart from diverse phospholipid (PL) classes, NS contains a substantial portion of glycosphingolipid classes whereas the plasmenyl subclass species are the major PL component in neuronal cell membranes [6]. Lipid molecular species containing very long fatty acyl chains (e.g., 22 and 24 carbon atoms) appear enriched, whereas a few neurosteroids are uniquely present in the NS. Ganglia of the peripheral NS have been found to contain a significant fraction of triacylglycerols with odd-numbered acyl chains [7]. MS-based neurolipidomics & biomarkers discovery Recent developments in neurolipidomics have undoubtedly benefited from concurrent tremendous improvements in soft ionization MS techniques, namely MALDI and ESI coupled to a separative step by, for example, LC or in a high-throughput format (shotgun lipidomic). Detection limit has been lowered from micro- to picomolar levels dramatically extending the affordable dynamic range; low abundance lipid classes and/or low abundance molecular species belonging to medium/high abundance lipid classes can now be identified/quantified making possible Bioanalysis (Epub ahead of print) ISSN 1757-6180 10.4155/bio-2018-0023 C  2018 Newlands Press