|Year : 2019 | Volume
| Issue : 4 | Page : 261-262
Lipidomics in psoriatic disease: The new kid on the omics block
Ashish J Mathew1, Vinod Chandran2
1 Centre for Prognosis Studies in Rheumatic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
2 Department of Medicine, Division of Rheumatology, University of Toronto, Toronto, Ontario, Canada
|Date of Web Publication||31-Dec-2019|
Dr. Ashish J Mathew
Centre for Prognosis Studies in Rheumatic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Mathew AJ, Chandran V. Lipidomics in psoriatic disease: The new kid on the omics block. Indian J Rheumatol 2019;14:261-2
Lipids are complex, hydrophobic molecules that are pivotal components of cellular membranes. Among their plethora of cellular functions, endogenous lipids act as major mediators in all phases of inflammation. Psoriatic disease is a chronic, heterogeneous, inflammatory condition with varied presentations and multi-organ implications. Lipid metabolism abnormalities and oxidative stress have been described commonly in patients with psoriatic disease. Fatty acid metabolism has a close relationship with the T-helper cell 17 function, which is known to play a critical role in psoriasis. Omega-3 polyunsaturated fatty acid (PUFA) has been shown to suppress inflammatory cell infiltration and epidermal hyperplasia by inhibiting interleukin-23 production by dendritic cells in a mouse model.
Lipidomics is a subfield of metabolomics that works on the principles of analytical chemistry. It relates to the large-scale profiling and quantification of lipidome (complete profile of cellular lipids) in biological systems and its interaction with other lipids, proteins, and metabolites. Lipidomics has undergone rapid progress over the past decade, largely driven by the continuous technological advances in mass spectrometry (MS), nuclear magnetic resonance, fluorescence spectroscopy, and computational methods. Sample preparation, MS-based analysis, and data processing constitute the three main steps of a customary lipidomics workflow. MS-based techniques are quite popular, allowing separation and characterization of charged ionized analytes based on their mass-to-charge ratios. These can be grouped into three categories:
- Global lipidomic analysis – identifying and stratifying thousands of cellular lipid species by a high-throughput basis. Shotgun lipidomics-based platforms play a major role in this analysis
- Targeted lipidomic analysis – identifying one or few lipid classes of interest. Liquid chromatography–mass spectrometry (LC-MS) and LC-MS/MS-based methods are used for this purpose.
- Novel lipid discovery – the discovery of lipid classes. LC coupled with MS methodology is applied in this area.
Lipidomics has found utility in several diseases over the years. Metabolic syndrome and ischemic heart disease, considering their close bond with lipids, have applied lipidomics for risk stratification, population profiling, identification of biomarkers, and monitoring therapeutic responses. Lipidomics has been useful in biomarker development for early diagnosis and prognosis of neurological disorders associated with lipid signaling and metabolism. Bioactive lipids play essential roles in rapidly proliferating cancer cells. Biomarker discovery for early detection of cancers and monitoring of efficacy and toxicity of anticancer therapies has been the major application of lipidomics in cancer management. Similar applications have been successfully tried in ophthalmic conditions. Nutritional lipidomics has enhanced the understanding of the molecular mechanism underlying the health benefits of dietary PUFA and the regulatory roles of omega-3 and omega-6 fatty acids in inflammation. It is early days for lipidomics in psoriatic disease. Targeted and untargeted LC-MS approaches quantifying bioactive lipid mediators in psoriasis patients and healthy controls have depicted disease-specific phenotype profiles represented by PUFA-oxidized derivatives in both skin and blood. Untargeted lipidomics used to identify lipid metabolite signatures through LC-MS in psoriasis patients and healthy controls detected differential expression of several lipids in plasma of the diseased patients. A recent study in patients with psoriatic arthritis (PsA) has described eicosanoid profiling and its association with joint inflammation using the LC-MS technique. Both pro- and anti-inflammatory eicosanoids were associated with joint disease scores.
In this issue of the Indian Journal of Rheumatology, Yaman et al. report the ratio of n-6/n-3 fatty acids in the erythrocyte membrane of psoriasis patients and its association with inflammatory markers. Lipids were extracted using a freeze dryer and fatty acid composition was determined using gas chromatography. The authors noted a significantly higher n-6/n-3 PUFA ratio correlating positively with inflammatory markers in PsA patients compared to the controls. Besides, a differential correlation was noted between the individual fractions with disease activity. No association was noted with disease severity. This may underscore a sampling bias, as most patients were inactive. Although limited by small, homogeneous patients and specificity of lipid extraction techniques, this study spurs interest toward adopting lipidomics in psoriatic disease for better defining the role of n-6 and n-3 PUFA in pathogenesis.
The implementation of lipidomics is often crippled by challenges. Lack of uniformity in methodologies and technologies has led to issues with reproducibility. Standardization of techniques and guidelines for the process is critical for better reporting. Profiling of low-abundant lipids in a minimal-sized sample is another limitation. The utility of lipidomics in psoriatic disease for biomarker discovery, treatment efficacy, and side effect profile of newer therapeutic targets warrants further evaluation in the quest for precision medicine.
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