Serum Metabolomics Reveals Higher Levels of Polyunsaturated Fatty Acids in Lepromatous Leprosy: Potential Markers for Susceptibility and Pathogenesis

Abstract

BackgroundLeprosy is a disease of the skin and peripheral nervous system caused by the obligate intracellular bacterium Mycobacterium leprae. The clinical presentations of leprosy are spectral, with the severity of disease determined by the balance between the cellular and humoral immune response of the host. The exact mechanisms that facilitate disease susceptibility, onset and progression to certain clinical phenotypes are presently unclear. Various studies have examined lipid metabolism in leprosy, but there has been limited work using whole metabolite profiles to distinguish the clinical forms of leprosy.Methodology and Principal FindingsIn this study we adopted a metabolomics approach using high mass accuracy ultrahigh pressure liquid chromatography mass spectrometry (UPLC-MS) to investigate the circulatory biomarkers in newly diagnosed untreated leprosy patients. Sera from patients having bacterial indices (BI) below 1 or above 4 were selected, subjected to UPLC-MS, and then analyzed for biomarkers which distinguish the polar presentations of leprosy. We found significant increases in the abundance of certain polyunsaturated fatty acids (PUFAs) and phospholipids in the high-BI patients, when contrasted with the levels in the low-BI patients. In particular, the median values of arachidonic acid (2-fold increase), eicosapentaenoic acid (2.6-fold increase) and docosahexaenoic acid (1.6-fold increase) were found to be greater in the high-BI patients.SignificanceEicosapentaenoic acid and docosahexaenoic acid are known to exert anti-inflammatory properties, while arachidonic acid has been reported to have both pro- and anti-inflammatory activities. The observed increase in the levels of several lipids in high-BI patients may provide novel clues regarding the biological pathways involved in the immunomodulation of leprosy. Furthermore, these results may lead to the discovery of biomarkers that can be used to investigate susceptibility to infection, facilitate early diagnosis and monitor the progression of disease.

Global Metabolomic Analysis of a Mammalian Host Infected with Bacillus anthracis

“…However, it appears that decreases in levels of eicosanoids and lysolipids are not universal traits during bacterial infections. Serum profiles of patients infected with Mycobacterium leprae revealed increased levels of anti-inflammatory PUFAs and accumulation of phospholipids (12,45). Feces and liver profiles from mice subjected to infection with Salmonella enterica serovar Typhimurium showed increases in levels of eicosanoid biosynthesis products (50).…”

“…In particular, for sepsis infections, metabolomics has been used to understand the dynamic physiological changes in individual patient metabolic profiles as an alternative to treating them as homogeneous populations (7)(8)(9). On the other hand, basic research studies focused on identifying key metabolic pathways have given insight into physiological changes in specific tissues and/or host systems (10)(11)(12). However, a comprehensive analysis of major host organs and tissues has not yet been performed.…”

Statins Increase Rifampin Mycobactericidal Effect

“…Parihar and colleagues (8) recently demonstrated that cholesterol reduction by statins reduces M. tuberculosis viability in vitro and in vivo, a strategy already proposed in the literature (9). This metabolic remodeling by the mycobacterial infection is responsible for an increase in different classes of lipids in a systemic way, as demonstrated in leprosy patient serum metabolomics studies, in which a correlation was established between the bacilloscopy index (BI) (the bacillary load in skin biopsy samples expressed in a logarithmic scale from 0 to 6) and the abundance of some polyunsaturated fatty acids and phospholipids, such as arachidonic acid, eicosapentaenoic acid, and docosahexaenoic acid (10). Our group also demonstrated an increase in cholesterol ester in multibacillary skin biopsy samples compared to paucibacillary ones (11).…”

Biomarkers of Ebola Viral Disease

“…Net reclassification (NRI) quantifies improvement in the model as a result of adding one or more biomarkers. This approach has been used in acute lung injury and cardiovascular disease to improve the accuracy of risk prediction [10][11][12][13].…”