Evolution of biomarker research in autoimmunity conditions for health professionals and clinical practice.

Medical abzymology has made a great contribution to the development of general autoimmunity theory: it has put the autoantibodies (Ab) as the key brick of the theory to the level of physiological functionality by providing such Ab with the ability to catalyze and mediate direct and independent cytotoxic effect on cellular and molecular targets. Natural catalytic autoantibodies (abzymes) while being a pool of canonical Abs and possessing catalytic activity belong to the new group of physiologically active substances whose features and properties are evolutionary consolidated in one functionally active biomolecule. Therefore, further studies on Ab-mediated autoAg degradation and other targeted Ab-mediated proteolysis may provide biomarkers of newer generations and thus a supplementary tool for assessing the disease progression and predicting disability of the patients and persons at risks. This chapter is a summary of current knowledge and prognostic perspectives toward catalytic Abs in autoimmunity and thus some autoimmune clinical cases, their role in pathogenesis, and the exploitation of both whole molecules and their constituent parts in developing highly effective targeted drugs of the future to come, and thus the therapeutic protocols being individualized.

Metabolic profiling of epidermal and mesophyll tissues under water-deficit stress in Opuntia ficus-indica reveals stress-adaptive metabolic responses.

Cactus pear (Opuntia ficus-indica) is a high productivity species within the Cactaceae grown in many semiarid parts of the world for food, fodder, forage, and biofuels. O. ficus-indica utilises obligate crassulacean acid metabolism (CAM), an adaptation that greatly improves water-use efficiency (WUE) and reduces crop water usage. To better understand CAM-related metabolites and water-deficit stress responses of O. ficus-indica, comparative metabolic profiling was performed on mesophyll and epidermal tissues collected from well-watered and water-deficit stressed cladodes at 50% relative water content (RWC). Tissues were collected over a 24-h period to identify metabolite levels throughout the diel cycle and analysed using a combination of acidic/basic ultra-high-performance liquid chromatography/tandem mass spectrometry (UHPLC/MS/MS) and gas chromatography/mass spectrometry (GC/MS) platforms. A total of 382 metabolites, including 210 (55%) named and 172 (45%) unnamed compounds, were characterised across both tissues. Most tricarboxylic acid (TCA) cycle and glycolysis intermediates were depleted in plants undergoing water-deficit stress indicative of CAM idling or post-idling, while the raffinose family oligosaccharides (RFO) accumulated in both mesophyll and epidermal tissues as osmoprotectants. Levels of reduced glutathione and other metabolites of the ascorbate cycle as well as oxylipins, stress hormones such as traumatic acid, and nucleotide degradation products were increased under water-deficit stress conditions. Notably, tryptophan accumulation, an atypical response, was significantly (24-fold) higher during all time points in water-deficit stressed mesophyll tissue compared with well-watered controls. Many of the metabolite increases were indicative of a highly oxidising environment under water-deficit stress. A total of 34 unnamed metabolites also accumulated in response to water-deficit stress indicating that such compounds might play important roles in water-deficit stress tolerance.

Identifying mental health issues in detained youth: Testing the structure and invariance of the Massachusetts Youth Screening Inventory-Version 2 (MAYSI-2).

This study examined the factor structure of the Massachusetts Youth Screening Instrument-Version 2 (MAYSI-2), a brief self-report measure designed to flag clinically significant mental health needs among youth entering the juvenile justice system. Participants were 981 detained youth in the southeastern United States (mean age = 14.58 years; SD = 1.28 years; 67.5% male; 71.5% African American). Confirmatory factor analyses showed that a seven-factor model represented a satisfactory solution for the data, similar to previous research. The factor structure fit well across gender, age group, race (Black/White), and offense type (violent/nonviolent). Given the widespread use of the MAYSI-2 in juvenile justice settings, examining its psychometric properties is of key importance. Implications and limitations of the study are discussed. (PsycINFO Database Record

Proteomics and metabolomics analyses reveal the cucurbit sieve tube system as a complex metabolic space.

The plant vascular system, and specifically the phloem, plays a pivotal role in allocation of fixed carbon to developing sink organs. Although the processes involved in loading and unloading of sugars and amino acids are well characterized, little information is available regarding the nature of other metabolites in the sieve tube system (STS) at specific sites along the pathway. Here, we elucidate spatial features of metabolite composition mapped with phloem enzymes along the cucurbit STS. Phloem sap (PS) was collected from the loading (source), unloading (apical sink region) and shoot-root junction regions of cucumber, watermelon and pumpkin. Our PS analyses revealed significant differences in the metabolic and proteomic profiles both along the source-sink pathway and between the STSs of these three cucurbits. In addition, metabolite profiles established for PS and vascular tissue indicated the presence of distinct compositions, consistent with the operation of the STS as a unique symplasmic domain. In this regard, at various locations along the STS we could map metabolites and their related enzymes to specific metabolic pathways. These findings are discussed with regard to the function of the STS as a unique and highly complex metabolic space within the plant vascular system.

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health.

Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.

Untargeted metabolomic analysis for the clinical screening of inborn errors of metabolism.

Global metabolic profiling currently achievable by untargeted mass spectrometry-based metabolomic platforms has great potential to advance our understanding of human disease states, including potential utility in the detection of novel and known inborn errors of metabolism (IEMs). There are few studies of the technical reproducibility, data analysis methods, and overall diagnostic capabilities when this technology is applied to clinical specimens for the diagnosis of IEMs. We explored the clinical utility of a metabolomic workflow capable of routinely generating semi-quantitative z-score values for ~900 unique compounds, including ~500 named human analytes, in a single analysis of human plasma. We tested the technical reproducibility of this platform and applied it to the retrospective diagnosis of 190 individual plasma samples, 120 of which were collected from patients with a confirmed IEM. Our results demonstrate high intra-assay precision and linear detection for the majority compounds tested. Individual metabolomic profiles provided excellent sensitivity and specificity for the detection of a wide range of metabolic disorders and identified novel biomarkers for some diseases. With this platform, it is possible to use one test to screen for dozens of IEMs that might otherwise require ordering multiple unique biochemical tests. However, this test may yield false negative results for certain disorders that would be detected by a more well-established quantitative test and in its current state should be considered a supplementary test. Our findings describe a novel approach to metabolomic analysis of clinical specimens and demonstrate the clinical utility of this technology for prospective screening of IEMs.

Plasma metabolomic biomarker panel to distinguish patients with amyotrophic lateral sclerosis from disease mimics.

Our objective was to identify plasma biomarkers of ALS that can aid in distinguishing patients with ALS from those with disease mimics. In this multi-center study, plasma samples were collected from 172 patients recently diagnosed with ALS, 50 healthy controls, and 73 neurological disease mimics. Samples were analyzed using metabolomics. Using all identified biochemicals detected in > 50% of all samples in the metabolomics analysis, samples were classified as ALS or mimic with 65% sensitivity and 81% specificity by LASSO analysis (AUC of 0.76). A subset panel of 32 candidate biomarkers classified these diagnosis groups with a specificity of 90%/sensitivity 58% (AUC of 0.81). Creatinine was lower in subjects with lower revised ALS Functional Rating Scale (ALSFRS-R) scores. In conclusion, ALS can be distinguished from neurological disease mimics by global biochemical profiling of plasma samples. Our analysis identified ALS versus mimics with relatively high sensitivity. We identified a subset of 32 metabolites that identify patients with ALS with a high specificity. Interestingly, lower creatinine correlates significantly with a lower ALSFRS-R score. Finally, molecules previously reported to be important in disease pathophysiology, such as urate, are included in our metabolite panel.

Serum metabolomics indicate altered cellular energy metabolism in children with cystic fibrosis.

BACKGROUND: Cystic fibrosis (CF) is a multi-system disease affecting multiple organs and cells besides the respiratory system. Metabolomic profiling allows simultaneous detection of biochemicals originating from cells, organs, or exogenous origin that may be valuable for monitoring of disease severity or in diagnosis. AIM: We hypothesized that metabolomics using serum from children would differentiate CF from non-CF lung disease subjects and would provide insight into metabolism in CF. METHODS: Serum collected from children with CF (n = 31) and 31 age and gender matched children with other lung diseases was used for metabolomic profiling by gas- and liquid-chromatography. Relative concentration of metabolites was compared between the groups using partial least square discriminant analyses (PLS-DA) and linear modeling. RESULTS: A clear separation of the two groups was seen in PLS-DA. Linear model found that among the 459 detected metabolites 92 differed between CF and non-CF. These included known biochemicals in lipid metabolism, oxidants, and markers consistent with abnormalities in bile acid processing. Bacterial metabolites were identified and differed between the groups indicating intestinal dysbiosis in CF. As a novel finding several pathways were markedly different in CF, which jointly point towards decreased activity in the ß-oxidation of fatty acids. These pathways include low ketone bodies, low medium chain carnitines, elevated di-carboxylic acids and decreased 2-hydroxybutyrate from amino acid metabolism in CF compared to non-CF. CONCLUSION: Serum metabolomics discriminated CF from non-CF and show altered cellular energy metabolism in CF potentially reflecting mitochondrial dysfunction. Future studies are indicated to examine their relation to the underlying CF defect and their use as biomarkers for disease severity or for cystic fibrosis transmembrane regulator (CFTR) function in an era of CFTR modifying drugs.

Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome.

Genetically modified (GM) crops currently constitute a significant and growing part of agriculture.An important aspect of GM crop adoption is to demonstrate safety; identifying differences in end points with respect to conventional crops is a part of the safety assessment process [corrected]. Untargeted metabolomics has the ability to profile diverse classes of metabolites and thus could be an adjunct for identification of differences between the GM crop and its conventional counterpart [corrected].To account for environmental effects and introgression of GM traits into diverse genetic backgrounds, we propose that the assessment for GM crop metabolic composition should be understood within the context of the natural variation for the crop. Using a non-targeted metabolomics platform, we profiled 169 metabolites and established their dynamic ranges from the seeds of 49 conventional soybean lines representing the current commercial genetic diversity. We further demonstrated that the metabolome of a GM line had no significant deviation from natural variation within the soybean metabolome, with the exception of changes in the targeted engineered pathway.

Application of combined omics platforms to accelerate biomedical discovery in diabesity.

Diabesity has become a popular term to describe the specific form of diabetes that develops late in life and is associated with obesity. While there is a correlation between diabetes and obesity, the association is not universally predictive. Defining the metabolic characteristics of obesity that lead to diabetes, and how obese individuals who develop diabetes different from those who do not, are important goals. The use of large-scale omics analyses (e.g., metabolomic, proteomic, transcriptomic, and lipidomic) of diabetes and obesity may help to identify new targets to treat these conditions. This report discusses how various types of omics data can be integrated to shed light on the changes in metabolism that occur in obesity and diabetes.

Examining the validity of the Structured Assessment of Violence Risk in Youth (SAVRY) for predicting probation outcomes among adjudicated juvenile offenders.

The current study examined the ability of the Structured Assessment of Violence Risk for Youth (SAVRY), a standardized risk assessment instrument, to predict probation outcomes among a sample of 158 adjudicated juvenile offenders placed on probation. Traditionally, the SAVRY has been used to measure violence risk among adolescents after release from custody. More recently, a delinquency risk measure based on SAVRY responses was developed, which could be useful for other types of outcome. This study examined the predictive validity of both summary risk ratings (SRR) for probation outcomes, including the reason for terminating probation and length of time on probation. A number of bivariate analyses and Cox regression models provided preliminary support for the ability of the nonviolent delinquency SRR, and modest support for the violence SRR, to predict probation outcomes. The implications for use of the SAVRY SRRs during juvenile justice system decision-making and recommendations for future research are discussed.

Perturbation of bile acid homeostasis is an early pathogenesis event of drug induced liver injury in rats.

Drug-induced liver injury (DILI) is a significant consideration for drug development. Current preclinical DILI assessment relying on histopathology and clinical chemistry has limitations in sensitivity and discordance with human. To gain insights on DILI pathogenesis and identify potential biomarkers for improved DILI detection, we performed untargeted metabolomic analyses on rats treated with thirteen known hepatotoxins causing various types of DILI: necrosis (acetaminophen, bendazac, cyclosporine A, carbon tetrachloride, ethionine), cholestasis (methapyrilene and naphthylisothiocyanate), steatosis (tetracycline and ticlopidine), and idiosyncratic (carbamazepine, chlorzoxasone, flutamide, and nimesulide) at two doses and two time points. Statistical analysis and pathway mapping of the nearly 1900 metabolites profiled in the plasma, urine, and liver revealed diverse time and dose dependent metabolic cascades leading to DILI by the hepatotoxins. The most consistent change induced by the hepatotoxins, detectable even at the early time point/low dose, was the significant elevations of a panel of bile acids in the plasma and urine, suggesting that DILI impaired hepatic bile acid uptake from the circulation. Furthermore, bile acid amidation in the hepatocytes was altered depending on the severity of the hepatotoxin-induced oxidative stress. The alteration of the bile acids was most evident by the necrosis and cholestasis hepatotoxins, with more subtle effects by the steatosis and idiosyncratic hepatotoxins. Taking together, our data suggest that the perturbation of bile acid homeostasis is an early event of DILI. Upon further validation, selected bile acids in the circulation could be potentially used as sensitive and early DILI preclinical biomarkers.

Metabolic profiling of transgenic potato tubers expressing Arabidopsis dehydration response element-binding protein 1A (DREB1A).

Untargeted metabolome analyses play a critical role in understanding possible metabolic fluctuations of crops under varying environmental conditions. This study reports metabolic profiles of transgenic potato tubers expressing the Arabidopsis DREB1A transcription factor gene, which induces expression of genes involved in environmental stress tolerance. A combination of targeted and untargeted metabolomics demonstrated considerable metabolome differences between the transgenic lines and nontransgenic parent cultivars. In the transgenic lines, stimulation of stress responses was suggested by elevated levels of the glutathione metabolite, γ-aminobutyric acid (GABA), and by the accumulation of ß-cyanoalanine, a byproduct of ethylene biosynthesis. These results suggest that the Arabidopsis DREB1A expression might directly or indirectly enhance endogenous potato stress tolerance systems. The results indicate that transgenesis events could alter the metabolic compositions in food crops, and therefore metabolomics analysis could be a most valuable tool to monitor such changes.

Metabolomic profiling in Selaginella lepidophylla at various hydration states provides new insights into the mechanistic basis of desiccation tolerance.

Selaginella lepidophylla is one of only a few species of spike mosses (Selaginellaceae) that have evolved desiccation tolerance (DT) or the ability to 'resurrect' from an air-dried state. In order to understand the metabolic basis of DT, S. lepidophylla was subjected to a five-stage, rehydration/dehydration cycle, then analyzed using non-biased, global metabolomics profiling technology based on GC/MS and UHLC/MS/MS(2) platforms. A total of 251 metabolites including 167 named (66.5%) and 84 (33.4%) unnamed compounds were characterized. Only 42 (16.7%) and 74 (29.5%) of compounds showed significantly increased or decreased abundance, respectively, indicating that most compounds were produced constitutively, including highly abundant trehalose, sucrose, and glucose. Several glycolysis/gluconeogenesis and tricarboxylic acid (TCA) cycle intermediates showed increased abundance at 100% relative water content (RWC) and 50% RWC. Vanillate, a potent antioxidant, was also more abundant in the hydrated state. Many different sugar alcohols and sugar acids were more abundant in the hydrated state. These polyols likely decelerate the rate of water loss during the drying process as well as slow water absorption during rehydration, stabilize proteins, and scavenge reactive oxygen species (ROS). In contrast, nitrogen-rich and γ-glutamyl amino acids, citrulline, and nucleotide catabolism products (e.g. allantoin) were more abundant in the dry states, suggesting that these compounds might play important roles in nitrogen remobilization during rehydration or in ROS scavenging. UV-protective compounds such as 3-(3-hydroxyphenyl)propionate, apigenin, and naringenin, were more abundant in the dry states. Most lipids were produced constitutively, with the exception of choline phosphate, which was more abundant in dry states and likely plays a role in membrane hydration and stabilization. In contrast, several polyunsaturated fatty acids were more abundant in the hydrated states, suggesting that these compounds likely help maintain membrane fluidity during dehydration. Lastly, S. lepidophylla contained seven unnamed compounds that displayed twofold or greater abundance in dry or rehydrating states, suggesting that these compounds might play adaptive roles in DT.

Comparative metabolic profiling between desiccation-sensitive and desiccation-tolerant species of Selaginella reveals insights into the resurrection trait.

Spike mosses (Selaginellaceae) represent an ancient lineage of vascular plants in which some species have evolved desiccation tolerance (DT). A sister-group contrast to reveal the metabolic basis of DT was conducted between a desiccation-tolerant species, Selaginella lepidophylla, and a desiccation-sensitive species, Selaginella moellendorffii, at 100% relative water content (RWC) and 50% RWC using non-biased, global metabolomics profiling technology, based on GC/MS and UHLC/MS/MS(2) platforms. A total of 301 metabolites, including 170 named (56.5%) and 131 (43.5%) unnamed compounds, were characterized across both species. S. lepidophylla retained significantly higher abundances of sucrose, mono- and polysaccharides, and sugar alcohols than did S. moellendorffii. Aromatic amino acids, the well-known osmoprotectant betaine and flavonoids were also more abundant in S. lepidophylla. Notably, levels of γ-glutamyl amino acid, linked with glutathione metabolism in the detoxification of reactive oxygen species, and with possible nitrogen remobilization following rehydration, were markedly higher in S. lepidophylla. Markers for lipoxygenase activity were also greater in S. lepidophylla, especially at 50% RWC. S. moellendorffii contained more than twice the number of unnamed compounds, with only a slightly greater abundance than in S. lepidophylla. In contrast, S. lepidophylla contained 14 unnamed compounds of fivefold or greater abundance than in S. moellendorffii, suggesting that these compounds might play critical roles in DT. Overall, S. lepidophylla appears poised to tolerate desiccation in a constitutive manner using a wide range of metabolites with some inducible components, whereas S. moellendorffii mounts only limited metabolic responses to dehydration stress.

Biochemical alterations associated with ALS.

Our objective was to identify metabolic pathways affected by ALS using non-targeted metabolomics in plasma, comparing samples from healthy volunteers to those from ALS patients. This discovery could become the basis for the identification of therapeutic targets and diagnostic biomarkers of ALS. Two distinct cross-sectional studies were conducted. Plasma was collected from 62 (Study 1) and 99 (Study 2) participants meeting El Escorial criteria for possible, probable, or definite ALS; 69 (Study 1) and 48 (Study 2) healthy controls samples were collected. Global metabolic profiling was used to detect and evaluate biochemical signatures of ALS. Twenty-three metabolites were significantly altered in plasma from ALS patients in both studies. These metabolites include biochemicals in pathways associated with neuronal change, hypermetabolism, oxidative damage, and mitochondrial dysfunction, all of which are proposed disease mechanisms in ALS. The data also suggest possible hepatic dysfunction associated with ALS. In conclusion, the data presented here provide insight into the pathophysiology of ALS while suggesting promising areas of focus for future studies. The metabolomics approach can generate novel hypotheses regarding ALS disease mechanisms with the potential to identify therapeutic targets and novel diagnostic biomarkers.

A sister group contrast using untargeted global metabolomic analysis delineates the biochemical regulation underlying desiccation tolerance in Sporobolus stapfianus.

Understanding how plants tolerate dehydration is a prerequisite for developing novel strategies for improving drought tolerance. The desiccation-tolerant (DT) Sporobolus stapfianus and the desiccation-sensitive (DS) Sporobolus pyramidalis formed a sister group contrast to reveal adaptive metabolic responses to dehydration using untargeted global metabolomic analysis. Young leaves from both grasses at full hydration or at 60% relative water content (RWC) and from S. stapfianus at lower RWCs were analyzed using liquid and gas chromatography linked to mass spectrometry or tandem mass spectrometry. Comparison of the two species in the fully hydrated state revealed intrinsic differences between the two metabolomes. S. stapfianus had higher concentrations of osmolytes, lower concentrations of metabolites associated with energy metabolism, and higher concentrations of nitrogen metabolites, suggesting that it is primed metabolically for dehydration stress. Further reduction of the leaf RWC to 60% instigated a metabolic shift in S. stapfianus toward the production of protective compounds, whereas S. pyramidalis responded differently. The metabolomes of S. stapfianus leaves below 40% RWC were strongly directed toward antioxidant production, nitrogen remobilization, ammonia detoxification, and soluble sugar production. Collectively, the metabolic profiles obtained uncovered a cascade of biochemical regulation strategies critical to the survival of S. stapfianus under desiccation.

Metabolomic profiling reveals biochemical pathways and biomarkers associated with pathogenesis in cystic fibrosis cells.

Cystic fibrosis (CF) is a life-shortening disease caused by a mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. To gain an understanding of the epithelial dysfunction associated with CF mutations and discover biomarkers for therapeutics development, untargeted metabolomic analysis was performed on primary human airway epithelial cell cultures from three separate cohorts of CF patients and non-CF subjects. Statistical analysis revealed a set of reproducible and significant metabolic differences between the CF and non-CF cells. Aside from changes that were consistent with known CF effects, such as diminished cellular regulation against oxidative stress and osmotic stress, new observations on the cellular metabolism in the disease were generated. In the CF cells, the levels of various purine nucleotides, which may function to regulate cellular responses via purinergic signaling, were significantly decreased. Furthermore, CF cells exhibited reduced glucose metabolism in glycolysis, pentose phosphate pathway, and sorbitol pathway, which may further exacerbate oxidative stress and limit the epithelial cell response to environmental pressure. Taken together, these findings reveal novel metabolic abnormalities associated with the CF pathological process and identify a panel of potential biomarkers for therapeutic development using this model system.

Ethylene glycol monomethyl ether-induced toxicity is mediated through the inhibition of flavoprotein dehydrogenase enzyme family.

Ethylene glycol monomethyl ether (EGME) is a widely used industrial solvent known to cause adverse effects to human and other mammals. Organs with high metabolism and rapid cell division, such as testes, are especially sensitive to its actions. In order to gain mechanistic understanding of EGME-induced toxicity, an untargeted metabolomic analysis was performed in rats. Male rats were administrated with EGME at 30 and 100 mg/kg/day. At days 1, 4, and 14, serum, urine, liver, and testes were collected for analysis. Testicular injury was observed at day 14 of the 100 mg/kg/day group only. Nearly 1900 metabolites across the four matrices were profiled using liquid chromatography-mass spectrometry/mass spectrometry and gas chromatography-mass spectrometry. Statistical analysis indicated that the most significant metabolic perturbations initiated from the early time points by EGME were the inhibition of choline oxidation, branched-chain amino acid catabolism, and fatty acid ß-oxidation pathways, leading to the accumulation of sarcosine, dimethylglycine, and various carnitine- and glycine-conjugated metabolites. Pathway mapping of these altered metabolites revealed that all the disrupted steps were catalyzed by enzymes in the primary flavoprotein dehydrogenase family, suggesting that inhibition of flavoprotein dehydrogenase-catalyzed reactions may represent the mode of action for EGME-induced toxicity. Similar urinary and serum metabolite signatures are known to be the hallmarks of multiple acyl-coenzyme A dehydrogenase deficiency in humans, a genetic disorder because of defects in primary flavoprotein dehydrogenase reactions. We postulate that disruption of key biochemical pathways utilizing flavoprotein dehydrogenases in conjugation with downstream metabolic perturbations collectively result in the EGME-induced tissue damage.