Pharmacometabonomic Investigation of Dynamic Metabolic Phenotypes Associated with Variability in Response to Galactosamine Hepatotoxicity

Abstract

Galactosamine (galN) is widely used as an in vivo model of acute liver injury. We have applied an integrative approach, combining histopathology, clinical chemistry, cytokine analysis, and nuclear magnetic resonance (NMR) spectroscopic metabolic profiling of biofluids and tissues, to study variability in response to galactosamine following successive dosing. On re-challenge with galN, primary non-responders displayed galN-induced hepatotoxicity (induced response), whereas primary responders exhibited a less marked response (adaptive response). A systems-level metabonomic approach enabled simultaneous characterization of the xenobiotic and endogenous metabolic perturbations associated with the different response phenotypes. Elevated serum cytokines were identified and correlated with hepatic metabolic profiles to further investigate the inflammatory response to galN. The presence of urinary N-acetylglucosamine (glcNAc) correlated with toxicological outcome and reflected the dynamic shift from a resistant to a sensitive phenotype (induced response). In addition, the urinary level of glcNAc and hepatic level of UDP-N-acetylhexosamines reflected an adaptive response to galN. The unique observation of galN-pyrazines and altered gut microbial metabolites in fecal profiles of non-responders suggested that gut microfloral metabolism was associated with toxic outcome. Pharmacometabonomic modeling of predose urinary and fecal NMR spectroscopic profiles revealed a diverse panel of metabolites that classified the dynamic shift between a resistant and sensitive phenotype. This integrative pharmacometabonomic approach has been demonstrated for a model toxin; however, it is equally applicable to xenobiotic interventions that are associated with wide variation in efficacy or toxicity and, in particular, for prediction of susceptibility to toxicity.

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

“…An OPLS-DA model based on the pre-dose urine metabolite profiles was able to distinguish the profiles of nonresponders to dose 1 from induced responders to dose 2, with significantly discriminating metabolites including hexanoic acid and the N-acetyl resonances of some α1 acid glycoproteins. [86] A similar discrimination, was observed from an OPLS-DA model of fecal extract profiles, with decreased levels of γ -aminobutyrate (GABA), α-ketoisovalerate, and lactate in predose fecal profiles of induced responders.…”

“…It was hoped that this pre-clinical study, the first to identify multiple isoniazid urinary metabolites, would have the ability to translate its finding to the human clinical setting. [85] Coen et al [86] used an NMR-based approach to investigate variability in the response of rats to the toxicity of galactosamine, a drug whose variable responses in rats triggered the design of the original pharmacometabonomics experiment. [46] Male Sprague-Dawley rats were dosed intraperitoneally with 415 mg/kg galactosamine and classified as responders or non-responders based on clinical pathology.…”

The metabolomic window into hepatobiliary disease

“…Metabolomic profiles of numerous hepatotoxins in laboratory animals have been described, and include hydrazine [117], bromobenzene [118, 119], methapyrilene [120], methylenedianiline [121], D-galactosamine [121–123], clofibrate [121], allyl formate [124], the anti-HBV compound Bay41-4109 [125], paracetamol [126–133], isoniazid [134, 135], carbon tetrachloride [131, 136–138], α-naphthylisothiocyanate [137], perfluorododecanoic acid [139], valproate [140], Huang-yao-zi [141], dimethylnitrosamine [142], polychlorinated biphenyls [143, 144], 2,3,7,8-tetrachlorodibenzo- p -dioxin [143], methamphetamine [145], (+)-usnic acid [146], pentamethychromanol [147] and methotrexate [131]. Detailed analysis of these drug-induced liver injury (DILI) studies falls beyond the scope of this review.…”

CHAPTER 3. High‐Resolution NMR‐Based Metabolic Profiling in Drug Discovery and Development

“…96 In addition, this strategy proved effective in explaining the response phenotype in a repeat dosing study in rodent with the hepatotoxin, galactosamine. 97 The pre-dose urine and fecal metabolite profiles were able to classify whether resistant or sensitive phenotypes presented on challenge with galactosamine. Furthermore, the concept of longitudinal pharmacometabonomics has also recently been proposed, 98 presenting the opportunity for monitoring or stratifying of patients over a period of time such as during clinical trials or pre-and post-surgery.…”