In the present study published in Nutrients, researchers summarized published scientific literature describing the use of metabolomics to detect metabolites in gout patients, with particular attention to biomarkers that provide an early prediction of gout.
Study: Analysis of Metabolites in Gout: A Systematic Review and Meta-Analysis. Image Credit: jittawit21/Shutterstock.com
Background
In the past, metabolomics, a platform making robust use of spectroscopy and separation techniques, facilitated metabolite determination and the search for predictive biomarkers for many serious diseases, e.g., liver cancer and osteoarthritis. It identifies metabolites comprehensively and with exceptional accuracy.
Gout, a metabolic-immune disease caused by the super-saturation of uric acid (UA), gradually progresses to joint damage, deformity, and reduced productivity, leading to high healthcare costs.
Doctors treat acute gout with high doses of drugs, such as glucocorticoids and colchicine. However, there is increasing evidence that medication adherence to these therapies is poor worldwide. Thus, prevention of acute and chronic gout and its early diagnosis appears to be the most cost-effective path for reducing healthcare costs.
After concerted efforts over many years, scholars have found some specific metabolites with promising prospects for gout prediction, examples of which are hypoxanthine, xanthine, and creatinine. Yet, a consistent and comprehensive concluding approach in this research direction is lacking.
About the study
In the present study, researchers used three keywords and their synonyms, gout, metabolites, and metabolomics, to compile all relevant studies published up to July 2022 in databases, such as the Cochrane Library, PubMed, EMBASE, VIP Date, Web of Science, CNKI, and Wanfang Data.
They screened studies based on meeting these four criteria:
i) encompassed gout patients;
ii) used some metabolomic techniques to analyze patient and control samples;
iii) documented the profile of the identified metabolites; and
iv) were human subjects based cohort or case-control studies or randomized controlled trials (RCTs).
Next, two independent researchers used the Newcastle–Ottawa Scale (NOS) to assess the risk of bias in all studies included in this systematic review and meta-analysis. Finally, the team performed a qualitative analysis to change the direction of metabolites.
They used the standardized mean difference (SMD) of 46 metabolites and 95% confidence intervals of 95% (95% CI) for the meta-analysis across studies, where they considered heterogeneity as substantial only when above 60%.
Results
The current study highlighted and helped better understand the intricacies of metabolism and immune systems in humans, which developed hand-in-hand from an evolutionary and survival perspective in the long history of human existence.
As resisting starvation and mounting an immune response to pathogens was paramount, nutrients use the pathogen-sensing system(s) to trigger inflammatory responses. This suggests that functional units controlling these functions originated from the same ancestral structure during evolution.
In today's world, most humans do not have to face food scarcity. Thus, once beneficial, UA metabolism triggers the accumulation of fats and inflammation even without infection, a biological process driving renal impairment.
The current analysis found a characteristic metabolite profile for gout, in which 10 of 46 metabolites showed marked differences, and nearly all were related to metabolic inflammation.
The authors noted that DL-2-aminoadipic acid, an intermediate lysine metabolism metabolite, and creatinine levels varied between gout patients and healthy controls.
The former plays a key role in glucose and lipid metabolism; thus, its elevated concentrations promote fat consumption. However, that damages renal function in gout patients by enhancing their metabolism. These findings confirmed the hypothesis that metabolic and immune systems use the same or overlapping signaling systems in humans to maximize energy efficiency.
The authors also noted that hypoxanthine could cause inflammation in the kidneys. Likewise, adenosine, a purine metabolite, bound different purinergic receptors to regulate interleukin-1beta (IL-1β) secretion and played an anti-inflammatory role in gout development and remission.
Similarly, kynurenic acid (KYNA), a byproduct of the tryptophan metabolism, regulates immune system cells and several immune-mediated diseases. Recent research suggests chronic stress or mild inflammation could promote KYNA production and immunomodulatory actions.
Furthermore, the researchers investigated the meta-inflammatory basis of gout attacks. As is known, sodium urate crystals precipitate in joints during the vicious cycle of nutrient surplus and inflammation, eventually causing gout arthritis.
The precipitation of sodium urate crystals also promotes pro-inflammatory cytokine secretion, further hampering kidney function. Similarly, monosodium urate crystals precipitate in the other types of joints to trigger a pro-inflammatory immune response.
Finally, they confirmed the significance of metabolic inflammation in gout pathogenesis. The authors found that the signaling pathways used by metabolic and traditional inflammation were relatively consistent and originated from the energy metabolism pathways finding related biomarkers in the evolutionary journey, which could help detect or prevent gout attacks.
Conclusions
Overall, the current study results pointed to how changes in the levels of metabolites, such as UA, hypoxanthine, adenosine, creatinine, and DL-2-aminoadipic acid, form the basis of gout development.
As prospective studies with larger cohorts validate these findings, all or at least some of these specific metabolites could serve as predictive biomarkers of gout.
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