Introduction
Sarcoidosis is a chronic, multisystemic inflammatory disease characterized by clusters of immune cells known as granulomas. The lungs account for more than 90% of sarcoidosis involvement, with ~20–30% of cases developing pulmonary fibrosis. Other organs such as the lymph nodes, eyes, skin, kidneys, heart, liver, spleen, and nervous system can also be affected [1,2].
Various risk factors elevate the likelihood of developing sarcoidosis, including a genetic predisposition, with notably higher prevalence rates found in African American and Northern European populations. Additionally, the disease disproportionately affects women. Environmental factors such as exposure to dust, metals, other occupational hazards, and certain bacterial, fungal, and viral infections also increase risk.
Moreover, immune system dysfunction is more common among sarcoidosis patients experiencing disease progression [3–6]. Despite considerable progress in scientific research, the actual cause of sarcoidosis remains elusive. Akin to other granulomatous disorders such as tuberculosis, visceral leishmaniasis, and chronic beryllium disease triggered by known antigens, sarcoid granuloma formation stems from an exaggerated immune response to different infectious and noninfectious antigens [7–9].
Clinically, the clinical outcome of sarcoidosis is varied; granulomas can resolve spontaneously without treatment, exacerbate intermittently, or progress into chronic fibrotic forms, causing irreversible damage to affected organs [2,10,11]. Because of sarcoidosis rising mortality and morbidity [12], the capacity to prognosticate sarcoidosis progression is paramount. Applying ‘omics’ to sarcoidosis research has provided unique perspectives in understanding disease development, progression, and maintenance [13].
This review will provide a comprehensive knowledge of sarcoidosis and the state-of-the-art metabolomics implications in sarcoidosis pathogenesis and potential biomarker identification (Figure 1).
Immunopathogenesis of sarcoidosis
The histological hallmark of sarcoidosis is the formation of noncaseating granulomas caused by an immunological response to an unknown antigen, which activates membrane-bound pattern-recognition receptors such as toll-like receptors. Various immune cells contribute to the phenomenon, including T-helper 1 (Th1) cells, T-helper 17 (Th17) cells, T-helper 17.1 (Th17.1) cells, regulatory T (Treg) cells, monocytes, macrophages, B cells, dendritic cells (DCs), and natural killer (NK) cells [14,15]. Interleukin-17A (IL-17A) is known to be vital for the formation of mature granulomas.
Th17 cells are a proinflammatory subset of CD4+ T-helper cells known for producing interleukin 17 (IL-17). Recent studies have highlighted the crucial role of Th17 cells in sarcoidosis, confirming the presence of Th17 cells in the peripheral blood and bronchoalveolar lavage fluid of sarcoidosis patients experiencing progression [16–18]. Th17 cells can be polarized into Th17.1 cells, which produce IFN-γ [19].
Similarly, an increased percentage of Th17.1 cells has been observed in the sarcoidosis mediastinal lymph nodes [19,20].
Metabolomics in sarcoidosis
Metabolomics is an emerging field that characterizes small molecules called metabolites in various biological systems. These metabolites have diverse chemical properties and are typically analyzed using two main analytical chemistry techniques: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry, which can be coupled with either gas chromatography (GC) or liquid chromatography (LC), known as gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS). Metabolomics provides insights into complex biochemical pathways, disease pathogenesis, and outcomes.
Understanding the metabolites, the source of metabolite production, and their effects on human health has provided more profound insights into physiology, immune response, and disease development in the host [21–25].
It is clear that metabolism and the immunological state are inextricably linked. Intrinsic metabolic pathways of immune cells themselves and how those pathways influence cell fate and function (immunometabolism) is an innovative area of research [26]. Macrophage metabolism can influence production of inflammatory cytokines, as alternatively activated macrophages rely on a different metabolic program than classically activated macrophages; altered metabolomic signaling has since been shown in T cells [27], myeloid-derived suppressor cells [28], and DCs [29].
Metabolomic investigations of sarcoidosis pathogenesis are an emerging pathway to further understand sarcoidosis pathogenesis (Table1).
Geamanu et al. conducted a metabolomic investigation of sarcoidosis serum, analyzing circulating molecules in the serum of sarcoidosis patients using a 1H NMR-based untargeted metabolomic approach. Several metabolites were altered in sarcoidosis, with higher levels of 3-hydroxybutyrate (3-HB), acetoacetate, and carnitine, which are critical in the beta-oxidation pathway. In addition, cysteine, homocysteine, pyruvate, and trimethylamine N-oxide (TMAO) levels were higher in sarcoidosis, compared to healthy controls.
Glutamine, isoleucine, and succinate levels were significantly low. Moreover, the deamination and decarboxylation of isoleucine produce succinyl-CoA, which plays an essential role in the tricarboxylic acid cycle [30]. The impact of these findings on sarcoidosis pathogenesis was not relayed, but the findings relay important groundwork nonetheless.
Another interesting investigation was a case-control study conducted by Mirsaeidi et al. that identified two metabolites, p-coumaroylagmatine and palmitoylcarnitine, to discriminate fibrosing from nonfibrosing pulmonary sarcoidosis [31]. Palmitoylcarnitine is an acylcarnitine that serves as a fatty acid intermediate. It is produced due to abnormalities in beta-oxidation and tricarboxylic acid processes.
A study comparing prostate cancer tissues with benign tissues found that palmitoylcarnitine levels were significantly higher in cancerous tissues. This study also indicated an upregulation of the proinflammatory cytokine IL-6 due to high palmitoylcarnitine levels [32]. Proinflammatory signaling using IL-6 pathways has been implicated in sarcoidosis progression as well [33,34].
This metabolite has elevated expression in fibrosing sarcoidosis [31].
Duchemann et al. investigated the potential of identifying disease biomarkers through saliva analysis, which is a relevant noninvasive mechanism [35]. They studied the metabolomic profiles of saliva samples from 24 individuals with sarcoidosis and 45 healthy participants using proton NMR spectroscopy. Their findings revealed six metabolites that significantly differed between the two groups.
Specifically, patients with sarcoidosis had lower levels of methanol and butyrate, while their lactate, acetate, and N-butyrate concentrations were higher. This study suggests that saliva-based metabolomic analysis is distinct from sarcoidosis and healthy controls [35]. Additional investigations to delineate its role in understanding sarcoidosis clinical outcomes are warranted.
Interestingly, acetate and N-butyrate were found in greater quantities in sarcoidosis patients than in healthy controls. These short-chain fatty acids are produced by the gut microbiome in the gastrointestinal tract from dietary fiber, and they are recognized for their protective role in various human diseases [36–40].
Banoei et al. conducted a comprehensive analysis comparing the metabolomic and metallomic profiles of patients with pulmonary sarcoidosis, which included 13 veterans and 30 civilians [41]. Their study utilized HILIC-MS/MS and 1H NMR spectroscopy to analyze plasma samples. The results showed that veterans had higher levels of glutamate, pyruvate, O-phosphocholine, and lactate than civilians.
Conversely, the concentrations of glutamine and acetone were significantly lower in the veteran group. Additionally, plasma samples from veterans exhibited a decrease in anti-inflammatory amino acids, including arginine and methionine [41]. Higher pyruvate and lactate levels have previously been reported in sarcoidosis [30, 35].
In a separate study aimed at identifying sensitive and specific biomarkers for sarcoidosis, Banoei et al. utilized semi-untargeted LC-MS to analyze serum samples from 40 individuals diagnosed with sarcoidosis. These samples were compared to those from COVID-19 patients and healthy individuals. The analysis revealed that levels of azelaic acid, glutarate, and itaconate were significantly higher in the sarcoidosis group compared to the other cohorts [42].
Despite their elevated levels in sarcoidosis, azelaic acid and itaconate have been shown to possess anti-inflammatory properties [43,44].
Metabolomics as a potential diagnostic tool and therapeutic approach in sarcoidosis
As mentioned earlier, there is currently no highly sensitive and specific test that portends sarcoidosis clinical outcome. However, technological advancements and improvements in analytical techniques, such as mass spectrometry, have made metabolomics a particularly promising approach. This technique allows for the characterization of key metabolites that could potentially serve as biomarkers for the clinical outcome.
In addition to the previously mentioned metabolomic studies that identify various urine metabolites as potential biomarkers for sarcoidosis, Jeny et al. found that levels of 3-hydroxyisovalerate were higher in cases of severe sarcoidosis. They also observed reduced taurine, hippurate, serine, and creatinine levels. This study highlights the potential use of urine samples to identify biomarkers that indicate the severity of pulmonary sarcoidosis using 1H NMR spectroscopy [45].
Sarcoidosis presents unique immune and metabolic profiles that vary with clinical outcome. Specific metabolites, such as increased TMAO and taurine concentrations in the serum, are associated with progressive sarcoidosis. Disease progression is defined as forced vital capacity reductions of > 10%, appearance of sarcoidosis involvement outside of the lung, or necessity to escalate immunosuppression to treat symptoms.
Resolvers had increased serum glycerate, alanine, and proline concentrations. It is noteworthy that these patterns were present at the time of diagnosis and before initiation of therapeutics, supporting further investigation as a biomarker. These metabolic changes indicate a disruption in energy production and a compromise in tissue repair mechanisms [46].
Similarly, elevated uric acid, testosterone sulfate, allopregnanolone sulfate, and 24,25-dihydroxyvitamin D3 emerged as key metabolites with prognostic value in the self-healing group of Chinese sarcoidosis subjects [47].
To clarify the ambiguities associated with the metabolic profiling of biological fluids in the search for potential biomarkers, Rai et al. conducted a study that distinguished the metabolomic profiles of sarcoidosis from those of tuberculosis using NMR spectroscopy. They discovered that tuberculosis patients had higher levels of lactate, acetate, 3HB, glutamate, succinate, and reduced glucose levels. They also found elevated levels of citrate, pyruvate, glutamine, and various lipid and membrane metabolites in the sera of tuberculosis patients [48].
Geamanu and Duchemann identified 3HB, lactate, and acetate as potential biomarkers for sarcoidosis, noting that their levels are elevated in comparison to healthy controls [30,35]. However, Rai et al. demonstrated that these metabolites are more abundant in tuberculosis cases, which raises concerns about the reliability of studies profiling metabolites in biological fluids to identify sensitive and specific biomarkers. Elevated metabolite levels by themselves are unrevealing; they may reflect reduced or no metabolism of a particular metabolite.
More in-depth and longitudinal analysis of downstream signaling is necessary to understand the role that a particular metabolite has in sarcoidosis clinical outcome. In addition, assessment of the impact of immunosuppressants on metabolite expression is warranted, as well as inclusion of sarcoidosis subjects by clinical outcomes, which will aid in understanding sarcoidosis pathogenesis.
Comparison of metabolomic profiles of other granulomatous diseases: tuberculosis, histoplasmosis, and coccidioidomycosis
The etiology of sarcoidosis is unknown; however, the agents responsible for other granulomatous diseases, such as tuberculosis, histoplasmosis, and coccidioidomycosis, have been identified. Metabolomic profiling of various biofluids of granulomatous diseases of known etiology has been utilized to study disease progression and to identify biomarkers for diagnosis and prognosis in multiple conditions, including chronic granulomatous diseases [49–54].
Biomarker discovery studies that utilize metabolomic profiling of various biofluids remain challenging, primarily because each sample type requires a different processing method. This variation can result in the loss of specific volatile organic compounds and other small molecules, which may get filtered out with macromolecules before analysis. Sputum is commonly used in metabolomic studies of pulmonary tuberculosis; it also contains metabolites from the infectious agent, Mycobacterium tuberculosis, which could potentially interfere with the host capacity to clear infection [50].
Cho et al. conducted a metabolomic profiling study using LC-MS/MS on serum samples from 21 patients with active pulmonary tuberculosis, 20 individuals with latent tuberculosis infection (LTBI), and 28 healthy controls. The results indicated that active tuberculosis patients had increased levels of glutamate, sulfoxy methionine, and aspartate while showing lower serum levels of glutamine, methionine, and asparagine compared to both LTBI subjects and healthy controls [49].
Rai et al. found elevated levels of glutamate in the serum of individuals with sarcoidosis, suggesting a potential metabolomics overlap between sarcoidosis and tuberculosis. In contrast, the levels of glutamine were found to be higher in sarcoidosis patients [48]. Consequently, the glutamate/glutamine ratio may serve as a valuable biomarker to further understand the pathogenesis of granulomatous inflammation, such as tuberculosis and sarcoidosis, when conducting metabolic profiling of serum samples.
Metabolomics has recently emerged as a promising tool for profiling metabolites in search of potential biomarkers. However, the number of metabolic profiling studies conducted to date is still very limited, which presents a significant challenge. Furthermore, there is minimal overlap in the metabolomic profiles of various granulomatous diseases.
Specifically, there have only been a few metabolomic studies focused on coccidioidomycosis and histoplasmosis.
Jasbi et al. utilized LC-MS to identify nine metabolites in plasma and urine that may be potential biomarkers for coccidioidomycosis. They found three plasma metabolites: inosine, 3-phosphoglyceric acid, and cyclic GMP, as well as six urinary metabolites: phenylacetic acid, tryptamine, N,N-dicyclohexylurea, p-coumaric acid, gentisic acid, and tetracaine, along with fructose-1,6-bisphosphate and amino valerate [53]. These metabolites have been proposed as candidates for further investigation as biomarkers.
Nonetheless, a comprehensive investigation with a larger sample size is necessary to validate these proposed metabolites as specific biomarkers for coccidioidomycosis.
Heckart et al. investigated the metabolites produced by Histoplasma capsulatum, the infectious yeast responsible for causing histoplasmosis, in an in vitro culture. This fungus overcomes biological challenges within the phagosomes of macrophages, where it proliferates. The in vitro analysis of Histoplasma yeast metabolites revealed two compounds secreted by the fungus: mannitol and anthranilates [51].
The field is still early in profiling metabolites as potential biomarkers. Currently, there is minimal overlap of metabolites between these granulomatous diseases; therefore, future efforts should focus on characterizing the metabolic profiles of these diseases simultaneously and longitudinally to determine if biomarker profiles correlate with clinical outcome, as well as standardizing the detection methods to reduce the risk of false positive biomarkers.
Conclusion
The etiology of sarcoidosis remains unclear to date. However, advances in analytical methodologies have rendered ‘omics’ an attractive approach for further understanding sarcoidosis pathogenesis. Metabolomics offers a powerful method to unravel the complex biochemical alterations associated with sarcoidosis.
By providing a comprehensive snapshot of metabolic changes in affected tissues and biofluids, metabolomic profiling may potentially identify disease-specific biomarkers, elucidate pathogenic mechanisms, and distinguish active from quiescent disease states. Studies on metabolomic profiling in sarcoidosis have identified significant changes in metabolites involved in various biological processes. Alterations in the levels of these metabolites open a new avenue for discovering potential biomarkers for sarcoidosis prognosis, diagnosis, and treatment.
Furthermore, the analytical methods used in these studies have inherent limitations in detecting small molecules. The limited research focusing on the metabolites involved in sarcoidosis pathogenesis has utilized various analytical techniques on different samples, such as serum, urine, and saliva, complicating the interpretation of the role of key metabolites in sarcoidosis clinical outcome. Future research in metabolomic profiling related to sarcoidosis should aim to standardize methodologies on the same samples and increase cohort sizes to enhance generalizability.
The work conducted to date provides a strong foundation for future investigations.