Nicotinamide N-methyltransferase (NNMT): a novel therapeutic target for metabolic syndrome

Metabolic syndrome (MetS) constitutes a multifaceted array of metabolic disorders, manifesting as disturbances in the body’s handling of energy substrates, including proteins, fats, and carbohydrates. As per the latest diagnostic criteria, MetS necessitates the presence of any three out of the following five conditions: elevated fasting glucose or type 2 diabetes (T2D), hypertriglyceridemia, lowered high-density lipoprotein (HDL) cholesterol levels, central obesity, or hypertension ( Alberti et al., 2009 ). Furthermore, these conditions can also result in the prothrombotic state, proinflammatory state, nonalcoholic fatty liver disease, and reproductive disorders ( Cornier et al., 2008 ). It is evident that MetS embodies not a singular malady but rather a confluence of ailments typified by obesity, hypertension, diabetes, and hyperlipidemia ( Kane and Sinclair, 2018 ; Tilg et al., 2020 ). The etiology and pathogenesis of MetS remain incompletely elucidated. However, obesity and insulin resistance (IR) are presently acknowledged as significant causative factors in MetS. Nicotinamide N-methyltransferase (NNMT) is a cytoplasmic enzyme that catalyzes the methylation of nicotinamide (NAM) with the methyl donor S-adenosyl-methionine (SAM) to form methylnicotinamide (MNAM) and S-adenosyl-l-homocysteine (SAH) ( Alston and Abeles, 1988 ; Van Haren et al., 2016 ). NNMT predominantly localizes in adipose tissue and liver ( Aksoy et al., 1994 ). Previous investigations have highlighted elevated NNMT expression in the liver and white adipose tissue (WAT) of diabetic mice and obese, with evidence suggesting that downregulating NNMT expression can mitigate diet-induced IR and obesity ( Kraus et al., 2014 ; Pissios, 2017 ). Our prior research identified a positive correlation between body mass index (BMI) and urinary MNAM levels ( Li and Wang, 2011 ). Additionally, significant associations were observed between single nucleotide variants in the NNMT gene and energy metabolism, obesity, T2D, hyperlipidemia, and hypertension ( Zhu et al., 2016 ; Zhou et al., 2017 ; Li et al., 2018 ; Guan et al., 2021 ; Liu et al., 2021 ). Giuliante et al. ( Giuliante et al., 2015 ) reported pronounced elevation of NNMT protein expression, gene expression, and enzyme activity in the adipose tissue of rats afflicted with MetS. Collectively, These results suggest a central position of NNMT in the development of MetS. This review delineates potential mechanisms underlying the NNMT-MetS association and provides insights into the progress of NNMT research within the domain of MetS-related diseases.

Decreased NAD + levels are associated with obesity, with studies demonstrating reduced NAD + levels in obese individuals. Elevating NAD + levels can increase lipolysis and reduce body weight. Picard et al. ( Picard et al., 2004 ) observed that overweight and obese patients could activate Sirtuin 1 (SIRT1) and Peroxisome proliferator-activated receptors (PPAR) through NAD + supplementation, resulting in weakened adipogenesis. Barbagallo et al . ( Barbagallo et al., 2022 ) demonstrated that NAD + supplementation activates Sirtuin 2 (SIRT2), enhancing the reciprocal inhibition of forkhead box O1 (FOXO1) and PPAR-γ to inhibit adipocyte differentiation and induce fat loss. Uddin et al . ( Uddin et al., 2017 ) reported that NAD + supplementation upregulates mitochondrial function, enhancing metabolism and promoting weight loss. Yamaguchi et al . ( Yamaguchi et al., 2019 ) created the ANKO (adipocyte-specific nicotinamide phosphoribosyl transferase (Nampt) knockout) mice to elucidate the role of NAD + in the regulation of adaptive thermogenesis and lipolysis. NAMPT serves as the rate-limiting enzyme in NAD + biosynthesis. The study found that ANKO mice, which lack NAMPT in both brown adipose tissue (BAT) and WAT, showed disturbed gene programs involving thermogenesis and mitochondrial function in BAT, resulting in a dampened thermal response. Furthermore, the absence of NAMPT in WAT resulted in a significant reduction in adrenergic-induced lipolysis. These results underscore the critical role of adipose NAD + in modulating adaptive thermogenesis, lipolysis, and overall energy metabolism. Decreased NAD + levels have been associated with hyperglycemia. NAD + plays a pivotal role in regulating the insulin signaling pathway and enhancing mitochondrial function, thereby contributing to the regulation of blood glucose levels. However, a decline in NAD + levels can precipitate a NAD + /NADH redox imbalance, resulting in an accumulation of excess NADH. This surplus of electron donors in the mitochondrial electron transport chain can overwhelm and impair mitochondrial complex I ( Yan et al., 2016 ). Furthermore, excessive accumulation of NADH in conjunction with reduced NAD + availability can inhibit glyceraldehyde-3-phosphate dehydrogenase (GAPDH) activity in the glycolytic pathway, leading to glucose shunting to the glycolytic branch pathway ( Yan et al., 2016 ; Song et al., 2019 ). This diversion activates the polyol pathway while diminishing cytoplasmic NAD + levels ( Luo et al., 2015 ). The hexosamine pathway can be activated to enhance O-GlcNAc acylation, potentially leading to IR ( Chen Y. et al., 2019 ). Additionally, Protein kinase C (PKC) pathway activation can induce insulin receptor substrate 1 (IRS-1) phosphorylation, inhibiting insulin signaling through downstream effectors such as Akt, phosphoinositide 3-kinase (PI3K), and glucose transporter 4 (GLUT-4) ( Ritter et al., 2015 ; Kolczynska et al., 2020 ). Furthermore, the formation of advanced glycosylation end products can exacerbate IR, pancreatic β-cell dysfunction, and cellular apoptosis ( Nowotny et al., 2015 ). Decreased levels of NAD + have been implicated in hypertension. NAD + exhibits vasorelaxant effects and diminishes oxidative stress, potentially contributing to the regulation of blood pressure. It is imperative to note that while these effects suggest a potential benefit, further research is needed to clarify the relationship between NAD + and hypertension. Investigations conducted on rat thoracic aorta and porcine coronary arteries have demonstrated that elevated levels of NAD + induce concentration-dependent vasorelaxation in endothelial cells (ECs) across various arterial beds. This vasorelaxation is mediated through actions on purinergic receptors, specifically adenosine receptors ( Alefishat et al., 2015 ). Moreover, NAD + regulates the activity of NADPH oxidase, a significant ROS source in vascular cells, thereby playing a key role in the modulation of vascular tone ( Reid et al., 2018 ). Elevated oxidative stress fosters the proliferation and hypertrophy of vascular smooth muscle cells, as well as collagen deposition, culminating in vascular medial thickening and constriction. Enhanced oxidative stress may also impair endothelial function, leading to diminished endothelium-dependent vasorelaxation and heightened vascular contractility. These observations underscore the potential link between heightened oxidative stress and the pathogenesis of hypertension ( Grossman, 2008 ). Consequently, by mitigating oxidative stress and enhancing vascular function, NAD + holds promise as a therapeutic target for blood pressure regulation. Decreased levels of NAD + have been associated with dyslipidemia. While direct evidence of NAD + ’s impact on lipid levels is limited, several studies have indicated that supplementation with NAD + precursors can ameliorate lipid profiles. Meta-analyses have shown that supplementation with NAD + precursors, including N

Elevated Hcy levels exert inhibitory effects on the insulin signaling pathway, primarily by inducing IR through the cysteine-homocysteinylation of the pro-insulin receptor. Hcy interacts with cysteine-825 residues situated on the pro-insulin receptor within the endoplasmic reticulum (ER), thereby disrupting the formation of initial disulfide bonds. This cysteine-homocysteinylation event perturbs the pro-insulin receptor and furin protease interaction within the Golgi apparatus, consequently inhibiting the cleavage of the pro-insulin receptor. Elevated Hcy levels in mice result in diminished levels of mature insulin receptors across various tissues, culminating in IR and the onset of T2D ( Zhang et al., 2021 ). 1Increased Hcy levels promote oxidative stress. Elevated Hcy leads to an increase in the generation of mitochondrial ROS, resulting in oxidative damage at the cellular and molecular levels, and suppression of antioxidant enzyme systems ( Kaplan et al., 2020 ). Hcy triggers oxidative stress by multiple means, such as generating ROS directly through auto-oxidation with transition metals, activating oxidative pathways, and blocking antioxidant pathways ( Perna et al., 2003 ; Esse et al., 2019 ; Ostrakhovitch and Tabibzadeh, 2019 ). This leads to damage to tissue cells, including vascular ECs ( Incalza et al., 2018 ), adipocytes ( Furukawa et al., 2004 ), and pancreatic β-cells ( Gerber and Rutter, 2017 ). Ultimately, this results in the development of MetS. Elevated Hcy levels have been implicated in perturbing fat metabolism, presenting a potential link between Hcy and adipose tissue dysfunction, which further contributes to cardiovascular disease risk. Recent research indicates that Hcy disrupts the breakdown of fats in fat cells by activation of the AMP-activated protein kinase (AMPK) pathway ( Wang et al., 2011 ). Exposure to Hcy leads to a decrease in glycerol and free fatty acid (FFA) release in fully differentiating 3T3-L1 and primary adipose cells in a dose-dependent manner. Notably, the inhibitory effects of Hcy on lipolysis are mediated through AMPK activation in adipocytes, underscoring the significance of AMPK in mitigating the impacts of Hcy on fat metabolism ( Wang et al., 2011 ). Furthermore, elevated plasma Hcy levels have been associated with decreased levels of HDL-cholesterol and disturbances in plasma lipid profiles, potentially leading to fatty liver accumulation ( Obeid and Herrmann, 2009 ). Hypomethylation induced by HHcy appears to contribute to lipid deposition in tissues. Investigating mechanisms underlying dysregulated lipid metabolism, Visram et al . ( Visram et al., 2018 ) established a model of HHcy in yeast and showed that Hcy supplementation resulted in increased cellular levels of fatty acids and triacylglycerols. Furthermore, the model demonstrated increased resistance to cerulenin, a fatty acid synthase inhibitor, and lower levels of condensing enzymes linked to the synthesis of very long-chain fatty acids ( Visram et al., 2018 ). These findings underscore the intricate relationship between Hcy and lipid metabolism dysregulation, shedding light on potential mechanisms underlying adipose tissue dysfunction and its implications for cardiovascular health. Increased Hcy levels activate inflammatory response. HHcy activates the release of inflammatory factors, induces leukocyte chemotaxis and activation, and causes ER stress. This results in an increased inflammatory response, which damages tissue cells, such as vascular ECs and pancreatic β-cells, ultimately leading to Mets. High levels of Hcy can activate the expression and release of inflammatory factors, leading to vascular endothelial dysfunction ( Balint et al., 2020 ). Numerous in vitro studies have corroborated the ability of Hcy to induce the release of inflammatory cytokines from ECs, including interleukin-6, interleukin-8, and tumor necrosis factor-α ( Kamat et al., 2013 ; Han et al., 2015 ; Li et al., 2016 ). This inflammatory response within the vasculature may stem from the activation of Nuclear Factor-kappa β (NFkβ) ( Zhao et al., 2017 ). Animal models of HHcy corroborate these findings. For instance, in a murine model, Hofmann et al. ( Hofmann et al., 2001 ) reported that HHcy exacerbates vascular inflammation and accelerates atherosclerosis. Additionally, Wu et al . ( Wu et al., 2019 ) demonstrated in human umbilical vein ECs and arteries of HHcy mice that Hcy triggers the expression of ER oxidoreductin-1α (Ero1α), leading to ER stress and subsequent inflammation. Notably, Ero1α knockdown has been found to mitigate HHcy-induced ER oxidative stress and inflammation.

Diabetes is caused by a fundamental disturbance in the metabolism of glucose and is characterised by IGT, elevated fasting blood glucose, and inadequate insulin secretion or IR ( Tripathi and Srivastava, 2006 ; Goldberg and Mather, 2012 ). MetS is a multifaceted condition that is defined as IR, IGT, T2D, or impaired fasting glucose (IFG) along with the existence of two or more of the followings: hypertension, microalbuminuria, hyperlipidemia, and obesity ( Giuliante et al., 2015 ). It is evident that disorders of glucose metabolism in the form of diabetes and IR are the core elements of the MetS. Multiple trials have robustly shown a strong association of NNMT with IR and T2D ( Kraus et al., 2014 ; Kannt et al., 2015 ; Liu et al., 2015 ). Our previous study also identified a significant association between the NNMT genetic variant at rs1941404 and T2D in the Chinese Han population ( Li et al., 2018 ). Additionally, NNMT has been shown to play a causal role in the development of T2D through quantitative trait locus mapping in mice ( Yaguchi et al., 2005 ). Elevated levels of MNAM were detected in the urine ( Li et al., 2018 ) and serum ( Kannt et al., 2015 ) of individuals with T2D, suggesting an increase in NNMT activity during T2D development. Further direct evidence supporting this relationship is primarily derived from the reports outlined below. Kannt et al. ( Souto et al., 2005 ) demonstrated an upregulation of NNMT expression in the WAT of individuals with IR or T2D. Additionally, a noteworthy correlation was found among plasma levels of MNAM and both the degree of IR and the expression levels of NNMT in WAT. Kraus et al. ( Kraus et al., 2014 ) reported an increase in NNMT expression levels in the livers and WATs of T2D mice. They also found that knockdown of NNMT improved insulin sensitivity and glucose tolerance in the T2D mice. The role of NNMT in the development of T2D was further confirmed by Hong et al . ( Hong et al., 2015 ). Their study revealed that hepatocyte glucose output decreased by 50% with NNMT knockdown, while NNMT overexpression increased it by 1.4-fold. Meanwhile, they observed a significantly lower overnight fasted glucose level in the livers of C57BL6/J mice with NNMT knockdown ( Hong et al., 2015 ). The potential mechanisms underlying NNMT’s regulation of glucose metabolism are primarily derived from two key reports. Kraus et al. ( Kraus et al., 2014 ) demonstrated that reduced NNMT expression enhances glucose tolerance and improves insulin sensitivity in DIO mice. The role of NNMT in gluconeogenesis was further elucidated by Hong et al . ( Hong et al., 2015 ). Their results revealed that decreasing NNMT expression in primary hepatocytes led to a reduction in the expression of phosphoenolpyruvate carboxykinase 1 (Pck1) and glucose-6-phosphatase (G6pc), resulting in decreased glucose output. Conversely, increasing NNMT expression in primary hepatocytes resulted in elevated glucose output and increased expression of Pck1 and G6pc. Furthermore, Hong et al. ( Hong et al., 2015 ) observed that mice subjected to NNMT knockdown exhibited reduced fasting glucose levels and diminished conversion of pyruvate to glucose. Such observations indicate that NNMT plays a beneficial role in regulating gluconeogenesis in hepatocytes. As shown in Figure 3 , in elucidating the regulatory mechanism of NNMT on glucose metabolism, Hong et al. ( Hong et al., 2015 ) proposed that NNMT’s product, MNAM, mediates its regulatory impact, with Sirt1 playing a pivotal role in this process. Their findings revealed a significant reduction in glucose production and expression of both G6pc and Pck1 in hepatocytes with NNMT overexpression and concurrent Sirt1 inhibition, compared to hepatocytes with NNMT overexpression alone. Furthermore, the downregulation of G6pc and Pck1 expressed by NNMT knockdown was reversed by the upregulation of Sirt1. These observations underscore the essential role of Sirt1 in mediating NNMT’s regulatory effect on glucose metabolism. Additionally, a significant correlation between Sirt1 protein expression and NNMT expression was noted in hepatocytes. In vitro experiments demonstrated that NNMT overexpression significantly increased Sirt1 protein expression in primary hepatocytes, while NNMT knockdown led to a notable decrease in Sirt1 protein expression. Consistent with these findings, in vivo experiments revealed a significant reduction in Sirt1 protein expression in the livers of mice upon NNMT knockdown. Furthermore, MNAM, a product of NNMT, was found to playing a key part in this process. Similar to the effects of NNMT overexpression, hepatocytes treated with MNAM exhibited significant increases in glucose production and expression of Sirt1, G6pc, and Pck1. Notably, the alterations induced by MNAM treatment were abrogated upon Sirt1 knockdown. These results collectively indicate that Sirt1 is indispensable for NNMT-mediated regulation of glucose metabolism, and both NNMT and MNAM have t

Hypertension is another common complication of MetS. Although there are limited reports regarding the association between NNMT and hypertension, our research has identified a significant association between a SNP in the NNMT gene (rs1941404) and hypertension within the Chinese Han population ( Guan et al., 2021 ). While direct evidence linking NNMT activity to hypertension is currently lacking, numerous studies have established a strong association between NNMT activity and various metabolic disorders, including cardiovascular diseases ( Li et al., 2006 ; Williams et al., 2012 ). For instance, Liu et al. ( Liu et al., 2017 ) demonstrated a significant association between serum MNAM levels and coronary artery disease, as well as left ventricular systolic dysfunction in Chinese patients ( Liu M. et al., 2018 ). Additionally, Bubenek et al. ( Bubenek et al., 2012 ) reported a robust association between NNMT expression, serum MNAM levels, and the onset and progression of peripheral arterial occlusive disease. Notably, NNMT expression has been found to be positively correlated with LDL levels and negatively correlated with HDL levels, both of which are relevant factors in cardiovascular diseases ( Herfindal et al., 2020 ; Kornev et al., 2023 ; Rus et al., 2023 ). As shown in Figure 5 , left ventricular contractile dysfunction and arterial vascular disease are significant contributors to the development of hypertension, suggesting a potential pathway through which NNMT may influence hypertension. Moreover, elevated plasma Hcy levels have been significantly associated with hypertension ( Van Guldener et al., 2003 ), particularly with systolic blood pressure (SBP) ( Esteghamati et al., 2014 ). Junedi et al. ( Junedi et al., 2022 ) reported higher Hcy levels in hypertensive cases compared to controls. Moreover, increased plasma Hcy levels were associated with elevated SBP, diastolic blood pressure (DBP), and a higher prevalence of hypertension among middle-aged and elderly individuals of Chinese descen ( Hidru et al., 2019 ). Notably, patients with HHcy exhibit significantly higher blood pressure compared to those without HHcy, and serum Hcy levels have been positively correlated with blood pressure in Wistar rats ( Shi et al., 2019 ). Thus, influencing Hcy levels may represent another important pathway through which NNMT is implicated in the development of hypertension. FIGURE 5 Possible Mechanisms of NNMT associated with hypertension.

In addition to RNAi drugs, the development of small molecule inhibitors targeting NNMT represents a current research focus for the treatment of MetS-related diseases. As shown in Table 1 and Figure 6 , the small molecule inhibitors targeting NNMT can be categorized into SAM-competitive inhibitors, NAM-competitive inhibitors, Dual-substrate-competitive inhibitors and isomerization inhibitors. TABLE 1 Overview of the small molecule inhibitors targeting NNMT. NNMT inhibitor type Compound SAM-competitive inhibitors SAH ( Gao et al., 2021 ), sinefungin a ( Zweygarth et al., 1986 ) NAM-competitive inhibitors MNAM ( Kraus et al., 2014 ; Hong et al., 2015 ), 5-amino-1MQ (NNMTi) ( Neelakantan et al., 2017 ; Neelakantan et al., 2018 ; Neelakantan et al., 2019 ), JBSNF-000088 ( Kannt et al., 2018 ), JBSNF-000265 ( Ruf et al., 2018 ), JBSNF-000028 ( Ruf et al., 2022 ), RS004 ( Horning et al., 2016 ), 4-chloro-3-ethynylpyridine ( Sen et al., 2019 ) Dual-substrate-competitive inhibitors MvH45 ( Van Haren et al., 2017 ), AK-12 ( Ruf et al., 2022 ), MS2756 ( Babault et al., 2018 ), MS2734 ( Babault et al., 2018 ), GYZ-78 ( Gao et al., 2019 ), NS1 ( Kuzmi et al., 2021 ), LL320 ( Chen et al., 2019a ), Yuanhuadine a ( Bach et al., 2018 ), CC-410 ( Roberti et al., 2023 ) Allosteric inhibitors Macrocyclic peptides ( Van Haren et al., 2021 ) a A natural inhibitor. FIGURE 6 Chemical structures of small molecule inhibitors targeting NNMT. 4.2.1 SAM-competitive inhibitors SAM-competitive inhibitors compete with the substrate SAM for the binding site in NNMT. There are two main types of such inhibitors, SAH ( Gao et al., 2021 ) and sinefungin ( Zweygarth et al., 1986 ) ( Table 1 ; Figure 6 ), but they are non-selective and inhibit all methyltransferases ( Van Haren et al., 2016 ). However, SAH demonstrates activity solely in enzyme-based biochemical assays; its activity is diminished in cellular assays owing to its swift degradation to adenosine and Hcy by SAH hydrolase ( Gao et al., 2021 ). Sinefungin, a naturally occurring compound derived from Streptomyces , serves as a SAM-mimicking methyltransferase inhibitor. However, it exhibits low cell membrane permeability and demonstrates substantial toxicity in animal models, thereby constraining its potential application as a therapeutic agent ( Zweygarth et al., 1986 ).

Dual-substrate-competitive inhibitors compete with the both substrates (SAM and NAM) for the binding sites in NNMT, thereby increasing inhibitors’ activity and selectivity ( Gao et al., 2021 ). As shown in Table 1 and Figure 6 , such inhibitors mainly include MvH45 ( Van Haren et al., 2017 ), AK-12 ( Ruf et al., 2022 ), MS2756 ( Babault et al., 2018 ), MS2734 ( Babault et al., 2018 ), GYZ-78 ( Gao et al., 2019 ), NS1 ( Kuzmi et al., 2021 ), LL320 ( Chen D. et al., 2019 ), Yuanhuadine ( Bach et al., 2018 ), and CC-410 ( Roberti et al., 2023 ). This class of inhibitors has been recently developed, thus there is a scarcity of reported cellular or in vivo data concerning these compounds. However, it will be intriguing to investigate whether this class of inhibitors targeting NNMT exhibits improved efficacy in this context. One notable dual-substrate NNMT inhibitor is Yuanhuadine, which is isolated from the flower buds of the traditional Chinese medicine Daphne genkwa. Some studies have reported that Yuanhuadine demonstrates a favorable inhibitory effect on the growth of various tumor cell lines ( He, 2002 ; Zhang et al., 2006 ; Hong et al., 2011 ). Additionally, Roberti et al. ( Roberti et al., 2023 ) reported a novel dual-substrate NNMT inhibitor, CC-410 , which stably binds to and exhibits high specificity in inhibiting NNMT.

As delineated in the text, NNMT is a crucial factor in MetS and has become a promising target for preventing or treating MetS-related diseases. However, despite the encouraging evidence, gaps in our knowledge remain to be filled in order to fully understand the mechanisms connecting NNMT with MetS-related disorders and to develop clinical agents against NNMT. The roles of NNMT in adipose tissues and livers appear to exhibit some contrasting effects. NNMT emerges as a novel regulator of adipose tissue function and energy expenditure. While NNMT influences energy metabolism in both adipose tissue and liver, its expression suppresses NAD + levels specifically in adipose tissue. However, it is noteworthy that knockdown of NNMT does not seem to affect NAD + levels in the liver, indicating potential divergent regulatory mechanisms of NNMT in these tissues and suggesting the existence of redundant pathways in NAD + metabolism regulation ( Kraus et al., 2014 ). Nonetheless, additional research is necessary to clarify the exact mechanisms behind NNMT’s actions in adipose tissues and liver. Specifically, it is necessary to determine how NNMT promotes fat accumulation in adipose tissues while managing fat accumulation in livers caused by nutrient overload ( Trammell and Brenner, 2015 ). Further study also is needed to understand how NNMT inhibits the formation of NAD + in adipose tissues and why there are redundant regulatory pathways for the metabolism of NAD + in livers. This could provide insight into the functional differences of NNMT in different tissues. Is NAD + necessary for NNMT to regulate energy metabolism processes? The competition between NAD + salvage and the methylation of NAM suggests that NNMT may reduce the oxidation of fuel and increase the storage of fat by regulating the formation of NAD + ( Trammell and Brenner, 2015 ). However, experiments have not demonstrated direct effects of NNMT on the intracellular levels of NAM and NAD + . In murine models, NNMT knockdown did not induce the accumulation of NAM in livers and adipose tissues, nor did it cause significant alterations in the intracellular levels of NAD + in hepatocytes ( Kraus et al., 2014 ; Hong et al., 2015 ). Therefore, it is possible that NNMT may regulate energy metabolism through other mechanisms, and that NAD + is not necessary for this regulatory process. Effects of NNMT on anaerobic energy metabolism remain unknown. Numerous studies have reported that NNMT has an inhibitory effect on the aerobic metabolism of sugars and fats, and NNMT Knockdown can increase oxygen consumption, promote sugar consumption and reduce fat synthesis, but the effects of NNMT on anaerobic energy metabolism have not been reported. Our previous study ( Li et al., 2017 ) revealed higher expression levels of NNMT in the toe extensor muscle, typically reliant on anaerobic energy metabolism for power generation, compared to the soleus muscle, typically reliant on aerobic energy metabolism. Additionally, inhibition of NNMT using MNAM resulted in a decline in performance during anaerobic endurance exercise in rats ( Zhou et al., 2018 ). These results suggest that NNMT may also contribute to the regulation of anaerobic energy metabolism. Additional investigations are warranted to ascertain the suitability of NNMT as a therapeutic target for MetS. The development of RNAi drugs and small molecule inhibitors targeting NNMT is facing several challenges. For RNAi drugs, challenges include safety, efficacy, and delivery issues. To address these challenges, various delivery methods have been investigated, including viral vectors, non-viral vectors, and rational design strategies such as chemical modifications, cationic liposomes, polymers, nanocarriers, and biocoupled siRNAs, aimed at enhancing stability and intracellular delivery ( Liu F. et al., 2018 ). Several RNAi drugs, including aptamers like pegaptanib targeting protein targets, and micro interfering RNAs like givosiran and patisiran, as well as antisense oligonucleotides like golodirsen and inotersen that interfere directly with RNA targets, have received FDA approval for medical use ( Yu et al., 2020 ). Despite significant progress in clinical RNAi drug development, there remains considerable room for improvement in pharmacokinetics, pharmacodynamics, and strategies to mitigate toxicity ( Setten et al., 2019 ). Regarding small molecule inhibitors targeting NNMT, challenges include the identification of efficient and selective inhibitors with robust in vivo activity ( Barrows et al., 2022 ). Presently, NNMTi, a small molecule inhibitor of NNMT, has been widely employed to investigate the pharmacological effects of NNMT. However, the efficacy of small molecule inhibitors targeting NNMT remains uncertain due to their lack of selectivity and low metabolic stability ( Iyamu and Huang, 2021 ).

W-DS: Resources, Writing–original draft, Writing–review and editing. X-JZ: Formal Analysis, Resources, Writing–review and editing. J-JL: Formal Analysis, Resources, Writing–review and editing. Y-ZM: Formal Analysis, Resources, Writing–review and editing. W-SL: Formal Analysis, Resources, Writing–review and editing. J-HL: Data curation, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing–review and editing.

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