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Detangling the interrelations between MAFLD, insulin resistance, and key hormones

Abstract

Metabolic dysfunction–associated fatty liver disease (MAFLD) has increasingly become a significant and highly prevalent cause of chronic liver disease, displaying a wide array of risk factors and pathophysiologic mechanisms of which only a few have so far been clearly elucidated. A bidirectional interaction between hormonal discrepancies and metabolic-related disorders, including obesity, type 2 diabetes mellitus (T2DM), and polycystic ovarian syndrome (PCOS) has been described. Since the change in nomenclature from non-alcoholic fatty liver disease (NAFLD) to MAFLD is based on the clear impact of metabolic elements on the disease, the reciprocal interactions of hormones such as insulin, adipokines (leptin and adiponectin), and estrogens have strongly pointed to the intrinsic links that lead to the heterogeneous epidemiology, clinical presentations, and risk factors involved in MAFLD in different populations. The objective of this work is twofold. Firstly, there is a brief discussion regarding the change in nomenclature as well as epidemiology, risk factors, and pathophysiologic mechanisms other than hormonal effects, which include nutrition and the gut microbiome, as well as genetic and epigenetic influences. Secondly, we review the basis of the most important hormonal factors involved in the development and progression of MAFLD that act both independently and in an interrelated manner.

Introduction

Metabolic dysfunction–associated fatty liver disease (MAFLD) constitutes the most prevalent chronic liver disease in Western countries, with a pattern of increasing incidence projected to be, within only 15 years, 21% higher than that in 2018 [1, 2]. MAFLD, rather than being a single clinical entity, encompasses a disease continuum, starting from liver steatosis which can progress to steatohepatitis (previously referred to as NASH, non-alcoholic steatohepatitis), cirrhosis, and hepatocellular carcinoma depending on the initial MAFLD characteristics and presence of a wide range of predisposing factors [3]. The high prevalence of MAFLD as well as its increasing trends are intimately related to the parallel increase in obesity and type 2 diabetes mellitus (T2DM) worldwide, which, over the last few years, have been considered health epidemics [4,5,6].

Systemic metabolic derangements have been closely associated with the development and progression of MAFLD [7], with the participating role of factors such as genetic predisposition, microbiome characteristics, and hormonal factors.

The presence of MAFLD entails the development of several extrahepatic organ alterations, including chronic kidney disease, sleep apnea, colorectal cancer, and cardiovascular diseases, the latter constituting one of the main causes of mortality in patients with MAFLD [8]. The direct implication of this is that mortality in patients with MAFLD extends beyond liver complications, such as cirrhosis and hepatocellular carcinoma, and includes a multisystem impact on overall patient health which requires a multidisciplinary approach to management [1, 9,10,11].

The role of obesity, hyperinsulinemia, and T2DM, as well as the multiple hormonal background that both influences and is affected by the existence of the fatty liver spectrum, are notorious for their impact and intrinsic interrelations and will therefore be discussed. While the topics selected for analysis in this review are by no means exhaustive, they cover the broad themes of hormonal regulation of MAFLD, including the role of adipokines, estrogen, and insulin resistance (IR), identifying the latter as forming the cornerstone of liver disease. In addition, we briefly discuss the bidirectional interaction between the disease spectrum and the distinct predisposing factors, namely, dietary habits, the microbiome, and genetic and epigenetic modifications.

The assessment of liver fibrosis is essential to the evaluation of all patients with chronic liver disease in order to predict outcomes, stratify risk, and develop surveillance strategies, and evaluate response to treatment over time. Although liver biopsy remains the gold standard for assessing the stages of liver disease in cases of MAFLD, including histological assessment of fibrosis and steatohepatitis, novel methods are being developed to reduce the need for invasive procedures [12, 13]. The efficacy of liver biopsy is limited by the potential for sampling errors and suboptimal agreement among pathologists, in addition to being associated with procedural risks. Non-invasive fibrosis scores based on simple and inexpensive clinical and routine laboratory parameters, such as the NAFLD fibrosis score (NFS), the aspartate aminotransferase (AST) to platelet ratio index (APRI), and the fibrosis-4 index (FIB-4), are commonly used to identify or exclude significant or advanced fibrosis in patients with fatty liver disease. The overall accuracy of these scores has been found to be modest. Artificial intelligence (AI) is currently being integrated with conventional diagnostic methods in the hopes of performance improvement [14]. In a recent meta-analysis of 13 studies, it was shown that AI significantly improves the diagnosis of NAFLD, NASH, and liver fibrosis. In this regard, it is worthwhile mentioning the work of Katsiki et al. [13], who utilized an AI-assisted ultrasonography technique for the diagnosis of MAFLD, revealing its sensitivity to be approximately 0.97 and specificity 0.98 [15].

Transition from NAFLD to MAFLD: the revolutionizing concept

The term non-alcoholic fatty liver disease (NAFLD) was first introduced by Klatskin in 1979, while Ludwig and colleagues coined the term “non-alcoholic steatohepatitis (NASH)” in 1980 to describe fatty liver disease arising in patients with minimal or no alcohol consumption (“consumption” is defined as ≥ 30 g for men and ≥ 20 g for women) [16]. Thereafter, 40 years of research led to the advancement of our understanding of the pathophysiologic mechanisms and histologic characterization of the disease. Metabolic factors have been demonstrated as having a pivotal role in the development of fatty liver disease, not only by enhancing the onset and increasing the rate of progression to the various range of fatty liver disorders, but also by being the primary direct cause of steatosis.

In 2020, a panel of experts from 22 countries proposed a comprehensive and simple redefinition process of fatty liver disease shaped by this growing frame of knowledge. This included introducing MAFLD as a substitute for NAFLD nomenclature and laying down a set of positive criteria for diagnosis instead of criteria based on the exclusion of differential diagnoses (as NAFLD had previously been established). The criteria for MAFLD diagnosis are based on evidence of hepatic steatosis in addition to one of the following three criteria: overweight or obesity, presence of T2DM, or metabolic dysregulation [17]; similar criteria were introduced for diagnosis of MAFLD in children as well [18].

However, since the term was proposed, multiple arguments both in favor and against the new nomenclature quickly appeared, not without reason. It has been contended that a premature change in nomenclature may be counterproductive, as targeting the main risk factors still does not clarify the exact etiology of the disease given its multifactorial origin [19, 20]. However, even though some authors still believe this, a global multi-stakeholder written by experts from 135 countries joined up to lay out the reasons for which a change in nomenclature is appropriate and necessary.

Even though the change in nomenclature means that including everything that has been established in NAFLD into the term MAFLD is unwarranted, the heterogeneity of the disease makes MAFLD a term that better adjusts to the current needs for prompt diagnosis and better treatment of a greater proportion of the population who require it. Considering the central role of metabolic dysregulation in fatty liver disease development (which is taken into account in the criteria for diagnosis for MAFLD, Fig. 1), this redefinition can only lead to a better understanding of the disease as well as of the multiple features that are yet to be explained, both regarding risk factors and pathogenesis. The new definition has been accepted by numerous societies, including the Latin American Association for the Study of the Liver (ALEH) and the Asian Pacific Association for the Study of the Liver (APASL]. It has moreover recently been endorsed by a global multiple stakeholder [17, 18, 21, 22]. Notably, a robust body of evidence has confirmed the superior utility of the definition of MAFLD compared to the previous definition of NAFLD in identifying patients at high risk of fibrosis and extrahepatic complications [23,24,25].

Fig. 1
figure 1

Differences in diagnostic criteria between NAFLD and MAFLD: while the definition of NAFLD among certain groups was based on the diagnosis of absence of other causes of steatosis, MAFLD diagnosis is based on the presence of hepatic steatosis (evidenced via imaging, biochemical markers, or biopsy) plus the presence of metabolic alterations. NAFLD: non-alcoholic fatty liver disease; MAFLD: metabolic dysfunction–associated fatty liver disease; EASL: European Association for the Study of the Liver; AASLD: American Association for the Study of Liver Diseases; T2DM: type 2 diabetes mellitus

Epidemiology and risk factors

MAFLD constitutes one of the most prevalent liver diseases worldwide, just behind viral hepatitis and alcoholic liver disease (ALD) [26]. Global prevalence of MAFLD was estimated to be 25.24% in a study conducted using data from 1989 to 2015 [27]. When analyzing the tendency of increasing prevalence of fatty liver over the years, it is evident that the strong association with numerous other entities, especially obesity in more than 50% of cases, T2DM in 20%, hyperlipidemia in 70%, and hypertension and metabolic syndrome (both in 40%), determines the increased prevalence of this liver disease [27]. In broad terms, the risk factors encompass the determinants of metabolic health, such as diet and physical activity, ethnicity, age and gender, socioeconomic factors, microbiota, and alcohol consumption [28,29,30,31].

Pathogenesis

Initially, MAFLD pathogenesis was conceptualized within the popular “two-hit pathogenesis,” which could be explained in brief terms as there being an initial hit that leads to hepatic lipid accumulation due to multifactorial environmental reasons (including lifestyle, high-fat diets, obesity, and IR) and a subsequent second hit, which presents with inflammation and development of fibrosis [32].

However, with our evolving understanding of the basis of the disease, the multifactorial pathogenesis of MAFLD, referred to as the “multiple-hit pathogenesis,” was put forward by Buzzeti in 2016 [33]. These causative factors include genetic and epigenetic factors (with constantly increasing studies showing their higher than expected impact), nutritional factors, gut microbiota, metabolic health, and, finally, hormonal influence, and particularly the role of IR [34, 35]. Although each of these elements warrants an extensive discussion, the present review will be focused mainly on the hormonal factors that lead to the development and progression of MAFLD.

Genetic predisposition and epigenetic modifications

Genetic influence

The importance of genetic factors in the multiple-hit pathogenesis of MAFLD is key to our understanding. Based on the genome-wide association study carried out in 2011 [36], numerous allele variations for more than one gene were found in association with MAFLD development and disease progression. The most significant associated gene is undoubtedly PNPLA3, which encodes for adiponutrin, a protein that exerts lipolytic activity on triacylglycerides (TAGs), given its resemblance to adipose triglyceride lipase [37]. Even though normal PNPLA3 allele decreases de novo lipogenesis (DNL), increased expression of the I148M (rs738409 C/G) PNPLA3 variant was found to increase fatty acid and TAG synthesis as well as leading to impaired TAG hydrolysis, effectively increasing its hepatic levels [38]. Apart from driving lipid accumulation, this mutation drives the progression to steatohepatitis and fibrosis through a yet-to-be-elucidated mechanism. Furthermore, the PNPLA3 I148M allele has different degrees of impact on disease development as it has been found to act by sensitizing the liver to environmental stressors, which, according to recent research, may even include aspects such as air pollution [37, 39]. Based on this premise, the existence of concomitant risk factors underlying predisposing genetic mutations is what leads to MAFLD development, as is seen in the vast majority of multifactorial diseases. To a lesser degree, PNPLA3 contributes to the development of other liver diseases, including HCC, ALD, and viral hepatitis [40], which must be taken into account to more correctly predict disease outcomes. Numerous other genes have been associated with development of MAFLD and have a pivotal role in its development and progression, such as LYPLAL1 and GCKR, the latter by enhancing an increase in hepatic triacylglycerol levels and IR, respectively [41]. The rs641738 C > T variant of MBOAT7, the rs58542926 C > T allele of TM6SF2, and a large number of other genes are also involved [42,43,44,45,46]. A role for variants in the interferon lambda 3/4 (IFNλ3/4), fibronectin type III domain–containing protein 5 (FNDC5), and fibroblast growth factor 21 (FGF-21) has also been described [47,48,49,50,51]. In addition, an emerging role for other types of genetic variations such as copy number variations (CNV) has been observed [52].

Finally, researchers have noted a twofold increased risk of developing both HCC and liver cirrhosis in a cohort of hospitalized patients with T2DM [53], while several studies have shown a clear association between metabolic syndrome and HCC [54, 55].

Epigenetic reprogramming

Epigenetic modifications are changes that occur within the DNA which alter the expression of specific genes without modifying the DNA sequence [56]. Epigenetics has taken on a crucial role in describing most multifactorial diseases given the wide-ranging implications that epigenetic modifications may have in risk burden, onset, and development of disease, as well as in pathophysiology and therapeutic targets. Even though epigenetics has mostly been studied in different kinds of cancer (mainly colorectal and breast cancers) [57, 58], research into the role they play in MAFLD development has also grown rapidly.

Epigenetic modifications can be induced by diverse elements, including dietary factors, drugs, or environmental exposures. Broadly speaking, epigenetic changes can occur at any of the following three levels: direct DNA modification through methylation of CpG dinucleotides; histone modifications (acetylation or deacetylation and/or methylation or demethylation); and non-coding RNAs [59, 60].

Flexibility in gene expression in MAFLD has been attributed mainly to DNA methylation changes [59], which occur in various situations, including modulation by fructose intake in the transcriptomic mechanisms [61] as well as choline-deficiency related MAFLD [62, 63]. Moreover, development of MAFLD and steatohepatitis has been shown to be influenced by GAB2 methylation through diet and exercise [64] and METTL3 upregulation through obesity and metabolic stress [65], while differential DNA methylation patterns occur at different fibrosis stages [66]. Epigenetic marks show the phenomenon of heritability, meaning that modifications can be passed from a cell to its subsequent divisions, as well as through a non-Mendelian pattern from parents to offspring in what is known as transgenerational inheritance, which is still under study in relation to MAFLD [67, 68].

Besides DNA methylation, epigenetic mechanisms involved in MAFLD and ALD can also take place through histone acetylation and miRNAs. Histone proteins are involved in the maintenance of chromatin structure and gene expression, while acetylation causes activation of gene transcription and deacetylation causes gene repression. Aberrant histone modifications promote the development of IR and DM2 [69].

The effect of circRNAs on MAFLD pathogenesis stems from the fact that IR and abnormal lipid metabolism are the hallmarks of the disease. By inducing mitochondrial dysfunction with a generation of reactive oxygen species (ROS) and endoplasmic reticulum (ER) stress, as well as modulating lipophagy in steatotic livers, circRNAs play a role in the development of the conditions that predispose to MAFLD. A few examples of circRNAs involved in MAFLD pathogenesis include the following: circScd1, which increases hepatocellular lipidosis via the JAK2/STAT5 pathway; circRNA_002581, which promotes steatohepatitis development through dysregulation of autophagy; and circRNA_0049392, by regulating low-density lipoprotein (LDL) levels in serum [70].

Similarly, the beneficial role of SIRT1, which in fact has led to new therapeutic targets, cannot be overlooked. Sirtuins are members of the silent information regulator 2 (Sir2) family, a group of class III highly conserved NAD + -dependent histone and protein deacetylases playing a pivotal role in numerous biological processes. There are seven different sirtuins in mammals (SIRT1-7), of which SIRT1 is the most recognized regulator involved in MAFLD, with both nuclear and cytoplasmic locations [71, 72]. SIRT1 is a key metabolic regulator which maintains homeostasis by regulating the transcriptional activity of multiple factors. The two principal contributions of SIRT1 in fatty liver disease are lipid metabolism and insulin secretion, along with concomitant regulation of oxidative stress and liver inflammation. Regarding lipid metabolism, SIRT1 causes downregulation of SREBP-1c’s transcriptional activity by deacetylating lysine in its DNA-binding domain [73], as well as inducing histone deacetylation in the ChREBP gene [74]. It thereby suppresses downstream lipogenic enzyme gene expression, consisting of enzymes such as fatty acid synthase (FAS), acetyl-CoA carboxylase 1 (ACC1), stearoyl-CoA desaturase-1 (SCD1), and elongase of the long-chain fatty acid family 6 (ELOVL6), which participate in the synthesis of free fatty acid (FFA) and TAG in the liver [72]. Furthermore, by increasing PPARα-dependent fatty acid β-oxidation (by deacetylating PGC-1α), SIRT1 increases hepatic lipid utilization, alleviating fatty liver. It has been shown that SIRT1 activation increases lipolysis by repressing PPARγ in adipose tissue, thereby inhibiting adipogenesis. Moreover, by regulating PPARγ and FOXO1, this sirtuin also modulates the secretion of insulin-sensitizing factors, such as adiponectin and FGF21 [75].

Due to its insulin regulating mechanism, which is known to constitute the basis for MAFLD genesis, SIRT1 improves the insulin sensitivity of liver, skeletal muscle, and adipose tissue, increases insulin secretion [through inhibition of uncoupling protein-2 (UCP-2)] [76], and conserves pancreatic β-cell mass [77].

Given these central functions in the pathogenesis of fatty liver disease, SIRT1 has been the target of a number of therapeutic drugs, including resveratrol, SRT1720, and NAD + precursors (nicotinamide riboside, nicotinic acid, and nicotinamide mononucleotide) which activate SIRT1, enhancing its functions and reducing overall oxidative stress [72].

Finally, a serum microRNA (miRNA) profile revealed the potential relationship between different miRNAs and the presence of steatosis or steatohepatitis in 16 patients. It was reported that miR-374a-5p, miR-1-3p, and miR-23a-3p do not target genes that are directly involved in the pathogenesis of MAFLD [78]. On the other hand, the specific roles of some miRNAs are still unknown. An example of this is miR-192-5p, which was originally found to have a beneficial role in MAFLD development. This observation is based on miR-192-5p downregulation seen in high-fat diet-induced MAFLD in mice, as well as the inhibitory lipid synthesis function found when upregulated (by SCD1 targeting) [79]. However, it was later determined that lipotoxic hepatocytes secreting miR-192-5p contribute to M1 macrophage activation, inflammatory response, and development of hepatic steatosis in MAFLD [80, 81]. One final example is miR-423-5p, which is upregulated in individuals with metabolic healthy obesity (MHO) compared to metabolic abnormal obesity (MAO), and appears to be associated with downregulation of proinflammatory markers that are linked to IR [82]. It has been considered a therapeutic target, given that its inhibition of the L/R-type pyruvate kinase (PKLR) could lead to a decrease in de novo lipogenesis (DNL) and oxidative phosphorylation in mitochondria, having a positive effect in the early stages of MAFLD. However, this particular miRNA was also found to inhibit the AMPK complex, thus contributing to progression to steatohepatitis as well as suppressing tumor necrosis factor (TNF) and Fas cell surface death receptor (FAS), possibly contributing to fibrosis and establishment of HCC [78].

Nutritional factors and gut microbiota

Microbiome and MAFLD

Human gut microbiota plays a pivotal role in the development of MAFLD through what is known as the gut-liver (or liver-microbiome) axis [83, 84]. Undoubtedly, the microbiome constitutes an important regulator of health and disease states in living organisms, dubbed the “second genome” [85]. One of the first studies demonstrating the influence of the microbiome on MAFLD was carried out in 2003 through the use of VSL#3 probiotics (as well as anti-TNF antibodies), which showed improvement in histological features of MAFLD in ob/ob mice [86]. Since then, multiple studies have shown the interplay between these two factors, starting from identification of what is referred to as the obesity-associated gut microbiome, a transmissible “enterotype” capable of increasing total body fat [87].

The gut-liver axis refers to the bidirectional relationship between the liver and the gut microbiome. This feedback loop is established by both the transport of gut-derived products to the liver as well as the secretion of bile and hepatic antibodies into the intestine [88]. Bile acids (BAs) are not only important for the absorption of lipid-soluble nutrients in the intestine but also crucial messengers that impact the gut microbiome and metabolic homeostasis. As important signaling molecules are involved in lipid and glucose metabolism, dysregulation of BA homeostasis has been associated with MAFLD disease severity [89]. However, the data published in the literature on the relationship between IR and the influence of bile acid on the disease are inconsistent. A 2021 study found that steatosis-associated increase of total cholic acid in plasma depends on the degree of systemic IR (assessed by HOMA2) [90], while another study found that MAFLD is associated with significant changes in bile acid composition, hypothesized to be unaffected by T2DM, and correlated with the histological features of steatohepatitis [91].

An important breakthrough occurred when obesity and the gut microbiome were discovered to be independent risk factors for the development of MAFLD through a study in which germ-free mice were colonized with different microbiota from two different C57BL/6 J mice that responded differently to high-fat diets (HFD): it was found that the mice that received the microbiome from MAFLD mice developed both hyperinsulinemia and macrovesicular steatosis (along with increased expression of genes involved in DNL), independent of the presence of obesity [92]. Following on this, Alferink et al. [93] carried out the largest scale population-based study (consisting of 1355 adults) which shed light on the association between specific gut microbiome characteristics and MAFLD: it determined that low-diversity microbiomes and the presence of Coprococcus and Ruminococcus gnavus were associated with liver steatosis [93]. Dysbiosis may lead to a cascade of mechanisms that modify the epithelial properties and facilitate bacterial translocation in diseases such as T2DM, obesity, and MAFLD [94]. Furthermore, endogenous alcohol production by steatosis-associated intestinal microbiota, its increased serum levels, and, consequently, its well-established role in inflammation induced by oxidative stress laid the basis for understanding the histological similarities between ALD and MAFLD [95, 96]. Recently, a role for microbiota in the pathogenesis of MAFLD in lean subjects has been described [97].

There is an important link not only between epigenetic modifiers and MAFLD, but also between epiphenomena and the other factors contributing to MAFLD development. Microbiome alteration through environmental and dietary factors is not the exception.

Dietary changes can induce gut microbiome change, this being confirmed through the finding that consumption of > 7.5 g/day of insoluble fiber improved liver fibrosis according to three different fibrosis evaluating scores [98].

There is a pivotal association in MAFLD development involving the microbiome and estrogen production. Basically, increased endogenous estrogen circulation occurs for the two following reasons: firstly, deconjugation of conjugated estrogen metabolites marked for excretion, which pushes them back through the enterohepatic circulation; and, secondly, the breakdown of otherwise indigestible dietary polyphenols to synthesize estrogen-mimicking compounds [85]. The relationship between estrogens and MAFLD will be discussed in the following sections.

Nutritional influence

A wide range of dietary factors also plays an important role in the development of MAFLD either by altering hepatic metabolism directly or by promoting dysbiosis [54, 58]. Excessive calorie intake is a major risk factor for MAFLD as well as for the entities directly related to fatty liver development (e.g., obesity and T2DM). While high-fat diets induce endotoxemia and low-grade systemic inflammation, trans-fat consumption stimulates cholesterogenesis, establishing a risk factor not only for MAFLD but also for the development of steatohepatitis [99,100,101]. Fructose, on the other hand, has been extensively studied for its role in MAFLD development by stimulating DNL and gluconeogenesis, which in turn stimulate ChREBP and SREBP1c, along with the induction of IR and mitochondrial oxidative stress [102, 103].

Mitochondrial dysfunction and oxidative stress

Alterations in mitochondrial structure and function, which constitute a determinant factor in MAFLD pathogenesis, include mitochondrial DNA depletion, morphological abnormalities, and changes in the respiratory chain, as well as β-oxidation [33]. There is strong evidence showing that respiratory chain deficiency in mitochondrial dysfunction plays a key role in steatohepatitis and also that alterations in mitochondrial β-oxidation of FFAs generate ROS. Oxidative stress acts on a fat-rich environment by inducing lipid peroxidation, which releases highly reactive substances (aldehyde derivatives) leading to deleterious effects on hepatocytes [129]. The above-described actions lead to mitochondrial dysfunction, which consequently drives the production of even more ROS, leading to a vicious cycle which eventually results in inflammation and apoptosis. Additionally, cytokine generation (specifically of TNF-α, TGF-β, and FAS ligand) by ROS and the products of lipid peroxidation play a key role in the development of steatohepatitis and fibrosis [129].

Finally, it is essential to understand how adipokines might also induce oxidative stress. Leptin is arguably the main adipokine mediator in the MAFLD pathogenic spectrum, as discussed in greater detail in the following sections. This segment, however, deals with the significant contribution of leptin to the oxidative stress–mediated damage in MAFLD. Leptin interacts with a variety of cells in the liver, including macrophages. Research has revealed that leptin acts on these cells in steatotic livers, prompting peroxynitrite-mediated oxidative stress, which is comprised of three main actions, namely, leptin-mediated protein radical formation, tyrosine nitration, and activation of Kupffer cells [130]. Thus, by promoting further oxidative stress, leptin probably plays an important role in the development of steatohepatitis.

Hormonal factors and IR

Glucose transport and hyperinsulinemia

Hyperinsulinemia is closely related to a wide range of components of metabolic dysfunction. Once thought to be a consequence of metabolic dysfunction (as in the case of obesity), recent evidence has indicated that hyperinsulinemia might well be the cause of metabolic abnormalities due to its role in inflammatory and multisystem pathways [104,105,106,107] (Fig. 2).

Fig. 2
figure 2

Hepatic fat metabolism’s direct relationship with IR and MAFLD: FFAs from the diet or as a product of lipolysis are stored in the liver as triglycerides, which constitute the main storage form of fat in this organ. Increased hepatic TAG levels contribute to the development of IR, which directly contributes to MAFLD development through the downregulation of IRS-2 and inhibition of β- oxidation of FFAs, which in turn inhibit lipolysis and stimulate PI3K, all of these leading to the overexpression of SREBP-1c and thus increase DNL and consequently hepatic steatosis. On the other hand, insulin directly increases nuclear translocation of PI3K, which modulates the cellular response to ER stress, leading to UPR (unfolded protein response) and therefore the activation of JNK, an activator of apoptosis and inflammation, resulting in steatosis and steatohepatitis. Additionally, JNK activation leads to impaired insulin signaling. FFAs: free fatty acids; CoA: coenzymeA; TAG: triacyglycerol; MAFLD: metabolic dysfunction–associated fatty liver disease; DGAT2: diacylglycerol O-acyltransferase 2; IRS-2: insulin receptor substrate 2; PI3K: phosphatidylinositol-3 kinase; SREBP-1c: sterol response element–binding protein 1c; DNL: de novo lipogenesis; XBP-1: X-box-binding protein 1; ER: eEndoplasmic reticulum; UPR: unfolded protein response; JNK: c-Jun kinase

IR is the result of multiple abnormalities that start at a cellular level, involving abnormalities in intracellular signaling pathways and, in the case of peripheral IR, alterations in glucose transporters [108]. Glucose transporter-4 (GLUT-4) is the main protein implicated in glucose transport in cells for its catabolism. Multiple parameters in the body are closely regulated for optimal homeostasis, these including such variables as pH, electrolyte concentrations, and glucose. Serum glucose levels are tightly regulated through multiple mechanisms, including peripheral and central nervous system control and hormonal influence involving glucagon, insulin, amylin, and GLP-1 (glucagon-like peptide-1) [109]. Serum glucose levels must be maintained within a specific range to prevent altered states of consciousness due to hypoglycemia or peripheral toxicity owing to chronic hyperglycemic states. After carbohydrate ingestion, the major cellular mechanism that diminishes blood glucose levels is insulin-stimulated glucose transport into skeletal muscle, which can both store it as glycogen and oxidize it for the subsequent metabolic steps, as described below. The principal glucose transporter protein that mediates skeletal muscle uptake is GLUT4, which plays a key role in body glucose homeostasis [110]. However, several GLUT subtypes play important roles in carbohydrate transport in different organs, leading to a certain degree of specificity.

GLUT-4 in the liver is principally expressed in hepatocytes and in endothelial and hepatic stellate cells (HSC) [111]. Expression in HSC is promoted by leptin signaling, leading to its activation and consequent contribution to fibrogenesis in MAFLD. It has been reported that GLP-1R agonists increase lipolysis, reduce lipogenesis, and improve hepatic fibrosis. Exendin-4 (a GLP agonist) was shown to improve hepatic steatosis by enhancing GLUT-4 via GLP-1R, as well as improving fibrosis by inhibiting connective tissue growth factor expression in HSC, thus exerting a protective effect on the liver in patients with T2DM and obesity [112].

Persistent hyperglycemia leads to a condition known as glucotoxicity, characterized by decreased insulin secretion from pancreatic β-cells and an increase in IR [113]. This well-known condition, which induces IR, affects both hepatic and adipose tissue metabolism, playing a crucial role in MAFLD pathogenesis. The key event is the suppression of hormone-sensitive lipase in adipocytes by IR, which increases lipolysis and thus FFA flow from adipose tissue to the liver. Persistently elevated glucose and hyperinsulinemia stimulate hepatic DNL by upregulating hepatic lipogenic transcription factors such as SREBP-1c and ChREBP, which enhance the activities of glucokinase, fatty acid synthase, and acetyl-CoA carboxylase [114]. Thus, while IR promotes FFA accumulation in the liver, the latter causes hepatic IR characterized by a lack of suppression of endogenous glucose production in the liver [115].

Lipid metabolism and IR

MAFLD is clinically characterized by the existence of visible fat-containing lipid droplets in 5% of hepatocytes, the latter determined when thin sections are assessed by light microscopy or by detection of excess of a percentage threshold of 5.56% when evaluated through proton magnetic resonance spectroscopy [116]. Hepatic steatosis is associated with IR in the liver, adipose tissue, and skeletal muscle, independent of the level of adiposity [117]. Moreover, exceeding a specific threshold for hepatic fat accumulation (1.5% for liver IR and 6% for muscle IR) is counterintuitively not associated with increased IR. Having said this, hepatic DNL was found to be inversely correlated with hepatic and peripheral insulin sensitivity, but directly correlated with plasma glucose and insulin concentrations. Along with weight loss, there are also decreased plasma glucose levels, insulin concentrations, and intrahepatic TAG content [118].

Triglycerides are the storage form of fat in the MAFLD liver, produced by the esterification of glycerol with three FFAs [119]. FFAs can originate from diet (exogenously) or endogenously through lipolysis in adipose tissue or from DNL in the liver. A series of steps then follows that leads directly to the development of IR (see Fig. 2) [33, 119]. Even though TAG accumulation is not hepatotoxic per se and can even act as a defensive mechanism to balance FFA excess, inhibition of DGAT2 expression results in a reduction of intrahepatic TAGs and subsequent increase of FFA oxidation, leading to a worsening of steatohepatitis and increased portal hypertension [120].

Thus, increased TAG concentration is an epiphenomenon which happens simultaneously with toxic metabolite generation, lipotoxicity, and liver damage [33]. Through quantitative proteomics, it has been shown that liver steatosis alters hepatokine secretion and that these protein signals alter fatty acid metabolism and induce inflammation and IR in other cell types [116].

Uric acid and MAFLD

Hyperuricemia has recently been associated with metabolic syndrome, IR, and oxidative stress–related conditions. As mentioned above, the relationship between IR and MAFLD development suggests that there is an indirect association between uric acid (UA) levels and MAFLD. Based on this hypothesis, two recent studies were conducted in the Korean population which showed that serum UA concentrations are associated with the degree of hepatic steatosis, this being found to be an independent risk factor for incidental fatty liver in a healthy population, with an adjusted hazard ratio reaching up to 1.51 [121, 122]. IR might act as the link between hyperuricemia and components of the metabolic syndrome, such as hypertension and dyslipidemia [123].

Systemic low-grade chronic inflammation and oxidative stress contribute to the physiopathology of fatty liver, this shedding light on the as yet only partially elucidated function of UA in MAFLD. A possible pathway that could account for the increased steatosis in patients with high UA levels is the observed direct hepatic lipogenic effect exerted through mitochondrial oxidative stress: the latter acts synergically with fructose-induced TAG production, with increased UA leading to increased hepatic response to fructose-induced lipogenesis, increasing UA even further, resulting in a vicious cycle [124]. Additionally, fatty liver predisposition to steatosis is linked to metabolism of fructose by fructokinase C, resulting in the consumption of ATP, nucleotide turnover, and UA generation, which mediates fat accumulation [125]. Furthermore, differential glucose transporter 9 (GLUT-9), which mediates UA uptake into hepatocytes, might play an important role in UA-induced MAFLD [126]. A meta-analysis carried out by Darmawan et al. [127] showed a significant association between serum UA levels and the presence of MAFLD, with an adjusted OR of 1.92. Furthermore, within this analysis, two studies revealed a correlation between serum UA and the severity of liver disease. Another analysis published in the same year also showed a positive correlation between UA and MAFLD, this time with a pooled OR of 2.08 [128].

Adipokines

Adipose tissue is now recognized not only as the main site of storage of excess energy derived from food intake but also as an endocrine organ [131]. This highly dynamic organ, along with the liver which is arguably the body’s main metabolic regulator, regulates body homeostasis through the release of a number of bioactive substances known as adipokines, which have been identified as a crucial signaling mechanism in MAFLD development and progression [132]. By triggering chronic low-grade inflammation, modulating metabolism, and inducing pleiotropic effects, adipokines have a central role not only in the genesis of MAFLD, but also in other obesity-related digestive diseases (e.g., cholelithiasis, Barret’s esophagus, and esophageal and colorectal cancer) as well as pancreatic cancer and diabetes [131]. The two main adipokines are leptin and adiponectin (Fig. 3).

Fig. 3
figure 3

Overview of hormonal factor in MAFLD: in patients with MAFLD, leptin levels increase, leading to the activation of different pathways, which ultimately results in the activation of stellate cells and secretion of extracellular matrix, leading to fibrosis. Hyper-responsiveness to leptin-mediated signaling leads to increased expression of CD14 and increased progression to steatohepatitis. Decreased levels of adiponectin, on the other hand, decrease its protective effects, namely, antifibrotic, anti-inflammatory, and antioxidant. MAFLD: metabolic dysfunction–associated fatty liver disease; TGF-β1: transforming growth factor beta; mTOR: mammalian target of rapamycin; AdipoR1: adipocyte receptor-1; AMPK: AMP-activated protein kinase; ECM: extracellular matrix; TNF-α: tumor necrosis factor alpha; IL-6: interleukin 6; NF-κB: nuclear factor kappa-light-chain-enhancer of activated B cells

Leptin

Leptin, the first adipokine identified, is a hormone principally expressed in adipose tissue; it displays pleiotropic effects involving neuroendocrine regulation, energy homeostasis, and even angiogenesis, as well as cognition and immune function [133]. It is widely known as the “satiety hormone,” playing a major role in the pathogenesis of obesity [134].

Leptin’s role in MAFLD pathogenesis is dual and involves a variety of mechanisms, this being supported by the fact that a high percentage of patients with MAFLD have increased weight or obesity. It is well known that leptin secretion is proportional to the increase in body fat volume, it being a mechanism that curbs the appetite in order to modulate energy balance and weight. However, after a certain limit, increased leptin secretion no longer exerts its expected effect, and leptin resistance ensues. Therefore, it is important to establish the fact that most patients with MAFLD also have hyperleptinemia, while a minority might present with hypo- or normoleptinemia.

In hepatocytes, leptin acts primarily via the JAK2/STAT3 pathway, while it can also act through the PIK3/Akt/mTOR pathway, particularly in insulin sensitivity improvement. Increased leptin exerts a proinflammatory effect and, by regulating cytokine production and T cell activation, increases susceptibility to hepatotoxic events. A correlation has been found between increased circulating leptin levels and MAFLD severity [134, 135]. There is an important overlap between hepatic insulin and leptin signaling pathways, which points to the intrinsic interrelation between seemingly separate hormonal factors. In this regard, Duan et al. [136] found that the src homology 2 domain–containing adapter protein B (SH2)-B mediated leptin-stimulated phosphorylation of IRS proteins, resulting in activation of the PIK3 pathway, which might be involved in MAFLD pathogenesis.

Leptin has a double role in progression of fatty liver disease. Although it has been reported that it may counteract the mechanisms leading to hepatic steatosis in the early stages of MAFLD (i.e., until leptin resistance develops), its role in inflammation and fibrogenesis is adverse. In hepatic cells, leptin inhibits DNL and stimulates FFA oxidation, reducing hepatic lipid content and thus inducing lipotoxicosis and lipoapoptosis [137]. Furthermore, leptin decreases hepatic glucose production by reducing glycogenolysis, its role in gluconeogenesis at present being controversial, and also suppresses hepatic glucogenesis, thus creating an insulin-sensitizing environment and reducing glucotoxicity [138].

On the other hand, after reaching a threshold for IR and steatosis, leptin acts as a proinflammatory and profibrogenic adipokine, as it upregulates collagen α1 and increases HSCs’ activation, which express leptin receptors (LepRb) [139]. Activated HSCs also produce leptin, which fuels the vicious cycle by further inducing HSC proliferation and inhibiting apoptosis, leading to liver fibrosis [140]. LepRb can also be found in Kupffer and sinusoidal endothelial cells, through which leptin signals the upregulation of matrix remodeling enzymes including TGF-β1 [141]. Furthermore, it also upregulates CD14 expression in Kupffer cells. CD14 is an endotoxin bacterial lipopolysaccharide receptor, upregulation of which leads to increased sensitizing of the cells to harmful stimuli and, consequently, greater oxidative stress. Upregulation of CD14 was found to increase the development of steatohepatitis and fibrosis, even in the absence of previous steatosis [114, 142] (Fig. 3). The absolute requirement of leptin for hepatic fibrosis was confirmed in a study carried out by Leclercq and colleagues [143].

Lipodystrophic syndromes (LS), which can be either generalized or partial, are disorders in which there is absence of subcutaneous fat and have been associated with HIV therapy (HAART) as well as other causes, such as genetic mutations (non-HAART LS) [144]. LS often lead to metabolic defects due to changes in the levels of circulating adipokines. These include IR, T2DM, and hypertriglyceridemia, which may lead to the development of atherosclerosis, acute pancreatitis, and MAFLD. Leptin replacement therapy (LRT) with metreleptin has been found to have a positive effect on the group of LS that present with either normal or low serum leptin levels, showing improvement in laboratory values in lipid and hepatic profiles as well as in fasting plasma glucose and Hb1Ac levels, irrespective of food intake, body weight, and insulin levels [145, 146]. However, it is possible that a minority of patients with MAFLD who present with hypoleptinemia could potentially benefit from treatment with LRT. [147]

Adiponectin

Adiponectin is an adipokine that improves hepatic and peripheral IR and has hepatoprotective and anti-inflammatory activities through the deactivation of nuclear factor Κb (NF-Κb), by stimulating the secretion of anti-inflammatory cytokines, including interleukin-10 (IL-10) and IL-1 receptor antagonist. It also suppresses the release of proinflammatory cytokines such as TNF-α, IL-6, and interferon-γ (IFN-γ). Adiponectin is involved in the AMP-activated protein kinase (AMPK) and PPARα pathway and acts through receptors AdipoR1 and AdipoR2 [148]. Adiponectin is diminished in conditions such as visceral obesity and IR and has differential expression in the different stages leading from simple steatosis to steatohepatitis. A 2004 study showed that 77% of patients with steatohepatitis presented adiponectin levels of less than 10 μg/mL and HOMA-IR greater than 3 units, while only 33% of those with simple steatosis had these findings [149].

Interestingly, the genetic factor also plays an important role in adiponectin’s role in MAFLD pathogenesis; a 4-year follow-up survey suggesting increased MAFLD progression with three specific single nucleotide polymorphisms (SNPs) in the adiponectin gene (rs2241767, rs1501299, rs3774261) [150]. A systematic review and meta-analysis showed relative hypoadiponectinemia in patients with MAFLD when compared with controls, with a WMD of 3.00 (simple steatosis)–4.75 (steatohepatitis). Furthermore, there were also differences in adiponectin levels between steatosis and steatohepatitis patients, with lower adiponectin levels in patients with steatohepatitis (WMD 1.81) [151].

Estrogen

Several factors account for the differences in the incidence and progression of inflammatory metabolic diseases among females and males, MAFLD not being an exception. Among these factors, estrogens play a central role, mainly through the regulation of several metabolic and inflammatory pathways [152] (Fig. 4). A number of studies started to shed light on these characteristics by studying its influence on the cardiovascular system, demonstrating an increased risk in postmenopausal women [153]. Similar studies conducted by Gutierrez-Gröbe et al. [154] showed an increased incidence of MAFLD in postmenopausal women and an even higher incidence in patients with polycystic ovarian syndrome (PCOS). By acting through the estrogen receptors (ER) ERα, ERβ, and GPER (G-protein coupled estrogen receptor), estrogens limit dietary-induced DNL, favor the distribution of adipose tissue to subcutaneous deposits, and reduce FFA uptake, thus restricting the influx of these into the liver [152].

Fig. 4
figure 4

Effects of estrogen on prevention of MAFLD. Estrogen exerts a protective effect by decreasing overall FFA influx into the liver as well as by decreasing de novo lipogenesis and promoting β-oxidation of FFA thereby acting against persistent activation of alternative pathways of FFA oxidation, which leads to the generation of reactive oxygen species and, finally, to inflammatory response, contributing to the progression to steatohepatitis. ERα: estrogen receptor-α; ERβ: estrogen receptor-β; GPER: G-protein-coupled estrogen receptor-1; FFA: free fatty acid; DNL: de novo lipogenesis; ROS: reactive oxygen species

Multiple studies have been conducted in rats that point to the role of estrogens in fatty liver genesis. D’eon et al. [155] found that estrogen supplementation in ovariectomized rats decreases the hepatic expression of SREBP-1c, decreasing lipogenic enzyme synthesis. Furthermore, an estrogen-deficient state in rats is seen to directly lead to hepatic steatosis [156]. In a clinical trial including more than 5000 women, tamoxifen (an estrogen receptor antagonist) was found to increase the incidence of fatty liver in overweight and obese women [157].

Regarding a topic touched upon briefly above, the microbiome regulates steroid hormone metabolism by encoding enzymes that have the capability of deconjugating already conjugated estrogen metabolites, increasing the active form in circulation. Additionally, dietary polyphenols can be broken down by the microbiota giving rise to estrogen-like compounds that exert estrogen’s hormonal effects to different degrees [85]. Even though the direct relationship between microbiome, estrogen availability, and MAFLD has not to date been directly decoded, the indirect relationships between these three variables make the association extremely likely.

Conclusions and outlook

The data summarized in this review outline the role of the “multiple parallel hits” involved in MAFLD, highlighting their connection and the importance of the hormonal component. The role of hormones in the onset and progression of MAFLD is only a tiny part of the wide spectrum of factors involved in this metabolic disease, as well as the complex interrelations that are yet to be discovered. That said, its importance is indisputable and could be considered the basis for its direct implications in development of steatosis and progression to steatohepatitis. The core of hormonal influence on MAFLD is undoubtedly centered on IR, which by itself carries a complete set of different risk factors, genetic components, and pathophysiologic processes. Beyond this, IR starts a chain reaction involving a wide range of processes, including alteration in de novo lipogenesis, fatty acid oxidation, and activation of second messenger systems, as well as generation of reactive oxygen species and subsequent inflammation. Adipokines are central to the understanding MAFLD not only by virtue of their involvement in overweight and obesity, but also through their direct impact on hepatic metabolism and their endocrine effect on stellate cells. Estrogen has time after time shown its effect on a variety of diseases that present sexual dimorphism, including MAFLD. In this context, greater insight into the hormonal mechanisms underlying MAFLD and their role in risk factor burden will likely provide a solid basis for fully recognizing MAFLD to be a multidisciplinary disease.

Abbreviations

MAFLD:

Metabolic dysfunction–associated fatty liver disease

T2DM:

Type 2 diabetes mellitus

PCOS:

Polycystic ovarian syndrome

NAFLD:

Non-alcoholic fatty liver disease

NASH:

Non-alcoholic steatohepatitis

ALEH:

Latin American Association for the Study of the Liver

TAG:

Triacylglyceride

HCC:

Hepatocellular carcinoma

ALD:

Alcoholic liver disease

DNA:

Deoxyribonucleic acid

RNA:

Ribonucleic acid

GAB2:

GRB2-associated-binding protein 2

GRB2:

Growth factor receptor–bound protein 2

METTL3:

Methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit

TNF:

Tumor necrosis factor

Ob/ob:

Obese

DNL:

De novo lipogenesis

ChREBP:

Carbohydrate response element–binding protein

SREBP1c:

Sterol response element–binding protein 1c

GLUT:

Glucose transporter (derivatives: GLUT-4, GLUT-9)

pH::

Potential of hydrogen

GLP-1:

Glucagon-like peptide-1

HSC:

Hepatic stellate cell

GLP-1R:

Glucagon-like peptide-1 receptor

FFA:

Free fatty acid

DGAT2:

Diacylglycerol O-Acyltransferase 2

UA:

Uric acid

ATP:

Adenosine triphosphate

PPARα:

Peroxisome proliferator–activated receptor-alpha

NF-Κb:

Nuclear factor kappa-light-chain-enhancer of activated B cells

IR:

Insulin resistance

IL:

Interleukin

IFN:

Interferon

AMPK:

AMP-activated protein kinase

AdipoR1, 2:

Adiponectin receptor-1, 2

HOMA-IR:

Homeostatic model assessment of insulin resistance

SNP:

Single nucleotide polymorphism

ER:

Estrogen receptor

GPER:

G-protein-coupled estrogen receptor

References

  1. Byrne CD, Targher G (2015) NAFLD: a multisystem disease. J Hepatol 62(S1):S47-64. https://doi.org/10.1016/j.jhep.2014.12.012

    Article  PubMed  Google Scholar 

  2. Estes C, Razavi H, Loomba R, Younossi Z, Sanyal AJ (2018) Modeling the epidemic of nonalcoholic fatty liver disease demonstrates an exponential increase in burden of disease. Hepatology 67(1):123–133

    CAS  Article  Google Scholar 

  3. Powell EE, Wong VWS, Rinella M (2021) Non-alcoholic fatty liver disease. Lancet 397(10290):2212–2224. https://doi.org/10.1016/S0140-6736(20)32511-3

    CAS  Article  PubMed  Google Scholar 

  4. Sarwar R, Pierce N, Koppe S (2018) Obesity and nonalcoholic fatty liver disease. Diabetes, Metab Syndrome Obes: Targets Ther 56(4):543–552. https://doi.org/10.2147/DMSO.S146339

    Article  Google Scholar 

  5. Younossi ZM (2019) Non-alcoholic fatty liver disease – a global public health perspective. J Hepatol 70(3):531–544. https://doi.org/10.1016/j.jhep.2018.10.033

    Article  PubMed  Google Scholar 

  6. Vernon G, Baranova A, Younossi ZM (2011) Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther 34(3):274–285. https://doi.org/10.1111/j.1365-2036.2011.04724

    CAS  Article  PubMed  Google Scholar 

  7. Nugent C, Younossi Z (2007) Evaluation and management of obesity-related nonalcoholic fatty liver disease. Nat Rev Gastroenterol Hepatol 4:432–441. https://doi.org/10.1038/ncpgasthep0879

    Article  Google Scholar 

  8. Kasper P, Martin A, Lang S, Kütting F, Goeser T, Demir M et al (2021) NAFLD and cardiovascular diseases: a clinical review. Clin Res Cardiol 110(7):921–937. https://doi.org/10.1007/s00392-020-01709-7

    Article  PubMed  Google Scholar 

  9. Targher G, Byrne CD, Tilg H (2020) NAFLD and increased risk of cardiovascular disease: clinical associations, pathophysiological mechanisms and pharmacological implications. Gut 69(9):1691–1705. https://doi.org/10.1136/gutjnl-2020-320622

    CAS  Article  PubMed  Google Scholar 

  10. Liang Y, Chen H, Liu Y, Hou X, Wei L, Bao Y et al (2022) Association of MAFLD with diabetes, chronic kidney disease, and cardiovascular disease: a 4.6-year cohort study in China. J Clin Endocrinol Metab. 107(1):88–97. https://doi.org/10.1210/clinem/dgab641

    Article  PubMed  Google Scholar 

  11. Eslam M, Ahmed A, Després J-P, Jha V, Halford JCG, Wei Chieh JT et al (2021) Incorporating fatty liver disease in multidisciplinary care and novel clinical trial designs for patients with metabolic diseases. Lancet Gastroenterol Hepatol 6(9):743–753. https://doi.org/10.1016/S2468-1253(21)00132-1

    Article  PubMed  Google Scholar 

  12. Perakakis N, Polyzos SA, Yazdani A, Sala-Vila A, Kountouras J, Anastasilakis AD et al (2019) Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: a proof of concept study. Metabolism 101:154005. https://doi.org/10.1016/j.metabol.2019.154005

    CAS  Article  PubMed  Google Scholar 

  13. Katsiki N, Gastaldelli A, Mikhailidis DP (2019) Predictive models with the use of omics and supervised machine learning to diagnose non-alcoholic fatty liver disease: a “non-invasive alternative” to liver biopsy? Metabolism 11(6):1078. https://doi.org/10.3390/diagnostics11061078

    Article  Google Scholar 

  14. Olveres J, González G, Torres F, Moreno-Tagle JC, Carbajal-Degante E, Valencia-Rodríguez A et al (2021) What is new in computer vision and artificial intelligence in medical image analysis applications. Quant Imaging Med Surg 11(8):3830–3853. https://doi.org/10.21037/qims-20-1151

    Article  PubMed  PubMed Central  Google Scholar 

  15. Decharatanachart P, Chaiteerakij R, Tiyarattanachai T, Treeprasertsuk S (2021) Application of artificial intelligence in non-alcoholic fatty liver disease and liver fibrosis: a systematic review and meta-analysis Pakanat. Therap Adv Gastroenterol 14:1–17. https://doi.org/10.1177/17562848211062807

    CAS  Article  Google Scholar 

  16. Marchesini G, Day CP, Dufour JF, Canbay A, Nobili V, Ratziu V et al (2016) EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J Hepatol 64(6):1388–1402. https://doi.org/10.1016/j.jhep.2015.11.004

    Article  Google Scholar 

  17. Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M et al (2020) A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol 73(1):202–209. https://doi.org/10.1016/j.jhep.2020.03.039

    Article  PubMed  Google Scholar 

  18. Eslam M, Alkhouri N, Vajro P, Baumann U, Weiss R, Socha P et al (2021) Defining paediatric metabolic (dysfunction)-associated fatty liver disease: an international expert consensus statement. Lancet Gastroenterol Hepatol 6(10):864–873. https://doi.org/10.1016/S2468-1253(21)00183-7

    Article  PubMed  Google Scholar 

  19. Younossi ZM, Rinella ME, Sanyal AJ, Harrison SA, Brunt EM, Goodman Z et al (2021) From NAFLD to MAFLD: implications of a premature change in terminology. Hepatology 73(3):1194–1198. https://doi.org/10.1002/hep.31420

    Article  PubMed  Google Scholar 

  20. Duell PB, Welty FK, Miller M, Chait A, Hammond G, Ahmad Z et al (2022) Nonalcoholic fatty liver disease and cardiovascular risk: a scientific statement from the American Heart Association. Arterioscler Thromb Vasc Biol 42:e168–e185. https://doi.org/10.1161/ATV.0000000000000153

    CAS  Article  PubMed  Google Scholar 

  21. Eslam M, Sarin SK, Wai V, Wong S, Gao J, Takumi F et al (2020) The Asian Pacific Association for the Study of the Liver clinical practice guidelines for the diagnosis and management of metabolic associated fatty liver disease. Hep Intl 14:889–919. https://doi.org/10.1007/s12072-020-10094-2

    Article  Google Scholar 

  22. Shiha G, Korenjak M, Eskridge W, Casanovas T, Velez-Moller P, Högström S et al (2022) Redefining fatty liver disease: an international patient perspective. Lancet Gastroenterol Hepatol 6(1):73–79. https://doi.org/10.1016/S2468-1253(20)30294-6

    Article  Google Scholar 

  23. Tsutsumi T, Eslam M, Kawaguchi T, Yamamura S, Kawaguchi A, Nakano D et al (2021) MAFLD better predicts the progression of atherosclerotic cardiovascular risk than NAFLD: generalized estimating equation approach. Hepatol Res 51(11):1115–1128. https://doi.org/10.1111/hepr.13685.25

    CAS  Article  PubMed  Google Scholar 

  24. Yamamura S, Eslam M, Kawaguchi T, Tsutsumi T, Nakano D, Yoshinaga S et al (2020) MAFLD identifies patients with significant hepatic fibrosis better than NAFLD. Liver Int 40(12):3018–3030. https://doi.org/10.1111/liv.14675

    CAS  Article  PubMed  Google Scholar 

  25. Alharthi J, Gastaldelli A, Cua IH, Ghazinian H, Eslam M (2022) Metabolic dysfunction-associated fatty liver disease. Curr Opin Gastroenterol 75(2):419–429. https://doi.org/10.1002/hep.32131

    CAS  Article  Google Scholar 

  26. Méndez-Sánchez N, Zamarripa-Dorsey F, Panduro A, Purón-González E, Coronado-Alejandro EU, Cortez-Hernández CA et al (2018) Current trends of liver cirrhosis in Mexico: similitudes and differences with other world regions. World J Clin Cases 6(15):922–930. https://doi.org/10.12998/wjcc.v6.i15.922

    Article  PubMed  PubMed Central  Google Scholar 

  27. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M (2016) Global epidemiology of nonalcoholic fatty liver disease—meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 64(1):73–84. https://doi.org/10.1002/hep.28431

    Article  PubMed  Google Scholar 

  28. Eslam M, George J (2019) Genetic insights for drug development in NAFLD. Trends Pharmacol Sci 40(7):506–516. https://doi.org/10.1016/j.tips.2019.05.002

    CAS  Article  PubMed  Google Scholar 

  29. Bayoumi A, Grønbæk H, George J, Eslam M (2020) The epigenetic drug discovery landscape for metabolic-associated fatty liver disease. Trends Genet 36(6):429–441. https://doi.org/10.1016/j.tig.2020.03.003

    CAS  Article  PubMed  Google Scholar 

  30. Petta S, Eslam M, Valenti L, Bugianesi E, Barbara M, Cammà C et al (2017) Metabolic syndrome and severity of fibrosis in nonalcoholic fatty liver disease: an age-dependent risk profiling study. Liver Int 37(9):1389–1396. https://doi.org/10.1111/liv.13397

    CAS  Article  PubMed  Google Scholar 

  31. Mendez-Sanchez N, Arrese M, Gadano A, Oliveira CP, Fassio E, Arab JP et al (2021) The Latin American Association for the Study of the Liver (ALEH) position statement on the redefinition of fatty liver disease. Lancet Gastroenterol Hepatol 6(1):65–72. https://doi.org/10.1016/S2468-1253(20)30340-X

    Article  PubMed  Google Scholar 

  32. Peverill W, Powell LW, Skoien R (2014) Evolving concepts in the pathogenesis of NASH: beyond steatosis and inflammation. Int J Mol Sci 15(5):8591–8638. https://doi.org/10.3390/ijms15058591

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. Buzzetti E, Pinzani M, Tsochatzis EA (2016) The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD). Metabolism 65(8):1038–1048. https://doi.org/10.1016/j.metabol.2015.12.012

    CAS  Article  PubMed  Google Scholar 

  34. Eslam M, George J (2019) Genetic contributions to NAFLD: leveraging shared genetics to uncover systems biology. Nat Rev Gastroenterol Hepatol 17(1):40–52. https://doi.org/10.1038/s41575-019-0212-0

    Article  PubMed  Google Scholar 

  35. Eslam M, Fan JG, Mendez-Sanchez N (2020) Non-alcoholic fatty liver disease in non-obese individuals: the impact of metabolic health. Lancet Gastroenterol Hepatol 5(8):713–715. https://doi.org/10.1016/S2468-1253(20)30090-X

    Article  PubMed  Google Scholar 

  36. Speliotes EK, Yerges-Armstrong LM, Wu J, Hernaez R, Kim LJ, Palmer CD et al (2011) Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits. PLoS Genet 7(3):e1001324. https://doi.org/10.1371/journal.pgen.1001324

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  37. Anstee QM, Day CP (2013) The genetics of NAFLD. Nat Rev Gastroenterol Hepatol 10(11):645–655. https://doi.org/10.1038/nrgastro.2013

    CAS  Article  PubMed  Google Scholar 

  38. Li JZ, Huang Y, Karaman R, Ivanova PT, Brown HA, Roddy T et al (2012) Chronic overexpression of PNPLA3 I148M in mouse liver causes hepatic steatosis. J Clin Invest 122(11):4130–4144. https://doi.org/10.1172/JCI65179

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  39. Guo B, Guo Y, Nima Q, Feng Y, Wang Z, Lu R et al (2022) Exposure to air pollution is associated with an increased risk of metabolic dysfunction-associated fatty liver disease. J Hepatol 76(3):518–525. https://doi.org/10.1016/j.jhep.2021.10.016

    CAS  Article  PubMed  Google Scholar 

  40. Trépo E, Romeo S, Zucman-Rossi J, Nahon P (2016) PNPLA3 gene in liver diseases. J Hepatol 65(2):399–412. https://doi.org/10.1016/j.jhep.2016.03.011

    CAS  Article  PubMed  Google Scholar 

  41. Sookoian S, Pirola CJ (2011) Meta-analysis of the influence of I148M variant of patatin-like phospholipase domain containing 3 gene (PNPLA3) on the susceptibility and histological severity of nonalcoholic fatty liver disease. Hepatology 53(6):1883–1894. https://doi.org/10.1002/hep.24283

    CAS  Article  PubMed  Google Scholar 

  42. Eslam M, Valenti L, Romeo S (2018) Genetics and epigenetics of NAFLD and NASH: clinical impact. J Hepatol 68(2):268–279. https://doi.org/10.1016/j.jhep.2017.09.003

    CAS  Article  PubMed  Google Scholar 

  43. Choudhary NS, Duseja A (2021) Genetic and epigenetic disease modifiers: non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD). Transl Gastroenterol Hepatol 6:2. https://doi.org/10.21037/tgh.2019.09.06

    Article  PubMed  PubMed Central  Google Scholar 

  44. Thabet K, Asimakopoulos A, Shojaei M, Romero-Gomez M, Mangia A, Irving WL et al (2016) MBOAT7 rs641738 increases risk of liver inflammation and transition to fibrosis in chronic hepatitis C. Nat Commun 7:12757. https://doi.org/10.1038/ncomms12757

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. Thabet K, Chan HLY, Petta S, Mangia A, Berg T, Boonstra A et al (2017) The membrane-bound O-acyltransferase domain-containing 7 variant rs641738 increases inflammation and fibrosis in chronic hepatitis B. Hepatology 65(6):1840–1850. https://doi.org/10.1002/hep.29064

    CAS  Article  PubMed  Google Scholar 

  46. Eslam M, Mangia A, Berg T, Chan HLY, Irving WL, Dore GJ et al (2016) Diverse impacts of the rs58542926 E167K variant in TM6SF2 on viral and metabolic liver disease phenotypes. Hepatology 64(1):34–46. https://doi.org/10.1002/hep.28475

    CAS  Article  PubMed  Google Scholar 

  47. Metwally M, Bayoumi A, Romero-Gomez M, Thabet K, John M, Adams LA et al (2019) A polymorphism in the Irisin-encoding gene (FNDC5) associates with hepatic steatosis by differential miRNA binding to the 3’UTR. J Hepatol 70(3):494–500. https://doi.org/10.1016/j.jhep.2018.10.021

    CAS  Article  PubMed  Google Scholar 

  48. Bayoumi A, Elsayed A, Han S, Petta S, Adams LA, Aller R, et al. (2021) Mistranslation drives alterations in protein levels and the effects of a synonymous variant at the fibroblast growth factor 21 locus. Adv Sci 8(11). doi: https://doi.org/10.1002/advs.202004168

  49. Eslam M, Hashem AM, Leung R, Romero-Gomez M, Berg T, Dore GJ et al (2015) Interferon-λ rs12979860 genotype and liver fibrosis in viral and non-viral chronic liver disease. Nat Commun 6:6422. https://doi.org/10.1038/ncomms7422

    CAS  Article  PubMed  Google Scholar 

  50. Eslam M, McLeod D, Kelaeng KS, Mangia A, Berg T, Thabet K et al (2017) IFN-λ3, not IFN-λ4, likely mediates IFNL3-IFNL4 haplotype-dependent hepatic inflammation and fibrosis. Nat Genet 49(5):795–800. https://doi.org/10.1038/ng.3836

    CAS  Article  PubMed  Google Scholar 

  51. Eslam M, Hashem AM, Romero-Gomez M, Berg T, Dore GJ, Mangia A et al (2016) FibroGENE: a gene-based model for staging liver fibrosis. J Hepatol 64(2):390–398. https://doi.org/10.1016/j.jhep.2015.11.008

    CAS  Article  PubMed  Google Scholar 

  52. Metwally M, Bayoumi A, Khan A, Adams LA, Aller R, García-Monzón C et al (2021) Copy number variation and expression of exportin-4 associates with severity of fibrosis in metabolic associated fatty liver disease. EBioMedicine 70:103521. https://doi.org/10.1016/j.ebiom.2021.103521

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  53. El-Serag HB, Tran T, Everhart JE (2004) Diabetes increases the risk of chronic liver disease and hepatocellular carcinoma. Gastroenterology 126(2):460–468. https://doi.org/10.1053/j.gastro.2003.10.065

    Article  PubMed  Google Scholar 

  54. Raxitkumar J, Suhag P, Suthat L (2013) The association between metabolic syndrome and hepatocellular carcinoma: systemic review and meta-analysis. J Clin Gastroenterol 47(1):33–44. https://doi.org/10.1097/MCG.0b013e3182a030c4

    CAS  Article  Google Scholar 

  55. Paradis V, Zalisnski S, Chelbi E, Guedj N, Degos F, Vilgrain V et al (2009) Hepatocellular carcinomas in patients with metabolic syndrome often develop without significant liverfibrosis: a pathological analysis. Hepatology 49(3):851–859. https://doi.org/10.1002/hep.22734

    Article  PubMed  Google Scholar 

  56. Paluch BE, Naqash AR, Brumberger Z, Nemeth MJ, Griffiths EA (2016) Epigenetics: a primer for clinicians. Blood Rev 30:285–295. https://doi.org/10.1016/j.blre.2016.02.002

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  57. Teegarden D, Romieu I, Lelièvre SA (2021) Redefining the impact of nutrition on breast cancer incidence: is epigenetics involved? Nutr Res Rev 25(1):68–95. https://doi.org/10.1017/S0954422411000199

    CAS  Article  Google Scholar 

  58. Lakhani CM, Tierney BT, Manrai AK, Yang J, Visscher PM, Patel CJ (2017) Epigenetic alterations in colorectal cancer: emerging biomarkers. Physiol Behav 176(3):139–148. https://doi.org/10.1053/j.gastro.2015.07.011

    CAS  Article  Google Scholar 

  59. Hyun J, Jung Y (2020) Dna methylation in nonalcoholic fatty liver disease. Int J Mol Sci 21(21):1–26. https://doi.org/10.3390/ijms21218138

    CAS  Article  Google Scholar 

  60. Bishop KS, Ferguson LR (2015) The interaction between epigenetics, nutrition and the development of cancer. Nutrients 7(2):922–947. https://doi.org/10.3390/nu7020922

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  61. DiStefano JK (2017) Fructose-mediated effects on gene expression and epigenetic mechanisms associated with NAFLD pathogenesis. Physiol Behav 176(10):139–148. https://doi.org/10.1007/s00018-019-03390-0

    CAS  Article  Google Scholar 

  62. Wortmann SB, Mayr JA (2019) Choline-related-inherited metabolic diseases—a mini review. J Inherit Metab Dis 42(2):237–242. https://doi.org/10.1002/jimd.12011

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  63. Cordero P, Campion J, Milagro FI, Martinez JA (2013) Transcriptomic and epigenetic changes in early liver steatosis associated to obesity: effect of dietary methyl donor supplementation. Mol Genet Metab 110(3):388–395. https://doi.org/10.1016/j.ymgme.2013.08.022

    CAS  Article  PubMed  Google Scholar 

  64. Wu N, Yuan F, Yue S, Jiang F, Ren D, Liu L et al (2021) Effect of exercise and diet intervention in NAFLD and NASH via GAB2 methylation. Cell Biosci 11(1):1–14. https://doi.org/10.1186/s13578-021-00701-6

    CAS  Article  Google Scholar 

  65. Qin Y, Li B, Arumugam S, Lu Q, Mankash SM, Li J, et al. (2021) m6A mRNA methylation-directed myeloid cell activation controls progression of NAFLD and obesity. Cell Rep. 37(6). https://doi.org/10.1016/j.celrep.2021.109968

  66. Johnson ND, Wu X, Still CD, Chu X, Petrick AT, Gerhard GS et al (2021) Differential DNA methylation and changing cell-type proportions as fibrotic stage progresses in NAFLD. Clin Epigenetics 13(1):1–14. https://doi.org/10.1186/s13148-021-01129-y

    CAS  Article  Google Scholar 

  67. Xavier MJ, Roman SD, Aitken RJ, Nixon B (2019) Transgenerational inheritance: how impacts to the epigenetic and genetic information of parents affect offspring health. Hum Reprod Update 25(5):519–541. https://doi.org/10.1093/humupd/dmz017

    CAS  Article  Google Scholar 

  68. Gori M, Arciello M, Balsano C (2014) MicroRNAs in nonalcoholic fatty liver disease: novel biomarkers and prognostic tools during the transition from steatosis to hepatocarcinoma. Biomed Res Int. https://doi.org/10.1155/2014/741465

    Article  PubMed  PubMed Central  Google Scholar 

  69. Ling C, Groop L (2009) Epigenetics: a molecular link between environmental factors and type 2 diabetes. Diabetes 58(12):2718–2725. https://doi.org/10.2337/db09-1003

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  70. Zeng X, Yuan X, Cai Q, Tang C, Gao J (2021) Circular rna as an epigenetic regulator in chronic liver diseases. Cells 10(8):1–15. https://doi.org/10.3390/cells10081945

    CAS  Article  Google Scholar 

  71. Pulla VK, Battu MB, Alvala M, Sriram D, Yogeeswari P (2012) Can targeting SIRT-1 to treat type 2 diabetes be a good strategy? A review Expert Opin Ther Targets 16(8):819–832. https://doi.org/10.1517/14728222.2012.703656

    CAS  Article  PubMed  Google Scholar 

  72. Ding RB, Bao JL, Deng CX (2017) Emerging roles of SIRT1 in fatty liver diseases. Int J Biol Sci 13(7):852–867. https://doi.org/10.7150/ijbs.19370

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  73. Ponugoti B, Kim DH, Xiao Z, Smith Z, Miao J, Zang M et al (2010) SIRT1 deacetylates and inhibits SREBP-IR 1C activity in regulation of hepatic lipid metabolism. J Biol Chem 285(44):33959–33970. https://doi.org/10.1074/jbc.M110.122978

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  74. Wang RH, Li C, Deng CX (2010) Liver steatosis and increased ChREBP expression in mice carrying a liver specific SIRT1 null mutation under a normal feeding condition. Int J Biol Sci 6(7):682–690. https://doi.org/10.7150/ijbs.6.682

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  75. Colak Y, Ozturk O, Senates E, Tuncer I, Yorulmaz E, Adali G et al (2011) SIRT1 as a potential therapeutic target for treatment of nonalcoholic fatty liver disease. Med Sci Monit 17(5):5–9. https://doi.org/10.12659/msm.881749

    Article  Google Scholar 

  76. Bordone L, Motta MC, Picard F, Robinson A, Jhala US, Apfeld J et al (2006) Sirt1 regulates insulin secretion by repressing UCP2 in pancreatic beta cells. PLoS Biol 4(2):210–220. https://doi.org/10.1371/journal.pbio.0040031

    CAS  Article  Google Scholar 

  77. Cao Y, Jiang X, Ma H, Wang Y, Xue P, Liu Y (2016) SIRT1 and insulin resistance. J Diabetes Complications 30(1):178–183. https://doi.org/10.1016/j.jdiacomp.2015.08.022

    Article  PubMed  Google Scholar 

  78. Vulf M, Shunkina D, Komar A, Bograya M, Zatolokin P, Kirienkova E et al (2021) Analysis of miRNAs profiles in serum of patients with steatosis and steatohepatitis. Front Cell Dev Biol. https://doi.org/10.3389/fcell.2021.736677

    Article  PubMed  PubMed Central  Google Scholar 

  79. Liu XL, Cao HX, Wang BC, Xin FZ, Zhang RN, Zhou D et al (2017) miR-192-5p regulates lipid synthesis in non-alcoholic fatty liver disease through SCD-1. World J Gastroenterol 23(46):8140–8151. https://doi.org/10.3748/wjg.v23.i46.8140

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  80. Liu XL, Pan Q, Cao HX, Xin FZ, Zhao ZH, Yang RX et al (2020) Lipotoxic hepatocyte-derived exosomal microRNA 192–5p activates macrophages through rictor/Akt/forkhead box transcription factor O1 signaling in nonalcoholic fatty liver disease. Hepatology 72(2):454–469. https://doi.org/10.1002/hep.31050

    CAS  Article  PubMed  Google Scholar 

  81. Ren FJ, Yao Y, Cai XY, Fang GY (2021) Emerging role of MiR-192-5p in human diseases. Front Pharmacol. https://doi.org/10.3389/fphar.2021.614068

    Article  PubMed  PubMed Central  Google Scholar 

  82. Doumatey AP, He WJ, Gaye A, Lei L, Zhou J, Gibbons GH et al (2018) Circulating MiR-374a-5p is a potential modulator of the inflammatory process in obesity. Sci Rep 8(1):1–9. https://doi.org/10.1038/s41598-018-26065-5

    CAS  Article  Google Scholar 

  83. Li B, Selmi C, Tang R, Gershwin ME, Ma X (2018) The microbiome and autoimmunity: a paradigm from the gut–liver axis. Cell Mol Immunol 15(6):595–609. https://doi.org/10.1038/cmi.2018.7

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  84. Adolph TE, Grander C, Moschen AR, Tilg H (2018) Liver–microbiome axis in health and disease. Trends Immunol 39(9):712–723. https://doi.org/10.1016/j.it.2018.05.002

    CAS  Article  PubMed  Google Scholar 

  85. Parida S, Sharma D (2019) The microbiome-estrogen connection and breast cancer risk. Cells 8(12):1642. https://doi.org/10.3390/cells8121642

    CAS  Article  PubMed Central  Google Scholar 

  86. Li Z, Yang S, Lin H, Huang J, Watkins PA, Moser AB et al (2003) Probiotics and antibodies to TNF inhibit inflammatory activity and improve nonalcoholic fatty liver disease. Hepatology 37(2):343–350. https://doi.org/10.1053/jhep.2003.50048

    CAS  Article  PubMed  Google Scholar 

  87. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444(7122):1027–1031. https://doi.org/10.1038/nature05414

    Article  PubMed  Google Scholar 

  88. Albillos A, de Gottardi A, Rescigno M (2020) The gut-liver axis in liver disease: pathophysiological basis for therapy. J Hepatol 72(3):558–577. https://doi.org/10.1016/j.jhep.2019.10.003

    CAS  Article  PubMed  Google Scholar 

  89. Xue R, Su L, Lai S, Wang Y, Zhao D, Fan J et al (2021) Bile acid receptors and the gut–liver axis in nonalcoholic fatty liver disease. Cells 10(11):2806. https://doi.org/10.3390/cells10112806

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  90. Grzych G, Chávez-Talavera O, Descat A, Thuillier D, Verrijken A, Kouach M et al (2021) NASH-related increases in plasma bile acid levels depend on insulin resistance. JHEP Reports. https://doi.org/10.1016/j.jhepr.2020.100222

    Article  PubMed  Google Scholar 

  91. Puri P, Daita K, Joyce A, Mirshahi F, Santhekadur PK, Cazanave S et al (2018) The presence and severity of nonalcoholic steatohepatitis is associated with specific changes in circulating bile acids. Hepatology 67(2):534. https://doi.org/10.1002/hep.29359

    CAS  Article  PubMed  Google Scholar 

  92. Le Roy T, Llopis M, Lepage P, Bruneau A, Rabot S, Bevilacqua C et al (2013) Intestinal microbiota determines development of non-alcoholic fatty liver disease in mice. Gut 62(12):1787–1794. https://doi.org/10.1136/gutjnl-2012-303816

    CAS  Article  PubMed  Google Scholar 

  93. Alferink LJM, Radjabzadeh D, Erler NS, Vojinovic D, Medina-Gomez C, Uitterlinden AG et al (2021) Microbiomics, metabolomics, predicted metagenomics, and hepatic steatosis in a population-based study of 1,355 adults. Hepatology 73(3):968–982. https://doi.org/10.1002/hep.31417

    CAS  Article  PubMed  Google Scholar 

  94. Hernández-Ceballos W, Cordova-Gallardo J, Mendez-Sanchez N (2021) Gut microbiota in metabolic-associated fatty liver disease and in other chronic metabolic diseases. J Clin Transl Hepatol 9(2):227–238. https://doi.org/10.14218/JCTH.2020.00131

    Article  PubMed  PubMed Central  Google Scholar 

  95. Zhu L, Baker SS, Gill C, Liu W, Alkhouri R, Baker RD et al (2013) Characterization of gut microbiomes in nonalcoholic steatohepatitis (NASH) patients: a connection between endogenous alcohol and NASH. Hepatology 57(2):601–609. https://doi.org/10.1002/hep.26093

    CAS  Article  PubMed  Google Scholar 

  96. Cope K, Risby T, Diehl AM (2000) Increased gastrointestinal ethanol production in obese mice: implications for fatty liver disease pathogenesis. Gastroenterology 119(5):1340–1347. https://doi.org/10.1053/gast.2000.19267

    CAS  Article  PubMed  Google Scholar 

  97. Chen F, Esmaili S, Rogers GB, Bugianesi E, Petta S, Marchesini G et al (2020) Lean NAFLD: a distinct entity shaped by differential metabolic adaptation. Hepatology 4:1213–1227. https://doi.org/10.1002/hep.30908

    CAS  Article  Google Scholar 

  98. Pérez-Montes de Oca A, Julián MT, Ramos A, Puig-Domingo M, Alonso N (2020) Microbiota, Fiber, and NAFLD: is there any connection? Nutrients 12(10):3100. https://doi.org/10.3390/nu12103100

    CAS  Article  PubMed Central  Google Scholar 

  99. Pendyala S, Walker JM, Holt PR (2012) A high-fat diet is associated with endotoxemia that originates from the gut. Gastroenterology 142(5):1–7. https://doi.org/10.1053/j.gastro.2012.01.034.%0AA

    Article  Google Scholar 

  100. Oteng AB, Loregger A, van Weeghel M, Zelcer N, Kersten S. (2019) Industrial trans fatty acids stimulate SREBP2-mediated cholesterogenesis and promote non-alcoholic fatty liver disease. Mol Nutr Food Res. 63(19):1–16. oi: https://doi.org/10.1002/mnfr.201900385

  101. Neuschwander-Tetri BA, Ford DA, Acharya S, Gilkey G, Basaranoglu M, Tetri LH et al (2012) Dietary trans-fatty acid induced NASH is normalized following loss. Lipids 47(10):1–7. https://doi.org/10.1007/s11745-012-3709-7

    CAS  Article  Google Scholar 

  102. Chen Q, Wang T, Li J, Wang S, Qiu F, Yu H et al (2017) Effects of natural products on fructose-induced nonalcoholic fatty liver disease (NAFLD). Nutrients 9(2):96. https://doi.org/10.3390/nu9020096

    CAS  Article  PubMed Central  Google Scholar 

  103. Ter Horst KW, Serlie MJ (2017) Fructose consumption, lipogenesis, and non-alcoholic fatty liver disease. Nutrients 9(9):1–20. https://doi.org/10.3390/nu9090981

    CAS  Article  Google Scholar 

  104. Zhang AMY, Wellberg EA, Kopp JL, Johnson JD (2021) Hyperinsulinemia in obesity, inflammation, and cancer. Diabetes Metab J 45(3):285–311. https://doi.org/10.4093/dmj.2020.0250

    Article  PubMed  PubMed Central  Google Scholar 

  105. Stout RW (1996) Hyperinsulinemia and atherosclerosis. Diabetes 45(3 SUPPL.):45–46. https://doi.org/10.2337/diab.45.3.s45

    Article  Google Scholar 

  106. Erion KA, Corkey BE (2017) Hyperinsulinemia: a cause of obesity? Curr Obes Rep 6(2):178–186

    Article  Google Scholar 

  107. Templeman NM, Skovsø S, Page MM, Lim GE, Johnson JD (2017) A causal role for hyperinsulinemia in obesity. J Endocrinol 232(3):R173–R183. https://doi.org/10.1007/s13679-017-0261-z

    CAS  Article  PubMed  Google Scholar 

  108. Sakurai Y, Kubota N, Yamauchi T, Kadowaki T (2021) Role of insulin resistance in mafld. Int J Mol 22(8):1–26. https://doi.org/10.3390/ijms22084156

    CAS  Article  Google Scholar 

  109. Aronoff SL, Berkowitz K, Shreiner B, Want L (2004) Glucose metabolism and regulation: beyond insulin and glucagon. Diabetes Spectr 17(3):183–190. https://doi.org/10.2337/diaspect.17.3.183

    Article  Google Scholar 

  110. Huang S, Czech MP (2007) The GLUT4 glucose transporter. Cell Metab 5(4):237–252. https://doi.org/10.1016/j.cmet.2007.03.006

    CAS  Article  PubMed  Google Scholar 

  111. Karim S, Adams DH, Lalor PF (2012) Hepatic expression and cellular distribution of the glucose transporter family. World J Gastroenterol 18(46):6771–6781. https://doi.org/10.3748/wjg.v18.i46.6771

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  112. Roh GS, Kim S, Jung J, Kim H, Heo RW, Yi CO et al (2014) Exendin-4 improves nonalcoholic fatty liver disease by regulating glucose transporter 4 expression in ob/ob mice. Korean J Physiol Pharmacol 18(4):333–339. https://doi.org/10.4196/kjpp.2014.18.4.333

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  113. Kawahito S, Kitahata H, Oshita S (2009) Problems associated with glucose toxicity: role of hyperglycemia-induced oxidative stress. World J Gastroenterol 15(33):4137. https://doi.org/10.3748/wjg.15.4137

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  114. Polyzos SA, Kountouras J, Mantzoros CS (2015) Leptin in nonalcoholic fatty liver disease: a narrative review. Metabolism 64(1):60–78. https://doi.org/10.1016/j.metabol.2014.10.012

    CAS  Article  PubMed  Google Scholar 

  115. Méndez-Sánchez N, Arrese M, Zamora-Valdés D, Uribe M (2007) Current concepts in the pathogenesis of nonalcoholic fatty liver disease. Liver Int 27(4):423–433. https://doi.org/10.1111/j.1478-3231.2007.01483.x

    CAS  Article  PubMed  Google Scholar 

  116. Watt MJ, Miotto PM, De Nardo W, Montgomery MK (2019) The liver as an endocrine organ - linking NAFLD and insulin resistance. Endocr Rev 40(5):1367–1393. https://doi.org/10.1210/er.2019-00034

    Article  PubMed  Google Scholar 

  117. Korenblat KM, Fabbrini E, Mohammed BS, Klein S (2008) Liver, muscle and adipose tissue insulin action is directly related to intrahepatic triglyceride content in obese subjects. Gastroenterology 134(5):1369–1375. https://doi.org/10.1053/j.gastro.2008.01.075

    CAS  Article  PubMed  Google Scholar 

  118. Smith GI, Shankaran M, Yoshino M, Schweitzer GG, Chondronikola M, Beals JW et al (2020) Insulin resistance drives hepatic de novo lipogenesis in nonalcoholic fatty liver disease. J Clin Invest 130(3):1453–1460. https://doi.org/10.1172/JCI134165

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  119. Alves-Bezerra M, Cohen DE (2018) Triglyceride metabolism in the liver. Compr Physiol 8(1):1–22. https://doi.org/10.1002/cphy.c170012

    Article  Google Scholar 

  120. Wasfy E, Elkassas G, Elnawasany S, Elkasrawy K, Abd-Elsalam S, Soliman S et al (2018) Predicting esophageal varices in cirrhotic hepatitis c virus patients using noninvasive measurement of insulin resistance variables. Endocrine, Metab Immune Disord - Drug Targets 18(6):573–580. https://doi.org/10.2174/18753183-v12-e2204040

    CAS  Article  Google Scholar 

  121. Ryu S, Chang Y, Kim SG, Cho J, Guallar E (2011) Serum uric acid levels predict incident nonalcoholic fatty liver disease in healthy Korean men. Metabolism 60(6):860–866. https://doi.org/10.1016/j.metabol.2010.08.005

    CAS  Article  PubMed  Google Scholar 

  122. Lee YJ, Lee HR, Lee JH, Shin YH, Shim JY (2010) Association between serum uric acid and non-alcoholic fatty liver disease in Korean adults. Clin Chem Lab Med 48(2):175–180. https://doi.org/10.1515/CCLM.2010.037

    CAS  Article  PubMed  Google Scholar 

  123. Tae WY, Ki CS, Hun SS, Byung JK, Bum SK, Jin HK et al (2005) Relationship between serum uric acid concentration and insulin resistance and metabolic syndrome. Circ J 69(8):928–933. https://doi.org/10.1253/circj.69.928

    Article  Google Scholar 

  124. Lanaspa MA, Sanchez-Lozada LG, Choi YJ, Cicerchi C, Kanbay M, Roncal-Jimenez CA et al (2012) Uric acid induces hepatic steatosis by generation of mitochondrial oxidative stress: potential role in fructose-dependent and -independent fatty liver. J Biol Chem 287(48):40732–40744. https://doi.org/10.1074/jbc.M112.399899

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  125. Jensen T, Abdelmalek MF, Sullivan S, Nadeau KJ, Green M, Roncal C et al (2018) Fructose and sugar: a major mediator of nonalcoholic fatty liver disease. J Hepatol 68(5):1063–1075. https://doi.org/10.1016/j.jhep.2018.01.019

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  126. So A, Thorens B (2010) Uric acid transport and disease. J Clin Invest 120(6):1791–1799. https://doi.org/10.1172/JCI42344

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  127. Darmawan G, Hamijoyo L, Hasan I (2017) Association between serum uric acid and non-alcoholic fatty liver disease: a meta-analysis. Acta Med Indones 49(2):136–147. https://doi.org/10.7717/peerj.7563

    Article  PubMed  Google Scholar 

  128. Huang F, Liu A, Fang H, Geng X (2017) Serum uric acid levels in non-alcoholic steatosis patients: a meta-analysis. Asia Pac J Clin Nutr 26(2):334–342. https://doi.org/10.6133/apjcn.092016.04

    CAS  Article  PubMed  Google Scholar 

  129. Begriche K, Igoudjil A, Pessayre D, Fromenty B (2006) Mitochondrial dysfunction in NASH: causes, consequences and possible means to prevent it. Mitochondrion 6(1):1–28. https://doi.org/10.1016/j.mito.2005.10.004

    CAS  Article  PubMed  Google Scholar 

  130. Chatterjee S, Ganini D, Tokar EJ, Kumar A, Das S, Corbett J et al (2013) Leptin is key to peroxynitrite-mediated oxidative stress and Kupffer cell activation in experimental nonalcoholic steatohepatitis. J Hepatol 58(4):778. https://doi.org/10.1016/j.jhep.2012.11.035

    CAS  Article  PubMed  Google Scholar 

  131. Jung UJ, Choi MS (2014) Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. Int J Mol Sci 15(4):6184–6223. https://doi.org/10.3390/ijms15046184

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  132. Chang ML, Yang Z, Yang SS (2020) Roles of adipokines in digestive diseases: markers of inflammation, metabolic alteration and disease progression. Int J Mol Sci 21(21):1–36. https://doi.org/10.3390/ijms21218308

    CAS  Article  Google Scholar 

  133. Dalamaga M, Chou SH, Shields K, Papageorgiou P, Polyzos SA, Mantzoros CS (2013) Leptin at the intersection of neuroendocrinology and metabolism: current evidence and therapeutic perspectives. Cell Metab 18(1):29–42. https://doi.org/10.1016/j.cmet.2013.05.010

    CAS  Article  PubMed  Google Scholar 

  134. Polyzos SA, Aronis KN, Kountouras J, Raptis DD, Vasiloglou MF, Mantzoros CS (2016) Circulating leptin in non-alcoholic fatty liver disease: a systematic review and meta-analysis. Diabetologia 59(1):30–43. https://doi.org/10.1007/s00125-015-3769-3

    CAS  Article  PubMed  Google Scholar 

  135. Boutari C, Perakakis N, Mantzoros CS (2018) Association of adipokines with development and progression of nonalcoholic fatty liver disease. Endocrinol Metab 33(1):33–43. https://doi.org/10.3803/EnM.2018.33.1.33

    CAS  Article  Google Scholar 

  136. Duan C, Li M, Rui L (2004) SH2-B promotes insulin receptor substrate 1 (IRS1)- and IRS2-mediated activation of the phosphatidylinositol 3-kinase pathway in response to leptin. J Biol Chem 279(42):43684–43691. https://doi.org/10.1074/jbc.M408495200

    CAS  Article  PubMed  Google Scholar 

  137. Martínez-Uña M, López-Mancheño Y, Diéguez C, Fernández-Rojo MA, Novelle MG (2020) Unraveling the role of leptin in liver function and its relationship with liver diseases. Int J Mol Sci 21(24):1–33. https://doi.org/10.3390/ijms21249368

    CAS  Article  Google Scholar 

  138. Moon HS, Dalamaga M, Kim SY, Polyzos SA, Hamnvik OP, Magkos F et al (2013) Leptin’s role in lipodystrophic and nonlipodystrophic insulin-resistant and diabetic individuals. Endocr Rev 34(3):377–412. https://doi.org/10.1210/er.2012-1053

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  139. Aleffi S, Petrai I, Bertolani C, Parola M, Colombatto S, Novo E et al (2005) Upregulation of proinflammatory and proangiogenic cytokines by leptin in human hepatic stellate cells. Hepatology 42(6):1339–1348. https://doi.org/10.1002/hep.20965

    CAS  Article  PubMed  Google Scholar 

  140. Yan K, Deng X, Zhai X, Zhou M, Jia X, Luo L et al (2012) p38 Mitogen-activated protein kinase and liver X receptor-α mediate the leptin effect on sterol regulatory element binding protein-1c expression in hepatic stellate cells. Mol Med 18(1):10. https://doi.org/10.2119/molmed.2011.00243

    CAS  Article  PubMed  Google Scholar 

  141. Ikejima K, Takei Y, Honda H, Hirose M, Yoshikawa M, Zhang YJ et al (2002) Leptin receptor-mediated signaling regulates hepatic fibrogenesis and remodeling of extracellular matrix in the rat. Gastroenterology 122(5):1399–1410. https://doi.org/10.1053/gast.2002.32995

    CAS  Article  PubMed  Google Scholar 

  142. Imajo K, Fujita K, Yoneda M, Nozaki Y, Ogawa Y, Shinohara Y et al (2012) Hyperresponsivity to low-dose endotoxin during progression to nonalcoholic steatohepatitis is regulated by leptin-mediated signaling. Cell Metab 16(1):44–54. https://doi.org/10.1016/j.cmet.2012.05.012

    CAS  Article  PubMed  Google Scholar 

  143. Leclercq IA, Farrell GC, Schriemer R, Robertson GR (2002) Leptin is essential for the hepatic fibrogenic response to chronic liver injury. J Hepatol 37(2):206–213. https://doi.org/10.1016/s0168-8278(02)00102-2

    CAS  Article  PubMed  Google Scholar 

  144. Rodríguez AJ, Neeman T, Giles AG, Mastronardi CA, Paz-Filho G (2014) Leptin replacement therapy for the treatment of non-HAART associated lipodystrophy syndromes: a meta-analysis into the effects of leptin on metabolic and hepatic endpoints. Arq Bras Endocrinol 58(8):783–797. https://doi.org/10.1590/0004-2730000003174

    Article  Google Scholar 

  145. Paz-Filho G, Mastronardi C, Wong M-L, Licinio J. (2012) Leptin therapy, insulin sensitivity, and glucose homeostasis. Indian J Endocrinol Metab 16(Suppl 3):S549. oi: https://doi.org/10.4103/2230-8210.105571

  146. Brown RJ, Oral EA, Cochran E et al (2018) Long-term effectiveness and safety of metreleptin in the treatment of patients with generalized lipodystrophy. Endocrine 60(3):479–489. https://doi.org/10.1007/s12020-018-1589-1

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  147. Akinci B, Subauste A, Ajluni N, et al. (2021) Metreleptin therapy for nonalcoholic steatohepatitis: open-label therapy interventions in two different clinical settings; 2(7):814–835. doi:https://doi.org/10.1016/j.medj.2021.04.001

  148. Heiker JT, Kosel D, Beck-Sickinger AG (2010) Molecular mechanisms of signal transduction via adiponectin and adiponectin receptors. Biol Chem 391(9):1005–1018. https://doi.org/10.1515/BC.2010.104

    CAS  Article  PubMed  Google Scholar 

  149. Hui JM, Hodge A, Farrell GC, Kench JG, Kriketos A, George J (2004) Beyond insulin resistance in NASH: TNF-α or adiponectin? Hepatology 40(1):46–54. https://doi.org/10.1002/hep.20280

    CAS  Article  PubMed  Google Scholar 

  150. Zhou YJ, Zhang ZS, Nie YQ, Cao J, Cao CY, Li YY (2015) Association of adiponectin gene variation with progression of nonalcoholic fatty liver disease: a 4-year follow-up survey. J Dig Dis 16(10):601–609. https://doi.org/10.1111/1751-2980.12288

    CAS  Article  PubMed  Google Scholar 

  151. Polyzos SA, Toulis KA, Goulis DG, Zavos C, Kountouras J (2011) Serum total adiponectin in nonalcoholic fatty liver disease: a systematic review and meta-analysis. Metabolism 60(3):313–326. https://doi.org/10.1016/j.metabol.2010.09.003

    CAS  Article  PubMed  Google Scholar 

  152. Della TS (2020) Non-alcoholic fatty liver disease as a canonical example of metabolic inflammatory-based liver disease showing a sex-specific prevalence: relevance of estrogen signaling. Front Endocrinol (Lausanne) 11:572490. https://doi.org/10.3389/fendo.2020.572490

    Article  Google Scholar 

  153. Mendelsohn ME, Karas RH (2010) The protective effects of estrogen on the cardiovascular system. Mech Dis 340(23):1801–1811. https://doi.org/10.1056/NEJM199906103402306

    Article  Google Scholar 

  154. Gutierrez-Grobe Y, Ponciano-Rodríguez G, Ramos MH, Uribe M, Méndez-Sánchez N (2010) Prevalence of non alcoholic fatty liver disease in premenopausal, posmenopausal and polycystic ovary syndrome women The role of estrogens. Ann Hepatol 9(4):402–409. https://doi.org/10.1016/S1665-2681(19)31616-3

    Article  PubMed  Google Scholar 

  155. D’Eon TM, Souza SC, Aronovitz M, Obin MS, Fried SK, Greenberg AS (2005) Estrogen regulation of adiposity and fuel partitioning: evidence of genomic and non-genomic regulation of lipogenic and oxidative pathways. J Biol Chem 280(43):35983–35991. https://doi.org/10.1074/jbc.M507339200

    CAS  Article  PubMed  Google Scholar 

  156. Paquette A, Shinoda M, Lhoret RR, Prud’homme D, Lavoie JM. (2007) Time course of liver lipid infiltration in ovariectomized rats: impact of a high-fat diet. 58(2):182–90. doi: https://doi.org/10.1016/j.maturitas.2007.08.002

  157. Bruno S, Maisonneuve P, Castellana P, Rotmensz N, Rossi S, Maggioni M et al (2005) Incidence and risk factors for non-alcoholic steatohepatitis: prospective study of 5408 women enrolled in Italian tamoxifen chemoprevention trial. BMJ 330(7497):932. https://doi.org/10.1136/bmj.38391.663287.E0

    Article  PubMed  PubMed Central  Google Scholar 

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SCP: manuscript writing, data analysis, and critical revision; ME: planning and critical revision; NM-S: conceptualization, manuscript design, critical revision, supervision.

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Correspondence to Nahum Mendez-Sanchez.

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Pal, S.C., Eslam, M. & Mendez-Sanchez, N. Detangling the interrelations between MAFLD, insulin resistance, and key hormones. Hormones (2022). https://doi.org/10.1007/s42000-022-00391-w

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Keywords

  • MAFLD
  • Insulin resistance
  • Adipokines
  • Estrogen