“The future is fatty”: so begins a 2013 editorial aimed at clarifying the challenges for an early diagnosis (lifestyle, genetic, imaging) of non-alcoholic fatty liver disease (NAFLD) (1). NAFLD is the most prevalent form of chronic liver disease in the world, frequently associated with obesity, type 2 diabetes mellitus, and insulin resistance (IR) (2).

NAFLD is characterized by an excessive hepatic fat accumulation, often responsible for the onset of IR, and it is defined by the presence of steatosis in >5% of hepatocytes (according to histological analysis), without ethanol consumption. In fact, the diagnosis of NAFLD requires the exclusion of both secondary causes and a daily alcohol consumption greater than P30 g for men and P20 g for women (3).

NAFLD is considered a multifactorial disease, a product of the numerous interactions between environmental factors, nutrition, and genetic factors. The interaction between all these factors is responsible for the disease phenotype and its progression (4, 5).

Given the growing interest of the scientific community on the genetic basis of NAFLD, in recent years, various associations have been described at the genomic level, particularly on some genes, which have improved our knowledge on the genetic basis of NAFLD (5). In fact, it seems that some genetic polymorphisms increase an individual’s susceptibility to environmental factors that, consequently, lead to the development of NAFLD, even in the case of an apparent lack of other risk factors (5). However, recently, the American Association for the Study of Liver Diseases (AASLD) in collaboration with other associations suggested a new nomenclature for steatotic liver disease, particularly the use of metabolic dysfunction-associated steatotic liver disease (MASLD) in place of NAFLD (6). This change has been introduced because several doubts were highlighted regarding the appropriateness of the term “non-alcoholic” that did not express accurately the etiology of the disease (for example, it is well known that there are overlapping biological processes that contribute to both NAFLD and ALD) (6). Moreover, the term “fatty” has been described as stigmatizing (6). Thus, the nomenclature MASLD, defined as the presence of hepatic steatosis associated with one cardiometabolic risk factor and no other discernible cause, has been widely accepted (6).

Since the first genome-wide association study (GWAS) was conducted to evaluate the genetic susceptibility of NAFLD, numerous other candidate gene studies have been conducted (7, 8).

The scientific literature has proposed several genes as both potentially responsible for the onset of this pathology and capable of influencing its natural history: among these, the membrane-bound O-acyl-transferase domain-containing 7 (MBOAT7), patatin-like phospholipase domain-containing 3 (PNPLA3), transmembrane 6 superfamily member 2 (TM6SF2), 17-beta hydroxysteroid dehydrogenase 13 (HSD17B13), and glucokinase regulator (GCKR) would appear to be those of greater interest (9). Further studies have focused on the possible association between increased oxidative stress and the onset of NAFLD (10).

In fact, there is a growing line of evidence that polymorphisms in genes encoding enzymes responsible for xenobiotic metabolism are among the key players in determining interindividual susceptibility to liver-related diseases (6). Oxidative stress and reactive oxygen species (ROS) production have also been widely implicated in the development of NAFLD. ROS production promotes lipid peroxidation, which leads to the formation of extremely reactive aldehyde compounds and the consequent damage at the intracellular level. At the same time, a decrease in antioxidant compounds is observed, such as GSTs, superoxide dismutase, and catalases (6).

Therefore, it can be stated that fatty liver is due to an interplay between genetic and environmental factors, with a major role played by oxidative stress.

In oxidative stress, many xenobiotic agents are metabolized by enzymes of both “phase I,” leading to the formation of procarcinogenic substances through oxidative reactions, and “phase II,” where metabolic intermediate products of the oxidative process are conjugated with endogenous mediators, leading to the production of hydrophilic products that can be easily excreted by the organism. GST is an example of a heterogeneous group of “phase II” enzymes (10).

GSTs are ubiquitous enzymes that catalyze the conjugation of reduced glutathione to electrophilic centers of various exogenous and endogenous substrates (xenobiotics, drugs, poisons, and ROS). Their importance in the human antioxidant system is confirmed by the significantly increased risk of oxidative stress‐related diseases in subjects bearing a “NULL” genotype for specific GST isoforms (i.e., homozygosity for genetic deletion), resulting in the lack of phenotypic expression of the corresponding enzyme (11, 12).

In humans, seven different isoforms of this enzyme have been found (α, ξ, μ, π, θ, σ, ω). Among these, GST-M1 falls into the μ class, while and GST-T1 falls into the θ class (13).

It is known that these genes can be affected by several mutations, capable of determining either a functional reduction or a complete absence of the related protein (14).

Numerous studies have also demonstrated that the functional alteration of the proteins encoded by the aforementioned genes renders their detoxification capacity ineffective, increasing oxidative stress (15). In fact, the “NULL” genotypes of GST-M1 and GST-T1 have been associated with an increased risk of developing several pathologies, including NAFLD, type 2 diabetes, and drug-induced hepatotoxicity (15).

Furthermore, literature data indicate geographic and ethnic variations in the frequency distribution of the “NULL” genotypes (12). Recent studies have documented that the percentage of individuals who do not express the enzyme encoded by the GST-M1 polymorphism is significantly higher in Caucasian and Asian populations than in the African population, while the frequency of the “NULL” genotype of the GST-T1 would be in the order of 60% among Asians, 40% among Africans, and approximately 20% among Caucasians (12, 16–18). The detected high frequency of the “NULL” genotype of these genetic polymorphisms (more than 50% for the GST-M1 polymorphism) has also been confirmed by a population study conducted in Eastern Sicily (11, 19).

The study aims to evaluate the relation between the GST-T1 and GST-M1 gene polymorphisms and the presence of NAFLD and to confirm the importance of magnetic resonance imaging-proton density fat fraction (MRI-PDFF) in quantifying liver fat fraction. MRI is considered a “state-of-the-art weapon” to quantify liver steatosis, considering that its reliability is by far better than ultrasonography, being comparable to biopsy.

A group of 117 volunteers were selected from a larger population through the analysis of previously administered short questionnaires: these questionnaires had the aim of selecting “apparently healthy” subjects, i.e., apparently without any risk factors.

In fact, the questionnaire was aimed at obtaining information on eating habits, smoking, lifestyle, professional profile (near and remote pathological history, physiological history, work history), use of drugs, and/or presence of concomitant pathologies, including those with metabolic disorders, ascertained by negative blood tests performed within the previous 3 months. Therefore, all enrolled subjects have a body mass index (BMI) between 18.5 and 24.9 and declare that they do not take drugs for any pathologies. The questionnaire was administered to Caucasian individuals residing in northeastern Sicily.

Both authorizations for the processing of sensitive data and informed consent have been acquired. These subjects then underwent genetic analysis.

A population of 117 apparently healthy volunteers underwent both genetic test for the identification of GST-T1 and GST-M1 gene polymorphisms and MRI exams to evaluate the presence and grade of NAFLD. The subjects were between 27 and 69 years of age, with an average age of 49.98, consisting of 61 men (52.1%) and 56 women (47.9%).

After performing genetic analysis, the following results were obtained: 53 subjects (45.3%) had “NO NULL” GST-T1 polymorphism and 64 (54.7%) had “NULL” GST-T1 polymorphism. Sixty-six subjects (56.4%) had “NO NULL” GST-M1 polymorphism, and 51 (43.6%) had GST-M1 polymorphism ( Figures 1A, B ).

The volunteers subsequently underwent MRI: 28 subjects (23.9%) had no steatosis (steatosis percentage <5%), 64 (54.7%) had mild steatosis (steatosis percentage 6%–33%), and 25 (21.4%) had moderate steatosis (steatosis percentage 34%–66%). No subjects with severe steatosis (>66%) were identified ( Table 1 ). GE T1-weighted in-phase images show loss of hepatic signal on opposed phase images, demonstrating the presence of steatosis ( Figures 2A, B ). However, a quantification of fat fraction is not possible. On the other hand, both spectroscopy and PDFF sequence allow a reliable evaluation of the liver fat fraction. The PDFF sequence allows to evaluate the whole liver ( Figures 3 , 4 ).

The association between the two polymorphism types detected was subsequently evaluated: 33 subjects (28.21%) had a “NULL” genotype for both GST-T1 and GST-M1, 33 (28.21%) had a “NULL” genotype for GST-T1 and “NO NULL” for GST-M1, 19 (16.24%) had a “NO NULL” genotype for GST-T1 and “NULL” for GST-M1, and 35 (29.91%) had a “NO NULL” genotype for both GST-T1 and GST-M1 ( Table 2 ).

Both GST-T1 and GST-M1 “NULL” genotypes show a statistically significant association with the presence of steatosis: for GST-T1, r = 0.258, p = 0.005; for GST-M1, r = 0.260, p = 0.005 ( Tables 3A, B ). A high statistically significant association between the GST-M1 “NULL” genotype and a higher grade of steatosis (moderate steatosis, 34%–66%) (r = 0.362, p < 0.001) was found. Therefore, subjects with GST-M1 “NULL” have a greater probability of developing not only steatosis but also a higher steatosis grade. On the other hand, no statistically significant association between the presence of the “NULL” GST-T1 genotype and the steatosis grade was found. In fact, the ordinal logistic regression model allowed to highlight that both the GST-M1 “NULL” and the GST-T1 “NULL” genotypes were associated with a greater probability of developing steatosis: in particular, the GST-M1 “NULL” genotype was associated with a greater risk (p = <0.001) of developing a higher grade of steatosis than the GST-T1 “NULL” genotype (p = 0.039) ( Figures 5A, B ; Table 4 ).

Age appeared inversely related to the GST-T1 “NULL” genotype (r = −0.216, p = 0.019) ( Table 3B ); therefore, the risk of developing hepatic steatosis in early age was higher in subjects with the GST-T1 “NULL” genotype (p = 0.019) than in those with the GST-M1 “NULL” genotype (p = 0.073), leading to consider it as a risk factor for the onset of NAFLD. No statistically significant correlations between the “NULL” genotype and sex were detected.

The results are to be considered expected given that the trend of the “NULL” polymorphism does not present any evidence of gender in the relevant literature. The particular distribution of the enzymatic polymorphism is a geographical one.

NAFLD is considered a complex disease resulting from the interactions between the environment and the different genetic profiles of each individual, which makes them susceptible to develop the disease and to influence its progression. In recent years, we have witnessed multiple genome-wide associations, which have then enriched our knowledge on the genetic basis of NAFLD (6, 20, 21).

Furthermore, more recently, direct evaluation of hepatic fat fraction by MRI led to an estimated heritability of NAFLD in the general population at approximately 52% (22, 23).

In the conducted study, 117 healthy subjects with no risk factors and appropriately selected from the general population using specific questionnaires were enrolled. Genetic analysis was carried out to identify the presence of GST-T1 and GST-M1 “NULL” and “NO NULL” polymorphisms. Subsequent MRI examination to evaluate the grade of steatosis was performed. These analyses were performed to evaluate any correlation between the aforementioned gene polymorphism and NAFLD.

In recent years, in the literature, increasing importance in the possible pathogenesis of NAFLD is attributed to the loss of function of some genes, including those encoding for both phase I and phase II metabolic enzymes, as GST families (24–26). In this perspective, oxidative stress is considered to play a key role in determining liver injury, leading to cell damage and then progression in NAFLD (27). Oxidative stress is due to the production of ROS during metabolic processes: ROS accumulation is usually prevented by the action of antioxidant systems; therefore, their malfunction can lead to its progressive increase (28, 29). At high concentrations, ROS can determine oxidative modifications of cellular macromolecules, such as lipids, resulting in their accumulation into hepatocytes. ROS promotes lipid peroxidation, causing the formation of extremely reactive aldehyde compounds and damage at the intracellular level (30). Thus, one of the mechanisms by which ROS could lead to NAFLD onset and progression may be related to indiscriminate oxidative biomolecular damage although specific molecular pathways are not yet clearly defined (31).

Despite that, various other mechanisms have been reported to cause lipid peroxidation: pro-oxidant systems, such as cytochrome P450, lipoxygenase, and cyclooxygenase, have been solely or synergistically implicated in the emergence of OxS in NAFLD (26).

Since GST enzymes intervene in ROS catabolism and detoxification processes, a reduction in their functionality can determine their increase, potentially predisposing to the onset of NAFLD (26).

MRI is considered a non-invasive method for the evaluation of intrahepatic fat accumulation and then steatosis grade (32, 33).

Steatosis is typically graded on a 0–3 scale based on the number of cells with intracellular vacuoles of fat: grade 0 (normal) = up to 5% of cells affected; grade 1 (mild) = 5% to 33% of cells affected; grade 2 (moderate) = 34% to 66% of cells affected; and grade 3 (severe) = 67% or greater of cells affected (34). MRI exploits the difference in the resonance frequencies between water and fat proton signals. By acquiring the images at echo times in which water and fat signals are approximately in-phase (W+F) and opposed phase (W−F), volumetric liver fat detection is possible according to the relative signal loss on opposed-phase (also known as “out-of-phase”) images (35). Echo times for in-phase and opposed-phase imaging are based on the relative chemical shift between water and the methylene peak (–CH₂) of fat (35). At 1.5 T and normal body temperature, this peak resonates approximately at −217 Hz, being slower than water (−434 Hz at 3.0 T) (35).

Unlike CT, where the pixel value directly reflects X-ray attenuation (in Hounsfield units), the signal intensity in MR images is arbitrary and depends on the receiver gain and the sensitivity of received RF coils. Fat signal fraction (η) can be calculated as

where W and F are the signal contributions from water and fat (35).

An attractive approach to create a PDFF map is to use a chemical shift based on the “water–fat separation method” that allows to separate the signal of both water and fat into water-only and fat-only images (36). Both the accurate separation of the signal of fat mobile protons from other mobile protons (i.e., water) and the correction for all those factors that influence MR signal intensity permit the calculation of PDFF: PDFF is defined as the density of hydrogen protons attributable to fat. To provide an accurate estimation of PDFF, the following five confounders must be evaluated: −T1 bias, −T2* decay, −spectral complexity of fat, −noise bias, and −eddy currents (36). After running the fix for the above five confounding factors, the fat-signal fraction and the PDFF are equivalent.

The right fat quantification techniques can be distinguished into two categories:

Although it is not possible to identify a threshold that allows to distinguish normal conditions from pathological ones, today, a reference threshold value of the fat fraction of 5.56% is commonly used (39).

The use of MRI as a quantitative biomarker of intracellular liver fat has shown tremendous progress in recent years and holds great promise to provide a cost-effective, accessible, and accurate evaluation of such a widespread disease (40, 41). Furthermore, MRI allows the acquisition of data comparable to those of conventional biopsy; however, it enables the entire liver parenchyma to be visualized, whereas only a small part is taken for histological examination.

In this study, MRI-PDFF has been used to detect the presence of hepatic steatosis in healthy subjects, apparently without any risk factors. Genetic analyses were conducted to identify “NULL” mutations of the GST-T1 and GST-M1 genes, evaluating their possible role in the genesis of NAFLD. As mentioned, these enzymes intervene in the catabolism processes of ROS; therefore, their loss of function (“NULL” genotype) is able to determine an increase in oxidative stress: ROS has been reported to cause lipid peroxidation, predisposing to the onset of NAFLD itself (41).

Four groups of cytological GSTs have been identified in humans, classified with the Greek letters alpha (α), mu (µ), pi (π), and theta (θ), and defined based on their isoelectric point (40). Four gene sequences were investigated for these enzymes: GSTA (GSTα), located on chromosome 6; GSTM (GSTµ), located on chromosome 1; GSTP (GSTπ), located on chromosome 11; and GSTT (GSTθ), located on chromosome 22. Several studies have described the specific structure, enzymology, and affinity of the tissue and gender of GST-M and GST-T polymorphisms (42). The enzymatic chains encoded by GST-M1 polymorphism are expressed by hepatic, gastric, and nervous systems, while the enzymatic chains encoded by GST-M2 and GST-M5 polymorphisms are expressed by extrahepatic tissues and synthesized by other cell lines (43).

The genetic polymorphisms GST-T1 and GST-T2 are located in the same region on chromosome 22, and the related enzyme chains are mainly expressed in the liver (44).

The genetic polymorphism GST-M1 can be typed by highlighting three allelic forms: GST-M1*0, GST-M1*A, and GST-M1*B. The GST-M1*0 allele (homozygous null) indicates a total deletion of the gene tract with a consequent lack of expression, at the cellular level, of the related enzyme chains (44). Alleles GST-M1*A and GST-M1*B differ from each other for a single base at the level of exon 7 and encode for protein monomers that constitute the functionally active isoform of the enzyme. It is also important to highlight that approximately 50% of the Caucasian population does not express the enzyme in relation to the gene deletion which, in homozygosity, gives rise to the GST-M1*0/*0 genotype (45). Another significant deletion is expressed at the level of the GST-T1 polymorphism; the null genotype of GST-T1 is expressed in approximately 15% of the Caucasian population and in approximately 60% of the Chinese and Korean populations (46).

According to the role played by these enzymes in the biotransformation of endogenous and exogenous toxicants, including carcinogens (for example, polycyclic aromatic hydrocarbons, PAHs), pollutants, alcohol, drugs, and other xenobiotic agents, it is probable that they play an important role even on the onset of pathologies widely spread in the general population, such as NAFLD (45, 46). The main mechanism appears to be related to the increase in oxidative stress and its consequences (46).

The “NULL” GST-T1 polymorphism has been associated with higher TNF-α concentration when compared with the “NO NULL” polymorphism; thus, it could indicate activation of the proinflammatory segment of the cytokine profile and inflammatory processes (47). Noteworthily, TNF-α is considered to play a pivotal role in those mechanisms leading to IR, inflammation, and apoptosis in the case of NAFLD; thus, its elevated level has been considered a predictive factor of NAFLD progression (48). Alterations in the adipokine profile were instead detected in subjects with the GST-M1 “NULL” genotype: leptin plasma levels were significantly higher than in patients with the “NO NULL” genotype. The high leptin level could be related to a high TNF-α concentration, which is capable of stimulating leptin production (49).

Prysyazhnyuk et al. (50) also documented a reduction of restored glutathione in patients with NAFLD and GST-T1 and GST-M1 gene “NULL” polymorphisms. A higher level of reaction products of thiobarbituric acid has also been detected in subjects with the zero genotype of the GST-M1 gene than in those with the functional allele of the gene. Furthermore, Kassab et al. (51) claimed that the “NULL” genotypes of GST-T1 and GST-M1 genes could determine an activity reduction of sulfhydryl binding and then a loss of detoxification body capacity. Despite this, some authors maintained that the presence of the “NULL” polymorphism alone cannot determine a relevant lack of GST isoenzyme synthesis to determine a greater susceptibility to genetic damage (52). In the literature, several studies have evaluated the different distribution of GST-T1 and GST-M1 polymorphisms between subjects with NAFLD and the rest of the general population. Hori et al. (53) conducted a study involving the Japanese population, reporting a higher frequency of the GST-M1 null genotype in NAFLD patients as compared to the control group. Similar results were obtained in the study conducted by Kordi-Tamandani et al. (54). On the other hand, Hori et al. (53) found liver function alterations in the presence of “NULL” GST-T1, GST-P1, and GST-M1 polymorphisms, with the synthesis, detoxification, and excretion parameters altered. No alterations in the lipid profile were found either (53). Different data have been obtained by Maciel et al. (55), who found hypertriglyceridemia in the presence of the aforementioned “NULL” polymorphisms. Furthermore, in agreement with the study of Hori et al., Prysyazhnyuk et al. (56) in a study conducted in Ukraine found a higher prevalence of “NULL” polymorphisms among NAFLD patients than in healthy individuals. Zhu et al. (40) conducted six studies including 700 NAFLD patients and 1,317 controls, aiming at identifying the frequency of GST-M1 gene polymorphism in subjects with NAFLD: it was revealed that GST-M1 is appreciably connected with NAFLD. Similar results have been obtained for GST-T1 “NULL” polymorphism distribution: five studies involving 620 NAFLD and 1,237 healthy subjects found a noticeable association between the SNP of GST-T1 and NAFLD vulnerability. Therefore, these data suggest a significant correlation between GST-M1/T1 “NULL” polymorphisms and the onset of NAFLD. These data are in agreement with the results of our study. Both GST-M1 and GST-T1 showed a higher prevalence in subjects with NAFLD although GST-M1 showed a greater strength of association. Furthermore, the GST-M1 NULL genotype is related to the onset of a higher grade of steatosis. Damavandi et al. (12) analyzed 242 NAFLD patients and 324 healthy controls in the Iranian population, reporting a higher prevalence of the GST-M1 and GST-T1 “NULL” genotypes in the first group. Subjects with those polymorphisms were then considered at a higher risk of developing NAFLD. Another study conducted by Hashemi et al. (6) in the Iranian population on 83 patients with NAFLD and 93 healthy subjects confirmed an increased risk of developing NAFLD in subjects with the GST-M1 “NULL” genotype. On the other hand, the GST-T1 “NULL” polymorphism distribution was not significantly different between NAFLD and control groups. Therefore, this study showed that GST-M1, but not GST-T1, can be considered a risk factor for developing NAFLD. These data disagree with what has been obtained in our study: in fact, although a stronger statistical association was identified between NAFLD and “NULL” GST-M1 polymorphism, also the “NULL” GST-T1 genotype has a statistically significant correlation. Therefore, it could also be considered an NAFLD genetic predisposing factor. The main data are summarized in Table 5 .

Furthermore, the correlation between GST-T1 and GST-M1 “NULL” polymorphisms and the etiopathogenesis of hepatic steatosis can be considered a challenge for forensic genetic laboratories since screening assumes the significance of biomarker of individual susceptibility in genetic predispositions to metabolic diseases especially in those subjects professionally exposed to xenobiotic substances. Genetic analysis could help us to understand some pathological findings in forensic cases in ascertaining the cause of steatosis even in the absence of specific dietary and/or environmental risk factors. Further forensic applications include the study of polymorphisms in association with liver function for those cases in which it is necessary to interpret the degree of drug biotransformation in postmortem toxicological investigations as a contribution to molecular autopsy. Therefore, the identification of genetic biomarkers linked to hepatic steatosis can support more accurate forensic and toxicological evaluations. The biomolecular interest in identifying the causes of hepatic steatosis cannot be overlooked, as this is a pathology of significant social interest for the resulting social security and tertiary protection aspects. Based on what has been described, the analysis of the correlation between the GST-M1 and GST-T1 NULL genotypes and hepatic steatosis would seem promising, and there are several future perspectives related to this area of research: i) the analysis of the role of both oxidative stress and lipid metabolism, ii) the interactions with environmental factors and other polymorphisms, iii) the potential role of GST NULL genotypes as risk factors and early biomarkers for the identification of hepatic steatosis, iv) the possibility of developing tailored prevention interventions based on genetic risk and thus identifying paths for the development of new strategies, and v) reconsidering social security and public protection strategies and the allocation of resources are certainly among the most relevant.

In conclusion, the study conducted by this research group aimed to demonstrate a correlation between the presence of the GST-T1 and GST-M1 “NULL” genotypes and the presence of steatosis. Thanks to the analysis of the collected data, it was possible to identify a statistically significant correlation between the presence of the GST-T1 and GST-M1 “NULL” genotypes and the presence of hepatic steatosis, which is higher for GST-M1 “NULL.” Furthermore, a high statistically significant association between the GST-M1 “NULL” genotype and a higher grade of steatosis was found. In contrast, no statistically significant association between the GST-T1 “NULL” genotype and steatosis grade was identified. It was also possible to underline the importance of MRI-estimated PDFF in the diagnosis of hepatic steatosis: this method allows the acquisition of data comparable to those of conventional biopsy; however, it permits the entire liver parenchyma to be visualized and only a small part is taken for histological examination. Despite this, considering both the stringent exclusion criteria that led to the healthy subjects without risk factors enrolled and the small number of the population analyzed, further studies are required to confirm the data obtained.