Association of PNPLA3 rs738409 C > G and rs2896019 T > G Polymorphisms with Nonalcoholic Fatty Liver Disease in a Turkish Population from Adıyaman Province

Abstract

Objectives:

The purpose of this study was to investigate the effect of patatin-like phospholipase domain-containing protein 3 (PNPLA3) rs738409 C > G and rs2896019 T > G polymorphisms on genetic susceptibility to nonalcoholic fatty liver disease (NAFLD) in a Turkish population from Adıyaman province, located in the Southeast Anatolia Region of Turkey.

Materials and Methods:

This hospital-based molecular epidemiological case-control study analyzed the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms in 335 NAFLD cases and 410 healthy controls. Genotype frequencies were determined using real-time polymerase chain reaction with the TaqMan assay. The association with NAFLD susceptibility was evaluated by calculating odds ratios (ORs) and 95% confidence intervals (CIs) using an unconditional logistic regression model.

Results:

We found that the PNPLA3 rs738409 C > G (CC vs. GG: OR = 1.90, 95% CI = 1.05-3.44) and rs2896019 T > G (TT vs. GG: OR = 3.24, 95% CI = 1.44-7.27) polymorphisms were linked to an increased risk of NAFLD in almost all genetic models (p < 0.05). In addition, the PNPLA3 Grs738409/Grs2896019 haplotype was associated with NAFLD development (p < 0.05). Significant differences in alanine aminotransferase and aspartate aminotransferase enzyme levels were observed across the genotypes of these polymorphisms (p < 0.05).

Conclusion:

This is the first study on PNPLA3 single nucleotide polymorphisms (SNPs) and NAFLD in the Turkish population of Adıyaman Province, Southeast Anatolia. Our findings suggest that the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms, along with their haplotypes, may influence NAFLD susceptibility. Further independent studies with larger sample sizes and diverse populations are needed to confirm these results.

Introduction

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide, affecting approximately 38% of adults (Younossi et al., 2023). It is characterized by excessive fat accumulation in liver cells without significant alcohol consumption or other known causes of liver damage (Younossi et al., 2023; Ye et al., 2020; Diehl and Day, 2017). NAFLD encompasses a spectrum of conditions, ranging from simple steatosis to nonalcoholic steatohepatitis, which can progress to hepatic fibrosis, cirrhosis, and hepatocellular carcinoma (Diehl and Day, 2017). The development and progression of NAFLD are influenced by a complex interplay of genetic predisposition, metabolic dysfunction, and environmental factors (Diehl and Day, 2017; Younossi, 2019). Several risk factors, including ethnicity, diet, metabolic status, immune responses, and gut microbiota composition, contribute to individual variability in disease susceptibility and severity (Diehl and Day, 2017; Younossi, 2019; Buzzetti et al., 2016). Recent genome-wide association studies have identified several genetic polymorphisms linked to NAFLD susceptibility (Lee et al., 2024; Anstee et al., 2020; Park et al., 2020; Namjou et al., 2019), highlighting the role of genetic and epigenetic factors in the disease’s pathogenesis. This underscores the need for further investigation into their contribution to NAFLD progression and severity across various populations.

The human genome encodes nine patatin-like phospholipase domain-containing proteins (PNPLA1-9), which play critical roles in lipid metabolism, membrane integrity, and energy regulation (Baulande et al., 2001; Wilson et al., 2006; Kienesberger et al., 2009). Among them, PNPLA3, also known as adiponutrin, is a lipoatrophic transmembrane protein composed of 481 amino acids (Kienesberger et al., 2009; Bruschi et al., 2017). It is primarily expressed in hepatocytes, hepatic stellate cells, adipocytes, and skin, with its expression regulated by nutritional status (Bruschi et al., 2017). Functionally, PNPLA3 acts as an enzyme with triacylglycerol hydrolase (catabolic lipase) activity on triglycerides and retinyl esters, as well as acylglycerol transacylase (anabolic lipogenic) activity on phospholipids (Bruschi et al., 2017; Kumari et al., 2012). Located on chromosome 22 (22q13.31), the PNPLA3 rs738409 C > G single nucleotide polymorphism (SNP) causes an isoleucine-to-methionine substitution at position 148 (p.I148M), which reduces the protein’s functionality (Bruschi et al., 2017; Dong, 2019). This polymorphism is linked to increased liver fat content and liver inflammation (Romeo et al., 2008). The G allele of rs738409 C > G is associated with a higher risk of steatosis, lobular inflammation, and hepatocyte ballooning through lipid reprogramming, characterized by triglyceride accumulation, polyunsaturated fatty acid depletion, and activation of inflammatory pathways via STAT3 (Romeo et al., 2008; Sookoian and Pirola, 2011; Ruhanen et al., 2014). In addition, along with rs738409, the rs2896019 T > G polymorphism, located in the intronic region of the PNPLA3 gene, has a strong association with NAFLD (Stasinou et al., 2022). The rs2896019 polymorphism (TG genotype) shows a significant correlation with the rs738409 polymorphism (CG and GG genotypes) (Njei et al., 2024; Stasinou et al., 2022). In patients with hepatic steatosis, the frequency of the rs2896019 polymorphism (TG + GG) is significantly high, up to 46.6% (Stasinou et al., 2022). Several studies have explored the association of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms with NAFLD in the Turkish population (Islek et al., 2014; Uygun et al., 2017; Idilman et al., 2020; Delik et al., 2020; Akkiz et al., 2021; Demirtas et al., 2024; Husseini, 2024), but the relationship remains unclear. Notably, none of these studies has been conducted in populations from the Southeastern Anatolia Region of Turkey (Islek et al., 2014; Uygun et al., 2017; Idilman et al., 2020; Delik et al., 2020; Akkiz et al., 2021; Demirtas et al., 2024; Husseini, 2024). Despite the high prevalence of NAFLD in the Turkish population, the relationship between PNPLA3 polymorphisms and NAFLD, particularly in Southeastern Anatolia, remains unclear due to a lack of studies (Değertekin et al., 2021). Given the significant disease burden in the region, the crucial role of the PNPLA3 gene in liver lipid metabolism, and the relevance of the respective polymorphisms within PNPLA3, this study aims to evaluate the prevalence of the rs738409 C > G and rs2896019 T > G polymorphisms and examine their association with NAFLD susceptibility in the Adıyaman population of Turkey.

Materials and Methods

Study population and setting

We conducted a hospital-based molecular epidemiological case-control study in Adıyaman Province, located in the Southeastern Anatolia Region of Turkey, using real-time polymerase chain reaction (PCR) with the TaqMan assay. NAFLD patients were diagnosed using established criteria based on liver ultrasonography (Brunt et al., 1999; Zeng et al., 2008). The characteristic ultrasound pattern for fatty liver disease shows a “bright” liver with increased brightness and posterior attenuation. This pattern features stronger echoes in the hepatic parenchyma compared with the renal parenchyma, along with vessel blurring and narrowing of the hepatic vein lumens, with no signs of other chronic liver diseases. Participants with secondary causes of steatosis were excluded from the study. These included alcohol abuse within the past year (defined as weekly ethanol consumption of ≥140 g for men and ≥70 g for women), total parenteral nutrition, hepatitis B and C infections, and the use of medications known to induce steatosis. Additional exclusions included patients with autoimmune hepatitis, drug-induced liver disease, primary biliary cirrhosis, and primary sclerosing cholangitis. The controls, with no steatosis confirmed by ultrasonography, were recruited from the same hospital during the study period. In addition to ultrasound examination, the absence of NAFLD in the control group was confirmed based on normal liver enzyme levels (alanine aminotransferase [ALT], aspartate transaminase [AST], gamma-glutamyl transpeptidase [GGT], alkaline phosphatase [ALP]) and metabolic parameters, including fasting glucose and lipid profile (total cholesterol, triglycerides, high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]). Controls had no history of metabolic syndrome, diabetes, obesity, or other risk factors associated with NAFLD. These controls were frequency matched to patients with NAFLD by sex, age (in 5-year intervals), and residential area. Two experienced physicians performed real-time ultrasonographic examinations of the upper abdominal organs using a 3.5-MHz transducer scanner (Siemens Adama, Erlangen, Germany). The physicians were not informed about the specifics of the study while conducting the ultrasounds. All subjects meeting the inclusion criteria were randomly sampled in both the case and control groups until the required sample size was reached or exceeded. Our study included 335 individuals with NAFLD and 410 controls.

Ethics committee approval

The study received ethical approval from the Non-Interventional Clinical Research Ethics Committee of the Faculty of Medicine, Adıyaman University (approval number 2022/03-2, approval date: March 26, 2022). All participants, including patients and controls from the Adıyaman Province, Southeast Anatolia, provided written informed consent to participate in the study and allow the use of their blood samples for genotyping. The study was conducted in accordance with the principles of the Declaration of Helsinki. Demographic and clinical information from both groups of participants was gathered by physicians through a structured questionnaire. Detailed data for individuals in both groups are presented in Table 1.

Table 1.

Demographic, Clinical, and Biochemical Profiles of Nonalcoholic Fatty Liver Disease Cases and the Control Groups

Characteristics	Healthy controls (n = 410)	NAFLD (n = 335)	p
Age (years, mean ± SD)	45.25 ± 16.17	45.33 ± 13.75	> 0.05
Gender			> 0.05
Males	209 (51.0%	145 (43.3%)
Females	201 (49.0%)	190 (56.7%)
Systolic blood pressure (mm Hg)	123.2 ± 14.80	126.4 ± 6.6	> 0.05
Diastolic blood pressure (mm Hg	70.4 ± 8.50	76.5 ± 10.4	> 0.05
BMI (kg/m²)	25.63 ± 2.29	30.25 ± 0.29	< 0.05
Fasting glucose (mg/dl)	99.31 ± 27.97	116.99 ± 47.75	< 0.05
HbA1c (%)	5,65 ± 1.01	6,24 ± 1,43	< 0.05
ALT (IU/l)	20,29 ± 11.23	61.71 ± 26.63	< 0.05
AST (IU/l)	19.34 ± 6,98	42.53 ± 16.33	< 0.05
GGT (mU/mL)	25.23 ± 21.33	38.09 ± 32.10	< 0.05
ALP (mU/mL)	75.11 ± 26.72	80.89 ± 29.64	0.068
Total cholesterol (mg/dL)	182.45 ± 21.68	202.46 ± 35.36	< 0.05
Triglycerides (mg/dL)	123.86 ± 51.61	168.26 ± 78.50	< 0.05
HDL cholesterol (mg/dL)	52.62 ± 13.68	40.05 ± 9.18	< 0.05
LDL cholesterol (mg/dL)	108.20 ± 20.87	131.43 ± 30.87	< 0.05

BMI, body mass index; HbA1c, hemoglobin A1c; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, gamma-glutamyl transpeptidase; ALP, alkaline phosphatase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NAFLD, nonalcoholic fatty liver disease.

Assessment of physical, anthropometric, and biochemical parameters

Each participant completed a comprehensive physical examination in the morning following an overnight fast. This examination included anthropometric measurements, a health behavior questionnaire, and biochemical tests. Body mass index (BMI) was calculated as follows: BMI = weight (kg)/height squared (m²). After the anthropometric examination, venous blood samples were taken. Standard clinical laboratory techniques were used to measure blood glucose, hemoglobin A1c (HbA1c), ALT, AST, GGT, ALP, total cholesterol, triglycerides, HDL-C, and LDL-C (Table 1).

Genomic DNA isolation

The researchers conducting the laboratory studies were kept unaware of the identities and conditions of the subjects in both the patient and control groups, as all blood samples were processed and anonymized in accordance with ethical and legal standards. Whole blood samples from all participants in both groups were collected in Vacutainer tubes with ethylenediaminetetraacetic acid and stored at −80°C until genomic DNA (gDNA) isolation. gDNA was then extracted from peripheral blood mononuclear cells of all participants using the High Pure PCR Template Preparation Kit, in accordance with the manufacturer’s instructions. The concentration and purity of the gDNA were assessed with a Qubit® fluorometer (Invitrogen, Carlsbad, CA, USA).

Genotyping of PNPLA3 (rs738409 C > G and rs2896019 T > G) polymorphisms

Genotyping of both PNPLA3 polymorphisms (rs738409 C > G and rs2896019 T > G) was performed using the TaqMan allelic discrimination kits, C__7241_10 and C__1840500_10 (Thermo Fisher Scientific Inc., Waltham, MA), obtained commercially, in accordance with the manufacturer’s instructions. Real-time PCR was conducted using the LightCycler 96 system (Roche Diagnostics GmbH, Mannheim) with the following standard cycling conditions: an initial 10-min step at 95°C, followed by 40 cycles of 15 s at 95°C and 1 min at 60°C. Genotyping for each subject in both groups was automatically determined using the LightCycler Genotyping software (Roche Diagnostics GmbH, Mannheim). For each subject, real-time PCRs were carried out in a final volume of 10 μL, consisting of 5 μL of 2× TaqMan® Mix (Thermo Fisher Scientific Inc., Waltham, MA), 900 nM of each primer (Thermo Fisher Scientific Inc., Waltham, MA), 200 nM of every probe (Thermo Fisher Scientific Inc., Waltham, MA), and about 10 ng of gDNA. The sequence context for each PNPLA3 polymorphism is as follows: the rs738409 C > G polymorphism (VIC/FAM) is described in the 5′→3′ direction as AGGCCTTGGTATGTTCCTGCTTCAT[C/G]CCCTTCTACAGTGGCCTTATCCCTC, and the rs2896019 T > G polymorphism (VIC/FAM) as TGAACCTCCATCGAATGGTGCTGTA[G/T]TTTATAATGTCATCAAATATCAAAT. To ensure quality control, genotyping was performed blinded to the case-control status of the participants. Furthermore, 15% of participants from each group underwent genotyping on two separate occasions by different researchers, achieving complete reproducibility.

Data analysis

Data processing, management, and statistical analyses of the data obtained during the study’s data collection phase were conducted using the Statistical Package for Social Sciences version 25.0 (SPSS 25.0) software package (IBM Corp. 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.). To assess the variations in demographic and clinical characteristics, as well as the genotype and allele distributions of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms between the two groups, we used Student’s t-test, one-way analysis of variance, and Pearson’s chi-squared (χ²) test. To test whether the observed and expected genotype frequencies of the PNPLA3 polymorphisms (rs738409 C > G and rs2896019 T > G) in the control group were in the Hardy-Weinberg equilibrium (HWE), Michael H. Court’s (2005-2008) Excel-based HWE test online calculator (https://accounts.smccd.edu/case/biol215/docs/HW_calculator.xls) was used. The associations between the PNPLA3 polymorphisms (rs738409 C > G and rs2896019 T > G) and NAFLD risk, along with haplotype estimation, corresponding odds ratios (ORs) and 95% confidence intervals (CIs), and linkage disequilibrium, were investigated with the SNPStats online tool: https://www.snpstats.net/start.htm (Solé et al., 2006). To evaluate the potential influence of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms on NAFLD susceptibility, ORs and 95% CIs were determined. This was done using an unconditional logistic regression model, incorporating log-additive, overdominant, recessive, dominant, codominant, and allele inheritance models. Akaike’s information criterion and Bayesian information criterion were used to select the best-fitting inheritance model for the logistic regression data. A two-sided p value of <0.05 was considered statistically significant.

Power calculations

The power of association studies depends on sample size, the specified level of type I error, and genotype frequencies in cases and controls. The power of association studies is influenced by factors such as sample size, the specified level of type I error, and genotype frequencies in both cases and controls. These genotype frequencies are determined by the population frequency of the allele of interest and its impact on disease susceptibility. Power analysis calculations were conducted before the initiation of the hospital-based molecular epidemiological case-control study using version 1.2.4 of Quanto software (https://keck.usc.edu/biostatistics/software/) (Gauderman and Morrison, 2006). The required sample size to achieve 80% power was calculated using the minor allele frequencies of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms, as reported in the database of PubMed SNPs (http://www.ncbi.nlm.nih.gov/snp/). The results indicated a power of over 90% for the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms under the dominant model, based on the allele frequencies and sample size available in this study.

Results

Characteristic of the study population

Clinical features, anthropometric variables, and laboratory findings at the time of diagnosis for the 335 subjects with NAFLD and the 410 control subjects are presented in Table 1. No significant differences were observed in the age and sex distributions between the NAFLD cases and control subjects (p > 0.05), indicating that the demographic matching was adequate. Compared with control subjects, patients with NAFLD had significantly higher levels of systolic blood pressure, diastolic blood pressure, BMI, fasting glucose, HbA1c, ALT, AST, GGT, ALP, total cholesterol, triglycerides, HDL-C, and LDL-C (p < 0.05) (Table 1).

The effects of PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms on NAFLD susceptibility risk

The allele and genotype frequencies of the PNPLA3 polymorphisms (rs738409 C > G and rs2896019 T > G) were determined in both NAFLD patients and control groups, and these frequency distribution data are presented in Table 2. It was found that both PNPLA3 rs738409 C > G (χ² = 0.15, p > 0.05) and PNPLA3 rs2896019 T > G (χ² = 0.95, p > 0.05) polymorphisms in the control group were in accordance with the HWE. As shown in Table 2, statistically significant associations were found for the PNPLA3 rs738409 C > G polymorphism in all inheritance models except the recessive model. The genetic models in which statistically significant associations were found are as follows: in allele (C vs. G: OR = 1.44, 95% CI = 1.14-1.82, p = 0.002), codominant (CC vs. CG: OR = 1.50, 95% CI = 1.11-2.04, p = 0.009; CC vs. GG: OR = 1.90, 95% CI = 1.05-3.44, p = 0.033), dominant (CC vs. CG + GG: OR = 1.56, 95% CI = 1.16-2.09, p = 0.003), overdominant (CC + GG vs. CG: OR = 1.40, 95% CI = 1.04-1.89, p = 0.026), and log-additive (OR = 1.44, 95% CI = 1.14-1.82, p = 0.002) patterns of inheritance (Table 2). Based on Akaike’s and Bayesian information criteria, the log-additive model was the best fit for the PNPLA3 rs738409 C > G polymorphism (Table 2).

Table 2.

Allele and Genotype Frequencies in the Nonalcoholic Fatty Liver Disease Cases and the Control Groups As Well As Association of PNPLA3 rs738409 C > G and rs2896019 T > G Polymorphisms with the Risk of Nonalcoholic Fatty Liver Disease Susceptibility According to Different Models of Inheritance

	Healthy controls n = 410 (%)	NAFLD casesn = 335 (%)	OR (95% CI)	p Value^a	AIC^b	BIC^c
PNPLA3 rs738409 C > G
Allele
C	636 (77.0%)	473 (71.0%)	1.00 (Reference)
G	184 (23.0%)	197 (29.0%)	1.44 (1.14-1.82)	0.002
Codominant
CC	248 (60.5%)	166 (49.5%)	1.00 (Reference)		1021.7	1035.6
CG	140 (34.1%)	141 (42.1%)	1.50 (1.11-2.04)	0.009
GG	22 (5.4%)	28 (8.4%)	1.90 (1.05-3.44)	0.033
Dominant
CC	248 (60.5%)	166 (49.5%)	1.00 (Reference)		1020.3	1029.5
CG + GG	162 (39.5%)	169 (50.5%)	1.56 (1.16-2.09)	0.003
Recessive
CC + CG	388 (94.6%)	307 (91.6%)	1.00 (Reference)		1026.6	1035.8
GG	22 (5.4%)	28 (8.4%)	1.61 (0.90-2.87)	0.11
Overdominant
CC+GG	270 (65.8%)	194 (57.9%)	1.00 (Reference)		1024.3	1033.5
CG	140 (34.1%)	141 (42.1%)	1.40 (1.04-1.89)	0.026
Log-additive	—	—	1.44 (1.14-1.82)	0.002	1019.9	1029.1
PNPLA3 rs2896019 T > G
Allele
T	681 (83.0%)	507 (76.0%)	1.00 (Reference)
G	139 (17.0%)	163 (24.0%)	1.58 (1.22-2.03)	0.0001
Codominant
TT	280 (68.3%)	192 (57.3%)	1.00 (Reference)		1018.0	1031.8
TG	121 (29.5%)	123 (36.7%)	1.48 (1.09-2.02)	0.013
GG	9 (2.2%)	20 (6%)	3.24 (1.44-7.27)	0.004
Dominant
TT	280 (68.3%)	192 (57.3%)	1.00 (Reference)		1019.7	1028.9
TG + GG	130 (31.7%)	143 (42.7%)	1.60 (1.19-2.17)	0.002
Recessive
TT + TG	401 (97.8%)	315 (94%)	1.00 (Reference)		1022.2	1031.4
GG	9 (2.2%)	20 (6%)	2.83 (1.27-6.30)	0.008
Overdominant
TT + TG	289 (70.5%)	212 (63.3%)	1.00 (Reference)		1024.9	1034.1
GG	121 (29.5%)	123 (36.7%)	1.39 (1.02-1.88)	0.037
Log-additive	—	—	1.59 (1.23-2.06)	0.0003	1016.6	1025.9

Data were calculated by logistic regression analysis.

AIC: Akaike’s information criterion.

BIC: Bayesian information criterion.

In the PNPLA3 rs2896019 T > G polymorphism, statistically significant associations were found in allele (T vs. G: OR = 1.58, 95% CI = 1.22-2.03, p = 0.0001), codominant (TT vs. TG: OR = 1.48, 95% CI = 1.09-2.02, p = 0.013; TT vs. GG: OR = 3.24, 95% CI = 1.44-7.27, p = 0.004), dominant (TT vs. TG + GG: OR = 1.60, 95% CI = 1.19-2.17, p = 0.002), recessive (TT+TG vs. GG: OR = 2.83, 95% CI = 1.27-6.30, p = 0.008), overdominant (TT + TG vs. GG: OR = 1.39, 95% CI = 1.02-1.88, p = 0.037), and log-additive (OR = 1.59, 95% CI = 1.23-2.06, p = 0.0003) patterns of inheritance (Table 2). As in the PNPLA3 rs738409 C > G polymorphism, based on Akaike’s and Bayesian information criteria, the log-additive model was the best fit (Table 2).

Analysis of haplotype

Haplotype analysis was used to assess the combined impact of the two PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms on the risk of developing NAFLD. The findings from the haplotype analysis are presented in Table 3. Four haplotypes were identified based on the genotypes observed. A statistically significant difference in the general haplotype frequencies was noted between patients with NAFLD and control subjects (p = 0.0049). The Crs738409/Trs2896019 (ht1) haplotype was the predominant in both patients with NAFLD and control subjects, with frequencies of 0.770 and 0.696, in the same order. Individuals carrying the Grs738409/Grs2896019 (ht2) haplotype had a higher risk of NAFLD susceptibility (OR: 1.59; 95% CI: 1.22-2.07, p = 0.0006). However, no statistically significant difference was found between the other constructed haplotypes and the risk of NAFLD susceptibility (Table 3).

Table 3.

Association of PNPLA3 Haplotypes with the Risk of Nonalcoholic Fatty Liver Disease

Haplotypes	PNPLA3 polymorphisms		Frequency		OR (95% CI)	p Value
Haplotypes	rs738409	rs2896019	Controls subjects	NAFLD subjects	OR (95% CI)	p Value
ht1	C	T	0.770	0.696	1.00 (Reference)	—
ht2	G	G	0.164	0.233	1.59 (1.22-2.07)	0.0006
ht3	G	T	0.060	0.060	1.10 (0.73-1.67)	0.64
ht4	C	G	0.005	0.009	1.96 (0.54-7.08)	0.30

Global haplotype association p value: 0.0049.

OR, odds ratio; CI, confidence interval.

Genotype distribution of PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms with respect to gender and biochemical parameters in NAFLD patients

We demonstrated the association of PNPLA3 rs738409 C > G and rs2896019 T > G polymorphism genotypes with gender and biochemical parameters in Table 4, including fasting glucose, HbA1c, ALT, AST, GGT, ALP, total cholesterol, triglycerides, HDL-C, and LDL-C. The genotype distributions of PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms between genders were found to be statistically insignificant. After adjusting for age and gender, our analyses found no statistically significant differences in the mean values of all biochemical parameters, except for ALT and AST enzymes, across the PNPLA3 rs738409 C > G genotypes. However, it was found that the mean values of HbA1c, ALT, and AST enzymes showed statistically significant differences across the genotypes of the PNPLA3 rs2896019 T > G polymorphism (Table 4).

Table 4.

Gender and Biochemical Parameter Results of Patients with Nonalcoholic Fatty Liver Disease According to the PNPLA3 rs738409 C > G and rs2896019 T > G Polymorphisms

Variables	PNPLA3 rs738409 C > G			p ^a	PNPLA3 rs2896019 T > G			p ^a
Variables	CC	CG	GG	p ^a	TT	TG	GG	p ^a
Gender				> 0.05				> 0.05
Males (n = 145)	67 (40.6%)	63 (44.6%)	15 (51.9%)		81 (42.4%)	52 (42.0%)	12 (57.9%)
Females (n = 190)	99 (59.4%)	78 (55.4%)	13 (48.1%)		111 (57.6%)	71 (58.0%)	8 (42.1%)
Fasting glucose (mg/dl)	111.91 ± 40.93	121.19 ± 51.51	127.85 ± 63.522	0.118	111.13 ± 38.39	124.72 ± 55.65	130.37 ± 71.25	0.025
HbA1c (%)	6.08 ± 1.27	6.43 ± 1.57	6.33 ± 1.52	0.111	6.04 ± 1.27	6.57 ± 1.58	6.36 ± 1.68	0.007
ALT (IU/l)	48.52 ± 29.58	73.11 ± 12.27	87.48 ± 6.66	0.000	53.07 ± 29.54	73.21 ± 13.22	80.79 ± 18.88	0.000
AST (IU/l)	33.44 ± 16.42	49.36 ± 7.28	65.15 ± 6.37	0.000	35.96 ± 16.61	50.38 ± 9.21	62.21 ± 8.56	0.000
GGT (mU/mL)	37.76 ± 34.09	41.26 ± 33.75	33.18 ± 16.48	0.599	37.19 ± 34.05	42.16 ± 32.79	34.18 ± 12.09	0.555
ALP (mU/mL)	83.96 ± 33.35	78.49 ± 25.88	70.00 ± 25.88	0.169	83.14 ± 31.85	78.77 ± 26.37	65.00 ± 20.63	0.131
Total cholesterol (mg/dL)	198.83 ± 31.44	205.43 ± 38.69	210.29 ± 39.89	0.137	200.11 ± 33.43	204.94 ± 38.86	211.53 ± 31.80	0.267
Triglycerides (mg/dL)	159.32 ± 68.36	174.62 ± 83.02	192.25 ± 105.33	0.063	160.22 ± 66.14	178.91 ± 90.78	186.37 ± 105.64	0.079
HDL cholesterol (mg/dL)	40.87 ± 10.10	39.42 ± 8.06	38.07 ± 8.03	0.204	40.82 ± 9.74	38.85 ± 8.28	39.42 ± 7.94	0.187
LDL cholesterol (mg/dL)	130.43 ± 28.83	132.48 ± 32.22	132.40 ± 36.86	0.840	131.57 ± 30.01	130.87 ± 32.81	133.32 ± 29.06	0.946

Adjusted for age, gender, and BMI.

Discussion

NAFLD, one of the chronic liver diseases, is quite prevalent worldwide, yet its causes and pathogenesis remain unclear (Younossi et al., 2023; Ye et al., 2020; Diehl and Day, 2017; Younossi, 2019; Buzzetti et al., 2016; Cherubini et al., 2021). Today, it is regarded as a multifactorial chronic liver disease influenced by the complex interplay of lifestyle, dietary habits, and genetic factors (Diehl and Day, 2017; Younossi, 2019; Stender et al., 2017). Genetic factors are thought to play critical roles in the development of NAFLD, and multiple genome-wide association studies (GWAS) have identified some genes (TM6SF2, SAMM50, PARVB, and PNPLA3) as potential candidates for NAFLD susceptibility and progression (Lee et al., 2024; Anstee et al., 2020; Park et al., 2020; Namjou et al., 2019; Romeo et al., 2008). Given the critical importance of PNPLA3 in the pathogenesis of NAFLD, it is suggested that genetic polymorphisms in the PNPLA3 gene may determine individual susceptibility to NAFLD (Bruschi et al., 2017; Kumari et al., 2012; Dong, 2019; Romeo et al., 2008). Therefore, recognizing functional SNPs that impact PNPLA3 gene regulation and increase NAFLD vulnerability is essential, as this could assist in forecasting NAFLD risk for both personal and community health and shed light on the underlying mechanisms associated with NAFLD. In addition, integrating these functional polymorphisms with conventional diagnostic approaches may help lower NAFLD-related mortality by enabling earlier detection, enhancing patient management, and supporting personalized treatment strategies (Younossi et al., 2023; Diehl and Day, 2017; Ioannou, 2021). In this hospital-based molecular epidemiological case-control study, we examined the relationship between the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms with the risk of NAFLD susceptibility in a sample from the Turkish population in Adıyaman Province, located in the Southeast Anatolia Region of Turkey. In this study, the genotype frequency distribution of both PNPLA3 polymorphisms (rs738409 and rs2896019 T > G) in the control group was consistent with HWE. It was determined that the allele frequency distribution of these two polymorphisms was similar to or closely aligned with the frequencies reported in studies conducted on individuals of European descent (Table 5). The key findings of our study are outlined below: the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms were associated with an increased risk of NAFLD susceptibility in all genetic models, including log-additive inheritance models. Moreover, PNPLA3 Grs738409/Grs2896019 haplotype (ht2) is concerned with the development of NAFLD. In addition, it was found that the mean values of ALT and AST enzymes showed statistically significant differences across the genotypes of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms. These findings support earlier studies that highlighted a significant association between the GG genotype of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms and NAFLD (Zhao et al., 2023; Salari et al., 2021; Dai et al., 2019; Zhang et al., 2015). This suggests that the GG genotype plays a crucial role in promoting liver fat accumulation.

Table 5.

Allele Frequencies of PNPLA3 rs738409 C > G and rs2896019 T > G Polymorphisms According to the 1000 GENOMES Data

Population ID	PNPLA3 polymorphisms
	rs738409 C > G		rs2896019 T > G
	C allele	G allele	T allele	G allele
EAS (East Asian)	0.6498	0.3502	0.6359	0.3641
EUR (European)	0.7744	0.2256	0.8012	0.1988
AFR (African)	0.8820	0.1180	0.8419	0.1581
AMR (Ad Mixed American)	0.5160	0.4840	0.5620	0.4380
SAS (South Asian)	0.7540	0.2460	0.7640	0.2360
Present study (Southeastern Anatolia Region)	0.7756	0.2243	0.8304	0.1695
Islek et al., 2014 (Marmara Region)	0.7277	0.2722	0.7970	0.2029
Uygun et al., 2017 (Mixed: Central Anatolia Region and Aegean Region)	0.7333	0.2666	—	—
Idilman et al., 2020 (Central Anatolia Region)	0.5231	0.4768	—	—
Delik et al., 2020 (Mediterranean Region)	0.6543	0.3456	—	—
Akkız et al., 2021 (Mediterranean Region)	0.6639	0.3360	—	—
Demirtas et al., 2024 (Marmara Region)	0.6993	0.3006	—	—
Husseini, 2024 (Marmara Region)	0.7375	0.2625	—	—

To date, many case-control studies have investigated the association between the PNPLA3 rs738409 C > G polymorphism and NAFLD susceptibility in the Turkish population (Islek et al., 2014; Uygun et al., 2017; Idilman et al., 2020; Delik et al., 2020; Akkiz et al., 2021; Husseini, 2024). However, the results of these studies have not been consistent (Islek et al., 2014; Uygun et al., 2017; Idilman et al., 2020; Delik et al., 2020; Akkiz et al., 2021; Husseini, 2024). Studies investigating the association between the PNPLA3 rs738409 C > G polymorphism and NAFLD susceptibility have been conducted in the Marmara, Central Anatolia, and Aegean Regions of Turkey. The results of these studies are consistent with the findings of our study conducted in a sample of the Turkish population from Adıyaman Province, located in the Southeast Anatolia Region of Turkey (Islek et al., 2014; Uygun et al., 2017; Idilman et al., 2020; Husseini, 2024). Although many studies indicate that the G allele or GG genotype of the PNPLA3 rs738409 C > G polymorphism is associated with NAFLD susceptibility in the Turkish population, two studies have reported no such association (Delik et al., 2020; Akkiz et al., 2021). The differences between the results of these two studies conducted in the Mediterranean Region of Turkey and our findings, as well as those of other studies in the Turkish population that identified an association between the PNPLA3 rs738409 C > G polymorphism and NAFLD susceptibility, may be due to the following reasons: (1) Upon closely examining the allele and genotype distributions of controls in the studies by Delik et al. (2020) and Akkız et al. (2021), which reported no association between the PNPLA3 rs738409 C > G polymorphism and NAFLD susceptibility in the Turkish population (see Table 5), it is evident that the allele distribution of this polymorphism in these studies does not resemble that of either the European population or other studies conducted in the Turkish population. (2) In addition, both studies (Delik et al., 2020; Akkiz et al., 2021) had relatively small sample sizes, and the statistical power of these studies was not calculated. Such small sample sizes may have affected the reliability and generalizability of the results.

In the meta-analysis conducted by Zhao et al. in 2023, 20 studies were included, encompassing a total of 3,240 NAFLD patients and 5,210 controls. The analysis demonstrated a significant association between the PNPLA3 rs738409 C > G polymorphism and NAFLD across five genetic models: allelic, homozygous, heterozygous, dominant, and recessive (Zhao et al., 2023). In another meta-analysis conducted in 2021, which included 31 studies, the total number of samples in the case and control groups was reported as 9,973 and 13,048, respectively (Salari et al., 2021). According to the results, individuals with the CC genotype of the PNPLA3 rs738409 C > G polymorphism had a 52% lower risk of developing NAFLD, with an OR of 0.48 (Salari et al., 2021). In contrast, the ORs for individuals with the CG and GG genotypes of the PNPLA3 rs738409 C > G polymorphism were found to be 1.19 and 2.05, respectively, indicating that those with the CG genotype have a 19% higher risk, while those with the GG genotype have a 105% higher risk of developing NAFLD (Salari et al., 2021). In another meta-analysis conducted by Dai et al., in 2019, a total of 21 studies involving 14,266 subjects were examined. This study identified the G allele of the PNPLA3 rs738409 C > G polymorphism as a risk factor for NAFLD (Dai et al., 2019). The odds of developing NAFLD in individuals with one G allele of the PNPLA3 rs738409 C > G polymorphism were found to be 1.88 compared with those without the G allele. This OR increased to 4.01 in individuals with both alleles as G for the PNPLA3 rs738409 C > G polymorphism (Dai et al., 2019). In the meta-analysis by Zhang et al. (2015), which included studies conducted in Asian countries, 12 studies with a total of 4,495 cases and 7,431 controls were examined. According to this meta-analysis, individuals with the G allele of the PNPLA3 rs738409 C > G polymorphism had odds of developing NAFLD that were 1.92 times higher compared with those with the C allele (Zhang et al., 2015). This result suggests that the G allele of the PNPLA3 rs738409 C > G polymorphism may elevate the risk of NAFLD by 92% (Zhang et al., 2015). These meta-analyses have shown that the risk of NAFLD increases as the number of G alleles of the PNPLA3 rs738409 C > G polymorphism in an individual rises, which is consistent with the results of our study (Zhao et al., 2023; Salari et al., 2021; Dai et al., 2019; Zhang et al., 2015) (Table 2).

The results of our study regarding the PNPLA3 rs738409 C > G polymorphism are biologically plausible and align with various laboratory and clinical findings from previous research, supporting a potential association with NAFLD susceptibility (Cherubini et al., 2021). PNPLA3 was initially identified as a lipase enzyme that breaks down glycerolipids, with a notable effect on monounsaturated fatty acids (Bruschi et al., 2017; Kumari et al., 2012). It was later discovered that the PNPLA3 rs738409 C > G polymorphism disrupts this function, leading to an impaired activity and subsequent loss of function (Huang et al., 2011). Moreover, Pingitore et al. (2014) confirmed that PNPLA3 has weak acyltransferase activity and that the PNPLA3 rs738409 C > G polymorphism results in a loss of function for both acyltransferase and lipase activities. PNPLA3 is also suggested to facilitate the transfer of polyunsaturated fatty acids (PUFAs) from diacylglycerol (DAG) to phosphatidylcholines or, alternatively, to act as a lipase that releases PUFAs from DAG, supplying substrates for the production of PUFA-enriched phosphatidylcholines (Bruschi et al., 2017; Kumari et al., 2012; Cherubini et al., 2021). Recent studies have shown that homozygosity for the PNPLA3 rs738409 C > G polymorphism results in the intrahepatic accumulation of PUFAs and exhibits a loss of function relative to this specific phenotype, as it phenocopies PNPLA3 knockout (KO) (Luukkonen et al., 2019; Tilson et al., 2021). Experimental models in mice have shown that the PNPLA3 rs738409 C > G polymorphism exhibits new biological functions as a neomorph variant and is resistant to ubiquitination-dependent degradation (BasuRay et al., 2019). As a result, proteins accumulate around lipid droplets, trapping lipids within the cells (BasuRay et al., 2019). This information suggests that the PNPLA3 rs738409 C > G polymorphism leads to both a loss of function (due to reduced enzymatic activity) and a gain of new function (neomorph) (Valenti and Cherubini, 2021; Cherubini et al., 2021). This new function is associated with negative transactivation, as the PNPLA3 rs738409 C > G polymorphism prevents protein degradation, which in turn leads to lipid accumulation (Valenti and Cherubini, 2021; Cherubini et al., 2021). All these biological mechanisms suggest that the PNPLA3 rs738409 C > G polymorphism promotes intrahepatic lipid accumulation and is associated with lipotoxicity, as well as more severe phenotypes, including fibrosis and carcinogenesis (Cherubini et al., 2021).

In this study, 335 individuals with NAFLD and 410 individuals from the Turkish population in Adıyaman Province, located in the Southeast Anatolia Region of Turkey, were examined. It was found that the PNPLA3 rs2896019 T > G polymorphism significantly increased the risk of NAFLD in all genetic models. According to our literature review, only one study has investigated the association between the PNPLA3 rs2896019 T > G polymorphism and NAFLD in the Turkish population from the Marmara Region, and it included a relatively small patient sample (Islek et al., 2014). This study, conducted with 80 patients with NAFLD, reported that the PNPLA3 rs2896019 T > G polymorphism increases the risk of developing NAFLD by 1.927-fold in individuals carrying the G allele (Islek et al., 2014). Our study and the one conducted in the Marmara Region of Turkey show similar results and allele frequencies in individuals (Islek et al., 2014). In addition, the allele frequencies in healthy individuals from these two studies conducted in Turkey closely resemble those observed in European populations (Table 5). In the study by Song et al. (2016), involving 384 patients with NAFLD and 384 controls from the Chinese population, individuals with homozygous GG and heterozygous GT genotypes of the PNPLA3 rs2896019 T > G polymorphism were found to have a significantly higher risk of developing NAFLD compared with those with homozygous TT genotype. Research involving the Caucasian, Hispanic, and Asian populations has demonstrated that the PNPLA3 rs2896019 T > G polymorphism is associated with hepatic steatosis (Stasinou et al., 2022). In addition, DiStefano et al. (2015) conducted a GWAS in obese individuals from the Caucasian population and found that the PNPLA3 rs2896019 T > G polymorphism was associated with hepatic fat grades, suggesting its involvement in the pathophysiology of hepatic lipid accumulation. The results obtained from the above studies are similar to the findings of our study, which indicate an association between the PNPLA3 rs2896019 T > G polymorphism and NAFLD (Islek et al., 2014; Song et al., 2016; Stasinou et al., 2022; DiStefano et al., 2015). Although literature data on the association between the PNPLA3 rs2896019 T > G polymorphism and NAFLD susceptibility are limited, existing studies suggest a potential link that warrants further investigation.

One of the key findings of our study is that when the biochemical parameters of patients with NAFLD were grouped according to the genotypes of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms, it was observed that the mean values of ALT and AST enzymes significantly increased with the higher frequency of the G variant allele. Similar to the findings from our study, there are studies in the literature that support the increase in liver enzyme levels as the frequency of the G allele in PNPLA3 rs738409 C > G polymorphism increases. For example, Larrieta-Carrasco et al. (2018) reported that the PNPLA3 rs738409 C > G polymorphism was strongly associated with elevated ALT levels in normal-weight and overweight/obese Mexican children. In addition, del Giudice et al. (2011) found that, after adjusting for age, gender, pubertal stage, and BMI, the PNPLA3 rs738409 C > G polymorphism was associated with a striking increase in circulating ALT and AST levels in children carrying the G allele. Another study consistent with our results was recently conducted by Rosso et al. (2023), demonstrating that NAFLD patients carrying the G risk allele of PNPLA3 rs738409 C > G polymorphism (additive model) or GG homozygote (recessive model) had higher AST and ALT levels compared with those carrying the CC genotype or the wild-type C allele, respectively. In light of recent information, there have been no studies investigating the differences in liver enzyme levels when grouping the genotypes of the PNPLA3 rs2896019 T > G polymorphism to date. In addition, there is a lack of studies in the literature investigating the genetic and biological significance of the PNPLA3 rs2896019 T > G polymorphism; since this polymorphism has been shown to be associated with genetic susceptibility to NAFLD, it presents a potential that warrants further investigation.

Routine assessment of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms through genetic screening tests in clinical practice may enable the early identification of individuals at high risk of developing NAFLD (Carlsson et al., 2020; Chen and Vespasiani-Gentilucci, 2025). This approach would allow individuals carrying the G allele for either polymorphism to be enrolled in monitoring programs before clinical symptoms manifest (Carlsson et al., 2020; Chen and Vespasiani-Gentilucci, 2025). Early detection facilitates timely identification of liver damage, enabling intervention before progression to more severe stages such as fibrosis and cirrhosis (Carlsson et al., 2020; Chen and Vespasiani-Gentilucci, 2025). Furthermore, individuals harboring the G allele in these polymorphisms may be classified into a higher risk group, particularly when combined with environmental or lifestyle factors such as obesity, high-fat diets, and low physical activity (Carlsson et al., 2020; Chen and Vespasiani-Gentilucci, 2025). This classification can guide health care professionals in closely monitoring these individuals, recommending lifestyle modifications, and implementing preventive measures. Identification of the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms can also contribute to the development of personalized treatment strategies (Carlsson et al., 2020; Chen and Vespasiani-Gentilucci, 2025; Dong, 2019; Cherubini et al., 2021). Given that the G allele of PNPLA3 rs738409 C > G is associated with increased hepatic lipid accumulation, steatosis, inflammation, and fibrosis, individuals carrying this variant may exhibit greater responsiveness to lipid metabolism-targeted interventions, including weight loss, dietary modifications, and pharmacological agents aimed at reducing hepatic fat accumulation (Dong, 2019; Cherubini et al., 2021). Moreover, genetic risk assessment can help predict which patients are more likely to respond favorably to specific therapeutic approaches, thereby enhancing treatment efficacy (Dong, 2019; Cherubini et al., 2021). In conclusion, integrating PNPLA3 rs738409 C > G and rs2896019 T > G polymorphism analysis into clinical practice may improve NAFLD screening, risk assessment, and personalized treatment strategies, ultimately leading to better patient outcomes and the prevention of severe liver-related complications.

Our hospital-based molecular epidemiological case-control study has several possible limitations that should be considered: (1) NAFLD diagnosis was primarily based on ultrasound imaging. While liver biopsy is the gold standard for diagnosing NAFLD, it is an invasive procedure and is not ethically permitted in epidemiological studies, making ultrasonography the most practical alternative. (2) Because this is a hospital-based case-control study, all NAFLD cases and controls were collected from the Adıyaman State Hospital. This may have led to a selection bias, possibly making the sample less representative of the general population. However, in the control group, the genotype frequencies for the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms aligned with the expected HWE model, indicating that selection bias was unlikely. Verifying our findings in future population-based studies is still important. (3) Our sample size might not have sufficient statistical power to identify subtle effects from genes or SNPs with low penetrance. Nevertheless, we had enough statistical power to detect the impact of the rs738409 C > G and rs2896019 T > G polymorphisms in the PNPLA3 gene on NAFLD risk. Larger studies are still needed to confirm these findings. (4) Only individuals from the Turkish population were included in this study. It is known that allele frequency distributions for the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms vary among different ethnic groups (Table 5). Additional research in diverse populations is required to support the relationship between these two polymorphisms (rs738409 C > G and rs2896019 T > G) in the PNPLA3 gene and NAFLD susceptibility with more reliable findings and to validate our results.

In conclusion, this association study on PNPLA3 SNPs and NAFLD demonstrated that the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms, along with their haplotypes, may modulate the risk of NAFLD susceptibility in the Turkish population of Adıyaman Province, located in the Southeast Anatolia Region of Turkey. Furthermore, when patients were grouped according to the genotypes of these polymorphisms, it was found that the mean values of ALT and AST enzymes may vary with a higher frequency of the G variant allele. This provides insights from both epidemiological and statistical perspectives, enhancing our understanding of the complex mechanisms behind the development of NAFLD. Further independent studies are needed to validate our findings in a larger cohort and among patients of different ethnic backgrounds, to better understand the PNPLA3 rs738409 C > G and rs2896019 T > G polymorphisms and their association with NAFLD susceptibility.

Footnotes

Acknowledgments

The authors sincerely thank all the patients and controls who generously donated their blood samples for this study.

Authors’ Contributions

Concept, design, and overall supervision: S.B. Sample collection, processing, and data acquisition: Y.Ü. Analysis or interpretation of data: S.B. Drafting of the article: S.B. and Y.Ü. Editing of the article: S.B. and Y.Ü. All authors provided comments on the article and evaluated critically. All authors provided their consent for publication.

Data Availability

The authors confirm that all data supporting the study’s findings are included in the article. In addition, the raw data can be requested from the corresponding author.

Ethical Approval

Adıyaman University Faculty of Medicine, Ethics Committee approved this study. (Protocol number: 2022/03-2; dated March 26, 2022.) This study conformed to the principles of Helsinki Declaration.

Consent to Participate

Informed consent was obtained from the individuals participating in the study.

Consent to Publish

As the article does not contain any personal or identifying information about the participants, consent for publication is not required.

Author Disclosure Statement

The authors declare no competing interests.

Funding Information

There was no funding for the study.

References

Akkiz

, Taskin

, Karaogullarindan

, et al. The influence of RS738409 I148M polymorphism of patatin-like phospholipase domain containing 3 gene on the susceptibility of non-alcoholic fatty liver disease. Medicine (Baltimore), 2021; 100(19):e25893; doi: 10.1097/MD.0000000000025893).

Anstee

, Darlay

, Cockell

, et al.; EPoS Consortium Investigators. Genome-wide association study of non-alcoholic fatty liver and steatohepatitis in a histologically characterised cohort(☆). J Hepatol, 2020; 73(3):505-515; doi: 10.1016/j.jhep.2020.04.003

BasuRay

, Wang

, Smagris

, et al. Accumulation of PNPLA3 on lipid droplets is the basis of associated hepatic steatosis. Proc Natl Acad Sci U S A, 2019; 116(19):9521-9526; doi: 10.1073/pnas.1901974116

Baulande

, Lasnier

, Lucas

, Pairault

. Adiponutrin, a transmembrane protein corresponding to a novel dietary- and obesity-linked mRNA specifically expressed in the adipose lineage. J Biol Chem, 2001; 276(36):33336-33344; doi: 10.1074/jbc.M105193200

Brunt

, Janney

, Di Bisceglie

, et al. Nonalcoholic steatohepatitis: A proposal for grading and staging the histological lesions. Am J Gastroenterol, 1999; 94(9):2467-2474; doi: 10.1111/j.1572-0241.1999.01377.x

Bruschi

, Tardelli

, Claudel

, et al. PNPLA3 expression and its impact on the liver: Current perspectives. Hepat Med, 2017; 9:55-66; doi: 10.2147/HMER.S125718

Buzzetti

, Pinzani

, Tsochatzis

. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD). Metabolism, 2016; 65(8):1038-1048; doi: 10.1016/j.metabol.2015.12.012

Carlsson

, Lindén

, Brolén

, et al. Review article: The emerging role of genetics in precision medicine for patients with non-alcoholic steatohepatitis. Aliment Pharmacol Ther, 2020; 51(12):1305-1320; doi: 10.1111/apt.15738

Chen

, Vespasiani-Gentilucci

. Integrating PNPLA3 into clinical risk prediction. Liver Int, 2025; 45(3):e16103; doi: 10.1111/liv.16103

10.

Cherubini

, Casirati

, Tomasi

, Valenti

. PNPLA3 as a therapeutic target for fatty liver disease: The evidence to date. Expert Opin Ther Targets, 2021; 25(12):1033-1043; doi: 10.1080/14728222.2021.2018418

11.

Dai

, Liu

, Li

, et al. Association between PNPLA3 rs738409 polymorphism and nonalcoholic fatty liver disease (NAFLD) susceptibility and severity: A meta-analysis. Medicine (Baltimore), 2019; 98(7):e14324; doi: 10.1097/MD.0000000000014324

12.

Değertekin

, Tozun

, Demir

, et al. The changing prevalence of Non-Alcoholic Fatty Liver Disease (NAFLD) in Turkey in the last decade. Turk J Gastroenterol, 2021; 32(3):302-312; doi: 10.5152/tjg.2021.20062

13.

Delik

, Akkız

, Dinçer

. The effect of PNPLA3 polymorphism as gain in function mutation in the pathogenesis of non-alcoholic fatty liver disease. Indian J Gastroenterol, 2020; 39(1):84-91; doi: 10.1007/s12664-020-01026-x

14.

Demirtas

, Eren

, Yilmaz

, et al. Does genetic variation in PNPLA3, TM6SF2 and HSD17B13 have a role in the development or prognosis of hepatocellular carcinoma in Turkish patients with Hepatitis B? J Gastrointestin Liver Dis, 2024; 33(2):203-211; doi: 10.15403/jgld-5474

15.

Diehl

, Day

. Cause, pathogenesis, and treatment of nonalcoholic steatohepatitis. N Engl J Med, 2017; 377(21):2063-2072; doi: 10.1056/NEJMra1503519

16.

DiStefano

, Kingsley

, Craig Wood

, et al. Genome-wide analysis of hepatic lipid content in extreme obesity. Acta Diabetol, 2015; 52(2):373-382; doi: 10.1007/s00592-014-0654-3

17.

Dong

. PNPLA3-A potential therapeutic target for personalized treatment of chronic liver disease. Front Med (Lausanne), 2019; 6:304; doi: 10.3389/fmed.2019.00304

18.

Gauderman

, Morrison

. QUANTO 1.1: A Computer Program for Power and Sample Size Calculations for Genetic-Epidemiology Studies. 2006. Available from: http://hydra.usc.edu/gxe

19.

Giudice

, Grandone

, Cirillo

, et al. The association of PNPLA3 variants with liver enzymes in childhood obesity is driven by the interaction with abdominal fat. PLoS One, 2011; 6(11):e27933; doi: 10.1371/journal.pone.0027933

20.

Huang

, Cohen

, Hobbs

. Expression and characterization of a PNPLA3 protein isoform (I148M) associated with nonalcoholic fatty liver disease. J Biol Chem, 2011; 286(43):37085-37093; doi: 10.1074/jbc.M111.290114

21.

Husseini

. Genotypic variation in CYP2E1, GCKR, and PNPLA3 among nonalcoholic steatohepatitis patients of Turkish origin. Mol Biol Rep, 2024; 51(1):845; doi: 10.1007/s11033-024-09787-w

22.

Idilman

, Karatayli

, Kabacam

, et al. The role of PNPLA3 (rs738409) c>g variant on histological progression of non-alcoholic fatty liver disease. Hepatol Forum, 2020; 1(3):82-87; doi: 10.14744/hf.2020.2020.0023

23.

Ioannou

. Epidemiology and risk-stratification of NAFLD-associated HCC. J Hepatol, 2021; 75(6):1476-1484; doi: 10.1016/j.jhep.2021.08.012

24.

Islek

, Sazci

, Ozel

, Aygun

. Genetic variants in the PNPLA3 gene are associated with nonalcoholic steatohepatitis. Genet Test Mol Biomarkers, 2014; 18(7):489-496; doi: 10.1089/gtmb.2014.0019

25.

Kienesberger

, Oberer

, Lass

, Zechner

. Mammalian patatin domain containing proteins: A family with diverse lipolytic activities involved in multiple biological functions. J Lipid Res, 2009; 50 (Suppl):S63-S68; doi: 10.1194/jlr.R800082-JLR200

26.

Kumari

, Schoiswohl

, Chitraju

, et al. Adiponutrin functions as a nutritionally regulated lysophosphatidic acid acyltransferase. Cell Metab, 2012; 15(5):691-702; doi: 10.1016/j.cmet.2012.04.008

27.

Larrieta-Carrasco

, Flores

, Macías-Kauffer

, et al. Genetic variants in COL13A1, ADIPOQ and SAMM50, in addition to the PNPLA3 gene, confer susceptibility to elevated transaminase levels in an admixed Mexican population. Exp Mol Pathol, 2018; 104(1):50-58; doi: 10.1016/j.yexmp.2018.01.001

28.

Lee

, Cho

, Choe

, et al. Genome-wide association study of metabolic dysfunction-associated fatty liver disease in a Korean population. Sci Rep, 2024; 14(1):9753; doi: 10.1038/s41598-024-60152-0

29.

Luukkonen

, Nick

, Hölttä-Vuori

, et al. Human PNPLA3-I148M variant increases hepatic retention of polyunsaturated fatty acids. JCI Insight, 2019; 4(16):e127902; doi: 10.1172/jci.insight.127902

30.

Namjou

, Lingren

, Huang

, et al.; eMERGE Network. GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE network. BMC Med, 2019; 17(1):135; doi: 10.1186/s12916-019-1364-z

31.

Njei

, Al-Ajlouni

, Ugwendum

, et al. Genetic and epigenetic determinants of non-alcoholic fatty liver disease (NAFLD) in lean individuals: A systematic review. Transl Gastroenterol Hepatol, 2024; 9:11; doi: 10.21037/tgh-23-31

32.

Park

, Li

, Sheng

, et al. Genome-wide association study of liver fat: The multiethnic cohort adiposity phenotype study. Hepatol Commun, 2020; 4(8):1112-1123; doi: 10.1002/hep4.1533

33.

Pingitore

, Pirazzi

, Mancina

, et al. Recombinant PNPLA3 protein shows triglyceride hydrolase activity and its I148M mutation results in loss of function. Biochim Biophys Acta, 2014; 1841(4):574-580; doi: 10.1016/j.bbalip.2013.12.006

34.

Romeo

, Kozlitina

, Xing

, et al. Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease. Nat Genet, 2008; 40(12):1461-1465; doi: 10.1038/ng.257

35.

Rosso

, Caviglia

, Birolo

, et al. Impact of PNPLA3 rs738409 polymorphism on the development of liver-related events in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol, 2023; 21(13):3314-3321; doi: 10.1016/j.cgh.2023.04.024

36.

Ruhanen

, Perttilä

, Hölttä-Vuori

, et al. PNPLA3 mediates hepatocyte triacylglycerol remodeling. J Lipid Res, 2014; 55(4):739-746; doi: 10.1194/jlr.M046607

37.

Salari

, Darvishi

, Mansouri

, et al. Association between PNPLA3 rs738409 polymorphism and nonalcoholic fatty liver disease: A systematic review and meta-analysis. BMC Endocr Disord, 2021; 21(1):125; doi: 10.1186/s12902-021-00789-4

38.

Solé

, Guinó

, Valls

, et al. SNPStats: A web tool for the analysis of association studies. Bioinformatics, 2006; 22(15):1928-1929; doi: 10.1093/bioinformatics/btl268

39.

Song

, Xiao

, Wang

, et al. Association of patatin-like phospholipase domain-containing protein 3 gene polymorphisms with susceptibility of nonalcoholic fatty liver disease in a Han Chinese population. Medicine (Baltimore), 2016; 95(33):e4569; doi: 10.1097/MD.0000000000004569

40.

Sookoian

, Pirola

. 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, 2011; 53(6):1883-1894; doi: 10.1002/hep.24283

41.

Stasinou

, Argyraki

, Sotiriadou

, et al. Association between rs738409 and rs2896019 single-nucleotide polymorphisms of phospholipase domain-containing protein 3 and susceptibility to nonalcoholic fatty liver disease in Greek children and adolescents. Ann Gastroenterol, 2022; 35(3):297-306; doi: 10.20524/aog.2022.0706

42.

Stender

, Kozlitina

, Nordestgaard

, et al. Adiposity amplifies the genetic risk of fatty liver disease conferred by multiple loci. Nat Genet, 2017; 49(6):842-847; doi: 10.1038/ng.3855

43.

Tilson

, Morell

, Lenaerts

, et al. Modeling PNPLA3-associated NAFLD using human-ınduced pluripotent stem cells. Hepatology, 2021; 74(6):2998-3017; doi: 10.1002/hep.32063

44.

Uygun

, Ozturk

, Demirci

, et al. The association of nonalcoholic fatty liver disease with genetic polymorphisms: A Multicenter Study. Eur J Gastroenterol Hepatol, 2017; 29(4):441-447; doi: 10.1097/MEG.0000000000000813

45.

Valenti

LVC

, Cherubini

. To be or not to be: The quest for patatin-like phospholipase domain containing 3 p.I148M Function. Hepatology, 2021; 74(6):2942-2944; doi: 10.1002/hep.32096

46.

Wilson

, Gardner

, Lambie

, et al. Characterization of the human patatin-like phospholipase family. J Lipid Res, 2006; 47(9):1940-1949; doi: 10.1194/jlr.M600185-JLR200

47.

, Zou

, Yeo

, et al. Global prevalence, incidence, and outcomes of non-obese or lean nonalcoholic fatty liver disease: A systematic review and meta-analysis. Lancet Gastroenterol Hepatol, 2020; 5(8):739-752; doi: 10.1016/S2468-1253(20)30077-7

48.

Younossi

. Non-alcoholic fatty liver disease-A global public health perspective. J Hepatol, 2019; 70(3):531-544; doi: 10.1016/j.jhep.2018.10.033

49.

Younossi

, Golabi

, Paik

, et al. The global epidemiology of Nonalcoholic Fatty Liver Disease (NAFLD) and Non-Alcoholic Steatohepatitis (NASH): A systematic review. Hepatology, 2023; 77(4):1335-1347; doi: 10.1097/HEP.0000000000000004

50.

Zeng

, Fan

, Lu

, et al.; Chinese National Consensus Workshop on Nonalcoholic Fatty Liver Disease. Guidelines for the diagnosis and treatment of nonalcoholic fatty liver diseases. J Dig Dis, 2008; 9(2):108-112; doi: 10.1111/j.1751-2980.2008.00331.x

51.

Zhang

, You

, Zhang

, et al. PNPLA3 polymorphisms (rs738409) and non-alcoholic fatty liver disease risk and related phenotypes: A meta-analysis. J Gastroenterol Hepatol, 2015; 30(5):821-829; doi: 10.1111/jgh.12889

52.

Zhao

, Zhao

, Ma

, et al. Patatin-like phospholipase domain-containing 3 gene (PNPLA3) polymorphic (rs738409) single nucleotide polymorphisms and susceptibility to nonalcoholic fatty liver disease: A meta-analysis of twenty studies. Medicine (Baltimore), 2023; 102(10):e33110; doi: 10.1097/MD.0000000000033110