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Relationship of FTO gene variations with NAFLD risk in Chinese men

  • Xuefen Chen , Yong Gao , Xiaobo Yang , Haiying Zhang , Zengnan Mo and Aihua Tan EMAIL logo
Published/Copyright: November 30, 2020
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Open Life Sciences
From the journal Open Life Sciences Volume 15 Issue 1

Abstract

Background

Fat mass and obesity-associated (FTO) gene is an obesity susceptibility gene and its relationship with the nonalcoholic fatty liver disease (NAFLD) remains unclear. This study aims to investigate the relationships of FTO gene variations with NAFLD risk in a Chinese male population.

Methods

A 1:2 matched case–control study was performed on 275 cases of NAFLD and 550 controls matched for age. Nine of the FTO gene single nucleotide polymorphisms (SNPs) were genotyped.

Results

Logistic regression analysis found that FTO rs1477196 was significantly associated with the susceptibility to NAFLD in recessive genetic models [unadjusted odds ratio (OR) = 2.52, 95% confidence interval (CI): 1.22–5.19, P = 0.012] and the relativity weakened after further adjustment for body mass index (BMI), uric acid, metabolic syndrome, smoking, and drinking (adjusted OR = 2.18, 95% CI: 0.96–4.99, P = 0.06). In the obese group, the AA + AG genotypes of rs1121980 and rs9940128 were associated with a decreased risk of NAFLD, when compared with the GG genotype, respectively (rs1121980: adjusted OR = 0.62, 95% CI = 0.39–0.99, P = 0.044; rs9940128: adjusted OR = 0.61, 95% CI = 0.38–0.97, P = 0.038). Furthermore, rs1477196 was associated with the severity of NAFLD (OR = 2.95, 95% CI = 1.09–7.94, P = 0.034).

Conclusions

Our results demonstrated that the FTO gene was related to the presence and severity of NAFLD in a Chinese male population, and the relationships of the tested SNPs with NAFLD are most probably mediated by BMI.

Keywords: FTO gene; nonalcoholic fatty liver disease; SNPs; obesity

1 Introduction

Nonalcoholic fatty liver disease (NAFLD), characterized by an excessive fat deposition in hepatocytes, excluding alcohol and other specific liver damaging factors [1], is an acquired metabolic stress liver injury closely related to insulin resistance and genetic predisposition. It can not only directly lead to cirrhosis and hepatocellular carcinoma but also affect the progression of other chronic liver diseases and be involved in the pathogenesis of type 2 diabetes and atherosclerosis [2]. It is estimated that NAFLD will become the leading cause of liver-related morbidity and mortality within 20 years.

The fat mass and obesity-associated (FTO) gene is located on chromosome 16q12.2. As a predictor of metabolic disorders, the FTO gene plays a conclusive role in the command of energy balance and is highly expressed in many tissues, including fat and liver [3,4]. The relationships of FTO gene polymorphisms with metabolic diseases have been extensively studied. FTO rs9939609 and rs17817449 were reported to be related to metabolic syndrome, type 2 diabetes mellitus, and obesity [5,6]; rs8050136 and rs7195539 were associated with type 2 diabetes mellitus in a Uyghur population [7]. A study in western Spain found that rs9921255 and rs1477196 could increase the risk of obesity-related traits [8]. Other studies found that rs1121980 and rs8061518 were strongly related to obesity [9,10], and rs9940128 had relationships with type 2 diabetes mellitus and obesity in south Indians [11]. Besides, Haupt et al. [12] have reported the relationship of FTO gene polymorphism with liver fat content and found that there was a significant effect of FTO rs8050136 on subcutaneous fat and a trend for liver fat content.

NAFLD is closely related to metabolic disorders, such as insulin resistance and obesity [13], and is also related to variability in some important NAFLD genes (i.e., PNPLA3 and TM6SF2) [14]. So far, the relationships of FTO gene variants with NAFLD risk remain unclear. Our study was designed to explore the relationships of FTO gene variations with NAFLD risk in a Chinese male population.

2 Participants and methods

2.1 Study population

We used a 1:2 nested case–control study design in our study, in which one NAFLD patient was matched to two non-NAFLD men on age (±3 years). The age-matched controls were selected randomly from all subjects without NAFLD. All participants were from the FAMHES cohort [15], which included 4,303 continuous male health examinees in the Medical Centre of Fangchenggang First People’s Hospital from September 2009 to December 2009. And participants with the following criteria were excluded: (1) coronary heart disease, stroke, diabetes mellitus, hyperthyroidism, or cancer; (2) hepatitis history; (3) heavy drinkers (≥ 20 g/day, according to the published report [16]); and (4) without ultrasound diagnostic data. A total of 334 men were diagnosed with NAFLD and 59 of them had no data on genotyping. In the end, 275 cases of NAFLD and 550 controls matched for age in 1:2 were included in the analysis.

  1. Informed consent: Informed consent has been obtained from all individuals included in this study.

  2. Ethical approval: The research related to human use has been complied with all the relevant national regulations, institutional policies and in accordance with the tenets of the Helsinki Declaration and has been approved by the Guangxi Medical University Ethics Committee.

2.2 Data collection

We collected participants’ age, smoking status, alcohol consumption, physical activity, and medical history by the questionnaire survey methods. Drinkers were defined as consuming at least one drink of alcohol (beer, wine, or hard liquor) per week. Smokers were defined as smoking at least once a day for more than 6 months. The exercise intensity was classified as low, moderate, or high according to the questionnaire scoring protocol [15]. We measured the height, body weight, waist circumference (WC), and blood pressure (BP) according to a standard protocol. Body mass index (BMI) was calculated as weight (kg)/[height (m)]2, with BMI < 25.0 defined as normal weight and BMI ≥ 25 as obese [17]. Metabolic syndrome was defined as including the following three or more components [15]: (1) WC ≥ 90 cm; (2) triglycerides (TG) ≥ 1.7 mmol/L; (3) high-density lipoprotein cholesterol (HDL-c) < 1.03 mmol/L; (4) BP ≥ 130/85 mmHg or current use of antihypertensive medications; and (5) fasting blood glucose (FBG) ≥ 5.6 mmol/L.

2.3 Definition of NAFLD

The NAFLD was diagnosed with abdominal ultrasound, excluding the other causes [excessive drinking (≥ 20 g/day), viral or autoimmune liver disease, etc.] of chronic liver disease [18]. The liver size, structure, contour, echogenicity, and posterior beam attenuation were assessed independently by two sonographers using a portable ultrasound device (GE LOGIQ e, 5.0 MHz transducer; GE Healthcare, Wauwatosa, Wisconsin, USA). Participants were ultrasonically diagnosed of fatty liver when having the following two or three symptoms [19]: (1) diffused liver enhanced near-field echo, with an echo intensity higher than that of the kidney; (2) dirty liver far-field echo decays; and (3) intrahepatic duct structure display is unclear.

2.4 Genotyping

The venous blood samples were collected, and genomic DNA was extracted. Nine single nucleotide polymorphisms (SNPs) (rs9939609, rs1121980, rs17817449, rs8050136, rs9940128, rs8061518, rs9921255, rs1477196, and rs7195539) of the FTO gene were selected, and these SNPs were reported to be related to metabolic disorders such as obesity, metabolic syndrome, and type 2 diabetes [5,6,7,8,9,10,11]. The genotyping method has been described previously [20]. All genotyping reactions were performed in 384-well plates, and each plate included a duplicate and a negative control for 3–4 samples selected at random. The average concordance rate was 99.8%.

2.5 Statistical analysis

Numeric variables were described as mean ± standard deviation (SD) or median (quartile range) and analyzed with the t-test or rank-sum test. Categorical data were described as percentages (%) and analyzed using the x2 test. Hardy–Weinberg equilibrium (HWE) was computed with the x2 test to compare the observed genotype frequencies with the expected genotype frequencies among the controls. We performed the binary logistic regression analysis to calculate the odds ratio (OR) and 95% confidence intervals (CIs) and evaluate the relationships of SNPs with NAFLD risk. The confounding factors included BMI, uric acid, metabolic syndrome, smoking, and drinking. All statistical analyses were performed using SPSS 17.0 (Chicago, IL, USA) and SNPStats (a web tool for the analysis of association studies) [21], and P < 0.05 was considered statistically significant.

3 Results

Characteristics of the 275 cases of NAFLD and 550 controls are described in Table 1. The mean age of the NAFLD group was 39.26 ± 1.28 years, similar to the controls (39.23 ± 1.28 years, P = 0.958). As expected, compared with the controls, the prevalence of metabolic syndrome and the levels of FBG, alanine aminotransferase (ALT), uric acid, TG, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-c) were all higher (all P < 0.01), and the HDL-c level was lower in the NAFLD group (P < 0.001). Besides, there were more smokers and drinkers among NAFLD patients (all P < 0.001). However, there was no difference in physical activity between the two groups (P = 0.539). Among the 275 NAFLD patients, the mild, moderate, and severe steatosis were 195 (70.91%), 62 (22.55%), and 18 (6.55%), respectively.

Table 1

Baseline characteristics of the study population stratified for the absence and presence of NAFLD

CharacteristicNAFLD groupControl groupP
n275550
Age (years)39.26 ± 1.2839.23 ± 1.280.958
BMI26.40 ± 2.8123.11 ± 3.07<0.001
Glucose (mmol/L)5.51 ± 1.205.28 ± 1.140.001
ALT (mmol/L)47.00 ± 1.4441.13 ± 1.60<0.001
TC (mmol/L)6.06 ± 1.045.73 ± 1.05<0.001
TG (mmol/L)1.95 ± 1.851.18 ± 1.87<0.001
HDL (mmol/L)1.26 ± 1.281.38 ± 1.23<0.001
LDL (mmol/L)3.24 ± 0.782.98 ± 0.83<0.001
Uric acid (µmol/L)412.34 ± 74.88369.52 ± 81.42<0.001
Metabolic syndrome (n, %)72 (26.18)42 (7.64)<0.001
DBP (mmHg) (M, QR)80 (18)78 (10)<0.001
SBP (mmHg) (M, QR)120 (20)120 (18.5)0.002
Smoking (n, %)227 (82.55)304 (55.27)<0.001
Drinking (n, %)149 (54.18)83 (15.10)<0.001
Physical activity (n, %)0.539
Low178 (64.7)368 (66.9)
Moderate71 (25.8)139 (25.3)
High26 (9.5)40 (7.3)
The severity of NAFLD (n, %)—
Mild195 (70.91)—
Moderate62 (22.55)—
Severe18 (6.55)—

Data are presented as mean ± SD. n, number; BMI, body mass index; ALT, alanine aminotransferase; TC, total cholesterol; TG, triglycerides; HDL, high-density lipoprotein; LDL, low-density lipoprotein; DBP, diastolic blood pressure; SBP, systolic blood pressure; M, median; QR, quartile range.

The genotype frequencies of the nine selected SNPs and their associations with risk of NAFLD are shown in Table 2. Logistic regression analysis showed that rs1477196 was significantly associated with the susceptibility to NAFLD in recessive genetic models (model 1), and carriers of the AA genotype increased the NAFLD risk in comparison with AG + GG carriers (OR = 2.52, 95% CI: 1.22–5.19, P = 0.012). However, the relativity weakened after adjustment for BMI (OR = 2.10, 95% CI: 0.93–4.72, P = 0.07 in model 2) and further for uric acid, metabolic syndrome, smoking, and drinking (OR = 2.18, 95% CI: 0.96–4.99, P = 0.06 in model 3). The other SNPs were not associated with the NAFLD risk in all genetic models. Besides, all the nine SNPs in the control group were in HWE (all P > 0.05, data not shown).

Table 2

Distribution of the genotypes of FTO and their associations with risk of NAFLD

Genotype frequencies, NModel 1Model 2Model 3
NAFLDControlsOR (95% CI)POR (95% CI)POR (95% CI)P
rs1121980
Dominant(AA + AG)/GG88/187192/3570.88 (0.64–1.19)0.390.79 (0.56–1.12)0.180.80 (0.56–1.14)0.21
RecessiveAA/(AG + GG)14/26116/5331.79 (0.86–3.72)0.121.68 (0.73–3.87)0.221.64 (0.70–3.81)0.26
Additive AA/AG/GG14/74/18716/176/3570.97 (0.75–1.27)0.850.90 (0.67–1.21)0.480.90 (0.67–1.22)0.50
rs1477196
Dominant(AA + AG)/GG94/180194/3530.95(0.70–1.29)0.740.95 (0.67–1.34)0.770.93 (0.66–1.32)0.70
RecessiveAA/(AG + GG)17/25714/5332.52 (1.22–5.19)0.0122.10 (0.93–4.72)0.072.18 (0.96–4.99)0.06
AdditiveAA/AG/GG17/77/18014/180/3531.08 (0.84–1.40)0.551.06 (0.79–1.41)0.691.05 (0.79–1.41)0.73
rs17817449
Dominant(GG + TG)/TT68/207144/4060.93 (0.66–1.29)0.650.78 (0.53–1.13)0.180.78 (0.53–1.15)0.20
RecessiveGG/(TG + TT)8/2679/5411.80 (0.69–4.72)0.241.34 (0.45–3.98)0.601.26 (0.41–3.87)0.69
AdditiveGG/TG/TT8/60/2079/135/4060.99 (0.74–1.33)0.960.84 (0.60–1.18)0.310.84 (0.60–1.18)0.32
rs7195539
Dominant(AG + GG)/AA46/228111/4370.79 (0.54–1.16)0.230.75 (0.49–1.15)0.180.72 (0.47–1.11)0.13
RecessiveGG/(AA + AG)4/2707/5411.14 (0.33–3.95)0.832.38 (0.60–9.42)0.232.48 (0.61–10.05)0.21
AdditiveGG/AG/AA4/42/2287/104/4370.84 (0.59–1.18)0.300.83 (0.56–1.24)0.360.81 (0.54–1.21)0.30
rs8050136
Dominant(AA + AC)/CC68/207142/407 0.94 (0.67–1.31)0.720.79 (0.54–1.16)0.220.80 (0.55–1.18)0.25
RecessiveAA/(AC + CC)8/2678/5412.03 (0.75–5.46)0.171.54 (0.50–4.77)0.461.48 (0.46–4.73)0.51
AdditiveAA/AC/CC8/60/2078/134/4071.01 (0.75–1.36)0.930.86 (0.62–1.21)0.390.87 (0.62–1.22)0.41
rs8061518
Dominant(AG + GG)/AA183/92342/2061.20 (0.88–1.62)0.241.11 (0.79–1.57)0.541.14 (0.80–1.61)0.47
RecessiveGG/(AA + AG)57/21891/4571.31 (0.91–1.90)0.151.28 (0.85–1.94)0.241.33 (0.87–2.02)0.19
AdditiveGG/AG/AA57/126/9291/251/2061.18 (0.96–1.44)0.121.13 (0.90–1.42)0.291.15 (0.91–1.45)0.23
rs9921255
Dominant(TC + CC)/TT53/215107/4210.97 (0.67–1.40)0.870.99 (0.65–1.49)0.951.03 (0.68–1.57)0.88
RecessiveCC/(TC + TT)3/2654/5241.48 (0.33–6.67)0.611.00 (0.18–5.47)1.001.04 (0.19–5.80)0.96
AdditiveCC/TC/TT3/50/2154/103/421 0.99 (0.70–1.40)0.970.99 (0.67–1.45)0.951.03 (0.70–1.52)0.88
rs9939609
Dominant(AA + TA)/TT68/207140/4060.95 (0.68–1.32)0.740.79 (0.54–1.16)0.230.80 (0.55–1.18)0.26
RecessiveAA/(TT + TA)8/2678/5392.02 (0.75–5.44)0.171.53 (0.49–4.74)0.461.46 (0.46–4.69)0.52
AdditiveAA/TA/TT8/60/2077/133/4061.02 (0.76–1.37)0.910.87 (0.62–1.21)0.400.87 (0.62–1.22)0.42
rs9940128
Dominant(AA + AG)/GG89/186195/3550.87 (0.64–1.18)0.380.77 (0.54–1.09)0.140.78 (0.55–1.10)0.16
RecessiveAA/(GG + AG)14/26117/5331.68 (0.82–3.46)0.161.66 (0.73–3.79)0.231.60 (0.69–3.72)0.27
AdditiveAA/AG/GG14/75/18617/178/3550.97 (0.74–1.25)0.790.88 (0.66–1.18)0.400.88 (0.65–1.19)0.41

Model 1 is not adjusted for other factors; model 2 is adjusted for BMI; model 3 is adjusted for BMI, uric acid, metabolic syndrome, smoking, and drinking.

We further evaluated the effect of FTO gene polymorphisms on NAFLD risk stratified by BMI. When BMI ≥ 25, significant correlations were found between genotypes of rs1121980, rs9940128 and susceptibility to NAFLD (Table 3). The AA + AG genotypes of rs1121980 and rs9940128 were associated with a decreased risk of NAFLD, compared with the GG genotype, respectively (rs1121980: adjusted OR = 0.62, 95% CI = 0.39–0.99, P = 0.044; rs9940128: adjusted OR = 0.61, 95% CI = 0.38–0.97, P = 0.038). No significant correlations were observed between the nine SNPs of FTO and NAFLD risk in all genetic models when BMI < 25 (Table S1).

Table 3

Distribution of the genotypes of FTO and their associations with risk of NAFLD when BMI ≥ 25

Genotype distribution, N (%)Dominant modelRecessive modelAdditive model
NAFLDControlsORa (95% CI)PORa (95% CI)PORa (95% CI)P
rs11219800.62 (0.39–0.99)0.0444.07 (0.88–18.83)0.140.81 (0.55–1.21)0.31
GG133 (69.3)78 (59.1)
AG47 (24.5)52 (39.4)
AA12 (6.2)2 (1.5)
rs14771960.71 (0.44–1.14)0.162.06 (0.72–5.90)0.160.90 (0.62–1.30)0.56
GG130 (68.1)80 (60.6)
AG47 (24.6)47 (35.6)
AA14 (7.3)5 (3.8)
rs178174490.67 (0.41–1.11)0.122.15 (0.43–10.81)0.330.79 (0.51–1.22)0.29
TT144 (75)89 (67.4)
GT41 (21.4)41 (31.1)
GG7 (3.6)2 (1.5)
rs71955390.90 (0.51–1.59)0.71——1.00 (0.59–1.71)0.99
AA156 (81.7)106 (80.3)
GA32 (16.8)26 (19.7)
GG3 (1.6)0 (0)
rs80501360.70 (0.43–1.15)0.162.15 (0.43–10.81)0.330.82 (0.53–1.26)0.36
CC144 (75)144 (75)
AC41 (21.4)41 (21.4)
AA7 (3.6)2 (1.5)
rs80615181.21 (0.76–1.95)0.421.35 (0.77–2.37)0.291.19 (0.87–1.62)0.27
AA63 (32.8)49 (37.4)
GA85 (44.3)58 (44.3)
GG44 (22.9)24 (18.3)
rs99212551.30 (0.71–2.36)0.391.91 (0.19–19.55)0.571.29 (0.75–2.24)0.35
TT150 (80.2)106 (83.5)
CT34 (18.2)20 (15.8)
CC3 (1.6)3 (1.6)
rs99396090.69 (0.42–1.14)0.152.12 (0.42–10.66)0.340.81 (0.52–1.24)0.33
TT144 (75)89 (67.9)
AT41 (21.4)40 (30.5)
AA7 (3.6)2 (1.5)
rs99401280.61 (0.38–0.97)0.0384.07 (0.88–18.83)0.140.81 (0.54–1.19)0.28
GG132 (68.8)77 (58.3)
AG48 (25)53 (40.1)
AA12 (6.2)2 (1.5)
  1. a

    Adjusted for BMI, uric acid, metabolic syndrome, smoking, and drinking.

Table S1

Distribution of the genotypes of FTO and their associations with risk of NAFLD when BMI < 25

Genotype distribution, N (%)Dominant modelRecessive modelAdditive model
NAFLDControlsORa (95% CI)PORa (95% CI)PORa (95% CI)P
rs11219800.98 (0.57–1.69)0.950.62 (0.13–2.97)0.530.94 (0.59–1.50)0.79
GG53 (64.6)279 (66.9)
AG27 (32.9)124 (29.7)
AA2 (2.4)14 (3.4)
rs14771961.38 (0.81–2.33)0.242.39 (0.57–10.10) 0.261.40 (0.88–2.24)0.16
GG49 (59.8)273 (65.8)
AG30 (36.6)133 (32)
AA3 (3.7)9 (2.2)
rs178174490.81 (0.44–1.49)0.500.49 (0.05–4.44)0.490.80 (0.46–1.39)0.43
TT62 (75.6)317 (75.8)
GT19 (23.2)94 (22.5)
GG1 (1.2)7 (1.7)
rs71955390.59 (0.29–1.23)0.141.41 (0.15–13.56) 0.770.66 (0.33–1.29)0.20
AA71 (86.6)331 (79.6)
GA10 (12.2)78 (18.8)
GG1 (1.2)7 (1.7)
rs80501360.81 (0.44–1.49)0.500.74 (0.08–6.90) 0.780.82 (0.47–1.44)0.49
CC62 (75.6)317 (76.0)
AC19 (23.2)94 (22.5)
AA1 (1.2)6 (1.4)
rs80615181.16 (0.67–2.02)0.591.19 (0.59–2.39) 0.621.13 (0.77–1.66)0.53
AA29 (35.4)157 (37.6)
GA40 (48.8)193 (46.3)
GG13 (15.8)67 (16.1)
rs99212550.81 (0.42–1.55)0.53––0.79 (0.42–1.48)0.45
TT65 (81.2)315 (78.5)
CT15 (18.8)83 (20.7)
CC0 (0)3 (0.8)
rs99396090.84 (0.46–1.54)0.570.73 (0.08–6.82)0.770.84 (0.48–1.48)0.55
TT62 (75.6)317 (76.2)
AT19 (23.2)93 (22.4)
AA1 (1.2)6 (1.4)
rs99401280.97 (0.57–1.67)0.920.61 (0.13–2.92)0.510.93 (0.58–1.49)0.76
GG53 (64.6)278 (66.5)
AG27 (32.9)125 (29.9)
AA2 (2.4)15 (3.6)
  1. a

    Adjusted for BMI, uric acid, metabolic syndrome, smoking, and drinking.

Linkage disequilibrium information on the nine SNPs is shown in Table S2. Haplotype analysis of nine SNPs in FTO was performed to evaluate the effect of haplotypes on NAFLD risk, and no significant relationships were found in all subjects or those with BMI ≥ 25 or < 25 (Tables S3 and S4). The analysis of the associations between the nine SNPs and BMI is reported in Table S5, and no associations were found in the subject with NAFLD or the controls (all P > 0.05).

Table S2

Linkage disequilibrium between pairs of the nine SNPs

rs1477196rs17817449rs7195539rs8050136rs8061518rs9921255rs9939609rs9940128
rs1121980D = 0.998D = 1.000D = 0.325D = 1.000D = 0.134D = 0.018D = 1.000D = 1.000
r2 = 0.056r2 = 0.697r2 = 0.052r2 = 0.686r2 = 0.003r2 = 0.000r2 = 0.693r2 = 0.980
rs1477196D = 0.994D = 0.356D = 0.994D = 0.279D = 0.033D = 0.994D = 0.998
r2 = 0.039r2 = 0.003r2 = 0.038r2 = 0.027r2 = 0.000r2 = 0.038r2 = 0.057
rs17817449D = 0.144D = 1.000D = 0.041D = 0.124D = 1.000D = 1.000
r2 = 0.015r2 = 0.985r2 = 0.000r2 = 0.000r2 = 1.000r2 = 0.683
rs7195539D = 0.147D = 0.999D = 0.103D = 0.140 D = 0.320
r2 = 0.015r2 = 0.079r2 = 0.010r2 = 0.014r2 = 0.049
rs8050136D = 0.038D = 0.100D = 1.000D = 1.000
r2 = 0.000r2 = 0.000r2 = 1.000r2 = 0.673
rs8061518D = 0.063D = 0.045D = 0.133
r2 = 0.000r2 = 0.000r2 = 0.003
rs9921255D = 0.096D = 0.051
r2 = 0.000r2 = 0.000
rs9939609D = 1.000
r2 = 0.680
Table S3

Association analysis of haplotypes derived from polymorphic sites using genotype data.

Haplotype123456789OR (95% CI)P1OR (95% CI)P2OR (95% CI)P3
H1GGTACGTTG0.76 (0.55–1.06)0.110.84 (0.58–1.22)0.360.86 (0.58–1.26)0.43
H2GATACGTTG0.88 (0.59–1.30)0.520.93 (0.60–1.45)0.750.88 (0.56–1.39)0.58
H3GATACATTG0.98 (0.56–1.71)0.931.21 (0.63–2.33)0.561.32 (0.67–2.59)0.43
H4AGGAAGTAA0.97 (0.55–1.72)0.921.22 (0.60–2.48)0.591.16 (0.57–2.39)0.68
H5AGGAAATAA0.85 (0.46–1.58)0.620.99 (0.47–2.09)0.981.04 (0.47–2.28)0.92
H6GGTGCATTG2.37 (0.90–6.23)0.082.64 (0.86–8.14)0.092.43 (0.78–7.56)0.13
H7GGTACGCTG1.21 (0.45–3.29)0.711.20 (0.43–3.34)0.731.13 (0.40–3.19)0.82
H8GGTACACTG0.75 (0.26–2.19)0.600.77 (0.23–2.61)0.680.76 (0.21–2.72)0.67
H9AGGGAATAA0.94 (0.42–2.12)0.881.16 (0.44–3.08)0.771.21 (0.45–3.27)0.70
H10AGTGCATTA0.67 (0.30–1.52)0.340.69 (0.28–1.72)0.430.68 (0.27–1.74)0.42
H11AGTACATTA1.75 (0.59–5.16)0.311.31 (0.40–4.29)0.651.34 (0.40–4.52)0.64
H12GGTGCACTG1.06 (0.33–3.40)0.921.29 (0.37–4.50)0.691.35 (0.39–4.64)0.22
H13GATGCATTG0.51 (0.13–2.03)0.340.37 (0.08–1.62)0.190.40 (0.09–1.72)1.00

1, rs1121980; 2, rs1477196; 3, rs17817449; 4, rs7195539; 5, rs8050136; 6, rs8061518; 7, rs9921255; 8, rs9939609; 9, rs9940128; P1 value is not adjusted for other factors; P2 value is adjusted for BMI; P3 is adjusted for BMI, uric acid, metabolic syndrome, smoking, and drinking.

Table S4

Association analysis of haplotypes derived from polymorphic sites using genotype data stratified by BMI

Haplotype123456789OR (95% CI)P1OR (95% CI)P2OR (95% CI)P3
BMI ≥ 25
H1GGTACGTTG0.69 (0.42–1.13)0.140.69 (0.42–1.14)0.140.69 (0.41–1.16)0.16
H2GATACGTTG1.17 (0.65–2.09)0.601.17 (0.65–2.10)0.611.14 (0.63–2.04)0.67
H3GATACATTG1.03 (0.50–2.13)0.931.04 (0.50––2.17)0.911.03 (0.50–2.14)0.93
H4AGGAAATAA0.76 (0.33–1.76)0.530.78 (0.33–1.83)0.560.73 (0.30–1.74)0.47
H5AGGAAGTAA1.26 (0.57–2.79)0.571.25 (0.55–2.82)0.601.40 (0.61–3.20)0.43
H6GGTACACTG1.25 (0.32–4.84)0.741.22 (0.32–4.68)0.771.23 (0.34–4.41)0.75
H7AGGGAATAA1.34 (0.36–4.96)0.661.39 (0.37–5.18)0.631.18 (0.31–4.46)0.81
H8GGTGCATTG0.52 (0.15–1.82)0.300.49 (0.14–1.75)0.270.54 (0.15–1.88)0.33
H9AGTGCATTA0.77 (0.19–3.06)0.710.83 (0.20–3.39)0.800.87 (0.21–3.55)0.85
H10GGTACGCTG0.66 (0.16–2.77)0.570.64 (0.15–2.75)0.550.62 (0.15–2.61)0.51
BMI < 25
H1GGTACGTTG1.11 (0.62–1.98)0.731.11 (0.60–2.06)0.730.98 (0.51–1.89)0.96
H2GATACGTTG0.65 (0.36–1.17)0.150.70 (0.37–1.31)0.260.55 (0.28–1.06)0.08
H3AGGAAGTAA1.53 (0.47–4.98)0.481.58 (0.52–4.80)0.421.45 (0.46–4.53)0.52
H4GATACATTG1.27 (0.37–4.34)0.701.17 (0.34–4.05)0.811.42 (0.40–5.05)0.59
H5AGGAAATAA0.60 (0.19–1.84)0.370.79 (0.25–2.54)0.700.72 (0.20–2.54)0.61
H6GGTGCATTG3.09 (0.44–22.01)0.262.57 (0.28–23.43)0.402.63 (0.29–24.27)0.39
H7GGTACGCTG0.55 (0.17–1.83)0.330.67 (0.19–2.39)0.532.21 (0.36–13.58)0.39
H8GGTACACTG1.92 (0.36–10.34)0.452.46 (0.43–13.97)0.310.52 (0.14–1.97)0.33
H9AGTACATTA1.05 (0.29–3.84)0.940.92 (0.24–3.57)0.900.86 (0.22–3.44)0.84
H10AGGGAATAA0.96 (0.24–3.95)0.961.07 (0.26–4.32)0.931.20 (0.28–5.06)0.81
H11AGTGCATTA1.34 (0.22–8.17)0.751.48 (0.22–9.74)0.690.98 (0.16–6.21)0.98
H12GATGCATTG0.59 (0.10–3.36)0.550.44 (0.05–3.50)0.440.43 (0.06–3.25)0.41
H13AGTACGTTA0.29 (0.04–1.87)0.190.37 (0.06–2.41)0.300.24 (0.04–1.58)0.14

1, rs1121980; 2, rs1477196; 3, rs17817449; 4, rs7195539; 5, rs8050136; 6, rs8061518; 7, rs9921255; 8, rs9939609; 9, rs9940128; P1 value is not adjusted for other factors; P2 value is adjusted for BMI; P3 is adjusted for BMI, uric acid, metabolic syndrome, smoking, and drinking.

Table S5

Association between SNPs and BMI investigated in NAFLD and control groups

NAFLD groupControl group
nM ± SDPnM ± SDP
rs1121980GG18026.47 ± 2.8620.4535722.43 ± 2.9820.14
AG7726.10 ± 2.83017622.97 ± 3.348
AA1726.94 ± 2.2211622.13 ± 3.096
rs1477196GG18726.43 ± 2.8480.5335322.57 ± 3.0690.95
GA7426.18 ± 2.78518022.66 ± 3.238
AA1427.07 ± 2.5151422.64 ± 2.818
rs17817449TT20726.34 ± 2.8590.5540622.43 ± 2.9950.16
GT6026.43 ± 2.69713522.43 ± 3.406
GG827.45 ± 2.534922.89 ± 3.371
rs7195539AA22826.33 ± 2.8320.3643722.59 ± 3.1100.07
GA4226.87 ± 2.80710422.80 ± 3.120
GG425.19 ± 1.571720.00 ± 2.380
rs8050136CC20726.34 ± 2.8590.5540722.44 ± 3.0030.16
AC6026.43 ± 2.69713423.04 ± 3.375
AA827.45 ± 2.534822.75 ± 3.576
rs8061518AA9226.36 ± 3.1380.9420622.42 ± 3.0010.60
GA12626.37 ± 2.68125122.71 ± 3.265
GG5726.52 ± 2.5789122.62 ± 2.947
rs9921255TT21526.30 ± 2.8460.5842122.63 ± 3.1980.73
CT5026.59 ± 2.42110322.40 ± 2.795
CC327.66 ± 2.346423.25 ± 3.304
rs9939609TT20726.34 ± 2.8590.5540622.43 ± 2.9950.16
AT6026.43 ± 2.69713323.03 ± 3.387
AA827.45 ± 2.534822.75 ± 3.576
rs9940128GG18626.40 ± 2.8290.6135522.41 ± 2.9500.08
AG7526.25 ± 2.84017823.00 ± 3.383
AA1427.07 ± 2.5151721.88 ± 3.160

The analysis of the associations between the nine SNPs and the severity of NAFLD is reported in Table 4. Rs1477196 was associated with the severity of NAFLD, and carriers of the AA genotype showed approximately a 2.95-fold increased risk of the moderate–severe NAFLD, compared with the AG + GG carriers (OR = 2.95, 95% CI = 1.09–7.94, P = 0.034). The other SNPs were not related to the severity of NAFLD (Table 4).

Table 4

Distribution of the genotypes of FTO and severity of the disease studied in the NAFLD group

Genotype frequencies, N
MildModerate–severeOR (95% CI)P
rs1121980
Dominant(AA + AG)/GG54/12720/600.62 (0.35–1.12)0.11
RecessiveAA/(AG + GG)10/1812/780.39 (0.09–1.79)0.18
AdditiveAA/AG/GG10/44/1272/18/600.64 (0.39–1.06)0.071
rs1477196
Dominant(AA + AG)/GG66/12828/521.04 (0.60–1.80)0.88
RecessiveAA/(AG + GG)8/1869/712.95 (1.09–7.94)0.034
AdditiveAA/AG/GG8/58/1289/19/521.24 (0.82–1.89)0.32
rs17817449
Dominant(GG + TG)/TT52/14316/640.69 (0.37–1.29)0.24
RecessiveGG/(TG + TT)7/1881/790.34 (0.04–2.81)0.26
AdditiveGG/GT/TT7/45/1431/15/640.69 (0.39–1.20)0.17
rs7195539
Dominant(AG + GG)/AA31/16316/651.21 (0.61–2.40)0.58
RecessiveGG/(AA + AG)4/1901/790.34 (0.04–2.81)0.095
AdditiveGG/GA/AA4/27/1631/15/641.04 (0.56–1.92)0.90
rs8050136
Dominant(AA + AC)/CC52/14316/640.69 (0.37–1.29)0.24
RecessiveAA/(AC + CC)7/1881/790.34 (0.04–2.81)0.26
AdditiveAA/AC/CC7/45/1431/15/640.69 (0.39–1.20)0.17
rs8061518
Dominant(AG + GG)/AA130/6553/270.98 (0.57–1.70)0.95
RecessiveGG/(AA + AG)41/15416/640.94 (0.49–1.79)0.85
AdditiveGG/AG/AA41/89/6516/37/270.97 (0.68–1.39)0.88
rs9921255
Dominant(TC + CC)/TT35/15418/611.30 (0.68–2.47)0.43
RecessiveCC/(TC + TT)2/1871/781.20 (0.11–13.41)0.88
AdditiveCC/TC/TT2/33/1541/17/611.26 (0.70–2.27)0.45
rs9939609
Dominant(AA + TA)/TT52/14316/640.69 (0.37–1.29)0.24
RecessiveAA/(TT + TA)7/1881/790.34 (0.04–2.81)0.26
AdditiveAA/AT/TT7/45/1431/15/640.69 (0.39–1.20)0.17
rs9940128
Dominant(AA + AG)/GG68/12721/590.66 (0.37–1.19)0.16
RecessiveAA/(GG + AG)12/1832/780.39 (0.09–1.79)0.18
AdditiveAA/AG/GG12/56/1272/19/590.67 (0.41–1.10)0.10

4 Discussion

Although several risk factors for NAFLD [22,23] had already been determined, the discovery of new genetic markers will advance the identification of individuals susceptible to the development of this disease. This might help ease the burden of NAFLD on individuals and society through the use of screening and proper interventions in those at risk of developing NAFLD. Previous studies suggested that FTO gene polymorphisms were commonly correlated with metabolic disorders, especially central obesity, low-density lipoprotein (LDL), insulin resistance, and hypertriglyceridemia [24], which are tightly related to NAFLD [25]. Therefore, FTO gene polymorphisms might have important implications related to NAFLD.

In this study, we performed an association analysis of NAFLD with nine FTO gene polymorphisms that have been previously found to be associated with metabolic disorders. Our study found that FTO rs1477196 was significantly associated with NAFLD risk in a Chinese male population and carriers of the AA genotype increased the NAFLD risk, in comparison with AG + GG carriers. Besides, rs1477196 was also associated with the severity of NAFLD. Previous study [26] reported that rs1477196 A allele was associated with an increased risk of obesity that was closely related to NAFLD, which indirectly supported our results. Nevertheless, after further adjustments for BMI, the relationship of rs1477196 and NAFLD weakened, suggesting that the relationship might be partly dependent on BMI. We further evaluated the relationships of FTO gene polymorphisms with NAFLD risk stratified by BMI. Our results found that in obese men, rs1121980 and rs9940128 were associated with NAFLD risk in the dominant model after adjusting for BMI, uric acid, metabolic syndrome, smoking, and drinking. No significant correlations were observed between FTO gene polymorphisms and NAFLD risk when BMI < 25. These results indicated the interaction between FTO gene polymorphisms and obesity for NAFLD risk.

Moreover, an animal model study of FTO expression in rat liver with NAFLD proposed that overexpression of FTO enhances oxidative stress and lipid accumulation [27]. Oxidative stress is the core feature of the pathogenesis of NAFLD and plays a critical role in the progress of this disease [28]. Notwithstanding the mechanism of FTO gene on lipid overaccumulation in liver has not been previously studied, FTO overexpression increases the rate of lipogenesis [29]. Coincidentally, another study on fatty liver disease in HIV-infected patients also put forward a similar opinion [30]. They proposed that FTO gene variations might be independent predictors of fatty liver disease in HIV-infected patients. To a certain degree, the results that the FTO gene polymorphisms are associated with NAFLD risk in our study are in agreement with the literature and highlight the role of the gene in metabolic disorder in Chinese population.

There were some limitations in our study. First, only males were included in this study, so we should be prudent when extrapolating the findings to women, and studies on females should be considered in the future. Second, the sample size of this study is moderate, which limited the subsequent stratified analysis, such as the severity of NAFLD. Third, our study included nine SNPs and multiple testing might increase the false-positive (type I error) rate under nominal significance thresholds. Therefore, large population-based prospective studies are needed to elucidate the impact of FTO SNPs on NAFLD risk.

5 Conclusion

Our results demonstrated that the FTO gene was related to the presence and severity of NAFLD in a Chinese male population, and the relationships of the tested SNPs with NAFLD are most probably mediated by BMI. In order to better uncover the relationships between FTO gene polymorphisms and NAFLD, further investigations would be required to assess the clinical consequences of FTO affecting hepatic fatty infiltration in different races, particularly among those who are overweight or obese.

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Acknowledgments

This study was supported by the Foundation for Young and Middle-Aged Teachers’ Basic Ability Enhancement Project of Guangxi (grant no. KY2016YB074) and the Guangxi Natural Science Foundation (grant no. 2016GXNSFAA380152).

  1. Conflict of interest: The authors state no conflict of interest.

  2. Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

[1] Angulo P, Lindor KD. Non-alcoholic fatty liver disease. J Gastroenterol Hepatol. 2002;17(Suppl):186–90.10.1046/j.1440-1746.17.s1.10.xSearch in Google Scholar PubMed

[2] Kumar R, Priyadarshi RN, Anand U. Non-alcoholic fatty liver disease: growing burden, adverse outcomes and associations. J Clin Transl Hepatol. 2020;8(1):76–86.10.14218/JCTH.2019.00051Search in Google Scholar PubMed PubMed Central

[3] Gerken T, Girard CA, Tung YC, Webby CJ, Saudek V, Hewitson KS, et al. The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science. 2007;318(5855):1469–72.10.1126/science.1151710Search in Google Scholar PubMed PubMed Central

[4] Gholamalizadeh M, Jarrahi AM, Akbari ME, Rezaei S, Doaei S, Mokhtari Z, et al. The possible mechanisms of the effects of IRX3 gene on body weight: an overview. Arch Med Sci Atheroscler Dis. 2019;4:225–30.10.5114/amsad.2019.87545Search in Google Scholar PubMed PubMed Central

[5] Do R, Bailey SD, Desbiens K, Belisle A, Montpetit A, Bouchard C, et al. Genetic variants of FTO influence adiposity, insulin sensitivity, leptin levels, and resting metabolic rate in the Quebec Family Study. Diabetes. 2008;57(4):1147–50.10.2337/db07-1267Search in Google Scholar PubMed

[6] Elouej S, Belfki-Benali H, Nagara M, Lasram K, Attaoua R, Sallem OK, et al. Association of rs9939609 polymorphism with metabolic parameters and FTO risk haplotype among tunisian metabolic syndrome. Metab Syndr Relat Disord. 2016;14(2):121–8.10.1089/met.2015.0090Search in Google Scholar PubMed

[7] Xiao S, Zeng X, Fan Y, Su YX, Ma Q, Zhu J, et al. Gene polymorphism association with type 2 diabetes and related gene–gene and gene–environment interactions in a Uyghur population. Med Sci Monit. 2016;22:474–87.Search in Google Scholar

[8] Gonzalez JR, Gonzalez-Carpio M, Hernandez-Saez R, Vargas VS, Hidalgo GT, Rubio-Rodrigo M, et al. FTO risk haplotype among early onset and severe obesity cases in a population of western Spain. Obes (Silver Spring). 2012;20(4):909–15.10.1038/oby.2011.325Search in Google Scholar PubMed

[9] Kolackov K, Laczmanski L, Lwow F, Ramsey D, Zdrojowy-Wełna A, Tupikowska M, et al. The frequencies of haplotypes of FTO gene variants and their association with the distribution of body fat in non-obese poles. Adv Clin Exp Med. 2016;25(1):33–42.10.17219/acem/60645Search in Google Scholar PubMed

[10] Olza J, Ruperez AI, Gil-Campos M, Leis R, Fernandez-Orth D, Tojo R, et al. Influence of FTO variants on obesity, inflammation and cardiovascular disease risk biomarkers in Spanish children: a case-control multicentre study. BMC Med Genet. 2013;14:123.10.1186/1471-2350-14-123Search in Google Scholar PubMed PubMed Central

[11] Ramya K, Radha V, Ghosh S, Majumder PP, Mohan V. Genetic variations in the FTO gene are associated with type 2 diabetes and obesity in south Indians (CURES-79). Diabetes Technol Ther. 2010;13(1):33–42.10.1089/dia.2010.0071Search in Google Scholar PubMed

[12] Haupt A, Thamer C, Machann J, Kirchhoff K, Stefan N, Tschritter O, et al. Impact of variation in the FTO gene on whole body fat distribution, ectopic fat, and weight loss. Obes (Silver Spring). 2008;16(8):1969–72.10.1038/oby.2008.283Search in Google Scholar

[13] Dongiovanni P, Rametta R, Meroni M, Valenti L. The role of insulin resistance in nonalcoholic steatohepatitis and liver disease development – a potential therapeutic target? Expert Rev Gastroenterol Hepatol. 2016;10(2):229–42.10.1586/17474124.2016.1110018Search in Google Scholar

[14] Stefan N, Häring HU, Cusi K. Non-alcoholic fatty liver disease: causes, diagnosis, cardiometabolic consequences, and treatment strategies. Lancet Diabetes Endocrinol. 2019;7(4):313–24.10.1016/S2213-8587(18)30154-2Search in Google Scholar

[15] Tan AH, Gao Y, Yang XB, Zhang HY, Qin X, Mo LJ, et al. Low serum osteocalcin level is a potential marker for metabolic syndrome: results from a Chinese male population survey. Metabolism. 2011;60(8):1186–92.10.1016/j.metabol.2011.01.002Search in Google Scholar PubMed

[16] Wang XL, Liu ZP, Wang K, Wang ZW, Sun X, Zhong L, et al. Additive effects of the risk alleles of PNPLA3 and TM6SF2 on non-alcoholic fatty liver disease (NAFLD) in a Chinese population. Front Genet. 2016;7:140.10.3389/fgene.2016.00140Search in Google Scholar PubMed PubMed Central

[17] Li H, Chen YZ, Tian X, Hong Y, Chen CL, Sharokh NK, et al. Comparison of clinical characteristics between lean and obese nonalcoholic fatty liver disease in the northeast Chinese population. Arch Med Sci Atheroscler Dis. 2019;4:191–5.10.5114/amsad.2019.87122Search in Google Scholar PubMed PubMed Central

[18] Reddavide R, Cisternino AM, Inguaggiato R, Rotolo O, Zinzi I, Veronese N, et al. Non-alcoholic fatty liver disease is associated with higher metabolic expenditure in overweight and obese subjects: a case-control study. Nutrients. 2019;11(8):1830.10.3390/nu11081830Search in Google Scholar PubMed PubMed Central

[19] Tian GX, Sun Y, Pang CJ, Tan AH, Gao Y, Zhang HY, et al. Oestradiol is a protective factor for non-alcoholic fatty liver disease in healthy men. Obes Rev. 2012;13(4):381–7.10.1111/j.1467-789X.2011.00978.xSearch in Google Scholar PubMed

[20] Tan AH, Sun JL, Xia N, Qin X, Hu YL, Zhang SJ, et al. A genome-wide association and gene-environment interaction study for serum triglycerides levels in a healthy Chinese male population. Hum Mol Genet. 2012;21(7):1658–64.10.1093/hmg/ddr587Search in Google Scholar PubMed

[21] Sole X, Guino E, Valls J, Iniesta R, Moreno V. SNPStats: a web tool for the analysis of association studies. Bioinformatics. 2006;22(15):1928–9.10.1093/bioinformatics/btl268Search in Google Scholar PubMed

[22] Liu JJ, Chen YY, Mo ZN, Tian GX, Tan AH, Gao Y, et al. Relationship between serum osteocalcin levels and non-alcoholic fatty liver disease in adult males, South China. Int J Mol Sci. 2013;14(10):19782–91.10.3390/ijms141019782Search in Google Scholar PubMed PubMed Central

[23] Wijarnpreecha K, Panjawatanan P, Lekuthai N, Thongprayoon C, Cheungpasitporn W, Ungprasert P. Hyperuricaemia and risk of nonalcoholic fatty liver disease: a meta-analysis. Liver Int. 2017;37(6):906–18.10.1111/liv.13329Search in Google Scholar PubMed

[24] Elouej S, Nagara M, Attaoua R, Sallem OK, Rejeb I, Hsouna S, et al. Association of genetic variants in the FTO gene with metabolic syndrome: a case-control study in the Tunisian population. J Diabetes Complicat. 2016;30(2):206–11.10.1016/j.jdiacomp.2015.11.013Search in Google Scholar PubMed

[25] Marchesini G, Bugianesi E, Forlani G, Cerrelli F, Lenzi M, Manini R, et al. Nonalcoholic fatty liver, steatohepatitis, and the metabolic syndrome. Hepatology. 2003;37(4):917–23.10.1053/jhep.2003.50161Search in Google Scholar PubMed

[26] Rampersaud E, Mitchell BD, Pollin TI, Fu M, Shen HQ, O’Connell JR, et al. Physical activity and the association of common FTO gene variants with body mass index and obesity. Arch Intern Med. 2008;168(16):1791–7.10.1001/archinte.168.16.1791Search in Google Scholar PubMed PubMed Central

[27] Guo JJ, Ren W, Li AM, Ding Y, Guo WH, Su DM, et al. Fat mass and obesity-associated gene enhances oxidative stress and lipogenesis in nonalcoholic fatty liver disease. Dig Dis Sci. 2013;58(4):1004–9.10.1007/s10620-012-2516-6Search in Google Scholar PubMed

[28] Rolo AP, Teodoro JS, Palmeira CM. Role of oxidative stress in the pathogenesis of nonalcoholic steatohepatitis. Free Radic Biol Med. 2012;52(1):59–69.10.1016/j.freeradbiomed.2011.10.003Search in Google Scholar PubMed

[29] Bravard A, Lefai E, Meugnier E, Pesenti S, Disse E, Vouillarmet J, et al. FTO is increased in muscle during type 2 diabetes, and its overexpression in myotubes alters insulin signaling, enhances lipogenesis and ROS production, and induces mitochondrial dysfunction. Diabetes. 2011;60(1):258–68.10.2337/db10-0281Search in Google Scholar PubMed PubMed Central

[30] Nunez-Torres R, Macias J, Rivero-Juarez A, Neukam K, Merino D, Téllez F, et al. Fat mass and obesity-associated gene variations are related to fatty liver disease in HIV-infected patients. HIV Med. 2017;18(8):546–54.10.1111/hiv.12489Search in Google Scholar PubMed

Received: 2020-04-28
Revised: 2020-07-22
Accepted: 2020-07-24
Published Online: 2020-11-30

© 2020 Xuefen Chen et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  53. Coexisting flavonoids and administration route effect on pharmacokinetics of Puerarin in MCAO rats
  54. GeneXpert Technology for the diagnosis of HIV-associated tuberculosis: Is scale-up worth it?
  55. Circ_001569 regulates FLOT2 expression to promote the proliferation, migration, invasion and EMT of osteosarcoma cells through sponging miR-185-5p
  56. Lnc-PICSAR contributes to cisplatin resistance by miR-485-5p/REV3L axis in cutaneous squamous cell carcinoma
  57. BRCA1 subcellular localization regulated by PI3K signaling pathway in triple-negative breast cancer MDA-MB-231 cells and hormone-sensitive T47D cells
  58. MYL6B drives the capabilities of proliferation, invasion, and migration in rectal adenocarcinoma through the EMT process
  59. Inhibition of lncRNA LINC00461/miR-216a/aquaporin 4 pathway suppresses cell proliferation, migration, invasion, and chemoresistance in glioma
  60. Upregulation of miR-150-5p alleviates LPS-induced inflammatory response and apoptosis of RAW264.7 macrophages by targeting Notch1
  61. Long non-coding RNA LINC00704 promotes cell proliferation, migration, and invasion in papillary thyroid carcinoma via miR-204-5p/HMGB1 axis
  62. Neuroanatomy of melanocortin-4 receptor pathway in the mouse brain
  63. Lipopolysaccharides promote pulmonary fibrosis in silicosis through the aggravation of apoptosis and inflammation in alveolar macrophages
  64. Influences of advanced glycosylation end products on the inner blood–retinal barrier in a co-culture cell model in vitro
  65. MiR-4328 inhibits proliferation, metastasis and induces apoptosis in keloid fibroblasts by targeting BCL2 expression
  66. Aberrant expression of microRNA-132-3p and microRNA-146a-5p in Parkinson’s disease patients
  67. Long non-coding RNA SNHG3 accelerates progression in glioma by modulating miR-384/HDGF axis
  68. Long non-coding RNA NEAT1 mediates MPTP/MPP+-induced apoptosis via regulating the miR-124/KLF4 axis in Parkinson’s disease
  69. PCR-detectable Candida DNA exists a short period in the blood of systemic candidiasis murine model
  70. CircHIPK3/miR-381-3p axis modulates proliferation, migration, and glycolysis of lung cancer cells by regulating the AKT/mTOR signaling pathway
  71. Reversine and herbal Xiang–Sha–Liu–Jun–Zi decoction ameliorate thioacetamide-induced hepatic injury by regulating the RelA/NF-κB/caspase signaling pathway
  72. Therapeutic effects of coronary granulocyte colony-stimulating factor on rats with chronic ischemic heart disease
  73. The effects of yam gruel on lowering fasted blood glucose in T2DM rats
  74. Circ_0084043 promotes cell proliferation and glycolysis but blocks cell apoptosis in melanoma via circ_0084043-miR-31-KLF3 axis
  75. CircSAMD4A contributes to cell doxorubicin resistance in osteosarcoma by regulating the miR-218-5p/KLF8 axis
  76. Relationship of FTO gene variations with NAFLD risk in Chinese men
  77. The prognostic and predictive value of platelet parameters in diabetic and nondiabetic patients with sudden sensorineural hearing loss
  78. LncRNA SNHG15 contributes to doxorubicin resistance of osteosarcoma cells through targeting the miR-381-3p/GFRA1 axis
  79. miR-339-3p regulated acute pancreatitis induced by caerulein through targeting TNF receptor-associated factor 3 in AR42J cells
  80. LncRNA RP1-85F18.6 affects osteoblast cells by regulating the cell cycle
  81. MiR-203-3p inhibits the oxidative stress, inflammatory responses and apoptosis of mice podocytes induced by high glucose through regulating Sema3A expression
  82. MiR-30c-5p/ROCK2 axis regulates cell proliferation, apoptosis and EMT via the PI3K/AKT signaling pathway in HG-induced HK-2 cells
  83. CTRP9 protects against MIA-induced inflammation and knee cartilage damage by deactivating the MAPK/NF-κB pathway in rats with osteoarthritis
  84. Relationship between hemodynamic parameters and portal venous pressure in cirrhosis patients with portal hypertension
  85. Long noncoding RNA FTX ameliorates hydrogen peroxide-induced cardiomyocyte injury by regulating the miR-150/KLF13 axis
  86. Ropivacaine inhibits proliferation, migration, and invasion while inducing apoptosis of glioma cells by regulating the SNHG16/miR-424-5p axis
  87. CD11b is involved in coxsackievirus B3-induced viral myocarditis in mice by inducing Th17 cells
  88. Decitabine shows anti-acute myeloid leukemia potential via regulating the miR-212-5p/CCNT2 axis
  89. Testosterone aggravates cerebral vascular injury by reducing plasma HDL levels
  90. Bioengineering and Biotechnology
  91. PL/Vancomycin/Nano-hydroxyapatite Sustained-release Material to Treat Infectious Bone Defect
  92. The thickness of surface grafting layer on bio-materials directly mediates the immuno-reacitivity of macrophages in vitro
  93. Silver nanoparticles: synthesis, characterisation and biomedical applications
  94. Food Science
  95. Bread making potential of Triticum aestivum and Triticum spelta species
  96. Modeling the effect of heat treatment on fatty acid composition in home-made olive oil preparations
  97. Effect of addition of dried potato pulp on selected quality characteristics of shortcrust pastry cookies
  98. Preparation of konjac oligoglucomannans with different molecular weights and their in vitro and in vivo antioxidant activities
  99. Animal Sciences
  100. Changes in the fecal microbiome of the Yangtze finless porpoise during a short-term therapeutic treatment
  101. Agriculture
  102. Influence of inoculation with Lactobacillus on fermentation, production of 1,2-propanediol and 1-propanol as well as Maize silage aerobic stability
  103. Application of extrusion-cooking technology in hatchery waste management
  104. In-field screening for host plant resistance to Delia radicum and Brevicoryne brassicae within selected rapeseed cultivars and new interspecific hybrids
  105. Studying of the promotion mechanism of Bacillus subtilis QM3 on wheat seed germination based on β-amylase
  106. Rapid visual detection of FecB gene expression in sheep
  107. Effects of Bacillus megaterium on growth performance, serum biochemical parameters, antioxidant capacity, and immune function in suckling calves
  108. Effects of center pivot sprinkler fertigation on the yield of continuously cropped soybean
  109. Special Issue On New Approach To Obtain Bioactive Compounds And New Metabolites From Agro-Industrial By-Products
  110. Technological and antioxidant properties of proteins obtained from waste potato juice
  111. The aspects of microbial biomass use in the utilization of selected waste from the agro-food industry
  112. Special Issue on Computing and Artificial Techniques for Life Science Applications - Part I
  113. Automatic detection and segmentation of adenomatous colorectal polyps during colonoscopy using Mask R-CNN
  114. The impedance analysis of small intestine fusion by pulse source
  115. Errata
  116. Erratum to “Diagnostic performance of serum CK-MB, TNF-α and hs-CRP in children with viral myocarditis”
  117. Erratum to “MYL6B drives the capabilities of proliferation, invasion, and migration in rectal adenocarcinoma through the EMT process”
  118. Erratum to “Thermostable cellulase biosynthesis from Paenibacillus alvei and its utilization in lactic acid production by simultaneous saccharification and fermentation”
https://doi.org/10.1515/biol-2020-0081
Keywords for this article
FTO gene; nonalcoholic fatty liver disease; SNPs; obesity
Creative Commons
BY 4.0

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  117. Erratum to “MYL6B drives the capabilities of proliferation, invasion, and migration in rectal adenocarcinoma through the EMT process”
  118. Erratum to “Thermostable cellulase biosynthesis from Paenibacillus alvei and its utilization in lactic acid production by simultaneous saccharification and fermentation”
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