IGF1 rs5742612多态性与代谢功能障碍相关脂肪性肝病发病风险的关联研究
Association between IGF1 rs5742612 Polymorphism and the Risk of Metabolic Dysfunction-Associated Fatty Liver Disease
DOI: 10.12677/acm.2025.152520, PDF, HTML, XML,   
作者: 林于蕾:青岛大学青岛市市立医院感染性疾病科,山东 青岛;赵真真*:青岛大学青岛市市立医院临床研究中心,山东 青岛
关键词: 非酒精性脂肪性肝病代谢功能障碍相关脂肪性肝病IGF1基因多态性Non-Alcoholic Fatty Liver Disease Metabolic Dysfunction-Associated Steatotic Liver Disease IGF1 Gene Polymorphisms
摘要: 目的:研究IGF1 rs5742612位点的基因多态性与中国青岛地区汉族人群中MASLD发病风险之间的相关性。方法:纳入2022年12月到2023年12月于青岛市市立医院就诊的确诊为MASLD的中国汉族患者205人作为研究的病例组;同时纳入130名健康体检者作为对照组。收集纳入研究的患者的基本临床信息,进行生化指标的临床检测及基因组DNA的提取和IGF1 rs5742612位点基因型测定。利用χ2检验来检验两组间基因型频率和等位基因频率是否存在差异。基于显性和隐性模型,采用Logistic回归分析基因型和等位基因与疾病发生风险的关联。结果:IGF1 rs5742612位点基因型频率(χ2 = 0.286, P = 0.867)和等位基因频率(χ2 = 0.083, P = 0.773)在两组之间的分布无统计学差异。显性和隐性模型均提示该位点与MASLD之间关联不存在统计学意义(P均 < 0.05)。不同等位基因携带者基本信息及生化指标间无统计学差异(P均 > 0.05)。结论:IGF1 rs5742612多态性与MASLD发病无显著相关性。
Abstract: Objective: To investigate the correlation between genetic polymorphisms at the IGF1 rs5742612 locus and the risk of developing MASLD in the Han Chinese population in Qingdao, China. Methods: A total of 205 Chinese Han patients diagnosed with MASLD who attended Qingdao Municipal Hospital from December 2022 to December 2023 were included as the case group of the study;130 healthy medical check-ups were also included as the control group. The basic clinical information of the patients included in the study was collected, and clinical tests of biochemical indexes as well as genomic DNA extraction and genotyping at the IGF1 rs5742612 locus were performed. The χ2 test was used to test whether there were differences in genotype frequencies and allele frequencies between the two groups. Based on the dominant and recessive models, logistic regression was used to analyse the association between genotype and allele and the risk of disease occurrence. Results: The distribution of genotype frequencies (χ2 = 0.286, P = 0.867) and allele frequencies (χ2 = 0.083, P = 0.773) at the IGF1 rs5742612 locus were not statistically different between the two groups. Both dominant and recessive models suggested that the association between this locus and MASLD was not statistically significant (both P < 0.05). There was no statistical difference between the basic information and biochemical indexes of different allele carriers (all P > 0.05). Conclusion: There was no significant correlation between IGF1 rs5742612 polymorphism and the development of MASLD.
文章引用:林于蕾, 赵真真. IGF1 rs5742612多态性与代谢功能障碍相关脂肪性肝病发病风险的关联研究[J]. 临床医学进展, 2025, 15(2): 1636-1645. https://doi.org/10.12677/acm.2025.152520

1. 引言

非酒精性脂肪肝病(Non-alcoholic fatty liver disease, NAFLD)这一术语最初由Ludwig等人在1980年提出,用以描述在排除酒精消费和其他已知肝脏损伤因素后,肝脏内脂肪异常积聚的病理状态[1]。随后,代谢功能障碍相关脂肪性肝病(Metabolic dysfunction-associated steatotic liver disease, MASLD)的概念在2019年被提出,并在2023年的欧洲肝脏研究协会(EASL)大会上正式宣布,旨在取代NAFLD这一术语。MASLD的定义更加全面,它指的是在肝脏脂肪变性的同时,至少存在以下五种心血管代谢风险因素中的一种:高血压、糖尿病、高甘油三酯血症、低高密度脂蛋白胆固醇血症和肥胖[2]。代谢综合征(MetS)是一组风险因素,包括高血压、高血糖、血脂异常和腹型肥胖。在MASLD的发病机制中,胰岛素抵抗(insulin resistance, IR)起着关键作用,它导致游离脂肪酸在肝细胞内积聚,引发脂毒性,进而损害肝细胞[3]。IR、MetS与MASLD之间存在密切的相互关系[4],它们在疾病的发生和发展中扮演着重要角色。全基因组关联研究(GWAS)和广泛的基础实验研究已经确立了I148M PNPLA3变体、TM6SF2、HSD17B13和MBOAT7等位点与MASLD的发病机制及其肝纤维化进展之间的显著相关性[5]-[9]。此外,胰岛素抵抗(IR)与易感基因及特定遗传位点之间的关联也得到了众多现有研究的支持,涉及的遗传标记包括MIR148A基因的rs4722551多态性位点、ARL15基因的rs4865796多态性位点以及PC-1基因的121Q变异等[10] [11]

胰岛素样生长因子1 (insulin-like growth factor 1, IGF1)是一种由70个氨基酸构成的单链多肽,其基因位于染色体12q22-q24区域[12],并包含6个外显子。IGF1基因在经过转录和剪接过程后,能够产生多种不同编码序列的mRNA [13]。已有研究指出,IGF1基因的多态性与多种疾病的发生有着密切的联系。在肝脏组织中高表达的IGF1及其受体(IGF-1R)与MASLD、IR和MetS的关系密切。研究显示,IGF-1的表达降低与肝脏脂肪的积累相关[14]。此外,IGF-1的减少与IR有关,在IR状态下,肝脏产生的IGF-1减少,这可能导致肝脏对胰岛素的敏感性降低,从而加剧胰岛素抵抗[15]

鉴于MASLD与胰岛素抵抗之间的密切关系,以及IGF1在调节IR中的关键作用,我们推测IGF1基因的多态性可能与MASLD的发病机制相关。多项研究证实,IGF1 rs5742612位点多态性与多种疾病的发病包括恶性肿瘤、骨质疏松和特发性脊柱侧弯的发生有关[16]-[21]。国外的一些研究已经发现IGF1 rs5742612位点与MASLD的发病风险相关[22]。然而,关于IGF1 rs5742612位点与中国汉族人群MASLD发病关系的研究成果尚未见报道。本研究拟探讨IGF1 rs5742612位点的基因多态性与青岛地区汉族人群中MASLD发病风险之间的相关性。通过这项研究,我们希望能够为MASLD的诊断和治疗提供新的思路,并且为预测MASLD的发病风险找到可靠的生物标志物。

2. 对象与方法

2.1. 研究对象的选取

选取2022年12月到2023年12月于青岛市市立医院就诊的确诊为MASLD的中国汉族患者205人作为研究的病例组;同时纳入130名就诊于青岛市市立医院的中国汉族健康体检者,经过详细的病史询问、体格检查以及肝胆胰脾超声、上腹CT、血尿粪便常规、血生化检查均未见异常,除外有MASLD者作为对照组。MASLD的诊断符合《非酒精性脂肪性肝病防治指南(2018更新版)》[23]的诊断标准。除外酒精性肝病(Alcoholic Liver Disease, ALD)、基因3型丙型肝炎病毒(HepatitisC Virus, HCV)、自身免疫性肝炎、肝豆状核变性等可导致脂肪肝的特定肝病,除外药物(如他莫昔芬、糖皮质激素等)、全胃肠外营养、炎症性肠病、乳糜泻、甲状腺功能减退症、库欣综合征、β脂蛋白缺乏血症、脂质萎缩性糖尿病、Mauriac综合征等导致脂肪肝的特殊情况。本研究启动于2022年,当时MASLD的定义尚未正式取代NAFLD。因此,本研究的纳入标准是基于2018年版本的指南。根据回顾性研究的结果,MASLD与NAFLD之间的差异并不显著,这表明即使在MASLD的新定义下,之前根据NAFLD定义进行的研究结果仍然具有参考价值[24]。研究经青岛市市立医院伦理委员会审批许可,所有受试者均签署知情同意书。

2.2. 临床资料收集和标本采集

使用标准问卷调查研究患者的基本信息,用专业仪表测量身高体重,计算体质量指数(Body Mass Index, BMI)。所有受试者的临床数据均以调查表的形式记录,包括年龄、性别、BMI等基线特征。在受试者禁饮食12 h后,于次日清晨采集8 mL静脉血,各取4 mL分别置于A、B两支EDTA抗凝管中。A管用于检测临床生化指标,B管用于DNA的提取和基因型鉴定。

2.3. 受试者生化指标的实验室检测

A管静脉血送医学检验中心检测空腹血糖(FPG)、总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白(LDL-C)、高密度脂蛋白(HDL-C)、总胆红素(STB)、丙氨酸氨基转移酶(ALT)、天冬氨酸氨基转移酶(AST)、γ-谷氨酰转移酶(GGT)、碱性磷酸酶(ALP)、尿酸等生化指标,结果以表格形式记录。

2.4. 全血基因组DNA的提取及测定

使用博淼生物科技(北京)有限公司提供的全血基因组DNA提取试剂盒来提取样本中的DNA,后利用聚合酶链反应(PCR)技术对特定DNA片段进行扩增,以便检验IGF1基因上的rs5742612位点多态性。PCR扩增所需的引物由博淼生物科技(北京)有限公司设计并合成,其序列分别为上游引物5′-ACGTTGGATGAGATTGGAAGACAGCACTCG-3′,下游引物5′-ACGTTGGATGCCTCCATAGGTTCTAGGAAA-3′。PCR扩增完成后,对PCR产物进行虾碱性磷酸酶(SAP)处理,以准备进行后续的单碱基延伸反应。延伸反应后,通过树脂纯化PCR产物,并将其点样到芯片上。最后,使用质谱技术对样品进行基因型分析。

2.5. 统计分析方法

在人口学特征描述中,首先对计量资料使用矩法检验(Skewness-Kurtosisi test)进行正态性检验,对符合正态分布的计量资料以均数 ± 标准差(SD)表示,不符合正态分布的计量资料以中位数(四分位数间距)表示,并采用独立t检验或Wilcoxon秩和检验进行组间比较。对于计数资料,使用频率(%)表示,并采用Pearson χ2检验或Fisher确切概率法进行组间比较。同时使用χ2检验来判断位点的基因型频率是否符合哈迪–温伯格平衡检验(Hardy-Weinberg Equilibrium, HWE),以此来确保样本的群体代表性。使用单因素Logistic回归分析,基于显性模型和隐性模型[25],计算得到各SNP位点与MCI在各模型下的OR和95%置信区间(confidence interval, CI)。本研究统计分析均采用SPSS 22.0软件完成。统计学检验均为双侧检验,将P < 0.05作为显著性标准。

3. 结果

3.1. 研究对象基本特征及实验室指标比较

本研究纳入研究对象共335人,其中MASLD组205人,对照组130人。研究对象基本特征及实验室指标见表1。组间比较结果表明,两组在年龄、BMI、收缩压、舒张压、ALT、AST、GGT、ALP/AKP、TG、HDL、STB、尿酸之间分布差异具有统计学意义(P < 0.05)。与对照组相比,MASLD组研究对象通常有更高的年龄、BMI、收缩压、舒张压、ALT、AST、GGT、ALP/AKP、TG、STB、尿酸值以及更低的HDL值。未发现两组在性别、TC、LDL和FPG之间的分布差异存在统计学意义(P > 0.05)。

Table 1. Comparison of clinical data between MASLD and control groups

1. MASLD组和对照组临床资料比较

变量

对照组(n = 130)

MASLD组(n = 205)

统计量

P

性别(男/女)

68/62

102/103

χ2 = 0.207

0.649

年龄(岁)

39.89 (38.05~41.74)

53.78 (52.06~55.50)

t = −10.508

<0.001*

BMI (kg/m2)

25.20 (24.54~25.86)

26.27 (25.84~26.71)

t = −2.798

0.003*

收缩压(mmHg)

122.50 (114.00~130.00)

138.00 (125.00~154.00)

Z = −8.343

<0.001*

舒张压(mmHg)

71.00 (66.00~77.00)

77.00 (71.00~84.00)

Z = −5.039

<0.001*

ALT (U/L)

19.52 (14.00~28.27)

30.33 (18.00~67.44)

Z = −5.994

<0.001*

AST (U/L)

20.82 (17.00~24.55)

26.87 (19.95~39.53)

Z = −6.044

<0.001*

GGT (U/L)

19.40 (14.00~28.00)

34.20 (22.00~57.37)

Z = −7.550

<0.001*

ALP/AKP (U/L)

58.31 (20.50~85.75)

90.27 (76.20~105.20)

Z = −8.797

<0.001*

TG (mmol/L)

1.11 (0.84~1.65)

1.70 (1.14~2.42)

Z = −5.939

<0.001*

TC (mmol/L)

4.98 (4.41~5.67)

5.11 (4.35~5.83)

Z = −0.880

0.379

HDL (mmol/L)

1.23 (1.04~1.45)

1.13 (0.98~1.31)

Z = 2.634

0.008*

LDL (mmol/L)

3.07 (2.63~3.46)

3.15 (2.64~3.69)

Z = −1.706

0.088

FPG (mmol/L)

4.98 (4.62~5.32)

5.07 (4.55~5.80)

Z = −1.062

0.288

STB (μmol/L)

12.65 (10.30~15.40)

13.60 (11.10~17.90)

Z = −2.198

0.028*

尿酸(μmol/L)

347.23 (295.00~434.14)

399.10 (345.20~480.60)

Z = −4.625

<0.001*

注:BMI,身体质量指;ALT,谷丙转氨酶;AST,谷草转氨酶;GGT,谷酰转移酶;ALP/AKP,碱性磷酸酶;TG,甘油三酯;TC,总胆固醇;HDL,高密度脂蛋白;LDL,低密度脂蛋白;FPG,空腹血糖;STB,总胆红素;*P < 0.05。

3.2. rs5742612位点的Hardy-Weinberg遗传平衡检验

rs5742612位点包括AA、GA、GG共三种基因型,分别对MASLD组和对照组进行Hardy-Weinberg遗传平衡检验,结果见表2,表明该位点符合Hardy-Weinberg遗传平衡(P > 0.05),提示本研究所纳入的研究对象来自同一人群,具有群体代表性。

Table 2. Hardy-Weinberg genetic balance test

2. Hardy-Weinberg遗传平衡检验

组别

基因型

χ2

P

对照组(n = 130)

AA/GA/GG

0.172

0.918

MASLD组(n = 205)

AA/GA/GG

0.041

0.980

3.3. rs5742612位点的基因型及等位基因组间比较

rs5742612位点在MASLD组和对照组之间基因型频率和等位基因频率比较结果见表3,组间比较结果表明,rs5742612位点基因型频率(χ2 = 0.286, P = 0.867)和等位基因频率(χ2 = 0.083, P = 0.773)在两组之间的分布差异均无统计学差异。

Table 3. Distribution of genotypes and alleles between control and MASLD groups

3. 对照组与MASLD组之间基因型和等位基因的分布

对照组(n = 130)

MASLD组(n = 205)

χ2

P

基因型

AA

73 (56.15%)

114 (55.61%)

0.286

0.867

GA

50 (38.46%)

77 (37.56%)

GG

7 (5.39%)

14 (6.83%)

等位基因

A

196 (75.38%)

305 (74.39%)

0.083

0.773

G

64 (24.62%)

105 (25.61%)

3.4. rs5742612位点在不同遗传模型下临床资料比较

rs5742612位点在不同遗传模型下临床资料比较见表4表5,结果显示,rs5742612位点不同基因型携带在年龄、BMI、收缩压、舒张压、ALT、AST、GGT、ALP/AKP、TG、HDL、STB、尿酸指标之间无统计学差异(P > 0.05)。

Table 4. Comparison of clinical data under dominant model of rs5742612 locus

4. rs5742612位点显性模型下临床资料比较

变量

AA (n = 187)

GA + GG (n = 148)

统计量

P

性别(男/女)

89/98

81/67

χ2 = 1.683

0.194

年龄(岁)

49.54 (47.51~51.58)

46.94 (44.86~49.02)

t = 1.746

0.082

BMI (kg/m2)

26.09 (25.56~26.61)

25.57 (25.05~26.09)

t = 1.365

0.173

收缩压(mmHg)

130.00 (119.00~145.00)

129.00 (120.5~142.00)

Z = 0.427

0.670

舒张压(mmHg)

74.00 (69.00~82.00)

75.00 (68.00~81.00)

Z = −0.440

0.660

ALT (U/L)

25.26 (15.53~37.21)

24.00 (16.00~52.49)

Z = −0.912

0.362

AST (U/L)

22.56 (18.60~29.32)

23.68 (18.94~34.27)

Z = −1.337

0.181

GGT (U/L)

27.00 (17.09~45.39)

26.15 (18.00~48.00)

Z = −0.343

0.732

ALP/AKP (U/L)

84.07 (62.54~97.28)

85.81 (59.20~102.10)

Z = −0.550

0.582

TG (mmol/L)

1.36 (0.95~2.03)

1.47 (0.99~2.12)

Z = −0.578

0.563

TC (mmol/L)

5.09 (4.43~5.72)

5.09 (4.31~5.83)

Z = 0.215

0.830

HDL (mmol/L)

1.19 (0.99~1.45)

1.17 (1.03~1.32)

Z = 0.471

0.638

LDL (mmol/L)

3.11 (2.67~3.59)

3.10 (2.59~3.51)

Z = 0.797

0.425

FPG (mmol/L)

5.00 (4.56~5.63)

5.03 (4.56~5.64)

Z = −0.256

0.798

STB (μmol/L)

13.00 (10.60~16.50)

13.25 (10.80~17.10)

Z = −0.776

0.438

尿酸(μmol/L)

377.60 (313.20~460.65)

378.80 (327.27~466.26)

Z = −0.536

0.592

注:BMI,身体质量指;ALT,谷丙转氨酶;AST,谷草转氨酶;GGT,谷酰转移酶;ALP/AKP,碱性磷酸酶;TG,甘油三酯;TC,总胆固醇;HDL,高密度脂蛋白;LDL,低密度脂蛋白;FPG,空腹血糖;STB,总胆红素;*P < 0.05。

Table 5. Comparison of clinical data under the recessive model of the rs5742612 locus

5. rs5742612位点隐性模型下临床资料比较

变量

AA + GA (n = 314)

GG (n = 21)

统计量

P

性别(男/女)

157/157

13/8

χ2 = 1.116

0.291

年龄(岁)

48.32 (46.81~49.82)

49.52 (42.74~56.31)

t = −0.394

0.694

BMI (kg/m2)

25.82 (25.43~26.20)

26.48 (25.36~27.59)

t = −0.852

0.395

收缩压(mmHg)

129.00 (119.00~144.00)

135.00 (126.00~147.00)

Z = −1.087

0.277

舒张压(mmHg)

74.00 (68.00~81.00)

77.00 (72.00~81.00)

Z = −1.044

0.296

ALT (U/L)

25.13 (16.00~39.79)

21.00 (14.26~37.00)

Z = 1.075

0.282

AST (U/L)

23.00 (18.88~32.89)

21.00 (18.67~30.00)

Z = 0.531

0.596

GGT (U/L)

27.09 (17.29~46.39)

21.28 (18.03~31.00)

Z = 0.937

0.349

ALP/AKP (U/L)

85.39 (62.46~99.98)

78.86 (57.62~99.33)

Z = 0.486

0.627

TG (mmol/L)

1.41 (0.98~2.05)

1.31 (1.04~2.11)

Z = −0.045

0.964

TC (mmol/L)

5.09 (4.35~5.78)

4.97 (4.59~5.56)

Z = 0.553

0.580

HDL (mmol/L)

1.18 (1.00~1.40)

1.22 (1.13~1.33)

Z = −0.221

0.825

LDL (mmol/L)

3.11 (2.64~3.56)

3.10 (2.58~3.47)

Z = 0.774

0.439

FPG (mmol/L)

5.02 (4.56~5.63)

5.12 (4.65~5.58)

Z = −0.415

0.678

STB (μmol/L)

13.00 (10.70~16.60)

14.10 (10.20~18.40)

Z = −0.436

0.663

尿酸(μmol/L)

378.40 (323.60~463.71)

378.40 (312.80~468.60)

Z = −0.122

0.903

注:BMI,身体质量指;ALT,谷丙转氨酶;AST,谷草转氨酶;GGT,谷酰转移酶;ALP/AKP,碱性磷酸酶;TG,甘油三酯;TC,总胆固醇;HDL,高密度脂蛋白;LDL,低密度脂蛋白;FPG,空腹血糖;STB,总胆红素;*P < 0.05。

3.5. rs5742612位点与MASLD的关联分析

rs5742612位点与MASLD的关联分析结果见表6。显性模型统计结果表明,基因型分布与MASLD易感性之间无统计学意义(OR = 1.02, 95% CI = 0.66~1.59),在调整年龄、性别和BMI后,结果仍不显著(OR = 1.40, 95% CI = 0.83~2.37)。隐性模型结果表明,基因型分布与MASLD易感性之间亦无统计学意义(OR = 1.29, 95% CI = 0.51~3.28),在调整年龄、性别和BMI后,结果仍不显著(OR = 1.25, 95% CI = 0.43~3.68)。

Table 6. Genetic model of the rs5742612 locus

6. rs5742612位点的遗传模型

遗传模型

对照组

MASLD组

OR (95% CI)a

Pa

OR (95% CI)b

Pb

显性模型

AA

73 (56.15%)

114 (55.61%)

Ref.

Ref.

GA + GG

57 (43.85%)

91 (44.39%)

1.02 (0.66~1.59)

0.922

1.40 (0.83~2.37)

0.211

隐性模型

AA + GA

123 (94.61%)

191 (93.17%)

Ref.

Ref.

GG

7 (5.39%)

14 (6.83%)

1.29 (0.51~3.28)

0.596

1.25 (0.43~3.68)

0.680

注:a为粗模型的结果;b为调整年龄、性别和BMI后的结果。

4. 讨论

作为一种与代谢相关的疾病,MASLD的发展受到遗传和环境等多种因素的共同作用。众多研究表明,遗传因素在MASLD的发病机制中扮演着关键角色[26]。现有研究已经证明了部分基因多态性通过影响脂质代谢和胰岛素抵抗对MASLD产生影响。PNPLA3基因的rs738409、rs6006460和rs139051位点多态性通过调控甘油三酯脂肪酶的活性,显著影响肝脏脂质代谢过程[27]。这种影响不仅导致肝脏脂肪的堆积,还进一步加剧了肝脏内的炎症反应,从而在MASLD的疾病进程中扮演了重要角色[28]。TM6SF2基因的rs58542926多态性对极低密度脂蛋白(VLDL)及甘油三酯水平具有显著影响,这同样影响肝脏脂质代谢平衡[29]。GCKR rs1260326多态性也通过影响甘油三酯水平来影响MASLD发展[30]。MBOAT7的基因表达与维持葡萄糖稳态密切相关,而MBOAT7基因的rs641738和rs626283突变可导致其表达缺失,研究证实,这种表达缺失会降低胰岛素敏感性,加剧胰岛素抵抗状态[31]

鉴于MASLD与胰岛素抵抗的密切联系,我们认为IGF1基因的多态性可能对MASLD的发病有显著影响。本研究首次在中国青岛地区的汉族人群中探讨了IGF1的rs5742612位点多态性与MASLD发生之间的关系,研究证实,IGF1的rs5742612位点多态性与MASLD发病风险无明显相关性。

IGF1是一种含有70个氨基酸的单链肽类生长因子,通过与其受体IGF1R结合发挥作用,在调控生长、发育和代谢等多个过程中扮演着至关重要的角色[32]。IGF1由肝脏产生,具有促进生长和发育、降糖、降脂等作用,IGF1和IGF1R 在肝脏组织中表达,参与肝脏的病理生理过程[33]。研究发现,IGF1在包括肝脏在内的多种组织中对胰岛素抵抗有保护作用[32]。位点突变导致的IGF1的表达减少与胰岛素抵抗密切相关,胰岛素抵抗是MASLD的重要病理生理基础。在胰岛素抵抗的状态下,肝脏的脂肪会加速沉积,导致脂肪肝的形成[34]。MASLD患者中,IGF1水平通常较低,低水平的IGF1还可能与MASLD的肝纤维化有关[35] [36]

多项研究证实,IGF1 rs5742612位点多态性与多种疾病的发病风险有相关性[16]-[21]。有研究已证实IGF1 rs6214位点与MASLD的发生风险有一定相关性[37]。rs5742612位点位于IGF1基因的启动子区域,其多态性与IGF1基因的表达水平密切相关。该位点的变异可能通过影响IGF1基因的转录活性,进而调节蛋白表达的水平及其生物活性,最终影响IGF1的生物学功能[38]。此外,基础实验研究表明,IGF1基因rs5742612位点中的C等位基因可能由于其较低的转录稳定性和蛋白翻译效率,导致IGF1蛋白的生物效应减弱,这可能是MASLD发病机制中的一个重要因素[39] [40]。一项伊朗的研究发现,IGF1 rs5742612位点的C等位基因与MASLD的发病风险呈正相关[22]。在本研究中,我们分析了中国青岛地区汉族人群的IGF1 rs5742612基因型多态性与MASLD发病风险之间的相关性,统计结果显示两者无明显相关性 (P > 0.05)。本研究与上述研究结果不一致,可能由于地域和人种的差异,而生活习惯的差异也可能减弱遗传易感性对疾病的影响。此外,我们的研究不可避免地带有一些局限性。鉴于时间和实验条件的约束,我们未能开展进一步的体内或体外基础实验,以验证IGF1表达与胰岛素抵抗及MASLD之间的关联性。因此,未来仍亟待更为深入的基础研究来加以证实。

本研究首次分析了IGF1基因的rs5742612位点多态性与MASLD在青岛地区汉族人群中的相关性。研究发现,该位点的多态性与MASLD的发病风险之间无显著相关性。鉴于MASLD的发病机制的复杂性以及IGF1 rs5742612位点多态性的功能,仍不能完全否定该多态性对MASLD的影响,尚需多地域多种族的研究进一步探索。

NOTES

*通讯作者。

参考文献

[1] Byrne, C.D. and Targher, G. (2015) NAFLD: A Multisystem Disease. Journal of Hepatology, 62, S47-S64.
https://doi.org/10.1016/j.jhep.2014.12.012
[2] Chan, W., Chuah, K., Rajaram, R.B., Lim, L., Ratnasingam, J. and Vethakkan, S.R. (2023) Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): A State-of-the-Art Review. Journal of Obesity & Metabolic Syndrome, 32, 197-213.
https://doi.org/10.7570/jomes23052
[3] Marušić, M., Paić, M., Knobloch, M. and Liberati Pršo, A. (2021) NAFLD, Insulin Resistance, and Diabetes Mellitus Type 2. Canadian Journal of Gastroenterology and Hepatology, 2021, Article ID: 6613827.
https://doi.org/10.1155/2021/6613827
[4] Bril, F., Sanyal, A. and Cusi, K. (2023) Metabolic Syndrome and Its Association with Nonalcoholic Steatohepatitis. Clinics in Liver Disease, 27, 187-210.
https://doi.org/10.1016/j.cld.2023.01.002
[5] Speliotes, E.K., Yerges-Armstrong, L.M., Wu, J., et al. (2011) Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits. PLOS Genetics, 7, e1001324.
[6] Parisinos, C.A., Wilman, H.R., Thomas, E.L., Kelly, M., Nicholls, R.C., McGonigle, J., et al. (2020) Genome-Wide and Mendelian Randomisation Studies of Liver MRI Yield Insights into the Pathogenesis of Steatohepatitis. Journal of Hepatology, 73, 241-251.
https://doi.org/10.1016/j.jhep.2020.03.032
[7] Mancina, R.M., Dongiovanni, P., Petta, S., Pingitore, P., Meroni, M., Rametta, R., et al. (2016) The MBOAT7-TMC4 Variant Rs641738 Increases Risk of Nonalcoholic Fatty Liver Disease in Individuals of European Descent. Gastroenterology, 150, 1219-1230.e6.
https://doi.org/10.1053/j.gastro.2016.01.032
[8] Thangapandi, V.R., Knittelfelder, O., Brosch, M., Patsenker, E., Vvedenskaya, O., Buch, S., et al. (2020) Loss of Hepatic Mboat7 Leads to Liver Fibrosis. Gut, 70, 940-950.
https://doi.org/10.1136/gutjnl-2020-320853
[9] Abul-Husn, N.S., Cheng, X., Li, A.H., Xin, Y., Schurmann, C., Stevis, P., et al. (2018) A Protein-Truncating hsd17b13 Variant and Protection from Chronic Liver Disease. New England Journal of Medicine, 378, 1096-1106.
https://doi.org/10.1056/nejmoa1712191
[10] Abate, N., Carulli, L., Cabo-Chan, A., Chandalia, M., Snell, P.G. and Grundy, S.M. (2003) Genetic Polymorphism PC-1 K121Q and Ethnic Susceptibility to Insulin Resistance. The Journal of Clinical Endocrinology & Metabolism, 88, 5927-5934.
https://doi.org/10.1210/jc.2003-030453
[11] Duan, Y., Ke, X., Wu, H., Yao, S., Shi, W., Han, J., et al. (2023) Multi‐Tissue Transcriptome‐Wide Association Study Reveals Susceptibility Genes and Drug Targets for Insulin Resistance‐Relevant Phenotypes. Diabetes, Obesity and Metabolism, 26, 135-147.
https://doi.org/10.1111/dom.15298
[12] Tricoli, J.V., Rall, L.B., Scott, J., Bell, G.I. and Shows, T.B. (1984) Localization of Insulin-Like Growth Factor Genes to Human Chromosomes 11 and 12. Nature, 310, 784-786.
https://doi.org/10.1038/310784a0
[13] Shimatsu, A. and Rotwein, P. (1987) Mosaic Evolution of the Insulin-Like Growth Factors. Organization, Sequence, and Expression of the Rat Insulin-Like Growth Factor I Gene. Journal of Biological Chemistry, 262, 7894-7900.
https://doi.org/10.1016/s0021-9258(18)47652-1
[14] Stanley, T.L., Fourman, L.T., Zheng, I., McClure, C.M., Feldpausch, M.N., Torriani, M., et al. (2020) Relationship of IGF-1 and Igf-Binding Proteins to Disease Severity and Glycemia in Nonalcoholic Fatty Liver Disease. The Journal of Clinical Endocrinology & Metabolism, 106, e520-e533.
https://doi.org/10.1210/clinem/dgaa792
[15] Petäjä, E.M., Zhou, Y., Havana, M., Hakkarainen, A., Lundbom, N., Ihalainen, J., et al. (2016) Phosphorylated IGFBP-1 as a Non-Invasive Predictor of Liver Fat in NAFLD. Scientific Reports, 6, Article No. 24740.
https://doi.org/10.1038/srep24740
[16] Guan, M., Wang, H., Fang, H., Zhang, C., Gao, S. and Zou, Y. (2016) Association between IGF1 Gene Single Nucleotide Polymorphism (rs5742612) and Adolescent Idiopathic Scoliosis: A Meta-Analysis. European Spine Journal, 26, 1624-1630.
https://doi.org/10.1007/s00586-016-4742-7
[17] Tang, W., Chen, S., Liu, J., Liu, C., Wang, Y. and Kang, M. (2018) Investigation of igf1, igf2bp2, and igfbp3 Variants with Lymph Node Status and Esophagogastric Junction Adenocarcinoma Risk. Journal of Cellular Biochemistry, 120, 5510-5518.
https://doi.org/10.1002/jcb.27834
[18] Zhang, W., Zhang, L.C., Chen, H., Tang, P.F. and Zhang, L.H. (2015) Association between Polymorphisms in Insulin-Like Growth Factor-1 and Risk of Osteoporosis. Genetics and Molecular Research, 14, 7655-7660.
https://doi.org/10.4238/2015.july.13.10
[19] Oh, S.Y., Shin, A., Kim, S., Hwang, J., Hong, S.H., Lee, Y., et al. (2016) Relationship between Insulin-Like Growth Factor Axis Gene Polymorphisms and Clinical Outcome in Advanced Gastric Cancer Patients Treated with Folfox. Oncotarget, 7, 31204-31214.
https://doi.org/10.18632/oncotarget.9100
[20] Wernli, K.J., Newcomb, P.A., Wang, Y., Makar, K.W., Shadman, M., Chia, V.M., et al. (2010) Body Size, IGF and Growth Hormone Polymorphisms, and Colorectal Adenomas and Hyperplastic Polyps. Growth Hormone & IGF Research, 20, 305-309.
https://doi.org/10.1016/j.ghir.2010.04.001
[21] Mao, J., Zhuang, G. and Chen, Z. (2017) Genetic Polymorphisms of Insulin-Like Growth Factor 1 Are Associated with Osteosarcoma Risk and Prognosis. Medical Science Monitor, 23, 5892-5898.
https://doi.org/10.12659/msm.908004
[22] Nobakht, H., Mahmoudi, T., Rezamand, G., Tabaeian, S.P., Jeddi, G., Asadi, A., et al. (2022) Association of Rs5742612 Polymorphism in the Promoter Region of igf1 Gene with Nonalcoholic Fatty Liver Disease: A Case-Control Study. Laboratory Medicine, 53, 504-508.
https://doi.org/10.1093/labmed/lmac039
[23] 中华医学会肝病学分会脂肪肝和酒精性肝病学组, 中国医师协会脂肪性肝病专家委员会. 非酒精性脂肪性肝病防治指南(2018更新版) [J]. 传染病信息, 2018, 31(5): 393-402+420.
[24] Song, S.J., Lai, J.C., Wong, G.L., Wong, V.W. and Yip, T.C. (2024) Can We Use Old NAFLD Data under the New MASLD Definition? Journal of Hepatology, 80, e54-e56.
https://doi.org/10.1016/j.jhep.2023.07.021
[25] Horita, N. and Kaneko, T. (2015) Genetic Model Selection for a Case-Control Study and a Meta-Analysis. Meta Gene, 5, 1-8.
https://doi.org/10.1016/j.mgene.2015.04.003
[26] Wei, S., Wang, L., Evans, P.C. and Xu, S. (2024) NAFLD and NASH: Etiology, Targets and Emerging Therapies. Drug Discovery Today, 29, Article ID: 103910.
https://doi.org/10.1016/j.drudis.2024.103910
[27] Cherubini, A., Casirati, E., Tomasi, M. and Valenti, L. (2021) PNPLA3 as a Therapeutic Target for Fatty Liver Disease: The Evidence to Date. Expert Opinion on Therapeutic Targets, 25, 1033-1043.
https://doi.org/10.1080/14728222.2021.2018418
[28] Romeo, S., Kozlitina, J., Xing, C., Pertsemlidis, A., Cox, D., Pennacchio, L.A., et al. (2008) Genetic Variation in PNPLA3 Confers Susceptibility to Nonalcoholic Fatty Liver Disease. Nature Genetics, 40, 1461-1465.
https://doi.org/10.1038/ng.257
[29] Stefan, N., Häring, H. and Cusi, K. (2019) Non-Alcoholic Fatty Liver Disease: Causes, Diagnosis, Cardiometabolic Consequences, and Treatment Strategies. The Lancet Diabetes & Endocrinology, 7, 313-324.
https://doi.org/10.1016/s2213-8587(18)30154-2
[30] Yuan, F., Gu, Z., Bi, Y., Yuan, R., Niu, W., Ren, D., et al. (2022) The Association between Rs1260326 with the Risk of NAFLD and the Mediation Effect of Triglyceride on NAFLD in the Elderly Chinese Han Population. Aging, 14, 2736-2747.
https://doi.org/10.18632/aging.203970
[31] Massey, W.J., Varadharajan, V., Banerjee, R., Brown, A.L., Horak, A.J., Hohe, R.C., et al. (2023) MBOAT7-Driven Lysophosphatidylinositol Acylation in Adipocytes Contributes to Systemic Glucose Homeostasis. Journal of Lipid Research, 64, Article ID: 100349.
https://doi.org/10.1016/j.jlr.2023.100349
[32] Werner, H. (2023) The IGF1 Signaling Pathway: From Basic Concepts to Therapeutic Opportunities. International Journal of Molecular Sciences, 24, Article No. 14882.
https://doi.org/10.3390/ijms241914882
[33] Sarmento-Cabral, A., del Rio-Moreno, M., Vazquez-Borrego, M.C., Mahmood, M., Gutierrez-Casado, E., Pelke, N., et al. (2021) GH Directly Inhibits Steatosis and Liver Injury in a Sex-Dependent and Igf1-Independent Manner. Journal of Endocrinology, 248, 31-44.
https://doi.org/10.1530/joe-20-0326
[34] Yao, Z., Gong, Y., Chen, W., Shao, S., Song, Y., Guo, H., et al. (2023) Upregulation of WDR6 Drives Hepatic De Novo Lipogenesis in Insulin Resistance in Mice. Nature Metabolism, 5, 1706-1725.
https://doi.org/10.1038/s42255-023-00896-7
[35] Ichikawa, T., Nakao, K., Hamasaki, K., Furukawa, R., Tsuruta, S., Ueda, Y., et al. (2007) Role of Growth Hormone, Insulin-Like Growth Factor 1 and Insulin-Like Growth Factor-Binding Protein 3 in Development of Non-Alcoholic Fatty Liver Disease. Hepatology International, 1, 287-294.
https://doi.org/10.1007/s12072-007-9007-4
[36] Marques, V., Afonso, M.B., Bierig, N., Duarte-Ramos, F., Santos-Laso, Á., Jimenez-Agüero, R., et al. (2021) Adiponectin, Leptin, and IGF-1 Are Useful Diagnostic and Stratification Biomarkers of NAFLD. Frontiers in Medicine, 8, Article ID: 683250.
https://doi.org/10.3389/fmed.2021.683250
[37] Sabzikarian, M., Mahmoudi, T., Tabaeian, S.P., Rezamand, G., Asadi, A., Farahani, H., et al. (2020) The Common Variant of Rs6214 in Insulin like Growth Factor 1 (igf1) Gene: A Potential Protective Factor for Non-Alcoholic Fatty Liver Disease. Archives of Physiology and Biochemistry, 129, 10-15.
https://doi.org/10.1080/13813455.2020.1791187
[38] Mahmoudi, T., Karimi, K., Arkani, M., Farahani, H., Vahedi, M., Dabiri, R., et al. (2014) Resistin-420c>g Promoter Variant and Colorectal Cancer Risk. The International Journal of Biological Markers, 29, 233-238.
https://doi.org/10.5301/jbm.5000079
[39] Wang, R., Xu, D., Liu, R., Zhao, L., Hu, L. and Wu, P. (2017) Microsatellite and Single Nucleotide Polymorphisms in the Insulin-Like Growth Factor 1 Promoter with Insulin Sensitivity and Insulin Secretion. Medical Science Monitor, 23, 3722-3736.
https://doi.org/10.12659/msm.902956
[40] Zhang, J., Chen, X., Zhang, L. and Peng, Y. (2017) igf1 Gene Polymorphisms Associated with Diabetic Retinopathy Risk in Chinese Han Population. Oncotarget, 8, 88034-88042.
https://doi.org/10.18632/oncotarget.21366