臺灣博碩士論文加值系統

背景:瘦型脂肪肝患者在脂肪肝中的比例越來越高。既是肝細胞激素又是脂肪激素的胎球蛋白-A還有脂聯素/瘦素比率和瘦性脂肪肝之間的關聯從未被研究過，此外，亞洲人群中瘦型脂肪肝的遺傳特徵也尚不清楚。
主旨:研究的目的是要探討調整中樞型肥胖和胰島素抵抗後，瘦型脂肪肝和非瘦型脂肪肝與血清胎球蛋白-A及脂聯素/瘦素比率濃度之間的關聯。此外，和瘦型對照組相比，我們旨在檢視瘦型脂肪肝的有或沒有與PNPLA3和SAMM50單核苷酸多型性的相關風險。
方法:此論文是從兩個不同的人群和數據庫中整理的三項研究。在生物標誌物和瘦型脂肪肝的研究中，納入對象是台灣北部新竹市的社區成年人。根據身體質量指數和腹部超音波的判定，將受試者分別分為瘦型對照組、瘦型脂肪肝組、單純超重/肥胖（非瘦型）組和超重/肥胖脂肪肝組。實驗室中使用酶聯免疫吸附測定法測量血清胎球蛋白-A、脂聯素和瘦素。之後，以多變量邏輯回歸分析估計在調整可能的干擾因子後，胎球蛋白-A和脂聯素/瘦素比率在不同血清濃度中患有瘦型脂肪肝的差異。我們使用接收者操作特徵曲線(以下稱ROC曲線)分析評估脂聯素/瘦素比率對瘦型脂肪肝的診斷準確度。至於單核苷酸多型性和瘦型脂肪肝相關的研究，是一項於2022年在台灣哈佛健診進行的病例對照研究。納入身體質量指數低於24 kg/m2的成年人，並藉由腹部超音波分類是否有脂肪肝。基於NHGRI-EBI網站庫料庫並使用Global Screening Array-24 v1.0 BeadChip於單核苷酸多態性的選擇，我們去除重複和不顯著的變異後，選擇了 PNPLA3 基因中的rs12483959 和SAMM50基因中的rs3761472。統計方法則使用了多重邏輯回歸模型和ROC曲線分析評估。
結果:胎球蛋白-A最高三分位數與最低三分位數血清濃度的脂肪肝勝算比為2.62（95% CI：1.72-3.98；趨勢P<0.001）。在以身體質量指數做分層分析，並調整可能的干擾因子後，胎球蛋白-A高三分位數與最低三分位數的瘦型脂肪肝勝算比為2.09（95% CI：1.09-3.98；趨勢P為0.026）；與瘦型對照組相比，在調整年齡、性別、吸煙習慣、運動習慣、胰島素阻抗、和肝功能後，脂聯素/瘦素比率在瘦型脂肪肝勝算比為0.28(95%CI: 0.12-0.69)。脂聯素/瘦素比率用以診斷脂肪肝的ROC曲線為0.85（95% CI：0.82-0.88）(P<0.001)。在基因研究中，共有1,652名的瘦型對照組和602名瘦型脂肪肝患者被納入哈佛數據庫。PNPLA3 rs12483959 (OR: 3.06; 95% CI: 2.15-4.37)和SAMM50 rs3761472 (OR: 2.90; 95% CI: 2.04-4.14)的GG基因型在調整年齡、性別、身體質量指數後，得到瘦型脂肪肝風險較高。PNPLA3 rs738409和SAMM50 rs3761472檢測瘦型脂肪肝的ROC曲線下面積分別為0.859（95%CI：0.841，0.877）和0.860（95%CI：0.843，0.877）。
結論:胎球蛋白-A和脂聯素/瘦素比率可能是早期區分瘦型脂肪肝和瘦型對照組的良好生物標誌物。針對基因變異，PNPLA3 rs738409和SAMM50 rs3761472基因多態性與亞洲人群中的瘦性脂肪肝的高風險獨立相關。這些都有待進一步研究。

Background:The prevalence of lean non-alcoholic fatty liver disease (NAFLD) is on the rise, contributing to a growing proportion of liver diseases. However, the phenotypic and genetic characteristics of lean NAFLD in Asian populations have yet to be fully understood.
Aims: Our study aims to investigate the correlation between serum levels of fetuin-A and the AL ratio in lean and non-lean individuals, considering their NAFLD status and adjusting for central obesity and insulin resistance. Furthermore, we intend to assess the varying risks of lean NAFLD in the presence or absence of PNPLA3 and SAMM50 variants, comparing them to lean individuals without NAFLD.
Methods:Three studies were conducted using data from two distinct populations and databases. The first set of studies included community-based adults residing in Hsinchu City, Northern Taiwan. The participants were categorized into different groups based on their BMI and ultrasonographic indicators of fatty liver, including lean controls, lean NAFLD, non-lean individuals with simple overweight/obesity, and overweight/obese individuals with NAFLD. Enzyme-linked immunosorbent assay was employed to measure serum levels of fetuin-A, adiponectin, and leptin. For the study related to SNPs and lean NAFLD, it was a cohort study conducted in the HAVO Health Exam Clinic from 2022 in Taiwan. Adults with a body mass index less than 24 kg/m2 were enrolled. Fatty liver was defined by ultrasonography. The candidate gene approach employed in the study relied on the NHGRI-EBI website's library for selecting relevant genes. To analyze single nucleotide polymorphisms (SNPs), the Global Screening Array-24 v1.0 Bead Chip was utilized for the selection process. After eliminating duplicates and insignificant variants, rs12483959 in the PNPLA3 gene and rs3761472 in the SAMM50 gene were chosen for analysis. Multiple logistic regression models and ROC curves were employed in these studies.
Results:The odds ratio (OR) for having NAFLD in the highest tertile compared to the lowest tertile of fetuin-A was 2.62 (95% CI: 1.72-3.98; P for trend < 0.001). When stratified by BMI and adjusted for confounding factors, the OR for having lean NAFLD in the highest versus the lowest tertile of fetuin-A was 2.09 (95% CI: 1.09-3.98; P for trend 0.026). Compared with the lean controls, the odds of having lean NAFLD for the highest versus the lowest tertile of AL ratio was 0.28(95%CI: 0.12-0.69) after adjustment. Regarding the diagnostic performance of NAFLD, incorporating the AL ratio, BMI, triglyceride levels, and AST/ALT ratio, the ROC analysis yielded an area under the curve (AUC) of 0.85 (95% CI: 0.82-0.88) for all NAFLD (P < 0.001). A total of 1,652 lean controls and 602 lean NAFLD patients were enrolled in HAVO database. After adjustment, individuals with GG genotypes of PNPLA3 rs12483959 had a higher risk of fatty liver with an odds ratio (OR) of 3.06 (95% CI: 2.15-4.37). Similarly, those with GG genotypes of SAMM50 rs3761472 also had an increased risk of fatty liver with an OR of 2.90 (95% CI: 2.04-4.14). The ROC analysis demonstrated good discriminatory ability for PNPLA3 rs738409 and SAMM50 rs3761472 in identifying lean NAFLD. The areas under the ROC curves were 0.859 (95% CI: 0.841, 0.877) for PNPLA3 rs738409 and 0.860 (95% CI: 0.843, 0.877) for SAMM50 rs3761472.
Conclusions: The findings suggest that Fetuin-A and the AL ratio have the potential to serve as promising biomarkers for early differentiation between lean NAFLD patients and lean controls, irrespective of insulin resistance. Additionally, the gene variants PNPLA3 rs738409 and SAMM50 rs3761472 are independently linked to an increased risk of fatty liver in lean individuals of Asian descent. These results indicate the need for further investigation and research in this area to better understand the implications and potential clinical applications of these biomarkers and gene variants in lean NAFLD.

口試委員會審定書 i
誌謝 ii
中文摘要 i ii
Abstract vi
I、INTRODCTION 1
Background 1
Aims 1
II、LITERATURE REVIEWS 2
2.1 The definition and prevalence of lean NAFLD 2
2.2 The biomarkers for lean NAFLD 5
2.3 SNPs for lean NAFLD 11
III、MATERIALS AND METHODS 14
3.1 Fetuin-A and lean NAFLD 14
3. 1.1 Study Subjects 14
3.1.2 Ultrasonography assessment 15
3.1.3 Blood Analysis 16
3. 1.4 Statistical analysis 16
3.2 AL ratio and lean NAFLD 17
3.2.1 Study Subjects 17
3.2.2 Ultrasonography assessment 18
3.2.3 Definition of Lean and NAFLD groups 18
3.2.4 Blood Analysis 18
3.2.5 Statistical Analysis 19
3.3. SNP and lead ALFD study population 20
3.3.1 Study Subjects 20
3.3.2 Selection of single nucleotide polymorphisms 21
3.3.3 Statistical analysis 23
IV、RESULTS 24
4.1. Fetuin-A and lean NAFLD 24
4.1.1. General Characteristics 24
4.1.2. Association of fetuin-A and NAFLD 24
4.2. AL ratio and lean NAFLD 26
4.2.1. General Characteristics 26
4.2.2. Association of AL ratio and NAFLD 26
4.3. SNPs for lean NAFLD 28
4.3.1 Baseline characteristics 28
4.3.2 Distribution of genotypes in lean subjects 29
4.3.3 Clinical characteristics according to genotype 29
4.3.4 Independent risk factors for lean NAFLD 30
V、DISCUSSIONS 32
5.1. Fetuin-A and lean NAFLD 32
5.2. AL ratio and lean NAFLD 35
5.3. SNPs for lean NAFLD 40
VI、CONCLUSIONS 45
References 46
Tables 62
Table 1. Baseline characteristics among the lean, non-lean, NAFLD, and non-NAFLD groups 62
Table 2. Comparison of lean, non-lean, NAFLD, and non-NAFLD groups in metabolic variables using Tukey’s post hoc analysis. 63
Table 3. Odds ratios of having NAFLD derived from multiple logistic regression analyses in tertiles of serum fetuin-A levels 64
Table 4. Odds ratios of having NAFLD derived from multiple logistic regression analyses in tertiles of serum fetuin-A levels, stratification by BMI 65
Table 5. Baseline characteristics among the lean controls, lean NAFLD, simple overweight/obesity and overweight/obesity NAFLD groups 66
Table 6. Comparison of lean controls, lean NAFLD, simple overweight/obesity and overweight/obesity NAFLD groups in metabolic variables using Tukey’s post hoc analysis. 69
Table 7. Relation between the serum adiponectin-leptin ratio and metabolic factors in multivariate linear regression models after adjusting for age and sex 70
Table 8. Odds ratios of having MAFLD related groups derived from multinomial regression analyses in relation to adiponectin leptin ratio 72
Table 9. Odds ratios of having MAFLD derived from multiple logistic regression analyses in serum gradient of adiponectin leptin level, stratification by BMI 73
Table 10. Odds ratios of having MAFLD derived from multiple logistic regression analyses in serum gradient of leptin adiponectin level, stratification by BMI 74
Table 11. Odds ratios of having NAFLD in relation to the serum tertile of adiponectin-leptin (AL x103) ratio using multiple logistic regression analyses 75
Table 12. Odds ratios of having NAFLD in relation to serum tertile of adiponectin leptin level using multiple logistic regression analyses, stratification by BMI 76
Table 13. Basic characteristics and biochemical profiles of the HAVO study population 77
Table 14 A. Gene location, cytogenetic region and most severe consequence of the SNPs related to PNPLA3 78
Table 14 B. Gene location, cytogenetic region and most severe consequence of the SNPs related to SAMM50 80
Table 15. The odds of having fatty liver in lean subjects in relation to PNPLA3 gene after adjustment by logistic regression models 81
Table 16. The odds of having fatty liver in lean subjects in relation to SAMM50 gene after adjustment by logistic regression models 82
Table 17A. SNPs of PNPLA3 gene which are associated with lean NAFLD (BMI<24kg/m2) in a Taiwanese population, N=2254 83
Table 17B. SNPs of SAMM50 gene which are associated with lean NAFLD (BMI<24kg/m2) in a Taiwanese population, N=2254 84
Table 18A. Correlation between genotype at locus rs738409 (representative of PNPLA3 gene) 85
Table 18B. Correlation between genotype at locus rs3761472 (representative of SAMM50 gene) 86
Table 19. The odds of having fatty liver in lean subjects in relation to PNPLA3 (rs738409) and SAMM50 (rs3761472) gene variants after adjustment by logistic regression models 87
Figures 88
Fig. 1. Flow chart of SNP selection for lean NAFLD 88
Figure 2. The distribution of Fetuin A concentration among lean non NAFLD, lean NAFLD, non-lean non-NAFLD and non lean NAFLD groups 89
Figure 3. Comparison of serum concentrations of Fetuin A in relation to the group of NAFLD. 90
Figure 4. The serum concentration of adiponectin showed a negative relation with BMI 91
Figure 5. The distribution of adiponectin concentration among groups 92
Figure 6. The serum concentration of leptin showed a positive relation with BMI 93
Figure 7 The distribution of leptin concentration among groups 94
Figure 8. The serum concentration of adiponectin-leptin ratio showed a negative relation with BMI 95
Figure 9. The distribution of adiponectin-leptin ratio among groups 96
Figure 10. Receiver operating characteristic (ROC) for the diagnosis of NAFLD. A. all subjects, AUROC was 0.85 (95% CI: 0.82-0.88), B. female subjects, AUROC was 0.83 (0.78-0.87), and C. male subjects, AUROC was 0.86 (081-0.91). 99
Figure 11. The area under the ROC curve for gene variants in the detection of lean NAFLD. The areas under the ROC curve for PNPLA3 rs738409 and SAMM50 rs3761472 in the detection of lean NAFLD were 0.859 (95%CI: 0.841, 0.877) and 0.860 (95%CI: 0.843, 0.877), respectively. A. PNPLA3 rs738409 and B. SAMM50 rs3761472. 101
Published papers
Independent Dose–Response Associations between Fetuin-A and Lean Nonalcoholic Fatty Liver Disease 102
Adiponectin–leptin ratio for the early detection of lean non-alcoholic fatty liver disease independent of insulin resistance 112

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