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研究生:林建佑
研究生(外文):LIN, CHIEN-YU
論文名稱:利用全基因組關聯性分析探討影響痛風的重要基因
論文名稱(外文):A Genome-Wide Association Study Identifies Important Genes Influencing Gout Disease
指導教授:張建國張建國引用關係
指導教授(外文):CHANG, JAN-GOWTH
口試委員:鄭如茜呂旭峯章順仁張偉嶠彭慶添張雅琁張建國
口試委員(外文):CHENG, JU-CHIENLU, HSI-FENGCHANG, SHUN-JENCHANG, WEI-CHIAOPENG, CHING-TIENCHANG, YA-SIANCHANG, JAN-GOWTH
口試日期:2022-07-14
學位類別:博士
校院名稱:中國醫藥大學
系所名稱:臨床醫學研究所博士班
學門:醫藥衛生學門
學類:醫學學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:46
中文關鍵詞:全基因組關聯性分析全基因體定序痛風高尿酸血症多基因風險分數
外文關鍵詞:GWASWGSGoutHyperuricemiaPRS
ORCID或ResearchGate:0000-0003-2705-9742
相關次數:
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  • 下載下載:21
  • 收藏至我的研究室書目清單書目收藏:1
高尿酸血症是肝臟代謝過度活躍或腎臟排泄不足的形成尿酸過高的生理現象。高尿酸血症會誘發痛風和腎結石,並加速腎臟和心血管疾病的進展。儘管全基因組關聯研究 (GWAS)已了解三個候選基因 (SLC2A9、ABCG2 和 SLC22A12) 是尿酸鹽水平的主要決定因素。但與尿酸吸收和排泄有關的基因尚未確定。本研究將利用台灣生物庫 (TWB) 提供的全基因組關聯研究和全基因組定序 (WGS) 數據進行後續研究,從而深入了解台灣人族群控制尿酸的基因數量,並確定表現出最顯著效果的基因。

主題一:
利用全基因組關聯研究 (GWAS) 探討女性痛風和無症狀性高尿酸血症 (AH) 相關的遺傳變異和多基因風險分數 (PRS)之探討。
方法:探討痛風、無症狀高尿酸血症以及尿酸正常者為研究族群。所有收案者,皆進入discovery以及replication的GWAS研究族群。根據基因變異是否表現出保護作用來估計多基因風險分數 (PRS)。
結果:共納入女性59472人,痛風和無症狀高尿酸血症,分別佔1.60%和19.59%。年齡 >=50 歲女性痛風患者的顯著預測因子,包括 SLC2A9、C5orf22、CNTNAP2 和 GLRX5 基因中的六個基因變異點位。對於年齡 <50 歲的人顯著預測因子,僅發現了 X 染色體上的基因變異 rs147750368 (SPANXN1)。另外,發現SLC2A9、ZNF518B、PKD2 和 ABCG2 中的大多數基因變異點位與兩個年齡組 (>=50 歲女性以及<50 歲) 的無症狀高尿酸血症顯著相關。利用多基因風險分數 (PRS),可以解釋大約 0.59% - 0.89% 的痛風變異點位,具有保護作用,且風險變異平均多基因風險分數 (PRS) 的6.2倍,但在無症狀高尿酸血症表現型中,僅為 1.2 倍。除此之外,多基因風險分數(PRS) 還顯示了無症狀高尿酸血症和四分位數分數之間的劑量反應呈現趨勢。
結論: SLC2A9的基因變異是50歲以上女性痛風相關的主要遺傳因素。在探討性狀影響變異的同質選擇下,多基因風險分數 (PRS) 可以提供更符合痛風/無症狀高尿酸血症風險預測。

主題二:
利用全基因體定序 (WGS) 探討台灣男性族群控制尿酸的基因以及可產生顯著影的重要基因。
方法:利用台灣生物資料庫 (TWB) 定序結果,透過生物資訊的分類和統計學的方式,探討影響尿酸的重要基因變異。
結果:利用台灣生物資料庫中,沒有被診斷出患有痛風的男性,包括 907 人的研究人群中。平均年齡為 49 歲,尿酸的平均值為 6.3 mg/dL。首先,我們探討了 11 個尿酸相關的基因多型性基因(ABCG2、SLC2A9、SLC22A12 和 PDZK1)。結果呈現,ABCG2(rs4148157 G>A、rs4693924 G>A、rs2231142 G>T)具有統計學意義,其p值分別為0.02047、0.01926和0.00074。此外,我們採用了 ABCG2 遺傳單倍型變異(ABCG2_rs4148157、ABCG2_rs4693924 和 ABCG2_rs2231142),共歸納出 44 名受測者有 ABCG2 (基因變異型;AAT);他們的尿酸值為8.5-3.6 mg/dL。將尿酸結果與致病基因變異的資料庫(ClinVar 和預測工具,包括 PolyPhen 和 SIFT)進行比較。我們排除了同時出現在尿酸 ≤7.0 mg/dL和> 7.0 mg/dL樣品中的尿酸代謝基因,只保留了那些僅出現在尿酸≤7.0 mg/dL或> 7.0 mg/dL樣品中的基因。結果顯示在尿酸 > 或 = 7.0 mg/dL 的樣品中,致病變異基因分別為 GCKR、SLC13A3 和 PRPSAP1。對於尿酸<7.0 mg/dL的樣本,變異基因為SLC17A3、SLC22A12和XDH。我們進一步探討了這些基因在ABCG2 單倍型的加乘效應下, SLC22A12_rs77782504 T>G 表現出顯著的影響(血液中尿酸為 3.7 mg/dL)。
結論:我們利用台灣生物資料庫提供的全基因體定序結果,發現SLC22A12 (rs77782504 T>G) 表現出顯著的影響。

Hyperuricemia is a physiological symptom involving excessive uric acid formation due to overactive liver metabolism or insufficient renal excretion. This symptom causes gout and the formation of kidney stones and accelerates the progression of renal and cardiovascular diseases. Although candidate-gene and genome-wide association studies (GWASs) have confirmed 3 genes, namely SLC2A9, ABCG2, and SLC22A12, as the decisive factors of urate levels, the number of genes involved in uric acid absorption and excretion has yet to be confirmed. This study employed the GWAS method and whole genome sequencing (WGS) data provided by Taiwan Biobank to explore the number of genes regulating uric acid in the Taiwanese population and identify the genes that exert the most notable effect on uric acid.

Project 1:
GWAS for exploring the genetic variants and polygenic risk score (PRS) associated with gout and asymptomatic hyperuricemia (AH) in women.
Methods: Patients with gout and AH and individuals with normal uric acid levels were recruited as the discovery and replication research population for GWAS. The PRS of each participant was evaluated on the basis of the protective effect of genetic variants.
Results: Among the 59472 female participants, 1.60% and 19.59% were diagnosed with gout and AH, respectively. For participants aged ≥50 years, the major predictors to gout were associated with 6 genetic variation sites in the genes SLC2A9, C5orf22, CNTNAP2, and GLRX5. For participants aged <50 years, the genetic variant rs147750368 (SPANXN1) in the X chromosome was identified as the sole major predictor. Moreover, most of the genetic variation sites in SLC2A9, C5orf22, CNTNAP2, and GLRX5 were significantly correlated with AH in the aforementioned two age groups. The PRS results revealed that 0.59%–0.89% of the genetic variation sites exerted a protective effect, and the risk variation was 6.2 and 1.2 times the average PRS score for gout and AH expressions, respectively. Additionally, a dose–response relationship was observed between the quartile PRS and AH.
Conclusion: The genetic variants in SLC2A9 are the main genetic factors associated with gout in female patients aged ≥50 years. The PRS, which is used for the homogenous selection for trait-affecting genetic variants, provides an accurate risk prediction of gout and AH.

Project 2:
WGS for exploring genes that regulate and exert notable effects on uric acid in men.
Method: WGS data provided by Taiwan Biobank were employed in combination with classification and statistics techniques in bioinformatics to examine genetic variants that exert notable effects on uric acid.
Results: The WGS data of 907 of male test receivers not diagnosed with gout were adopted. They were aged 49 years on average and exhibited a mean uric acid level of 6.3 mg/dL. Analysis of 11 polymorphic genes related to uric acid (e.g., ABCG2, SLC2A9, SLC22A12, and PDZK1) revealed that ABCG2 attained statistical significance (rs4148157 G>A, rs4693924 G>A, and rs2231142 G>T); the p values were 0.02047, 0.01926, and 0.00074, respectively. The genetic haplotype of ABCG2 (ABCG2_rs4148157, ABCG2_rs4693924, and ABCG2_rs2231142) was examined to reveal that 44 of the test receivers exhibited ABCG2 with the genetic variant of AAT, and they displayed uric acid levels of 8.5–3.6 mg/dL. The uric acid analysis results were compared with databases of pathogenic gene variants (ClinVar and prediction tools such as PolyPhen and Sorting Intolerant from Tolerant). We exclude uric acid metabolism genes that appeared in both samples with ≤7.0 and >7.0 mg/dL of uric acid, and retained those that appeared only in either samples with ≤7.0 mg/dL of uric acid or those with >7.0 mg/dL. The results indicated that the pathogenic gene variants in the samples with ≥7.0 mg/dL of uric acid were GCKR, SLC13A3, and PRPSAP1, whereas those in the samples with <7.0 mg/dL of uric acid were SLC17A3, SLC22A12, and XDH. Further analysis revealed that when the effects of these variants are magnified by the genetic haplotype of ABCG2, SLC22A12_rs77782504 T>G demonstrated a notable effect (uric acid: 3.7 mg/dL in blood).
Conclusion: The WGS data provided by Taiwan Biobank confirmed that SLC22A12 (rs77782504 T>G) exerts considerable effect on uric acid in men.

誌謝辭 i
中文摘要 ii
英文摘要 iv
目次 vii
圖表目次 viii
一、文獻討論 1
二、研究目的 4
三、材料和方法 5
四、研究結果 8
五、討論 12
六、總結 15
七、未來展望 16
八、參考書目 40
附錄一 博士班期間相關論文 44
附錄二 縮寫對照表 46

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