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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭柏秀(Po-Hsiu Kuo) | |
| dc.contributor.author | Wen-Ya Hsu | en |
| dc.contributor.author | 許雯雅 | zh_TW |
| dc.date.accessioned | 2023-03-19T21:06:20Z | - |
| dc.date.copyright | 2022-10-17 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-09-22 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83387 | - |
| dc.description.abstract | 微生物佔了人體細胞總數的一半以上，而它們大多都生活在宿主的腸道中，稱為腸道微生物，過去研究發現這些迷你居民與許多宿主的身體表徵和疾病有關，動物實驗更證明雙向腸腦軸的存在，顯示人類的第二個大腦－大腸及腸道菌相與宿主的壓力、焦慮、情緒和行為之間存在密切關係，腸道菌相在其中更是扮演了重要的角色，而情緒疾患中，憂鬱症在全球疾病負擔中名列前茅，每年奪走超過 70 萬人的生命，因此，研究人類腸道菌相和憂鬱症狀的交互作用或許可以使我們更加了解疾病機制。然而一項回顧性研究顯示，多篇研究在憂鬱與菌相組成之間的增減方向不一致，這可能不僅由環境造成，還與宿主基因有關，由於特定細菌豐度在雙胞胎研究中發現了適中的遺傳力，顯示宿主遺傳因子對腸道菌相的影響需要更全面的研究。微生物菌相與全基因體關聯分析 (mbGWAS) 近年來被用於研究宿主遺傳變異與菌相之間的交互作用，然而，即使最顯著的訊號也無法在重現在每篇mbGWAS中，且大多關注健康的歐洲及美洲人。 本研究欲探索臺灣人群中遺傳變異與腸道菌相之間的關聯，並評估是否可以複製先前mbGWAS的研究結果。此外，也單獨分析憂鬱患者的基因與腸道菌相之間是否存在特殊關係。 本研究在臺灣北部醫院招募了 280 位患有情緒疾患的成年人 (143位憂鬱症和 137位非躁症下的躁鬱症) 和 101名從未診斷為精神疾患的健康對照組。使用訪談和自評的問卷蒐集人口學、臨床和飲食變項。我們定序糞便樣本中的微生物16S rRNA 基因的 V3–V4 和 V4 區域，並以屬作為最小分類的腸道菌相資料；由血液樣本取得宿主遺傳變異。我們使用線性和邏輯回歸進行了 2 個模型 (全部個案和僅納入憂鬱病患) 來分析腸道菌相，並校正相關協變量以盡量減少它們對腸道菌相組成的影響，接著從模型中提出殘差，以累加性模型 (additive model) 進行遺傳關聯分析。 我們在通過品質控管的全樣本 (n=368) 和情緒疾患個案 (n=267) 中分別找到 14 個和 9 個達到 GWAS 顯著水準 (P < 5×10-8) 的菌相和遺傳變異之間的關聯，其中有4個基因 (LRP1B、NPSR1-AS1、MGAT5、SLIT3) 複製了之前的 mbGWAS 結果，儘管位點和相關的細菌種類並不完全相同。此外，我們也發現僅在憂鬱患者中特有的 5 個信號。然而，這些關聯的潛在機制仍然未知。 未來的研究需要擴大樣本數，以獲得台灣人群中更穩定且可重複的結果，並進行動物模型研究宿主的分子生物學和疾病機制。隨著遺傳變異對腸道菌相組成的影響有更進一步的發現，可以使我們對宿主-微生物的交互作用和疾病機制 (包括情緒疾患) 有更多的了解。 | zh_TW |
| dc.description.abstract | The human microbiome makes up more than half of the body's total cell counts, almost all of them live in our gut, and we call them gut microbiota. Previous studies have identified these tiny residents are associated with many host body traits and diseases. Experimental studies provided convincing evidence of the strong connection between gut and host’s stress, anxiety, mood, and behavior (the bidirectional gut-brain axis) and the important effect of gut microbiota ,indicating the need for investigation of human gut microbiota and mood disorders interaction. Mood disturbance is common in the population, and depression ranks high in the global disease burden and takes away over 700,000 people’s lives every year. A review study showed inconsistent associations of depression and microbial traits, which might be caused by the environment and host genes. The heritability of specific bacteria abundance estimated from twin studies in human was moderate, indicating the need to investigate the impacts of host genetic factors on gut microbiota. Microbiome genome-wide association studies (mbGWAS) were recently used to study the interaction between host genetic variants and microbiota composition. It is still a field in its infancy and lacks overlap for even the most vital signals among studies and is mostly conducted in European or American healthy populations. To fill in the study gaps, the current study explored associations between genetic variants and gut microbiota in a Taiwanese sample. It evaluated whether findings in the previous mbGWAS in European populations can be replicated. We also explicitly investigated the relationships between associated genes for mood disorders and gut microbiota among depressive patients using a case-only design. We recruited 280 adult patients with mood disorders (143 major depressive disorder and 137 bipolar disorder under depressive episode) in several central and regional hospitals in Taipei and 101 healthy controls. We assessed demographic, clinical and dietary information using interviewed and self-reported questionnaires. For stool samples, we amplified V3-V4 and V4 only regions of the 16S rRNA gene for sequencing and identified microbiota at the genus level. Genetic variants were genotyped from blood samples. We conducted two models (whole samples and case only) using multivariate linear and logistic regression to analyze microbiota data with relevant covariates adjusted to minimize their influences on gut microbiota composition. We then extracted residuals from these models to perform genetic association analysis using additive genetic model. Satisfying a GWAS evidence threshold P < 5 × 10?8, we identified 14 and 9 significant signals for the association between taxa and genetic markers in qualified 368 samples and 267 cases, respectively. Notably, there were four genes, including LRP1B, NPSR1-AS1, MGAT5, and SLIT3, replicated previous mbGWAS results, although not precisely the same SNPs and associated taxa. Furthermore, using case-only design helps us explore exclusive 5 signals only shown in depression patients. However, uthe nderlying mechanism of these associations is still unknown. Future studies are needed to expand the sample size for more stable and replicated results in Taiwanese and conduct animal modto investigaten of host molecular biology and disease. With a further expanded discovery of convincing genetic variants contributing to gut microbiota composition, there will be more insights into host-microbial interaction and the mechanisms of diseases, including mood disturbances. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T21:06:20Z (GMT). No. of bitstreams: 1 U0001-2209202204554800.pdf: 5316651 bytes, checksum: ff593c9c82500a72b8839fcd898c7de5 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 致謝 I 摘要 II Abstract IV Chapter 1 Introduction 1 1.1 Background 1 1.1.1 The role of gut microbiota in health 1 1.1.2 The Gut-Brain axis 1 1.1.3 Gut microbiota and mood disorders 2 1.1.4 Association between host genetic variants and gut microbiota composition 3 1.2 Study aims 5 Chapter 2 Materials and Methods 6 2.1 Participants 6 2.2 Assessment 6 2.2.1 Clinical characteristics and mood severity 6 2.2.2 Dietary characteristics 8 2.3 Stool sample collection and Gut microbiota sequencing 8 2.3.1 Sample collection 8 2.3.2 DNA extraction 9 2.3.3 Sequencing 10 2.4 16S rRNA microbiota data processing and trait preparation 11 2.4.1 QIIME2 dada2 denoise 11 2.4.2 α-diversity and β-diversity 11 2.4.3 Taxa retention and transformation 12 2.5 Genotyping and quality control 13 2.5.1 DNA extraction from blood samples 13 2.5.2 Genome-wide genotyping 13 2.5.3 Imputation and quality control (QC) 14 2.6 Statistical analysis 14 2.6.1 Description of demographics and clinical characteristics 14 2.6.2 Association analysis of genetic variates and microbiota traits 15 Chapter 3 Results 17 3.1 Demographic, clinical, dietary and stool-related characteristics 17 3.2 Gut microbiota traits – distribution and diversity indices 18 3.3 Genome-wide association analysis 19 3.3.1 Results of Model 1 (All participants) 19 3.3.2 Results of Model 2 (Case only) 20 3.3.3 Replicated mbGWAS results 21 Chapter 4 Discussion 22 4.1 Association between host genetic variates and gut microbiota 22 4.2 Limitations 26 4.3 Conclusion 27 References 28 Figures 35 Tables 43 Supplementary 48 | |
| dc.language.iso | en | |
| dc.subject | 情緒疾患 | zh_TW |
| dc.subject | 腸道菌相 | zh_TW |
| dc.subject | 全基因體關聯分析 | zh_TW |
| dc.subject | 宿主遺傳變異 | zh_TW |
| dc.subject | 憂鬱 | zh_TW |
| dc.subject | Gut microbiota | en |
| dc.subject | mood disorder | en |
| dc.subject | depression | en |
| dc.subject | host genetic | en |
| dc.subject | Genome-wide association analysis | en |
| dc.title | 情緒疾患宿主之遺傳變異與腸道菌相組成之關聯性 | zh_TW |
| dc.title | Association between host genetic variants and gut microbiota composition in mood disorders | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 盧子彬(Tzu-Pin Lu),馮嬿臻(Yen-Chen Anne Feng),吳偉愷(Wei-Kai Wu) | |
| dc.subject.keyword | 腸道菌相,全基因體關聯分析,宿主遺傳變異,憂鬱,情緒疾患, | zh_TW |
| dc.subject.keyword | Gut microbiota,Genome-wide association analysis,host genetic,depression,mood disorder, | en |
| dc.relation.page | 63 | |
| dc.identifier.doi | 10.6342/NTU202203786 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2022-09-22 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
| 顯示於系所單位： | 流行病學與預防醫學研究所 | |
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