生物資訊學於阿茲海默症研究之運用

Application of Bioinformatics in the Research of Alzheimer's Disease

黃柏穎(Poyin Huang)

指導教授 ： 陳璿宇

高雄醫學大學/醫學院/轉譯醫學博士學位學程/博士(2019年)

摘要

阿茲海默症Alzheimer’s Disease (AD)是最常見的失智症並且是一種很複雜的中樞神經系統疾病。由於人口日益老化，全世界越來越多的人口受到此疾病影響。這種疾病無法治癒，病人狀況只會隨著疾病的進展而惡化，最終導致死亡。AD是已開發國家最主要的死亡原因之一。在已開發國家十大死亡原因中，AD是唯一無法預防，治癒甚至減慢疾病進展速度的疾病。不管是在已開發國家或發展中國家，AD對罹病的患者、醫療從業相關人員和整個社會皆產生了巨大的衝擊與影響。然而，AD是一個異質性很高的疾病且成因至今尚不明確。目前主流的學說認為AD是由β類澱粉樣蛋白(amyloid plaques)及神經纖維糾結(neurofibrillary tangles)的形成、腦神經細胞失去連結與神經細胞凋亡所造成。除此之外，慢性神經發炎也被認為是造成AD的一項重要致病因子。雖然AD可分為早發型和晚發型，但不管是哪一種，其致病機轉應該類似且都跟基因具有一定程度的關聯性。隨著對AD的了解逐漸增加，研究學者發現基因在AD扮演著重要角色，並在不同種族之間存在著差異。舉例來說，ApoE基因就是一個眾所周知跟AD相關的基因。雖然目前已可抽血檢驗ApoE對偶基因型，但是ApoEε4頂多只能作為一項可以當作參考的跟AD相關之危險因子。ApoEε4對偶基因檢測並不能用來預測一個人是否會得到AD，或作為其他用途的AD相關生物標記。而其他比較知名的AD相關基因則包含了跟形成β類澱粉樣蛋白路經相關的APP，PSEN-1，PSEN-2和BACE等。至於跟AD慢性神經發炎這個致病機轉有關的基因，則是人類白細胞抗原(HLA)基因。HLA基因藉由調控神經發炎而與AD有關，而其他致病機轉如β類澱粉樣蛋白，也是透過在轉譯後有異常修飾而形成不斷累積的自體抗原，引起神經發炎，最終造成AD。因此，HLA基因型和自體抗原的呈現在AD應該具有重要角色，但因HLA基因的高度多態性和複雜結構使得相關的研究十分不易。
在過去十年中，與常見疾病相關的遺傳變異知識呈現爆炸式增長。雖然遺傳學在所有常見人類疾病，包括AD中皆扮演著重要角色，但目前為止並沒有適用的分子可以把AD做更細的分類，或當作生物標記以評估重要臨床資訊如預後等。由於近年來生物資訊學和次世代定序Next Generation Sequencing (NGS)技術的進步，我們已可使用NGS建立HLA精細的基因分型，並利用全外顯子定序的方法來搜尋有潛力作為生物標記的分子，並獲得以HLA基因分型為基礎的自體抗原呈現數據。因此，本博士論文是以AD為研究族群，想要(一)探討不同種族人口中AD相關基因組變異的頻率差異；(二)找尋可以作為AD生物標記的分子；(三)以NGS的定序技術結合生物資訊學的分析，來得到AD患者的HLA基因分型和以其為基礎的自體抗原呈現，以期闡明神經發炎在AD所扮演的角色。

關鍵字

阿茲海默症 ； 種族差異遺傳學 ； 生物標記 ； 神經發炎 ； 預後

並列摘要

Alzheimer's Disease (AD) is the most common form of dementia and is highly heterogeneous. AD is the leading cause of death in developed countries. Of the top ten causes of death in developed countries, AD is the only disease that cannot be prevented, cured or even slowed. In both developed and developing nations, AD has had an enormous impact on the affected patients, caregivers, and society as a whole. Currently, the pathogeneses of AD are still not clear. The main hypotheses include the amyloid plaques hypothesis, tau- protein neurofibrillary tangles hypothesis and chronic neuroinflammation. At present, neuroinflammation is considered to be one of the most important pathogeneses of AD.

Although AD can be divided into early-onset and late-onset, however, they both have similar pathogeneses and are associated with genetics to a certain degree. As the understanding of AD pathogeneses has increased, researchers have found that genetics play an important role in AD with prominent variations between different ethnics. For example, the ApoE gene is well-known to be associated with AD. Although now we are able to identify ApoE genotype in different individuals, ApoEε4 can only be considered as a risk factor associated with AD and cannot be used as a predictive biomarker for AD. Other well-known AD-associated genes include APP, PSEN-1, PSEN-2 and BACE, which are involved in the pathway of amyloid plaque formation. As for the gene associated with chronic neuroinflammation of AD, the human leukocyte antigen (HLA) gene plays a major role. Latest researches showed that HLA gene is associated with AD through regulation of neuroinflammation. Other important pathogeneses of AD including amyloid-β are also associated with neuroinflammation due to abnormally modified peptides after translation. These abnormally modified peptides became self antigens and induced neuroinflammation, ultimately causing AD. Therefore, HLA genotypes and self-antigen presentation should play an important role in AD, but it is difficult to study HLA gene due to the its high polymorphism and complex structure.

The last ten years has seen an explosion in the knowledge of genetic variants associated with common diseases. Genetics play a role in susceptibility to all common human diseases including AD, and so identifying genetic biomarkers including single nucleotide polymorphisms (SNPs) and epigenetic markers for AD may facilitate classification of individuals according to drug response, disease progression and prognosis, thereby improving therapeutic outcomes and allowing for personalized management. Currently there are no applicable molecules that can be used to classify AD or as a biomarker to assess important clinical outcomes such as prognosis or progression. Due to the advances in bioinformatics and Next Generation Sequencing (NGS) technology, we are now able to perform fine HLA genotyping and obtain self-antigen presentation data based on HLA genotyping using whole exome sequencing and targeted gene resequencing techniques. Whole exome sequencing and targeted gene resequencing techniques could also be used to search biomarkers for AD. In this doctoral dissertation, we aim to 1. Study differences in the frequency of AD-associated genomic variations in populations of different races; 2. Search potential biomarkers for AD; 3. Use NGS sequencing techniques combining bioinformatics to obtain HLA genotyping and self-antigen presentation in AD patients, in order to delineate the role of neuroinflammation in AD.

並列關鍵字

Alzheimer's disease ； racial differences ； genetics ； biomarker ； neuroinflammation ； prognosis

參考文獻

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