近來微型RNA (MicroRNAs or miRNAs ) 已被證明是轉錄後基因表現的主要調節者，微型RNA表現的不正常也是許多疾病產生的原因，研究更顯示微型RNA 可在組織、血液、尿液中發現，亦與各種相關疾病及腫瘤有關。因miRNA表現量在體液相較其他分子穩定，自2008年開始便有以體液中微型RNA做為疾病標記的相關研究發表。因此，微型RNA有機會成為新穎的偵測疾病標記，並應用於治療和追蹤療效的疾病標記。 急性冠心症(ACS)是一種心血管疾病，是在季節變換的時候很容易發生，其發生的主因是供給心臟氧氣的冠狀動脈因為粥狀動脈硬化阻塞了原本的血液供給導致心肌缺氧造成，因為缺乏準確的預測標記所以目前還是臨床很嚴重的議題。目前臨床上使用cTn、CK-MB只能在發生心肌梗塞輔助診斷無法早期預測因此沒有一個良好的生物標記可以用來有效的預測或是當作治療的標的。miRNAs和mRNA比起來較有效且穩定性高也容易在周邊體液採集到。所以我們認為它是一種有潛力的生物標記可以用來預測、診斷ACS的發生。 我們利用世代研究法(cohort study)：又稱為前瞻法(prospective study)針對一群健康者，追蹤其處於健康危險因子下的發病情形。我們預計由壢新醫院生物資料庫中取得已罹患冠心症及未罹患冠心症者之血液樣本，並利用高通量qPCR和microRNA PCR array (為定量microRNA的實驗方法)的方式去分析他們之間的miRNAs表現量差異，藉此希望可以從中找出可以用來當作診斷、或預測的生物標記。我們已經分析四組受試者血液樣本，比較未罹患冠心症時及已罹患冠心症後，結果發現有些miRNAs是有明顯的區別，我們挑選出數個有潛力的miRNAs。 本次計畫中我們希望收160個受試者(80 ACS)利用數個有潛力的miRNAs找出一個公式可以預測受試者三年內罹患冠心症的機率，最後再收100個受試者(50 ACS)來驗證此公式。這種ACS新型標誌物的研究將有助於推動ACS的早期診斷及科學有效的醫療干預，對改善心梗預後及降低死亡率具有重要意義，其前景值得期待。 ;MicroRNAs (miRNAs) have revolutionized our comprehension of post-transcriptional regulation of gene expression and modulate a board range of biology function including the pathogenesis of disease. According to literature, miRNAs profiles are more effective and stable than mRNA profiles due to minor differences during sample preparation and can be collected around peripheral body fluids. This indicates miRNAs would be potential and novel biomarkers that can be applied in clinical diagnosis and prediction. Acute coronary syndrome (ACS) is a cardiac vascular disease and usually occurred in seasonal alternation. The coronary artery is blocked by atherosclerosis, and it causes lacking oxygen supply in myocardium. Lacking a sensitive and stable biomarker to predict the occurrence of ACS clinically is the serious issue. We collected blood samples from the same patient before and after ACS occurrence from cohort database of Landseed hospital. High-throughput quantification real-time PCR arrays were used to analysis the expression differences of miRNAs from plasma before and after ACS of same persons. The results indicate candidate miRNAs displayed significant differences after the development of ACS among these patients. In this project of the first year, we want to collect 160 samples (80 samples from ACS patients and 80 samples from health control with no ACS record at least 3 years) to measure the expressions of candidate miRNAs selected from our screen and miRNAs selected from ACS literature. We will produce the ACS miRNAs panel from our training group and further test another 100 samples in second year. We believe that training and testing groups data can established the ACS miRNAs panel which could be used in clinical ACS diagnosis and prediction. This new type of ACS miRNAs biomarker study would promote the early diagnosis of ACS and early medical intervention for health persons.
