摘要:阻塞性睡眠呼吸中止症 (OSA)為睡眠時上呼吸道塌陷,進而引起慢性間歇性缺氧及睡眠片段。整夜睡眠多項生理檢查(PSG) 為目前 OSA 診斷標準,以每小時呼吸停止次數(AHI)為評量 OSA 嚴重度的指標,但其與 OSA 臨床嚴重度無法有很好的關聯。相同AHI 的病患,其臨床表現可從無症狀的單純打鼾到併發嗜睡及心血管疾病。 OSA 併發症包括心血管疾病,神經認知異常及代謝異常。許多研究顯示自由機產生、全身性發炎與內皮細胞功能失調,為造成 OSA 心血管疾病重要機制之一。連續陽壓呼吸器(CPAP)目前為 OSA 首選治療,可將 OSA 患者心血疾管風險降至跟常人一樣。然而CPAP 降低心血管併發症的機制尚未釐清。 現今研究顯示,OSA 是一個複雜性基因疾病,其臨床中度表型(phenotyping)包括髗顏特徵、呼吸驅動力及上呼吸道塌陷度、嗜睡感受力,以及體脂肪堆積及代謝症候群。雖然許多生物路徑被提出與 OSA 臨床表型相關,然而確切的機制仍未明。 代謝體(metabolomics)為最近發展的新技術,應用在瞭解基因缺陷、疾病機轉,與發掘生物標誌(biomarker)。近來許多利用研究探討缺氧細胞的代謝體變化,來瞭解細胞如何存活在低氧環境。我們之前針對缺氧模式乳癌細胞的研究,也顯示代謝體變化與文獻上以微陣舉列(microarray)發掘的生物路徑變化是相呼應的。此外代謝體也被應用在探討中藥的抗缺氧作用,提供了發展藥物的新途徑。 迄今僅有一研究探討 OSA 病患代謝體,其比較輕度及重度 OSA 的代謝體,結果顯示14 項特徵有統計意義且該變化與 AHI 相關。然而在該篇研究中,受試者的基準差異包括 OSA 嚴重度,身高體重指數(BMI)等未被控制,代謝體的差異可能源自基準線的差異而非 OSA 本身。為了克服此研究缺點,我們比較了 60 位重度 OSA 患者,在隨機接受12 星期 therapeutic 及 subtherapeutic CPAP 治療後血漿代謝體差異。結果顯示以subtherapeutic CPAP 為安慰劑控制生活習慣帶來的變因(如運動飲食),仍顯示 CPAP 的確可以改變代謝體表現。標的(profile) CPAP 治療前後有差異且牽涉在生物路徑的代謝物顯示,在 therapeutic CPAP 有 17 個代謝物在 3 個生物路徑上,在 subtherapeutic CPAP 則為 13 個代謝體在 6 個生物路徑上。比較 Therapeutic 及 subtherapeutic CPAP 兩組變化代謝體,則可找到 16 個代謝體在 3 個生物路徑上。雖然此研究控制可能變因,然而仍有幾個缺點,包括沒有正常人當控制組。60% OSA 受試者有內科疾病、CPAP 治療時間僅12 週無法代表長期效果,更重要的是有差異的代謝物與 OSA 直接關係必須藉由人體外model 方能證實。 因此為了克服文獻與我們之前研究的缺點,在此研究我們打算比較正常人與健康OSA 患者血漿代謝體差異,其中 OSA 患者為隨機經六個月 therapeutic 及 subtherapeutic CPAP 治療。接著在有差異的代謝體中,挑選牽涉在與臨床表型與 CPAP 治療反應相關的生物路徑的血漿候選代謝物(candidate metabolite)。其中臨床表型定義為嗜睡(Epworth Sleepiness Scale,ESS10),心血管疾病(高血壓或冠狀動脈疾病),以及代謝失調(以metabolic score評估)。CPAP治療反應則以CPAP治療前後ESS、24小時血壓,及metabolic score 變化量評估。接著,將 OSA 病患周邊血單核球以正常氧氣(21% O2)以及間歇缺氧器(1% O2)培養 48 小時,取上清液比較代謝體差異。最後血漿後候選代謝物再與上清液代謝物比較,以證實候選代謝物與相關生物路徑與 OSA 直接關係,特別是氧化還原,發炎,以及代謝等生物路徑。
Abstract: Background: Obstructive sleep apnea is characterized with chronic intermittent hypoxia and sleep fragmentations. The sequels of OSA included excessive daytime sleepiness, cardiovascular disease, and neurocognitive dysfunction which could be reversed with continuous positive airway pressure (CPAP). A couple of biologic pathways have been associated with the phenotyping of OSA which included craniofacial morphology, ventilator control, body fat distribution/metabolism, and sleepiness vulnerability. Metabolomics, a recently developed technique to detect metabolomic profiles, could help to understand the disease pathophysiology and explore biomarkers. So far, only one paper studied the metabolomic profile in patients with OSA where putative identifications of 14 statistically significant features were profiled. Our pilot study comparing the metabolic profiling in OSA patients randomly assigned to therapeutic and subtherapeutic CPAP showed CPAP treatment did alter the metabolomic profile. Seventeen metabolites in three biologic pathways and 13 metabolites in the six biologic pathways were identified in therapeutic and subtherapeutic CPAP, respectively. Sixteen metabolites in three biologic pathways were identified by comparing two groups. However, there were a couple of weakness in studies in the literature and ours. Furthermore, the direct causal relationship of the profiled metabolites and OSA needs to be clarified. Therefore, we plan to compare the metabolic profiling in control subjects and healthy OSA patients, before and after six-month CPAP treatment, to identify candidate metabolites involved in biologic pathways attributing to phenotyping and response to CPAP treatment. Furthermore, candidate metabolites involved in biologic pathways, especially pathways of ROS, inflammation, and metabolism, will be validated in the intermittent hypoxia model of peripheral monocytes. Aim: This three-year project aims to (1) Profile the differentially expressed metabolites in control subjects and healthy patients with severe OSA before and after six-month CPAP treatment (2) Identify the candidate metabolites involved in biologic pathways attributing to OSA phenotyping and response to CPAP treatment (3) Validate candidate metabolites in the intermittent-hypoxia model of peripheral monocytes Participants: 12 male control participants and 24 male healthy OSA patients Protocol: Enrolled participants are evaluated at baseline for OSA phenotyping which is defined as presence of excessive daytime sleepiness (EDS), cardiovascular disease (CVD), and metabolic dysregulation. EDS is defined as ESS 10 and CVD is defined as presence of hypertension or coronary artery disease (CAD) where the metabolic dysregulation is assessed with metabolic score. After completing baseline measurements, the OSA patients are randomly assigned to either therapeutic or subtherapeutic CPAP (<1 cmH2O) for six months and reevaluated at the end of treatment. The response to CPAP treatment is assessed in terms of change in ESS, 24hr blood pressure, and metabolic score. Blood sample is collected in the next morning of PSG after overnight fasting for isolation of plasma and monocyte. After resting for 24 hr, isolated monocyte are exposed to either normoxia (O2 21%) or intermittent hypoxia (O2 1%) for 48hr. The metabolomic assay of plasma and supernatant is conducted at the “The Metabolomics Core Laboratory” in National Taiwan University. Outcome: The plasma metabolomic profiles in control subjects and OSA patients before and after CPAP treatment; and supernatant metabolomic profiles in normoxia and intermittent hypoxia cell model were compared to profile differentially expressed metabolomic profile. The candidate metabolites involved in at least two biologic pathways attributing to phenotyping and response to CPAP treatment are identified from differentially plasma metabolomic profile. Furthermore, the candidate metabolites are compared to differentially supernatant metabolomic profile to validate metabolomic profile and the putative biologic pathways involved in the pathogenesis of OSA, especially pathway of ROS, inflammation, and metabolism.