評估遺忘型輕度認知功能障礙亞型的代償機制

Abstract

研究目的: 遺忘型輕度認知障礙被認為有很高的機率會轉換成阿茲海默症，且它能夠再細分成遺忘型單認知域及遺忘型多認知域的輕度認知功能障礙。當病患的認知功能中只有情境記憶受損，則被歸類為遺忘型單認知域輕度認知功能障礙，如果除了情境記憶外還有其他認知功能受損，則歸類為遺忘型多認知域輕度認知功能障礙。過去的文獻當中，已經有很多核磁共振的研究發現在神經性退化疾病存在著代償機制，聲稱包括阿茲海默症和輕度認知功能障礙在內的許多疾病都有很明顯的代償機制。相對的，很少有文獻探討遺忘型輕度認知障礙的代償機制，特別是遺忘型單認知域及遺忘型多認知域的輕度認知功能障礙。在本研究當中，我們透過比較神經纖維之共變性變化矩陣 (tract covariance matrix) 來檢驗遺忘型單認知域輕度認知功能障礙白質成功的代償機制，遺忘型多認知域輕度認知功能障礙白質不成功的代償機制之假設，我們更進一步地去探討與許多關鍵認知任務相關的網路，包含情境記憶、語言、感覺運動和注意力網路。 研究方法： 我們招收28名健康老人、25名遺忘型單認知域輕度認知功能障礙與22名遺忘型多認知域輕度認知功能障礙，輕度認知功能障礙的診斷是基於國際工作組織，並且基於先前的研究評估認知功能變化。我們於3T磁振造影儀進行75位受試者之T1 權重結構影像(T1WI)與擴散頻譜影像(diffusion spectrum imaging, DSI) 掃描，觀察大腦白質神經纖維束之水分子擴散特性，計算水分子在白質神經纖維中之非等向性指標(generalized fractional anisotropy, GFA)，透過全腦基於神經束之自動化分析(Tract-based automatic analysis, TBAA)來擷取全腦主要76條神經纖維束之GFA值，我們平均每條神經纖維束之路徑上的GFA值後進行神經纖維束之共變性分析來得到神經纖維之共變性變化矩陣。神經纖維束之共變性是使用淨相關(partial correlation)的方法控制年齡、性別和Fazekas scale之影響後，進行76條神經纖維束中任意兩條在同一群體受試者之間之共變性分析。接著，我們利用隨機排列統計檢定(random permutation statistics)找出組間神經纖維之共變性變化矩陣間的差異(p<0.01)，並更進一步找出與情境記憶、語言、感覺運動和注意力網路相關之白質的差異。最後，我們透過散佈圖以及圓圈圖來比較這些有差異的z值(Fisher z轉換的淨相關係數)。 研究結果與討論： 在情境記憶網路分析中，遺忘型單認知域及遺忘型多認知域的輕度認知功能障礙之神經纖維之共變性（亦即z值）是下降的。這個結果被認為是不成功的代償機制。在語言與感覺運動網路分析中，我們觀察到神經纖維之共變性在遺忘型單認知域輕度認知功能障礙是上升的，在遺忘型多認知域的輕度認知功能障礙是下降的。這個結果暗示著遺忘型單認知域輕度認知功能障礙透過成功的代償機制來維持基本功能，遺忘型多認知域輕度認知功能障礙則因為不成功的代償機制，所以語言與感覺運動的功能下降了。在注意力網路分析中，遺忘型單認知域及遺忘型多認知域的輕度認知功能障礙之神經纖維之共變性是上升的。可是，相對於遺忘型單認知域輕度認知功能障礙，遺忘型多認知域輕度認知功能障礙的神經纖維之共變性是明顯較低的。這個結果被認為是遺忘型單認知域輕度認知功能障礙的代償機制是成功的，遺忘型多認知域輕度認知功能障礙之代償機制則是不成功的。 結論： 本研究結果支持了遺忘型單認知域輕度認知功能障礙白質成功的代償機制，遺忘型多認知域輕度認知功能障礙白質不成功的代償機制之假設。特別的是，我們發現情境記憶、語言、感覺運動和注意力網路之白質代償機制的表現在兩組當中是有顯著差異的。從這結果，我們還推測成功的代償機制是發生在遺忘型輕度認知功能障礙的初期階段，並且在症狀更嚴重的階段變得不成功了。

Introduction: Amnestic MCI (aMCI) is of high risk to early AD, and could be further categorized into single-domain aMCI (SD-aMCI) and multi-domain aMCI (MD-aMCI). The cognitive decline seen in SD-aMCI is especially prominent in episodic memory, and MD-aMCI represents additional deficits in at least one other cognitive domains. In previous studies, many MRI studies have explored compensation in neurodegenerative disease, claiming that compensation is evident across a number of disorders, including AD and MCI. Comparatively, few studies observed compensation in aMCI, especially in SD-aMCI and MD-aMCI. In the present study, we tested the hypothesis which described the successful white matter compensation in SD-aMCI and unsuccessful compensation in MD-aMCI by compared white matter tract covariance matrices, we especially discussed the episodic memory, language, sensorimotor and attention networks that associated many key cognitive tasks. Materials and Methods: Three groups of participants were recruited in the study: 28 healthy aging participants (age: 71.0±5.25 years, male:14), 25 patients with SD-aMCI (age: 73.0±7.49 years, male:12), and 22 patients with MD-aMCI (age: 73.0±7.85 years, male:16). MCI was diagnosed based on the International Working Group and cognitive changes were assessed based on a previous study. The patients with merely impaired episodic memory were classified into SD- aMCI, otherwise, MD-aMCI. All participants received T1-weighted imaging (T1WI) and diffusion spectrum imaging (DSI) on a 3T MRI system. Then, we used tract-based automatic analysis to obtain generalized fractional anisotropy (GFA) values of 76 white matter tracts. Tract covariance was defined as the partial correlation of GFA values across subjects between each pair of tracts, using age, sex, and Fazekas scale as confounders. We used random permutation statistics to examine the differences (p<0.01) of tract covariance between three groups, and further found out the differences that related to the white matter tract of episodic memory, language, sensorimotor and attention networks. Finally, we compared z value (Fisher z -transformed partial correlation coefficients) of these differences by scatter and circos plots. Results and Discussions: The decreased tract covariance (i.e. z value) of the episodic memory network suggested that compensatory mechanisms unsuccessful in SD-aMCI and MD-aMCI. In language and sensorimotor network, we observed increased tract covariance in SD-aMCI and decreased in MD-aMCI. These results implied that the SD-aMCI maintained basic function through tract-to-tract successful compensation and reduced the language and sensorimotor ability due to unsuccessful compensation in patients with MD-aMCI. In attention network, the tract covariance of SD-aMCI and MD-aMCI were increased. However, MD-aMCI showed significantly lower tract covariance compared to SD-aMCI. These results suggested that the successful compensation in SD-aMCI and the unsuccessful compensation in patients with MD-aMCI. Conclusion: The present study results supported our hypothesis that the successful white matter compensation in SD-aMCI and unsuccessful compensation in MD-aMCI. Especially, the performance of white matter compensation in the episodic memory, language, sensorimotor and attention networks were significantly difference between two groups. From present study results, we also suggested that the successful compensation at the beginning of the aMCI patients and unsuccessful in patients with more severe symptoms.