分享:
分享到微信朋友圈
X
综述
帕金森病患者脑结构与功能改变及代谢紊乱相关因素MRI研究进展
李琬瑶 杜伟 苗延巍

Cite this article as: Li WY, Du W, Miao YW. Advances in MRI study of brain structure and function changes and related factors of metabolic disorders in Parkinson's disease[J]. Chin J Magn Reson Imaging, 2022, 13(7): 138-142.本文引用格式:李琬瑶, 杜伟, 苗延巍. 帕金森病患者脑结构与功能改变及代谢紊乱相关因素MRI研究进展[J]. 磁共振成像, 2022, 13(7): 138-142. DOI:10.12015/issn.1674-8034.2022.07.027.


[摘要] 帕金森病(Parkinson's disease, PD)是一种进行性中枢神经系统退行性疾病,以神经营养不良导致脑结构改变和功能丧失为特征。代谢综合征(metabolic syndrome, MS)是指一组导致胰岛素抵抗的若干相互关联的脑血管疾病危险因素。近年来越来越多研究表明代谢紊乱可严重影响神经退行性疾病的诱发和进展。MRI是一项评估脑结构和功能改变的无创技术。现就PD患者脑结构与功能改变及代谢紊乱相关因素MRI研究进展进行综述。
[Abstract] Parkinson's disease (PD) is a progressive degenerative disease of the central nervous system, characterized by brain structural change and loss of function caused by neurodystrophy. Metabolic syndrome (MS) refers to a group of interrelated cerebrovascular disease risk factors that lead to insulin resistance. In recent years, more and more studies have shown that metabolic disorders can seriously affect the induction and progression of neurodegenerative diseases. MRI is a non-invasive technique to evaluate the changes of brain structure and function. This article reviews the progress of MRI research on changes in brain structure and function and metabolic disorders in patients with PD.
[关键词] 帕金森病;代谢综合征;脑功能;脑结构;磁共振成像
[Keywords] Parkinson's disease;metabolic syndrome;brain function;brain structure;magnetic resonance imaging

李琬瑶    杜伟    苗延巍 *  

大连医科大学附属第一医院放射科,大连 116011

苗延巍,E-mail:ywmiao716@163.com

作者利益冲突声明:全体作者均声明无利益冲突。


基金项目: 国家自然科学基金 81671646
收稿日期:2022-01-26
接受日期:2022-06-22
中图分类号:R445.2  R742.5 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2022.07.027
本文引用格式:李琬瑶, 杜伟, 苗延巍. 帕金森病患者脑结构与功能改变及代谢紊乱相关因素MRI研究进展[J]. 磁共振成像, 2022, 13(7): 138-142. DOI:10.12015/issn.1674-8034.2022.07.027

       帕金森病(Parkinson's disease, PD)是一种随时间进展的累及中枢神经系统的退行性疾病,以神经营养不良导致脑结构改变和功能丧失为特征。PD主要临床表现包括运动特征和非运动特征,认知障碍是其重要的非运动特征之一,可发生在疾病的早期,甚至出现在运动特征之前[1]。中脑黑质致密部多巴胺神经元的选择性死亡和纹状体通路中路易小体的出现是PD的核心病理改变[2];但是,PD的病理改变不仅发生在黑质中,随疾病进展,路易小体从脑干扩展至皮层下区域,导致部分神经元坏死、丢失,进而导致大脑形态学改变[3]。近期研究表明,氧化应激是导致PD中多巴胺神经元变性的关键驱动因素[4]。脑形态学和结构改变是脑功能性改变的基础,而人体代谢平衡对于正常的神经元功能至关重要。代谢、微生物群和饮食是参与大脑存储和功能复杂网络的三个主要枢纽,当任何一个枢纽平衡受到破坏时,便可打破中枢神经系统的稳态[5]。代谢综合征(metabolic syndrome, MS)是导致糖尿病心脑血管疾病的危险因素,属于人体碳水化合物、脂肪和蛋白质等物质代谢紊乱的一种病理状态,其集簇发生可能与胰岛素抵抗有关。2型糖尿病(type 2 diabetes mellitus, T2DM)、肥胖、血脂异常和肝脏脂肪变性是MS的关键诱因,它们通过独立以及共同的机制来影响神经系统,导致共同的下游通路,如氧化应激、能量稳态改变、神经炎症和神经元死亡[6],其中氧化应激是MS的核心特征[7]。近年多项研究表明代谢紊乱严重影响神经退行性疾病的诱发和进展[8]。本文将对PD的代谢影响因素及影像改变进行综述。

1 PD患者脑结构与功能MRI研究

1.1 脑铁代谢

       多个研究发现PD患者黑质铁沉积过多,尤其是黑质致密部[9, 10, 11]。最近的一项研究通过高分辨率MRI在猴PD模型观察到黑质铁含量升高[12]。铁在灰质核团内分布是不均匀的,Ghassaban等[13]应用基于年龄的阈值定义高铁含量区域,发现黑质是唯一一个在PD患者中表现出明显易感性的结构。除黑质以外,PD患者的红核中也存在铁异常沉积[14]。高冰冰等[15]研究发现,PD患者苍白球、尾状核头、红核和黑质内均存在铁过量沉积,并且壳核、黑质以及红核内过度铁沉积与其微结构的改变具有不同程度的相关性,其中以黑质最为敏感。不同阶段的PD患者脑铁含量不同,高铁水平可能提示处于晚期,而低铁水平可能是疾病早期的信号[16]。研究表明,PD发病年龄对铁沉积模式有很大影响,早发型PD和晚发型PD患者黑质致密部和网状部铁含量均增加,然而壳核铁含量增加仅见于晚发型PD患者[17]。Blazejewska等[18]研究显示,正常人黑质小体-1在磁敏感加权成像(susceptibility weighted imaging, SWI)上呈黑质尾部背侧高信号(此区域铁含量较少),即“燕尾征”,而PD患者黑质铁含量增加导致黑质小体-1的SWI高信号缺失,即“燕尾征”消失。Calloni等[19]称黑质小体-1是PD的敏感标志物,但在PD与原发性非典型PD的鉴别中并不具特异性。脑铁沉积部位有助于对临床表现相近的PD综合征进行鉴别,Fedeli等[20]发现PD表型多系统萎缩患者和PD患者相比,进展性核上性麻痹患者的红核的铁沉积增加。脑铁沉积部位与其临床表型也具有相关性。He等[21]提出齿状核铁沉积是震颤型PD的潜在生物标志物(P=0.02),齿状核内的铁负荷可能在PD运动症状的发展中发挥重要的作用。脑铁异常沉积与PD病理严重程度、运动缺陷呈正相关,这一点被Shi等[22]的动物实验进一步证实。PD患者黑质铁含量与Hoehn and Yahr(H-Y)评分、统一帕金森病评定量表(Unifed Parkinson's Disease Rating Scale, UPDRS)和汉密尔顿焦虑量表(Hamilton Anxiety, HAMA)评分显著相关[23]

1.2 脑结构改变

1.2.1 灰质核团改变

       基底神经节萎缩是PD的主要病理改变之一。郭晓丽等[24]研究发现,PD患者基底节区灰质核团的体积与患者的H-Y分期呈负相关。Breen等[25]研究发现,PD患者下丘脑核团体积明显减小,可能是由于下丘脑中多巴胺神经元被破坏,导致神经元数量减少所致。然而,Crutcher等[26]研究结果显示,PD组尾状核、苍白球、壳核、海马、背侧丘脑、脑干体积与健康对照组没有差异。PD患者灰质核团萎缩与其临床症状具有相关性。Hagiwara等[27]发现PD患者区域性和全脑灰质体积减小与步态不稳及痴呆存在相关性。纹状体多巴胺能神经元缺失,纹状体苍白球丘脑网络到背外侧前额叶皮层的回路中断被认为是PD发生认知障碍的基础[28]。Vriend等[29]指出PD患者焦虑症状的严重程度与纹状体中可用的多巴胺转运蛋白的减少有关,杏仁核在情绪处理和恐惧条件反射中起重要作用;此项对110例伴有焦虑症状PD患者的杏仁核和海马体积与焦虑症状进行相关性分析显示,PD患者的焦虑症状与左侧杏仁核体积呈负相关。此外,高冰冰等[30]采用扩散峰度成像技术在PD组中发现黑质和苍白球中径向扩散峰度增加,提示灰质核团微结构改变。

1.2.2 大脑皮层改变

       大脑皮层是调节和控制机体运动的最高级中枢神经系统,平均厚度约为2.5~3.0 mm。皮层厚度虽然与人体衰老过程密切相关,但发生神经退行性疾病时会进一步降低,可以作为其影像诊断标准之一[31]。PD患者普遍存在大脑皮层萎缩。在一项最大规模的多中心研究中发现,所有PD患者平均皮质厚度均较正常人低,疾病程度越重时就越明显,并且在早期即可观察到额叶、颞叶皮层萎缩;额叶及颞叶的结构和功能异常是PD的重要影像特征之一[32]。张昌群等[33]发现在PD患者中,皮层厚度异常的区域主要包括颞叶、顶叶、右侧岛叶、左楔前叶和舌回,然而只有颞叶皮层萎缩早期即出现。Wilson等[34]的横断面研究显示,早期PD患者眶额区域皮质变薄,中期PD患者额上回、额中回尾侧和下顶叶皮质变薄,晚期PD患者颞叶和枕叶皮质进一步变薄,并推测PD患者皮质萎缩与疾病发展阶段和认知障碍具有相关性。Sampedro等[35]的纵向研究中表明,PD患者多巴胺能神经元丧失与额叶和枕叶皮质萎缩率增加有关,胆碱能神经元丧失进一步加重已经存在的皮质损伤。使用分层贝叶斯空间模型分析发现非痴呆的PD患者表现出广泛的皮质变薄,累及双侧顶下叶、顶上叶、额上叶和颞上叶[36]。PD患者认知障碍涉及胆碱能系统,尤其是位于基底前脑的Meynert基底核。Rong等[37]研究发现伴有认知障碍的PD患者的Meynert基底核体积减小,且与额叶、岛叶、顶叶和扣带回的皮质厚度具有相关性,而不伴认知障碍的PD患者和健康对照者则没有这种相关性。

1.2.3 脑白质改变

       脑白质结构的改变,如轴突直径、密度、髓鞘形成和方向以及白质结构连接,可能会在PD早期即有改变[38]。在早期PD患者中,典型运动障碍出现前可发生脑白质广泛损伤,特别是在扣带束、胼胝体和颞叶等区域[39]。扩散张量成像(diffusion tensor imaging, DTI)研究显示PD患者各向异性分数(fractional anisotropy, FA)减低的区域包括双侧上放射冠、前放射冠、视辐射、丘脑后辐射、穹窿和胼胝体等[40]。陈晨等[41]发现PD患者脑白质损伤主要表现在多个脑区FA值降低,而平均扩散率(mean diffusivity, MD)、轴向扩散率(axial diffusivity, AD)和径向扩散率(dadial diffusivity, RD)值升高,累及胼胝体、穹窿、前放射冠、后放射冠、上放射冠、外囊、内囊、丘脑后辐射、钩束等。PD不同亚型之间的白质完整性改变不同,以平衡障碍为主的亚型双侧上纵束的FA值降低[42];丘脑、放射冠、半卵圆中心和胼胝体的MD值升高,而以震颤亚型的皮质纹状体运动环路和额叶区域白质的参与程度更高[43]。Li等[44]研究发现,合并抑郁症状的PD患者在胼胝体、右侧前放射冠和左侧海马均出现白质微结构损伤。对于伴有非运动症状的PD患者来说,合并不同的非运动症状,其脑白质完整性改变也不同。Zarkali等[45]基于fixel分析,进一步观察到伴有幻觉的PD患者表现出胼胝体压部和左侧丘脑后辐射的宏观结构改变;视觉障碍的PD患者表现为胼胝体膝部和压部、双侧丘脑后辐射和左侧额枕下束广泛的微结构和宏观结构改变。Bledsoe等[46]研究表明,认知功能受损的PD患者胼胝体区白质的AD值、MD值和RD值均高于认知功能正常的PD患者,但两组间FA值无差异;此外,DTI参数与PD患者在不同认知领域的表现之间也存在显著关联。

1.3 脑功能网络连接

       人类大脑的神经网络控制着运动、学习、思考、说话和情感,在神经退行性疾病的研究中发挥着基础性作用,具有“小世界”属性、拓扑稳定性和高效性[47]。血氧水平依赖(blood oxygenation level dependent, BOLD)功能磁共振成像(functional magnetic resonance imaging, fMRI)可以准确地评估与PD感觉运动功能障碍相关的全脑功能连接。Wang等[48]通过脑功能网络连接分析发现PD患者感觉运动网络中感觉皮层与运动皮层之间的连接减少,小脑与岛叶网络之间的连接减少,主要改变部位为中央旁小叶、双侧中央后回、双侧岛叶后及小脑。一些研究者还发现,在运动相关的小脑和感觉运动网络之间的功能连接减少,感觉运动网络内部的功能连接减少[49]。Hepp等[50]研究发现伴有视幻觉的PD患者功能连接性明显减低,涉及额叶、颞叶、枕叶和纹状体等结构,部分脑区的功能连接部分与认知障碍有关。Ji等[51]通过交叉验证Meta分析,发现PD患者左中央后回皮质基底神经节-丘脑皮层网络的功能连接增加。Maiti等[52]研究表明,伴有认知障碍PD组的小脑蚓部和背外侧前额叶皮层之间的静息状态功能连接减弱。部分研究显示伴有抑郁的PD患者左侧额中回的局部一致性(regional homogeneity, ReHo)显著增加,左侧扣带回、双侧舌回和左侧杏仁核的ReHo减低[53]。动脉自旋标记(arterial spin labeling, ASL)是一种有前景的PD评估技术,可以在不使用外源性对比剂的情况下进行绝对脑血流量(cerebral blood flow, CBF)评估。事实上,使用ASL可以发现PD的异常脑灌注模式。该技术被证明可以有效地检测非痴呆性PD患者的CBF改变[54]。研究表明PD患者和HC之间没有发现显著的CBF差异。然而,在下丘脑核内观察到灌注增加的趋势(在FDR校正前显著),由更大的CBF反映的下丘脑核的高代谢与神经元活动的增加和不规则放电模式相一致[55]。另外一项研究显示PD患者在疾病早期和中期都存在壳核灌注不足[56]

2 MS对PD影响的临床与基础研究

       研究表明,PD的一些机制途径(如脂代谢异常、氧化应激和神经炎症)与MS中观察到的系统性代谢功能障碍有一些相同的组成元素[57]。MS被认为是PD的早期危险因素[58],是PD患者抑郁、脑白质损伤和认知障碍的风险因素[59]。甚至,有人提出代谢紊乱可能是PD的病因[60]。Rahmani等[61]研究表明减重或代谢保护疗法对有PD疾病风险的患者有益。Roos等[62]研究发现体质量指数(body mass index, BMI)≥30与BMI<25相比,PD患病风险增加13%,但并无证据表明高BMI会增加PD的风险。一项队列研究发现BMI和PD患病率之间呈正相关,揭示肥胖(BMI>30)是PD的独立危险因素[63]。但是,部分流行病学研究并未发现BMI与PD之间存在相关性[64]。也有研究发现体质量过轻(BMI<18.5)者患PD的风险也增加1.56倍(95% CI:1.35~1.82)[65]。此外,其他肥胖指标,如有较高的三头肌皮褶厚度[66]和腰臀比的患者具有更高的PD患病风险,提示与整体体质量相比,中心性肥胖可能是更敏感的患病风险指标。

       神经元具有复杂的结构特征,长时间的神经元投射和广泛的突触连接,使得它们需要更高的能量代谢来维持其结构复杂性[67]。成人大脑中的神经元主要依赖葡萄糖作为能量来源[68]。正常衰老过程中,神经细胞的氧和葡萄糖代谢率逐渐降低,而在PD、阿尔茨海默病、肌萎缩性侧索硬化症和亨廷顿病等疾病中则会进一步恶化[69]。MRI和正电子发射断层扫描技术已经证实PD患者的大脑中葡萄糖代谢率减低[70]。在PD早期阶段,壳核和小脑中磷酸戊糖途径关键酶(葡萄糖-6-磷酸脱氢酶和6-磷酸葡萄糖酸脱氢酶)减少[71]。一项随访10年的研究采用Cox生存分析模型在调整年龄、性别和药物使用条件后得出,与非T2DM队列相比,T2DM队列中PD的发病率高1.19倍(95% CI:1.08~1.32)[72]。T2DM进一步加重PD患者的运动症状(HR:4.521;95% CI:1.35~1.82;P<0.01)和认知功能障碍(HR:9.314;95% CI:1.164~74.519;P<0.05)[73]。Santiago等[74]实验研究支持多巴胺能神经元胰岛素抵抗是PD相关神经退行性变重要因素的假设。但是,美国一项大规模队列研究并未发现PD与T2DM之间存在相关性,推测可能由于其他代谢因素基线不平而导致影响其发病风险[75]。高胆固醇血症与PD之间的关系尚不明确。Rotterdam队列研究和HAAS队列研究均发现高血清胆固醇的患者罹患PD的风险较低[76]。一项Meta分析收集了8项前瞻性研究和13项回顾性研究,表明总胆固醇对PD具有保护作用[77]。早期PD患者较高的胆固醇水平与疾病进展缓慢[78]和较低的黑质铁含量[79]相关,这也揭示了胆固醇代谢在多巴胺能神经毒性中的潜在作用。但是,Paul等[80]研究表明,高胆固醇是PD的危险因素,胆固醇可导致α突触核蛋白的沉积和多巴胺神经元的损伤。流行病学显示高胆固醇血症可诱发PD动物模型的表型恶化[81]。Liu等[82]研究表明高密度脂蛋白(high density lipoprotein, HDL)直接参与抗炎和抗氧化作用,会减少铁蛋白中铁的释放,HDL不足会增加神经元变性的风险。HDL缺乏也可通过影响动脉粥样硬化风险而导致认知能力下降[83]。然而,血脂水平在PD中的作用仍需进一步研究。

       Gillies等[84]发现男性PD患者血清尿酸水平明显降低,而在女性中没有观察到,可能与雌激素对女性尿酸代谢的不同影响有关。研究表明尿酸对PD具有保护作用,可通过自由基清除剂和铁螯合剂在神经元中发挥抗氧化作用[85]。尿酸水平较低与尾状体、壳核中多巴胺转运结合蛋白较低显著相关[86]。一项Meta分析结果显示PD患者血清尿酸水平明显低于性别和年龄匹配的健康对照组,且不存在地理区域差异和性别差异[87]。以上均是单一代谢因素对PD患病率的影响,Nam等[57]研究发现MS不仅是PD的影响因素,PD发病风险还会随MS组分个数的增多而升高。

3 MS对PD影响的MRI研究

       Pagano基于FreeSurfer分析发现,PD伴T2DM组与PD不伴T2DM组相比灰质体积与皮层厚度无差异[73]。Petrou等[88]比较了12例PD伴T2DM患者与24例PD患者,发现T2DM选择性地影响PD患者额叶区域的灰质体积,执行和视觉空间认知功能与T2DM的存在以及额叶灰质体积的损失有关。最近的另一项研究表明,PD伴T2DM患者的灰质(皮层、尾状核、壳核、杏仁核和伏隔核)和白质(额叶、顶叶和颞叶)体积发生了变化,并且长达29个月的随访发现PD伴T2DM患者在顶叶和枕叶区域较PD不伴T2DM患者表现出更明显的脑白质萎缩[89]。由于以上研究未统一研究期间T2DM的药物治疗,并且T2DM在PD的某一时段会对其进行代偿,因此,各研究结果不一致。目前,其他代谢紊乱因素对PD影响的影像学研究尚未见报道。

4 总结与展望

       MS可影响PD的罹患风险及灰白质结构变化,但目前的相关研究有限且结果也不尽一致。氧化应激可能为PD与MS间共同的损伤机制,并且PD患者和MS患者在脑结构和功能方面有相关的改变,深入了解MS对PD的影响对改善患者预后有重要意义。然而关于MS对PD患者脑结构及功能改变的影像学研究较少,需要进一步深入。

[1]
Polo-Morales A, Alcocer-Salas A, Rodríguez-Violante M, et al. Association Between Somatization and Nonmotor Symptoms Severity in People With Parkinson Disease[J]. J Geriatr Psychiatry Neurol, 2021, 34(1): 60-65. DOI: 10.1177/0891988720901787.
[2]
Cuenca L, Gil-Martinez AL, Cano-Fernandez L, et al. Parkinson's disease: a short story of 200 years[J]. Histol Histopathol, 2019, 34(6): 573-591. DOI: 10.14670/HH-18-073.
[3]
Chung KK, Zhang Y, Lim KL, et al. Parkin ubiquitinates the alpha-synuclein-interacting protein, synphilin-1: implications for Lewy-body formation in Parkinson disease[J]. Nat Med, 2001, 7(10): 1144-1150. DOI: 10.1038/nm1001-1144.
[4]
Trist BG, Hare DJ, Double KL. Oxidative stress in the aging substantia nigra and the etiology of Parkinson's disease[J/OL]. Aging Cell, 2019, 18(6) [2022-01-26]. https://onlinelibrary.wiley.com/doi/10.1111/acel.13031. DOI: 10.1111/acel.13031.
[5]
Gentile F, Doneddu PE, Riva N, et al. Diet, Microbiota and Brain Health: Unraveling the Network Intersecting Metabolism and Neurodegeneration[J/OL]. Int J Mol Sci, 2020, 21(20) [2022-01-26]. https://www.mdpi.com/1422-0067/21/20/7471. DOI: 10.3390/ijms21207471.
[6]
Qin J, Li Y, Cai Z, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes[J]. Nature, 2012, 490(7418): 55-60. DOI: 10.1038/nature11450.
[7]
Carrier A. Metabolic Syndrome and Oxidative Stress: A Complex Relationship[J]. Antioxid Redox Signal, 2017, 26(9): 429-431. DOI: 10.1089/ars.2016.6929.
[8]
Camandola S, Mattson MP. Brain metabolism in health, aging, and neurodegeneration[J]. EMBO J, 2017, 36(11): 1474-1492. DOI: 10.15252/embj.201695810.
[9]
Murakami Y, Kakeda S, Watanabe K, et al. Usefulness of quantitative susceptibility mapping for the diagnosis of Parkinson disease[J]. AJNR Am J Neuroradiol, 2015, 36(6): 1102-1108. DOI: 10.3174/ajnr.A4260.
[10]
He N, Ling H, Ding B, et al. Region-specific disturbed iron distribution in early idiopathic Parkinson's disease measured by quantitative susceptibility mapping[J]. Hum Brain Mapp, 2015, 36(11): 4407-4420. DOI: 10.1002/hbm.22928.
[11]
Guan X, Xuan M, Gu Q, et al. Regionally progressive accumulation of iron in Parkinson's disease as measured by quantitative susceptibility mapping[J/OL]. NMR Biomed, 2017, 30(4) [2022-01-26]. https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/nbm.3489. DOI: 10.1002/nbm.3489.
[12]
Li SJ, Ren YD, Li J, et al. The role of iron in Parkinson's disease monkeys assessed by susceptibility weighted imaging and inductively coupled plasma mass spectrometry[J/OL]. Life Sci, 2020, 240 [2022-01-26]. https://www.sciencedirect.com/science/article/abs/pii/S0024320519310185?via%3Dihub. DOI: 10.1016/j.lfs.2019.117091.
[13]
Ghassaban K, He N, Sethi SK, et al. Regional High Iron in the Substantia Nigra Differentiates Parkinson's Disease Patients From Healthy Controls[J/OL]. Front Aging Neurosci, 2019, 11 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fnagi.2019.00106/full. DOI: 10.3389/fnagi.2019.00106.
[14]
Martin-Bastida A, Lao-Kaim NP, Loane C, et al. Motor associations of iron accumulation in deep grey matter nuclei in Parkinson's disease: a cross-sectional study of iron-related magnetic resonance imaging susceptibility[J]. Eur J Neurol, 2017, 24(2): 357-365. DOI: 10.1111/ene.13208.
[15]
高冰冰, 苗延巍, 田诗云, 等. SWI与DKI对帕金森病患者脑灰质核团铁沉积及微观结构变化的联合研究[J]. 磁共振成像, 2017, 8(12): 881-886. DOI: 10.12015/issn.1674-8034.2017.12.001.
Gao BB, Miao YW, Tian SY, et al. SWI and DKI study of brain iron deposition and microstructure change in gray matter nucleus in Parkinson's disease[J]. Chin J Magn Reson Imaging, 2017, 8(12): 881-886. DOI: 10.12015/issn.1674-8034.2017.12.001.
[16]
Mochizuki H, Choong CJ, Baba K. Parkinson's disease and iron[J]. J Neural Transm (Vienna), 2020, 127(2): 181-187. DOI: 10.1007/s00702-020-02149-3.
[17]
Xuan M, Guan X, Gu Q, et al. Different iron deposition patterns in early- and middle-late-onset Parkinson's disease[J]. Parkinsonism Relat Disord, 2017, 44: 23-27. DOI: 10.1016/j.parkreldis.2017.08.013.
[18]
Blazejewska AI, Schwarz ST, Pitiot A, et al. Visualization of nigrosome 1 and its loss in PD: pathoanatomical correlation and in vivo 7T MRI[J]. Neurology, 2013, 81: 534-540. DOI: 10.1212/WNL.0000000000000398.
[19]
Calloni SF, Conte G, Sbaraini S, et al. Multiparametric MR imaging of Parkinsonisms at 3 tesla: Its role in the differentiation of idiopathic Parkinson's disease versus atypical Parkinsonian disorders[J]. Eur J Radiol, 2018, 109: 95-100. DOI: 10.1016/j.ejrad.2018.10.032.
[20]
Fedeli MP, Contarino VE, Siggillino S, et al. Iron deposition in Parkinsonisms: A Quantitative Susceptibility Mapping study in the deep grey matter[J/OL]. Eur J Radiol, 2020, 133 [2022-01-26]. https://www.ejradiology.com/article/S0720-048X(20)30584-2/fulltext. DOI: 10.1016/j.ejrad.2020.109394.
[21]
He N, Huang P, Ling H, et al. Dentate nucleus iron deposition is a potential biomarker for tremor-dominant Parkinson's disease[J/OL]. NMR Biomed, 2017, 30(4) [2022-01-26]. https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/nbm.3554. DOI: 10.1002/nbm.3554.
[22]
Shi L, Huang C, Luo Q, et al. The Association of Iron and the Pathologies of Parkinson's Diseases in MPTP/MPP+-Induced Neuronal Degeneration in Non-human Primates and in Cell Culture[J/OL]. Front Aging Neurosci, 2019, 11 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fnagi.2019.00215/full. DOI: 10.3389/fnagi.2019.00215.
[23]
An H, Zeng X, Niu T, et al. Quantifying iron deposition within the substantia nigra of Parkinson's disease by quantitative susceptibility mapping[J]. J Neurol Sci, 2018, 386: 46-52. DOI: 10.1016/j.jns.2018.01.008.
[24]
郭晓丽, 耿承军, 陈利华. 3.0T磁共振成像-磁敏感加权成像评估不同分期帕金森病患者基底节区体积的价值[J]. 实用临床医药杂志, 2021, 25(11): 18-21. DOI: 10.7619/jcmp.20211242.
Guo XL, Geng CJ, Chen LH. Value of 3.0T magnetic resonance imaging plussusceptibility weighted imaging in evaluating basal ganglia volume in patients withParkinson's disease at different stages[J]. Journal of Clinical Medicine in Practice, 2021, 25(11): 18-21. DOI: 10.7619/jcmp.20211242.
[25]
Breen DP, Nombela C, Vuono R, et al. Hypothalamic volume loss is associated with reduced melatonin output in Parkinson's disease[J]. Mov Disord, 2016, 31(7): 1062-1066. DOI: 10.1002/mds.26592.
[26]
Crutcher MD, DeLong MR. Single cell studies of the primate putamen[J]. Exp Brain Res, 1984, 53(2): 233-243. DOI: 10.1007/bf00238153.
[27]
Hagiwara A, Warntjes M, Hori M, et al. SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement[J]. Invest Radiol, 2017, 52(10): 647-657. DOI: 10.1097/RLI.0000000000000365.
[28]
Honma M, Kuroda T, Futamura A, et al. Mental time dysfunction in Parkinson's and Alzheimer's diseases[J]. Brain Nerve, 2015, 67(3): 297-302. DOI: 10.11477/mf.1416200135.
[29]
Vriend C, Boedhoe PS, Rutten S, et al. A smaller amygdala is associated with anxiety in Parkinson's disease: a combined FreeSurfer-VBM study[J]. J Neurol Neurosurg Psychiatry, 2016, 87(5): 493-500. DOI: 10.1136/jnnp-2015-310383.
[30]
Bingbing G, Yujing Z, Yanwei M, et al. Diffusion Kurtosis Imaging of Microstructural Changes in Gray Matter Nucleus in Parkinson Disease[J/OL]. Front Neurol, 2020, 11 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fneur.2020.00252/full. DOI: 10.3389/fneur.2020.00252.
[31]
Khundrakpam BS, Lewis JD, Kostopoulos P, et al. Cortical Thickness Abnormalities in Autism Spectrum Disorders Through Late Childhood, Adolescence, and Adulthood: A Large-Scale MRI Study[J]. Cereb Cortex, 2017, 27(3): 1721-1731. DOI: 10.1093/cercor/bhx038.
[32]
Laansma MA, Bright JK, Al-Bachari S, et al. International Multicenter Analysis of Brain Structure Across Clinical Stages of Parkinson's Disease[J]. Mov Disord, 2021, 36(11): 2583-2594. DOI: 10.1002/mds.28706.
[33]
张昌群. 早期帕金森病患者脑结构与功能的定量分析方法[D]. 青岛: 山东科技大学, 2019. DOI: 10.27275/d.cnki.gsdku.2019.000488.
Zhang CQ. Quantitative analysis methods of brain structure and function in patients with early Parkinson's disease[D]. Qingdao: Shandong University of Science and Technology, 2019. DOI: 10.27275/d.cnki.gsdku.2019.000488.
[34]
Wilson H, Niccolini F, Pellicano C, et al. Cortical thinning across Parkinson's disease stages and clinical correlates[J]. J Neurol Sci, 2019, 398: 31-38. DOI: 10.1016/j.jns.2019.01.020.
[35]
Sampedro F, Marín-Lahoz J, Martínez-Horta S, et al. Dopaminergic degeneration induces early posterior cortical thinning in Parkinson's disease[J]. Neurobiol Dis, 2019, 124: 29-35. DOI: 10.1016/j.nbd.2018.11.001.
[36]
Zhang L, Wang M, Sterling NW, et al. Cortical Thinning and Cognitive Impairment in Parkinson's Disease without Dementia[J]. IEEE/ACM Trans Comput Biol Bioinform, 2018, 15(2): 570-580. DOI: 10.1109/TCBB.2015.2465951.
[37]
Rong S, Li Y, Li B, et al. Meynert nucleus-related cortical thinning in Parkinson's disease with mild cognitive impairment[J]. Quant Imaging Med Surg, 2021, 11(4): 1554-1566. DOI: 10.21037/qims-20-444.
[38]
Bergamino M, Keeling EG, Mishra VR, et al. Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review[J/OL]. Front Neurol, 2020, 11 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fneur.2020.00314/full. DOI: 10.3389/fneur.2020.00314.
[39]
Sanjari Moghaddam H, Dolatshahi M, Mohebi F, et al. Structural white matter alterations as compensatory mechanisms in Parkinson's disease: A systematic review of diffusion tensor imaging studies[J]. J Neurosci Res, 2020, 98(7): 1398-1416. DOI: 10.1002/jnr.24617.
[40]
Pelizzari L, Di Tella S, Laganà MM, et al. White matter alterations in early Parkinson's disease: role of motor symptom lateralization[J]. Neurol Sci, 2020, 41(2): 357-364. DOI: 10.1007/s10072-019-04084-y.
[41]
陈晨. 帕金森病患者脑白质微结构改变的DTI评价[D]. 郑州: 郑州大学, 2019.
Chen C. DTI assessment of brain white matter structural changes in Parkinson's diseasepatients[D]. Zhengzhou: Zhengzhou University, 2019.
[42]
Gu Q, Huang P, Xuan M, et al. Greater loss of white matter integrity in postural instability and gait difficulty subtype of Parkinson's disease[J]. Can J Neurol Sci, 2014, 41(6): 763-768. DOI: 10.1017/cjn.2014.34.
[43]
Lewis SJ, Foltynie T, Blackwell AD, et al. Heterogeneity of Parkinson's disease in the early clinical stages using a data driven approach[J]. J Neurol Neurosurg Psychiatry, 2005, 76(3): 343-348. DOI: 10.1136/jnnp.2003.033530.
[44]
Li Z, Liu W, Xiao C, et al. Abnormal white matter microstructures in Parkinson's disease and comorbid depression: A whole-brain diffusion tensor imaging study[J/OL]. Neurosci Lett, 2020, 735 [2022-01-26]. https://linkinghub.elsevier.com/retrieve/pii/S0304394020305085. DOI: 10.1016/j.neulet.2020.135238.
[45]
Zarkali A, McColgan P, Leyland LA, et al. Fiber-specific white matter reductions in Parkinson hallucinations and visual dysfunction[J/OL]. Neurology, 2020, 94(14) [2022-01-26]. https://n.neurology.org/content/94/14/e1525. DOI: 10.1212/WNL.0000000000009014.
[46]
Bledsoe IO, Stebbins GT, Merkitch D, et al. White matter abnormalities in the corpus callosum with cognitive impairment in Parkinson disease[J/OL]. Neurology, 2018, 91(24) [2022-01-26]. https://n.neurology.org/content/91/24/e2244. DOI: 10.1212/WNL.0000000000006646.
[47]
Herrington TM, Briscoe J, Eskandar E. Structural and Functional Network Dysfunction in Parkinson Disease[J]. Radiology, 2017, 285(3): 725-727. DOI: 10.1148/radiol.247172401.
[48]
Wang S, Zhang Y, Lei J, et al. Investigation of sensorimotor dysfunction in Parkinson disease by resting-state fMRI[J/OL]. Neurosci Lett, 2021, 742 [2022-01-26]. https://linkinghub.elsevier.com/retrieve/pii/S0304394020307825. DOI: 10.1016/j.neulet.2020.135512.
[49]
Helmich RC. The cerebral basis of Parkinsonian tremor: A network perspective. Mov Disord, 2018, 33(2): 219-231. DOI: 10.1002/mds.27224.
[50]
Hepp DH, Foncke EMJ, Olde Dubbelink KTE, et al. Loss of Functional Connectivity in Patients with Parkinson Disease and Visual Hallucinations[J]. Radiology, 2017, 285(3): 896-903. DOI: 10.1148/radiol.2017170438.
[51]
Ji GJ, Hu P, Liu TT, et al. Functional Connectivity of the Corticobasal Ganglia-Thalamocortical Network in Parkinson Disease: A Systematic Review and Meta-Analysis with Cross-Validation[J]. Radiology, 2018, 287(3): 973-982. DOI: 10.1148/radiol.2018172183.
[52]
Maiti B, Koller JM, Snyder AZ, et al. Cognitive correlates of cerebellar resting-state functional connectivity in Parkinson disease[J/OL]. Neurology, 2020, 94(4) [2022-01-26]. https://n.neurology.org/content/94/4/e384. DOI: 10.1212/WNL.0000000000008754.
[53]
Wang M, Liao H, Shen Q, et al. Changed Resting-State Brain Signal in Parkinson's Patients With Mild Depression[J/OL]. Frontiers in Neurology, 2020, 11 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fneur.2020.00028/full. DOI: 10.3389/fneur.2020.00028.
[54]
Syrimi ZJ, Vojtisek L, Eliasova I, et al. Arterial spin labelling detects posterior cortical hypoperfusion in non-demented patients with Parkinson's disease[J]. J Neural Transm, 2017, 124 (5): 551-557. DOI: 10.1007/s00702-017-1703-1.
[55]
Pelizzari L, Laganà MM, Di TS, et al. Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson's Disease[J]. Front Aging Neurosci, 2019, 11: 134. DOI: 10.3389/fnagi.2019.00134.
[56]
Wei XB, Yan RH, Chen ZY, et al. Combined Diffusion Tensor Imaging and Arterial Spin Labeling as Markers of Early Parkinson's disease[J/OL]. Sci Rep, 2016, 6 [2022-01-26]. https://www.nature.com/articles/srep33762. DOI: 10.1038/srep33762.
[57]
Nam GE, Kim SM, Han K, et al. Metabolic syndrome and risk of Parkinson disease: A nationwide cohort study[J/OL]. PLoS Med, 2018, 15(8) [2022-01-26]. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002640. DOI: 10.1371/journal.pmed.1002640.
[58]
de Bem AF, Krolow R, Farias HR, et al. Animal Models of Metabolic Disorders in the Study of Neurodegenerative Diseases: An Overview[J/OL]. Front Neurosci, 2020, 14 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fnins.2020.604150/full. DOI: 10.3389/fnins.2020.604150.
[59]
de A Boleti AP, Almeida JA, Migliolo L. Impact of the metabolic syndrome on the evolution of neurodegenerative diseases[J]. Neural Regen Res, 2021, 16(4): 688-689. DOI: 10.4103/1673-5374.295329.
[60]
Alecu I, Bennett SAL. Dysregulated Lipid Metabolism and Its Role in α-Synucleinopathy in Parkinson's Disease[J/OL]. Front Neurosci, 2019, 13 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fnins.2019.00328/full. DOI: 10.3389/fnins.2019.00328.
[61]
Rahmani J, Roudsari AH, Bawadi H, et al. Body mass index and risk of Parkinson, Alzheimer, Dementia, and Dementia mortality: a systematic review and dose-response meta-analysis of cohort studies among 5 million participants[J]. Nutr Neurosci, 2020, 25(3): 425-431. DOI: 10.1080/1028415X.2020.1758888.
[62]
Roos E, Grotta A, Yang F, et al. Body mass index, sitting time, and risk of Parkinson disease[J/OL]. Neurology, 2018, 90(16) [2022-01-26]. https://n.neurology.org/content/90/16/e1413. DOI: 10.1212/WNL.0000000000005328.
[63]
Hu G, Jousilahti P, Nissinen A, et al. Body mass index and the risk of Parkinson disease[J]. Neurology, 2006, 67(11): 1955-1959. DOI: 10.1212/01.wnl.0000247052.18422.e5.
[64]
Kyrozis A, Ghika A, Stathopoulos P, et al. Dietary and lifestyle variables in relation to incidence of Parkinson's disease in Greece[J]. Eur J Epidemiol, 2013, 28(1): 67-77. DOI: 10.1007/s10654-012-9760-0.
[65]
Jeong SM, Han K, Kim D, et al. Body mass index, diabetes, and the risk of Parkinson's disease[J]. Mov Disord, 2020, 35(2): 236-244. DOI: 10.1002/mds.27922.
[66]
Abbott RD, Ross GW, White LR, et al. Midlife adiposity and the future risk of Parkinson's disease[J]. Neurology, 2002, 59(7): 1051-1057. DOI: 10.1212/wnl.59.7.1051.
[67]
Muddapu VR, Dharshini SAP, Chakravarthy VS, et al. Neurodegenerative Diseases-Is Metabolic Deficiency the Root Cause?[J/OL]. Front Neurosci, 2020, 14 [2022-01-26]. https://www.frontiersin.org/articles/10.3389/fnins.2020.00213/full. DOI: 10.3389/fnins.2020.00213.
[68]
Yin F, Boveris A, Cadenas E. Mitochondrial energy metabolism and redox signaling in brain aging and neurodegeneration[J]. Antioxid Redox Signal, 2014, 20(2): 353-71. DOI: 10.1089/ars.2012.4774.
[69]
Hoyer S. The young-adult and normally aged brain. Its blood flow and oxidative metabolism. A review—part I[J]. Arch Gerontol Geriatr, 1982, 1(2): 101-116. DOI: 10.1016/0167-4943(82)90010-3..
[70]
Borghammer P, Chakravarty M, Jonsdottir KY, et al. Cortical hypometabolism and hypoperfusion in Parkinson's disease is extensive: probably even at early disease stages[J]. Brain Struct Funct, 2014: 303-317. DOI: 10.1007/s00429-010-0246-0.
[71]
Dunn L, Allen GF, Mamais A, et al. Dysregulation of glucose metabolism is an early event in sporadic Parkinson's disease[J]. Neurobiol Aging, 2014, 35(5): 1111-1115. DOI: 10.1016/j.neurobiolaging.2013.11.001.
[72]
Yang YW, Hsieh TF, Li CI, et al. Increased risk of Parkinson disease with diabetes mellitus in a population-based study[J/OL]. Medicine (Baltimore), 2017, 96(3) [2022-01-26]. https://journals.lww.com/md-journal/Fulltext/2017/01200/Increased_risk_of_Parkinson_disease_with_diabetes.30.aspx. DOI: 10.1097/MD.0000000000005921.
[73]
Pagano G, Polychronis S, Wilson H, et al. Diabetes mellitus and Parkinson disease[J/OL]. Neurology, 2018, 90(19) [2022-01-26]. https://n.neurology.org/content/90/19/e1654. DOI: 10.1212/WNL.0000000000005475.
[74]
Santiago JA, Potashkin JA. Shared dysregulated pathways lead to Parkinson's disease and diabetes[J]. Trends Mol Med, 2013, 19(3): 176-186. DOI: 10.1016/j.molmed.2013.01.002.
[75]
Simon KC, Chen H, Schwarzschild M, et al. Hypertension, hypercholesterolemia, diabetes, and risk of Parkinson disease[J]. Neurology, 2007, 69(17): 1688-1695. DOI: 10.1212/01.wnl.0000271883.45010.8a.
[76]
Ascherio A, Schwarzschild MA. The epidemiology of Parkinson's disease: risk factors and prevention[J]. Lancet Neurol, 2016, 15(12): 1257-1272. DOI: 10.1016/S1474-4422(16)30230-7.
[77]
Fu X, Wang Y, He X, et al. A systematic review and meta-analysis of serum cholesterol and triglyceride levels in patients with Parkinson's disease[J]. Lipids Health Dis, 2020, 19(1): 97. DOI: 10.1186/s12944-020-01284-w.
[78]
Huang X, Auinger P, Eberly S, et al. Serum cholesterol and the progression of Parkinson's disease: results from DATATOP[J/OL]. PLoS One, 2011, 6(8) [2022-01-26]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0022854. DOI: 10.1371/journal.pone.0022854.
[79]
Du G, Lewis MM, Shaffer ML, et al. Serum cholesterol and nigrostriatal R2* values in Parkinson's disease[J/OL]. PLoS One, 2012, 7(4) [2022-01-26]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0035397. DOI: 10.1371/journal.pone.0035397.
[80]
Paul R, Choudhury A, Borah A. Cholesterol—A putative endogenous contributor towards Parkinson's disease[J]. Neurochem Int, 2015, 90: 125-133. DOI: 10.1016/j.neuint.2015.07.025.
[81]
Paul R, Choudhury A, Kumar S, et al. Cholesterol contributes to dopamine-neuronal loss in MPTP mouse model of Parkinson's disease: Involvement of mitochondrial dysfunctions and oxidative stress[J/OL]. PLoS One, 2017, 12(2) [2022-01-26]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0171285. DOI: 10.1371/journal.pone.0171285.
[82]
Liu Z, Fan Q, Wu S, et al. Compared with the monocyte to high-density lipoprotein ratio (MHR) and the neutrophil to lymphocyte ratio (NLR), the neutrophil to high-density lipoprotein ratio (NHR) is more valuable for assessing the inflammatory process in Parkinson's disease[J]. Lipids Health Dis, 2021, 20(1): 35. DOI: 10.1186/s12944-021-01462-4.
[83]
Bahrami A, Barreto GE, Lombardi G, et al. Emerging roles for high-density lipoproteins in neurodegenerative disorders[J]. Biofactors, 2019, 45(5): 725-739. DOI: 10.1002/biof.1541.
[84]
Gillies GE, McArthur S. Estrogen actions in the brain and the basis for differential action in men and women: a case for sex-specific medicines[J]. Pharmacol Rev, 2010, 62(2): 155-198. DOI: 10.1124/pr.109.002071.
[85]
Sakuta H, Suzuki K, Miyamoto T, et al. Serum uric acid levels in Parkinson's disease and related disorders[J/OL]. Brain Behav, 2017, 7(1) [2022-01-26]. https://onlinelibrary.wiley.com/doi/10.1002/brb3.598. DOI: 10.1002/brb3.598.
[86]
Moccia M, Pappatà S, Erro R, et al. Uric acid relates to dopamine transporter availability in Parkinson's disease[J]. Acta Neurol Scand, 2015, 131(2): 127-131. DOI: 10.1111/ane.12295.
[87]
Wen M, Zhou B, Chen YH, et al. Serum uric acid levels in patients with Parkinson's disease: A meta-analysis[J/OL]. PLoS One, 2017, 12(3) [2022-01-26]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0173731. DOI: 10.1371/journal.pone.0173731.
[88]
Petrou M, Davatzikos C, Hsieh M, et al. Diabetes, Gray Matter Loss, and Cognition in the Setting of Parkinson Disease[J]. Acad Radiol, 2016, 23(5): 577-581. DOI: 10.1016/j.acra.2015.07.014.
[89]
Ong M, Foo H, Chander RJ, et al. Influence of diabetes mellitus on longitudinal atrophy and cognition in Parkinson's disease[J]. J Neurol Sci, 2017, 377: 122-126. DOI: 10.1016/j.jns.2017.04.010.

上一篇 IgG4相关硬化性胆管炎的影像诊断现状
下一篇 功能磁共振成像在青少年肌阵挛性癫痫中的脑网络及内表型研究进展
  
诚聘英才 | 广告合作 | 免责声明 | 版权声明
联系电话:010-67113815
京ICP备19028836号-2