基于组学技术探讨生物标记物在抑郁症中的研究进展
2025-01-14刘洽程俊香刘娜杨国芳马辰婧赵奕雯朱瑞芳韩世范
摘要" 基于组学技术综述神经递质、神经内分泌系统、精神神经免疫系统、神经营养因子系统、代谢及神经影像学六大潜在抑郁症生物学标志物在抑郁症诊断、治疗、干预效果观察、预后及护理中的作用,以期对后续抑郁症的研究临床诊治及护理工作提供支持。
关键词" 抑郁症;生物学标志物;炎症;氧化应激;综述
doi:10.12102/j.issn.1009-6493.2025.01.026
基金项目 2023—2024年度山西省大健康产业高质量发展科研专项项目,编号:DJKZXKT2023002;山西省食疗和农产品处方产业技术创新战略联盟项目基金
作者简介 刘洽,护士,硕士研究生在读
通讯作者 韩世范,E⁃mail:shifan.han@sxmu.edu.cn;朱瑞芳,E⁃mail: ruifang.zhu@sxmu.edu.cn
引用信息 刘洽,程俊香,刘娜,等.基于组学技术探讨生物标记物在抑郁症中的研究进展[J].护理研究,2025,39(1):151⁃159.
Research progress on biomarkers in depression based on omics technologies
LIU Qia1, CHENG Junxiang1,2,LIU Na2,YANG Guofang1, MA Chenjing1, ZHAO Yiwen3, ZHU Ruifang1,2,3*, HAN Shifan1,2,4,5,6*
1.Nursing College, Shanxi Medical University, Shanxi 030001 China;2.First Hospital of Shanxi Medical University;3.Shanxi Medical Periodical Press Co.,Ltd.;4.Shanxi Province Food Therapy and Agricultural Products Prescription Industry Technology Innovation Strategic Alliance;5.Major Platform Carrier and Training Base for the Integration of Health Industry and Education in Shanxi Province;6.Dietotherapy Science and Technology Research Center, Shanxi Medical University
*Corresponding Author" HAN Shifan, E⁃mail: shifan.han@sxmu.edu.cn; ZHU Ruifang, E⁃mail: ruifang.zhu@sxmu.edu.cn
Abstract""" It summarizes the roles of six potential biological markers of depression based on omics technologies, including neurotransmitters, the neuroendocrine system,the psychoneuroimmune system,neurotrophic factor systems,metabolism⁃related factors, and neuroimaging, in the diagnosis,treatment,observation of intervention effects, and prognosis of depression. The aim is to provide support for subsequent research clinical diagnosis and treatment and nursing work on depression.
Keywords""" depression; biological markers; inflammation; oxidative stress; review
抑郁症(MDD)是一种常见的精神障碍,以持续的情绪低落、兴趣减退、意志力降低为主要临床表现,其终身患病率约为17%,全球约有3.5亿人受其影响。世界卫生组织报告,到2030年抑郁症在全球疾病总负担中将升至第1位[1]。该病常反复发作,自杀率高达15%~25%,已成为困扰人类身心健康的重大精神疾患,而抑郁症更是青少年发病和死亡的主要原因[2]。研究显示,抑郁症的患病风险自青少年早期开始上升并在整个青春期继续以线性方式上升,到青春期后期,终生患病率估计在15%~25%[3⁃4]。然而,与如此庞大的患病人群和疾病负担形成对比的是,迄今为止对这一疾病还缺乏行之有效、简便可靠的客观诊断及疗效预测方法。青少年抑郁发作或复发可能会持续到成年,对其生理、心理及社会功能产生负面影响。更好地了解抑郁症的病因、病理生理将有助于制定和实施更有效的一级和二级预防策略,从而降低抑郁的发病率[5]。目前普遍认为,抑郁症是由多种遗传和环境因素之间的复杂相互作用引起,而目前抑郁症的诊断还是基于自我经历、行为或家属、亲人基于对病人观察的报告,因此疾病诊断的不确定性高。Freedman等[6]采用Kappa 统计分析对精神疾病诊断与统计手册(DSM⁃Ⅴ)的诊断一致性进行测试,结果显示重度抑郁症的可靠性评估仅为28%。内表型或生物标志物有助于靶向分析潜在的机制,还可用于加强临床表型的分类,或区分可能的生物亚型,这些标志物反过来可能具有不同的临床或治疗特征,对临床诊断、治疗、干预效果观察、预后及护理提供支持[7]。近年来,随着各组学技术的不断发展,对抑郁症的生物学标志物的探索也有了新的突破,本研究基于组学技术在各系统假说的基础上对潜在的抑郁症标志物进行探讨,为未来研究、临床诊治及护理工作提供参考。
1" 神经递质生物学标志物
单胺假说是目前为止临床认识抑郁症的主要依据,它假设抑郁症病人神经回路中呈现出较低的血清素、多巴胺和去甲肾上腺素水平,临床抗抑郁药物的作用是增加他们在突触间隙的生物利用度。5⁃羟色胺转运体(5⁃HTT)是一种负责从突触向突触前神经元再摄取5⁃羟色胺的蛋白质,是目前首选的抗抑郁药物的主要目标。在5⁃羟色胺转运基因(SLC6A4)的启动子内,有一个5⁃羟色胺转运基因连接的多态性区域5⁃HTTLPR,该区域有一个长(l)或短(s)的等位基因,分别导致SLC6A4基因活性的升高和降低[8]。研究表明,童年期遭受压力应激的青少年携带5⁃HTTLPR的S等位基因会增加抑郁的发生风险[9⁃11]。此外,色氨酸羟化酶(TPH2)基因多态性也被发现与青少年抑郁相关联,且多数研究结果显示其可预测SSRIs类抗抑郁药物的应答 [12]。表观遗传研究发现,SLC6A4基因近端启动子甲基化水平升高可作为预测青春期应激下杏仁核反应性及后期抑郁症状表现的潜在标记物。尽管如此,关于这些标记物是否可以作为诊断及预测抑郁的标准仍存有争议,Porcelli 等[13]人在控制人种等因素后进行的Meta分析中证实5⁃HTTLPR与抑郁及治疗存在关联,但Taylor等[14]的工作却否定了这一论断。因此,仍需对此进一步深入观察和研究。
临床多项研究证实了多巴胺在抑郁症病理生理过程中特别是在快感缺失中的作用,这种观点也在抗精神病药辅助治疗抑郁症的有效性中得到印证[15⁃17]。多巴胺受体D3、D4、D5在外周循环中的表达均有报道,特别是D4,有研究显示,抑郁患者杏仁核中D4 mRNA的表达增加,然而,其他研究却发现,抑郁组与健康对照组之间在D4 表达水平上无差异,且无抽搐电休克治疗和异氟醚麻醉可降低D4 的表达水平[18⁃21]。
γ⁃胺基丁酸(GABA)是一种重要的抑制性神经递质,它参与多种代谢活动并具有很高的生理活性,免疫学研究表明其浓度最高的区域为中脑中黑质。越来越多的证据表明它不仅在抑郁症的病理生理学中起作用,而且是抗抑郁药治疗的目标[22⁃24]。大多数研究报告了抑郁症病人脑脊液中GABA水平降低[25],血浆中也报告了类似的减少[26],尽管这不一定是抑郁症特有的,但GABA的缺陷,通过增强细胞突触后α5⁃GABA⁃A受体活性可改善认知及情绪[27]以及氯胺酮可快速逆转抑郁情绪,从另一方面也证实了GABA可以成为预测抑郁发作及治疗的潜在生物学标志物[28]。此外,较高的血浆GABA基线水平已被证明可以预测电休克治疗应答[29]。然而,尸体检查研究中关于谷氨酸脱羧酶(GAD)在抑郁症病人中的表达数据尚不足以支持GABA作为可靠的抑郁预测标志物[30]。
2" 神经内分泌系统的生物学标志物
有证据证明下丘脑⁃垂体⁃肾上腺轴(HPA)的功能失调或受损在抑郁发作的机制中起重要作用,而该机制与成长过程的压力应激等相关。在地塞米松抑制试验(DST)中,抑郁症患者表现为持续性高皮质醇水平和对抑制不敏感。此外,研究表明,抑郁症患者在进行DST时,表现出皮质醇反应异常升高的现象,这种升高通常与症状的严重程度成正相关,因此,它可能作为一个临床抑郁症状严重程度的指标[31]。青春期HPA轴功能亢进引起的高皮质醇节律以及反应性增高比成人更敏感,且在女性中表现更明显。一项囊括17项研究的Meta分析显示,与对照组相比,抑郁表现的青少年HPA轴系统往往有功能失调的表现,可以从对DST的非典型反应、较高的基线皮质醇值以及对心理应激源的过度反应中得到证明[32]。另一项研究报告指出,与对照组相比,在抑郁症病人的下丘脑以及抑郁男性自杀病人的蓝斑核和中缝核中促肾上腺皮质激素释放素(CRF)和CRF的mRNA表达增加[33]。糖皮质激素受体(GR)mRNA在抑郁症病人下额叶回、额叶皮层Ⅲ⁃Ⅵ层和颞叶皮层Ⅳ层中的表达降低[34⁃36]。相比之下,另一项研究报告称,抑郁病人和对照组在几个大脑区域的GR mRNA水平没有差异,但扣带回和杏仁核中GR亚型GRα的mRNA表达减少[37⁃38]。
基于组学技术的研究显示,早期的压力会改变HPA轴调节,并通过对糖皮质激素受体基因(NR3C1)的表观遗传修饰增加抑郁症的发生风险[39]。一项前瞻性研究表明,NR3C1基因中的甲基化水平可预测青春期及成年早期抑郁的发病,另一项研究在控制了抑郁的遗传变异后关联仍然显著,而NR3C1的外周表达水平降低,这些证据表明NR3C1的甲基化可以独立作为抑郁症非遗传性生物学标志物。一些研究还表明,NR3C1基因中的高甲基化与儿童和青少年的压力史和抑郁症状的出现有关[39⁃42]。
FKBP51是糖皮质激素受体的有效抑制剂,是HPA轴应激反应的重要调节剂,涉及成人及青少年儿童的研究均表明,FKBP5基因的单核苷酸多态性(SNP)的次要等位基因会增加抑郁的风险,特别是rs1360780,rs9470080,rs3800373;成人组的研究表明,FKBP5 rs1360780和rs3800373基因型的非显著趋势与抗抑郁药低反应率相关,证明FKBP5的表达调节了成人对抗抑郁药物的反应[43⁃46]。但青少年组的研究并未显示该相关性[47],因此,需要对青少年群体进行更多研究,以验证FKBP5表达改变与青少年抑郁症治疗结果之间的关系。
3" 精神神经免疫系统生物学标志物
自提出抑郁症炎症病因假说以来,越来越多的研究表明抑郁症通常伴随着免疫反应,其表现为促炎细胞因子分泌增加,例如肿瘤坏死因子α(TNF⁃α)、白细胞介素(IL)和干扰素γ(IFN⁃γ)[48]。慢性应激以及持续的神经炎性反应一方面诱导糖皮质激素受体脱敏和糖皮质激素抵抗,导致HPA轴反应系统发生双向改变,从而损害糖皮质激素的抗炎活性;另一方面,促炎细胞因子可以增加吲哚胺2,3⁃双加氧酶(IDO)的活性,导致色氨酸(一种血清素前体)的生物利用度降低。此外,氧化应激反应会损害几乎所有已知的与抑郁症相关单胺的合成[49]。神经系统慢性炎症反应引发神经元兴奋性毒性并阻碍脑源性神经营养因子(BDNF)的产生,导致与情绪调节相关的神经元回路变性[50]。
抑郁与促炎细胞因子和抗炎细胞因子例如IL⁃1β、IL⁃6、IFN⁃γ、TNF⁃α、c ⁃反应蛋白(CRP)水平升高有关。细胞因子是由淋巴细胞、巨噬细胞和自然杀伤细胞(NK)产生的一组多种生化化合物[51]。细胞因子通常根据其对炎症的影响分为刺激炎症发展的促炎因子(例如IFN⁃γ、TNF、IL⁃1、IL⁃2,IL⁃5、IL⁃8)和抗炎因子(例如IL⁃1β、IL⁃6、TNF⁃α、IL⁃10、IL⁃19、IL⁃20、IL⁃22、IL⁃24、IL⁃26、IL⁃28、IL⁃29),其中有一部分根据情况不同其角色会发生改变(如IL⁃6、TGF⁃β、INF⁃α)[52⁃53]。一些研究报告显示,抑郁症患者外周血中的促炎细胞因子 IL⁃1ɑ、IL⁃1β、IL⁃6、IL⁃8、IL⁃10、IFN⁃γ、MIF和TNF⁃α的mRNA 表达升高[54⁃57]。一项以前瞻性研究为基础的Meta分析证实了IL⁃6和CRP与抑郁症呈正相关,两者可以很好地预测抑郁的发作,但该研究显示TNF⁃α与抑郁的发作并没有预测关系[58],关于TNF⁃α的这一结果与相关研究得出的结论[59]相矛盾。炎性标记物相关研究显示IL⁃6和CRP被证实是最具有潜力预测抑郁发作的标记物,多项Meta分析结果显示IL⁃6和CRP是抑郁症发作的显著预测因子,同时可以评估抗抑郁药的应答[60⁃62]。炎症性标志物在未来有可能作为抑郁症发作或抗抑郁药物治疗应答的生物学指标,尽管目前仍需要更多研究进一步探索。
微生物⁃肠⁃脑轴理论在多数研究中得以印证,明显的微生物生态失调可能导致抑郁发作。Fernstrom等[63]利用血液微生物组将抑郁症病人与健康对照组相比,抑郁病人紫色杆菌属比例较高而奈瑟菌水平较低。在肠道菌群的研究中发现抑郁症病人中微生物多样性减少,在门水平上厚壁菌、拟杆菌和变形杆菌的丰度不一致,抑郁症病人放线菌和梭菌门的丰度很高[64]。也有研究报告抑郁患者厚壁菌门及梭杆菌属丰度低,类杆菌科、肠杆菌科等的丰度高[65]。还有研究指出抑郁症病人乳酸杆菌、另枝菌属、副拟杆菌属、链球菌属水平较高,而粪球菌属、普氏菌属和瘤胃球菌属则呈现低水平状态[66]。Szczesniak等[67]发现,粪便杆菌、阿利司提普杆菌和瘤胃球菌与抑郁症相关。总之,抑郁症病人粪便微生物群检测结果所呈现出来的是潜在有害和炎症性细菌(如放线菌和肠杆菌科)过多,而有益细菌(厚壁菌)总体上减少[68⁃69],但聚焦于哪一特定菌属,目前研究结论存在矛盾。有学者认为,这些矛盾是由于诊断标准、分组标准、粪便微生物群检测方法等研究方法之间的不同所导致的。此外,肠道是一个复杂的生态系统,其环境受人种、遗传、地理环境、饮食习惯等多重因素影响,未来研究应在人种、地区等人口统计学和临床特征一致的受试者中进行,以获得更具可比性和推广性的结果[70]。
4" 神经营养因子系统标志物
脑源性神经营养因子(brain⁃derived neurotrophic factor, BDNF)是神经营养因子家族中的一种蛋白,通过促进神经元增殖和突触发生在神经发育中发挥重要作用。它还刺激成熟大脑中的神经可塑性过程,包括新细胞的形成和神经元的消除。抑郁症的神经营养理论认为环境应激因素和突变会降低大脑中的BDNF合成,导致突触可塑性降低、突触传递减少和神经元变性增加。这些改变可能导致已知的参与认知和情绪调节的大脑区域的特定结构发生变化,例如前额叶皮层萎缩和海马收缩。研究显示,抑郁症病人外周BDNF表达水平降低,有研究将汉密尔顿抑郁量表评分与BDNF外周表达相结合发现,BDNF可用于判断疾病严重程度[56]。但是也有学者对此提出质疑,且研究结果表明全血中BDNF mRNA的表达在抑郁症病人组和对照组中无差异,Gururajan 等[71]认为造成这种研究结果不同的原因可能是研究所采用的方法不同。
大脑中BDNF的生物利用度受BDNF基因的单核苷酸多态性(Val66Met)的影响,研究发现抑郁与BDNF Met 等位基因相关,特别是在青少年女性中更为显著[72⁃74]。此外,BDNF表观遗传的研究发现抑郁受试者BDNF基因启动子甲基化与健康对照组不同,Bakusic等[75]的研究显示抑郁症病人BDNF启动子I甲基化水平低,Val66Met多态性和启动子I的DNA甲基化与抑郁症状相关,但两者没有交互作用。另一方面,BDNF外显子Ⅸ的甲基化对抑郁病人的执行功能有负面影响,并介导了Val66Met对抑郁症病人这一结局的影响。然而,Froud等[76]的横断面研究(探讨饮食模式、BDNF水平、Val66Met与抑郁症的相关性)显示,Val66Met多态性与抑郁发作无关。未来还应开展关于这一标志物的大样本纵向研究来进一步验证其有效性。
5" 代谢标志物
代谢组学聚焦于代谢的底物和产物,如脂质、脂肪酸、氨基酸、同型半胱氨酸、腺苷以及线粒体功能障碍等。研究表明,抑郁症状与代谢组学中的一些特异性改变之间存在联系。有人提出,血清胆固醇可能直接影响脑脂和细胞膜的流动性,而对5⁃羟色胺能神经传递具有继发性效应。此外,高浓度的胆固醇促发炎症反应并增加了IL⁃6和TNF⁃α的释放,这与抑郁症的炎症理论相关联。研究表明代谢综合征与抑郁呈双向关系,纳入183项研究的系统综述报告了体质指数(BMI)过高和过低都会增加抑郁的风险[77],而在肥胖人群中腹型肥胖的人抑郁的发生风险会更高[78]。Meta分析证明成人抑郁症与特征性脂质水平有关,主要与血液中甘油三酯(TG)水平升高、极低密度脂蛋白(VLDL)和高密度脂蛋白(HDL)胆固醇水平降低有关[79]。有证据表明,TG与自杀及自残行为有相对一致的关联,HDL和抑郁呈现中等水平因果关联,LDL和总胆固醇(TC)没有显示出与抑郁表型的强相关[80]。但由于以上代谢指标与多种临床疾病以及症状相关联,其作为抑郁症特异性靶标的可靠性仍需进一步验证。
同型半胱氨酸是蛋氨酸代谢过程中的一种含硫氨基酸,该产物在外周的升高被证实与抑郁症相关,其主要原因是同型半胱氨酸代谢通路的甲基化过程在合成神经递质、蛋白质和膜磷脂中至关重要,任何干扰都可能影响神经功能和情绪调节。各年龄段的研究结果一致显示,高水平的同型半胱氨酸与抑郁症密切相关[81⁃83]。同时,叶酸在同型半胱氨酸的代谢中起关键作用,Khosravi 等[84]发现通过调整饮食模式(增加叶酸的摄入)可以降低抑郁的发病率。
有证据表明,各大脑区域的线粒体功能障碍与抑郁症有关。最近的发现引发了人们对线粒体在许多细胞内的作用以及突触可塑性和细胞弹性的重新认识。神经可塑性损害是抑郁症病理生理机制的一种基础假说。线粒体在三磷酸腺苷(ATP)的产生过程中有重要作用,包括细胞内Ca2+信号传导,以建立膜稳定性、活性氧(ROS)平衡以及执行神经传递和可塑性等作用[85]。因此,理解抑郁症发病机制中线粒体功能障碍的各种概念无疑有助于为抑郁症治疗提供更具针对性的治疗方法。研究发现线粒体功能的改变,如氧化磷酸化(OXPHOS)和膜极性增加了氧化应激和细胞凋亡,这些改变可能早于抑郁症状的出现[86]。神经炎性病变会对线粒体健康产生负面影响,导致兴奋性毒性、氧化应激、能量不足,最终导致神经元死亡。而另一方面,受损的线粒体又会释放各种与损伤相关的分子,这些分子是炎症反应的有效激活剂,在氧化应激、线粒体损伤、炎症和神经元功能障碍之间形成前馈循环[87⁃88]。Cai等[89]通过对血液及唾液样本的分析发现重度抑郁症病人的线粒体DNA(mtDNA)比对照组多,同时mtDNA的量与生活中的压力应激暴露相关联,而Kageyama等[90]的研究发现却与之相反,抑郁症病人的mtDNA水平较正常人群低。
6" 神经影像学标志物
随着神经成像技术的发展,神经影像学生物标志物在精神疾病领域的研究也越来越多。神经成像技术包括脑容量MRI、功能性 MRI(fMRI)、脑电图(EEG)、弥散张量成像(DTI)、磁共振波谱(MRS)、近红外光谱(NIRS)等[91]。近年来,这些技术已被用来研究抑郁症发病或各种治疗应答的效应预测。
海马体在抑郁病因病理中很重要。研究发现,抑郁病人糖皮质激素水平升高与海马体损伤有关,海马体是参与记忆和学习的大脑区域,相关研究发现抑郁病人的左海马体积通常比健康对照组小19%[92],且在治疗前后对比抑郁症受试者和对照组受试者海马体和杏仁核体积的MRI扫描中发现,与抑郁症状缓解者相比,未缓解者的双侧海马体容量显著减少[93]。有学者将该方法用于预测病人应用抗抑郁药物氟西汀的治疗应答,结果显示准确率为88.9%,同时,症状缓解者额叶、枕叶和扣带皮层的灰质体积大于未缓解者[94]。一项神经影像学研究的系统评价报告了电休克治疗(ECT)对脑结构的影响,应答者在颞叶和皮质下结构的体积有所增加,并且扣带回皮质体积与抗抑郁药、ECT和认知行为治疗(CBT)治疗应答存在正相关[95]。
fMRI测量与神经活动相关的大脑血流变化引起的信号,反映静息状态或任务执行期间激活的大脑区域,其优点是无创、无辐射暴露[96⁃98]。研究表明,无论是青少年还是成人,静息态功能磁共振成像(fMRI)检测到的杏仁核、中额叶、右后扣带皮层和右前楔体的静息态功能连接(RSFC)水平与抗抑郁药物的治疗反应有关。但相关研究结果不一致,这种情况可能与研究区域以及研究变量不同有关。基于任务的fMRI研究显示,双侧下额叶皮层、背外侧前额叶皮层、岛叶、伏隔核、喙前扣带和左杏仁核的激活与治疗效果或预后相关[99⁃100];在关于耐药抑郁病人的fMRI研究中发现,重复经颅磁刺激治疗(r⁃TMS)任务中对低频rTMS刺激有反应的病人额叶回的双侧激活减少[101]。睡眠异常是抑郁症病人的常见主诉,脑电图在抑郁诊疗中的应用研究发现与正常对照组相比,抑郁青少年的睡眠脑电图显示睡眠效率降低,快动眼睡眠(REM)潜伏期缩短,REM密度升高,而症状缓解后没有发现睡眠质量的变化,这种脑电图变化可能代表生物痕迹[102],Ghiasi等[103]研究证实皮质连接在θ波段中对早期抑郁症识别具有核心作用。
近红外光谱(near⁃infrared spectroscopy,NIRS)是用于测量生物组织中含氧血红蛋白或脱氧血红蛋白浓度变化的一种神经成像技术,该方法简便且是一种非侵入性方法,为大多数病人接受,临床上常用于评价治疗效果。临床研究发现受试者前、中颞叶、额叶区含氧血红蛋白的值和血流动力学可预测反映相关治疗效果[99, 104⁃105]。相对外周生物学标志物而言,神经影像学生物标志物更稳定,且不易受机体内环境影响,然而,由于抑郁症本身的特点难以从单个研究区域获得足够的样本量,未来应聚焦抑郁临床亚型着力发掘相应标志物。
7" 小结与展望
综上所述,尽管在抑郁症生物学标志物领域各国学者们做了大量的研究且技术手段日趋先进,但目前为止尚无抑郁症生物学诊断的金标准,这可能与抑郁症病因病理的异质性相关,某一区域、人种、文化背景、生物样本无法概括整个人类群体,且受疾病亚型、分期、严重程度影响无法用单一的指标去评估,因此,对该领域的研究是一大挑战。但基于多种组学技术(如基因组学、转录组学、代谢组学和蛋白质组学)及神经影像学技术的研究逐渐揭示了抑郁症潜在的生物学标志物,如单胺假说和GABA系统的异常在抑郁症的发病机制中起关键作用,5⁃HTT、TPH2的基因多态性和多巴胺受体被认为是潜在的生物标志物;HPA轴功能失调(如皮质醇水平升高)已被广泛证明与抑郁症的发病机制及病情严重程度密切相关;FKBP5基因及其多态性与应激反应及抗抑郁药物的疗效相关;抑郁症患者常伴有促炎细胞因子升高(如IL⁃6、TNF⁃α),且炎症标志物与抗抑郁药物的疗效相关;微生物组学研究发现抑郁症患者常表现出微生物生态失调,肠道菌群的多样性及特定菌属的丰度与抑郁发作密切相关;BDNF在神经发育和可塑性中发挥重要作用,其表达水平的降低与抑郁症的发病有关;代谢相关产物、底物(如胆固醇、BMI、三酰甘油等)和线粒体功能障碍与抑郁症的病理生理机制相关;通过MRI、fMRI和NIRS等技术发现,抑郁症患者大脑特定区域(如海马体、额叶皮层等)体积和功能的变化与抑郁症的症状表现及治疗反应密切相关等。这些生物学指标的确立将对抑郁症疾病的诊断、治疗及预后提供强有力的支撑,也为早期疾病识别,降低疾病总体负担提供保障。在上述研究中,大多数研究的样本量相对较小,难以得出广泛适用的结论,未来应开展大样本、多中心、长期随访的研究,以提高结果的稳定性和可重复性;不同研究方法和检测技术的标准化程度不高导致了研究结果的差异性,所以未来应制定统一的检测标准和流程,减少技术偏差,提高不同研究之间结果的可比性。同时,抑郁症的多因素病因使得单一标志物难以全面反映其病理生理过程,亟需整合多种生物标志物及组学数据,以实现更精准的疾病分类和个性化治疗策略。同时大量文献已经表明,生物标志物有可能改善抑郁症患者的治疗,除了几十年来一直被广泛研究的神经递质和神经内分泌标志物外,慢性炎症反应是近年来颇受关注的话题,且有可能成为有效的治疗靶点,但也有可能局限于抑郁症的亚组。尽管目前尚无统一的生物标志物标准,但通过整合多种生物指标和组学技术从疾病不同层次、阶段进行研究,有望在未来实现更精准的抑郁症的诊断、治疗及个性化护理。
参考文献:
[1]" MALHI G S,MANN J J.Course and prognosis[J].Lancet,2018,392(10161):2299-2312.
[2]" 季建林.中国抑郁障碍防治指南修订与抑郁障碍的规范治疗[J].中华行为医学与脑科学杂志,2015,24(4):292-293.
[3]" ZWOLIŃSKA W,DMITRZAK-WĘGLARZ M,SŁOPIEŃ A.Biomarkers in child and adolescent depression[J].Child Psychiatry amp; Human Development,2023,54(1):266-281.
[4]" RAO U.Biomarkers in pediatric depression[J].Depression and Anxiety,2013,30(9):787-791.
[5]" ZISOOK S,LESSER I,STEWART J W,et al.Effect of age at onset on the course of major depressive disorder[J].The American Journal of Psychiatry,2007,164(10):1539-1546.
[6]" FREEDMAN R,LEWIS D A,MICHELS R,et al.The initial field trials of DSM-5:new blooms and old thorns[J].The American Journal of Psychiatry,2013,170(1):1-5.
[7]" NONE.BEST (Biomarkers,endpoints,and other tools)resource[M].Silver Spring:Food and Drug Administration,2016:1.
[8]" LESCH K P,BENGEL D,HEILS A,et al.Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region[J].Science,1996,274(5292):1527-1531.
[9]" PRIESS-GROBEN H A,HYDE J S.5-HTTLPR X stress in adolescent depression:moderation by MAOA and gender[J].Journal of Abnormal Child Psychology,2013,41(2):281-294.
[10]" KOHEN R,MYAING M T,RICHARDS J,et al.Depression persistence and serotonin transporter genotype in adolescents under usual care conditions[J].Journal of Child and Adolescent Psychopharmacology,2013,23(4):290-294.
[11]" KANG H J,KIM J M,STEWART R,et al.Association of SLC6A4 methylation with early adversity,characteristics and outcomes in depression[J].Progress in Neuro-Psychopharmacology amp; Biological Psychiatry,2013,44:23-28.
[12] "ROTBERG B,KRONENBERG S,CARMEL M,et al.Additive effects of 5-HTTLPR (serotonin transporter) and tryptophan hydroxylase 2 G-703T gene polymorphisms on the clinical response to citalopram among children and adolescents with depression and anxiety disorders[J].Journal of Child and Adolescent Psychopharmacology,2013,23(2):117-122.
[13]" PORCELLI S,FABBRI C,SERRETTI A.Meta-analysis of serotonin transporter gene promoter polymorphism(5-HTTLPR) association with antidepressant efficacy[J].European Neuropsychopharmacology,2012,22(4):239-258.
[14]" TAYLOR M J,SEN S,BHAGWAGAR Z.Antidepressant response and the serotonin transporter gene-linked polymorphic region[J].Biological Psychiatry,2010,68(6):536-543.
[15]" DUNLOP B W,NEMEROFF C B.The role of dopamine in the pathophysiology of depression[J].Archives of General Psychiatry,2007,64(3):327.
[16]" FRISCH A,POSTILNICK D,ROCKAH R,et al.Association of unipolar major depressive disorder with genes of the serotonergic and dopaminergic pathways[J].Molecular Psychiatry,1999,4(4):389-392.
[17]" LÓPEZ LEÓN S,CROES E A,SAYED-TABATABAEI F A,et al.The dopamine D4 receptor gene 48-base-pair-repeat polymorphism and mood disorders:a meta-analysis[J].Biological Psychiatry,2005,57(9):999-1003.
[18]" ERSCHE K D,ROISER J P,LUCAS M,et al.Peripheral biomarkers of cognitive response to dopamine receptor agonist treatment[J].Psychopharmacology,2011,214(4):779-789.
[19]" IACOB E,TADLER S C,LIGHT K C,et al.Leukocyte gene expression in patients with medication refractory depression before and after treatment with ECT or isoflurane anesthesia:a pilot study[J].Depression Research and Treatment,2014,2014:582380.
[20]" ROCC P,LEO C D,EVA C,et al.Decrease of the D4 dopamine receptor messenger RNA expression in lymphocytes from patients with major depression[J].Progress in Neuro-Psychopharmacology amp; Biological Psychiatry,2002,26(6):1155-1160.
[21]" XIANG L B,SZEBENI K,SZEBENI A,et al.Dopamine receptor gene expression in human amygdaloid nuclei:elevated D4 receptor mRNA in major depression[J].Brain Research,2008,1207:214-224.
[22]" KALUEFF A V,NUTT D J.Role of GABA in anxiety and depression[J].Depression and Anxiety,2007,24(7):495-517.
[23]" PAYNE J L,MAGUIRE J.Pathophysiological mechanisms implicated in postpartum depression[J].Frontiers in Neuroendocrinology,2019,52:165-180.
[24]" DUMAN R S,SANACORA G,KRYSTAL J H.Altered connectivity in depression:GABA and glutamate neurotransmitter deficits and reversal by novel treatments[J].Neuron,2019,102(1):75-90.
[25]" ROY A,DEJONG J,FERRARO T.CSF GABA in depressed patients and normal controls[J].Psychological Medicine,1991,21(3):613-618.
[26]" PETTY F,KRAMER G L,GULLION C M,et al.Low plasma gamma-aminobutyric acid levels in male patients with depression[J].Biological Psychiatry,1992,32(4):354-363.
[27]" PRÉVOT T,SIBILLE E.Altered GABA-mediated information processing and cognitive dysfunctions in depression and other brain disorders[J].Molecular Psychiatry,2021,26(1):151-167.
[28]" LENER M S,NICIU M J,BALLARD E D,et al.Glutamate and gamma-aminobutyric acid systems in the pathophysiology of major depression and antidepressant response to ketamine[J].Biological Psychiatry,2017,81(10):886-897.
[29]" DEVANAND D P,SHAPIRA B,PETTY F,et al.Effects of electroconvulsive therapy on plasma GABA[J].Convulsive Therapy,1995,11(1):3-13.
[30]" PEHRSON A L,SANCHEZ C.Altered γ-aminobutyric acid neurotransmission in major depressive disorder:a critical review of the supporting evidence and the influence of serotonergic antidepressants[J].Drug Design,Development and Therapy,2015,9:603-624.
[31]" NONE.The dexamethasone suppression test:an overview of its current status in psychiatry.The APA Task Force on Laboratory Tests in Psychiatry[J].The American Journal of Psychiatry,1987,144(10):1253-1262.
[32]" LOPEZ-DURAN N L,KOVACS M,GEORGE C J.Hypothalamic-pituitary-adrenal axis dysregulation in depressed children and adolescents:a meta-analysis[J].Psychoneuroendocrinology,2009,34(9):1272-1283.
[33]" AUSTIN M C,JANOSKY J E,MURPHY H A.Increased corticotropin-releasing hormone immunoreactivity in monoamine-containing pontine nuclei of depressed suicide men[J].Molecular Psychiatry,2003,8(3):324-332.
[34]" KLOK M D,ALT S R,IRURZUN LAFITTE A J,et al.Decreased expression of mineralocorticoid receptor mRNA and its splice variants in postmortem brain regions of patients with major depressive disorder[J].Journal of Psychiatric Research,2011,45(7):871-878.
[35]" WEBSTER M J,KNABLE M B,O'GRADY J,et al.Regional specificity of brain glucocorticoid receptor mRNA alterations in subjects with schizophrenia and mood disorders[J].Molecular Psychiatry,2002,7(9):985-994.
[36]" PANDEY G N,RIZAVI H S,REN X G,et al.Region-specific alterations in glucocorticoid receptor expression in the postmortem brain of teenage suicide victims[J].Psychoneuroendocrinology,2013,38(11):2628-2639.
[37]" ALT S R,TURNER J D,KLOK M D,et al.Differential expression of glucocorticoid receptor transcripts in major depressive disorder is not epigenetically programmed[J].Psychoneuroendocrinology,2010,35(4):544-556.
[38]" HUMPHREYS K L,MOORE S R,DAVIS E G,et al.DNA methylation of HPA-axis genes and the onset of major depressive disorder in adolescent girls:a prospective analysis[J].Translational Psychiatry,2019,9(1):245.
[39]" EFSTATHOPOULOS P,ANDERSSON F,MELAS P A,et al.NR3C1 hypermethylation in depressed and bullied adolescents[J].Translational Psychiatry,2018,8(1):121.
[40]" CICCHETTI D,HANDLEY E D.Methylation of the glucocorticoid receptor gene,nuclear receptor subfamily 3,group C,member 1 (NR3C1),in maltreated and nonmaltreated children:associations with behavioral under control,emotional lability/negativity,and externalizing and internalizing symptoms[J].Development and Psychopathology,2017,29(5):1795-1806.
[41]" GARDINI E S,SCHAUB S,NEUHAUSER A,et al.Methylation of the glucocorticoid receptor promoter in children:links with parents as teachers,early life stress,and behavior problems[J].Development and Psychopathology,2022,34(3):810-822.
[42]" WANG Q Z,SHELTON R C,DWIVEDI Y.Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder:a systematic review and meta-analysis[J].Journal of Affective Disorders,2018,225:422-428.
[43]" PIECHACZEK C E,GREIMEL E,FELDMANN L,et al.Interactions between FKBP5 variation and environmental stressors in adolescent major depression[J].Psychoneuroendocrinology,2019,106:28-37.
[44]" BINDER E B,SALYAKINA D,LICHTNER P,et al.Polymorphisms in FKBP5 are associated with increased recurrence of depressive episodes and rapid response to antidepressant treatment[J].Nature Genetics,2004,36(12):1319-1325.
[45]" ISING M,MACCARRONE G,BRÜCKL T,et al.FKBP5 gene expression predicts antidepressant treatment outcome in depression[J].International Journal of Molecular Sciences,2019,20(3):485.
[46]" BRENT D,MELHEM N,FERRELL R,et al.Association of FKBP5 polymorphisms with suicidal events in the Treatment of Resistant Depression in Adolescents (TORDIA) study[J].The American Journal of Psychiatry,2010,167(2):190-197.
[47]" JIA Y,LIU L L,SHENG C Q,et al.Increased serum levels of cortisol and inflammatory cytokines in people with depression[J].The Journal of Nervous and Mental Disease,2019,207(4):271-276.
[48]" NEURAUTER G,SCHRÖCKSNADEL K,SCHOLL-BÜRGI S,et al.Chronic immune stimulation correlates with reduced phenylalanine turnover[J].Current Drug Metabolism,2008,9(7):622-627.
[49]" LEONARD B E.Inflammation and depression:a causal or coincidental link to the pathophysiology?[J].Acta Neuropsychiatrica,2018,30(1):1-16.
[50]" MOSIOŁEK A,PIĘTA A,JAKIMA S,et al.Effects of antidepressant treatment on peripheral biomarkers in patients with major depressive disorder (MDD)[J].Journal of Clinical Medicine,2021,10(8):1706.
[51]" GRUDZIEN M,RAPAK A.Effect of natural compounds on NK cell activation[J].Journal of Immunology Research,2018,2018(1):4868417.
[52]" LIU J J,WEI Y B,STRAWBRIDGE R,et al.Peripheral cytokine levels and response to antidepressant treatment in depression:a systematic review and meta-analysis[J].Molecular Psychiatry,2020,25(2):339-350.
[53]" IACOB E,LIGHT K C,TADLER S C,et al.Dysregulation of leukocyte gene expression in women with medication-refractory depression versus healthy non-depressed controls[J].BMC Psychiatry,2013,13:273.
[54]" MILLER A H,MALETIC V,RAISON C L.Inflammation and its discontents:the role of cytokines in the pathophysiology of major depression[J].Biological Psychiatry,2009,65(9):732-741.
[55]" CATTANEO A,GENNARELLI M,UHER R,et al.Candidate genes expression profile associated with antidepressants response in the GENDEP study:differentiating between baseline 'predictors' and longitudinal 'targets'[J].Neuropsychopharmacology,2013,38(3):377-385.
[56]" MILLER G E,COLE S W.Clustering of depression and inflammation in adolescents previously exposed to childhood adversity[J].Biological Psychiatry,2012,72(1):34-40.
[57]" MAC GIOLLABHUI N,NG T H,ELLMAN L M,et al.The longitudinal associations of inflammatory biomarkers and depression revisited:systematic review,meta-analysis,and meta-regression[J].Molecular Psychiatry,2021,26(7):3302-3314.
[58]" RAISON C L,RUTHERFORD R E,WOOLWINE B J,et al.A randomized controlled trial of the tumor necrosis factor antagonist infliximab for treatment-resistant depression:the role of baseline inflammatory biomarkers[J].JAMA Psychiatry,2013,70(1):31-41.
[59]" COLASANTO M,MADIGAN S,KORCZAK D J.Depression and inflammation among children and adolescents:a meta-analysis[J].Journal of Affective Disorders,2020,277:940-948.
[60]" STRAWBRIDGE R,ARNONE D,DANESE A,et al.Inflammation and clinical response to treatment in depression:a meta-analysis[J].European Neuropsychopharmacology,2015,25(10):1532-1543.
[61]" OSIMO E F,PILLINGER T,RODRIGUEZ I M,et al.Inflammatory markers in depression:a meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls[J].Brain,Behavior,and Immunity,2020,87:901-909.
[62]" BRYDGES C R,BHATTACHARYYA S,DEHKORDI S M,et al.Metabolomic and inflammatory signatures of symptom dimensions in major depression[J].Brain,Behavior,and Immunity,2022,102:42-52.
[63]" FERNSTRÖM J,MELLON S H,MCGILL M A,et al.Blood-based mitochondrial respiratory chain function in major depression[J].Translational Psychiatry,2021,11(1):593.
[64]" BARANDOUZI Z A,STARKWEATHER A R,HENDERSON W A,et al.Altered composition of gut microbiota in depression:a systematic review[J].Frontiers in Psychiatry,2020,11:541.
[65]" JIANG H Y,LING Z X,ZHANG Y H,et al.Altered fecal microbiota composition in patients with major depressive disorder[J].Brain,Behavior,and Immunity,2015,48:186-194.
[66]" LIU Y X,ZHANG L,WANG X Q,et al.Similar fecal microbiota signatures in patients with diarrhea-predominant irritable bowel syndrome and patients with depression[J].Clinical Gastroenterology and Hepatology,2016,14(11):1602-1611.
[67]" SZCZESNIAK O,HESTAD K A,HANSSEN J F,et al.Isovaleric acid in stool correlates with human depression[J].Nutritional Neuroscience,2016,19(7):279-283.
[68]" HUANG T T,LAI J B,DU Y L,et al.Current understanding of gut microbiota in mood disorders:an update of human studies[J].Frontiers in Genetics,2019,10:98.
[69]" HUANG Y C,SHI X,LI Z Y,et al.Possible association of Firmicutes in the gut microbiota of patients with major depressive disorder[J].Neuropsychiatric Disease and Treatment,2018,14:3329-3337.
[70]" AVERINA O V,ZORKINA Y A,YUNES R A,et al.Bacterial metabolites of human gut microbiota correlating with depression[J].International Journal of Molecular Sciences,2020,21(23):9234.
[71]" GURURAJAN A,CLARKE G,DINAN T G,et al.Molecular biomarkers of depression[J].Neuroscience and Biobehavioral Reviews,2016,64:101-133.
[72]nbsp; STONE L B,MCGEARY J E,PALMER R H,et al.Identifying genetic predictors of depression risk:5-HTTLPR and BDNF Val66Met polymorphisms are associated with rumination and corumination in adolescents[J].Frontiers in Genetics,2013,4:246.
[73]" CHEN J,LI X Y,MCGUE M.The interacting effect of the BDNF Val66Met polymorphism and stressful life events on adolescent depression is not an artifact of gene-environment correlation:evidence from a longitudinal twin study[J].Journal of Child Psychology and Psychiatry,and Allied Disciplines,2013,54(10):1066-1073.
[74]" HILT L M,SANDER L C,NOLEN-HOEKSEMA S,et al.The BDNF Val66Met polymorphism predicts rumination and depression differently in young adolescent girls and their mothers[J].Neuroscience Letters,2007,429(1):12-16.
[75]" BAKUSIC J,VRIEZE E,GHOSH M,et al.Interplay of Val66Met and BDNF methylation:effect on reward learning and cognitive performance in major depression[J].Clinical Epigenetics,2021,13(1):149.
[76]" FROUD A,MURPHY J,CRIBB L,et al.The relationship between dietary quality,serum brain-derived neurotrophic factor (BDNF) level,and the Val66met polymorphism in predicting depression[J].Nutritional Neuroscience,2019,22(7):513-521.
[77]" JUNG S J,WOO H T,CHO S,et al.Association between body size,weight change and depression:systematic review and meta-analysis[J].The British Journal of Psychiatry,2017,211(1):14-21.
[78]" DOLATIAN A,ARZAGHI S M,QORBANI M,et al.The relationship between body mass index (BMI) and depression according to the rs16139NPY gene[J].Iranian Journal of Psychiatry,2017,12(3):201-205.
[79]" BOT M,MILANESCHI Y,AL-SHEHRI T,et al.Metabolomics profile in depression:a pooled analysis of 230 metabolic markers in 5 283 cases with depression and 10 145 controls[J].Biological Psychiatry,2020,87(5):409-418.
[80]" SO H C,CHAU C K,CHENG Y Y,et al.Causal relationships between blood lipids and depression phenotypes:a Mendelian randomisation analysis[J].Psychological Medicine,2021,51(14):2357-2369.
[81]" CHUNG K H,CHIOU H Y,CHEN Y H.Associations between serum homocysteine levels and anxiety and depression among children and adolescents in China[J].Scientific Reports,2017,7:8330.
[82]" NARAYAN S K,VERMAN A,KATTIMANI S,et al.Plasma homocysteine levels in depression and schizophrenia in south Indian Tamilian population[J].Indian Journal of Psychiatry,2014,56(1):46-53.
[83]" FORTI P,RIETTI E,PISACANE N,et al.Blood homocysteine and risk of depression in the elderly[J].Archives of Gerontology and Geriatrics,2010,51(1):21-25.
[84]" KHOSRAVI M,SOTOUDEH G,AMINI M,et al.The relationship between dietary patterns and depression mediated by serum levels of Folate and vitamin B12[J].BMC Psychiatry,2020,20(1):63.
[85]" BANSAL Y,KUHAD A.Mitochondrial dysfunction in depression[J].Current Neuropharmacology,2016,14(6):610-618.
[86]" ALLEN J,ROMAY-TALLON R,BRYMER K J,et al.Mitochondria and mood:mitochondrial dysfunction as a key player in the manifestation of depression[J].Frontiers in Neuroscience,2018,12:386.
[87]" CASARIL A M,DANTZER R,BAS-ORTH C.Neuronal mitochondrial dysfunction and bioenergetic failure in inflammation-associated depression[J].Frontiers in Neuroscience,2021,15:725547.
[88]" RAPPENEAU V,WILMES L,TOUMA.Molecular correlates of mitochondrial dysfunctions in major depression:evidence from clinical and rodent studies[J].Molecular and Cellular Neurosciences,2020,109:103555.
[89]" CAI N,CHANG S,LI Y H,et al.Molecular signatures of major depression[J].Current Biology:CB,2015,25(9):1146-1156.
[90]" KAGEYAMA Y,KASAHARA T,KATO M,et al.The relationship between circulating mitochondrial DNA and inflammatory cytokines in patients with major depression[J].Journal of Affective Disorders,2018,233:15-20.
[91]" KANG S G,CHO S E.Neuroimaging biomarkers for predicting treatment response and recurrence of major depressive disorder[J].International Journal of Molecular Sciences,2020,21(6):2148.
[92]" BREMNER J D,NARAYAN M,ANDERSON E R,et al.Hippocampal volume reduction in major depression[J].The American Journal of Psychiatry,2000,157(1):115-118.
[93]" FRODL T,MEISENZAHL E M,ZETZSCHE T,et al.Hippocampal and amygdala changes in patients with major depressive disorder and healthy controls during a 1-year follow-up[J].The Journal of Clinical Psychiatry,2004,65(4):492-499.
[94]" COSTAFREDA S G,CHU C,ASHBURNER J,et al.Prognostic and diagnostic potential of the structural neuroanatomy of depression[J].PLoS One,2009,4(7):e6353.
[95]" ENNEKING V,LEEHR E J,DANNLOWSKI U,et al.Brain structural effects of treatments for depression and biomarkers of response:a systematic review of neuroimaging studies[J].Psychological Medicine,2020,50(2):187-209.
[96]" CULLEN K R,KLIMES-DOUGAN B,VU D P,et al.Neural correlates of antidepressant treatment response in adolescents with major depressive disorder[J].Journal of Child and Adolescent Psychopharmacology,2016,26(8):705-712.
[97]" ANDREESCU C,TUDORASCU D L,BUTTERS M A,et al.Resting state functional connectivity and treatment response in late-life depression[J].Psychiatry Research,2013,214(3):313-321.
[98]" ROSENBAUM D,HAGEN K,DEPPERMANN S,et al.State-dependent altered connectivity in late-life depression:a functional near-infrared spectroscopy study[J].Neurobiology of Aging,2016,39:57-68.
[99]" LANGENECKER S A,KENNEDY S E,GUIDOTTI L M,et al.Frontal and limbic activation during inhibitory control predicts treatment response in major depressive disorder[J].Biological Psychiatry,2007,62(11):1272-1280.
[100]" GYURAK A,PATENAUDE B,KORGAONKAR M S,et al.Frontoparietal activation during response inhibition predicts remission to antidepressants in patients with major depression[J].Biological Psychiatry,2016,79(4):274-281.
[101]" FITZGERALD P B,SRITHARAN A,DASKALAKIS Z J,et al.A functional magnetic resonance imaging study of the effects of low frequency right prefrontal transcranial magnetic stimulation in depression[J].Journal of Clinical Psychopharmacology,2007,27(5):488-492.
[102]" RAO U,POLAND R E.Electroencephalographic sleep and hypothalamic-pituitary-adrenal changes from episode to recovery in depressed adolescents[J].Journal of Child and Adolescent Psychopharmacology,2008,18(6):607-613.
[103]" GHIASI S,DELL'ACQUA C,BENVENUTI S M,et al.Classifying subclinical depression using EEG spectral and connectivity measures[J].IEEE Engineering in Medicine and Biology Society,2021,2021:2050-2053.
[104]" YAMAGATA B,YAMANAKA K,TAKEI Y,et al.Brain functional alterations observed 4-weekly in major depressive disorder following antidepressant treatment[J].Journal of Affective Disorders,2019,252:25-31.
[105]" TOMIOKA H,YAMAGATA B,KAWASAKI S,et al.A longitudinal functional neuroimaging study in medication-naïve depression after antidepressant treatment[J].PLoS One,2015,10(3):e0123.
(收稿日期:2024-07-23;修回日期:2024-12-15)
(本文编辑 崔晓芳)