抑郁症中的酰基肉碱代谢：与NESDA队列中的诊断状态、抑郁严重程度和症状特征的关联-动脉网

Acylcarnitines metabolism in depression: association with diagnostic status, depression severity and symptom profile in the NESDA cohort

Nature 等信源发布 2025-02-23 22:03



可切换为仅中文







Abstract

摘要

Acylcarnitines (ACs) are involved in bioenergetics processes that may play a role in the pathophysiology of depression. Previous genomic evidence identified four ACs potentially linked to depression risk. We carried forward these ACs and tested the association of their circulating levels with Major Depressive Disorder (MDD) diagnosis, overall depression severity and specific symptom profiles.

酰基肉碱（ACs）参与可能在抑郁症病理生理中起作用的生物能量过程。先前的基因组证据确定了四种可能与抑郁风险相关的ACs。我们进一步研究了这些ACs，并测试了它们的循环水平与重度抑郁症（MDD）诊断、整体抑郁严重程度及特定症状特征之间的关联。

The sample from the Netherlands Study of Depression and Anxiety included participants with current (n = 1035) or remitted (n = 739) MDD and healthy controls (n = 800). Plasma levels of four ACs (short-chain: acetylcarnitine C2 and propionylcarnitine C3; medium-chain: octanoylcarnitine C8 and decanoylcarnitine C10) were measured.

荷兰抑郁症和焦虑症研究的样本包括当前（n=1035）或缓解（n=739）的重度抑郁症（MDD）患者以及健康对照组（n=800）。测量了四种酰基肉碱（短链：乙酰肉碱C2和丙酰肉碱C3；中链：辛酰肉碱C8和癸酰肉碱C10）的血浆水平。

Overall depression severity as well as atypical/energy-related (AES), anhedonic and melancholic symptom profiles were derived from the Inventory of Depressive Symptomatology. As compared to healthy controls, subjects with current or remitted MDD presented similarly lower mean C2 levels (Cohen’s d = 0.2, p ≤ 1e-4).

总体抑郁严重程度以及非典型/能量相关（AES）、快感缺失和忧郁症状特征来源于抑郁症状量表。与健康对照组相比，当前或已缓解的重度抑郁症（MDD）受试者的平均C2水平同样较低（Cohen’s d = 0.2，p ≤ 1e-4）。

Higher overall depression severity was significantly associated with higher C3 levels (ß = 0.06, SE = 0.02, p = 1.21e-3). No associations were found for C8 and C10. Focusing on symptom profiles, only higher AES scores were linked to lower C2 (ß = −0.05, SE = 0.02, p = 1.85e-2) and higher C3 (ß = 0.08, SE = 0.02, p = 3.41e-5) levels.

总体抑郁严重程度较高与C3水平较高显著相关（ß = 0.06，SE = 0.02，p = 1.21e-3）。未发现C8和C10的相关性。聚焦于症状特征时，仅较高的AES评分与较低的C2（ß = −0.05，SE = 0.02，p = 1.85e-2）和较高的C3（ß = 0.08，SE = 0.02，p = 3.41e-5）水平相关。

Results were confirmed in analyses pooling data with an additional internal replication sample from the same subjects measured at 6-year follow-up (totaling 4141 observations). Small alterations in levels of short-chain acylcarnitine levels were related to the presence and severity of depression, especially for symptoms reflecting altered energy homeostasis.

结果在分析中得到证实，这些分析汇总了来自相同受试者在6年随访时测量的额外内部重复样本的数据（总共4141个观察值）。短链酰基肉碱水平的微小变化与抑郁症的存在和严重程度有关，尤其是反映能量稳态改变的症状。

Cellular metabolic dysfunctions may represent a key pathway i.

细胞代谢功能障碍可能代表了一个关键途径。

Introduction

简介

Depression is the second-leading cause of disability worldwide [

抑郁症是全球第二大导致残疾的原因 [

]. The detrimental impact of depression includes sequelae that extend beyond mental health, including increased risk for the development of cardiometabolic conditions such as cardiovascular disease and diabetes. Immuno-metabolic dysregulations have been proposed as mechanisms contributing to the overlapping pathophysiology of depression and cardiometabolic disorders [.

]. 抑郁症的有害影响包括超出心理健康的后遗症，包括增加心血管疾病和糖尿病等心代谢疾病的风险。免疫代谢失调被认为是导致抑郁症和心代谢疾病共同病理生理机制的因素之一 [.

Mitochondrial dysfunction has been recently proposed as a key pathophysiological mechanism [

线粒体功能障碍最近被提出作为一种关键的病理生理机制 [

] linked to processes commonly found in depression, including neurotoxicity, impaired neuroplasticity, inflammation and insulin resistance [

与抑郁症中常见的过程有关，包括神经毒性、神经可塑性受损、炎症和胰岛素抵抗。

，

]. Emerging evidence suggests a potential association of altered levels of acylcarnitines (ACs), which are involved in mitochondrial fatty acids β-oxidation, with insulin resistance, cardiovascular and neurodegenerative diseases [

]. 新出现的证据表明，酰基肉碱（ACs）水平的改变可能与胰岛素抵抗、心血管疾病和神经退行性疾病有关，这些酰基肉碱参与了线粒体脂肪酸的β-氧化过程 [

，

]. Currently, ACs are classified according the length of the carbon chain in short-chain (C2–C5), medium-chain (C6–C12), long-chain (C13–C20) and very long-chain ( > C21) [

]. 目前，ACs根据碳链长度分为短链（C2–C5）、中链（C6–C12）、长链（C13–C20）和超长链（>C21）[

]. The main function of ACs is to be carriers, transporting long-chain fatty acids into mitochondria, where a series of reactions will make possible their use in β-oxidation, for the production of adenosine triphosphate (ATP), the main source of energy for use and storage at cellular level (Fig.

]. ACs的主要功能是作为载体，将长链脂肪酸转运到线粒体中，在那里一系列反应将使它们能够用于β-氧化，以产生三磷酸腺苷（ATP），这是细胞层面使用和储存能量的主要来源（图。

) [

，

]. The end products of these reactions, acetyl-CoAs, are converted to acetylcarnitines (C2), which can then transport acyl groups outside mitochondria, a step required for utilization of fatty acids and glucose [

]. 这些反应的最终产物乙酰辅酶A（acetyl-CoAs）被转化为乙酰肉碱（C2），后者可以将酰基转运到线粒体外，这是利用脂肪酸和葡萄糖所需的一步 [

Fig. 1: Acylcarnitine production and main roles in mitochondrial function.

图1：酰基肉碱的产生及其在线粒体功能中的主要作用。

Abbreviations: CIT, cytosol; MIT, mitochondria; PEX, peroxisome; LC, long-chain; MC, medium-chain; SC, short-chain; CoA, coenzyme A; LACS, long-chain acyl-coenzyme A synthetase; CACT, carnitine/acylcarnitine translocase; CPT1 and CPT2, carnitine palmitoyl-transferase 1 and 2; CRAT, carnitine O-acetyltransferase; ATP, adenosine triphosphate; BCAA, branched-chain amino acid; OC Fatty Acid, Odd-chain fatty acid.

缩写：CIT，细胞质；MIT，线粒体；PEX，过氧化物酶体；LC，长链；MC，中链；SC，短链；CoA，辅酶A；LACS，长链酰基辅酶A合成酶；CACT，肉碱/酰基肉碱转运蛋白；CPT1和CPT2，肉碱棕榈酰转移酶1和2；CRAT，肉碱O-乙酰转移酶；ATP，三磷酸腺苷；BCAA，支链氨基酸；OC脂肪酸，奇数链脂肪酸。

Model based on Dambrova et al. [.

基于 Dambrova 等人的模型 [。

] and Li et al. [

]和李等人[

]. Full description in online supplement.

]. 完整描述见在线补充材料。

Full size image

全尺寸图像

Thus, ACs play a critical role in mitochondrial energy metabolism, essential for functioning of all tissues, as they transport long-chain fatty acids into mitochondria for β-oxidation, a key energy production process [

因此，ACs在线粒体能量代谢中发挥关键作用，对所有组织的功能都至关重要，因为它们将长链脂肪酸转运到线粒体中进行β-氧化，这是关键的能量产生过程。

]. Disruptions in this pathway can cause energy deficits affecting multiple organs, including those involved in mood and behavior regulation [

]. 这一途径的中断可能导致能量不足，影响多个器官，包括那些参与情绪和行为调节的器官 [

]. Emerging evidence suggests that ACs play a pivotal role in immune-metabolic pathways, linking lipid metabolism to mitochondrial function, with inadequate energy production contributing to metabolic stress, inflammation, and insulin resistance, all of which tied to depression pathophysiology [

]. 新出现的证据表明，ACs 在免疫代谢通路中起着关键作用，将脂质代谢与线粒体功能联系起来，能量产生不足会导致代谢应激、炎症和胰岛素抵抗，所有这些都与抑郁症的病理生理学有关 [

]. ACs influence immune responses by modulating inflammatory cytokine production [

]. ACs通过调节炎症细胞因子的产生来影响免疫反应 [

], while mitochondrial dysfunction exacerbates oxidative stress and inflammatory signaling [

], 而线粒体功能障碍会加剧氧化应激和炎症信号传导 [

]. Altered AC levels in peripheral tissues may indicate systemic metabolic dysregulation affecting energy homeostasis and immune-metabolic pathways in depression [

]. 外周组织中AC水平的改变可能表明系统性代谢失调，影响抑郁症中的能量稳态和免疫代谢途径 [

]. Although peripheral AC levels may not directly reflect brain-specific alterations, their role in systemic energy balance suggests an impact on central processes like mood regulation [

]. 尽管外周AC水平可能并不直接反映大脑特异性改变，但它们在系统能量平衡中的作用表明其对情绪调节等中枢过程有影响 [

Besides its role in energy metabolism, a number of studies have shown that C2 actions range from antioxidant, neuromodulatory, and neuroprotective effects to modulation of gene expression [

除了在能量代谢中的作用外，还有许多研究表明，C2 的作用范围从抗氧化、神经调节和神经保护作用到基因表达的调节 [

，

In the past decades, a growing number of studies have observed unique acylcarnitine signatures in patients with neurodegenerative and neuropsychiatric disorders [

在过去的几十年中，越来越多的研究观察到神经退行性和神经精神障碍患者中独特的酰基肉碱特征 [

]. In clinical studies, higher levels of circulating long- and medium-chain acylcarnitines showed mixed results in patients with Alzheimer’s disease [

]. 在临床研究中，循环中的长链和中链酰基肉碱水平较高，在阿尔茨海默病患者中显示出混合结果 [

，

] whereas clinical trials of patients with Parkinson’s disease have consistently shown that circulating levels of long-chain acylcarnitines are decreased [

] 然而，帕金森病患者的临床试验一致表明，长链酰基肉碱的循环水平降低 [

，

Findings on altered ACs levels in depression have recently emerged [

关于抑郁症中ACs水平改变的发现最近出现了[

]. In a clinical sample of 116 participants [

]. 在一个包含116名参与者的临床样本中 [

], subjects with Major Depressive Disorder (MDD) showed significantly lower C2 levels than healthy controls. A recent epidemiological study [

], 重度抑郁症（MDD）患者的C2水平显著低于健康对照组。最近的一项流行病学研究 [

] on >1000 subjects from the general population identified lower levels of the medium-chain decanoylcarnitine (C10) and dodecanoylcarnitine/laurylcarnitine (C12) in participants with elevated depressive symptoms assessed with self-report symptom questionnaires. In order to establish the role of AC metabolism in depression risk, we previously [.

] 对来自普通人群的1000多名受试者的研究发现，通过自我报告症状问卷评估，具有较高抑郁症状的参与者体内的中链癸酰肉碱（C10）和十二酰肉碱/月桂酰肉碱（C12）水平较低。为了确定AC代谢在抑郁风险中的作用，我们之前 [。

] leveraged summary-level data from large GWAS (up to ~800,000 samples) and Mendelian randomization analyses to examine the potential reciprocal relationships between circulating levels of 15 ACs and depression. We showed that genetically-predicted lower levels of short-chain C2 (acetylcarnitine) and C3 (propionylcarnitine) and genetically-predicted higher levels of medium-chain C8 (octanoylcarnitine) and C10 (decanoylcarnitine) were associated with increased depression risk.

利用大型GWAS（多达约80万样本）的汇总级数据和孟德尔随机化分析，研究了15种酰基肉碱（ACs）循环水平与抑郁症之间潜在的相互关系。我们发现，基因预测的短链C2（乙酰肉碱）和C3（丙酰肉碱）水平较低，以及基因预测的中链C8（辛酰肉碱）和C10（癸酰肉碱）水平较高，与抑郁风险增加相关。

No reverse impact of depression liability on AC levels was found. These Mendelian randomization findings provide valuable insights into the potential causal roles of acylcarnitines in depression pathophysiology, further supporting the need for additional studies to confirm these relationships..

未发现抑郁症对AC水平的反向影响。这些孟德尔随机化研究结果为酰基肉碱在抑郁症病理生理学中的潜在因果作用提供了有价值的见解，进一步支持了需要更多研究来证实这些关系。

In the present study, we carried forward these four ACs and tested whether the relationships with depression predicted from genomic data (negative with C2 and C3, and positive with C8 and C10) were expressed in actual phenotypes measured in a large cohort (N ~ 2500) with extensive clinical phenotyping.

在本研究中，我们推进了这四种ACs，并测试了从基因组数据预测的与抑郁症的关系（与C2和C3负相关，与C8和C10正相关）是否在具有广泛临床表型的大规模队列（N ~ 2500）中实际测量的表型中有所体现。

We examined the association of ACs blood levels with the presence of MDD and with overall depression severity. We also explored whether this association varied across different symptom profiles. Previous research has shown that immuno-metabolic dysregulations map more consistently to symptoms of the “atypical” spectrum characterized by altered energy intake/output (in particular the reversed neurovegetative symptoms of hyperphagia, hypersomnia with leaden paralysis and fatigue) [.

我们检查了ACs血浆水平与MDD的存在以及整体抑郁严重程度之间的关联。我们还探讨了这种关联是否在不同的症状表现中有所不同。先前的研究表明，免疫代谢失调更一致地映射到“非典型”谱系的症状，这些症状表现为能量摄入/输出的改变（特别是暴食、嗜睡伴随铅样瘫痪和疲劳等逆向神经植物症状）。

] and symptoms of anhedonia [

] 和快感缺失的症状 [

]. We examined the associations of AC levels with three symptom profile scores of atypical/energy-related, anhedonic and melancholic symptoms.

]. 我们检查了AC水平与非典型/能量相关、快感缺失和忧郁症状的三个症状特征评分之间的关联。

Methods

方法

Study design and setting

研究设计与背景

Data were obtained from the Netherlands Study of Depression and Anxiety (NESDA), an ongoing naturalistic longitudinal cohort study examining course and consequences of depressive and anxiety disorders. A description of the study rationale, design, and methods is given elsewhere [

数据来源于荷兰抑郁和焦虑研究 (NESDA)，这是一项正在进行的自然主义纵向队列研究，旨在调查抑郁和焦虑障碍的病程及后果。有关该研究的原理、设计和方法的描述见其他文献 [

]. Briefly, in 2003–2007, 2981 participants were recruited from community settings, primary care practices and mental health care institutions and were followed-up during biennial assessments. During the 9-year follow-up (2014–2017), full-biological siblings of NESDA participants with a lifetime affective disorder were additionally recruited.

]. 简而言之，在2003-2007年间，从社区环境、初级保健机构和心理健康护理机构招募了2981名参与者，并在每两年一次的评估中进行随访。在为期9年的随访期间（2014-2017年），还额外招募了NESDA参与者的全生物兄弟姐妹，这些参与者患有终身情感障碍。

Participants were excluded if they had a self-reported diagnosis of psychiatric disorders not subject of NESDA (e.g. bipolar, psychotic, or cognitive disorders) or were not fluent in Dutch. All participants provided written informed consent, and the study was approved by the Medical Ethics Committees of all the participating universities..

如果参与者自我报告诊断出患有不属于NESDA研究范围的精神疾病（例如，双相情感障碍、精神病或认知障碍），或不精通荷兰语，则被排除在外。所有参与者均提供了书面知情同意书，该研究得到了所有参与大学的医学伦理委员会的批准。

From the 3348 subjects of the NESDA cohort, we aimed to select healthy controls (without any lifetime depressive/anxiety disorder) and those with a diagnosis of MDD at their baseline assessment. Thus, among participants without a current diagnosis of MDD we excluded those with a diagnosis of anxiety disorder (n = 508) and dysthymia or minor depression (n = 66).

在NESDA队列的3348名受试者中，我们旨在选择健康对照组（无任何终身抑郁/焦虑障碍）和那些在基线评估时诊断为重度抑郁症（MDD）的个体。因此，在没有当前MDD诊断的参与者中，我们排除了那些诊断为焦虑障碍（n=508）和心境恶劣或轻度抑郁（n=66）的个体。

Among the remaining subjects, we further excluded those who received a diagnosis of bipolar disorder during the follow-up assessment (n = 9), those with missing metabolite data due to the lack of blood samples (n = 158) and those who did not complete the Inventory for Depressive Symptoms questionnaire (n = 33).

在其余的受试者中，我们进一步排除了那些在随访评估期间被诊断为双相情感障碍的个体（n=9）、因缺乏血液样本而导致代谢物数据缺失的个体（n=158），以及未完成抑郁症状问卷的个体（n=33）。

Supplemental Fig. .

补充图。

shows the flow chart for subject’ inclusion.

显示了受试者纳入的流程图。

Thus, the main analytical sample included 2574 participants (2363 from NESDA baseline and 211 siblings) with data on MDD diagnostic status, overall depression severity, and depressive symptoms profiles and at least one of the investigated metabolites.

因此，主要的分析样本包括2574名参与者（2363名来自NESDA基线调查，211名为兄弟姐妹），这些参与者具有关于重度抑郁症诊断状态、整体抑郁严重程度和抑郁症状概况的数据，并且至少有一种被研究的代谢物数据。

Furthermore, additional data from 1567 subjects with the same measures of depression and metabolites repeated at 6-year follow-up (2010–2013) were used in a secondary analysis.

此外，来自1567名受试者的额外数据，这些受试者在6年随访（2010-2013年）中重复测量了相同的抑郁和代谢物指标，被用于次要分析。

Specific analysis comparing the characteristics of included vs. excluded participants demonstrates that the excluded group is generally comparable to the included group in terms of sociodemographic and health-related factors (Table

对纳入参与者与排除参与者的特征进行的具体分析表明，排除组在社会人口统计学和健康相关因素方面通常与纳入组具有可比性（表

）。

MDD diagnostic status, overall depression severity and profiles

MDD诊断状态、总体抑郁严重程度和概况

The presence of DSM-IV diagnosis of MDD was assessed using the Composite Interview Diagnostic Instrument version 2.1 [

使用复合访谈诊断工具2.1版评估了DSM-IV诊断的重度抑郁症（MDD）的存在。[

] administered by specially trained research staff. Three groups were identified: participants with current MDD (that is, participants meeting DSM-IV criteria for MDD within the past 6 months), with remitted (i.e., lifetime but not current) MDD, and healthy controls (without any lifetime depressive/anxiety disorder).

由专门培训的研究人员进行管理。确定了三组：当前患有重度抑郁症（MDD）的参与者（即，在过去6个月内符合DSM-IV标准的参与者）、缓解型（即，终生曾患但当前未患）MDD的参与者，以及健康对照组（没有任何终生抑郁/焦虑障碍）。

Overall depression symptom severity was measured with the Inventory of Depressive Symptomatology self-report questionnaire (IDS-SR.

总体抑郁症状严重程度通过抑郁症状清单自评问卷（IDS-SR）进行测量。

) [

，

], with scores ranging from 0 to 84.

]，分数范围从0到84。

Three depression symptom profiles were created using items from the IDS-SR

使用IDS-SR中的条目创建了三种抑郁症状概况

as described in previous studies [

正如之前的研究中所描述的[

，

]. The atypical energy-related symptom (AES) profile is based on the five items of hypersomnia, increased appetite, increased weight, low energy and leaden paralysis (range 0–15); the definition of this profile showed a good level of homogeneity (mean inter-item Spearman 0.25) [

]. 非典型能量相关症状（AES）概况基于五个项目：嗜睡、食欲增加、体重增加、低能量和铅样瘫痪（范围0-15）；该概况的定义显示出良好的同质性水平（平均项目间 Spearman 系数为 0.25）[

] and has been extensively described previously as belonging to the immuno-metabolic depression (IMD) domain, based on previous findings on individual symptoms with immuno-metabolic dysregulation [

] 并且之前已被广泛描述为属于免疫代谢性抑郁（IMD）领域，基于以往对具有免疫代谢失调的个体症状的研究结果 [

]. The anhedonic profile is based on three items of response of mood to good or desired events, general interest and capacity for pleasure or enjoyment (range 0–9); this IDS-SR

]. 快感缺失特征基于对良好或期望事件的情绪反应、普遍兴趣及愉悦或享受能力的三项指标（范围0-9）；此为IDS-SR

anhedonia subscale has been previously demonstrated to highly correlate with the self-administered and clinician-administered versions of the SHAPS [

以前已经证明快感缺乏子量表与SHAPS的自我管理和临床医生管理版本高度相关 [

] and replicated in other samples [

] 并在其他样本中复制 [

]. Lastly, the melancholic profile is based on eight items of waking up too early, quality of mood, hypophagia, decreased weight, linkage of mood to time of day (if worse in the morning), view of self, psychomotor agitation and psychomotor retardation (range 0–24).

]. 最后，忧郁型特征基于八项内容：早醒、情绪质量、食欲减退、体重下降、情绪与一天中的时间关联（如果早晨更糟）、自我看法、精神运动性激越和精神运动性迟缓（范围0-24）。

Metabolomics profiling and data processing

代谢组学分析和数据处理

After an overnight fast, EDTA plasma samples were collected and stored in aliquots at −80 °C until further analysis. Samples were sent in two shipments to the USA. Metabolic profiles were measured using the untargeted metabolomics platform from Metabolon Inc (Durham, NC). Extended description of the assessment is provided elsewhere [.

隔夜禁食后，收集EDTA血浆样本并分装保存在-80°C直至进一步分析。样本分两批送往美国。代谢谱使用Metabolon公司（北卡罗来纳州达勒姆）的非靶向代谢组学平台进行测量。评估的详细描述见其他文献[。

] and in

】并在

Supplemental methods

补充方法

. Three of the four ACs (C2, C8 and C10) investigated in the present study were not available in the previously described [

本研究调查的四种AC中的三种（C2、C8和C10）在之前描述的研究中并未提供。

] metabolomics dataset. Issues with batch normalization using NIST (National Institute of Standards and Technology) samples as reference due to low levels of these ACs in NIST compared to NESDA samples led to exclusion of these measures according to our quality control criteria after batch correction.

] 代谢组学数据集。由于NIST（美国国家标准与技术研究院）样本中这些ACs的水平较NESDA样本低，使用NIST样本作为参考进行批次归一化时出现问题，根据我们的质量控制标准，在批次校正后这些测量值被排除。

For the present analyses, we re-processed the raw measurements of these three ACs using their median ion counts in each batch for normalization. Applying this approach, coefficients of variation of plasma reference samples that were run along with the NESDA samples met the original quality control criteria.

对于当前的分析，我们使用这三个AC每批次的中位离子计数对原始测量值进行了重新处理以进行归一化。应用这种方法，与NESDA样本一起运行的血浆参考样本的变异系数符合原始质量控制标准。

Batch-normalized values of the four AC metabolites were log2-transformed and metabolite levels higher than 3 standard deviations (C2 1.30%; C3 0.82%; C8 0.90%; C10 0.70%) were set as missing. Quality Check was performed according to the established pipeline used by previous epidemiological studies and international metabolomics consortia [.

四种AC代谢物的批标准化值经过log2转换，高于3个标准差的代谢物水平（C2 1.30%；C3 0.82%；C8 0.90%；C10 0.70%）被设为缺失值。质量检查按照之前流行病学研究和国际代谢组学联盟使用的既定流程进行。

，

Covariates

协变量

Covariates included age, sex, educational level (as total year of formal education), obtained from structured interviews conducted at the beginning of the study, as well as metabolomic assessment shipment (first vs second). Health and lifestyle information included smoking status (non-smoker vs current smoker), alcohol consumption as units per week, physical activity assessed using the International Physical Activity Questionnaire (IPAQ, expressed in Metabolic Equivalent Total (MET) minutes per week [.

协变量包括年龄、性别、教育水平（以正式教育的总年数计算），这些数据来自研究开始时进行的结构化访谈，以及代谢组学评估的运送批次（第一批与第二批）。健康和生活方式信息包括吸烟状态（非吸烟者与当前吸烟者）、每周酒精摄入量（单位：周）、使用国际体力活动问卷（IPAQ）评估的身体活动情况（以每周代谢当量总分钟数 [MET] 表示）。

], and body mass index (BMI) measured during physical examination. The number of self-reported current somatic diseases (including cardiometabolic, respiratory, musculoskeletal, digestive, neurological, endocrine diseases and cancer) for which participants received medical treatment was counted (coded as 0, 1, 2+) as a global marker of poor physical health.

]，以及体检时测量的体重指数（BMI）。参与者自我报告的当前接受治疗的躯体疾病（包括心代谢、呼吸系统、肌肉骨骼、消化系统、神经系统、内分泌疾病和癌症）的数量被统计（编码为0、1、2+），作为身体健康的总体指标。

In specific secondary analyses we examined the impact of antidepressant use, measured based on drug container inspection of medications used in the past month, classified according to the World Health Organization Anatomical Therapeutic Chemical classification: selective serotonin reuptake inhibitors (N06AB), tricyclic antidepressants (N06AA) and other less commonly prescribed medications (N06AX, N06AF, N06AG)..

在特定的次要分析中，我们检查了抗抑郁药物使用的影响，该影响是根据过去一个月内使用的药物容器检查来测量的，并按照世界卫生组织解剖学治疗化学分类进行分类：选择性5-羟色胺再摄取抑制剂（N06AB）、三环类抗抑郁药（N06AA）以及其他较少处方的药物（N06AX、N06AF、N06AG）。

Statistical methods

统计方法

Variables were reported as percentages or means ± SD as appropriate. Pairwise correlation between depressive symptom scores were estimated with Pearson’s r coefficient.

变量以百分比或均值±标准差表示。抑郁症状评分之间的两两相关性通过皮尔逊相关系数r进行估计。

All analyses were performed using linear mixed models with “family-factor” as random effect, in order to take into account the pedigree structure of the sample. We initially tested differences in adjusted mean AC levels across the three diagnostic groups: current MDD, remitted MDD and healthy controls.

所有分析均使用线性混合模型进行，“家族因素”作为随机效应，以考虑样本的家系结构。我们最初测试了三个诊断组（当前重度抑郁症、缓解的重度抑郁症和健康对照组）之间调整后的平均AC水平的差异。

Adjusted mean AC levels across the three groups were estimated from the mixed models, standardized differences between groups were reported using Cohen’s .

通过混合模型估算了三组的调整平均AC水平，并使用Cohen's d报告了组间的标准化差异。

tested in post-hoc pairwise comparisons. To estimate the association between metabolites and overall depression severity, we regressed AC levels on IDS-SR

在事后成对比较中进行了测试。为了评估代谢物与整体抑郁严重程度之间的关联，我们对IDS-SR进行了AC水平的回归分析。

total scores. Metabolite levels and depressive symptom scales were expressed as SD unit increase to derive standardized estimates. To further explore the functional shape of this association we applied restricted cubic splines with 3 knots to regression models. We examined the potential impact of antidepressant use on previous analyses by repeating the models excluding participants on antidepressants.

总分。代谢物水平和抑郁症状量表以标准差单位增加来表示，以得出标准化估计值。为了进一步探索这种关联的功能形状，我们在回归模型中应用了带有3个节点的限制性立方样条。我们通过重复模型并排除使用抗抑郁药的参与者，检验了抗抑郁药使用对先前分析的潜在影响。

ACs significantly linked to MDD status and/or depression severity were carried forward in subsequent analyses examining whether the association was mainly driven by specific symptom profiles, by regressing the metabolite levels on each of the three symptom profile scales..

与MDD状态和/或抑郁严重程度显著相关的ACs在后续分析中被保留，以检验这种关联是否主要由特定的症状特征驱动，方法是将代谢物水平对三个症状特征量表分别进行回归分析。

All models were adjusted for age, sex, educational level, and shipment. For significant associations, we tested the potential explanatory effect of lifestyle and health-related variables by further including alcohol consumption, smoking status, physical activity, BMI and the number of self-reported current somatic diseases in the analytical models..

所有模型均针对年龄、性别、教育水平和批次进行了调整。对于显著的关联，我们通过在分析模型中进一步纳入酒精消费、吸烟状况、身体活动、BMI 和自我报告的当前躯体疾病数量，测试了生活方式和健康相关变量的潜在解释效应。

Lastly, to evaluate the robustness of the associations detected, we additionally included data collected from NESDA subjects still available at 6-year follow-up by pooling all observations (N = 4141) in a unified mixed model with two random factors (one for the family effect and one for the repeated observations from the same subject over time)..

最后，为了评估检测到的关联的稳健性，我们还纳入了在6年随访时仍可获得的NESDA受试者的数据，将所有观察结果（N = 4141）汇总到一个包含两个随机因素的统一混合模型中（一个用于家庭效应，另一个用于同一受试者随时间的重复观察）。

Analyses were performed in

分析在以下方面进行：

RStudio

version 2023.03.0 + 386 (RStudio: Integrated Development for R). All statistical tests were two-sided and used a significance level of

版本 2023.03.0 + 386（RStudio：R 的集成开发环境）。所有统计检验均为双侧检验，并使用了显著性水平为

< 0.05. In main analyses, False-Discovery Rate (FDR) q-values were calculated. The present study report follows the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) Statement (Supplementary Table

小于0.05。在主要分析中，计算了错误发现率（FDR）q值。本研究报告遵循STROBE（加强流行病学观察性研究的报告）声明（补充表）。

）。

Results

结果

The sample’s mean age was 42.8 years (SD 13.19) and 65.3% were females (Table

样本的平均年龄为42.8岁（标准差13.19），其中65.3%为女性（表

). Participants had current MDD (N = 1035), remitted MDD (N = 739) or were healthy controls (N = 800); the mean IDS-SR

参与者目前患有重度抑郁症（MDD，N = 1035）、已缓解的重度抑郁症（N = 739），或是健康对照组（N = 800）；IDS-SR的平均值

score was 20.01 ± 13.98. Table

分数为20.01±13.98。表格

describe the main characteristics in the total sample and across the three diagnostic groups. Distributions of metabolite levels are depicted in Supplementary Figure

描述总样本和三个诊断组的主要特征。代谢物水平的分布见补充图。

and pairwise correlation between metabolites are shown in Supplementary Figure

代谢物之间的成对相关性如补充图中所示

. C8 and C10 were highly correlated (Pearson’s r = 0.9) in line with previously reported genetic correlations (rg = 0.98) [

C8和C10高度相关（Pearson’s r = 0.9），与之前报道的遗传相关性（rg = 0.98）一致 [

] while all other pairs showed Pearson’s r < 0.5.

】而所有其他配对的皮尔逊相关系数 r < 0.5。

Table 1 General characteristics of the main sample.

表1 主要样本的总体特征。

Full size table

全尺寸表格

Differences in ACs across MDD groups

MDD组间AC的差异

Figure

图

shows the age-, sex-, education-, and shipment-adjusted standardized means of the four metabolite levels across the three diagnostic groups. A significant overall difference across groups was found only for C2 levels (overall-p = 1.05e-5, q = 4.26e-5): current (mean = −0.06, SE = 0.01) and remitted (mean = −0.05, SE = 0.03) MDD cases had similar significantly lower mean C2 levels (.

显示了三个诊断组中四种代谢物水平的经年龄、性别、教育程度和样本运输调整后的标准化均值。仅在C2水平上发现了显著的组间总体差异（总体-p = 1.05e-5，q = 4.26e-5）：当前（均值 = −0.06，标准误 = 0.01）和缓解（均值 = −0.05，标准误 = 0.03）的重度抑郁症（MDD）病例具有相似的显著较低的C2水平。

= −0.2) as compared to controls (mean=0.03, SE = 0.06). This difference remained statistically significant after further adjustment for alcohol consumption, smoking status, physical activity, BMI and number of somatic diseases (current MDD mean = −0.06, SE = 0.01; remitted MDD mean = −0.06, SE = 0.02; healthy controls mean 0.03, SE = 0.02; overall-p = 3.14e-5, q = 1.26e-4).

= −0.2) 与对照组相比（均值=0.03，标准误=0.06）。在进一步调整了酒精摄入、吸烟状况、体力活动、BMI 和躯体疾病数量后，这一差异仍然具有统计学意义（当前重度抑郁症均值= −0.06，标准误=0.01；已缓解重度抑郁症均值= −0.06，标准误=0.02；健康对照组均值=0.03，标准误=0.02；总体 p = 3.14e-5，q = 1.26e-4）。

Of interest, C3 levels were increasingly elevated from healthy controls (mean = 0.63, SE = 0.02) to subjects with remitted (mean = 0.65, SE = 0.02) to those with current (mean = 0.68, SE = 0.02) MDD, although the overall difference was not statistically significant (overall-p = 1.65e-1, q = 2.32e-1)..

有趣的是，C3水平从健康对照组（均值=0.63，标准误=0.02）到缓解期（均值=0.65，标准误=0.02）再到当前患有MDD的受试者（均值=0.68，标准误=0.02）逐渐升高，尽管总体差异并不具有统计学显著性（总体p=1.65e-1，q=2.32e-1）。

Fig. 2: Metabolite levels across the three groups: current MDD (n = 1035), remitted MDD (n = 739) and healthy controls (n = 800).

图2：三组之间的代谢物水平：当前MDD（n=1035）、缓解MDD（n=739）和健康对照（n=800）。

Y-axes: SD change. Analysis were adjusted for age, sex, education and shipment. Adjusted P-levels (q) are obtained by BH-FDR (Benjamini-Hochberg False Discovery Rate) correction, used to control the rate of false positives in multiple testing.

Y轴：标准差变化。分析调整了年龄、性别、教育程度和运输批次。调整后的P值（q）通过BH-FDR（Benjamini-Hochberg错误发现率）校正获得，用于控制多重检验中的假阳性率。

Full size image

全尺寸图像

Participants using antidepressants were 24.9% of the total sample, and specifically 44.9% of those with current MDD and 31.5% of those in the remitted group. To evaluate whether the identified association between C2 and MDD status was driven by antidepressant use, we repeated the analysis only considering participants who did not use antidepressants (Table .

使用抗抑郁药的参与者占总样本的24.9%，其中当前患有重度抑郁症（MDD）的参与者中有44.9%使用抗抑郁药，缓解组中有31.5%使用抗抑郁药。为了评估C2与MDD状态之间确定的关联是否由抗抑郁药使用驱动，我们重复了分析，仅考虑未使用抗抑郁药的参与者（表。

). The differences in C2 levels between cases (both current and remitted) versus healthy controls was confirmed to be similar (d = −0.2) and statistically significant (overall-p = 1.20e-3).

). 确认病例（包括当前和已缓解）与健康对照组之间的C2水平差异相似（d = -0.2），且具有统计学意义（总体p = 1.20e-3）。

Association of ACs with overall depression severity

ACs与总体抑郁严重程度的关系

We estimated the association between AC levels and overall severity of depression measured by IDS-SR

我们估算了AC水平与IDS-SR测量的抑郁整体严重程度之间的关联。

total score (Table

总分（表

). Higher depression severity was significantly associated only with higher C3 levels (ß = 0.06, SE = 0.02, p = 1.20e-3, q = 9.60e-3) correcting for age, sex, education and shipment. Although slightly reduced, the association was still statistically significant (ß = 0.04, SE = 0.02, p = 2.67e-3) in the fully adjusted model.

较高的抑郁严重程度仅与较高的C3水平显著相关（ß = 0.06，SE = 0.02，p = 1.20e-3，q = 9.60e-3），校正了年龄、性别、教育程度和运输批次。尽管略有减弱，但在完全校正模型中，该关联仍然具有统计学显著性（ß = 0.04，SE = 0.02，p = 2.67e-3）。

To examine the potential impact of antidepressant use, we re-estimated the association between C3 and depression severity in participants without such medications (N = 1916): results were substantially similar (ß = 0.06, SE = 0.02, p = 1.16e-2). In line with previous analyses examining MDD diagnostic status, we found a negative association between overall depressive severity and C2 levels, although not reaching statistical significance (ß = −0.03, SE = 0.02, p = 8.10e-2, q = 2.16e-1).

为了检查抗抑郁药使用的潜在影响，我们重新评估了在未使用此类药物的参与者（N = 1916）中C3与抑郁严重程度之间的关联：结果基本相似（ß = 0.06，SE = 0.02，p = 1.16e-2）。与先前分析MDD诊断状态的研究一致，我们发现总体抑郁严重程度与C2水平呈负相关，尽管未达到统计学显著性（ß = −0.03，SE = 0.02，p = 8.10e-2，q = 2.16e-1）。

Furthermore, IDS-SR.

此外，IDS-SR。

scores were not significantly associated with C8 (ß = −0.001, SE = 0.02, p = 9.48e-1, q = 9.48e-1) or C10 (ß = −0.002, SE = 0.02, p = 9.26e-1, q = 9.48e-1).

分数与C8（ß = −0.001，SE = 0.02，p = 9.48e-1，q = 9.48e-1）或C10（ß = −0.002，SE = 0.02，p = 9.26e-1，q = 9.48e-1）无显著关联。

Table 2 Metabolite levels association with IDS-SR

表2 代谢物水平与IDS-SR的相关性

total scores and with symptom profiles.

总分和症状特征。

Full size table

全尺寸表格

To study the apparently discordant results for C2 and C3 in analyses using MDD diagnostic status versus those with continuous symptom severity, we examined the functional shape of the association between depression severity and ACs by fitting restricted cubic splines (3 knots) regression models. As shown in Fig.

为了研究在使用MDD诊断状态与连续症状严重程度的分析中，C2和C3结果明显不一致的原因，我们通过拟合限制性立方样条（3个节点）回归模型，考察了抑郁严重程度与ACs之间关联的功能形态。如图所示。

。

the fitted spline (adjusted for age, sex, education and shipment) revealed a threshold in the symptoms-C2 relationship, becoming inversely associated mainly for IDS-SR

拟合样条（调整了年龄、性别、教育程度和运输因素）揭示了症状与C2关系中的一个阈值，主要在IDS-SR中呈现负相关。

scores values below the sample mean. Healthy controls had mean IDS-SR

得分低于样本均值。健康对照组的IDS-SR平均值

of ~1 SD above the mean (the threshold point of the association), while MDD cases with remitted and those with current MDD had mean value, respectively, around the mean and ~1 SD below it. This shows how this non-fully-linear relationship was better captured by the analyses employing categorical diagnostic groups.

大约在均值以上1个标准差（关联的阈值点）附近，而缓解期的MDD病例和当前的MDD病例的平均值分别在均值附近和低于均值约1个标准差。这表明这种非完全线性关系通过使用分类诊断组的分析能够更好地捕捉到。

In contrast, the association between IDS-SR.

相比之下，IDS-SR之间的关联。

scores and C3 appeared substantially linear (Fig.

分数和C3呈现显著的线性关系（图。

), thus potentially better captured in analyses using continuous depressive symptom scores.

因此，可能在使用连续抑郁症状评分的分析中更好地捕捉到。

Fig. 3: Restricted cubic spline for C2 and C3.

图3：C2和C3的限制性立方样条。

Dashed fitted spline of C2 (

C2的虚线拟合样条曲线 (

) and C3 (

) 和 C3 (

) levels across IDS-SR

) IDS-SR中的水平

scores. Vertical lines illustrate the mean IDS-SR

分数。垂直线表示IDS-SR的平均值

values across the three diagnostic groups: current MDD (red line), remitted MDD (yellow line), HC (blue line).

三个诊断组的值：当前MDD（红线），缓解MDD（黄线），HC（蓝线）。

Full size image

全尺寸图像

Associations of ACs with symptom profiles

空调与症状特征的关联

We further evaluated whether the identified associations were specific for certain symptom profiles. There were moderate positive correlations between the three symptom profiles (Figure

我们进一步评估了所确定的关联是否特定于某些症状特征。三个症状特征之间存在中等程度的正相关（图

) varying from r = 0.75 (anhedonic and melancholic profiles) to r = 0.56 (AES and melancholic profiles), indicating that the scales captured partially non-overlapping dimensions. The AES profile score was significantly associated with lower C2 (ß = −0.05, SE = 0.02, p = 1.85e-2, q = 7.40e-2) and higher C3 (ß = 0.08, SE = 0.02, p = 3.42e-5, q = 5.47e-4) levels (Table .

）从 r = 0.75（快感缺失和忧郁型特征）到 r = 0.56（AES 和忧郁型特征）不等，表明这些量表捕捉到了部分非重叠的维度。AES 特征评分与较低的 C2（ß = −0.05，SE = 0.02，p = 1.85e-2，q = 7.40e-2）和较高的 C3（ß = 0.08，SE = 0.02，p = 3.42e-5，q = 5.47e-4）水平显著相关（表。

). These associations remained statistically significant after further adjustment for lifestyle and health-related variables (C2 ß = −0.04, SE = 0.02, p = 3.92e-2; C3 ß = 0.04, SE = 0.02, p = 3.13e-2).

这些关联在进一步调整生活方式和健康相关变量后仍然具有统计学显著性（C2 β = -0.04，SE = 0.02，p = 3.92e-2；C3 β = 0.04，SE = 0.02，p = 3.13e-2）。

The anhedonic profile score was associated with higher C3 (ß = 0.05, SE = 0.02, p = 5.80e-3, q = 3.09e-2) levels, although the association was reduced (ß = 0.03, SE = 0.02, p = 5.98e-2) after additional adjustment for lifestyle and health-related variables. The melancholic profile score was not significantly associated with C2 or C3.

无快感症特征评分与较高的C3水平相关（ß = 0.05，SE = 0.02，p = 5.80e-3，q = 3.09e-2），尽管在进一步调整生活方式和健康相关变量后，这种关联有所减弱（ß = 0.03，SE = 0.02，p = 5.98e-2）。忧郁特征评分与C2或C3无显著关联。

No associations were found for C8 and C10 (Table .

未发现C8和C10的相关性（表。

）。

To consider the possible non-linear shape of the relationship between C2 levels and symptom profile scales, we performed additional analysis for C2 dividing the profile scores in tertiles. Analyses confirmed the association between C2 and AES (Table

为了考虑C2水平与症状特征量表之间关系可能存在的非线性形状，我们对C2进行了额外的分析，将特征评分按三分位数划分。分析证实了C2与AES之间的关联（表）。

) and its non-fully linear functional form (Figure

）及其非完全线性函数形式（图

）。

Pooled analyses

汇总分析

The robustness of the significant associations detected using baseline data were further tested including an additional sample of 1567 subjects with metabolites and depressive symptoms assessed at the 6-year follow-up. Participants still available at this later wave of assessment had a substantially improved clinical profile as compared to baseline, with a significantly lower proportion of subjects currently depressed (16% versus 40% at baseline) and lower symptom severity measured with IDS-SR.

使用基线数据检测到的重要关联的稳健性通过纳入额外的1567名受试者样本得到了进一步测试，这些受试者的代谢物和抑郁症状在6年随访时进行了评估。与基线相比，在这一后续评估阶段仍然可用的参与者临床状况显著改善，当前抑郁的受试者比例较低（16% 对比基线时的40%），并且使用IDS-SR测量的症状严重程度也较低。

(15.21 ± 12.09 versus 20.01 ± 13.98 at baseline). Furthermore, among subjects from the main NESDA sample potentially available at multiple waves, those still present at the 6-year follow-up exhibited a substantially better baseline health profile (including physical health, lifestyle metrics, and lower depression symptom severity) compared to those lost to follow-up.

（基线时15.21 ± 12.09 vs 20.01 ± 13.98）。此外，在可能多次参与调查的NESDA主要样本中，那些在6年随访时仍然存在的人，其基线健康状况明显更好（包括身体健康、生活方式指标以及较低的抑郁症状严重程度），相比失访者。

(Table .

（表。

). Estimates derived for the 6-year follow-up assessment from the main mixed model (Table

). 从主要混合模型（表）中得出的6年随访评估的估计值

, obtained by modeling depression measure by assessment wave interactions) showed consistent but substantially diluted associations between depression and AC levels. Nevertheless, despite including these diluted signals, the overall model pooling 4141 observations (Table

，通过建模抑郁测量与评估波次交互作用获得）显示抑郁与AC水平之间存在一致但显著稀释的关联。然而，尽管包含了这些稀释信号，汇总4141个观测值的整体模型（表

) confirmed the associations between C2 and current MDD (ß = −0.07, SE = 0.02, p = 1.03e-4), remitted MDD (ß = −0.04, SE = 0.02, p = 1.06e-2) and with the AES profile (ß = −0.01, SE = 0.003, p = 1.99e-2). For C3, the model confirmed the association with overall MDD severity (ß = 0.002, SE = 0.001, p = 1.24e-2) and AES (ß = 0.01, SE = 0.003, p = 1.34e-3) symptom scores..

确认了C2与当前MDD（ß = -0.07，SE = 0.02，p = 1.03e-4）、缓解的MDD（ß = -0.04，SE = 0.02，p = 1.06e-2）以及AES特征（ß = -0.01，SE = 0.003，p = 1.99e-2）之间的关联。对于C3，模型确认了其与总体MDD严重程度（ß = 0.002，SE = 0.001，p = 1.24e-2）和AES（ß = 0.01，SE = 0.003，p = 1.34e-3）症状评分的关联。

Discussion

讨论

This is the largest study to date to explore the relationship between ACs blood concentrations and depression in a cohort enriched of clinical cases psychiatrically well characterized. Alterations in levels of short-chain ACs, reduced acetylcarnitine (C2) and elevated propionylcarnitine (C3), were linked to the presence and intensity of depression.

这是迄今为止最大的研究，旨在探讨在一个富含精神病学特征明确的临床病例的队列中，ACs血浆浓度与抑郁症之间的关系。短链ACs水平的改变、乙酰肉碱（C2）的减少和丙酰肉碱（C3）的升高与抑郁症的存在和严重程度有关。

Differences in C2 levels between MDD cases and controls were of small effect size (Cohen’s d = 0.2) comparable to those previously reported for other biomarkers such as CRP (d = 0.15) [.

MDD病例和对照组之间C2水平的差异效应量较小（Cohen’s d = 0.2），与之前报道的其他生物标志物如CRP（d = 0.15）相当。

] and insulin resistance (d = 0.19) [

] 和胰岛素抵抗 (d = 0.19) [

] Results were confirmed in pooled analyses with >4000 observations additionally including an additional sample with data collected in subjects still available at 6-year follow-up.

结果在包含超过4000个观察值的汇总分析中得到确认，此外还包括在6年随访时仍可获取数据的受试者提供的额外样本。

Findings from a previous study [

之前研究的发现 [

] leveraging genomic data and Mendelian randomization analyses suggested a potential causal relationship between low C2 and depression risk, although longitudinal studies are necessary to confirm these findings. Consistently, in the present study lower C2 levels as compared to healthy controls were observed for subjects experiencing a current depressive episode as well those who had remitted.

】利用基因组数据和孟德尔随机化分析表明，低C2水平与抑郁风险之间可能存在潜在的因果关系，尽管需要纵向研究来确认这些发现。一致地，在本研究中，与健康对照组相比，当前抑郁发作的受试者以及已缓解的受试者的C2水平较低。

This pattern supports the interpretation of decreased C2 levels as a potential “trait marker” indexing an underlying vulnerability for the development of depression, in line with previous genetic analyses [.

这种模式支持将C2水平降低解释为潜在的“特征标志”，作为抑郁发展基础脆弱性的指标，这与之前的遗传分析一致。

]. Nevertheless, lower C2 in remitted subjects could also represent the result of a “scar effect” of depression, not improving after symptomatologic remission. Further longitudinal analyses in initially non-depressed subjects are needed to properly disentangle these two mutually non-exclusive scenarios..

]. 然而，缓解期患者较低的C2也可能代表了抑郁症的“疤痕效应”，在症状缓解后并未改善。需要对最初未抑郁的受试者进行进一步的纵向分析，以正确区分这两种并非互相排斥的情形。

Furthermore, we found that C3 levels were positively correlated with the severity of depression, acting as a potential “state marker” of the current symptomatology. This finding is in contrast with the expectation from Mendelian randomization analyses, showing an association between genetically predicted lower C3 levels and depression risk.

此外，我们发现C3水平与抑郁严重程度呈正相关，可作为当前症状的潜在“状态标志物”。这一发现与孟德尔随机化分析的预期相反，后者显示遗传预测的较低C3水平与抑郁风险之间存在关联。

Discrepancies between analyses employing genetic instruments and actual phenotypes may provide intriguing insights on relevant dynamics. For instance, it could be speculated that such discrepancies may reflect compensatory mechanisms aimed at correcting underlying vulnerability, consistently with previous findings [.

使用遗传工具和实际表型进行分析之间的差异可能提供有关相关动态的有趣见解。例如，可以推测这些差异可能反映了一种旨在纠正潜在脆弱性的补偿机制，这与以前的研究结果一致[。

] showing an increase in C3 during antidepressant treatment. Presently such hypothesis remains merely speculative; to reconcile the genetics and observational estimates additional longitudinal and experimental studies are needed. Intriguingly, the direction of the association with depression was opposite for the two short-chain ACs C2 and C3.

] 显示在抗抑郁治疗期间C3增加。目前，这种假设仍然只是推测性的；要调和遗传学和观察估计，还需要更多的纵向和实验研究。有趣的是，与抑郁症相关的方向对于两种短链ACs C2和C3是相反的。

Although having a partially overlapping genetic basis, the actual correlation of C2 and C3 blood concentrations was weak (r = 0.2) and these ACs are components of partially independent pathways (Fig. .

尽管具有部分重叠的遗传基础，C2 和 C3 血液浓度的实际相关性较弱 (r = 0.2)，并且这些 AC 是部分独立通路的组成部分（图。

). C2 is a downstream product of mitochondrial beta-oxidation of long-chain fatty acids. Disruptions in this process may result in reduced in C2 levels. C3 is a downstream product of the metabolism of branched-chain amino-acids (leucine, isoleucine, valine) and of odd-chain fatty acids. In diseases where amino-acid metabolizing enzymes are dysfunctional or absent (e.g., propionic acidemia and methylmalonic acidemias characterized by neurological symptoms, muscle weakness and low energy) C3 accumulates, and higher blood levels are used as a screening tool.

C2是长链脂肪酸线粒体β氧化的下游产物。此过程的中断可能导致C2水平降低。C3是支链氨基酸（亮氨酸、异亮氨酸、缬氨酸）和奇数链脂肪酸代谢的下游产物。在氨基酸代谢酶功能失调或缺失的疾病中（例如，伴有神经系统症状、肌肉无力和低能量的丙酸血症和甲基丙二酸血症），C3会积累，其较高的血液水平被用作筛查工具。

Hence, it is possible that C2 and C3 play distinct roles in various molecular pathways associated with depression. Further research is required to gain a more comprehensive understanding of this aspect..

因此，C2和C3可能在与抑郁症相关的多种分子通路中发挥不同的作用。需要进一步研究以更全面地了解这一方面。

Finally, while genetically predicted higher levels of the medium-chain ACs C8 and C10 were associated with increased depression risk in previous Mendelian randomization analyses, no significant association with depression presence or severity was found for levels of these ACs in the present study. Potential compensatory mechanisms correcting underlying vulnerability may be speculated as one of the reasons for such discrepancies, consistently with previous findings showing decrease in C8 and C10 after antidepressant treatment [.

最后，虽然在之前的孟德尔随机化分析中，基因预测的中链酰基肉碱（ACs）C8 和 C10 水平较高与抑郁风险增加相关，但在本研究中未发现这些 ACs 的水平与抑郁存在或严重程度之间存在显著关联。潜在的补偿机制纠正了潜在的脆弱性，这可能被推测为这种差异的原因之一，这也与之前显示抗抑郁治疗后 C8 和 C10 下降的研究结果一致。

]. Nevertheless, other conceptual and methodological differences may explain discrepancies in results between genetically informed (capturing average lifetime risk and etiological mechanisms) and observational (capturing time specific or acute events and disease progression) analyses. As addressed for other mental disorders, the integration of static genetic data and dynamic “omics” data is necessary to define better biomarkers for clinical management [.

]. 然而，其他概念和方法上的差异可能解释了基因信息分析（捕捉平均终身风险和病因机制）与观察性分析（捕捉特定时间或急性事件及疾病进展）之间结果的差异。正如其他精神障碍所讨论的，整合静态基因数据和动态“组学”数据对于定义更好的临床管理生物标志物是必要的 [。

]. Furthermore, the network of biological pathways involving ACs and converging on the mitochondria is extremely complex (Fig.

]. 此外，涉及ACs并汇聚于线粒体的生物通路网络极其复杂（图。

). Rather than alterations in single components, the impact on depression pathobiology may be due to the net effect of different dysregulations and interrelated compensatory mechanisms in such a complex network, which could be fully unraveled only by further functional and mechanistic studies.

）。抑郁症病理生物学的影响可能是由于复杂网络中不同失调和相互关联的补偿机制的综合作用，而非单一组分的改变，这只有通过进一步的功能性和机制性研究才能完全揭示。

The present findings are in line with previous evidence suggesting that metabolic alterations are not uniformly associated with all clinical manifestation of depression, but map more consistently with specific symptom profiles [

目前的研究结果与之前的证据一致，表明代谢改变并不是与抑郁症的所有临床表现都均匀相关，而是更一致地映射到特定的症状特征上。

]. Across different analyses, lower C2 and higher C3 levels were associated with an atypical/energy-related symptom profile characterized by altered energy intake/expenditure balance (e.g. hyperphagia, weight gain, hypersomnia, fatigue, leaden paralysis) and previously shown to be linked [

]. 在不同的分析中，较低的C2和较高的C3水平与一种非典型的/能量相关的症状特征相关，这种特征表现为能量摄入/消耗平衡的改变（例如，食欲亢进、体重增加、嗜睡、疲劳、铅样瘫痪），并且之前已被证明与[

，

] to inflammatory and metabolic alterations. Less consistent evidence across analyses were found for an association between higher C3 levels and an anhedonic symptom profile previously linked with inflammation and neurobiological reward processes. The clustering between specific biological and clinical features has been postulated to identify a theoretical dimension labelled “immuno-metabolic depression (IMD)” [.

] 与炎症和代谢改变相关。在较高C3水平与之前与炎症和神经生物学奖励过程相关的快感缺失症状之间的关联，不同分析的结果证据不太一致。特定生物学和临床特征之间的聚类被认为可以识别一个被称为“免疫代谢性抑郁（IMD）”的理论维度 [。

] (aligning with the Research Domain Criteria (RDoC) framework [

] （与研究领域标准 (RDoC) 框架保持一致 [

]; that may be conceptualized as a depression dimension in mapping the degree of expression of transdiagnostic bio-behavioral processes overlapping with those of other constructs (e.g. sickness behavior) [

]; 这可以被概念化为一个抑郁维度，用于映射与其它构念（例如疾病行为）重叠的跨诊断生物行为过程的表达程度 [

，

], psychiatric diagnoses (e.g. bipolar disorder, seasonal affective disorder) or somatic (e.g. cardiovascular diseases, diabetes) conditions. In this context, engagement of the specific immuno-metabolic biological pathways (e.g. AC metabolism) in conjunction with the expression of specific clinical symptoms (e.g.

]，精神科诊断（例如，双相情感障碍、季节性情感障碍）或躯体状况（例如，心血管疾病、糖尿病）。在这种情况下，特定的免疫代谢生物通路（例如，AC代谢）与特定临床症状的表达相结合（例如，

atypical/energy-related, anhedonia) may identify depressed subjects at higher cardiometabolic risk. For example, altered levels of short-chain ACs, including C2 and C3, have been observed in coronary artery disease and diabetes [.

非典型/与能量相关的，快感缺失）可能识别出具有较高心代谢风险的抑郁患者。例如，在冠状动脉疾病和糖尿病中观察到短链ACs（包括C2和C3）水平的改变。

，

Findings from the present study align with hypotheses [

本研究的发现与假设一致 [

] suggesting that mitochondrial energetic dysfunction may be involved in the pathophysiology of depression. Cellular energy dysfunction may contribute to depression through various pathways, leading to neurotoxicity and impaired neuroplasticity [

] 表明线粒体能量功能障碍可能参与了抑郁症的病理生理过程。细胞能量功能障碍可能通过多种途径导致神经毒性并损害神经可塑性，从而促成抑郁症的发生 [

，

]. In animal models, C2 supplementation promoted neuroplasticity, synthesis of neurotrophic factors, modulation of glutamatergic dysfunction, reversal of neuronal atrophy in regions like the hippocampus and amygdala, and improvement in depression-like behavioral symptoms [

]. 在动物模型中，C2补充剂促进了神经可塑性、神经营养因子的合成、谷氨酸能功能障碍的调节、海马和杏仁核等区域神经元萎缩的逆转，以及抑郁样行为症状的改善 [

，

Moreover, mitochondrial dysfunction and related oxidative stress can activate the innate branch of the immune system, leading to the release of pro-inflammatory cytokines influencing various depression-related pathophysiological mechanisms: monoaminergic neurotransmission disruption, tryptophan degradation toward neurotoxic catabolites, glutamate-related excitotoxicity, decreased neurotrophic factors and alterations in the hypothalamic-pituitary-adrenal axis [.

此外，线粒体功能障碍和相关的氧化应激可以激活免疫系统的先天分支，导致释放影响各种抑郁相关病理生理机制的促炎细胞因子：单胺能神经传递中断、色氨酸降解为神经毒性代谢物、谷氨酸相关的兴奋性毒性、神经营养因子减少以及下丘脑-垂体-肾上腺轴的改变。

，

]. Mitochondrial bioenergetic dysfunctions may also have broader impact on immune processes. It has been recently shown [

]. 线粒体生物能量学功能障碍也可能对免疫过程产生更广泛的影响。最近的研究表明 [

] that T cells from depressed patients displayed a compromised metabolic profile accompanied by heightened gene expression of CTP1a (carnitine palmitoyltransferase 1 A), the mitochondrial enzyme responsible for ACs synthesis.

] 抑郁症患者的T细胞显示出受损的代谢特征，并伴有CTP1a（肉碱棕榈酰转移酶1A）基因表达的升高，该线粒体酶负责ACs的合成。

It is important to acknowledge that the relationships we found between AC levels, MDD diagnosis, depression severity and depression profiles may be explained to some extent by shared distal environmental and lifestyle factors (e.g., comorbid somatic diseases, sedentary behavior, smoking, high-fat diet, alcohol consumption [.

重要的是要承认，我们发现的AC水平、MDD诊断、抑郁严重程度和抑郁特征之间的关系，在某种程度上可以通过共同的远端环境和生活方式因素（如共病躯体疾病、久坐行为、吸烟、高脂饮食、饮酒）来解释。

，

] that could act as confounder or mediators of the association. Nevertheless, when analyses were adjusted for BMI, level of physical activity, number of somatic comorbidities, smoking status and alcohol use, results were substantially unchanged.

] 可能作为混淆因素或中介因素影响关联性。然而，当分析调整了BMI、体力活动水平、躯体共病数量、吸烟状况和饮酒情况后，结果基本保持不变。

Alternatively, altered levels of ACs may be a direct consequence of depression or related clinical aspect such as use of antidepressants. Nevertheless, previous genetic study employing Mendelian randomization [

或者，ACs水平的改变可能是抑郁症或相关临床因素（如抗抑郁药物的使用）的直接结果。然而，先前利用孟德尔随机化的遗传学研究[

] found no evidence supporting a causal role of depression liability in influencing AC levels. Furthermore, in the present study we repeated the analysis excluding subjects using antidepressants and associations were not substantially impacted.

] 没有发现支持抑郁责任在影响AC水平方面起因果作用的证据。此外，在本研究中，我们重复了分析，排除了使用抗抑郁药的受试者，关联并未受到实质性影响。

A major limitation of the present study is the cross-sectional design of the analyses, which estimated the associations between AC levels and depression at the same assessment (either baseline or 6-year follow-up), precluding conclusions about causality. Also, to assess the AES symptoms, items from a previously established questionnaire available in the cohort were utilized, following theoretical models and earlier research findings.

本研究的一个主要局限性是分析的横断面设计，该设计评估了AC水平与抑郁之间的关联（在基线或6年随访时的同一次评估中），无法得出因果关系的结论。此外，为了评估AES症状，研究利用了队列中已有的先前建立的问卷中的条目，依据理论模型和早期研究结果。

The consistent correlations between AES symptoms and immuno-metabolic benchmark markers point to a satisfactory level of internal consistency in the scoring approach. Nonetheless, future studies should prioritize the development or adoption of specialized tools designed specifically for this clinical profile, ensuring these are subjected to comprehensive psychometric validation.

AES症状与免疫代谢基准标志物之间的一致相关性表明评分方法具有令人满意的内部一致性水平。然而，未来的研究应优先开发或采用专为该临床特征设计的专用工具，并确保这些工具经过全面的心理测量学验证。

Strengths of the current study include the large sample size, the detailed clinical assessment of depression and related characteristics, and the availability of the same data collected from participants still involved after 6 years of follow-up (totaling over 4,000 observations), which allowed further testing of the consistency of the detected associations.

当前研究的优势包括大样本量、对抑郁症及其相关特征的详细临床评估，以及在6年随访后仍参与的受试者中收集到的相同数据（总计超过4000次观察），这些数据允许进一步测试所检测到的关联的一致性。

However, the sample available at the 6-year follow-up was not entirely comparable to the one selected for the main analyses, as it included subjects with a substantially better health profile (indicative of survival bias) compared to those lost to follow-up. These differences may have resulted in a relative reduction in effect sizes when pooling cross-sectional estimates obtained in the main analyses and those from 6-year follow-up analyses.

然而，6年随访时可用的样本与主要分析中选取的样本并不完全可比，因为其包含了健康状况明显更好的个体（表明存在生存偏倚），而这些个体在失访人群中并未包含。这种差异可能导致在汇总主要分析中的横断面估计值和6年随访分析中的估计值时，效应量出现相对减少。

Thus, the present findings warrant external replication in independent samples with similar measures when these become available. At the same time, it is important to remark.

因此，当有类似的测量方法时，本研究的发现需要在独立的样本中进行外部复制。同时，重要的是要强调。

，

In the future, longitudinal studies will be necessary to capture trajectories of changes over time in AC levels and depressive symptoms in order to properly disentangle trait vs state effects and provide empirical grounding for causal interpretation, triangulating evidence with experimental medicine approaches.

未来，有必要进行纵向研究，以捕捉AC水平和抑郁症状随时间变化的轨迹，从而正确区分特质效应与状态效应，并为因果解释提供实证依据，同时结合实验医学方法进行证据三角验证。

To date, only few small studies with heterogeneous methodology tested carnitine/acetylcartinitine supplementation in depressed patients, producing inconsistent results [.

迄今为止，只有少数方法学异质的小型研究测试了肉碱/乙酰肉碱补充剂在抑郁症患者中的应用，结果不一致。

]. In parallel, in-depth mechanistic studies could identify the precise biological mechanisms underlying the association between ACs and depression. An interesting approach would be to study differences in ratios between long, medium and short chain ACs in order to assess possible alterations in enzymatic function in depressed patients, a method already used in other fields of medicine [.

]. 同时，深入的机制研究可以确定ACs与抑郁症之间关联的确切生物学机制。一个有趣的方法是研究长链、中链和短链ACs之间的比例差异，以评估抑郁症患者酶功能可能的改变，这种方法已经在医学的其他领域得到应用 [。

，

In conclusion, the present study identified alterations of small effect size in blood levels of short-chain ACs related to the presence and severity of depression, especially of clinical profiles expressing symptoms reflecting altered energy homeostasis. Cellular metabolic dysfunctions may represent the biological substrate connecting depression with different cardiometabolic outcomes and a key pathway in depression pathophysiology potentially accessible through AC metabolism..

总之，本研究发现抑郁的存在和严重程度与短链ACs血液水平的小效应改变有关，尤其是表现出反映能量稳态改变的症状的临床特征。细胞代谢功能障碍可能是连接抑郁与不同心代谢结果的生物学基础，并且是可能通过AC代谢途径触及的抑郁症病理生理学中的关键通路。

Data availability

数据可用性

Access to NESDA data used in the present study can be obtained by submitting a research proposal. Information on how to request the study data, including the data sharing policy, can be found at

可以通过提交研究计划书来获取本研究中使用的NESDA数据。关于如何请求研究数据的信息，包括数据共享政策，可以在以下位置找到：

www.nesda.nl

。

References

参考文献

GBD Results. Inst. Health Metr. Eval.

GBD结果。健康指标与评估研究所。

https://vizhub.healthdata.org/gbd-results

(accessed 20 Oct2023).

（访问日期：2023年10月20日）。

Milaneschi Y, Lamers F, Berk M, Penninx BWJH. Depression heterogeneity and its biological underpinnings: toward immunometabolic depression. Biol. Psychiatry. 2020;88:369–80.

米拉内斯基 Y，拉默斯 F，伯克 M，彭宁克斯 BWJH。抑郁症的异质性及其生物学基础：迈向免疫代谢性抑郁。《生物精神病学》。2020年；88：369-80。

https://doi.org/10.1016/j.biopsych.2020.01.014

。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术索

Morris G, Berk M. The many roads to mitochondrial dysfunction in neuroimmune and neuropsychiatric disorders. BMC Med. 2015;13:68.

Morris G, Berk M. 神经免疫和神经精神障碍中线粒体功能障碍的多条路径。BMC医学。2015年；13:68。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Picard M, McEwen BS. Mitochondria impact brain function and cognition. Proc Natl Acad Sci USA. 2014;111:7–8.

皮卡德 M，麦克尤恩 BS。线粒体影响大脑功能和认知。美国国家科学院院刊。2014年；111:7-8。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术搜索

McEwen BS, Bowles NP, Gray JD, Hill MN, Hunter RG, Karatsoreos IN, et al. Mechanisms of stress in the brain. Nat Neurosci. 2015;18:1353–63.

麦克尤恩 BS，鲍尔斯 NP，格雷 JD，希尔 MN，亨特 RG，卡拉索雷奥斯 IN，等。大脑中的压力机制。《自然神经科学》。2015；18：1353–63。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术索

Adams SH, Hoppel CL, Lok KH, Zhao L, Wong SW, Minkler PE, et al. Plasma acylcarnitine profiles suggest incomplete long-chain fatty acid beta-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-American women. J Nutr. 2009;139:1073–81.

Adams SH, Hoppel CL, Lok KH, 赵L, Wong SW, Minkler PE, 等。血浆酰基肉碱谱表明2型糖尿病非裔美国女性中长链脂肪酸β氧化不完全和三羧酸循环活性改变。《营养学杂志》。2009;139:1073–81。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

McCoin CS, Knotts TA, Adams SH. Acylcarnitines–old actors auditioning for new roles in metabolic physiology. Nat Rev Endocrinol. 2015;11:617–25.

McCoin CS, Knotts TA, Adams SH. 酰基肉碱——代谢生理学中试镜新角色的老演员。《自然综述内分泌学》。2015年；11:617–25。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术

Guasch-Ferré M, Zheng Y, Ruiz-Canela M, Hruby A, Martínez-González MA, Clish CB, et al. Plasma acylcarnitines and risk of cardiovascular disease: effect of Mediterranean diet interventions. Am J Clin Nutr. 2016;103:1408–16.

Guasch-Ferré M, Zheng Y, Ruiz-Canela M, Hruby A, Martínez-González MA, Clish CB, 等。血浆酰基肉碱与心血管疾病风险：地中海饮食干预的效果。《美国临床营养学杂志》。2016；103：1408–16。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Aitken-Buck HM, Krause J, Zeller T, Jones PP, Lamberts RR. Long-Chain acylcarnitines and cardiac excitation-contraction coupling: links to arrhythmias. Front Physiol. 2020;11:577856.

艾特肯-巴克 HM，克劳斯 J，泽勒 T，琼斯 PP，兰伯茨 RR。长链酰基肉碱与心脏兴奋-收缩耦联：与心律失常的联系。《生理学前沿》。2020；11：577856。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Dambrova M, Makrecka-Kuka M, Kuka J, Vilskersts R, Nordberg D, Attwood MM, et al. Acylcarnitines: nomenclature, biomarkers, therapeutic potential, drug targets, and clinical trials. Pharmacol Rev. 2022;74:506–51.

Dambrova M, Makrecka-Kuka M, Kuka J, Vilskersts R, Nordberg D, Attwood MM, 等。酰基肉碱：命名法、生物标志物、治疗潜力、药物靶点及临床试验。药理学评论。2022；74：506–51。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Li S, Gao D, Jiang Y. Function, detection and alteration of acylcarnitine metabolism in hepatocellular carcinoma. Metabolites. 2019;9:36.

李S，高D，江Y。肝细胞癌中酰基肉碱代谢的功能、检测及改变。《代谢物》。2019；9：36。

https://doi.org/10.3390/metabo9020036

。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Farrell S, Vogel J, Bieber LL. Entry of acetyl-L-carnitine into biosynthetic pathways. Biochim Biophys Acta. 1986;876:175–7.

法雷尔 S，沃格尔 J，比伯 LL。乙酰-L-肉碱进入生物合成途径。《生物化学与生物物理学报》。1986年；876：175-7。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

McCann MR, la Rosa MVGD, Rosania GR, Stringer KA. L-Carnitine and acylcarnitines: mitochondrial biomarkers for precision medicine. Metabolites. 2021;11:51.

McCann MR，la Rosa MVGD，Rosania GR，Stringer KA。L-肉碱和酰基肉碱：用于精准医学的线粒体生物标志物。《代谢物》。2021；11：51。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Clemente-Suárez VJ, Beltrán-Velasco AI, Redondo-Flórez L, Martín-Rodríguez A, Yáñez-Sepúlveda R, Tornero-Aguilera JF. Neuro-Vulnerability in energy metabolism regulation: a comprehensive narrative review. Nutrients. 2023;15:3106.

Clemente-Suárez VJ, Beltrán-Velasco AI, Redondo-Flórez L, Martín-Rodríguez A, Yáñez-Sepúlveda R, Tornero-Aguilera JF。神经脆弱性在能量代谢调节中的研究：一项全面的叙述性综述。《营养素》。2023；15:3106。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术索

Mehdi S, Wani SUD, Krishna KL, Kinattingal N, Roohi TF. A review on linking stress, depression, and insulin resistance via low-grade chronic inflammation. Biochem Biophys Rep. 2023;36:101571.

Mehdi S, Wani SUD, Krishna KL, Kinattingal N, Roohi TF. 通过低度慢性炎症关联压力、抑郁和胰岛素抵抗的综述。《生物化学与生物物理报告》。2023；36：101571。

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Rutkowsky JM, Knotts TA, Ono-Moore KD, McCoin CS, Huang S, Schneider D, et al. Acylcarnitines activate proinflammatory signaling pathways. Am J Physiol Endocrinol Metab. 2014;306:E1378–87.

Rutkowsky JM, Knotts TA, Ono-Moore KD, McCoin CS, 黄S, Schneider D, 等。酰基肉碱激活促炎信号通路。《美国生理学杂志：内分泌与代谢》。2014;306:E1378–87。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术索

Zong Y, Li H, Liao P, Chen L, Pan Y, Zheng Y, et al. Mitochondrial dysfunction: mechanisms and advances in therapy. Signal Transduct Target Ther. 2024;9:1–29.

宗毅，李华，廖平，陈亮，潘宇，郑阳，等。线粒体功能障碍：机制与治疗进展。信号转导与靶向治疗。2024；9：1–29。

Google Scholar

谷歌学术索

Jones LL, McDonald DA, Borum PR. Acylcarnitines: role in brain. Prog Lipid Res. 2010;49:61–75.

琼斯 LL，麦克唐纳 DA，博勒姆 PR。酰基肉碱：在大脑中的作用。《脂质研究进展》。2010年；49：61-75。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术索

Calabrese V, Giuffrida Stella AM, Calvani M, Butterfield DA. Acetylcarnitine and cellular stress response: roles in nutritional redox homeostasis and regulation of longevity genes. J Nutr Biochem. 2006;17:73–88.

Calabrese V, Giuffrida Stella AM, Calvani M, Butterfield DA. 乙酰左旋肉碱与细胞应激反应：在营养氧化还原稳态和长寿基因调控中的作用。《营养生物化学杂志》。2006;17:73–88.

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术搜索

Cuccurazzu B, Bortolotto V, Valente MM, Ubezio F, Koverech A, Canonico PL, et al. Upregulation of mGlu2 receptors via NF-κB p65 acetylation is involved in the Proneurogenic and antidepressant effects of acetyl-L-carnitine. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol. 2013;38:2220–30.

Cuccurazzu B, Bortolotto V, Valente MM, Ubezio F, Koverech A, Canonico PL, 等。通过NF-κB p65乙酰化上调mGlu2受体参与了乙酰-L-肉碱的促神经发生和抗抑郁作用。《神经精神药理学》美国神经精神药理学院官方出版物。2013年；38:2220–30。

Article

文章

CAS

中文名：化学文摘社

Google Scholar

谷歌学术

Pettegrew JW, Levine J, McClure RJ. Acetyl-L-carnitine physical-chemical, metabolic, and therapeutic properties: relevance for its mode of action in Alzheimer’s disease and geriatric depression. Mol Psychiatry. 2000;5:616–32.

Pettegrew JW, Levine J, McClure RJ. 乙酰-L-肉碱的物理化学、代谢及治疗特性：其在阿尔茨海默病和老年抑郁症作用机制中的相关性。《分子精神病学》2000;5:616–32.

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Virmani A, Binienda Z. Role of carnitine esters in brain neuropathology. Mol Aspects Med. 2004;25:533–49.

Virmani A，Binienda Z。肉碱酯在脑神经病理学中的作用。《分子医学方面》。2004；25：533-49。

Article

文章

CAS

中文名：化学文摘社

PubMed

Google Scholar

谷歌学术

F Guerreiro Costa LN, Carneiro BA, Alves GS, Lins Silva DH, Faria Guimaraes D, Souza LS, et al. Metabolomics of major depressive disorder: a systematic review of clinical studies. Cureus. 2022;14:e23009.

F Guerreiro Costa LN, Carneiro BA, Alves GS, Lins Silva DH, Faria Guimaraes D, Souza LS, 等。重度抑郁症的代谢组学：临床研究的系统综述。Cureus。2022；14:e23009。

PubMed

PubMed Central

Google Scholar

谷歌学术索

van der Velpen V, Teav T, Gallart-Ayala H, Mehl F, Konz I, Clark C, et al. Systemic and central nervous system metabolic alterations in Alzheimer’s disease. Alzheimers Res Ther. 2019;11:93.

van der Velpen V, Teav T, Gallart-Ayala H, Mehl F, Konz I, Clark C, 等。阿尔茨海默病的系统性和中枢神经系统代谢改变。《阿尔茨海默病研究与治疗》。2019；11：93。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术索

Huo Z, Yu L, Yang J, Zhu Y, Bennett DA, Zhao J. Brain and blood metabolome for Alzheimer’s dementia: findings from a targeted metabolomics analysis. Neurobiol Aging. 2020;86:123–33.

霍泽、余莉、杨杰、朱毅、贝内特DA、赵静。阿尔茨海默病痴呆的脑和血液代谢组：来自靶向代谢组学分析的发现。《神经生物学与衰老》。2020年；86卷：123-33页。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Saiki S, Hatano T, Fujimaki M, Ishikawa K-I, Mori A, Oji Y, et al. Decreased long-chain acylcarnitines from insufficient β-oxidation as potential early diagnostic markers for Parkinson’s disease. Sci Rep. 2017;7:7328.

齐木 S、波多野 T、藤卷 M、石川 K-I、森 A、尾崎 Y 等。由于β氧化不足导致的长链酰基肉碱减少可作为帕金森病潜在的早期诊断标志物。《科学报告》，2017年；7:7328。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术

Chang K-H, Cheng M-L, Tang H-Y, Huang C-Y, Wu Y-R, Chen C-M. Alternations of metabolic profile and kynurenine metabolism in the plasma of Parkinson’s disease. Mol Neurobiol. 2018;55:6319–28.

张K-H，程M-L，唐H-Y，黄C-Y，吴Y-R，陈C-M。帕金森病患者血浆中代谢谱和犬尿氨酸代谢的变化。《分子神经生物学》。2018；55：6319-28。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Molsberry S, Bjornevik K, Hughes KC, Zhang ZJ, Jeanfavre S, Clish C, et al. Plasma metabolomic markers of insulin resistance and diabetes and rate of incident Parkinson’s disease. J Park Dis. 2020;10:1011–21.

Molsberry S, Bjornevik K, Hughes KC, Zhang ZJ, Jeanfavre S, Clish C, 等。血浆代谢组学标志物与胰岛素抵抗和糖尿病及帕金森病发病率的关系。《帕金森病杂志》。2020年；10:1011–21。

CAS

中国科学院

Google Scholar

谷歌学术

Palacios N, Bhupathiraju SN, Kelly RS, Lee JS, Ordovas JM, Tucker KL. Acylcarnitines are associated with lower depressive symptomatology in a mainland puerto rican cohort. Metabolomics Off J Metabolomic Soc. 2024;20:85.

帕拉西奥斯 N，布帕提拉朱 SN，凯利 RS，李 JS，奥多瓦斯 JM，塔克 KL。酰基肉碱与波多黎各大陆队列中较低的抑郁症状相关。《代谢组学学会官方期刊：代谢组学》。2024年；20:85。

CAS

中国科学院

Google Scholar

谷歌学术

Nasca C, Xenos D, Barone Y, Caruso A, Scaccianoce S, Matrisciano F, et al. L-acetylcarnitine causes rapid antidepressant effects through the epigenetic induction of mGlu2 receptors. Proc Natl Acad Sci USA. 2013;110:4804–9.

Nasca C, Xenos D, Barone Y, Caruso A, Scaccianoce S, Matrisciano F, 等。L-乙酰肉碱通过表观遗传诱导mGlu2受体产生快速抗抑郁效果。美国国家科学院院刊。2013;110:4804–9。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术索

Zacharias HU, Hertel J, Johar H, Pietzner M, Lukaschek K, Atasoy S, et al. A metabolome-wide association study in the general population reveals decreased levels of serum laurylcarnitine in people with depression. Mol Psychiatry. 2021;26:7372–83.

Zacharias HU, Hertel J, Johar H, Pietzner M, Lukaschek K, Atasoy S, 等。一项在普通人群中的代谢组学关联研究揭示抑郁患者血清月桂酰肉碱水平降低。《分子精神病学》。2021年；26:7372–83。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Milaneschi Y, Arnold M, Kastenmüller G, Dehkordi SM, Krishnan RR, Dunlop BW, et al. Genomics-based identification of a potential causal role for acylcarnitine metabolism in depression. J Affect Disord. 2022;307:254–63.

Milaneschi Y, Arnold M, Kastenmüller G, Dehkordi SM, Krishnan RR, Dunlop BW, 等。基于基因组学的酰基肉碱代谢在抑郁症中潜在因果作用的鉴定。《情感障碍杂志》。2022年；307：254-63。

Article

文章

CAS

中文名：化学文摘社

PubMed

Google Scholar

谷歌学术索

Miller AH, Raison CL. The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat Rev Immunol. 2016;16:22–34.

Miller AH, Raison CL。炎症在抑郁症中的作用：从进化需求到现代治疗靶点。《自然免疫学评论》。2016年；16:22-34。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Penninx BWJH, Eikelenboom M, Giltay EJ, van Hemert AM, Riese H, Schoevers RA, et al. Cohort profile of the longitudinal Netherlands Study of Depression and Anxiety (NESDA) on etiology, course and consequences of depressive and anxiety disorders. J Affect Disord. 2021;287:69–77.

Penninx BWJH，Eikelenboom M，Giltay EJ，van Hemert AM，Riese H，Schoevers RA，等。荷兰抑郁症与焦虑症纵向研究（NESDA）关于抑郁和焦虑障碍的病因、病程及后果的队列概况。《情感障碍杂志》。2021；287：69-77。

https://doi.org/10.1016/j.jad.2021.03.026

。

Article

文章

PubMed

Google Scholar

谷歌学术索

Wittchen HU. Reliability and validity studies of the WHO-Composite International Diagnostic Interview (CIDI): a critical review. J Psychiatr Res. 1994;28:57–84.

Wittchen HU。世界卫生组织复合性国际诊断访谈（CIDI）的信度和效度研究：一项批判性综述。《精神病学研究杂志》。1994年；28卷：57-84页。

https://doi.org/10.1016/0022-3956(94)90036-1

。

Article

文章

CAS

中文名：化学文摘社

PubMed

Google Scholar

谷歌学术索

Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. The inventory of depressive symptomatology (IDS): Psychometric properties. Psychol Med. 1996;26:477–86.

Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. 抑郁症状清单 (IDS): 心理测量特性。《心理医学》。1996;26:477–86.

https://doi.org/10.1017/s0033291700035558

。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术搜索

Rush AJ, Giles DE, Schlesser MA, Fulton CL, Weissenburger J, Burns C. The Inventory for Depressive Symptomatology (IDS): preliminary findings. Psychiatry Res. 1986;18:65–87.

Rush AJ, Giles DE, Schlesser MA, Fulton CL, Weissenburger J, Burns C. 抑郁症状清单 (IDS): 初步发现。《精神病学研究》1986;18:65–87。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术索

Corruble E, Legrand JM, Duret C, Charles G, Guelfi JD. IDS-C and IDS-sr: psychometric properties in depressed in-patients. J Affect Disord. 1999;56:95–101.

Corruble E, Legrand JM, Duret C, Charles G, Guelfi JD. IDS-C 和 IDS-sr：抑郁住院患者的心理测量特性。《情感障碍杂志》。1999年；56卷：95-101页。

Article

文章

CAS

中文名：化学文摘社

PubMed

Google Scholar

谷歌学术

Lamers F, Milaneschi Y, Vinkers CH, Schoevers RA, Giltay EJ, Penninx BWJH. Depression profilers and immuno-metabolic dysregulation: longitudinal results from the NESDA study. Brain Behav Immun. 2020;88:174–83.

Lamers F, Milaneschi Y, Vinkers CH, Schoevers RA, Giltay EJ, Penninx BWJH。抑郁特征与免疫代谢失调：来自NESDA研究的纵向结果。《大脑、行为与免疫》。2020年；第88卷：174-83页。

https://doi.org/10.1016/j.bbi.2020.04.002

。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术索

Felger JC, Li Z, Haroon E, Woolwine BJ, Jung MY, Hu X, et al. Inflammation is associated with decreased functional connectivity within corticostriatal reward circuitry in depression. Mol Psychiatry. 2016;21:1358–65.

Felger JC, Li Z, Haroon E, Woolwine BJ, Jung MY, Hu X, 等。炎症与抑郁症中皮质纹状体奖赏回路功能连接减弱相关。《分子精神病学》。2016年；21:1358–65。

https://doi.org/10.1038/mp.2015.168

。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术索

de Kluiver H, Jansen R, Penninx BWJH, Giltay EJ, Schoevers RA, Milaneschi Y. Metabolomics signatures of depression: the role of symptom profiles. Transl Psychiatry. 2023;13:198.

德克鲁伊弗 H，扬森 R，彭宁克斯 BWJH，吉尔塔伊 EJ，斯库弗斯 RA，米拉内斯基 Y。抑郁症的代谢组学特征：症状谱的作用。转化精神病学。2023年；13:198。

https://doi.org/10.1038/s41398-023-02484-5

。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Ameli R, Luckenbaugh DA, Gould NF, Holmes MK, Lally N, Ballard ED, et al. SHAPS-C: the Snaith-Hamilton pleasure scale modified for clinician administration. PeerJ. 2014;2:e429.

Ameli R, Luckenbaugh DA, Gould NF, Holmes MK, Lally N, Ballard ED, 等。SHAPS-C：为临床医生管理修改的Snaith-Hamilton快乐量表。PeerJ。2014;2:e429。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Jansen R, Milaneschi Y, Schranner D, Kastenmuller G, Arnold M, Han X, et al. The metabolome-wide signature of major depressive disorder. Mol Psychiatry. 2024;29:3722–33.

扬森 R，米拉内斯基 Y，施兰纳 D，卡斯滕穆勒 G，阿诺德 M，韩 X，等。重度抑郁症的代谢组学特征。《分子精神病学》。2024；29：3722–33。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Surendran P, Stewart ID, Au Yeung VPW, Pietzner M, Raffler J, Wörheide MA, et al. Rare and common genetic determinants of metabolic individuality and their effects on human health. Nat Med. 2022;28:2321–32.

Surendran P, Stewart ID, Au Yeung VPW, Pietzner M, Raffler J, Wörheide MA, 等。罕见和常见的代谢个体性遗传决定因素及其对人类健康的影响。《自然医学》。2022年；28:2321–32。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术索

van der Spek A, Stewart ID, Kühnel B, Pietzner M, Alshehri T, Gauß F, et al. Circulating metabolites modulated by diet are associated with depression. Mol Psychiatry. 2023;28:3874–87.

van der Spek A, Stewart ID, Kühnel B, Pietzner M, Alshehri T, Gauß F, 等。饮食调节的循环代谢物与抑郁症相关。《分子精神病学》。2023;28:3874–87。

Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-Country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–95.

Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, 等。国际体力活动问卷：12国可靠性与有效性。《医学科学运动与锻炼》。2003年；35:1381–95。

https://doi.org/10.1249/01.MSS.0000078924.61453.FB

。

Article

文章

PubMed

Google Scholar

谷歌学术搜索

Dowlati Y, Herrmann N, Swardfager W, Liu H, Sham L, Reim EK, et al. A meta-analysis of cytokines in major depression. Biol Psychiatry. 2010;67:446–57.

Dowlati Y, Herrmann N, Swardfager W, Liu H, Sham L, Reim EK, 等。重度抑郁症细胞因子的荟萃分析。《生物精神病学》。2010；67：446-57。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Kan C, Silva N, Golden SH, Rajala U, Timonen M, Stahl D, et al. A systematic review and meta-analysis of the association between depression and insulin resistance. Diabetes Care. 2013;36:480–9.

坎 C，席尔瓦 N，戈尔登 SH，拉贾拉 U，蒂蒙恩 M，斯塔尔 D，等。抑郁与胰岛素抵抗相关性的系统评价与荟萃分析。《糖尿病护理》。2013；36：480-9。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术

MahmoudianDehkordi S, Ahmed AT, Bhattacharyya S, Han X, Baillie RA, Arnold M, et al. Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression. Transl Psychiatry. 2021;11:153.

MahmoudianDehkordi S, Ahmed AT, Bhattacharyya S, Han X, Baillie RA, Arnold M, 等。酰基肉碱、胺和脂质的改变揭示了西酞普兰/艾司西酞普兰在重度抑郁中的作用机制。《转化精神病学》。2021年；11:153。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Guan F, Ni T, Zhu W, Williams LK, Cui L-B, Li M, et al. Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction. Mol Psychiatry. 2022;27:113–26.

关F，倪T，朱W，威廉姆斯LK，崔L-B，李M，等。精神分裂症的综合组学：从遗传决定因素到临床分类和风险预测。《分子精神病学》。2022年；27卷：113-26页。

Article

文章

PubMed

Google Scholar

谷歌学术

Brydges CR, Bhattacharyya S, Dehkordi SM, Milaneschi Y, Penninx B, Jansen R, et al. Metabolomic and inflammatory signatures of symptom dimensions in major depression. Brain Behav Immun. 2022;102:42–52.

Brydges CR, Bhattacharyya S, Dehkordi SM, Milaneschi Y, Penninx B, Jansen R, 等。重度抑郁症症状维度的代谢组学和炎症特征。《大脑、行为与免疫》。2022；102：42-52。

Article

文章

CAS

中文名：化学文摘社

PubMed

PubMed Central

Google Scholar

谷歌学术索

Morris SE, Sanislow CA, Pacheco J, Vaidyanathan U, Gordon JA, Cuthbert BN. Revisiting the seven pillars of RDoC. BMC Med. 2022;20:220.

Morris SE, Sanislow CA, Pacheco J, Vaidyanathan U, Gordon JA, Cuthbert BN。重新审视RDoC的七大支柱。BMC医学。2022年；20:220。

https://doi.org/10.1186/s12916-022-02414-0

。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术索

Pizzagalli D. Depression, stress, and anhedonia: toward a synthesis and integrated model. Annu Rev Clin Psychol. 2014;10:393–423.

皮扎加利 D. 抑郁、压力与快感缺失：走向综合与整合模型。《临床心理学年鉴》。2014年；10卷：393-423页。

https://doi.org/10.1146/annurev-clinpsy-050212-185606

。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Bekhbat M, Treadway M, Felger J. Inflammation as a pathophysiologic pathway to anhedonia: mechanisms and therapeutic implications. Curr Top Behav Neurosci. 2022;58:397–419.

贝赫巴特 M，特雷德韦 M，费尔格 J。炎症作为快感缺失的病理生理途径：机制与治疗意义。《当前行为神经科学主题》。2022年；58卷：397-419页。

https://doi.org/10.1007/7854_2021_294

。

Article

文章

PubMed

Google Scholar

谷歌学术

Shah SH, Hauser ER, Bain JR, Muehlbauer MJ, Haynes C, Stevens RD, et al. High heritability of metabolomic profiles in families burdened with premature cardiovascular disease. Mol Syst Biol. 2009;5:258.

Shah SH, Hauser ER, Bain JR, Muehlbauer MJ, Haynes C, Stevens RD, 等。早发性心血管疾病家族中代谢组学特征的高遗传性。《分子系统生物学》。2009年；5:258。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术索

Mattson MP, Arumugam TV. Hallmarks of brain aging: adaptive and pathological modification by metabolic states. Cell Metab. 2018;27:1176–99.

Mattson MP, Arumugam TV. 脑衰老的标志：代谢状态对适应性及病理性改变的影响。《细胞代谢》2018；27:1176–99。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Wang W, Lu Y, Xue Z, Li C, Wang C, Zhao X, et al. Rapid-acting antidepressant-like effects of acetyl-l-carnitine mediated by PI3K/AKT/BDNF/VGF signaling pathway in mice. Neuroscience. 2015;285:281–91.

王伟、卢毅、薛铮、李超、王晨、赵欣等。乙酰-L-肉碱通过PI3K/AKT/BDNF/VGF信号通路在小鼠中发挥快速抗抑郁样作用。《神经科学》。2015年；第285卷：281-291页。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Lau T, Bigio B, Zelli D, McEwen BS, Nasca C. Stress-induced structural plasticity of medial amygdala stellate neurons and rapid prevention by a candidate antidepressant. Mol Psychiatry. 2017;22:227–34.

刘T，比乔B，泽利D，麦克尤恩BS，纳asca C。压力诱导的内侧杏仁核星形神经元的结构可塑性及候选抗抑郁药的快速预防。《分子精神病学》。2017年；22：227-34。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术索

Karan KR, Trumpff C, McGill MA, Thomas JE, Sturm G, Lauriola V, et al. Mitochondrial respiratory capacity modulates LPS-induced inflammatory signatures in human blood. Brain Behav Immun - Health. 2020;5:100080.

Karan KR, Trumpff C, McGill MA, Thomas JE, Sturm G, Lauriola V, 等。线粒体呼吸能力调节人类血液中LPS诱导的炎症特征。《脑行为免疫健康》。2020年；5:100080。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术索

Gamradt S, Hasselmann H, Taenzer A, Brasanac J, Stiglbauer V, Sattler A, et al. Reduced mitochondrial respiration in T cells of patients with major depressive disorder. iScience. 2021;24:103312.

Gamradt S, Hasselmann H, Taenzer A, Brasanac J, Stiglbauer V, Sattler A, 等。重度抑郁症患者T细胞线粒体呼吸减少。《iScience》。2021年；24：103312。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Liepinsh E, Makrecka-Kuka M, Makarova E, Volska K, Svalbe B, Sevostjanovs E, et al. Decreased acylcarnitine content improves insulin sensitivity in experimental mice models of insulin resistance. Pharmacol Res. 2016;113:788–95.

Liepinsh E, Makrecka-Kuka M, Makarova E, Volska K, Svalbe B, Sevostjanovs E, 等。酰基肉碱含量降低可改善实验性胰岛素抵抗小鼠模型的胰岛素敏感性。《药理学研究》。2016；113：788-95。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术搜索

Langenau J, Boeing H, Bergmann MM, Nöthlings U, Oluwagbemigun K. The association between alcohol consumption and serum metabolites and the modifying effect of smoking. Nutrients. 2019;11:2331.

兰内瑙 J，波音 H，伯格曼 MM，诺斯林斯 U，奥卢瓦格贝米贡 K。饮酒与血清代谢物之间的关联及吸烟的修饰效应。《营养素》。2019；11：2331。

Article

文章

CAS

中文名：化学文摘社

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Paapstel K, Kals J. Metabolomics of arterial stiffness. Metabolites. 2022;12:370.

Paapstel K, Kals J. 动脉硬化代谢组学。《代谢物》。2022；12：370。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术

Wu Y-Y, Gou W, Yan Y, Liu C-Y, Yang Y, Chen D, et al. Gut microbiota and acylcarnitine metabolites connect the beneficial association between equol and adiposity in adults: a prospective cohort study. Am J Clin Nutr. 2022;116:1831–41.

吴宇宇，苟伟，颜莹，刘春燕，杨洋，陈栋，等。肠道微生物群和酰基肉碱代谢物连接了大豆苷元与成人肥胖之间的有益关联：一项前瞻性队列研究。《美国临床营养学杂志》。2022年；116卷：1831-41页。

Article

文章

CAS

中国科学院

PubMed

Google Scholar

谷歌学术

Nasca C, Bigio B, Lee FS, Young SP, Kautz MM, Albright A, et al. Acetyl-l-carnitine deficiency in patients with major depressive disorder. Proc Natl Acad Sci USA. 2018;115:8627–32.

纳斯卡 C，比焦 B，李 FS，杨 SP，考茨 MM，奥尔布赖特 A，等。重度抑郁症患者的乙酰-L-肉碱缺乏症。美国国家科学院院刊。2018；115：8627–32。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术索

Liu T, Deng K, Xue Y, Yang R, Yang R, Gong Z, et al. Carnitine and depression. Front Nutr. 2022;9:853058.

刘 T, 邓 K, 薛 Y, 杨 R, 杨 R, 龚 Z, 等。肉碱与抑郁症。《营养前沿》。2022；9：853058。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Baydakova GV, Tsygankova PG, Pechatnikova NL, Bazhanova OA, Nazarenko YD, Zakharova EY. New acylcarnitine ratio as a reliable indicator of long-chain 3-Hydroxyacyl-CoA dehydrogenase deficiency. Int J Neonatal Screen. 2023;9:48.

巴伊达科娃 GV，茨冈科娃 PG，佩恰特尼科娃 NL，巴扎诺娃 OA，纳扎连科 YD，扎哈罗娃 EY。新的酰基肉碱比率作为长链3-羟酰辅酶A脱氢酶缺乏症的可靠指标。《国际新生儿筛查杂志》。2023年；9：48。

Article

文章

PubMed

PubMed Central

Google Scholar

谷歌学术索

Shi C, Ao Z, Liu B, Xiao X, Gu X, Yang Q, et al. Increased acylcarnitine ratio indices in newborn screening for carnitine-acylcarnitine translocase deficiency shows increased sensitivity and reduced false-positivity. Transl Pediatr. 2023;12:871–81.

施C，敖Z，刘B，肖X，顾X，杨Q，等。在新生儿筛查中增加酰基肉碱比值指数用于肉碱-酰基肉碱转位酶缺乏症的检测，显示出更高的敏感性和更低的假阳性率。《转化儿科》。2023年；12：871–81。

Article

文章

CAS

中国科学院

PubMed

PubMed Central

Google Scholar

谷歌学术搜索

Download references

下载参考资料

Acknowledgements

致谢

The infrastructure for the NESDA study (

NESDA研究的基础设施（

http://www.nesda.nl

) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (ZonMw, grant number 10-000-1002) and financial contributions by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Leiden University Medical Center, Leiden University, GGZ Rivierduinen, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekscentrum).

）通过荷兰卫生研究与发展组织（ZonMw，资助编号10-000-1002）的Geestkracht计划以及参与大学和精神卫生保健组织（VU大学医学中心、GGZ inGeest、莱顿大学医学中心、莱顿大学、GGZ Rivierduinen、格罗宁根大学医学中心、格罗宁根大学、Lentis、GGZ Friesland、GGZ Drenthe、Rob Giel研究中心）的财政贡献提供资金支持。

R. Kaddurah-Daouk at Duke is PI of the Mood disorder Precision Medicine Consortium (funded by NIMH R01MH108348) and the Alzheimer Gut Microbiome Project (funded by NIA U19AG063744). She also received additional funding from NIA that enabled her research (RF1AG058942, RF1AG059093, U01AG061359, and R01AG081322).

杜克大学的R. Kaddurah-Daouk是情绪障碍精准医学联盟（由NIMH R01MH108348资助）和阿尔茨海默病肠道微生物组项目（由NIA U19AG063744资助）的首席研究员。她还获得了来自NIA的额外资助以支持她的研究（RF1AG058942、RF1AG059093、U01AG061359 和 R01AG081322）。

Y. Milaneschi received funding from Amsterdam UMC (Starter Grant 2023). M. Arnold and G. Kastenmüller received funding (through their institutions) from the National Institutes of Health/National Institute on Aging through grants RF1AG058942, RF1AG059093, U01AG061359, U19AG063744, R01AG069901, and R01AG081322..

Y. Milaneschi 收到了来自阿姆斯特丹 UMC 的资助（2023 年启动基金）。M. Arnold 和 G. Kastenmüller 通过他们的机构收到了来自美国国立卫生研究院/国家老龄化研究所的资助，资助编号为 RF1AG058942、RF1AG059093、U01AG061359、U19AG063744、R01AG069901 和 R01AG081322。

Author information

作者信息

Author notes

作者笔记

These authors contributed equally: Rima Kaddurah-Daouk, Yuri Milaneschi.

这些作者贡献相同：Rima Kaddurah-Daouk，Yuri Milaneschi。

Authors and Affiliations

作者与所属机构

Department of Neuroscience, Section of Psychiatry, Università Cattolica del Sacro Cuore, Rome, Italy

意大利罗马天主教圣心大学神经科学系精神病学部

Silvia Montanari, Delfina Janiri & Gabriele Sani

西尔维娅·蒙塔纳里、德尔菲娜·亚尼里和加布里埃莱·萨尼

Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

荷兰阿姆斯特丹，阿姆斯特丹大学医学中心，自由大学阿姆斯特丹，精神病学系

Rick Jansen, Brenda W. H. J. Penninx & Yuri Milaneschi

里克·扬森，布伦达·W·H·J·彭宁克斯，尤里·米拉内斯基

Amsterdam Public Health, Mental Health program, Amsterdam, The Netherlands

阿姆斯特丹公共健康，心理健康项目，阿姆斯特丹，荷兰

Rick Jansen, Brenda W. H. J. Penninx & Yuri Milaneschi

里克·扬森、布伦达·W·H·J·佩宁克斯和尤里·米拉内斯基

Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, The Netherlands

阿姆斯特丹神经科学，情绪、焦虑、精神病、睡眠与压力项目，阿姆斯特丹，荷兰

Rick Jansen, Brenda W. H. J. Penninx & Yuri Milaneschi

里克·扬森、布伦达·W·H·J·彭宁克斯、尤里·米拉内斯基

Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany

德国慕尼黑亥姆霍兹中心计算生物学研究所，纽赫贝格

Daniela Schranner, Gabi Kastenmüller & Matthias Arnold

丹妮拉·施兰纳、加比·卡斯滕穆勒和马蒂亚斯·阿诺德

Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA

美国北卡罗来纳州达勒姆杜克大学精神病学与行为科学系

Matthias Arnold, Siamak Mahmoudian Dehkordi, A. John Rush & Rima Kaddurah-Daouk

马蒂亚斯·阿诺德，西亚马克·马哈茂迪安·德赫尔迪，A. 约翰·拉什，里玛·卡杜拉-达乌克

Department of Psychiatry, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy

意大利罗马圣心天主教大学综合医院基金会精神病学系

Delfina Janiri & Gabriele Sani

德尔菲娜·亚尼里 & 加布里埃莱·萨尼

Arkansas Biosciences Institute, Department of Biological Sciences, Arkansas State University, Jonesboro, AR, USA

阿肯色州立大学生物科学系，阿肯色生物科学研究所，琼斯伯勒，阿肯色州，美国

Sudeepa Bhattacharyya

苏迪帕·巴塔查里亚

Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA

美国佐治亚州亚特兰大埃默里大学医学院精神病学与行为科学系

Boadie W. Dunlop

博阿迪·W·邓洛普

Duke-National University of Singapore, Singapore, Singapore

新加坡国立大学杜克学院，新加坡，新加坡

A. John Rush

A. 约翰·拉什

Duke Institute of Brain Sciences, Duke University, Durham, NC, USA

杜克大学脑科学研究所，杜克大学，北卡罗来纳州达勒姆，美国

Rima Kaddurah-Daouk

里玛·卡杜拉-达乌克

Department of Medicine, Duke University, Durham, NC, USA

美国北卡罗来纳州达勒姆杜克大学医学系

Rima Kaddurah-Daouk

里玛·卡杜拉-达乌克

Authors

作者

Silvia Montanari

西尔维娅·蒙塔纳里

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索该作者在

PubMed

Google Scholar

谷歌学术搜索

Rick Jansen

里克·扬森

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术

Daniela Schranner

丹妮拉·施兰纳

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术索

Gabi Kastenmüller

加布里埃勒·卡斯滕穆勒

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术

Matthias Arnold

马蒂亚斯·阿诺德

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术索

Delfina Janiri

德尔菲娜·贾尼里

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术搜索

Gabriele Sani

加布里埃莱·萨尼

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术索

Sudeepa Bhattacharyya

苏迪帕·巴塔查里亚

View author publications

查看作者出版物

You can also search for this author in

您还可以搜索该作者在

PubMed

Google Scholar

谷歌学术搜索

Siamak Mahmoudian Dehkordi

西亚马克·马哈茂迪安·德赫科迪

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术搜索

Boadie W. Dunlop

博阿迪·W·邓洛普

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索该作者在

PubMed

Google Scholar

谷歌学术

A. John Rush

A. 约翰·拉什

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术

Brenda W. H. J. Penninx

布伦达·W·H·J·彭宁克斯

View author publications

查看作者出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术搜索

Rima Kaddurah-Daouk

里玛·卡杜拉-达乌克

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术搜索

Yuri Milaneschi

尤里·米拉内斯基

View author publications

查看作者的出版物

You can also search for this author in

您还可以搜索此作者在

PubMed

Google Scholar

谷歌学术

Contributions

贡献

YM conceived the initial research idea and designed the analysis plan. SM and YM performed all of the analyses. DS and GK performed quality control of the metabolomics platform and contributed to the interpretation of metabolomics results together with SB, SMD and RKD. DJ, GS, BD, AJR and BWHJP contributed to the interpretation of results related to psychiatric phenotypes.

YM提出了最初的研究想法并设计了分析计划。SM和YM进行了所有的分析。DS和GK对代谢组学平台进行了质量控制，并与SB、SMD和RKD一起参与了代谢组学结果的解释。DJ、GS、BD、AJR和BWHJP参与了与精神疾病表型相关的结果解释。

BWHJP and RKD secured funding for the project. SM and YM wrote and finalized the manuscript, with contributions from all of the other authors. All of the authors read, reviewed and approved the final version of the manuscript..

BWHJP 和 RKD 为该项目获得了资金支持。SM 和 YM 撰写了手稿并最终定稿，其他所有作者均做出了贡献。所有作者阅读、审阅并批准了手稿的最终版本。

Corresponding authors

通讯作者

Correspondence to

致信

Rima Kaddurah-Daouk

里玛·卡杜拉-达乌克

或

Yuri Milaneschi

尤里·米拉内斯基

。

Ethics declarations

伦理声明

Competing interests

竞争利益

Y. Milaneschi has received consulting fees from Noema Pharma. A. John Rush has received consulting fees from Compass Inc., Curbstone Consultant LLC, Emmes Corp., Evecxia Therapeutics, Inc., Holmusk Technologies, Inc., ICON, PLC, Johnson and Johnson (Janssen), Liva-Nova, MindStreet, Inc., Neurocrine Biosciences Inc., Otsuka-US; speaking fees from Liva-Nova, Johnson and Johnson (Janssen); and royalties from Wolters Kluwer Health, Guilford Press and the University of Texas Southwestern Medical Center, Dallas, TX (for the Inventory of Depressive Symptoms and its derivatives).

Y. Milaneschi 收到了来自 Noema Pharma 的咨询费。A. John Rush 收到了来自 Compass Inc.、Curbstone Consultant LLC、Emmes Corp.、Evecxia Therapeutics, Inc.、Holmusk Technologies, Inc.、ICON, PLC、Johnson and Johnson（Janssen）、Liva-Nova、MindStreet, Inc.、Neurocrine Biosciences Inc.、Otsuka-US 的咨询费；来自 Liva-Nova、Johnson and Johnson（Janssen）的演讲费；以及来自 Wolters Kluwer Health、Guilford Press 和德克萨斯大学西南医学中心（达拉斯，TX）（针对抑郁症状清单及其衍生品）的版税。

He is also named co-inventor on two patents: U.S. Patent No. 7,795,033: Methods to Predict the Outcome of Treatment with Antidepressant Medication, Inventors: McMahon FJ, Laje G, Manji H, Rush AJ, Paddock S, Wilson AS; and U.S. Patent No. 7,906,283: Methods to Identify Patients at Risk of Developing Adverse Events During Treatment with Antidepressant Medication, Inventors: McMahon FJ, Laje G, Manji H, Rush AJ, Paddock S.

他还是两项专利的共同发明人：美国专利号 7,795,033：预测抗抑郁药物治疗结果的方法，发明人：McMahon FJ、Laje G、Manji H、Rush AJ、Paddock S、Wilson AS；以及美国专利号 7,906,283：识别在抗抑郁药物治疗期间有发生不良事件风险的患者的方法，发明人：McMahon FJ、Laje G、Manji H、Rush AJ、Paddock S。

M. Arnold and G. Kastenmüller are co-inventors (through Duke University/Helmholtz Zentrum München) on patents on applications of metabolomics in diseases of the central nervous system and hold equity in Chymia LLC and IP in PsyProtix and Atai that are exploring the potential for therapeutic applications targeting mitochondrial metabolism in treatment-resistant depression.

M. Arnold 和 G. Kastenmüller 是通过杜克大学/亥姆霍兹慕尼黑中心申请的关于代谢组学在中枢神经系统疾病中应用的专利的共同发明人，并持有 Chymia LLC 的股权以及 PsyProtix 和 Atai 的知识产权，这些公司正在探索针对治疗抵抗性抑郁症的线粒体代谢治疗应用潜力。

B. Dunlop has received research support from Boehringer Ingelheim, Compass Pathways, NIMH, Otsuka, Sage, Usona Institute, and Takeda and has served as a consultant for Biohaven, Cerebral Therapeutics, Myriad Neuroscience, NRx Pharmaceuticals, Otsuka, and Sage. R. Kaddurah-Daouk is an inventor on key patents in the field of Metabolomics and hold equity in Metabolon, a biotech company in North Carolina.

B. Dunlop 曾接受来自勃林格殷格翰、Compass Pathways、NIMH、大冢制药、Sage、Usona 研究所和武田制药的研究支持，并曾担任 Biohaven、Cerebral Therapeutics、Myriad Neuroscience、NRx Pharmaceuticals、大冢制药和 Sage 的顾问。R. Kaddurah-Daouk 是代谢组学领域关键专利的发明者，并持有北卡罗来纳州生物技术公司 Metabolon 的股份。

In addition, she.

此外，她。

Ethics approval

伦理批准

NESDA’s research protocol was approved by the ethical review board of each participating research center in Amsterdam, Leiden, and Groningen (METC number 2003-183). All participants provided written informed consent after having received detailed verbal and printed study information.

NESDA的研究协议获得了阿姆斯特丹、莱顿和格罗宁根各参与研究中心的伦理审查委员会的批准（METC编号2003-183）。所有参与者在收到详细的口头和书面研究信息后，均提供了书面知情同意。

Additional information

更多信息

Publisher’s note

出版社说明

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Springer Nature 对已发布地图中的管辖权声明和机构隶属关系保持中立。

Supplementary information

补充信息

Supplemental materials

补充材料

Rights and permissions

权利与权限

Open Access

开放获取

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

本文根据知识共享署名4.0国际许可证获得许可，该许可证允许您在任何媒介或格式中使用、分享、改编、分发和复制，只要您对原作者和来源给予适当的署名，提供知识共享许可证的链接，并说明是否进行了修改。

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

本文中的图像或其他第三方材料包含在文章的Creative Commons许可中，除非材料的信用条款另有说明。如果材料未包含在文章的Creative Commons许可中，且您打算的使用方式不被法律法规允许或超出了允许的使用范围，您需要直接从版权持有人处获得许可。

To view a copy of this licence, visit .

要查看此许可证的副本，请访问。

http://creativecommons.org/licenses/by/4.0/

。

Reprints and permissions

重印和权限

About this article

关于本文

Cite this article

引用这篇文章

Montanari, S., Jansen, R., Schranner, D.