Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-27T07:43:39.319Z Has data issue: false hasContentIssue false

Metabolomic profiles of 38 acylcarnitines in major depressive episodes before and after treatment

Published online by Cambridge University Press:  25 May 2023

Abd El Kader Ait Tayeb
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Service Hospitalo-Universitaire de Psychiatrie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Le Kremlin Bicêtre, Paris, F-94275, France
Romain Colle
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Service Hospitalo-Universitaire de Psychiatrie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Le Kremlin Bicêtre, Paris, F-94275, France
Kenneth Chappell
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France
Khalil El-Asmar
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Department of Epidemiology and Population Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
Cécile Acquaviva-Bourdain
Affiliation:
Service de Biochimie et Biologie Moléculaire; Unité Médicale Pathologies Héréditaires du Métabolisme et du Globule Rouge; Centre de Biologie et Pathologie Est; CHU de Lyon; F-69500 Bron, France
Denis J. David
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France
Séverine Trabado
Affiliation:
INSERM UMR-S U1185, Physiologie et Physiopathologie Endocriniennes, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Service de Génétique Moléculaire, Pharmacogénétique et Hormonologie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Le Kremlin Bicêtre, F-94275, France
Philippe Chanson
Affiliation:
INSERM UMR-S U1185, Physiologie et Physiopathologie Endocriniennes, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Université Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital Bicêtre, Service d'Endocrinologie et des Maladies de la Reproduction, Centre de Référence des Maladies Rares de l'Hypophyse, Hôpital de Bicêtre, Le Kremlin Bicêtre, F-94275, France
Bruno Feve
Affiliation:
Sorbonne Université-INSERM, Centre de Recherche Saint-Antoine, Institut Hospitalo-Universitaire ICAN, Service d'Endocrinologie, CRMR PRISIS, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, F-75012, France
Laurent Becquemont
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Centre de recherche clinique, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Le Kremlin Bicêtre, Paris, F-94275, France
Céline Verstuyft
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Service de Génétique Moléculaire, Pharmacogénétique et Hormonologie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Le Kremlin Bicêtre, F-94275, France
Emmanuelle Corruble*
Affiliation:
CESP, MOODS Team, INSERM UMR 1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre, Paris, F-94275, France Service Hospitalo-Universitaire de Psychiatrie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Le Kremlin Bicêtre, Paris, F-94275, France
*
Corresponding author: Emmanuelle Corruble; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Background

Major depression is associated with changes in plasma L-carnitine and acetyl-L-carnitine. But its association with acylcarnitines remains unclear. The aim of this study was to assess metabolomic profiles of 38 acylcarnitines in patients with major depression before and after treatment compared to healthy controls (HCs).

Methods

Metabolomic profiles of 38 plasma short-, medium-, and long-chain acylcarnitines were performed by liquid chromatography-mass spectrometry in 893 HCs from the VARIETE cohort and 460 depressed patients from the METADAP cohort before and after 6 months of antidepressant treatment.

Results

As compared to HCs, depressed patients had lower levels of medium- and long-chain acylcarnitines. After 6 months of treatment, increased levels of medium- and long-chain acyl-carnitines were observed that no longer differed from those of controls. Accordingly, several medium- and long-chain acylcarnitines were negatively correlated with depression severity.

Conclusions

These medium- and long-chain acylcarnitine dysregulations argue for mitochondrial dysfunction through fatty acid β-oxidation impairment during major depression.

Type
Original Article
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Introduction

Major depressive disorder (MDD) is the first leading cause of disability worldwide. By affecting over 350 million individuals, MDD is a public health priority inducing a high cost for society (Malhi & Mann, Reference Malhi and Mann2018). However, its clinical outcome after treatment remains poor and its physiopathology is poorly understood (Malhi & Mann, Reference Malhi and Mann2018; Trivedi et al., Reference Trivedi, Rush, Wisniewski, Nierenberg, Warden and Ritz2006).

Recent data suggest impairments of energy availability and mitochondrial metabolites in MDD (Giménez-Palomo et al., Reference Giménez-Palomo, Dodd, Anmella, Carvalho, Scaini, Quevedo and Berk2021). Moreover, changes in plasma L-carnitine (C0) and acetyl-L-carnitine (C2) have been shown during a major depressive episode (MDE) before and after antidepressant treatment (Ait Tayeb et al., Reference Ait Tayeb, Colle, El-Asmar, Chappell, Acquaviva-Bourdain, David and Corruble2023; Nasca et al., Reference Nasca, Bigio, Lee, Young, Kautz, Albright and Rasgon2018). However, there are only few data regarding the metabolomic profiles of short-, medium-, and long-chain acylcarnitines in MDE (from C3 to C18) whereas in other brain-related diseases, such as mental disorders (e.g. schizophrenia, autism) or Alzheimer's disease, studies identified associations with acylcarnitines (Frye, Melnyk, & MacFabe, Reference Frye, Melnyk and MacFabe2013; Horgusluoglu et al., Reference Horgusluoglu, Neff, Song, Wang, Wang and Arnold2021; Kriisa et al., Reference Kriisa, Leppik, Balõtšev, Ottas, Soomets, Koido and Zilmer2017). In daily clinical practice, metabolomic profiles of acylcarnitines allow for the assessment of fatty acid β-oxidation (FAO), a main mitochondrial pathway leading to energy production, and for the diagnosis of inborn errors of metabolism related to it (Houten & Wanders, Reference Houten and Wanders2010; Merritt, Norris, & Kanungo, Reference Merritt, Norris and Kanungo2018). Of note, short-, medium-, and long-chain acylcarnitines are specific to mitochondrial FAO (online Supplementary Fig. S1).

Decreased plasma levels of acylcarnitines are observed in patients with a MDE (Liu et al., Reference Liu, Zheng, Zhao, Zhang, Hu, Li and Xu2015) and individuals with depressive symptoms (Cassol et al., Reference Cassol, Misra, Morgello, Kirk, Mehta and Gabuzda2015; Mukerji et al., Reference Mukerji, Misra, Lorenz, Chettimada, Keller, Letendre and Gabuzda2021; Zacharias et al., Reference Zacharias, Hertel, Johar, Pietzner, Lukaschek, Atasoy and Ladwig2021). Besides, changes of acylcarnitine metabolic profiles have been shown after antidepressant treatment in 3 clinical cohorts of depressed patients. Indeed, increased levels of short-chain acylcarnitines and decreased levels of medium- and long-chain acylcarnitines were observed after an 8-week treatment with escitalopram/citalopram in 2 samples of 92 and 136 patients (Ahmed et al., Reference Ahmed, MahmoudianDehkordi, Bhattacharyya, Arnold, Liu, Neavin and Kaddurah-Daouk2020; MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021). Moreover, a decrease of short-chain acylcarnitines and an increase of medium- and long-chain acylcarnitines were observed 2 h after a ketamine/esketamine treatment in a sample of 53 depressed patients (Rotroff et al., Reference Rotroff, Corum, Motsinger-Reif, Fiehn, Bottrel, Drevets and Kaddurah-Daouk2016).

Nonetheless, to the best of our knowledge, there are no data comparing healthy subjects with depressed patients before and after 6 months of antidepressant treatment.

Hence, the first goal of this study was to assess plasma metabolomic profiles of acylcarnitines in depressed patients before and after antidepressant treatment as compared to healthy controls (HCs). The second goal was to assess the association between acylcarnitines and clinical outcomes of depressed patients.

Material and methods

Patients with major depression

This study was conducted in the METADAP cohort (Corruble et al., Reference Corruble, El Asmar, Trabado, Verstuyft, Falissard, Colle and Becquemont2015), a 6-month prospective, multicenter (6 French university hospitals), naturalistic, treatment study, including patients suffering from a current MDE in the context of MDD (DSM-IV-TR criteria), and requiring a new antidepressant treatment. The antidepressant treatment had to be a monotherapy. The choice of drug and its dose were left to the treating psychiatrist using ‘real-world’ treatment options. Written informed consent was obtained from all patients participating in this study, which was approved by the Ethics Committee and registered by the French National Agency for Medicine and Health Products Safety (ANSM) and the Commission Nationale de l'Informatique et des Libertés (CNIL) (ClinicalTrials.gov Identifier: NCT00526383).

Patients were included based on the following criteria: aged 18–65 years, with a minimum score of 18 on the Hamilton Depression Rating Scale-17 items (HDRS-17) (Hamilton, Reference Hamilton1960). Patients with psychotic symptoms, bipolar disorders, psychotic disorders, eating disorders, current substance abuse or dependence, organic brain syndromes, severe unstable medical conditions, or pregnancy were excluded from this study. Patients receiving antipsychotics or mood stabilizers before inclusion and/or for 4 months or more during the last year were not included. Of the 624 patients of the METADAP cohort, blood samples for metabolomic analyses from 164 patients of a single center were not available. Thus, 460 patients were analyzed. Patients were assessed at inclusion before treatment (M0), and three (M3) and six months (M6) after beginning treatment. Among depressed patients, 175 (38.5%) were treated with a selective serotonin reuptake inhibitor (SSRI), mainly escitalopram and citalopram, 177 (38.5%) were treated with a serotonin-norepinephrine reuptake inhibitor (SNRI), mainly venlafaxine, 38 (8.3%) were treated by tricyclic antidepressant (TCA), and 70 (15.2%) with another one (Table 1). The specific antidepressant treatments received by patients are reported in online Supplementary Table S1 (online Supplementary Table S1). 282 patients dropped out from the study. The main reasons were antidepressant drug changes for insufficient effectiveness /tolerance and loss to follow-up.

Table 1. Sociodemographic and clinical characteristics of healthy controls and depressed patients at baseline

Student's t tests were performed to compared healthy controls and depressed patients – BMI, Body mass index; MDD, Major depressive disorder; HDRS-17, 17-item Hamilton Depression Rating Scale; n, number of subjects; SD, Standard deviation; SSRI, Selective serotonin reuptake inhibitors; SNRI, Serotonin-norepinephrine reuptake inhibitors; TCA, Tricyclic antidepressant.

Clinical assessments were performed by the same senior psychiatrist for each visit. The HDRS-17, and the Quick Inventory of Depressive Symptomatology – Self-Report (QIDS-SR) (Rush et al., Reference Rush, Trivedi, Ibrahim, Carmody, Arnow, Klein and Keller2003), a self-questionnaire, were used to assess severity of MDE symptoms. Response and remission were defined as recommended by the American College of Neuropsychopharmacology Task Force (Rush et al., Reference Rush, Kraemer, Sackeim, Fava, Trivedi, Frank and Schatzberg2006). Response was based on a decrease of at least 50% from baseline in the HDRS score. Remission was based on a HDRS score lower or equal to 7. After 3 months of treatment, 132 patients (54.1%) were responders and 69 (28.3%) were remitters, while after 6 months, 119 patients (66.9%) were responders and 77 (43.3%) were remitters. There were no missing values at baseline, 8 at M3, and none at M6 for the HDRS-17. For the QIDS-SR, there were 14 missing values at baseline, 13 at M3, and none at M6.

Healthy controls

HCs were part of VARIETE, a cross-sectional study in the general population (Chanson et al., Reference Chanson, Arnoux, Mavromati, Brailly-Tabard, Massart and Young2016; Trabado et al., Reference Trabado, Al-Salameh, Croixmarie, Masson, Corruble, Fève and Chanson2017). This study was approved by the French National Agency for Medicine and Health Products Safety (ANSM) and the Ethics Committee (ClinicalTrials.gov Identifier: NCT01831648). To be included in the study, adult subjects (aged between 18 and 89 years) had to be healthy according to medical and psychiatric history, without any current diseases or disorders, including psychiatric disorders, assessed during a medical examination, and standard biological tests performed after an overnight fast. The exclusion criteria were history of a medical condition or psychiatric disorder, substance use, pregnancy or breastfeeding, and a history of blood transfusion or donation within the 3 months prior to inclusion. The VARIETE cohort included 895 subjects, but 2 blood samples were not available. Thus, 893 subjects were analyzed.

Metabolomic profiles of plasma acylcarnitines

EDTA blood samples were obtained from each subject in fasting standardized conditions for both depressed patients and HCs. Blood samples were obtained before any drug intake between 8:00 and 10:00 a.m. after an overnight fast and were prepared and analyzed as previously described (Ait Tayeb et al., Reference Ait Tayeb, Colle, El-Asmar, Chappell, Acquaviva-Bourdain, David and Corruble2023). Briefly, blood was centrifuged immediately (10 min, 2000 g at 4 °C) and plasma was aliquoted into separate polypropylene tubes that were immediately stored at −80 °C. Each aliquot was further divided into the volumes required for different analytical methods. One 10-μL aliquot was analyzed with the Biocrates AbsoluteIDQ p180 kit (Biocrates Life Science AG®, Innsbruck, Austria). The plasma samples were processed as recommended by the manufacturer and analyzed on an API 4000 Q-TRAP mass spectrometer (AB Sciex®, Darmstadt, Germany) coupled to an ACQUITY UPLC I Class system (Waters Corporation®, Milford, MA, USA) equipped with an Agilent C18 HPLC column.

The identification and the quantification of metabolites were performed as previously published (Trabado et al., Reference Trabado, Al-Salameh, Croixmarie, Masson, Corruble, Fève and Chanson2017). Briefly, the Biocrates AbsoluteIDQ p180 kit allows for the identification and measurement of more than 180 metabolites, including acylcarnitines. Acylcarnitines were analyzed using flow injection analysis (FIA) coupled to tandem mass spectrometry. Identification and quantification were performed based on internal standards and multiple reactions monitoring detection. After a pre-processing step (peak integration and concentration determination from calibration curves) with Multiquant software (AB Sciex, Darmstadt, Germany), data were uploaded into Biocrates MetIDQ software (included in the kit). Then, metabolite concentrations were directly calculated in MetIDQ.

EDTA sample management, plasma metabolomic analyses with Biocrates AbsolutIDQ p180 kit, and plasma sample processing were performed for HCs and depressed patients at each study time point (M0, M3, and M6) (Ait Tayeb et al., Reference Ait Tayeb, Colle, El-Asmar, Chappell, Acquaviva-Bourdain, David and Corruble2023). There were no missing biological data in HCs and in depressed patients at baseline, and 14 and 5 missing data at M3 and M6, respectively, in depressed patients. To prevent potential storage and batch effects, biological samples were assayed at the same time (randomly mixing both cohorts (METADAP and VARIETE) independently of the evaluation time for depressed patients) in the same laboratory using the same techniques for all subjects.

Thirty-eight acylcarnitines were measured, of which 12 were short chain acylcarnitines (from C3 to C5), 11 were medium chain (from C6 to C12) and 15 were long chain (from C14 to C18) (Table 2). Metabolites with less than 40% of values below the lower limit of quantification (LLOQ) at each time point in depressed patients and in HCs were analyzed as quantitative variables (MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021) and were described as ‘acylcarnitines with continuous values’. Metabolites with 40% or more values below the LLOQ at any time point in depressed patients or in HCs were analyzed as qualitative variables (above or under the LLOQ) and were described as ‘acylcarnitines with discretized dichotomized values’. Thus, among the 38 acylcarnitines, 12 were analyzed as quantitative variables and 26 as qualitative variables. For quantitative variables, values of acylcarnitines below the LLOQ were imputed as LLOQ/√2 (Colle et al., Reference Colle, Masson, Verstuyft, Fève, Werner, Boursier-Neyret and Becquemont2020). The plasma concentrations of acylcarnitines with continuous values in depressed patients during follow-up and in HCs are reported in online Supplementary Table S2 (online Supplementary Table S2). Concentrations of acylcarnitines with continuous values were log2 transformed for statistical analyses (MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021).

Table 2. The 38 acylcarnitines studied

Abbreviations were the name of acylcarnitines in the form ‘C(n)’ – Quantitative analyses were performed for metabolites with <40% of measurements under the lower limit of quantification in healthy controls and depressed patients at baseline, 3 months, and 6 months – Qualitative analyses were performed for other metabolites

Statistical analyses

The statistical analyses were performed using R 4.0.3.

Bivariate analyses were performed to compare depressed patients and HCs for socio-demographical (chi2 tests for qualitative variables and Student's t tests or Wilcoxon tests for quantitative variables).

Linear regressions (for quantitative variables) and logistic regressions (for qualitative variables) adjusted for age, gender, body mass index (BMI), blood total cholesterol, and glycemia were performed to compare plasma acylcarnitine levels between depressed patients and HCs and between depressed patients at each time point. In the event of a significant difference in linear regressions between HCs and depressed patients at baseline, receiver operating characteristic (ROC) curves were performed to explore the potential diagnostic relevance of the acylcarnitine.

Then, changes of acylcarnitines with continuous values after treatment were assessed with mixed-effect models for repeated measures adjusted for age, gender, BMI at baseline, HDRS at baseline, blood total cholesterol, glycemia, and antidepressant class. Using mixed-effect models, a patient with missing data on a specific visit/time-point will not result in a complete loss of information for that patient and an average estimation can still be calculated based on the remaining non-missing data points (Mallinckrodt et al., Reference Mallinckrodt, Sanger, Dubé, DeBrota, Molenberghs, Carroll and Tollefson2003). Covariables of the multivariate models were selected based on differences in bivariate analyses, with a significance threshold of p < 0.05. Spearman's correlation tests and linear regressions adjusted for age, gender, BMI, blood total cholesterol, and glycemia were used to test associations between levels of acylcarnitines with continuous values and MDE severity (according to HDRS total scores and QIDS-SR total scores). Finally, logistic regressions adjusted for age, gender, BMI, blood total cholesterol, glycemia, and antidepressant class were performed to compare acylcarnitine levels according to response/remission after 3 and 6 months of antidepressant treatment. All tests were two-tailed. Bonferroni corrections were applied. Based on the 38 metabolites measured, the significance threshold retained was p < 0.00131, except for analyses of acylcarnitine levels according to clinical outcomes and MDE severity, based on the 12 acylcarnitines with continuous values, for which the significance threshold retained was p < 0.00417.

Results

Socio-demographic and clinical characteristics

Socio-demographic and clinical characteristics of the 460 depressed patients and 893 HCs are shown in Table 1. At baseline, depressed patients and HCs differed with respect to age, gender, BMI, blood total cholesterol, and glycemia (Table 1).

Metabolomic profiles of acylcarnitines in MDE patients at baseline and HCs

Among the 12 short-chain acylcarnitines, 6 were increased (C3:1, C4-OH, C4:1, C5-DC, C5-OH and C5:1-DC) and one was decreased (C5) in depressed patients compared to HCs. There was no significant difference for 5 of them (C3, C3-OH, C4, C5:1, C5-M-DC). Among the 11 medium-chain acylcarnitines, 6 were decreased (C6, C7-DC, C8, C10, C12 and C12:1) and 2 were increased (C6:1 and C10:2) in depressed patients compared to HCs. There was no significant difference for 3 of them (C9, C10:1, C12-DC). Among the 15 long-chain acylcarnitines, 13 were decreased (C14, C14:1, C14:1-OH, C14:2, C14:2-OH, C16, C16-OH, C16:1, C16:1-OH, C16:2, C18, C18:1 and C18:2) in depressed patients compared to HCs. There was no significant difference for 2 of them (C16:2-OH, C18:1-OH) (Fig. 1 and online Supplementary Tables S3 and S4). The performed ROC curves were associated with the diagnosis of MDE for C4-OH (area under the curve (AUC): 0.644; p < 0.0001), C5 (AUC: 0.654; p < 0.0001), C6 (AUC:0.604; p < 0.0001), C10 (AUC: 0.740; p < 0.0001), C14:1 (AUC: 0.732; p < 0.0001), C16 (AUC: 0.667; p < 0.0001), C18 (AUC: 0.632; p < 0.0001), C18:1 (AUC: 0.584; p < 0.0001), and C18:2 (AUC: 0.657; p < 0.0001). The performed ROC curves were described in the online Supplementary Figure S2 (online Supplementary Fig. S2).

Figure 1. Plasma levels of acylcarnitines in healthy controls and in depressed patients during follow-up. Logistic regression adjusted for age, gender, BMI, HDRS score, total blood cholesterol, glycemia, and antidepressant class were performed for qualitative variables – Linear regression adjusted for age, gender, BMI, HDRS scores, total blood cholesterol, glycemia, and antidepressant class were performed for quantitative variables – MDE: Major depressive episode – M3: at 3 months – M6: at 6 months – Metabolite abbreviations and quantitative/qualitative variables are defined in Table 2: Statistically lower/decreased – : Statistically higher/increased – : No statistical difference – *: Significance after Bonferroni corrections (p < 0.00131) – **: p < 0.0001 – ***: p < 0.00001.

Metabolomic profiles of acylcarnitines and severity of MDE

In correlation plots, two clusters of acylcarnitines were identified in depressed patients. The first comprised short-chain acylcarnitines, while the second comprised medium- and long-chain acylcarnitines (Fig. 2). Of note, similar clusters were identified in HCs (online Supplementary Fig. S3). In depressed patients at baseline, M3, and M6, correlation plots show that HDRS total scores were negatively correlated with medium- and long-chain acylcarnitines, but not with short- ones (Fig. 2). Accordingly, negative correlations were observed between HDRS total scores and C6, C9, C10, C14:1, C16, and C18 (respectively rho = −0.105; p = 0.002 – rho = −0.141; p = 3.1E-5 – rho = −0.201; p = 2.3E-9 – rho = −0.247; p = 1.9E-13 – rho = −0.116; p = 0.0006 – rho = −0.129; p = 0.0001) (online Supplementary Table S5). In multivariate analyses adjusted for age, gender, BMI, blood total cholesterol, and glycemia, these associations remained statistically significant for C9, C10, and C14:1. Similar correlations were identified with the QIDS-SR total scores. Moreover, in bivariate analyses, negative correlations were observed between HDRS total scores and C6, C9, C10, C14:1, C16, and C18 (respectively rho = −0.099; p = 0.004 – rho = −0.169; p = 7.2E-7 – rho = −0.206; p = 1.5E-9 – rho = −0.215; p = 2.4E-10 – rho = −0.133; p = 1.0E-4 – rho = −0.150; p = 1.5E-6). In multivariate analyses adjusted for age, gender, BMI, blood total cholesterol, and glycemia, these associations remained statistically significant, except for C6 (online Supplementary Table S5).

Figure 2. Correlation plot of acylcarnitines and depression severity in depressed patients. Blue represents positive correlations and red represents negative correlations – Acylcarnitine concentrations were log2 transformed – The first cluster (C3, C4, C4-OH, C5) was short-chain acylcarnitines – The second cluster (C6, C9, C10, C14:1, C16, C18, C18:1, C18:2) was medium- and long-chain acylcarnitines – The third cluster (HDRS-17, QIDS-SR) was scales of depression severity – Metabolite abbreviations are defined in Table 2 – MDE, Major depressive episode; HDRS-17, 17-item Hamilton Depression Rating Scale; QIDS-SR, Quick Inventory of Depressive Symptomatology-Self-Report.

Metabolomic profiles of acylcarnitines after treatment in depressed patients

In mixed models for repeated measures adjusted for age, gender, BMI at baseline, HDRS at baseline, blood total cholesterol, glycemia, and antidepressant class, only one short-chain acylcarnitine with continuous values (C4) among the 4 analyzed increased over time after 3 and 6 months of treatment. Among the 8 medium- and long-chain acylcarnitines with continuous values, 6 increased (C6, C9, C10, C14:1, C16 and C18) over the 6 months of treatment, while there was no significant change for the other 2 (Table 3).

Table 3. Mixed model analyses for repeated measures for plasma levels of acylcarnitines in depressed patients over time

Mixed model analyses were adjusted for age, gender, BMI at baseline, HDRS at baseline, blood total cholesterol at baseline, glycemia at baseline, and antidepressant class – Metabolite concentrations were log2 transformed – CI: Confidence interval – Metabolite abbreviations are defined in Table 2Bold p-value: Significance after Bonferroni corrections

Moreover, the differences in acylcarnitine levels between HCs and depressed patients decreased progressively until a normalization after 6 months of treatment (Fig. 1 and online Supplementary Tables S3 and S4). In analyses at each time point during follow-up, there was an increase in the levels of several medium- and long-chain acylcarnitines, but not in the levels of short-chain acylcarnitines compared to baseline (Fig. 1 and online Supplementary Tables S4 and S6).

Acylcarnitines and clinical outcomes after treatment in depressed patients

Plasma acylcarnitine values did not differ between responders and non-responders or remitters and non-remitters at baseline or during follow-up (online Supplementary Tables S7 and S8).

Discussion

This study compared the plasma metabolomic profiles of 38 acylcarnitines in depressed patients and HCs and described their changes after treatment in depressed patients. Depressed patients had lower levels of medium- and long-chain acylcarnitines. Globally, these acylcarnitine levels were normalized after 6 months of treatment. Nonetheless, these changes were not associated with clinical outcomes.

First, we showed that plasma levels of medium- and long-chain acylcarnitine were lower in MDE patients as compared to controls. This result is consistent with previous clinical data. Indeed, in a sample of 135 depressed patients and 111 controls, medium- and long-chain acylcarnitine levels were lower in MDE patients (Liu et al., Reference Liu, Zheng, Zhao, Zhang, Hu, Li and Xu2015). Cassol et al., showed that the levels of all acylcarnitines decreased, though it did not specifically focus on MDE in the context of MDD, but rather on depressive symptoms in a specific sample of 104 HIV-positive and HIV-negative patients compared to controls (Cassol et al., Reference Cassol, Misra, Morgello, Kirk, Mehta and Gabuzda2015). In another specific sample of 99 HIV-positive patients, plasma acylcarnitine levels decreased while depressive symptoms increased (Mukerji et al., Reference Mukerji, Misra, Lorenz, Chettimada, Keller, Letendre and Gabuzda2021). Accordingly, in 2 large samples of 1411 and 968 participants, subjects with depressive symptoms had lower levels of medium-chain acylcarnitines (Zacharias et al., Reference Zacharias, Hertel, Johar, Pietzner, Lukaschek, Atasoy and Ladwig2021).

Our result suggests an increase of FAO in depressed patients (Warren et al., Reference Warren, Lou, Lucchinetti, Zhang, Clanachan, Affolter and Lemieux2014). Indeed, medium- and long-chain fatty acids enter mitochondria through the carnitine shuttle in the form of acylcarnitines to be converted into acyl-CoA, which is essential for FAO (Houten & Wanders, Reference Houten and Wanders2010). Consequently, reduced levels of acylcarnitines reveal an upregulation of FAO. Interestingly, in schizophrenia, enhanced FAO has also been reported among 110 patients and 190 healthy subjects (Yang et al., Reference Yang, Sun, Zhao, Hu, Qing, Jiang and Wan2017). In line with our results, a meta-analysis of peripheral metabolites showed an alteration of fatty acid metabolism in MDE patients (Pu et al., Reference Pu, Liu, Zhang, Tian, Gui, Yu and Xie2021).

Second, we showed that plasma medium- and long-chain acylcarnitine levels significantly increased over time after antidepressant treatment in depressed patients until a normalization after 6 months of treatment. In preclinical studies using various rodent models of depression, the antidepressant fluoxetine normalized plasma acylcarnitine alterations (Chen et al., Reference Chen, Wei, Gao, Kong, Jia, Hu and Xu2014; Hamilton et al., Reference Hamilton, Chen, Tolstikov, Peña, Picone, Shah and Nestler2020; Xue et al., Reference Xue, Zhou, Xue, Liu, Cai, Luo and Peng2020). However, previous clinical data are still contentious. In two samples of depressed patients treated with escitalopram or citalopram for 8 weeks, there were changes in acylcarnitine levels after treatment (Ahmed et al., Reference Ahmed, MahmoudianDehkordi, Bhattacharyya, Arnold, Liu, Neavin and Kaddurah-Daouk2020; Rotroff et al., Reference Rotroff, Corum, Motsinger-Reif, Fiehn, Bottrel, Drevets and Kaddurah-Daouk2016; MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021). Recently, decreased levels of medium- and long-chain acylcarnitines and increased levels of short-chain acylcarnitines have been shown in a small sample of 136 depressed patients (Ahmed et al., Reference Ahmed, MahmoudianDehkordi, Bhattacharyya, Arnold, Liu, Neavin and Kaddurah-Daouk2020; MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021). Another study exploring acylcarnitines in 53 MDE patients treated with ketamine or esketamine showed increased plasma long chain acylcarnitine levels after treatment (Rotroff et al., Reference Rotroff, Corum, Motsinger-Reif, Fiehn, Bottrel, Drevets and Kaddurah-Daouk2016). Of note, none of these studies had a control group of healthy subjects.

Third, we showed a negative correlation between medium- and long-chain acylcarnitines and depression severity. Consistent results have been described previously for 11 acylcarnitines, whereas we show a complete metabolomic profile (Liu et al., Reference Liu, Zheng, Zhao, Zhang, Hu, Li and Xu2015). Nevertheless, a previous study showed increased levels of acylcarnitines in MDE patients in remission compared to HCs, whereas we show no difference in acylcarnitine levels according to remission in MDE patients after antidepressant treatment, nor between MDE patients after treatment and HCs (Mocking et al., Reference Mocking, Naviaux, Li, Wang, Monk, Bright and Naviaux2021).

Finally, we found different changes according to the size of acylcarnitines, with short-chain acylcarnitines on one hand and medium- and long-chain acylcarnitines on the other. Similar differences were observed in previous studies that explored antidepressant effects on acylcarnitines levels (Ahmed et al., Reference Ahmed, MahmoudianDehkordi, Bhattacharyya, Arnold, Liu, Neavin and Kaddurah-Daouk2020; MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021), antipsychotic treatment in psychotic disorders (Kriisa et al., Reference Kriisa, Leppik, Balõtšev, Ottas, Soomets, Koido and Zilmer2017), autism (Frye et al., Reference Frye, Melnyk and MacFabe2013) and neurological disorders such as Parkinson's disease (Saiki et al., Reference Saiki, Hatano, Fujimaki, Ishikawa, Mori, Oji and Hattori2017) and Alzheimer's disease (Horgusluoglu et al., Reference Horgusluoglu, Neff, Song, Wang, Wang and Arnold2021). Unlike medium- and long-chain fatty acids, short-chain fatty acids do not need the carnitine shuttle to enter mitochondria. Moreover, short-chain acylcarnitines reflect the metabolism of some amino acids, such as leucine, valine, or isoleucine (MahmoudianDehkordi et al., Reference MahmoudianDehkordi, Ahmed, Bhattacharyya, Han, Baillie and Arnold2021). Consequently, they are less in line with FAO and should be further explored. Effects on medium- and long-chain acylcarnitines were stronger among medium-chain acylcarnitines. This result was consistent with those of previous studies showing that even medium-chain acylcarnitines are the main biomarkers of FAO activity (Lehmann et al., Reference Lehmann, Zhao, Weigert, Simon, Fehrenbach, Fritsche and Niess2010).

Relations between plasma acylcarnitine concentrations on the one hand and brain metabolism and cerebral acylcarnitine concentrations on the other hand are still unclear (Dambrova et al., Reference Dambrova, Makrecka-Kuka, Kuka, Vilskersts, Nordberg, Attwood and Schiöth2022). Nevertheless, hypotheses can be raised and several mechanisms could underly our results. Recent evidence suggests the implication of mitochondrial and energy metabolic disturbances and a reduced metabolic flexibility in psychiatric disorders including MDD (Lin & Beal, Reference Lin and Beal2006; Moore, Christensen, Lafer, Fava, & Renshaw, Reference Moore, Christensen, Lafer, Fava and Renshaw1997). In preclinical models, depression-like behavior is related to a decreased level of acetyl-CoA (the final product of FAO, which is important for ATP production via the citric acid cycle) (Kubota, Goto, Hagiya, Chohnan, & Toyoda, Reference Kubota, Goto, Hagiya, Chohnan and Toyoda2016; Xie et al., Reference Xie, Shen, Yu, Xiao, Zhou, Xiong and Fu2020) and consequently decreased energy availability. In line with this hypothesis, decreased FAO could be expected during MDE. Nevertheless, we observed an upregulation of FAO (Houten & Wanders, Reference Houten and Wanders2010). This upregulation might be an attempt to restore acetyl-CoA levels. In the brain, the FAO is largely based in astrocytes to support neurons, probably by regulating the concentrations of cerebral neurotransmitters and should be further explored (Bartlett & Eaton, Reference Bartlett and Eaton2004; Souza, Almeida, Souza, & Zimmer, Reference Souza, Almeida, Souza and Zimmer2019; White et al., Reference White, Lee, Choi, Chu, Scafidi and Wolfgang2020). Equally, the FAO is based in the hypothalamus (Lam, Schwartz, & Rossetti, Reference Lam, Schwartz and Rossetti2005). Of note, MDD is known to be related with hypothalamic and astroglial abnormalities (Malhi & Mann, Reference Malhi and Mann2018). Therefore, MDE could be related to FAO dysregulation in the brain. Moreover, during stress or cerebral diseases, there is an increased hepatic production of ketone bodies by FAO upregulation to support brain metabolism (Jensen, Wodschow, Nilsson, & Rungby, Reference Jensen, Wodschow, Nilsson and Rungby2020; McGarry, Robles-Valdes, & Foster, Reference McGarry, Robles-Valdes and Foster1975). Hence, the observed FAO upregulation in MDD could be systemic, as suggested by plasma modifications of medium- and long-chain acylcarnitines (online Supplementary Fig. S1) (Saiki et al., Reference Saiki, Hatano, Fujimaki, Ishikawa, Mori, Oji and Hattori2017). However, FAO upregulation leads to increased oxidative stress and inflammation characterized by a production of reactive oxygen species (Jensen et al., Reference Jensen, Wodschow, Nilsson and Rungby2020; White et al., Reference White, Lee, Choi, Chu, Scafidi and Wolfgang2020), which could maintain the MDD.

The present study has some limitations. First, there were differences with respect to socio-demographic characteristics and biological parameters between MDE patients and HCs. Furthermore, patients were treated with different antidepressant classes. Thus, the models used were adjusted on these potentially cofounding factors. Second, data regarding food intake were not evaluated, though it could influence acylcarnitine concentrations. However, we showed in a previous analysis of the same cohorts an increase in plasma L-carnitine (C0) levels in depressed patients compared to HCs (Ait Tayeb et al., Reference Ait Tayeb, Colle, El-Asmar, Chappell, Acquaviva-Bourdain, David and Corruble2023). This result does not suggest a deficiency in total carnitine levels (L-carnitine and acylcarnitines) in depressed patients, but rather a change in metabolomic profiles. Even if a decreased appetite is observed in MDE, the constant levels of total carnitines argue against acylcarnitine deficiency in the food intake of depressed patients, and observed abnormalities were in line with FAO disturbances (Reuter & Evans, Reference Reuter and Evans2012). Third, some metabolite levels were below the LLOQ and were either imputed for analysis or were analyzed as qualitative variables. Fourth, targeted metabolomic profiles of acylcarnitines were performed instead of a large-scale metabolomic profile. However, this allowed for the study of a specific pathway with a clear rationale, the FAO. Moreover, acylcarnitines are currently used in daily practice and could have earlier clinical implications after replication and determination of specific pathologic thresholds adapter for MDD. Finally, the attrition rate was high and could limit the power of the study. However, it is close to those of other similar cohorts, like the STAR*D cohort (Trivedi et al., Reference Trivedi, Rush, Wisniewski, Nierenberg, Warden and Ritz2006).

This study has several strengths. First, the number of MDE patients compared to controls is the largest to assess the whole metabolomic profile of plasma acylcarnitines. This sample confers a reasonable confidence and generalizability of the results. Second, it is also a naturalistic study of ‘real-life’ patients, which reduces the gap between research and practice. Third, it offers the first extensive quantification of plasma acylcarnitine metabolomic profiles in depressed patients assessed in a central laboratory with controlled sampling and pre-analytical procedures. Hence, it provides a reliable picture of FAO in depressed patients. Finally, to the best of our knowledge, it is the first case-control study exploring the whole plasma metabolomic profiles of acylcarnitines in MDE in the context of MDD before and after antidepressant treatment.

To conclude, this study is the largest to explore the association between acylcarnitine metabolomic profiles, major depression, and long-term outcome after treatment. It provides new insights into the biological mechanisms of major depression. MDE in the context of MDD is associated with lower levels of plasma medium- and long-chain acylcarnitines, which are normalized after treatment. These results suggest an implication of FAO in MDD and should be further investigated.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S003329172300140X.

Acknowledgements

Centre de Ressources Biologiques Paris-Saclay (CRB PARIS SACLAY) for the METADAP biobank's storage (BRIF Number: BB-0033-00089).

Financial support

This work was supported by the Programme Hospitalier de Recherche Clinique (PHRC) from the French Ministry of Health (AOM06022:PC and AOM09122:EC); and the Assistance Publique – Hôpitaux de Paris (P060219:EC).

Conflict of interest

Abd El Kader AIT TAYEB, Romain COLLE, Kenneth CHAPPELL, Khalil EL-ASMAR, Cécile ACQUAVIVA-BOURDAIN, Séverine TRABADO, Phillipe CHANSON, Bruno FEVE, Laurent BECQUEMONT, Céline VERSTUYFT, and Emmanuelle CORRUBLE had no conflict of interest to disclose.

Denis J. DAVID serves as a consultant for Lundbeck Inc, received compensation from Lundbeck and named on non-provisional patent applications for the prophylactic use of RS67333 against stress-related psychiatric disorders.

Footnotes

*

These authors contributed equally to this work.

References

Ahmed, A. T., MahmoudianDehkordi, S., Bhattacharyya, S., Arnold, M., Liu, D., Neavin, D., … Kaddurah-Daouk, R. (2020). Acylcarnitine metabolomic profiles inform clinically-defined major depressive phenotypes. Journal of Affective Disorders, 264, 9097. https://doi.org/10.1016/j.jad.2019.11.122.CrossRefGoogle ScholarPubMed
Ait Tayeb, A. E. K., Colle, R., El-Asmar, K., Chappell, K., Acquaviva-Bourdain, C., David, D. J., … Corruble, E. (2023). Plasma acetyl-l-carnitine and l-carnitine in major depressive episodes: A case–control study before and after treatment. Psychological Medicine, 53(6), 23072316. https://doi.org/10.1017/S003329172100413X.CrossRefGoogle ScholarPubMed
Bartlett, K., & Eaton, S. (2004). Mitochondrial beta-oxidation. European Journal of Biochemistry, 271(3), 462469. https://doi.org/10.1046/j.1432-1033.2003.03947.x.CrossRefGoogle ScholarPubMed
Cassol, E., Misra, V., Morgello, S., Kirk, G. D., Mehta, S. H., & Gabuzda, D. (2015). Altered monoamine and acylcarnitine metabolites in HIV-positive and HIV-negative subjects with depression. JAIDS Journal of Acquired Immune Deficiency Syndromes, 69(1), 1828. https://doi.org/10.1097/QAI.0000000000000551.CrossRefGoogle ScholarPubMed
Chanson, P., Arnoux, A., Mavromati, M., Brailly-Tabard, S., Massart, C., & Young, J., … for the VARIETE Investigators. (2016). Reference values for IGF-I serum concentrations: Comparison of six immunoassays. The Journal of Clinical Endocrinology & Metabolism, 101(9), 34503458. https://doi.org/10.1210/jc.2016-1257.CrossRefGoogle ScholarPubMed
Chen, S., Wei, C., Gao, P., Kong, H., Jia, Z., Hu, C., … Xu, G. (2014). Effect of Allium macrostemon on a rat model of depression studied by using plasma lipid and acylcarnitine profiles from liquid chromatography/mass spectrometry. Journal of Pharmaceutical and Biomedical Analysis, 89, 122129. https://doi.org/10.1016/j.jpba.2013.10.045.CrossRefGoogle ScholarPubMed
Colle, R., Masson, P., Verstuyft, C., Fève, B., Werner, E., Boursier-Neyret, C., … Becquemont, L. (2020). Peripheral tryptophan, serotonin, kynurenine, and their metabolites in major depression: A case–control study. Psychiatry and Clinical Neurosciences, 74(2), 112117. https://doi.org/10.1111/pcn.12944.CrossRefGoogle ScholarPubMed
Corruble, E., El Asmar, K., Trabado, S., Verstuyft, C., Falissard, B., Colle, R., … Becquemont, L. (2015). Treating major depressive episodes with antidepressants can induce or worsen metabolic syndrome: Results of the METADAP cohort. World Psychiatry, 14(3), 366367. https://doi.org/10.1002/wps.20260.CrossRefGoogle ScholarPubMed
Dambrova, M., Makrecka-Kuka, M., Kuka, J., Vilskersts, R., Nordberg, D., Attwood, M. M., … Schiöth, H. B. (2022). Acylcarnitines: Nomenclature, biomarkers, therapeutic potential, drug targets, and clinical trials. Pharmacological Reviews, 74(3), 506551. https://doi.org/10.1124/pharmrev.121.000408.CrossRefGoogle ScholarPubMed
Frye, R. E., Melnyk, S., & MacFabe, D. F. (2013). Unique acyl-carnitine profiles are potential biomarkers for acquired mitochondrial disease in autism spectrum disorder. Translational Psychiatry, 3(1), e220e220. https://doi.org/10.1038/tp.2012.143.CrossRefGoogle ScholarPubMed
Giménez-Palomo, A., Dodd, S., Anmella, G., Carvalho, A. F., Scaini, G., Quevedo, J., … Berk, M. (2021). The role of mitochondria in mood disorders: From physiology to pathophysiology and to treatment. Frontiers in Psychiatry, 12, 546801. https://doi.org/10.3389/fpsyt.2021.546801.CrossRefGoogle ScholarPubMed
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery & Psychiatry, 23(1), 5662. https://doi.org/10.1136/jnnp.23.1.56.CrossRefGoogle ScholarPubMed
Hamilton, P. J., Chen, E. Y., Tolstikov, V., Peña, C. J., Picone, J. A., Shah, P., … Nestler, E. J. (2020). Chronic stress and antidepressant treatment alter purine metabolism and beta oxidation within mouse brain and serum. Scientific Reports, 10(1), 18134. https://doi.org/10.1038/s41598-020-75114-5.CrossRefGoogle ScholarPubMed
Horgusluoglu, E., Neff, R., Song, W., Wang, M., Wang, Q., & Arnold, M., … the Alzheimer Disease Metabolomics Consortium. (2021). Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease. Alzheimer's & Dementia, 18(6), 12601278. https://doi.org/10.1002/alz.12468.CrossRefGoogle ScholarPubMed
Houten, S. M., & Wanders, R. J. A. (2010). A general introduction to the biochemistry of mitochondrial fatty acid β-oxidation. Journal of Inherited Metabolic Disease, 33(5), 469477. https://doi.org/10.1007/s10545-010-9061-2.CrossRefGoogle Scholar
Jensen, N. J., Wodschow, H. Z., Nilsson, M., & Rungby, J. (2020). Effects of ketone bodies on brain metabolism and function in neurodegenerative diseases. International Journal of Molecular Sciences, 21(22), 8767. https://doi.org/10.3390/ijms21228767.CrossRefGoogle ScholarPubMed
Kriisa, K., Leppik, L., Balõtšev, R., Ottas, A., Soomets, U., Koido, K., … Zilmer, M. (2017). Profiling of acylcarnitines in first episode psychosis before and after antipsychotic treatment. Journal of Proteome Research, 16(10), 35583566. https://doi.org/10.1021/acs.jproteome.7b00279.CrossRefGoogle ScholarPubMed
Kubota, Y., Goto, T., Hagiya, Y., Chohnan, S., & Toyoda, A. (2016). Decreased hepatic contents of coenzyme A molecular species in mice after subchronic mild social defeat stress. Stress (Amsterdam, Netherlands), 19(2), 192197. https://doi.org/10.3109/10253890.2015.1137558.CrossRefGoogle ScholarPubMed
Lam, T. K. T., Schwartz, G. J., & Rossetti, L. (2005). Hypothalamic sensing of fatty acids. Nature Neuroscience, 8(5), 579584. https://doi.org/10.1038/nn1456.CrossRefGoogle ScholarPubMed
Lehmann, R., Zhao, X., Weigert, C., Simon, P., Fehrenbach, E., Fritsche, J., … Niess, A. M. (2010). Medium chain acylcarnitines dominate the metabolite pattern in humans under moderate intensity exercise and support lipid oxidation. PLoS One, 5(7), e11519. https://doi.org/10.1371/journal.pone.0011519.CrossRefGoogle ScholarPubMed
Lin, M. T., & Beal, M. F. (2006). Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature, 443(7113), 787795. https://doi.org/10.1038/nature05292.CrossRefGoogle ScholarPubMed
Liu, X., Zheng, P., Zhao, X., Zhang, Y., Hu, C., Li, J., … Xu, G. (2015). Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography–mass spectrometry. Journal of Proteome Research, 14(5), 23222330. https://doi.org/10.1021/acs.jproteome.5b00144.CrossRefGoogle ScholarPubMed
MahmoudianDehkordi, S., Ahmed, A. T.,Bhattacharyya, S., Han, X., Baillie, R. A., Arnold, M., … The Mood Disorders Precision Medicine Consortium (MDPMC). (2021). Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression. Translational Psychiatry, 11(1), 153. https://doi.org/10.1038/s41398-020-01097-6.CrossRefGoogle ScholarPubMed
Malhi, G. S., & Mann, J. J. (2018). Depression. The Lancet, 392(10161), 22992312. https://doi.org/10.1016/S0140-6736(18)31948-2.CrossRefGoogle ScholarPubMed
Mallinckrodt, C. H., Sanger, T. M., Dubé, S., DeBrota, D. J., Molenberghs, G., Carroll, R. J., … Tollefson, G. D. (2003). Assessing and interpreting treatment effects in longitudinal clinical trials with missing data. Biological Psychiatry, 53(8), 754760. https://doi.org/10.1016/S0006-3223(02)01867-X.CrossRefGoogle ScholarPubMed
McGarry, J. D., Robles-Valdes, C., & Foster, D. W. (1975). Role of carnitine in hepatic ketogenesis. Proceedings of the National Academy of Sciences, 72(11), 43854388. https://doi.org/10.1073/pnas.72.11.4385.CrossRefGoogle ScholarPubMed
Merritt, J. L. II, Norris, M., & Kanungo, S. (2018). Fatty acid oxidation disorders. Annals of Translational Medicine, 6(24), 473473. https://doi.org/10.21037/atm.2018.10.57.CrossRefGoogle ScholarPubMed
Mocking, R. J. T., Naviaux, J. C., Li, K., Wang, L., Monk, J. M., Bright, A. T., … Naviaux, R. K. (2021). Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence. Translational Psychiatry, 11(1), 37. https://doi.org/10.1038/s41398-020-01182-w.CrossRefGoogle ScholarPubMed
Moore, C. M., Christensen, J. D., Lafer, B., Fava, M., & Renshaw, P. F. (1997). Lower levels of nucleoside triphosphate in the basal ganglia of depressed subjects: A phosporous-31 magnetic resonance spectroscopy study. American Journal of Psychiatry, 154(1), 116118. https://doi.org/10.1176/ajp.154.1.116.Google ScholarPubMed
Mukerji, S. S., Misra, V., Lorenz, D. R., Chettimada, S., Keller, K., Letendre, S., … Gabuzda, D. (2021). Low neuroactive steroids identifies a biological subtype of depression in adults with human immunodeficiency virus on suppressive antiretroviral therapy. The Journal of Infectious Diseases, 223(9), 16011611. https://doi.org/10.1093/infdis/jiaa104.CrossRefGoogle ScholarPubMed
Nasca, C., Bigio, B., Lee, F. S., Young, S. P., Kautz, M. M., Albright, A., … Rasgon, N. (2018). Acetyl- l -carnitine deficiency in patients with major depressive disorder. Proceedings of the National Academy of Sciences, 115(34), 86278632. https://doi.org/10.1073/pnas.1801609115.CrossRefGoogle ScholarPubMed
Pu, J., Liu, Y., Zhang, H., Tian, L., Gui, S., Yu, Y., … Xie, P. (2021). An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder. Molecular Psychiatry, 26(8), 42654276. https://doi.org/10.1038/s41380-020-0645-4.CrossRefGoogle ScholarPubMed
Reuter, S. E., & Evans, A. M. (2012). Carnitine and acylcarnitines. Clinical Pharmacokinetics, 51(9), 553572. https://doi.org/10.1007/BF03261931.CrossRefGoogle ScholarPubMed
Rotroff, D. M., Corum, D. G., Motsinger-Reif, A., Fiehn, O., Bottrel, N., Drevets, W. C., … Kaddurah-Daouk, R. (2016). Metabolomic signatures of drug response phenotypes for ketamine and esketamine in subjects with refractory major depressive disorder: New mechanistic insights for rapid acting antidepressants. Translational Psychiatry, 6(9), e894e894. https://doi.org/10.1038/tp.2016.145.CrossRefGoogle ScholarPubMed
Rush, A. J., Kraemer, H. C., Sackeim, H. A., Fava, M., Trivedi, M. H., Frank, E., … Schatzberg, A. F. (2006). Report by the ACNP task force on response and remission in major depressive disorder. Neuropsychopharmacology, 31(9), 18411853. https://doi.org/10.1038/sj.npp.1301131.CrossRefGoogle ScholarPubMed
Rush, A. J., Trivedi, M. H., Ibrahim, H. M., Carmody, T. J., Arnow, B., Klein, D. N., … Keller, M. B. (2003). The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): A psychometric evaluation in patients with chronic major depression. Biological Psychiatry, 54(5), 573583. https://doi.org/10.1016/S0006-3223(02)01866-8.CrossRefGoogle ScholarPubMed
Saiki, S., Hatano, T., Fujimaki, M., Ishikawa, K.-I., Mori, A., Oji, Y., … Hattori, N. (2017). Decreased long-chain acylcarnitines from insufficient β-oxidation as potential early diagnostic markers for Parkinson's disease. Scientific Reports, 7(1), 7328. https://doi.org/10.1038/s41598-017-06767-y.CrossRefGoogle ScholarPubMed
Souza, D. G., Almeida, R. F., Souza, D. O., & Zimmer, E. R. (2019). The astrocyte biochemistry. Seminars in Cell & Developmental Biology, 95, 142150. https://doi.org/10.1016/j.semcdb.2019.04.002.CrossRefGoogle ScholarPubMed
Trabado, S., Al-Salameh, A., Croixmarie, V., Masson, P., Corruble, E., Fève, B., … Chanson, P. (2017). The human plasma-metabolome: Reference values in 800 French healthy volunteers; impact of cholesterol, gender and age. PLOS One, 12(3), e0173615. https://doi.org/10.1371/journal.pone.0173615.CrossRefGoogle ScholarPubMed
Trivedi, M. H., Rush, A. J., Wisniewski, S. R., Nierenberg, A. A., Warden, D., & Ritz, L., … STAR*D Study Team. (2006). Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: Implications for clinical practice. American Journal of Psychiatry, 163(1), 2840. https://doi.org/10.1176/appi.ajp.163.1.28.CrossRefGoogle Scholar
Warren, B. E., Lou, P.-H., Lucchinetti, E., Zhang, L., Clanachan, A. S., Affolter, A., … Lemieux, H. (2014). Early mitochondrial dysfunction in glycolytic muscle, but not oxidative muscle, of the fructose-fed insulin-resistant rat. American Journal of Physiology-Endocrinology and Metabolism, 306(6), E658E667. https://doi.org/10.1152/ajpendo.00511.2013.CrossRefGoogle Scholar
White, C. J., Lee, J., Choi, J., Chu, T., Scafidi, S., & Wolfgang, M. J. (2020). Determining the bioenergetic capacity for fatty acid oxidation in the mammalian nervous system. Molecular and Cellular Biology, 40(10), e00037–20. https://doi.org/10.1128/MCB.00037-20.CrossRefGoogle ScholarPubMed
Xie, X., Shen, Q., Yu, C., Xiao, Q., Zhou, J., Xiong, Z., … Fu, Z. (2020). Depression-like behaviors are accompanied by disrupted mitochondrial energy metabolism in chronic corticosterone-induced mice. The Journal of Steroid Biochemistry and Molecular Biology, 200, 105607. https://doi.org/10.1016/j.jsbmb.2020.105607.CrossRefGoogle ScholarPubMed
Xue, S., Zhou, C., Xue, F., Liu, L., Cai, Y., Luo, J., … Peng, Z. (2020). The impact of repetitive transcranial magnetic stimulation and fluoxetine on the brain lipidome in a rat model of chronic unpredictable stress. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 102, 109946. https://doi.org/10.1016/j.pnpbp.2020.109946.CrossRefGoogle Scholar
Yang, X., Sun, L., Zhao, A., Hu, X., Qing, Y., Jiang, J., … Wan, C. (2017). Serum fatty acid patterns in patients with schizophrenia: A targeted metabonomics study. Translational Psychiatry, 7(7), e1176e1176. https://doi.org/10.1038/tp.2017.152.CrossRefGoogle ScholarPubMed
Zacharias, H. U., Hertel, J., Johar, H., Pietzner, M., Lukaschek, K., Atasoy, S., … Ladwig, K.-H. (2021). A metabolome-wide association study in the general population reveals decreased levels of serum laurylcarnitine in people with depression. Molecular Psychiatry, 26, 73737383. https://doi.org/10.1038/s41380-021-01176-0.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Sociodemographic and clinical characteristics of healthy controls and depressed patients at baseline

Figure 1

Table 2. The 38 acylcarnitines studied

Figure 2

Figure 1. Plasma levels of acylcarnitines in healthy controls and in depressed patients during follow-up. Logistic regression adjusted for age, gender, BMI, HDRS score, total blood cholesterol, glycemia, and antidepressant class were performed for qualitative variables – Linear regression adjusted for age, gender, BMI, HDRS scores, total blood cholesterol, glycemia, and antidepressant class were performed for quantitative variables – MDE: Major depressive episode – M3: at 3 months – M6: at 6 months – Metabolite abbreviations and quantitative/qualitative variables are defined in Table 2 – : Statistically lower/decreased – : Statistically higher/increased – : No statistical difference – *: Significance after Bonferroni corrections (p < 0.00131) – **: p < 0.0001 – ***: p < 0.00001.

Figure 3

Figure 2. Correlation plot of acylcarnitines and depression severity in depressed patients. Blue represents positive correlations and red represents negative correlations – Acylcarnitine concentrations were log2 transformed – The first cluster (C3, C4, C4-OH, C5) was short-chain acylcarnitines – The second cluster (C6, C9, C10, C14:1, C16, C18, C18:1, C18:2) was medium- and long-chain acylcarnitines – The third cluster (HDRS-17, QIDS-SR) was scales of depression severity – Metabolite abbreviations are defined in Table 2 – MDE, Major depressive episode; HDRS-17, 17-item Hamilton Depression Rating Scale; QIDS-SR, Quick Inventory of Depressive Symptomatology-Self-Report.

Figure 4

Table 3. Mixed model analyses for repeated measures for plasma levels of acylcarnitines in depressed patients over time

Supplementary material: File

Ait Tayeb et al. supplementary material

Tables S1-S8 and Figures S1-S3

Download Ait Tayeb et al. supplementary material(File)
File 441.4 KB