Carnitine and Depression

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

Background

Acylcarnitines (ACs) are involved in bioenergetics processes that may play a role in the pathophysiology of depression. Studies linking AC levels to depression are few and provide mixed findings. We examined the association of circulating ACs levels with Major Depressive Disorder (MDD) diagnosis, overall depression severity and specific symptom profiles.

Methods

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. Overall depression severity as well as atypical/energy-related (AES), anhedonic and melancholic symptom profiles were derived from the Inventory of Depressive Symptomatology.

Results

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). 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. Results were confirmed in analyses pooling data with an additional internal replication sample from the same subjects measured at 6-year follow-up (totaling 4195 observations).

Conclusions

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. Cellular metabolic dysfunctions may represent a key pathway in depression pathophysiology potentially accessible through AC metabolism.

Untargeted Plasma Metabolomic Profiling in Patients with Depressive Disorders: A Preliminary Study

Depressive disorder is a multifactorial disease that is based on dysfunctions in mental and biological processes. The search for biomarkers can improve its diagnosis, personalize therapy, and lead to a deep understanding of the biochemical processes underlying depression. The purpose of this work was a metabolomic analysis of blood serum to classify patients with depressive disorders and healthy individuals using Compound Discoverer software. Using high-resolution mass spectrometry, blood plasma samples from 60 people were analyzed, of which 30 were included in a comparison group (healthy donors), and 30 were patients with a depressive episode (F32.11) and recurrent depressive disorder (F33.11). Differences between patient and control groups were identified using the built-in utilities in Compound Discoverer software. Compounds were identified by their accurate mass and fragment patterns using the mzCloud database and tentatively identified by their exact mass using the ChemSpider search engine and the KEGG, ChEBI, FDA UNII-NLM, Human Metabolome and LipidMAPS databases. We identified 18 metabolites that could divide patients with depressive disorders from healthy donors. Of these, only two compounds were tentatively identified using the mzCloud database (betaine and piperine) based on their fragmentation spectra. For three compounds ((4S,5S,8S,10R)-4,5,8-trihydroxy-10-methyl-3,4,5,8,9,10-hexahydro-2H-oxecin-2-one, (2E,4E)-N-(2-hydroxy-2-methylpropyl)-2,4-tetradecadienamide and 17α-methyl-androstan-3-hydroxyimine-17β-ol), matches were found in the mzCloud database but with low score, which could not serve as reliable evidence of their structure. Another 13 compounds were identified by their exact mass in the ChemSpider database, 9 (g-butyrobetaine, 6-diazonio-5-oxo-L-norleucine, 11-aminoundecanoic acid, methyl N-acetyl-2-diazonionorleucinate, glycyl-glycyl-argininal, dilaurylmethylamine, 12-ketodeoxycholic acid, dicetylamine, 1-linoleoyl-2-hydroxy-sn-glycero-3-PC) had only molecular formulas proposed, and 4 were unidentified. Thus, the use of Compound Discoverer software alone was not sufficient to identify all revealed metabolites. Nevertheless, the combination of the found metabolites made it possible to divide patients with depressive disorders from healthy donors.

Conceptual foundations of acetylcarnitine supplementation in neuropsychiatric long COVID syndrome: a narrative review

Post-acute sequelae of COVID-19 can present as multi-organ pathology, with neuropsychiatric symptoms being the most common symptom complex, characterizing long COVID as a syndrome with a significant disease burden for affected individuals. Several typical symptoms of long COVID, such as fatigue, depressive symptoms and cognitive impairment, are also key features of other psychiatric disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and major depressive disorder (MDD). However, clinically successful treatment strategies are still lacking and are often inspired by treatment options for diseases with similar clinical presentations, such as ME/CFS. Acetylcarnitine, the shortest metabolite of a class of fatty acid metabolites called acylcarnitines and one of the most abundant blood metabolites in humans can be used as a dietary/nutritional supplement with proven clinical efficacy in the treatment of MDD, ME/CFS and other neuropsychiatric disorders. Basic research in recent decades has established acylcarnitines in general, and acetylcarnitine in particular, as important regulators and indicators of mitochondrial function and other physiological processes such as neuroinflammation and energy production pathways. In this review, we will compare the clinical basis of neuropsychiatric long COVID with other fatigue-associated diseases. We will also review common molecular disease mechanisms associated with altered acetylcarnitine metabolism and the potential of acetylcarnitine to interfere with these as a therapeutic agent. Finally, we will review the current evidence for acetylcarnitine as a supplement in the treatment of fatigue-associated diseases and propose future research strategies to investigate the potential of acetylcarnitine as a treatment option for long COVID.

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Venlafaxine's effect on resilience to stress is associated with a shift in the balance between glucose and fatty acid utilization

Brain metabolism is a fundamental process involved in the proper development of the central nervous system and in the maintenance of the main higher functions in humans. As consequence, energy metabolism imbalance has been commonly associated to several mental disorders, including depression. Here, by employing a metabolomic approach, we aimed to establish if differences in energy metabolite concentration may underlie the vulnerability and resilience in an animal model of mood disorder named chronic mild stress (CMS) paradigm. In addition, we have investigated the possibility that modulation of metabolite concentration may represent a pharmacological target for depression by testing whether repeated treatment with the antidepressant venlafaxine may normalize the pathological phenotype by acting at metabolic level. The analyses were conducted in the ventral hippocampus (vHip) for its key role in the modulation of anhedonia, a core symptom of patients affected by depression. Interestingly, we showed that a shift from glycolysis to beta oxidation seems to be responsible for the vulnerability to chronic stress and that vHip metabolism contributes to the ability of the antidepressant venlafaxine to normalize the pathological phenotype, as shown by the reversal of the changes observed in specific metabolites. These findings may provide novel perspectives on metabolic changes that could serve as diagnostic markers and preventive strategies for the early detection and treatment of depression as well as for the identification of potential drug targets.

Role of mucin glycosylation in the gut microbiota-brain axis of core 3 O-glycan deficient mice

Alterations in intestinal mucin glycosylation have been associated with increased intestinal permeability and sensitivity to inflammation and infection. Here, we used mice lacking core 3-derived O-glycans (C3GnT-/-) to investigate the effect of impaired mucin glycosylation in the gut-brain axis. C3GnT-/- mice showed altered microbial metabolites in the caecum associated with brain function such as dimethylglycine and N-acetyl-L-tyrosine profiles as compared to C3GnT+/+ littermates. In the brain, polysialylated-neural cell adhesion molecule (PSA-NCAM)-positive granule cells showed an aberrant phenotype in the dentate gyrus of C3GnT-/- mice. This was accompanied by a trend towards decreased expression levels of PSA as well as ZO-1 and occludin as compared to C3GnT+/+. Behavioural studies showed a decrease in the recognition memory of C3GnT-/- mice as compared to C3GnT+/+ mice. Combined, these results support the role of mucin O-glycosylation in the gut in potentially influencing brain function which may be facilitated by the passage of microbial metabolites through an impaired gut barrier.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

Metabolic Alterations and Related Biological Functions of Post-Stroke Depression in Ischemic Stroke Patients

Background

Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. However, the underlying mechanisms of PSD remain ambiguous, and no objective diagnosis tool is available to diagnose PSD. Previous metabolomic studies on PSD included patients with ischemic and hemorrhagic stroke indiscriminately, which is not conducive to elucidating and predicting the occurrence of PSD. The aim of this study is to elucidate the pathogenesis of PSD and provide potential diagnostic markers for PSD in ischemic stroke patients.

Methods

In total, 51 ischemic stroke patients at 2 weeks were included in this study. Those with depressive symptoms were assigned to the PSD group, while the others were assigned to the non-PSD group. Plasma metabolomics based on liquid chromatography-mass spectrometry (LC-MS) was performed to explore the differential plasma metabolites between the PSD and non-PSD groups.

Results

Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) showed significant metabolic alterations between PSD patients and non-PSD patients. In total, 41 differential metabolites were screened out, mainly including phosphatidylcholines (PCs), L-carnitine and acyl carnitines, succinic acid, pyruvic acid and L-lactic acid. Metabolite-related pathway analysis revealed that alanine, aspartate and glutamate metabolism, glycerophospholipid metabolism and the citrate cycle (TCA cycle) may contribute to the pathogenesis of PSD. A panel of three signature metabolites [PC(22:5(7Z,10Z,13Z,16Z,19Z)/15:0), LysoPA(18:1(9Z)/0:0) and 1,5-anhydrosorbitol] was determined as potential biomarkers for PSD in ischemic stroke patients.

Conclusion

These findings are conducive to providing new insights into the pathogenesis of PSD and developing objective diagnostic tools for PSD in ischemic stroke patients.

Effects of carnitine on glucose and lipid metabolic profiles and fertility outcomes in women with polycystic ovary syndrome: A systematic review and meta-analysis

OBJECTIVES

To quantify the effect of carnitine on glucose and lipid metabolic profiles and fertility outcomes in women with Polycystic ovary syndrome (PCOS).

DESIGN

A systematic review and meta-analysis were conducted.

PATIENTS

Women with PCOS diagnosed by Rotterdam or Androgen Excess Society (AES) criteria and taking carnitine supplement were assessment.

MEASUREMENTS

Fertility outcomes (ovulation, clinical pregnancy, live birth, and miscarriage), lipid parameters (BMI, triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein), fasting glucose and insulin, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR).

RESULTS

In total, 839 participants were included in this analysis. The dosage of carnitine and treatment duration reported by studies varied from 250 mg to 3000 mg daily and 84 to 90 days, respectively. The publication bias was absent. Compared with placebo, carnitine significantly improved ovulation rates (RR 3.42, 95% CI 2.39 to 4.89, I2 = 0%) and pregnancy rates (RR 11.05, 95% CI 1.21 to 100.58, I2 = 79%). None of included studies reported live birth. After treatment, carnitine resulted in significant reductions relative to baseline in body mass index (BMI, MD -0.93 kg/m2, 95% CI -1.15 to -0.70, I2 = 55.0%), insulin levels (MD -2.47 mIU/L, 95% CI -4.49 to -0.45, I2 = 0%) and the Homeostasis Model Assessment index (MD -0.67, 95% CI -1.20 to -0.14, I2 = 0%) than placebo, but not for lipid profiles including triglyceride, total cholesterol, and low-density lipoprotein.

CONCLUSION

With the available literature, carnitine seems to improve ovulation and clinical pregnancy and insulin resistance, BMI in women with PCOS. These effects are warranted to be further validated, due to insufficient statistical power.