Desipramine restores the alterations in circadian entrainment induced by prenatal exposure to glucocorticoids

Sex Differences in Long-term Outcome of Prenatal Exposure to Excess Glucocorticoids-Implications for Development of Psychiatric Disorders

Exposure to prenatal insults, such as excess glucocorticoids (GC), may lead to pathological outcomes, including neuropsychiatric disorders. The aim of the present study was to investigate the long-term effects of in utero exposure to the synthetic GC analog dexamethasone (Dex) in adult female offspring. We monitored spontaneous activity in the home cage under a constant 12 h/12 h light/dark cycle, as well as the changes following a 6-h advance of dark onset (phase shift). For comparison, we re-analysed data previously recorded in males. Dex-exposed females were spontaneously more active, and the activity onset re-entrained slower than in controls. In contrast, Dex-exposed males were less active, and the activity onset re-entrained faster than in controls. Following the phase shift, control females displayed a transient reorganisation of behaviour in light and virtually no change in dark, while Dex-exposed females showed limited variations from baseline in both light and dark, suggesting weaker photic entrainment. Next, we ran bulk RNA-sequencing in the suprachiasmatic nucleus (SCN) of Dex and control females. SPIA pathway analysis of ~ 2300 differentially expressed genes identified significantly downregulated dopamine signalling, and upregulated glutamate and GABA signalling. We selected a set of candidate genes matching the behaviour alterations and found consistent differential regulation for ~ 73% of tested genes in SCN and hippocampus tissue samples. Taken together, our data highlight sex differences in the outcome of prenatal exposure to excess GC in adult mice: in contrast to depression-like behaviour in males, the phenotype in females, defined by behaviour and differential gene expression, is consistent with ADHD models.

Integrating serum metabolomics and network analysis to explore the antidepressant activity of crocin in rats with chronic unexpected mild stress-induced depression

CONTEXT

Crocin exhibits anti-depressant properties. However, its underlying mechanisms and its relationship with metabolomics remain unclear.

OBJECTIVE

This study elucidates the mechanism of action and potential targets of crocin in treating chronic unexpected mild stress (CUMS)-induced depression in rats.

MATERIALS AND METHODS

Male Sprague-Dawley (SD) rats underwent 4 weeks of CUMS to establish the depression model. The normal control (distilled water), crocin (25 mg/kg), and fluoxetine (5.4 mg/kg) groups were orally administered for 4-weeks. Behavioural tests evaluated the effects of crocin, while liquid chromatography-mass spectrometry metabolomics identified differential metabolites and their associated metabolic pathways. Subsequently, network pharmacology was utilized to predict the targets of crocin.

RESULTS

Crocin significantly increased body weight (from 319.16 ± 4.84 g to 325.67 ± 2.84 g), sucrose preference (from 0.46 ± 0.09 to 0.70 ± 0.09), vertical activity (from 2.83 ± 1.94 to 8 ± 2.36), horizontal activity (from 1 ± 0.63 to 4.5 ± 3.08) and decreased immobilization time (from 13.16 ± 2.69 to 3.97 ± 3.00). Metabolomics analysis identified 7 metabolites and 5 associated metabolic pathways. From the combined analysis of network pharmacology and metabolomics, three targets (PRMT1, CYP3A4, and GLB1) are the overlapping targets and the two most important metabolic pathways are tryptophan metabolism and glycerolipid metabolism.

DISCUSSION AND CONCLUSIONS

This study provides insights into the antidepressant therapeutic effect of crocin and its underlying mechanisms. The findings contribute to a better understanding of the metabolic mechanism involved in the anti-depressant effect of crocin, establishing a strong foundation for future research in this area.

Patterns of activity correlate with symptom severity in major depressive disorder patients

Objective measures, such as activity monitoring, can potentially complement clinical assessment for psychiatric patients. Alterations in rest-activity patterns are commonly encountered in patients with major depressive disorder. The aim of this study was to investigate whether features of activity patterns correlate with severity of depression symptoms (evaluated by Montgomery-Åsberg Rating Scale (MADRS) for depression). We used actigraphy recordings collected during ongoing major depressive episodes from patients not undergoing any antidepressant treatment. The recordings were acquired from two independent studies using different actigraphy systems. Data was quality-controlled and pre-processed for feature extraction following uniform procedures. We trained multiple regression models to predict MADRS score from features of activity patterns using brute-force and semi-supervised machine learning algorithms. The models were filtered based on the precision and the accuracy of fitting on training dataset before undergoing external validation on an independent dataset. The features enriched in the models surviving external validation point to high depressive symptom severity being associated with less complex activity patterns and stronger coupling to external circadian entrainers. Our results bring proof-of-concept evidence that activity patterns correlate with severity of depressive symptoms and suggest that actigraphy recordings may be a useful tool for individual evaluation of patients with major depressive disorder.

Antidepressants and Circadian Rhythm: Exploring Their Bidirectional Interaction for the Treatment of Depression

Scientific evidence that circadian rhythms affect pharmacokinetics and pharmacodynamics has highlighted the importance of drug dosing-time. Circadian oscillations alter drug absorption, distribution, metabolism, and excretion (ADME) as well as intracellular signaling systems, target molecules (e.g., receptors, transporters, and enzymes), and gene transcription. Although several antidepressant drugs are clinically available, less than 50% of depressed patients respond to first-line pharmacological treatments. Chronotherapeutic approaches to enhance the effectiveness of antidepressants are not completely known. Even so, experimental results found until this day suggest a positive influence of drug dosing-time on the efficacy of depression therapy. On the other hand, antidepressants have also demonstrated to modulate circadian rhythmicity and sleep-wake cycles. This review aims to evidence the potential of chronotherapy to improve the efficacy and/or safety of antidepressants. It includes pre-clinical and clinical studies that demonstrate the relevance of determining the most appropriate time of administration for antidepressant drugs. In parallel, their positive influence on the resynchronization of disrupted circadian rhythms is also herein discussed. It is expected that this review will promote the investigation of chronotherapy for the treatment of depression, contribute to a better understanding of the relationship between antidepressants and circadian rhythms, and consequently promote the development of new therapeutics.

Identification of Hub Genes Related to Alzheimer's Disease and Major Depressive Disorder

BackgroundAlthough many studies reported a close relationship between depression and Alzheimer's disease (AD), the underlying pathophysiological mechanism remains unclear. The present study aimed to investigate the mechanism of AD and major depressive disorder (MDD). Method: The datasets were downloaded from the Gene Expression Omnibus. After screening differentially expressed genes (DEGs), gene ontology and pathway analysis were performed and protein-protein interaction, TF-target gene, and miRNA-target gene networks were established. Results: 171 DEGs of AD-related datasets and 79 DEGs shared by AD and MDD were detected. Functional analysis revealed that AD and MDD common genes were significantly enriched in circadian entrainment and long-term depression signaling pathways. Five hub genes were identified after construction of networks and validation of hub gene signatures. In conclusion, DYNC1H1, MAPRE3, TTBK2, ITGB1, and WASL may be potential targets for the diagnosis and treatment of AD and MDD.