Associations between disordered gut microbiota and changes of neurotransmitters and short-chain fatty acids in depressed mice

Wu, Min; Tian, Tian; Mao, Qiang; Zou, Tao; Zhou, Chanjuan; Xie, Jing; Chen, Jianjun

doi:10.1038/s41398-020-01038-3

Cited by 112 publications

(91 citation statements)

References 43 publications

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“…Although other researchers and we have done many works, the treatment and diagnosis of depression is still in the exploratory stage. [7][8][9][10] The diagnosis of depression in stroke survivors is still based on the subjective identification of symptom clusters, which often causes a misdiagnosis or under-diagnosis. 11 To solve this problem, many works have been done to identify PSDrelated biomarkers.…”

Section: Introductionmentioning

confidence: 99%

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

Jin¹,

Lv²,

Li³

et al. 2021

NDT

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Background Post-stroke depression (PSD) is a major complication in stroke survivors, especially in elderly stroke survivors. But there are still no objective methods to diagnose depression in elderly stroke survivors. Thus, this study was conducted to identify potential biomarkers for diagnosing elderly PSD subjects. Methods Elderly (60 years or older) stroke survivors with depression were assigned into the PSD group, and elderly stroke survivors without depression and elderly healthy controls (HCs) were assigned into the non-depressed group. Urinary metabolite signatures obtained from gas chromatography-mass spectrometry (GC-MS)-based metabolomic platform were collected. Both univariate and multivariate statistical analysis were used to find the differential urinary metabolites between the two groups. Results The 78 elderly HCs, 122 elderly stroke survivors without depression and 124 elderly PSD subjects were included. A set of 13 differential urinary metabolites responsible for distinguishing PSD subjects from non-depressed subjects were found. The Phenylalanine, tyrosine and tryptophan biosynthesis, Phenylalanine metabolism and Galactose metabolism were found to be significantly changed in elderly PSD subjects. The phenylalanine was significantly negatively correlated with age and depressive symptoms. Meanwhile, a biomarker panel consisting of 3-hydroxyphenylacetic acid, tyrosine, phenylalanine, sucrose, palmitic acid, glyceric acid, azelaic acid and α-aminobutyric acid was identified. Conclusion These results provided candidate molecules for developing objective methods to diagnose depression in elderly stroke survivors, suggested that taking supplements of phenylalanine might be an effective method to prevent depression in elderly stroke survivors, and would be helpful for future revealing the pathophysiological mechanism of PSD.

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Section: Introductionmentioning

confidence: 99%

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

Jin¹,

Lv²,

Li³

et al. 2021

NDT

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“… 1 Nowadays, the pathogenesis of MDD is still unknown, although many theories have been developed to reveal the underline biological mechanisms of this disease. 2–4 What is worse, MDD can significantly increase the risk of suicide if it was not timely and effectively treated. Both MDD and suicide are major health hazards, which bring big economic burden to individual and society.…”

Section: Introductionmentioning

confidence: 99%

Potential Biomarkers for Diagnosing Major Depressive Disorder Patients with Suicidal Ideation

Bai

Fang

Xie

et al. 2021

JIR

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Background Major depressive disorder (MDD) and suicide are two major health problems, but there are still no objective methods to diagnose MDD or suicidal ideation (SI). This study was conducted to identify potential biomarkers for diagnosing MDD patients with SI. Methods First-episode drug-naïve MDD patients with SI and demographics-matched healthy controls (HCs) were recruited. First-episode drug-naïve MDD patients without SI were also included. The serum lipids, C-reactive protein (CRP), transferring (TRSF), homocysteine (HCY) and alpha 1-antitrypsin (AAT) in serum were detected. The univariate and multivariate statistical analyses were used to identify and validate the potential biomarkers. Results The 86 HCs, 53 MDD patients with SI and 20 MDD patients without SI were included in this study. Four potential biomarkers were identified: AAT, TRSF, high-density lipoprotein cholesterol (HDLC), and apolipoprotein A1 (APOA1). After one month treatment, the levels of AAT and APOA1 were significantly improved. The panel consisting of these potential biomarkers had an excellent diagnostic performance, yielding an area under the ROC curve (AUC) of 0.994 and 0.990 in the training and testing set, respectively. Moreover, this panel could effectively distinguish MDD patients with SI from MDD patients without SI (AUC=0.928). Conclusion These results showed that these potential biomarkers could facilitate the development of an objective method for diagnosing MDD patients with SI, and the decreased AAT levels in MDD patients might lead to the appearance of SI by resulting in the elevated inflammation.

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“…Previous studies reported that the disturbances in leukocyte function and/or leukocyte number could be potential biomarkers of MDD [7,8]. Our previous animal and human studies found that the disordered gut microbiota might have a causal role in the development of MDD [9,10]. These theories have made a great contribution to the prevention and treatment of MDD.…”

Section: Introductionmentioning

confidence: 91%

“…Many theories have been developed to explain the pathogenesis of MDD, such as neurotransmission de ciency [6], oxidative stress and immune system dysfunction [7,8] and gut microbiota alternation [9][10][11][12]. Luscher et al proposed the central and causal role of GABAergic de cits in the etiology of MDD [6].…”

Section: Introductionmentioning

confidence: 99%

Absence of gut microbiota affects lipid metabolism in the prefrontal cortex of mice

Chen

Xie

Zeng

et al. 2021

Preprint

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Despite decades of intensive research on major depressive disorder (MDD), the pathogenesis of MDD is still unclear and the objectively diagnostic method remains unavailable. Therefore, we conducted this study to assess whether alpha 1-antitrypsin (AAT) could be a potential biomarker for diagnosing MDD. Here, the levels of AAT, liver function-related indicators, renal function-related indicators, blood lipids-related indicators, high sensitivity C-reactive protein, homocysteine and transferrin were detected. The orthogonal partial least-squares discriminant analysis (OPLS-DA) was used to find the differential variables, Random Forest was used to identify the simplified biomarker panel, and receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the identified panel. In total, 86 MDD patients and 99 healthy controls (HCs) were recruited. Finally, we found nine differential variables between MDD patients and HCs, and a potential biomarker panel consisting of AAT, albumin (ALB) and apolipoprotein A1 (APOA) was identified. This panel could effectively separate MDD patients from HCs in two independent samples sets. The level of AAT was significantly negatively correlated with HDRS score and improved after antidepressant treatment. Meanwhile, MDD patients with suicide idea or behavior had significantly lower AAT levels compared to MDD patients without suicide idea or behavior. Our results suggested that AAT held the promise to become a potential biomarker for diagnosing MDD, and also might be a potential novel therapeutic target for MDD.

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Associations between disordered gut microbiota and changes of neurotransmitters and short-chain fatty acids in depressed mice

Cited by 112 publications

References 43 publications

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

Potential Biomarkers for Diagnosing Major Depressive Disorder Patients with Suicidal Ideation

Absence of gut microbiota affects lipid metabolism in the prefrontal cortex of mice

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