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Li H, Seugnet L. Decoding the nexus: branched-chain amino acids and their connection with sleep, circadian rhythms, and cardiometabolic health. Neural Regen Res 2025; 20:1350-1363. [PMID: 39075896 DOI: 10.4103/nrr.nrr-d-23-02020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 05/12/2024] [Indexed: 07/31/2024] Open
Abstract
The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and, either directly or indirectly, overall body health, encompassing metabolic and cardiovascular well-being. Given the heightened metabolic activity of the brain, there exists a considerable demand for nutrients in comparison to other organs. Among these, the branched-chain amino acids, comprising leucine, isoleucine, and valine, display distinctive significance, from their contribution to protein structure to their involvement in overall metabolism, especially in cerebral processes. Among the first amino acids that are released into circulation post-food intake, branched-chain amino acids assume a pivotal role in the regulation of protein synthesis, modulating insulin secretion and the amino acid sensing pathway of target of rapamycin. Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors, competing for a shared transporter. Beyond their involvement in protein synthesis, these amino acids contribute to the metabolic cycles of γ-aminobutyric acid and glutamate, as well as energy metabolism. Notably, they impact GABAergic neurons and the excitation/inhibition balance. The rhythmicity of branched-chain amino acids in plasma concentrations, observed over a 24-hour cycle and conserved in rodent models, is under circadian clock control. The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood. Disturbed sleep, obesity, diabetes, and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics. The mechanisms driving these effects are currently the focal point of ongoing research efforts, since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies. In this context, the Drosophila model, though underutilized, holds promise in shedding new light on these mechanisms. Initial findings indicate its potential to introduce novel concepts, particularly in elucidating the intricate connections between the circadian clock, sleep/wake, and metabolism. Consequently, the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle. They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health, paving the way for potential therapeutic interventions.
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Affiliation(s)
- Hui Li
- Department of Neurology, Xijing Hospital, Xi'an, Shaanxi Province, China
| | - Laurent Seugnet
- Centre de Recherche en Neurosciences de Lyon, Integrated Physiology of the Brain Arousal Systems (WAKING), Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR 5292, Bron, France
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Zhang MY, Yin C, Ding L, Cheng L, Lv Q, Wang P, Zhang SB, You QY. Mechanism of Panax notoginseng saponins in improving cognitive impairment induced by chronic sleep deprivation based on the integrative analysis of serum metabolomics and network pharmacology. JOURNAL OF ETHNOPHARMACOLOGY 2024:118988. [PMID: 39447711 DOI: 10.1016/j.jep.2024.118988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2024] [Revised: 10/21/2024] [Accepted: 10/22/2024] [Indexed: 10/26/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Panax notoginseng saponin (PNS) has a variety of biological activities, such as improvement of myocardial ischemia, improvement of learning and memory, hypolipidemia, and immunomodulation. However, its protective mechanism on the central nervous system (CNS) is not clear. AIM OF THE STUDY The present study initially evaluated the possible mechanism of PNS to improve cognitive dysfunction due to chronic sleep deprivation (CSD). MATERIALS AND METHODS In the present study, we used a modified multi-platform aquatic environment sleep deprivation method to induce a cognitively impaired rat model, and explored the mechanism of action of PNS by integrating serum metabolomics and network pharmacology, which was further verified by molecular docking and experiments. RESULTS The results showed that PNS significantly shortened the escape latency, increased the target quadrant time and the number of traversing platforms, and attenuated the inflammatory damage in the hippocampal Cornu Ammonis 1 (CA1) region in CSD rats. The non-targeted metabolomics results indicated that 35 biomarkers significantly altered following PNS therapy intervention, with metabolic pathways enriched for the effects of One carbon pool by folate, Riboflavin metabolism, Glycerophospholipid metabolism, Sphingolipid metabolism, Glycerolipid metabolism, Arachidonic acid metabolism, and Tryptophan metabolism. In addition, network pharmacology identified 234 potential targets for PNS intervention in CSD with cognitive impairment. Metabolite-response-enzyme-gene network was constructed by MetaScape and matched with the network pharmacology results to identify a total of five shared targets (LPL, GPAM, HSD11B1, HSD11B2, and SULT2A1) and two metabolic pathways (Sphingolipid metabolism and Steroid hormone biosynthesis). The results of molecular docking revealed that the five active ingredients had good binding ability with the five core targets. qPCR analysis confirmed the ability of PNS to modulate the above five targets. CONCLUSIONS The combination of metabolomics and network analysis provides a scientific basis for promoting the clinical application of PNS in cognitive impairment.
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Affiliation(s)
- Mei-Ya Zhang
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China; Hubei Shizhen Laboratory, Hubei University of Chinese Medicine, Wuhan 430065, China; Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Chao Yin
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China; Hubei Shizhen Laboratory, Hubei University of Chinese Medicine, Wuhan 430065, China; Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Li Ding
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China; Hubei Shizhen Laboratory, Hubei University of Chinese Medicine, Wuhan 430065, China; Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Li Cheng
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Qing Lv
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Ping Wang
- Hubei Shizhen Laboratory, Hubei University of Chinese Medicine, Wuhan 430065, China; Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Shun-Bo Zhang
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China; Hubei Shizhen Laboratory, Hubei University of Chinese Medicine, Wuhan 430065, China; Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Hubei University of Chinese Medicine, Wuhan 430065, China.
| | - Qiu-Yun You
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China; Hubei Shizhen Laboratory, Hubei University of Chinese Medicine, Wuhan 430065, China; Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Hubei University of Chinese Medicine, Wuhan 430065, China.
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Chen J, Qiu Y, Guo J, Shan L, Chen G, Wang F, Wang W. Determining of 18 amino acids in plasma of pregnant women with sleep disorders by UHPLC-MS/MS. J Chromatogr B Analyt Technol Biomed Life Sci 2024; 1241:124163. [PMID: 38815356 DOI: 10.1016/j.jchromb.2024.124163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 05/10/2024] [Accepted: 05/18/2024] [Indexed: 06/01/2024]
Abstract
Many pregnant women experience sleep disorders, and amino acid levels could play a crucial role in affecting maternal sleep. To explore this potential relationship, an accurate and effective UHPLC-MS/MS method has been developed to monitor 18 amino acids in the plasma samples of pregnant women. This method aims to assess how plasma amino acid levels might be linked to sleep disorders during pregnancy. Plasma samples were precipitated with acetonitrile containing 0.2% formic acid. We used 5% seralbumin as the surrogate matrix to establish quantitative curves for amino acid determination in human plasma. The method was validated in both the surrogate matrix and human plasma. The optimized UHPLC-MS/MS method was validated, showing that that the analytes had comparable recovery and negligible matrix effects in both 5% seralbumin and human plasma. The linearity, lower limit of quantification, precision, accuracy, and stability all met the acceptance criteria. The validated method was successfully applied to determination of the plasma levels of 18 amino acids in pregnant women with or without sleep disorders, indicating that alanine, lysine, tryptophan, glutamic acid, and phenylalanine levels had significant changes which may be related to sleep disorders during early pregnancy. An accurate, reliable, and efficient UHPLC-MS/MS method was successfully developed and support to find the specific amino acids as potential biomarkers for sleep disorders in pregnant women.
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Affiliation(s)
- Jindong Chen
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China
| | - Yifan Qiu
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China
| | - Jing Guo
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China
| | - Ligang Shan
- Department of Anesthesiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China
| | - Guangxue Chen
- Department of Gynaecology and Obstetrics, Beijing Jishuitan Hospital, Beijing102208, China
| | - Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing 100096, China.
| | - Wenyan Wang
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China.
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Yan H, Li G, Zhang X, Zhang C, Li M, Qiu Y, Sun W, Dong Y, Li S, Li J. Targeted metabolomics-based understanding of the sleep disturbances in drug-naïve patients with schizophrenia. BMC Psychiatry 2024; 24:355. [PMID: 38741058 DOI: 10.1186/s12888-024-05805-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Sleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia. METHODS Plasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia. RESULTS 16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p<0.001), the butanoate metabolism (Impact: 0.032, p=0.008), and the sphingolipid metabolism (Impact: 0.270, p=0.104) were identified as metabolic pathways associated with sleep disturbances in drug-naïve patients with schizophrenia. CONCLUSIONS Our study identified 16 characteristic metabolites (mainly lipids) and 3 metabolic pathways related to sleep disturbances in drug-naïve schizophrenia. The detection of these distinct metabolites provide valuable insights into the underlying biological mechanisms associated with sleep disturbances in schizophrenia.
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Affiliation(s)
- Huiming Yan
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Gang Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
- Chifeng Anding Hospital, NO.18 Gongger Street, Hongshan District, Chifeng City, 024000, Inner Mongolia Autonomous Region, China
| | - Xue Zhang
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
- Chifeng Anding Hospital, NO.18 Gongger Street, Hongshan District, Chifeng City, 024000, Inner Mongolia Autonomous Region, China
| | - Chuhao Zhang
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Meijuan Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Yuying Qiu
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Wei Sun
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Yeqing Dong
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Shen Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China.
| | - Jie Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China.
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Zhan Q, Wang L, Liu N, Yuan Y, Deng L, Ding Y, Wang F, Zhou J, Xie L. Serum metabolomics study of narcolepsy type 1 based on ultra-performance liquid chromatography-tandem mass spectrometry. Amino Acids 2023; 55:1247-1259. [PMID: 37689600 PMCID: PMC10689557 DOI: 10.1007/s00726-023-03315-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 08/07/2023] [Indexed: 09/11/2023]
Abstract
Narcolepsy is a chronic and underrecognized sleep disorder characterized by excessive daytime sleepiness and cataplexy. Furthermore, narcolepsy type 1 (NT1) has serious negative impacts on an individual's health, society, and the economy. Currently, many sleep centers lack the means to measure orexin levels in the cerebrospinal fluid. We aimed to analyze the characteristics of metabolite changes in patients with NT1, measured by ultra-performance liquid chromatography-tandem mass spectrometry. A principal component analysis (PCA), an orthogonal partial least square discriminant analysis (OPLS-DA), t tests, and volcano plots were used to construct a model of abnormal metabolic pathways in narcolepsy. We identified molecular changes in serum specimens from narcolepsy patients and compared them with control groups, including dehydroepiandrosterone, epinephrine, N-methyl-D-aspartic acid, and other metabolites, based on an OPLS-loading plot analysis. Nine metabolites yielded an area under the receiver operating curve > 0.75. Meanwhile, seven abnormal metabolic pathways were correlated with differential metabolites, such as metabolic pathways; neuroactive ligand‒receptor interaction; and glycine, serine, and threonine metabolism. To our knowledge, this is the first study to reveal the characteristic metabolite changes in sera from NT1 patients for the selection of potential blood biomarkers and the elucidation of NT1 pathogenesis.
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Affiliation(s)
- Qingqing Zhan
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Lili Wang
- Institute of Neuroscience, School of Basic Medical Sciences, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China
| | - Nan Liu
- Institute of Neuroscience, School of Basic Medical Sciences, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China
| | - Yuqing Yuan
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Liying Deng
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Yongmin Ding
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Fen Wang
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Jian Zhou
- Institute of Neuroscience, School of Basic Medical Sciences, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China.
| | - Liang Xie
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China.
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Liu D, Wang Q, Li Y, Yuan Z, Liu Z, Guo J, Li X, Zhang W, Tao Y, Mei J. Fructus gardeniae ameliorates anxiety-like behaviors induced by sleep deprivation via regulating hippocampal metabolomics and gut microbiota. Front Cell Infect Microbiol 2023; 13:1167312. [PMID: 37377643 PMCID: PMC10291143 DOI: 10.3389/fcimb.2023.1167312] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023] Open
Abstract
Fructus gardeniae (FG) is a traditional Chinese medicine and health food for thousands of years of application throughout Chinese history and is still widely used in clinical Chinese medicine. FG has a beneficial impact on anxiety, depression, insomnia, and psychiatric disorders; however, its mechanism of action requires further investigation. This study aimed to investigate the effects and mechanisms of FG on sleep deprivation (SD)-induced anxiety-like behavior in rats. A model of SD-induced anxiety-like behavior in rats was established by intraperitoneal injection of p-chlorophenylalanine (PCPA). This was accompanied by neuroinflammation and metabolic abnormalities in the hippocampus and disturbance of intestinal microbiota. However reduced SD-induced anxiety-like behavior and decreased levels of pro-inflammatory cytokines including TNF-α and IL-1β were observed in the hippocampus of rats after 7 days of FG intervention. In addition, metabolomic analysis demonstrated that FG was able to modulate levels of phosphatidylserine 18, Phosphatidylinositol 18, sn-glycero-3-phosphocholine, deoxyguanylic acid, xylose, betaine and other metabolites in the hippocampus. The main metabolic pathways of hippocampal metabolites after FG intervention involve carbon metabolism, glycolysis/gluconeogenesis, pentose phosphate, and glycerophospholipid metabolism. 16S rRNA sequencing illustrated that FG ameliorated the dysbiosis of gut microbiota in anxious rats, mainly increased the abundance of Muribaculaceae and Lactobacillus, and decreased the abundance of Lachnospiraceae_NK4A136_group. In addition, the correlation analysis demonstrated that there was a close relationship between hippocampal metabolites and intestinal microbiota. In conclusion, FG improved the anxiety behavior and inhibited of neuroinflammation in sleep-deprived rats, and the mechanism may be related to the FG regulation of hippocampal metabolites and intestinal microflora composition.
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Affiliation(s)
- Dong Liu
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- Department of Traditional Chinese Medicine, Hebei General Hospital, Shijiazhuang, Hebei, China
| | - Qianfei Wang
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Ying Li
- Department of Pharmacy, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Zhenshuang Yuan
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Zhiliang Liu
- Department of Emergency, Hebei Yiling Hospital, Shijiazhang, Hebei, China
| | - Junli Guo
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Xin Li
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Weichao Zhang
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Yulei Tao
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Jianqiang Mei
- Department of Emergency, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
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Caffeine-Induced Sleep Restriction Alters the Gut Microbiome and Fecal Metabolic Profiles in Mice. Int J Mol Sci 2022; 23:ijms232314837. [PMID: 36499163 PMCID: PMC9737546 DOI: 10.3390/ijms232314837] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 12/02/2022] Open
Abstract
Insufficient sleep is becoming increasingly common and contributes to many health issues. To combat sleepiness, caffeine is consumed daily worldwide. Thus, caffeine consumption and sleep restriction often occur in succession. The gut microbiome can be rapidly affected by either one's sleep status or caffeine intake, whereas the synergistic effects of a persistent caffeine-induced sleep restriction remain unclear. In this study, we investigated the impact of a chronic caffeine-induced sleep restriction on the gut microbiome and its metabolic profiles in mice. Our results revealed that the proportion of Firmicutes and Bacteroidetes was not altered, while the abundance of Proteobacteria and Actinobacteria was significantly decreased. In addition, the content of the lipids was abundant and significantly increased. A pathway analysis of the differential metabolites suggested that numerous metabolic pathways were affected, and the glycerophospholipid metabolism was most significantly altered. Combined analysis revealed that the metabolism was significantly affected by variations in the abundance and function of the intestinal microorganisms and was closely relevant to Proteobacteria and Actinobacteria. In conclusion, a long-term caffeine-induced sleep restriction affected the diversity and composition of the intestinal microbiota in mice, and substantially altered the metabolic profiles of the gut microbiome. This may represent a novel mechanism by which an unhealthy lifestyle such as mistimed coffee breaks lead to or exacerbates disease.
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Humer E, Pieh C, Brandmayr G. Metabolomics in Sleep, Insomnia and Sleep Apnea. Int J Mol Sci 2020; 21:ijms21197244. [PMID: 33008070 PMCID: PMC7583860 DOI: 10.3390/ijms21197244] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 09/28/2020] [Accepted: 09/29/2020] [Indexed: 02/06/2023] Open
Abstract
Sleep-wake disorders are highly prevalent disorders, which can lead to negative effects on cognitive, emotional and interpersonal functioning, and can cause maladaptive metabolic changes. Recent studies support the notion that metabolic processes correlate with sleep. The study of metabolite biomarkers (metabolomics) in a large-scale manner offers unique opportunities to provide insights into the pathology of diseases by revealing alterations in metabolic pathways. This review aims to summarize the status of metabolomic analyses-based knowledge on sleep disorders and to present knowledge in understanding the metabolic role of sleep in psychiatric disorders. Overall, findings suggest that sleep-wake disorders lead to pronounced alterations in specific metabolic pathways, which might contribute to the association of sleep disorders with other psychiatric disorders and medical conditions. These alterations are mainly related to changes in the metabolism of branched-chain amino acids, as well as glucose and lipid metabolism. In insomnia, alterations in branched-chain amino acid and glucose metabolism were shown among studies. In obstructive sleep apnea, biomarkers related to lipid metabolism seem to be of special importance. Future studies are needed to examine severity, subtypes and treatment of sleep-wake disorders in the context of metabolite levels.
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Affiliation(s)
- Elke Humer
- Department for Psychotherapy and Biopsychosocial Health, Danube University Krems, 3500 Krems, Austria;
- Correspondence: ; Tel.: +43-273-2893-2676
| | - Christoph Pieh
- Department for Psychotherapy and Biopsychosocial Health, Danube University Krems, 3500 Krems, Austria;
| | - Georg Brandmayr
- Section for Artificial Intelligence and Decision Support, Medical University of Vienna, 1090 Vienna, Austria;
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Zhang J, Gao Y, Guo H, Ding Y, Ren W. Comparative metabolome analysis of serum changes in sheep under overgrazing or light grazing conditions. BMC Vet Res 2019; 15:469. [PMID: 31878922 PMCID: PMC6933664 DOI: 10.1186/s12917-019-2218-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 12/19/2019] [Indexed: 12/28/2022] Open
Abstract
Background Overgrazing is a primary contributor to severe reduction in forage quality and production in Inner Mongolia, leading to extensive ecosystem degradation, sheep health impairment and growth performance reduction. Further studies to identify serum biomarkers that reflect changes in sheep health and nutritional status following overgrazing would be beneficial. We hereby hypothesize that reduced sheep growth performance under overgrazing conditions would be associated with metabolic and immune response alterations. This study used an untargeted metabolomics analysis by conducting ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) of sheep serum under overgrazing and light grazing conditions to identify metabolic disruptions in response to overgrazing. Results The sheep body weight gains as well as serum biochemical variables associated with immune responses and nutritional metabolism (immunoglobulin G, albumin, glucose, and nonesterified fatty acids) were significantly decreased with overgrazing compared with light grazing condition. In contrast, other serum parameters such as alanine and aspartate aminotransferase, alkaline phosphatase, total bilirubin, blood urea nitrogen, and interleukin-8 were markedly higher in the overgrazing group. Principal component analysis discriminated the metabolomes of the light grazing from the overgrazing group. Multivariate and univariate analyses revealed changes in the serum concentrations of 15 metabolites (9 metabolites exhibited a marked increase, whereas 6 metabolites showed a significant decrease) in the overgrazing group. Major changes of fatty acid oxidation, bile acid biosynthesis, and purine and protein metabolism were observed. Conclusions These findings offer metabolic evidence for putative biomarkers for overgrazing-induced changes in serum metabolism. Target-identification of these particular metabolites may potentially increase our knowledge of the molecular mechanisms of altered immune responses, nutritional metabolism, and reduced sheep growth performance under overgrazing conditions.
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Affiliation(s)
- Jize Zhang
- Key Laboratory of Forage Grass, Ministry of Agriculture, Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot, 010010, Inner Mongolia, China
| | - Yang Gao
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin, 130018, China
| | - Huiqin Guo
- College of Life Sciences, Inner Mongolia Agricultural University, Hohhot, 010019, Inner Mongolia, China
| | - Yong Ding
- Key Laboratory of Forage Grass, Ministry of Agriculture, Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot, 010010, Inner Mongolia, China
| | - Weibo Ren
- School of Ecology and Environment, Inner Mongolia University, Hohhot, 010021, Inner Mongolia, China.
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Yoon SJ, Long NP, Jung KH, Kim HM, Hong YJ, Fang Z, Kim SJ, Kim TJ, Anh NH, Hong SS, Kwon SW. Systemic and Local Metabolic Alterations in Sleep-Deprivation-Induced Stress: A Multiplatform Mass-Spectrometry-Based Lipidomics and Metabolomics Approach. J Proteome Res 2019; 18:3295-3304. [PMID: 31313932 DOI: 10.1021/acs.jproteome.9b00234] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Sleep deprivation (SD) is known to be associated with metabolic disorders and chronic diseases. Complex metabolic alterations induced by SD at omics scale and the associated biomarker candidates have been proposed. However, in vivo systemic and local metabolic shift patterns of the metabolome and lipidome in acute and chronic partial SD models remain to be elucidated. In the present study, the serum, hypothalamus, and hippocampus CA1 of sleep-deprived rats (SD rats) from acute and chronic sleep restriction models were analyzed using three different omics platforms for the discovery and mechanistic assessment of systemic and local SD-induced dysregulated metabolites. We found a similar pattern of systemic metabolome alterations between two models, for which the area under the curve (AUC) of receiver operating characteristic curves was AUC = 0.847 and 0.930 with the pseudotargeted and untargeted metabolomics approach, respectively. However, SD-induced systemic lipidome alterations were significantly different and appeared to be model-dependent (AUC = 0.374). Comprehensive pathway analysis of the altered lipidome and metabolome in the hypothalamus indicated the abnormal behavior of eight metabolic and lipid metabolic pathways. The metabolic alterations of the hippocampus CA1 was subtle in two SD models. Collectively, these results extend our understanding of the quality of sleep and suggest metabolic targets in developing diagnostic biomarkers for better SD control.
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Affiliation(s)
- Sang Jun Yoon
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Nguyen Phuoc Long
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Kyung-Hee Jung
- Department of Biomedical Sciences, College of Medicine , Inha University , Incheon 22212 , Republic of Korea
| | - Hyung Min Kim
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Yu Jin Hong
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Zhenghuan Fang
- Department of Biomedical Sciences, College of Medicine , Inha University , Incheon 22212 , Republic of Korea
| | - Sun Jo Kim
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Tae Joon Kim
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Nguyen Hoang Anh
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
| | - Soon-Sun Hong
- Department of Biomedical Sciences, College of Medicine , Inha University , Incheon 22212 , Republic of Korea
| | - Sung Won Kwon
- College of Pharmacy , Seoul National University , Seoul 08826 , Republic of Korea
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Ma W, Song J, Wang H, Shi F, Zhou N, Jiang J, Xu Y, Zhang L, Yang L, Zhou M. Chronic paradoxical sleep deprivation-induced depression-like behavior, energy metabolism and microbial changes in rats. Life Sci 2019; 225:88-97. [PMID: 30953642 DOI: 10.1016/j.lfs.2019.04.006] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 03/28/2019] [Accepted: 04/02/2019] [Indexed: 12/14/2022]
Abstract
AIMS Given the lasting impact of chronic paradoxical sleep deprivation (PSD) on behavior and organism metabolic alternations, along with the role of the microbiome in neurobehavioral development and metabolism, we sought to examine the relationship between the microbiota and chronic PSD-induced behavioral and metabolic changes. MATERIALS AND METHODS Psychological status of 7-day PSD (7d-PSD) male rats was tested by behavioral method, serum inflammatory cytokines and hypothalamic-pituitary-adrenal (HPA) axis-related hormones. In addition, GC-MS based urine metabolomics and 16S rRNA gene sequencing approaches were applied to estimate the influences of chronic PSD on host metabolism and gut-microbiota. Furtherly, microbial functional prediction and Spearman's correlation analysis were implemented to manifest the relations between the differential urinary metabolites and gut microbiota. KEY FINDINGS 7d-PSD rats displayed depression-like behavior, metabolic and microbial changes. By integrating differential gut bacteria with indicators of depression and differential metabolites, we found that the alterations of Akkermansia, Oscillospira, Ruminococcus, Parabacteroides, Aggregatibacter and Phascolarctobacterium were closely related to abnormalities of depression symptoms and inflammatory cytokines. These bacteria also had close connections with host energy metabolism concerning arginine and proline metabolism, glycine, serine and threonine metabolism, and glyoxylate and dicarboxylate metabolism, pyruvate metabolism, which overlapped with the results of 16S rRNA gene function annotation. SIGNIFICANCE These data suggest that a specific situation of circadian disturbance, chronic PSD-induced alterations in gut microbiota and related host changes in metabolism may be the pathogenesis of depression.
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Affiliation(s)
- Weini Ma
- Center for Chinese Medicine Therapy and Systems Biology, Institute for Interdisciplinary Medicine Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Jing Song
- Center for Chinese Medicine Therapy and Systems Biology, Institute for Interdisciplinary Medicine Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Heran Wang
- School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Fangyu Shi
- School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Nian Zhou
- Center for Chinese Medicine Therapy and Systems Biology, Institute for Interdisciplinary Medicine Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Jiaye Jiang
- Experiment Center of Teaching & Learning, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Ying Xu
- Department of Physiology, School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Lei Zhang
- Shanghai Innovation Center of TCM Health Service, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Li Yang
- Center for Chinese Medicine Therapy and Systems Biology, Institute for Interdisciplinary Medicine Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China; The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines and the State Administration of Traditional Chinese Medicine (SATCM) Key Laboratory for New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Mingmei Zhou
- Center for Chinese Medicine Therapy and Systems Biology, Institute for Interdisciplinary Medicine Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
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