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Moreno-Cortés ML, Meza-Alvarado JE, García-Mena J, Hernández-Rodríguez A. Chronodisruption and Gut Microbiota: Triggering Glycemic Imbalance in People with Type 2 Diabetes. Nutrients 2024; 16:616. [PMID: 38474745 DOI: 10.3390/nu16050616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/27/2024] [Accepted: 01/28/2024] [Indexed: 03/14/2024] Open
Abstract
The desynchronization of physiological and behavioral mechanisms influences the gut microbiota and eating behavior in mammals, as shown in both rodents and humans, leading to the development of pathologies such as Type 2 diabetes (T2D), obesity, and metabolic syndrome. Recent studies propose resynchronization as a key input controlling metabolic cycles and contributing to reducing the risk of suffering some chronic diseases such as diabetes, obesity, or metabolic syndrome. In this analytical review, we present an overview of how desynchronization and its implications for the gut microbiome make people vulnerable to intestinal dysbiosis and consequent chronic diseases. In particular, we explore the eubiosis-dysbiosis phenomenon and, finally, propose some topics aimed at addressing chronotherapy as a key strategy in the prevention of chronic diseases.
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Affiliation(s)
- María Luisa Moreno-Cortés
- Laboratorio de Biomedicina, Instituto de Investigaciones Biológicas, Universidad Veracruzana, Xalapa 91190, Veracruz, Mexico
| | | | - Jaime García-Mena
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, CDMX 07360, Mexico
| | - Azucena Hernández-Rodríguez
- Laboratorio de Biomedicina, Instituto de Investigaciones Biológicas, Universidad Veracruzana, Xalapa 91190, Veracruz, Mexico
- Facultad de Bioanálisis, Universidad Veracruzana, Xalapa 91010, Veracruz, Mexico
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Perez-Lloret S, Chevalier G, Bordet S, Barbar H, Capani F, Udovin L, Otero-Losada M. The Genetic Basis of Probable REM Sleep Behavior Disorder in Parkinson's Disease. Brain Sci 2023; 13:1146. [PMID: 37626502 PMCID: PMC10452689 DOI: 10.3390/brainsci13081146] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/25/2023] [Accepted: 07/27/2023] [Indexed: 08/27/2023] Open
Abstract
Patients with Parkinson's Disease (PD) experience REM sleep behavior disorder (RBD) more frequently than healthy controls. RBD is associated with torpid disease evolution. To test the hypothesis that differential genetic signatures might contribute to the torpid disease evolution in PD patients with RBD we compared the rate of genetic mutations in PD patients with or without probable RBD. Patients with a clinical diagnosis of PD in the Parkinson's Progression Markers Initiative (PPMI) database entered the study. We excluded those with missing data, dementia, psychiatric conditions, or a diagnosis change over the first five years from the initial PD diagnosis. Probable RBD (pRBD) was confirmed by a REM Sleep Behavior Disorder Screening Questionnaire score > 5 points. Logistic regression and Machine Learning (ML) algorithms were used to relate Single Nucleotide Polymorphism (SNPs) in PD-related genes with pRBD. We included 330 PD patients fulfilling all inclusion and exclusion criteria. The final logistic multivariate model revealed that the following SNPs increased the risk of pRBD: GBA_N370S_rs76763715 (OR, 95% CI: 3.38, 1.45-7.93), SNCA_A53T_rs104893877 (8.21, 2.26-36.34), ANK2. CAMK2D_rs78738012 (2.12, 1.08-4.10), and ZNF184_rs9468199 (1.89, 1.08-3.33). Conversely, SNP COQ7. SYT17_rs11343 reduced pRBD risk (0.36, 0.15-0.78). The ML algorithms led to similar results. The predictive models were highly specific (95-99%) but lacked sensitivity (9-39%). We found a distinctive genetic signature for pRBD in PD. The high specificity and low sensitivity of the predictive models suggest that genetic mutations are necessary but not sufficient to develop pRBD in PD. Additional investigations are needed.
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Affiliation(s)
- Santiago Perez-Lloret
- Observatorio de Salud Pública, Vicerrectorado de Investigación e Innovación Académica, Pontificia Universidad Católica Argentina (UCA), Consejo Nacional de Investigaciones Científicas y Técnicas (UCA-CONICET), Buenos Aires C1107AAZ, Argentina
- Centro de Investigaciones en Psicología y Psicopedagogía (CIPP), Facultad de Psicología y Psicopedagogía, Pontificia Universidad Católica Argentina (UCA), Buenos Aires C1107AFB, Argentina;
- Departamento de Fisiología, Facultad de Medicina, Universidad de Buenos Aires (UBA), Buenos Aires C1053ABH, Argentina
| | - Guenson Chevalier
- Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas, CAECIHS.UAI-CONICET, Buenos Aires C1270AAH, Argentina; (G.C.); (H.B.); (F.C.); (L.U.); (M.O.-L.)
| | - Sofia Bordet
- Centro de Investigaciones en Psicología y Psicopedagogía (CIPP), Facultad de Psicología y Psicopedagogía, Pontificia Universidad Católica Argentina (UCA), Buenos Aires C1107AFB, Argentina;
- Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas, CAECIHS.UAI-CONICET, Buenos Aires C1270AAH, Argentina; (G.C.); (H.B.); (F.C.); (L.U.); (M.O.-L.)
| | - Hanny Barbar
- Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas, CAECIHS.UAI-CONICET, Buenos Aires C1270AAH, Argentina; (G.C.); (H.B.); (F.C.); (L.U.); (M.O.-L.)
| | - Francisco Capani
- Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas, CAECIHS.UAI-CONICET, Buenos Aires C1270AAH, Argentina; (G.C.); (H.B.); (F.C.); (L.U.); (M.O.-L.)
- Instituto de Ciencias Biomédicas, Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Santiago 7500912, Chile
| | - Lucas Udovin
- Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas, CAECIHS.UAI-CONICET, Buenos Aires C1270AAH, Argentina; (G.C.); (H.B.); (F.C.); (L.U.); (M.O.-L.)
| | - Matilde Otero-Losada
- Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas, CAECIHS.UAI-CONICET, Buenos Aires C1270AAH, Argentina; (G.C.); (H.B.); (F.C.); (L.U.); (M.O.-L.)
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Recovery Sleep Immediately after Prolonged Sleep Deprivation Stimulates the Transcription of Integrated Stress Response-Related Genes in the Liver of Male Rats. Clocks Sleep 2022; 4:623-632. [PMID: 36412581 PMCID: PMC9680379 DOI: 10.3390/clockssleep4040048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/27/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
Sleep loss induces performance impairment and fatigue. The reactivation of human herpesvirus-6, which is related to the phosphorylation of eukaryotic translation initiation factor 2α (eIF2α), is one candidate for use as an objective biomarker of fatigue. Phosphorylated eIF2α is a key regulator in integrated stress response (ISR), an intracellular stress response system. However, the relation between sleep/sleep loss and ISR is unclear. The purpose of the current study was to evaluate the effect of prolonged sleep deprivation and recovery sleep on ISR-related gene expression in rat liver. Eight-week-old male Sprague-Dawley rats were subjected to a 96-hour sleep deprivation using a flowerpot technique. The rats were sacrificed, and the liver was collected immediately or 6 or 72 h after the end of the sleep deprivation. RT-qPCR was used to analyze the expression levels of ISR-related gene transcripts in the rat liver. The transcript levels of the Atf3, Ddit3, Hmox-1, and Ppp15a1r genes were markedly increased early in the recovery sleep period after the termination of sleep deprivation. These results indicate that both activation and inactivation of ISRs in the rat liver occur simultaneously in the early phase of recovery sleep.
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Sahu M, Tripathi R, Jha NK, Jha SK, Ambasta RK, Kumar P. Cross talk mechanism of disturbed sleep patterns in neurological and psychological disorders. Neurosci Biobehav Rev 2022; 140:104767. [PMID: 35811007 DOI: 10.1016/j.neubiorev.2022.104767] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/20/2022] [Accepted: 07/01/2022] [Indexed: 11/25/2022]
Abstract
The incidence and prevalence of sleep disorders continue to increase in the elderly populace, particularly those suffering from neurodegenerative and neuropsychiatric disorders. This not only affects the quality of life but also accelerates the progression of the disease. There are many reasons behind sleep disturbances in such patients, for instance, medication use, nocturia, obesity, environmental factors, nocturnal motor disturbances and depressive symptoms. This review focuses on the mechanism and effects of sleep dysfunction in neurodegenerative and neuropsychiatric disorders. Wherein we discuss disturbed circadian rhythm, signaling cascade and regulation of genes during sleep deprivation. Moreover, we explain the perturbation in brainwaves during disturbed sleep and the ocular perspective of neurodegenerative and neuropsychiatric manifestations in sleep disorders. Further, as the pharmacological approach is often futile and carries side effects, therefore, the non-pharmacological approach opens newer possibilities to treat these disorders and widens the landscape of treatment options for patients.
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Affiliation(s)
- Mehar Sahu
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Delhi, India
| | - Rahul Tripathi
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Delhi, India
| | - Niraj Kumar Jha
- Department of Biotechnology, School of Engineering & Technology (SET) Sharda University, UP, India
| | - Saurabh Kumar Jha
- Department of Biotechnology, School of Engineering & Technology (SET) Sharda University, UP, India.
| | - Rashmi K Ambasta
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Delhi, India
| | - Pravir Kumar
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Delhi, India.
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Hu S, Li P, Zhang R, Liu X, Wei S. Integrated metabolomics and proteomics analysis reveals energy metabolism disorders in the livers of sleep-deprived mice. J Proteomics 2021; 245:104290. [PMID: 34089895 DOI: 10.1016/j.jprot.2021.104290] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 05/16/2021] [Accepted: 05/24/2021] [Indexed: 02/07/2023]
Abstract
Sleep deprivation (SD) has been linked to impaired mental and physical health, obesity, and various diseases. However, the molecular mechanism underlying the effects of SD in the liver is still unclear. To investigate the metabolome and proteome alterations in the liver, an in vivo model of SD was established based on automated random motion platform techniques by applying a strategy of 10 consecutive days of 20 h of sleep deprivation +4 h of resting. The liver's altered metabolites and proteins were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and data analyses were performed with MetaboAnalyst 5.0. This study found 15 differential metabolites, including 12 upregulated- metabolites and 3 downregulated- metabolites. A total of 493 proteins were differentially regulated, including 377 upregulated- proteins and 116 downregulated- proteins. The glutathione metabolism, fructose and mannose metabolism, and pyruvate metabolism pathways had significant effects on the sleep-deprived mouse livers. These three active pathways cause energy metabolism disorder and may induce obesity. In conclusion, this study demonstrates that SD could change the metabolism of glucose, and specific fatty acids, amino acids, and critical enzymes in the liver, providing a reference for the health effects of insufficient sleep. SIGNIFICANCE STATEMENT: So far, little is known about the changes in metabolites and proteins in the liver of individuals who suffer from SD. Metabolites and proteins in serum, urine and hypothalamus do not entirely reflect the effects of sleep deprivation on the whole body. In addition, many SD-induced models used the multiplatform water environment method, which causes mice to fall into the water frequently. Under this condition, the physical exertion of mice is extremely high, and it is not suitable for long-term sleep deprivation. The SD induction process has caused some influence on the model. Finally, few studies have elucidated the imbalance of energy metabolism caused by SD to induce obesity from the molecular mechanism. This study used a rotary table deprivation apparatus to trigger SD. This method will not cause excessive consumption and stimulation of mice. Furthermore, this study analyzed the metabolic and proteomic changes in the liver and enriched the range and means of metabolic and proteomic changes in sleep deprived mice. Finally, this research provides reference for elucidating the molecular mechanism of sleep deprivation causing energy metabolism disorders in the liver of mice.
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Affiliation(s)
- Shuang Hu
- Department of Child, Adolescent and Women's Health, School of Public Health, Capital Medical University, Beijing, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Pengxiang Li
- Department of Child, Adolescent and Women's Health, School of Public Health, Capital Medical University, Beijing, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Rong Zhang
- Department of Child, Adolescent and Women's Health, School of Public Health, Capital Medical University, Beijing, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Xuan Liu
- Department of Child, Adolescent and Women's Health, School of Public Health, Capital Medical University, Beijing, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Shougang Wei
- Department of Child, Adolescent and Women's Health, School of Public Health, Capital Medical University, Beijing, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China.
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