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Guo L, Jia C, Luo K, Liang J, Wang L, Hui T. Elevated HIF-1α levels in maintenance hemodialysis patients: a potential link to increased cognitive impairment risk. Front Aging Neurosci 2024; 16:1455596. [PMID: 39717345 PMCID: PMC11663881 DOI: 10.3389/fnagi.2024.1455596] [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: 07/18/2024] [Accepted: 11/26/2024] [Indexed: 12/25/2024] Open
Abstract
Introduction In China, an increasing number of patients with end-stage renal disease are undergoing hemodialysis treatment. While this treatment yields relatively positive outcomes, the prevalence of cognitive impairment in patients receiving maintenance hemodialysis ranges from 24 to 80%, which is significantly higher than the general population. Method In this retrospective study, a total of 120 patients with kidney disease undergoing maintenance hemodialysis (MHD) were enrolled. The cognitive status of these patients was assessed using the C-MoCA score, which allowed categorization into two groups: the no cognitive impairment (NCI) group and the cognitive impairment (CI) group. Relevant clinical data, laboratory test results, as well as HIF-1α levels, were collected and analyzed to determine their relationship with the cognitive status of the patients. Results In this study, a total of 45 patients (37.5%) developed CI, and their C-MoCA scores were significantly lower (21.6 ± 2.43) compared to patients in the NCI group (27.56 ± 1.48) (P < 0.001). The CI group was characterized by older age, lower levels of education, as well as lower levels of serum total bilirubin, serum total protein (TP), albumin, serum creatinine, and serum phosphorus in comparison to the NCI group. Additionally, CI patients exhibited higher levels of HIF-1α, received fewer monthly hemodiafiltration or hemoperfusion treatments, and had a lower rate of rosacastat treatment. Furthermore, univariate and multivariate logistic regression analyses demonstrated that older age (OR = 11.266 [95% CI: 2.775-45.747], P = 0.001) and higher HIF-1α (OR = 20.654 [4.831-88.298], P < 0.001) increased the risk of developing CI, while higher educational attainment reduced the risk of developing CI (> 12 years, OR = 0.004 [95% CI: 0.016-0.619], P≤0.001; 6-12 years, OR = 0.099 [95% CI: 0.000-0.049], P = 0.013). Discussion Cognitive impairment in patients undergoing maintenance hemodialysis (MHD) was found to be associated with older age, lower level of education, and higher HIF-1α levels. These factors should be taken into consideration by clinicians to monitor the cognitive status of MHD patients.
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Affiliation(s)
- Lan Guo
- Department of Nephrology, Hebei General Hospital, Shijiazhuang, China
| | - Caiyun Jia
- Department of Pharmacy, Hebei General Hospital, Shijiazhuang, China
| | - Ke Luo
- Department of Nephrology, The First People’s Hospital of Tianmen City, Tianmen, China
| | - Juanrong Liang
- Department of Nephrology, Hebei General Hospital, Shijiazhuang, China
| | - Lijun Wang
- Department of Nephrology, Hebei General Hospital, Shijiazhuang, China
| | - Tianli Hui
- Breast Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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Gaeta AM, Quijada-López M, Barbé F, Vaca R, Pujol M, Minguez O, Sánchez-de-la-Torre M, Muñoz-Barrutia A, Piñol-Ripoll G. Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach. Front Aging Neurosci 2024; 16:1369545. [PMID: 38988328 PMCID: PMC11233742 DOI: 10.3389/fnagi.2024.1369545] [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: 01/12/2024] [Accepted: 06/04/2024] [Indexed: 07/12/2024] Open
Abstract
Introduction Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a lumbar puncture to be performed, making them impractical as screening tools. Considering the role of sleep disturbances in AD, recent research suggests quantitative sleep electroencephalography features as potential non-invasive biomarkers of AD pathology. However, quantitative analysis of comprehensive polysomnography (PSG) signals remains relatively understudied. PSG is a non-invasive test enabling qualitative and quantitative analysis of a wide range of parameters, offering additional insights alongside other biomarkers. Machine Learning (ML) gained interest for its ability to discern intricate patterns within complex datasets, offering promise in AD neuropathology detection. Therefore, this study aims to evaluate the effectiveness of a multimodal ML approach in predicting core AD CSF biomarkers. Methods Mild-moderate AD patients were prospectively recruited for PSG, followed by testing of CSF and blood samples for biomarkers. PSG signals underwent preprocessing to extract non-linear, time domain and frequency domain statistics quantitative features. Multiple ML algorithms were trained using four subsets of input features: clinical variables (CLINVAR), conventional PSG parameters (SLEEPVAR), quantitative PSG signal features (PSGVAR) and a combination of all subsets (ALL). Cross-validation techniques were employed to evaluate model performance and ensure generalizability. Regression models were developed to determine the most effective variable combinations for explaining variance in the biomarkers. Results On 49 subjects, Gradient Boosting Regressors achieved the best results in estimating biomarkers levels, using different loss functions for each biomarker: least absolute deviation (LAD) for the Aβ42, least squares (LS) for p-tau and Huber for t-tau. The ALL subset demonstrated the lowest training errors for all three biomarkers, albeit with varying test performance. Specifically, the SLEEPVAR subset yielded the best test performance in predicting Aβ42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors. Conclusions Multimodal ML can help predict the outcome of CSF biomarkers in early AD by utilizing non-invasive and economically feasible variables. The integration of computational models into medical practice offers a promising tool for the screening of patients at risk of AD, potentially guiding clinical decisions.
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Affiliation(s)
- Anna Michela Gaeta
- Servicio de Neumología, Hospital Universitario Severo Ochoa, Leganés, Spain
| | - María Quijada-López
- Departamento de Bioingeniería, Universidad Carlos III de Madrid, Leganés, Spain
| | - Ferran Barbé
- Group of Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova and Santa Maria, Institut de Recerca Biomedica de Lleida (IRBLleida), Lleida, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Rafaela Vaca
- Group of Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova and Santa Maria, Institut de Recerca Biomedica de Lleida (IRBLleida), Lleida, Spain
| | - Montse Pujol
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Institut de Recerca Biomedica de Lleida (IRBLleida), Hospital Universitari Santa Maria, Lleida, Spain
| | - Olga Minguez
- Group of Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova and Santa Maria, Institut de Recerca Biomedica de Lleida (IRBLleida), Lleida, Spain
| | - Manuel Sánchez-de-la-Torre
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Group of Precision Medicine in Chronic Diseases, Hospital Nacional de Parapléjicos, IDISCAM, Department of Nursing, Physiotherapy and Occupational Therapy, Faculty of Physiotherapy and Nursing, University of Castilla-La Mancha, Toledo, Spain
| | - Arrate Muñoz-Barrutia
- Departamento de Bioingeniería, Universidad Carlos III de Madrid, Leganés, Spain
- Departamento de Bioingegneria, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Gerard Piñol-Ripoll
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Institut de Recerca Biomedica de Lleida (IRBLleida), Hospital Universitari Santa Maria, Lleida, Spain
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Fehsel K. Why Is Iron Deficiency/Anemia Linked to Alzheimer's Disease and Its Comorbidities, and How Is It Prevented? Biomedicines 2023; 11:2421. [PMID: 37760862 PMCID: PMC10526115 DOI: 10.3390/biomedicines11092421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/29/2023] Open
Abstract
Impaired iron metabolism has been increasingly observed in many diseases, but a deeper, mechanistic understanding of the cellular impact of altered iron metabolism is still lacking. In addition, deficits in neuronal energy metabolism due to reduced glucose import were described for Alzheimer's disease (AD) and its comorbidities like obesity, depression, cardiovascular disease, and type 2 diabetes mellitus. The aim of this review is to present the molecular link between both observations. Insufficient cellular glucose uptake triggers increased ferritin expression, leading to depletion of the cellular free iron pool and stabilization of the hypoxia-induced factor (HIF) 1α. This transcription factor induces the expression of the glucose transporters (Glut) 1 and 3 and shifts the cellular metabolism towards glycolysis. If this first line of defense is not adequate for sufficient glucose supply, further reduction of the intracellular iron pool affects the enzymes of the mitochondrial electron transport chain and activates the AMP-activated kinase (AMPK). This enzyme triggers the translocation of Glut4 to the plasma membrane as well as the autophagic recycling of cell components in order to mobilize energy resources. Moreover, AMPK activates the autophagic process of ferritinophagy, which provides free iron urgently needed as a cofactor for the synthesis of heme- and iron-sulfur proteins. Excessive activation of this pathway ends in ferroptosis, a special iron-dependent form of cell death, while hampered AMPK activation steadily reduces the iron pools, leading to hypoferremia with iron sequestration in the spleen and liver. Long-lasting iron depletion affects erythropoiesis and results in anemia of chronic disease, a common condition in patients with AD and its comorbidities. Instead of iron supplementation, drugs, diet, or phytochemicals that improve energy supply and cellular glucose uptake should be administered to counteract hypoferremia and anemia of chronic disease.
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Affiliation(s)
- Karin Fehsel
- Neurobiochemical Research Unit, Department of Psychiatry, Medical Faculty, Heinrich-Heine-University, 240629 Düsseldorf, Germany
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Li G, Liu J, Guo M, Gu Y, Guan Y, Shao Q, Ma W, Ji X. Chronic hypoxia leads to cognitive impairment by promoting HIF-2α-mediated ceramide catabolism and alpha-synuclein hyperphosphorylation. Cell Death Dis 2022; 8:473. [PMID: 36450714 PMCID: PMC9712431 DOI: 10.1038/s41420-022-01260-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 11/13/2022] [Accepted: 11/16/2022] [Indexed: 12/05/2022]
Abstract
Chronic hypoxia leads to irreversible cognitive impairment, primarily due to hippocampal neurodegeneration, for which the underlying mechanism remains poorly understood. We administered hypoxia (13%) to C57BL mice for 1-14 days in this study. Chronic hypoxia for 7 or 14 d, but not 1 or 3 d, resulted in alpha-synuclein hyperphosphorylation at serine129 (α-Syn p-S129) and protein aggregation, hippocampal neurodegeneration, and cognitive deficits, whereas the latter could be prevented by alpha-synuclein knockdown or an administered short peptide competing at α-Syn S129. These results suggest that α-Syn p-S129 mediates hippocampal degeneration and cognitive impairment following chronic hypoxia. Furthermore, we found that chronic hypoxia enhanced ceramide catabolism by inducing hypoxia-inducible factor (HIF)-2α and HIF-2α-dependent transcriptional activation of alkaline ceramidase 2 (Acer2). Thus, the enzymatic activity of protein phosphatase 2A (PP2A), a specific phosphatase for α-syn, is inhibited, leading to the sustained induction of α-Syn p-S129. Finally, we found that intermittent hypoxic preconditioning protected against subsequent chronic hypoxia-induced hippocampal neurodegeneration and cognitive impairment by preventing α-Syn p-S129. These results proved the critical role of α-syn pathology in chronic hypoxia-afforded cognitive impairment and revealed a novel mechanism underlying α-syn hyperphosphorylation during chronic hypoxia. The findings bear implications in developing novel therapeutic interventions for chronic hypoxia-related brain disorders.
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Affiliation(s)
- Gaifen Li
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China ,grid.413259.80000 0004 0632 3337Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jia Liu
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China
| | - Mengyuan Guo
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China
| | - Yakun Gu
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China
| | - Yuying Guan
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China ,grid.413259.80000 0004 0632 3337Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Qianqian Shao
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China
| | - Wei Ma
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China
| | - Xunming Ji
- grid.24696.3f0000 0004 0369 153XBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, Beijing, China ,grid.413259.80000 0004 0632 3337Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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Pang YQ, Yang J, Jia CM, Zhang R, Pang Q. Hypoxic preconditioning reduces NLRP3 inflammasome expression and protects against cerebral ischemia/reperfusion injury. Neural Regen Res 2022; 17:395-400. [PMID: 34269215 PMCID: PMC8464000 DOI: 10.4103/1673-5374.314317] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 01/29/2021] [Accepted: 04/02/2021] [Indexed: 11/28/2022] Open
Abstract
Hypoxic preconditioning can protect against cerebral ischemia/reperfusion injury. However, the underlying mechanisms that mediate this effect are not completely clear. In this study, mice were pretreated with continuous, intermittent hypoxic preconditioning; 1 hour later, cerebral ischemia/reperfusion models were generated by middle cerebral artery occlusion and reperfusion. Compared with control mice, mice with cerebral ischemia/reperfusion injury showed increased Bederson neurological function scores, significantly increased cerebral infarction volume, obvious pathological damage to the hippocampus, significantly increased apoptosis; upregulated interleukin-1β, interleukin-6, and interleukin-8 levels in brain tissue; and increased expression levels of NOD-like receptor family pyrin domain containing 3 (NLRP3), NLRP inflammasome-related protein caspase-1, and gasdermin D. However, hypoxic preconditioning significantly inhibited the above phenomena. Taken together, these data suggest that hypoxic preconditioning mitigates cerebral ischemia/reperfusion injury in mice by reducing NLRP3 inflammasome expression. This study was approved by the Medical Ethics Committee of the Fourth Hospital of Baotou, China (approval No. DWLL2019001) in November 2019.
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Affiliation(s)
- Yi-Qiang Pang
- Department of Neurosurgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China
- Department of Neurosurgery, The Fourth Hospital of Baotou, Baotou, Inner Mongolia Autonomous Region, China
| | - Jing Yang
- Department of Basic Medicine and Forensic Medicine, Baotou Medical College, Baotou, Inner Mongolia Autonomous Region, China
| | - Chun-Mei Jia
- Department of Neurosurgery, The Fourth Hospital of Baotou, Baotou, Inner Mongolia Autonomous Region, China
| | - Rui Zhang
- Department of Neurosurgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China
| | - Qi Pang
- Department of Neurosurgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China
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