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Meier L, Bruginski E, Marafiga JR, Caus LB, Pasquetti MV, Calcagnotto ME, Campos FR. Hippocampal metabolic profile during epileptogenesis in the pilocarpine model of epilepsy. Biomed Chromatogr 2024; 38:e5820. [PMID: 38154955 DOI: 10.1002/bmc.5820] [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: 11/11/2023] [Revised: 12/02/2023] [Accepted: 12/07/2023] [Indexed: 12/30/2023]
Abstract
Temporal lobe epilepsy (TLE) is a common form of refractory epilepsy in adulthood. The metabolic profile of epileptogenesis is still poorly investigated. Elucidation of such a metabolic profile using animal models of epilepsy could help identify new metabolites and pathways involved in the mechanisms of epileptogenesis process. In this study, we evaluated the metabolic profile during the epileptogenesis periods. Using a pilocarpine model of epilepsy, we analyzed the global metabolic profile of hippocampal extracts by untargeted metabolomics based on ultra-performance liquid chromatography-high-resolution mass spectrometry, at three time points (3 h, 1 week, and 2 weeks) after status epilepticus (SE) induction. We demonstrated that epileptogenesis periods presented different hippocampal metabolic profiles, including alterations of metabolic pathways of amino acids and lipid metabolism. Six putative metabolites (tryptophan, N-acetylornithine, N-acetyl-L-aspartate, glutamine, adenosine, and cholesterol) showed significant different levels during epileptogenesis compared to their respective controls. These putative metabolites could be associated with the imbalance of neurotransmitters, mitochondrial dysfunction, and cell loss observed during both epileptogenesis and epilepsy. With these findings, we provided an overview of hippocampal metabolic profiles during different stages of epileptogenesis that could help investigate pathways and respective metabolites as predictive tools in epilepsy.
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Affiliation(s)
- Letícia Meier
- Biosciences and Mass Spectrometry Laboratory, Department of Pharmacy, Universidade Federal do Paraná, Curitiba, PR, Brazil
- Graduate Program in Pharmaceutical Science, Universidade Federal do Paraná, Curitiba, PR, Brazil
| | - Estevan Bruginski
- Biosciences and Mass Spectrometry Laboratory, Department of Pharmacy, Universidade Federal do Paraná, Curitiba, PR, Brazil
- Graduate Program in Pharmaceutical Science, Universidade Federal do Paraná, Curitiba, PR, Brazil
| | - Joseane Righes Marafiga
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory (NNNESP Lab.), Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Graduate Program in Biological Science: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Letícia Barbieri Caus
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory (NNNESP Lab.), Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Mayara Vendramin Pasquetti
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory (NNNESP Lab.), Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Maria Elisa Calcagnotto
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory (NNNESP Lab.), Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Graduate Program in Biological Science: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Francinete Ramos Campos
- Biosciences and Mass Spectrometry Laboratory, Department of Pharmacy, Universidade Federal do Paraná, Curitiba, PR, Brazil
- Graduate Program in Pharmaceutical Science, Universidade Federal do Paraná, Curitiba, PR, Brazil
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Huang SY, Zhang YR, Yang L, Li YZ, Wu BS, Chen SD, Feng JF, Dong Q, Cheng W, Yu JT. Circulating metabolites and risk of incident dementia: A prospective cohort study. J Neurochem 2023; 167:668-679. [PMID: 37908051 DOI: 10.1111/jnc.15997] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 11/02/2023]
Abstract
Identifying circulating metabolites associated with dementia, cognition, and brain volume may improve the understanding of dementia pathogenesis and provide novel insights for preventive and therapeutic interventions. This cohort study included a total of 87 885 participants (median follow-up of 9.1 years, 54% female) without dementia at baseline from the UK Biobank. A total of 249 plasma metabolites were measured using nuclear magnetic resonance spectroscopy at baseline. Cox proportional regression was used to examine the associations of each metabolite with incident dementia (cases = 1134), Alzheimer's disease (AD; cases = 488), and vascular dementia (VD; cases = 257) during follow-up. Dementia-associated metabolites were further analyzed for association with cognitive deficits (N = 87 885) and brain volume (N = 7756) using logistic regression and linear regression. We identified 26 metabolites associated with incident dementia, of which 6 were associated with incident AD and 5 were associated with incident VD. These 26 dementia-related metabolites were subfractions of intermediate-density lipoprotein, large low-density lipoprotein (L-LDL), small high-density lipoprotein (S-HDL), very-low-density lipoprotein, fatty acids, ketone bodies, citrate, glucose, and valine. Among them, the cholesterol percentage in L-LDL (L-LDL-C%) was associated with lower risk of AD (HR [95% CI] = 0.92 [0.87-0.97], p = 0.002), higher brain cortical (β = 0.047, p = 3.91 × 10-6 ), and hippocampal (β = 0.043, p = 1.93 × 10-4 ) volume. Cholesteryl ester-to-total lipid ratio in L-LDL (L-LDL-CE%) was associated with lower risk of AD (HR [95% CI] = 0.93 [0.90-0.96], p = 1.48 × 10-4 ), cognitive deficits (odds ratio = 0.98, p = 0.009), and higher hippocampal volume (β = 0.027, p = 0.009). Cholesteryl esters in S-HDL (S-HDL-CE) were associated with lower risk of VD (HR [95% CI] = 0.81 [0.71-0.93], p = 0.002), but not AD. Taken together, circulating levels of L-LDL-CE% and L-LDL-C% were robustly associated with risk of AD and AD phenotypes, but not with VD. S-HDL-CE was associated with lower risk of VD, but not with AD or AD phenotypes. These metabolites may play a role in the advancement of future intervention trials. Additional research is necessary to gain a complete comprehension of the molecular mechanisms behind these associations.
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Affiliation(s)
- Shu-Yi Huang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu-Zhu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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Han J, Huang H, Lei Z, Pan R, Chen X, Chen Y, Lu T. Association Between the Early Serum Lipid Metabolism Profile and Delayed Neurocognitive Recovery After Cardiopulmonary Bypass in Cardiac Surgical Patients: a Pilot Study. J Cardiovasc Transl Res 2022:10.1007/s12265-022-10332-y. [PMID: 36271179 DOI: 10.1007/s12265-022-10332-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 10/10/2022] [Indexed: 11/26/2022]
Abstract
Cardiac surgery with extracorporeal circulation is considered to be one of the surgical types with the highest incidence of delayed neurocognitive recovery (DNR), but the mechanism is unclear. Metabolomics technology can be used to understand the early postoperative metabolic profile and find the relationship between serum metabolites and disease. We performed untargeted analyses of postoperative serum metabolites in all surgical groups, as well as serum metabolites in healthy nonsurgical adults, by using liquid chromatography‒mass spectrometry (LC‒MS). DNR after cardiopulmonary bypass surgery occurred in 35% of surgical patients. Sixty-nine metabolites were found to be associated with DNR. Lipids and lipid-like molecules occupy a total of 55 positions. Lipid metabolism occupies an important position in the serum metabolic profile of DNR patients in the early postoperative period. Phosphatidylinositol (PI), sphingomyelin (SM), and phosphatidylglycerol (PG) appear at the highest frequency. Correlation analysis and receiver operator characteristic curve analysis confirmed PI and SM as potential biomarkers for an increased risk of DNR.
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Affiliation(s)
- Jingjing Han
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China
| | - He Huang
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China
| | - Zheng Lei
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China
| | - Rui Pan
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China
| | - Xiaodong Chen
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China
| | - Yu Chen
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China.
| | - Ting Lu
- Department of Anesthesiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Gulou District, Nanjing City, Jiangsu Province, 210029, China.
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Huang SY, Yang YX, Zhang YR, Kuo K, Li HQ, Shen XN, Chen SD, Chen KL, Dong Q, Tan L, Yu JT. Investigating Causal Relations Between Circulating Metabolites and Alzheimer's Disease: A Mendelian Randomization Study. J Alzheimers Dis 2022; 87:463-477. [PMID: 35275550 DOI: 10.3233/jad-220050] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
BACKGROUND Metabolomics is a promising approach that can be used to understand pathophysiological pathways of Alzheimer's disease (AD). However, the causal relationships between metabolism and AD are poorly understood. OBJECTIVE We aimed to investigate the causal association between circulating metabolites and risk of AD through two-sample Mendelian randomization (MR) approach. METHODS Genetic associations with 123 circulating metabolic traits were utilized as exposures. Summary statistics data from International Genomics of Alzheimer's Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD, and 272,244 controls). We utilized inverse-variance weighted method as primary method. RESULTS We found significantly increased risks of developing AD per standard deviation increase in the levels of circulating ApoB (odd ratio[OR] = 3.18; 95% confidence interval[CI]: 1.52-6.66, p = 0.0022), glycoprotein acetyls (OR = 1.21; 95% CI: 1.05-1.39, p = 0.0093), total cholesterol (OR = 2.73; 95% CI: 1.41-5.30, p = 0.0030), and low-density lipoprotein (LDL) cholesterol (OR = 2.34; 95% CI: 1.53-3.57, p = 0.0001). Whereas glutamine (OR = 0.81; 95% CI: 0.71-0.92, p = 0.0011) were significantly associated with lower risk of AD. We also detected causal effects of several different composition of LDL fractions on increased AD risk, which has been verified in validation. However, we found no association between circulating high-density lipoprotein cholesterol and AD. CONCLUSION Our findings suggest causal effects of circulating glycoprotein acetyls, ApoB, LDL cholesterol, and serum total cholesterol on higher risk of AD, whereas glutamine showed the protective effect.
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Affiliation(s)
- Shu-Yi Huang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Yu-Xiang Yang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Ya-Ru Zhang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Kevin Kuo
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Hong-Qi Li
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Shi-Dong Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Ke-Liang Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, China
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Watanabe Y, Kasuga K, Tokutake T, Kitamura K, Ikeuchi T, Nakamura K. Alterations in Glycerolipid and Fatty Acid Metabolic Pathways in Alzheimer's Disease Identified by Urinary Metabolic Profiling: A Pilot Study. Front Neurol 2021; 12:719159. [PMID: 34777195 PMCID: PMC8578168 DOI: 10.3389/fneur.2021.719159] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 10/06/2021] [Indexed: 11/13/2022] Open
Abstract
An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) is needed. Evidence suggests that metabolic dysfunction underlies the pathophysiology of AD. While urine is a non-invasively collectable biofluid and a good source for metabolomics analysis, it is not yet widely used for this purpose. This small-scale pilot study aimed to examine whether the metabolic profile of urine from AD patients reflects the metabolic dysfunction reported to underlie AD pathology, and to identify metabolites that could distinguish AD patients from cognitively healthy controls. Spot urine of 18 AD patients (AD group) and 18 age- and sex-matched, cognitively normal controls (control group) were analyzed by mass spectrometry (MS). Capillary electrophoresis time-of-flight MS and liquid chromatography–Fourier transform MS were used to cover a larger range of molecules with ionic as well as lipid characteristics. A total of 304 ionic molecules and 81 lipid compounds of 12 lipid classes were identified. Of these, 26 molecules showed significantly different relative concentrations between the AD and control groups (Wilcoxon's rank-sum test). Moreover, orthogonal partial least-squares discriminant analysis revealed significant discrimination between the two groups. Pathway searches using the KEGG database, and pathway enrichment and topology analysis using Metaboanalyst software, suggested alterations in molecules relevant to pathways of glycerolipid and glycerophospholipid metabolism, thermogenesis, and caffeine metabolism in AD patients. Further studies of urinary metabolites will contribute to the early detection of AD and understanding of its pathogenesis.
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Affiliation(s)
- Yumi Watanabe
- Division of Preventive Medicine, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Takayoshi Tokutake
- Department of Neurology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kaori Kitamura
- Division of Preventive Medicine, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kazutoshi Nakamura
- Division of Preventive Medicine, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
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Yan X, Zhao X, Zhou Z, McKay A, Brunet A, Zare RN. Cell-Type-Specific Metabolic Profiling Achieved by Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Immunofluorescence Staining. Anal Chem 2020; 92:13281-13289. [PMID: 32880432 PMCID: PMC8782277 DOI: 10.1021/acs.analchem.0c02519] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Cell-type-specific metabolic profiling in tissue with heterogeneous composition has been of great interest across all mass spectrometry imaging (MSI) technologies. We report here a powerful new chemical imaging capability in desorption electrospray ionization (DESI) MSI, which enables cell-type-specific and in situ metabolic profiling in complex tissue samples. We accomplish this by combining DESI-MSI with immunofluorescence staining using specific cell-type markers. We take advantage of the variable frequency of each distinct cell type in the lateral septal nucleus (LSN) region of mouse forebrain. This allows computational deconvolution of the cell-type-specific metabolic profile in neurons and astrocytes by convex optimization-a machine learning method. Based on our approach, we observed 107 metabolites that show different distributions and intensities between astrocytes and neurons. We subsequently identified 23 metabolites using high-resolution mass spectrometry (MS) and tandem MS, which include small metabolites such as adenosine and N-acetylaspartate previously associated with astrocytes and neurons, respectively, as well as accumulation of several phospholipid species in neurons which have not been studied before. Overall, this method overcomes the relatively low spatial resolution of DESI-MSI and provides a new platform for in situ metabolic investigation at the cell-type level in complex tissue samples with heterogeneous cell-type composition.
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Affiliation(s)
- Xin Yan
- Department of Chemistry, Texas A&M University, College Station, TX 77843.; Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Xiaoai Zhao
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Zhenpeng Zhou
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Andrew McKay
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Anne Brunet
- Glenn Laboratories for the Biology of Aging, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Richard N. Zare
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
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7
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Abstract
Cerebrospinal fluid (CSF) has been considered the key source for the search of biomarkers, in particular for neurological diseases, such as Alzheimer's and Parkinson's disease, since it reflects the state of the central nervous system (CNS). Finding biomarkers in the earliest stages of neurodegenerative diseases has become imperative, since, at the moment, there are no drugs that can reverse these pathological processes. Untargeted metabolomics analysis by liquid chromatography combined with SWATH-MS relative quantification is an emerging approach to search for potential biomarkers. In this chapter, we describe a method for untargeted metabolomics analysis of CSF samples that can also be used in parallel to a proteomics approach. The analysis is focused on the SWATH acquisition mode, where beyond precursor's relative quantification, the information of the MS/MS relative quantification is also used to help in the search of new potential biomarkers.
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Peterson MJ, Geoghegan S, Lawhorne LW. An Exploratory Analysis of Potential New Biomarkers of Cognitive Function. J Gerontol A Biol Sci Med Sci 2019; 74:299-305. [PMID: 29846522 DOI: 10.1093/gerona/gly122] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Indexed: 12/23/2022] Open
Abstract
We examined the relationship between serially measured, novel serum biomarkers and a measure of cognitive functioning in older adults. We assayed stored serum samples from two Fels Longitudinal Study visits in N = 100 adult participants (visit 1 ages 59.3 ± 8.5 years; 53% female), and Montreal Cognitive Assessment (MoCA) scores also assessed at the second visit. Assays included acylcarnitines, amino acids, and 2-hydroxybutyric acid (b-HBA). Cross-sectional correlations between acylcarnitines and amino acids and MoCA were identified. Serial change in short-chain acylcarnitines and visit 2 MoCA were also correlated. Participants with MoCA scores <26 were more likely to have an increase in short-chain acylcarnitines between visits 1 and 2 [adjusted odds ratio (OR) = 5.24; 95% confidence interval (CI) 1.07-25.9]. b-HBA was also correlated with acylcarnitines. Several cross-sectional and serial associations between novel serum biomarkers and cognitive functioning were identified. b-HBA may also be a cost-effective marker of dysregulation associated with cognitive decline.
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Affiliation(s)
- Matthew J Peterson
- Department of Geriatrics, Boonshoft School of Medicine, Wright State University, Dayton, Ohio
| | - Sheena Geoghegan
- Department of Geriatrics, Boonshoft School of Medicine, Wright State University, Dayton, Ohio
| | - Larry W Lawhorne
- Department of Geriatrics, Boonshoft School of Medicine, Wright State University, Dayton, Ohio
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D'Andrea G, Pizzolato G, Gucciardi A, Stocchero M, Giordano G, Baraldi E, Leon A. Different Circulating Trace Amine Profiles in De Novo and Treated Parkinson's Disease Patients. Sci Rep 2019; 9:6151. [PMID: 30992490 PMCID: PMC6467876 DOI: 10.1038/s41598-019-42535-w] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Accepted: 03/29/2019] [Indexed: 12/18/2022] Open
Abstract
Early diagnosis of Parkinson’s disease (PD) remains a challenge to date. New evidence highlights the potential clinical value of circulating trace amines (TAs) in early-stage PD and their involvement in disease progression. A new ultra performance chromatography mass spectrometry (UPLC-MS/MS) method was developed to quantify plasmatic TAs, and the catecholamines and indolamines pertaining to the same biochemical pathways. Three groups of subjects were recruited: 21 de novo, drug untreated, PD patients, 27 in treatment PD patients and 10 healthy subjects as controls. Multivariate and univariate data analyses were applied to reveal metabolic changes among the groups in attempt to discover new putative markers for early PD detection and disease progression. Different circulating levels of tyrosine (p = 0.002), tyramine (p < 0.001), synephrine (p = 0.015), norepinephrine (p = 0.012), metanephrine (p = 0.001), β-phenylethylamine (p = 0.001) and serotonin (p = 0.006) were found among the three groups. While tyramine behaves as a putative biomarker for early-stage PD (AUC = 0.90) tyramine, norepinephrine, and tyrosine appear to act as biomarkers of disease progression (AUC > 0.75). The findings of this pilot cross-sectional study suggest that biochemical anomalies of the aminergic and indolic neurotransmitters occur in PD patients. Compounds within the TAs family may constitute putative markers for early stage detection and progression of PD.
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Affiliation(s)
| | - Gilberto Pizzolato
- Department of Medical Sciences, Neurology Unit, University of Trieste, Trieste, Italy
| | - Antonina Gucciardi
- Mass Spectrometry and Metabolomic Laboratory, Women's and Children's Health Department, University of Padova, Padova, Italy. .,Fondazione Istituto di Ricerca Pediatrica Cittàdella Speranza, Padova, Italy.
| | - Matteo Stocchero
- Mass Spectrometry and Metabolomic Laboratory, Women's and Children's Health Department, University of Padova, Padova, Italy.,Fondazione Istituto di Ricerca Pediatrica Cittàdella Speranza, Padova, Italy
| | - Giuseppe Giordano
- Mass Spectrometry and Metabolomic Laboratory, Women's and Children's Health Department, University of Padova, Padova, Italy.,Fondazione Istituto di Ricerca Pediatrica Cittàdella Speranza, Padova, Italy
| | - Eugenio Baraldi
- Mass Spectrometry and Metabolomic Laboratory, Women's and Children's Health Department, University of Padova, Padova, Italy.,Fondazione Istituto di Ricerca Pediatrica Cittàdella Speranza, Padova, Italy
| | - Alberta Leon
- Research and Innovation (R&I Genetics) s.r.l., Padova, Italy
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10
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Luan H, Wang X, Cai Z. Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders. MASS SPECTROMETRY REVIEWS 2019; 38:22-33. [PMID: 29130504 DOI: 10.1002/mas.21553] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 10/12/2017] [Indexed: 05/10/2023]
Abstract
Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies.
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Affiliation(s)
- Hemi Luan
- Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
| | - Xian Wang
- Key Laboratory of Analytical Chemistry of State Ethnic Affairs Commission, College of Chemistry and Materials Science, South-Central University for Nationalities, Wuhan, Hubei, China
| | - Zongwei Cai
- Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
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Bourgognon JM, Steinert JR. The metabolome identity: basis for discovery of biomarkers in neurodegeneration. Neural Regen Res 2019; 14:387-390. [PMID: 30539802 PMCID: PMC6334598 DOI: 10.4103/1673-5374.245464] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Neurodegenerative disorders are often associated with cellular dysfunction caused by underlying protein-misfolding signalling. Numerous neuropathologies are diagnosed at late stage symptomatic changes which occur in response to these molecular malfunctions and treatment is often too late or restricted only to the slowing of further cell death. Important new strategies to identify early biomarkers with predictive value to intervene with disease progression at stages where cell dysfunction has not progressed irreversibly is of paramount importance. Thus, the identification of these markers presents an essential opportunity to identify and target disease pathways. This review highlights some important metabolic alterations detected in neurodegeneration caused by misfolded prion protein and discusses common toxicity pathways identified across different neurodegenerative diseases. Thus, having established some commonalities between various degenerative conditions, detectable metabolic changes may be of extreme value as an early diagnostic biomarker in disease.
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Affiliation(s)
| | - Joern R Steinert
- MRC Toxicology Unit, University of Leicester, Lancaster Road, Leicester, UK
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12
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Teunissen CE, Otto M, Engelborghs S, Herukka SK, Lehmann S, Lewczuk P, Lleó A, Perret-Liaudet A, Tumani H, Turner MR, Verbeek MM, Wiltfang J, Zetterberg H, Parnetti L, Blennow K. White paper by the Society for CSF Analysis and Clinical Neurochemistry: Overcoming barriers in biomarker development and clinical translation. ALZHEIMERS RESEARCH & THERAPY 2018; 10:30. [PMID: 29544527 PMCID: PMC5855933 DOI: 10.1186/s13195-018-0359-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 02/20/2018] [Indexed: 12/27/2022]
Abstract
Body fluid biomarkers have great potential for different clinical purposes, including diagnosis, prognosis, patient stratification and treatment effect monitoring. This is exemplified by current use of several excellent biomarkers, such as the Alzheimer’s disease cerebrospinal fluid (CSF) biomarkers, anti-neuromyelitis optica antibodies and blood neurofilament light. We still, however, have a strong need for additional biomarkers and several gaps in their development and implementation should be filled. Examples of such gaps are i) limited knowledge of the causes of neurological diseases, and thus hypotheses about the best biomarkers to detect subclinical stages of these diseases; ii) the limited success translating discoveries obtained by e.g. initial mass spectrometry proteomic low-throughput studies into immunoassays for widespread clinical implementation; iii) lack of interaction among all stakeholders to optimise and adapt study designs throughout the biomarker development process to medical needs, which may change during the long period needed for biomarker development. The Society for CSF Analysis and Clinical Neurochemistry (established in 2015) has been founded as a concerted follow-up of large standardisation projects, including BIOMARKAPD and SOPHIA, and the BioMS-consortium. The main aims of the CSF society are to exchange high level international scientific experience, to facilitate the incorporation of CSF diagnostics into clinical practice and to give advice on inclusion of CSF analysis into clinical guidelines. The society has a broad scope, as its vision is that the gaps in development and implementation of biomarkers are shared among almost all neurological diseases and thus they can benefit from the activities of the society.
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Affiliation(s)
- Charlotte E Teunissen
- Neurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, Amsterdam, The Netherlands.
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Sanna-Kaisa Herukka
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Sylvain Lehmann
- Université de Montpellier, University Hospital, INSERM U1183, Montpellier, France
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, Erlangen, Germany.,Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Neurodegeneration Diagnostics, Medical University of Białystok, Białystok, Poland.,Department of Biochemical Diagnostics, University Hospital of Białystok, Białystok, Poland
| | - Alberto Lleó
- Memory Unit, Department of Neurology, Institut d'Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Armand Perret-Liaudet
- Neurobiology Laboratory, Department of Biochemistry and Molecular Biology, Hospices Civils de Lyon, Lyon, France.,University of Lyon 1, CNRS UMR5292, INSERM U1028, BioRan, Lyon, France
| | - Hayrettin Tumani
- Department of Neurology, CSF Laboratory, MS Outpatient Unit, University Hospital of Ulm, Ulm, Germany.,Specialty Hospital of Neurology Dietenbronn, Acadamic Hospital of University of Ulm, Schwendi, Germany
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Marcel M Verbeek
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Departments of Neurology and Laboratory Medicine, Radboud Alzheimer Centre, Nijmegen, The Netherlands
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August University, Goettingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany.,iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Lucilla Parnetti
- Center for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
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13
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Havelund JF, Heegaard NHH, Færgeman NJK, Gramsbergen JB. Biomarker Research in Parkinson's Disease Using Metabolite Profiling. Metabolites 2017; 7:E42. [PMID: 28800113 PMCID: PMC5618327 DOI: 10.3390/metabo7030042] [Citation(s) in RCA: 97] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Revised: 08/08/2017] [Accepted: 08/09/2017] [Indexed: 01/08/2023] Open
Abstract
Biomarker research in Parkinson's disease (PD) has long been dominated by measuring dopamine metabolites or alpha-synuclein in cerebrospinal fluid. However, these markers do not allow early detection, precise prognosis or monitoring of disease progression. Moreover, PD is now considered a multifactorial disease, which requires a more precise diagnosis and personalized medication to obtain optimal outcome. In recent years, advanced metabolite profiling of body fluids like serum/plasma, CSF or urine, known as "metabolomics", has become a powerful and promising tool to identify novel biomarkers or "metabolic fingerprints" characteristic for PD at various stages of disease. In this review, we discuss metabolite profiling in clinical and experimental PD. We briefly review the use of different analytical platforms and methodologies and discuss the obtained results, the involved metabolic pathways, the potential as a biomarker and the significance of understanding the pathophysiology of PD. Many of the studies report alterations in alanine, branched-chain amino acids and fatty acid metabolism, all pointing to mitochondrial dysfunction in PD. Aromatic amino acids (phenylalanine, tyrosine, tryptophan) and purine metabolism (uric acid) are also altered in most metabolite profiling studies in PD.
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Affiliation(s)
- Jesper F Havelund
- Villum Centre for Bioanalytical Sciences, Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense, Denmark.
| | - Niels H H Heegaard
- Department of Autoimmunology and Biomarkers, Statens Serum Institute, DK-2300 Copenhagen, Denmark.
- Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, University of Southern Denmark, DK-5000 Odense, Denmark.
| | - Nils J K Færgeman
- Villum Centre for Bioanalytical Sciences, Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense, Denmark.
| | - Jan Bert Gramsbergen
- Institute of Molecular Medicine, University of Southern Denmark, DK-5000 Odense, Denmark.
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