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van der Velpen V, Teav T, Gallart-Ayala H, Mehl F, Konz I, Clark C, Oikonomidi A, Peyratout G, Henry H, Delorenzi M, Ivanisevic J, Popp J. Systemic and central nervous system metabolic alterations in Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2019; 11:93. [PMID: 31779690 PMCID: PMC6883620 DOI: 10.1186/s13195-019-0551-7] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 10/30/2019] [Indexed: 12/12/2022]
Abstract
Background Metabolic alterations, related to cerebral glucose metabolism, brain insulin resistance, and age-induced mitochondrial dysfunction, play an important role in Alzheimer’s disease (AD) on both the systemic and central nervous system level. To study the extent and significance of these alterations in AD, quantitative metabolomics was applied to plasma and cerebrospinal fluid (CSF) from clinically well-characterized AD patients and cognitively healthy control subjects. The observed metabolic alterations were associated with core pathological processes of AD to investigate their relation with amyloid pathology and tau-related neurodegeneration. Methods In a case-control study of clinical and biomarker-confirmed AD patients (n = 40) and cognitively healthy controls without cerebral AD pathology (n = 34) with paired plasma and CSF samples, we performed metabolic profiling, i.e., untargeted metabolomics and targeted quantification. Targeted quantification focused on identified deregulated pathways highlighted in the untargeted assay, i.e. the TCA cycle, and its anaplerotic pathways, as well as the neuroactive tryptophan and kynurenine pathway. Results Concentrations of several TCA cycle and beta-oxidation intermediates were higher in plasma of AD patients, whilst amino acid concentrations were significantly lower. Similar alterations in these energy metabolism intermediates were observed in CSF, together with higher concentrations of creatinine, which were strongly correlated with blood-brain barrier permeability. Alterations of several amino acids were associated with CSF Amyloidβ1–42. The tryptophan catabolites, kynurenic acid and quinolinic acid, showed significantly higher concentrations in CSF of AD patients, which, together with other tryptophan pathway intermediates, were correlated with either CSF Amyloidβ1–42, or tau and phosphorylated Tau-181. Conclusions This study revealed AD-associated systemic dysregulation of nutrient sensing and oxidation and CNS-specific alterations in the neuroactive tryptophan pathway and (phospho)creatine degradation. The specific association of amino acids and tryptophan catabolites with AD CSF biomarkers suggests a close relationship with core AD pathology. Our findings warrant validation in independent, larger cohort studies as well as further investigation of factors such as gender and APOE genotype, as well as of other groups, such as preclinical AD, to identify metabolic alterations as potential intervention targets.
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Affiliation(s)
- Vera van der Velpen
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.,Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Tony Teav
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Héctor Gallart-Ayala
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Florence Mehl
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Ioana Konz
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | | | - Aikaterini Oikonomidi
- Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausane, Switzerland
| | - Gwendoline Peyratout
- Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausane, Switzerland
| | - Hugues Henry
- Clinical Chemistry Laboratory, Department of Biomedicine, Lausanne University Hospital, Lausane, Switzerland
| | - Mauro Delorenzi
- Translational Bioinformatics and Statistics, Department of Oncology, Swiss Cancer Center Leman (SCCL), University of Lausanne, Lausanne, Switzerland.,Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Julijana Ivanisevic
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
| | - Julius Popp
- Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausane, Switzerland. .,Department of Psychiatry, University of Geneva, Geneva, Switzerland.
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Shen L, Xia S, Zhang H, Yao F, Liu X, Zhao Y, Ying M, Iqbal J, Liu Q. Precision Medicine: Role of Biomarkers in Early Prediction and Diagnosis of Alzheimer’s Disease. Mol Med 2019. [DOI: 10.5772/intechopen.82035] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
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253
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Fujii Y, Nguyen TTT, Fujimura Y, Kameya N, Nakamura S, Arakawa K, Morita H. Fecal metabolite of a gnotobiotic mouse transplanted with gut microbiota from a patient with Alzheimer’s disease. Biosci Biotechnol Biochem 2019; 83:2144-2152. [DOI: 10.1080/09168451.2019.1644149] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
ABSTRACT
Studies of Alzheimer’s disease are based on model mice that have been altered by transgenesis and other techniques to elicit pathogenesis. However, changes in the gut microbiota were recently suggested to diminish cognitive function in patients, as well as in model mice. Accordingly, we have created model mice of the human gut microbiota by transplanting germ-free C57BL/6N mice with fecal samples from a healthy volunteer and from an affected patient. These humanized mice were stably colonized and reproduced the bacterial diversity in donors. Remarkably, performance on Object Location Test and Object Recognition Test was significantly reduced in the latter than in the former at 55 weeks of age, suggesting that gut microbiota transplanted from an affected patient affects mouse behavior. In addition, metabolites related to the nervous system, including γ-aminobutyrate, taurine, and valine, were significantly less abundant in the feces of mice transplanted with microbiota from the affected patient.
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Affiliation(s)
- Yusuke Fujii
- Graduate School of Environmental and Life Science, Okayama University, Okayama, Japan
- Fundamental Laboratory, Ohayo Dairy Products Co., Ltd., Okayama, Japan
| | - Thuy Tien Thi Nguyen
- Graduate School of Environmental and Life Science, Okayama University, Okayama, Japan
- College of Agriculture and Forestry, Hue University, Hue, Vietnam
| | - Yuta Fujimura
- Graduate School of Environmental and Life Science, Okayama University, Okayama, Japan
| | - Naotaka Kameya
- Sales/marketing Division, Human Metabolome Technologies Inc., Tsuruoka, Japan
| | - Shoji Nakamura
- Fundamental Laboratory, Ohayo Dairy Products Co., Ltd., Okayama, Japan
| | - Kensuke Arakawa
- Graduate School of Environmental and Life Science, Okayama University, Okayama, Japan
| | - Hidetoshi Morita
- Graduate School of Environmental and Life Science, Okayama University, Okayama, Japan
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254
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Li KW, Ganz AB, Smit AB. Proteomics of neurodegenerative diseases: analysis of human post-mortem brain. J Neurochem 2019; 151:435-445. [PMID: 30289976 PMCID: PMC6899881 DOI: 10.1111/jnc.14603] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 08/15/2018] [Accepted: 10/01/2018] [Indexed: 12/12/2022]
Abstract
Dementias are prevalent brain disorders in the aged population. Dementias pose major socio-medical burden, but currently there is no cure available. Novel proteomics approaches hold promise to identify alterations of the brain proteome that could provide clues on disease etiology, and identify candidate proteins to develop further as a biomarker. In this review, we focus on recent proteomics findings from brains affected with Alzheimer's Disease, Parkinson Disease Dementia, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. These studies confirmed known cellular changes, and in addition identified novel proteins that may underlie distinct aspects of the diseases. This article is part of the special issue "Proteomics".
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Affiliation(s)
- K. W. Li
- Department of Molecular and Cellular NeurobiologyCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVrije UniversiteitAmsterdamThe Netherlands
| | - Andrea B. Ganz
- Department of Molecular and Cellular NeurobiologyCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVrije UniversiteitAmsterdamThe Netherlands
| | - August B. Smit
- Department of Molecular and Cellular NeurobiologyCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVrije UniversiteitAmsterdamThe Netherlands
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St John-Williams L, Mahmoudiandehkordi S, Arnold M, Massaro T, Blach C, Kastenmüller G, Louie G, Kueider-Paisley A, Han X, Baillie R, Motsinger-Reif AA, Rotroff D, Nho K, Saykin AJ, Risacher SL, Koal T, Moseley MA, Tenenbaum JD, Thompson JW, Kaddurah-Daouk R. Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts. Sci Data 2019; 6:212. [PMID: 31624257 PMCID: PMC6797798 DOI: 10.1038/s41597-019-0181-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 07/10/2019] [Indexed: 12/28/2022] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.
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Affiliation(s)
- Lisa St John-Williams
- Proteomics and Metabolomics Shared Resource, Center for Genomics and Computational Biology, Duke University, Durham, NC, USA
| | | | - Matthias Arnold
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, USA
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Tyler Massaro
- Duke Clinical Research Institute, Duke University, Durham, NC, USA
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Gregory Louie
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, USA
| | | | - Xianlin Han
- University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | | | - Alison A Motsinger-Reif
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC, USA
| | - Daniel Rotroff
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - M Arthur Moseley
- Proteomics and Metabolomics Shared Resource, Center for Genomics and Computational Biology, Duke University, Durham, NC, USA
| | - Jessica D Tenenbaum
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - J Will Thompson
- Proteomics and Metabolomics Shared Resource, Center for Genomics and Computational Biology, Duke University, Durham, NC, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, USA.
- Duke Institute for Brain Sciences, Duke University, Durham, NC, USA.
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Cuperlovic-Culf M, Badhwar A. Recent advances from metabolomics and lipidomics application in alzheimer's disease inspiring drug discovery. Expert Opin Drug Discov 2019; 15:319-331. [PMID: 31619081 DOI: 10.1080/17460441.2020.1674808] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction: Although age is a major risk factor for Alzheimer's disease (AD), it is not an inevitable consequence of aging nor is it exclusively an old-age disease. Several other major risk factors for AD are strongly associated with metabolism and include lack of exercise, obesity, diabetes, high blood pressure and cholesterol, over-consumption of alcohol and depression in addition to low educational level, social isolation, and cognitive inactivity. Approaches for Alzheimer prevention and treatment through manipulation of metabolism and utilization of active metabolites have great potential either as a primary or secondary treatment avenue or as a preventative strategy in high-risk individuals.Areas covered: This review outlines the current knowledge concerning the relationship between AD and metabolism and the novel treatments attempting to correct changes in AD patients determined through metabolomics or lipidomic analyses.Expert opinion: Metabolites are one of the main driving factors and indicators of AD and can offer many possible avenues for prevention and treatment. However, with the highly interconnected effects of metabolites and metabolism, as well as the many different routes for metabolism dysfunction, successful treatment would have to include the correction of metabolic errors as well as errors in transport and metabolite processing in order to affect and revert AD progression.
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Affiliation(s)
| | - Amanpreet Badhwar
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, Canada
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Fleszar MG, Wiśniewski J, Zboch M, Diakowska D, Gamian A, Krzystek-Korpacka M. Targeted metabolomic analysis of nitric oxide/L-arginine pathway metabolites in dementia: association with pathology, severity, and structural brain changes. Sci Rep 2019; 9:13764. [PMID: 31551443 PMCID: PMC6760237 DOI: 10.1038/s41598-019-50205-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 09/05/2019] [Indexed: 12/16/2022] Open
Abstract
L-Arginine/NO pathway is altered in Alzheimer disease (AD). Its clinical relevance and pathway status in vascular dementia (VaD) are unknown. Using targeted metabolomics (a liquid chromatography-mass spectrometry) we assessed L-arginine, L-citrulline, dimethylamine (DMA), asymmetric dimethyl arginine (ADMA) and symmetric dimethylarginine (SDMA) in AD (n = 48), mixed-type dementia (MD; n = 34), VaD (n = 40) and non-demented individuals (n = 140) and determined their clinical relevance (the association with dementia pathology, cognitive impairment, and structural brain damage). L-Arginine, ADMA, L-arginine/ADMA, and L-citrulline levels were decreased in dementia and L-arginine, L-citrulline, age and sex were its independent predictors correctly classifying 91% of cases. L-Arginine and L-arginine/ADMA were differentiating between VaD and AD with moderate accuracy. L-Arginine, L-arginine/ADMA, SDMA, and DMA reflected structural brain changes. DMA and L-citrulline were elevated in patients with strategic infarcts and SDMA, L-arginine/ADMA, and DMA were independent predictors of Hachinski ischemic score. ADMA and SDMA accumulation reflected severity of cognitive impairment. In summary, L-Arginine/NO pathway is altered in neurodegenerative and vascular dementia in association with neurodegenerative and vascular markers of brain damage and severity of cognitive impairment.
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Affiliation(s)
- Mariusz G Fleszar
- Department of Medical Biochemistry, Wroclaw Medical University, 50-368, Wroclaw, Poland
- PORT Polski Ośrodek Rozwoju Technologii sp. z o.o., 54-066, Wrocław, Poland
| | - Jerzy Wiśniewski
- Department of Medical Biochemistry, Wroclaw Medical University, 50-368, Wroclaw, Poland
| | - Marzena Zboch
- Research, Scientific, and Educational Center for Dementia Diseases of Wroclaw Medical University, 59-330, Ścinawa, Poland
| | - Dorota Diakowska
- Department of Nervous System Diseases, Wroclaw Medical University, 51-618, Wroclaw, Poland
| | - Andrzej Gamian
- Department of Medical Biochemistry, Wroclaw Medical University, 50-368, Wroclaw, Poland
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Barupal DK, Baillie R, Fan S, Saykin AJ, Meikle PJ, Arnold M, Nho K, Fiehn O, Kaddurah-Daouk R. Sets of coregulated serum lipids are associated with Alzheimer's disease pathophysiology. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:619-627. [PMID: 31517024 PMCID: PMC6732667 DOI: 10.1016/j.dadm.2019.07.002] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction Comorbidity with metabolic diseases indicates that lipid metabolism plays a role in the etiology of Alzheimer's disease (AD). Comprehensive lipidomic analysis can provide new insights into the altered lipid metabolism in AD. Method In this study, a total 349 serum lipids were measured in 806 participants enrolled in the Alzheimer's Disease Neuroimaging Initiative Phase 1 cohort and analyzed using lipid-set enrichment statistics, a data mining method to find coregulated lipid sets. Results We found that sets of blood lipids were associated with current AD biomarkers and with AD clinical symptoms. AD diagnosis was associated with 7 of 28 lipid sets of which four also correlated with cognitive decline, including polyunsaturated fatty acids. Cerebrospinal fluid amyloid beta (Aβ1-42) correlated with glucosylceramides, lysophosphatidylcholines and unsaturated triacylglycerides; cerebrospinal fluid total tau and brain atrophy correlated with monounsaturated sphingomyelins and ceramides, in addition to EPA-containing lipids. Discussion AD-associated lipid sets indicated that lipid desaturation, elongation, and acyl chain remodeling processes are disturbed in AD subjects. Monounsaturated lipid metabolism was important in early stages of AD, whereas the polyunsaturated lipid metabolism was associated with later stages of AD. Our study provides several new hypotheses for studying the role of lipid metabolism in AD. Twenty eight coregulatory lipid sets are identified in Alzheimer's Disease Neuroimaging Initiative lipidomics data. Distinct lipid pathways are associated with cerebrospinal fluid biomarkers, brain atrophy, and Alzheimer's disease (AD) diagnosis. Monounsaturated lipids play a role in the AD initiation and early neurodegeneration. Polyunsaturated lipids are associated with AD diagnosis.
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Affiliation(s)
- Dinesh Kumar Barupal
- NIH-West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
| | | | - Sili Fan
- NIH-West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
| | - Andrew J. Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Medical and Molecular Genetics Department, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter J. Meikle
- Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Matthias Arnold
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Oliver Fiehn
- NIH-West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
- Corresponding author. Tel.: +1-530-754-8258; Fax: +1-530-754-9658.
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Department of Medicine and the Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
- Corresponding author. Tel.: +1-919-684-2611; Fax: +1-919-681-7668.
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Xicota L, Ichou F, Lejeune FX, Colsch B, Tenenhaus A, Leroy I, Fontaine G, Lhomme M, Bertin H, Habert MO, Epelbaum S, Dubois B, Mochel F, Potier MC. Multi-omics signature of brain amyloid deposition in asymptomatic individuals at-risk for Alzheimer's disease: The INSIGHT-preAD study. EBioMedicine 2019; 47:518-528. [PMID: 31492558 PMCID: PMC6796577 DOI: 10.1016/j.ebiom.2019.08.051] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 08/23/2019] [Accepted: 08/23/2019] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND One of the biggest challenge in Alzheimer's disease (AD) is to identify pathways and markers of disease prediction easily accessible, for prevention and treatment. Here we analysed blood samples from the INveStIGation of AlzHeimer's predicTors (INSIGHT-preAD) cohort of elderly asymptomatic individuals with and without brain amyloid load. METHODS We performed blood RNAseq, and plasma metabolomics and lipidomics using liquid chromatography-mass spectrometry on 48 individuals amyloid positive and 48 amyloid negative (SUVr cut-off of 0·7918). The three data sets were analysed separately using differential gene expression based on negative binomial distribution, non-parametric (Wilcoxon) and parametric (correlation-adjusted Student't) tests. Data integration was conducted using sparse partial least squares-discriminant and principal component analyses. Bootstrap-selected top-ten features from the three data sets were tested for their discriminant power using Receiver Operating Characteristic curve. Longitudinal metabolomic analysis was carried out on a subset of 22 subjects. FINDINGS Univariate analyses identified three medium chain fatty acids, 4-nitrophenol and a set of 64 transcripts enriched for inflammation and fatty acid metabolism differentially quantified in amyloid positive and negative subjects. Importantly, the amounts of the three medium chain fatty acids were correlated over time in a subset of 22 subjects (p < 0·05). Multi-omics integrative analyses showed that metabolites efficiently discriminated between subjects according to their amyloid status while lipids did not and transcripts showed trends. Finally, the ten top metabolites and transcripts represented the most discriminant omics features with 99·4% chance prediction for amyloid positivity. INTERPRETATION This study suggests a potential blood omics signature for prediction of amyloid positivity in asymptomatic at-risk subjects, allowing for a less invasive, more accessible, and less expensive risk assessment of AD as compared to PET studies or lumbar puncture. FUND: Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epiniere (IHU-A-ICM), French Ministry of Research, Fondation Alzheimer, Pfizer, and Avid.
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Affiliation(s)
- Laura Xicota
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France
| | - Farid Ichou
- ICANalytcis Platforms, Institute of Cardiometabolism and Nutrition ICAN, Paris, France
| | - François-Xavier Lejeune
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France
| | - Benoit Colsch
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay, MetaboHUB, Gif-sur-Yvette, France
| | - Arthur Tenenhaus
- Laboratoire des Signaux et Systèmes, CentraleSupélec, Université Paris-Saclay, Gif sur Yvette, France
| | - Inka Leroy
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France
| | - Gaëlle Fontaine
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France
| | - Marie Lhomme
- ICANalytcis Platforms, Institute of Cardiometabolism and Nutrition ICAN, Paris, France
| | - Hugo Bertin
- Centre Acquisition et Traitement des Images, Paris, France
| | - Marie-Odile Habert
- Laboratoire d'Imagerie Biomédicale, Nuclear Medicine Department, Sorbonne Université, Hôpital de la Salpêtrière, Paris, France
| | - Stéphane Epelbaum
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France; Centre des Maladies Cognitives et Comportementales, Sorbonne Université, Hôpital de la Salpêtrière, Paris, France; Inria, Aramis-Project Team, Paris, France
| | - Bruno Dubois
- Centre des Maladies Cognitives et Comportementales, Sorbonne Université, Hôpital de la Salpêtrière, Paris, France
| | - Fanny Mochel
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France.
| | - Marie-Claude Potier
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France.
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Perez Ortiz JM, Swerdlow RH. Mitochondrial dysfunction in Alzheimer's disease: Role in pathogenesis and novel therapeutic opportunities. Br J Pharmacol 2019; 176:3489-3507. [PMID: 30675901 PMCID: PMC6715612 DOI: 10.1111/bph.14585] [Citation(s) in RCA: 255] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Accepted: 12/07/2018] [Indexed: 12/13/2022] Open
Abstract
Dysfunction of cell bioenergetics is a common feature of neurodegenerative diseases, the most common of which is Alzheimer's disease (AD). Disrupted energy utilization implicates mitochondria at its nexus. This review summarizes some of the evidence that points to faulty mitochondrial function in AD and highlights past and current therapeutic development efforts. Classical neuropathological hallmarks of disease (β-amyloid and τ) and sporadic AD risk genes (APOE) may trigger mitochondrial disturbance, yet mitochondrial dysfunction may incite pathology. Preclinical and clinical efforts have overwhelmingly centred on the amyloid pathway, but clinical trials have yet to reveal clear-cut benefits. AD therapies aimed at mitochondrial dysfunction are few and concentrate on reversing oxidative stress and cell death pathways. Novel research efforts aimed at boosting mitochondrial and bioenergetic function offer an alternative treatment strategy. Enhancing cell bioenergetics in preclinical models may yield widespread favourable effects that could benefit persons with AD. LINKED ARTICLES: This article is part of a themed section on Therapeutics for Dementia and Alzheimer's Disease: New Directions for Precision Medicine. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.18/issuetoc.
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Affiliation(s)
- Judit M. Perez Ortiz
- University of Kansas Alzheimer's Disease CenterFairwayKSUSA
- Department of NeurologyUniversity of Kansas Medical CenterKansas CityKSUSA
| | - Russell H. Swerdlow
- University of Kansas Alzheimer's Disease CenterFairwayKSUSA
- Department of NeurologyUniversity of Kansas Medical CenterKansas CityKSUSA
- Department of Molecular and Integrative PhysiologyUniversity of Kansas Medical CenterKansas CityKSUSA
- Department of Biochemistry and Molecular BiologyUniversity of Kansas Medical CenterKansas CityKSUSA
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Low DY, Lefèvre‐Arbogast S, González‐Domínguez R, Urpi‐Sarda M, Micheau P, Petera M, Centeno D, Durand S, Pujos‐Guillot E, Korosi A, Lucassen PJ, Aigner L, Proust‐Lima C, Hejblum BP, Helmer C, Andres‐Lacueva C, Thuret S, Samieri C, Manach C. Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort. Mol Nutr Food Res 2019; 63:e1900177. [PMID: 31218777 PMCID: PMC6790579 DOI: 10.1002/mnfr.201900177] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/24/2019] [Indexed: 12/21/2022]
Abstract
SCOPE Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome. METHODS AND RESULTS A case-control study nested in the prospective Three-City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium-chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE-ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross-validated Area Under the Receiver Operating Curve = 75% [95% CI 70-80%] compared to 62% [95% CI 56-67%]. CONCLUSIONS The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging.
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Affiliation(s)
- Dorrain Yanwen Low
- Human Nutrition UnitINRA, Université Clermont AuvergneF‐63000Clermont‐FerrandFrance
| | - Sophie Lefèvre‐Arbogast
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | - Raúl González‐Domínguez
- Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)Instituto de Salud Carlos IIIUniversity of BarcelonaAv Joan XXIII 27–3108028BarcelonaSpain
| | - Mireia Urpi‐Sarda
- Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)Instituto de Salud Carlos IIIUniversity of BarcelonaAv Joan XXIII 27–3108028BarcelonaSpain
| | - Pierre Micheau
- Human Nutrition UnitINRA, Université Clermont AuvergneF‐63000Clermont‐FerrandFrance
| | - Melanie Petera
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Delphine Centeno
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Stephanie Durand
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Estelle Pujos‐Guillot
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Aniko Korosi
- Brain Plasticity Group, SILS‐CNSUniversity of AmsterdamScience Park 9041098 XHAmsterdamThe Netherlands
| | - Paul J Lucassen
- Brain Plasticity Group, SILS‐CNSUniversity of AmsterdamScience Park 9041098 XHAmsterdamThe Netherlands
| | - Ludwig Aigner
- Institute of Molecular Regenerative Medicine, Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical UniversitySalzburg5020Austria
| | - Cécile Proust‐Lima
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | | | - Catherine Helmer
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | - Cristina Andres‐Lacueva
- Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)Instituto de Salud Carlos IIIUniversity of BarcelonaAv Joan XXIII 27–3108028BarcelonaSpain
| | - Sandrine Thuret
- Department of Basic and Clinical NeuroscienceMaurice Wohl Neuroscience InstituteInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 9NUUK
| | - Cécilia Samieri
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | - Claudine Manach
- Human Nutrition UnitINRA, Université Clermont AuvergneF‐63000Clermont‐FerrandFrance
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Huan T, Tran T, Zheng J, Sapkota S, MacDonald SW, Camicioli R, Dixon RA, Li L. Metabolomics Analyses of Saliva Detect Novel Biomarkers of Alzheimer's Disease. J Alzheimers Dis 2019; 65:1401-1416. [PMID: 30175979 DOI: 10.3233/jad-180711] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Using a non-invasive biofluid (saliva), we apply a powerful metabolomics workflow for unbiased biomarker discovery in Alzheimer's disease (AD). We profile and differentiate Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD groups. The workflow involves differential chemical isotope labeling liquid chromatography mass spectrometry using dansylation derivatization for in-depth profiling of the amine/phenol submetabolome. The total sample (N = 109) was divided in to the Discovery Phase (DP) (n = 82; 35 CN, 25 MCI, 22 AD) and a provisional Validation Phase (VP) (n = 27; 10 CN, 10 MCI, 7 AD). In DP we detected 6,230 metabolites. Pairwise analyses confirmed biomarkers for AD versus CN (63), AD versus MCI (47), and MCI versus CN (2). We then determined the top discriminating biomarkers and diagnostic panels. A 3-metabolite panel distinguished AD from CN and MCI (DP and VP: Area Under the Curve [AUC] = 1.000). The MCI and CN groups were best discriminated with a 2-metabolite panel (DP: AUC = 0.779; VP: AUC = 0.889). In addition, using positively confirmed metabolites, we were able to distinguish AD from CN and MCI with good diagnostic performance (AUC > 0.8). Saliva is a promising biofluid for both unbiased and targeted AD biomarker discovery and mechanism detection. Given its wide availability and convenient accessibility, saliva is a biofluid that can promote diversification of global AD biomarker research.
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Affiliation(s)
- Tao Huan
- Department of Chemistry, University of Alberta, Edmonton, Canada
| | - Tran Tran
- Department of Chemistry, University of Alberta, Edmonton, Canada
| | - Jiamin Zheng
- Department of Chemistry, University of Alberta, Edmonton, Canada
| | - Shraddha Sapkota
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Stuart W MacDonald
- Department of Psychology, University of Victoria, British Columbia, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.,Department of Medicine (Neurology), University of Alberta, Edmonton, Canada
| | - Roger A Dixon
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.,Department of Psychology, University of Alberta, Edmonton, Canada
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, Canada
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Bergau N, Maul S, Rujescu D, Simm A, Navarrete Santos A. Reduction of Glycolysis Intermediate Concentrations in the Cerebrospinal Fluid of Alzheimer's Disease Patients. Front Neurosci 2019; 13:871. [PMID: 31496932 PMCID: PMC6713159 DOI: 10.3389/fnins.2019.00871] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 08/02/2019] [Indexed: 12/22/2022] Open
Abstract
The profile of 122 metabolites in the cerebrospinal fluid (CSF) of patients suffering from Alzheimer's disease (AD) and controls was studied. Among the 122 metabolites analyzed, 61 could be detected. Statistically significant differences between the AD and control group were only detected for metabolites of the glycolysis. Thus, accurate quantification of 11 glycolytic metabolites was done. We detected a significant reduction of five of them, namely phosphoenolpyruvate, 2-phosphoglycerate, 3-phosphoglycerate, pyruvate and dihydroxyacetone phosphate in the AD CSF compared to controls. These results correlate with the known reduction of glucose metabolism in the brain of patients with AD and indicate that metabolic analysis of the central carbon metabolism can be a potential tool in AD diagnostic. Although the Receiver operating characteristic (ROC) analyses of the metabolites do not reach the level of the diagnostic informativity of AD biomarkers, the combination of specific glycolysis metabolites with the established biomarkers may lead to an improvement in sensitivity and specificity.
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Affiliation(s)
- Nick Bergau
- Department of Cell and Metabolic Biology, Leibniz Institute of Plant Biochemistry, Halle (Saale), Germany
| | - Stephan Maul
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Dan Rujescu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Andreas Simm
- Center for Basic Medical Research, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany.,Clinic for Cardiac Surgery, University Hospital, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexander Navarrete Santos
- Center for Basic Medical Research, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany.,Clinic for Cardiac Surgery, University Hospital, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
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Cummings J, Passmore P, McGuinness B, Mok V, Chen C, Engelborghs S, Woodward M, Manzano S, Garcia-Ribas G, Cappa S, Bertolucci P, Chu LW. Souvenaid in the management of mild cognitive impairment: an expert consensus opinion. ALZHEIMERS RESEARCH & THERAPY 2019; 11:73. [PMID: 31421681 PMCID: PMC6698334 DOI: 10.1186/s13195-019-0528-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 08/06/2019] [Indexed: 02/06/2023]
Abstract
Background Mild cognitive impairment (MCI) among an aging global population is a growing challenge for healthcare providers and payers. In many cases, MCI is an ominous portent for dementia. Early and accurate diagnosis of MCI provides a window of opportunity to improve the outcomes using a personalized care plan including lifestyle modifications to reduce the impact of modifiable risk factors (for example, blood pressure control and increased physical activity), cognitive training, dietary advice, and nutritional support. Souvenaid is a once-daily drink containing a mixture of precursors and cofactors (long-chain omega-3 fatty acids, uridine, choline, B vitamins, vitamin C, vitamin E, and selenium), which was developed to support the formation and function of neuronal membranes and synapses. Healthcare providers, patients, and carers require expert advice about the use of Souvenaid. Methods An international panel of experts was convened to review the evidence and to make recommendations about the diagnosis and management of MCI, identification of candidates for Souvenaid, and use of Souvenaid in real-world practice. This article provides a summary of the expert opinions and makes recommendations for clinical practice and future research. Summary of opinion Early diagnosis of MCI requires the use of suitable neuropsychological tests combined with a careful clinical history. A multimodal approach is recommended; dietary and nutritional interventions should be considered alongside individualized lifestyle modifications. Although single-agent nutritional supplements have failed to produce cognitive benefits for patients with MCI, a broader nutritional approach warrants consideration. Evidence from randomized controlled trials suggests that Souvenaid should be considered as an option for some patients with early Alzheimer’s disease (AD), including those with MCI due to AD (prodromal AD). Conclusion Early and accurate diagnosis of MCI provides a window of opportunity to improve the outcomes using a multimodal management approach including lifestyle risk factor modification and consideration of the multinutrient Souvenaid. Electronic supplementary material The online version of this article (10.1186/s13195-019-0528-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jeffrey Cummings
- Department of Brain Health, School of Integrated Health Sciences, UNLV; Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA.
| | - Peter Passmore
- Centre for Public Health, Institute of Clinical Sciences, Queens University Belfast, Belfast, UK
| | - Bernadette McGuinness
- Centre for Public Health, Institute of Clinical Sciences, Queens University Belfast, Belfast, UK
| | - Vincent Mok
- Therese Pei Fong Chow Research Center for Prevention of Dementia, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Christopher Chen
- Departments of Pharmacology and Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore
| | - Sebastiaan Engelborghs
- Reference Centre for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium.,Department of Neurology, Centre for Neurosciences, UZ Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Michael Woodward
- Department of Medicine, The University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | | | | | - Stefano Cappa
- University School for Advanced Studies IUSS, Pavia and IRCCS Istituto Centro, S. Giovanni di Dio, Brescia, Italy
| | - Paulo Bertolucci
- Service of Cognitive and Behavioral Neurology, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil
| | - Leung-Wing Chu
- Department of Medicine, The University of Hong Kong and Hong Kong Brain Memory Centre, Hong Kong Special Administrative Region, China
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Abstract
Dementia is an overarching term which describes a group of symptoms that result in long-term decline in cognitive functioning that is significant enough to affect daily function. It is caused by a number of different diseases, the most common of which is Alzheimer's disease. Currently, there are no definitive biomarkers for preclinical or diagnostic use, or which differentiate between underlying disease types. The purpose of this review is to highlight several important areas of research on blood-based biomarkers of dementia, with a specific focus on epigenetic biomarkers. A systematic search of the literature identified 77 studies that compared blood DNA methylation between individuals with dementia and controls and 45 studies that measured microRNA. Very few studies were identified that focused on histone modifications. There were many promising findings from studies in the field of blood-based epigenetic biomarkers of dementia, however, a lack of consistency in study design, technologies, and platforms used for the biomarker measurement, as well as statistical analysis methods, have hampered progress. To date, there are very few findings that have been independently replicated across more than one study, indicating a preponderance of false-positive findings and the field has likely been plagued by positive publication bias. Here, we highlight and discuss several of the limitations of existing studies and provide recommendations for how these could be overcome in future research. A robust framework should be followed to enable development of the most valid and reproducible biomarkers with the strongest clinical utility. Defining a series of biomarkers that may be complimentary to each other could permit a stronger multifactorial biomarker to be developed that would allow for not only accurate dementia diagnosis but preclinical detection.
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Affiliation(s)
- Peter D Fransquet
- Department of Epidemiology and Preventive Medicine, Monash University , Melbourne , Australia.,Disease Epigenetics, Murdoch Children's Research Institute , Parkville , Australia
| | - Joanne Ryan
- Department of Epidemiology and Preventive Medicine, Monash University , Melbourne , Australia.,Disease Epigenetics, Murdoch Children's Research Institute , Parkville , Australia
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266
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Yan T, Ding F, Zhao Y. Integrated identification of key genes and pathways in Alzheimer's disease via comprehensive bioinformatical analyses. Hereditas 2019; 156:25. [PMID: 31346329 PMCID: PMC6636172 DOI: 10.1186/s41065-019-0101-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 07/09/2019] [Indexed: 12/23/2022] Open
Abstract
Background Alzheimer's disease (AD) is known to be caused by multiple factors, meanwhile the pathogenic mechanism and development of AD associate closely with genetic factors. Existing understanding of the molecular mechanisms underlying AD remains incomplete. Methods Gene expression data (GSE48350) derived from post-modern brain was extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were derived from hippocampus and entorhinal cortex regions between AD patients and healthy controls and detected via Morpheus. Functional enrichment analyses, including Gene Ontology (GO) and pathway analyses of DEGs, were performed via Cytoscape and followed by the construction of protein-protein interaction (PPI) network. Hub proteins were screened using the criteria: nodes degree≥10 (for hippocampus tissues) and ≥ 8 (for entorhinal cortex tissues). Molecular Complex Detection (MCODE) was used to filtrate the important clusters. University of California Santa Cruz (UCSC) and the database of RNA-binding protein specificities (RBPDB) were employed to identify the RNA-binding proteins of the long non-coding RNA (lncRNA). Results 251 & 74 genes were identified as DEGs, which consisted of 56 & 16 up-regulated genes and 195 & 58 down-regulated genes in hippocampus and entorhinal cortex, respectively. Biological analyses demonstrated that the biological processes and pathways related to memory, transmembrane transport, synaptic transmission, neuron survival, drug metabolism, ion homeostasis and signal transduction were enriched in these genes. 11 genes were identified as hub genes in hippocampus and entorhinal cortex, and 3 hub genes were identified as the novel candidates involved in the pathology of AD. Furthermore, 3 lncRNAs were filtrated, whose binding proteins were closely associated with AD. Conclusions Through GO enrichment analyses, pathway analyses and PPI analyses, we showed a comprehensive interpretation of the pathogenesis of AD at a systematic biology level, and 3 novel candidate genes and 3 lncRNAs were identified as novel and potential candidates participating in the pathology of AD. The results of this study could supply integrated insights for understanding the pathogenic mechanism underlying AD and potential novel therapeutic targets.
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Affiliation(s)
- Tingting Yan
- Department of Bioengineering, Harbin Institute of Technology, Weihai, 264209 Shandong China
| | - Feng Ding
- Department of Bioengineering, Harbin Institute of Technology, Weihai, 264209 Shandong China
| | - Yan Zhao
- Department of Bioengineering, Harbin Institute of Technology, Weihai, 264209 Shandong China
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267
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Nutrition and Metabolic Profiles in the Natural History of Dementia: Recent Insights from Systems Biology and Life Course Epidemiology. Curr Nutr Rep 2019; 8:256-269. [DOI: 10.1007/s13668-019-00285-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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268
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Nho K, Kueider-Paisley A, Ahmad S, MahmoudianDehkordi S, Arnold M, Risacher SL, Louie G, Blach C, Baillie R, Han X, Kastenmüller G, Trojanowski JQ, Shaw LM, Weiner MW, Doraiswamy PM, van Duijn C, Saykin AJ, Kaddurah-Daouk R. Association of Altered Liver Enzymes With Alzheimer Disease Diagnosis, Cognition, Neuroimaging Measures, and Cerebrospinal Fluid Biomarkers. JAMA Netw Open 2019; 2:e197978. [PMID: 31365104 PMCID: PMC6669786 DOI: 10.1001/jamanetworkopen.2019.7978] [Citation(s) in RCA: 125] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
IMPORTANCE Increasing evidence suggests an important role of liver function in the pathophysiology of Alzheimer disease (AD). The liver is a major metabolic hub; therefore, investigating the association of liver function with AD, cognition, neuroimaging, and CSF biomarkers would improve the understanding of the role of metabolic dysfunction in AD. OBJECTIVE To examine whether liver function markers are associated with cognitive dysfunction and the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD. DESIGN, SETTING, AND PARTICIPANTS In this cohort study, serum-based liver function markers were measured from September 1, 2005, to August 31, 2013, in 1581 AD Neuroimaging Initiative participants along with cognitive measures, cerebrospinal fluid (CSF) biomarkers, brain atrophy, brain glucose metabolism, and amyloid-β accumulation. Associations of liver function markers with AD-associated clinical and A/T/N biomarkers were assessed using generalized linear models adjusted for confounding variables and multiple comparisons. Statistical analysis was performed from November 1, 2017, to February 28, 2019. EXPOSURES Five serum-based liver function markers (total bilirubin, albumin, alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase) from AD Neuroimaging Initiative participants were used as exposure variables. MAIN OUTCOMES AND MEASURES Primary outcomes included diagnosis of AD, composite scores for executive functioning and memory, CSF biomarkers, atrophy measured by magnetic resonance imaging, brain glucose metabolism measured by fludeoxyglucose F 18 (18F) positron emission tomography, and amyloid-β accumulation measured by [18F]florbetapir positron emission tomography. RESULTS Participants in the AD Neuroimaging Initiative (n = 1581; 697 women and 884 men; mean [SD] age, 73.4 [7.2] years) included 407 cognitively normal older adults, 20 with significant memory concern, 298 with early mild cognitive impairment, 544 with late mild cognitive impairment, and 312 with AD. An elevated aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio and lower levels of ALT were associated with AD diagnosis (AST to ALT ratio: odds ratio, 7.932 [95% CI, 1.673-37.617]; P = .03; ALT: odds ratio, 0.133 [95% CI, 0.042-0.422]; P = .004) and poor cognitive performance (AST to ALT ratio: β [SE], -0.465 [0.180]; P = .02 for memory composite score; β [SE], -0.679 [0.215]; P = .006 for executive function composite score; ALT: β [SE], 0.397 [0.128]; P = .006 for memory composite score; β [SE], 0.637 [0.152]; P < .001 for executive function composite score). Increased AST to ALT ratio values were associated with lower CSF amyloid-β 1-42 levels (β [SE], -0.170 [0.061]; P = .04) and increased amyloid-β deposition (amyloid biomarkers), higher CSF phosphorylated tau181 (β [SE], 0.175 [0.055]; P = .02) (tau biomarkers) and higher CSF total tau levels (β [SE], 0.160 [0.049]; P = .02) and reduced brain glucose metabolism (β [SE], -0.123 [0.042]; P = .03) (neurodegeneration biomarkers). Lower levels of ALT were associated with increased amyloid-β deposition (amyloid biomarkers), and reduced brain glucose metabolism (β [SE], 0.096 [0.030]; P = .02) and greater atrophy (neurodegeneration biomarkers). CONCLUSIONS AND RELEVANCE Consistent associations of serum-based liver function markers with cognitive performance and A/T/N biomarkers for AD highlight the involvement of metabolic disturbances in the pathophysiology of AD. Further studies are needed to determine if these associations represent a causative or secondary role. Liver enzyme involvement in AD opens avenues for novel diagnostics and therapeutics.
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Affiliation(s)
- Kwangsik Nho
- Center for Computational Biology and Bioinformatics, Indiana Alzheimer Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis
| | | | - Shahzad Ahmad
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | | | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Shannon L. Risacher
- Center for Computational Biology and Bioinformatics, Indiana Alzheimer Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, North Carolina
| | | | - Xianlin Han
- University of Texas Health Science Center at San Antonio, San Antonio
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | - Michael W. Weiner
- Center for Imaging of Neurodegenerative Diseases, Department of Radiology, San Francisco Veterans Affairs Medical Center and University of California, San Francisco
| | - P. Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Institute of Brain Sciences, Duke University, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
- Nuffield Department of Population Health, Oxford University, Oxford, United Kingdom
| | - Andrew J. Saykin
- Center for Computational Biology and Bioinformatics, Indiana Alzheimer Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Institute of Brain Sciences, Duke University, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
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Li D, Hagen C, Fett AR, Bui HH, Knopman D, Vemuri P, Machulda MM, Jack CR, Petersen RC, Mielke MM. Longitudinal association between phosphatidylcholines, neuroimaging measures of Alzheimer's disease pathophysiology, and cognition in the Mayo Clinic Study of Aging. Neurobiol Aging 2019; 79:43-49. [PMID: 31026621 PMCID: PMC6591044 DOI: 10.1016/j.neurobiolaging.2019.03.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 03/07/2019] [Accepted: 03/10/2019] [Indexed: 12/12/2022]
Abstract
Plasma phosphatidylcholines (PCs) have been examined in the context of Alzheimer's disease dementia. However, their association with longitudinal changes in amyloid deposition remains unknown. This study investigated the associations of 8 plasma PC levels (PC aa [14:0_14:0], PC aa [16:0_16:0], PC aa [16:0_18:2], PC aa [16:0_22:6], PC aa [18:0_18:0], PC aa [18:0_18:1], PC aa [18:0_20:4], PC aa [18:1_18:1]) with cross-sectional and longitudinal measures of amyloid deposition, Alzheimer's disease-associated neurodegeneration (glucose metabolism and cortical thickness), and cognition (global- and domain-specific) of 1440 cognitively unimpaired participants (47% female, aged 50.7-95.3 years) in the Mayo Clinic Study of Aging. Longitudinally, higher baseline levels of PC aa [16:0_18:2], PC aa [18:0_18:1], and PC aa [18:1_18:1] were associated with slower decline in performance on tests of global cognition and specific cognitive domains. Furthermore, higher baseline levels of plasma PC aa (14:0_14:0) were associated with slower amyloid deposition and cortical thinning after multiple covariable adjustment (age, sex, education, medical comorbidity, dyslipidemia, statin use, and APOE4 allele presence). Our study findings support an independent association between plasma PC aa (14:0_14:0) with slower amyloid deposition and cortical thinning among cognitively unimpaired older adults.
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Affiliation(s)
- Danni Li
- Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Clinton Hagen
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Ashely R Fett
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Hai H Bui
- Eli Lilly and Company, Indianapolis, IN, USA
| | - David Knopman
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA; Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA; Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
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270
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Ash JR, Kuenemann MA, Rotroff D, Motsinger-Reif A, Fourches D. Cheminformatics approach to exploring and modeling trait-associated metabolite profiles. J Cheminform 2019; 11:43. [PMID: 31236709 PMCID: PMC6591908 DOI: 10.1186/s13321-019-0366-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 06/17/2019] [Indexed: 12/17/2022] Open
Abstract
Developing predictive and transparent approaches to the analysis of metabolite profiles across patient cohorts is of critical importance for understanding the events that trigger or modulate traits of interest (e.g., disease progression, drug metabolism, chemical risk assessment). However, metabolites’ chemical structures are still rarely used in the statistical modeling workflows that establish these trait-metabolite relationships. Herein, we present a novel cheminformatics-based approach capable of identifying predictive, interpretable, and reproducible trait-metabolite relationships. As a proof-of-concept, we utilize a previously published case study consisting of metabolite profiles from non-small-cell lung cancer (NSCLC) adenocarcinoma patients and healthy controls. By characterizing each structurally annotated metabolite using both computed molecular descriptors and patient metabolite concentration profiles, we show that these complementary features enhance the identification and understanding of key metabolites associated with cancer. Ultimately, we built multi-metabolite classification models for assessing patients’ cancer status using specific groups of metabolites identified based on high structural similarity through chemical clustering. We subsequently performed a metabolic pathway enrichment analysis to identify potential mechanistic relationships between metabolites and NSCLC adenocarcinoma. This cheminformatics-inspired approach relies on the metabolites’ structural features and chemical properties to provide critical information about metabolite-trait associations. This method could ultimately facilitate biological understanding and advance research based on metabolomics data, especially with respect to the identification of novel biomarkers. ![]()
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Affiliation(s)
- Jeremy R Ash
- Department of Chemistry, North Carolina State University, Raleigh, NC, USA.,Department of Statistics, North Carolina State University, Raleigh, NC, USA.,Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Melaine A Kuenemann
- Department of Chemistry, North Carolina State University, Raleigh, NC, USA.,Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Daniel Rotroff
- Department of Statistics, North Carolina State University, Raleigh, NC, USA.,Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Alison Motsinger-Reif
- Department of Statistics, North Carolina State University, Raleigh, NC, USA.,Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Denis Fourches
- Department of Chemistry, North Carolina State University, Raleigh, NC, USA. .,Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA.
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271
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Characterization of Bulk Phosphatidylcholine Compositions in Human Plasma Using Side-Chain Resolving Lipidomics. Metabolites 2019; 9:metabo9060109. [PMID: 31181753 PMCID: PMC6631474 DOI: 10.3390/metabo9060109] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 06/04/2019] [Accepted: 06/05/2019] [Indexed: 01/05/2023] Open
Abstract
Kit-based assays, such as AbsoluteIDQTM p150, are widely used in large cohort studies and provide a standardized method to quantify blood concentrations of phosphatidylcholines (PCs). Many disease-relevant associations of PCs were reported using this method. However, their interpretation is hampered by lack of functionally-relevant information on the detailed fatty acid side-chain compositions as only the total number of carbon atoms and double bonds is identified by the kit. To enable more substantiated interpretations, we characterized these PC sums using the side-chain resolving LipidyzerTM platform, analyzing 223 samples in parallel to the AbsoluteIDQTM. Combining these datasets, we estimated the quantitative composition of PC sums and subsequently tested their replication in an independent cohort. We identified major constituents of 28 PC sums, revealing also various unexpected compositions. As an example, PC 16:0_22:5 accounted for more than 50% of the PC sum with in total 38 carbon atoms and 5 double bonds (PC aa 38:5). For 13 PC sums, we found relatively high abundances of odd-chain fatty acids. In conclusion, our study provides insights in PC compositions in human plasma, facilitating interpretation of existing epidemiological data sets and potentially enabling imputation of PC compositions for future meta-analyses of lipidomics data.
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272
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Figueira J, Adolfsson R, Nordin Adolfsson A, Nyberg L, Öhman A. Serum Metabolite Markers of Dementia Through Quantitative NMR Analysis: The Importance of Threonine-Linked Metabolic Pathways. J Alzheimers Dis 2019; 69:763-774. [PMID: 31127768 DOI: 10.3233/jad-181189] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
There is a great need for diagnostic biomarkers of impending dementia. Metabolite markers in blood have been investigated in several studies, but inconclusive findings encourage further investigation, particularly in the pre-diagnostic phase. In the present study, the serum metabolomes of 110 dementia or pre-diagnostic dementia individuals and 201 healthy individuals matched for age, gender, and education were analyzed by nuclear magnetic resonance spectroscopy in combination with multivariate data analysis. 58 metabolites were quantified in each of the 311 samples. Individuals with dementia were discriminated from controls using a panel of seven metabolites, while the pre-diagnostic dementia subjects were distinguished from controls using a separate set of seven metabolites, where threonine was a common significant metabolite in both panels. Metabolite and pathway alterations specific for dementia and pre-diagnostic dementia were identified, in particular a disturbed threonine catabolism at the pre-diagnostic stage that extends to several threonine-linked pathways at the dementia stage.
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Affiliation(s)
- João Figueira
- Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden
| | - Rolf Adolfsson
- Department of Clinical Sciences, Psychiatry, Umeå University, Umeå, Sweden
| | | | - Lars Nyberg
- Departments of Radiation Sciences and Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Anders Öhman
- Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden
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273
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Associations of AD Biomarkers and Cognitive Performance with Nutritional Status: The NUDAD Project. Nutrients 2019; 11:nu11051161. [PMID: 31126170 PMCID: PMC6566264 DOI: 10.3390/nu11051161] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 05/15/2019] [Accepted: 05/21/2019] [Indexed: 11/17/2022] Open
Abstract
As malnutrition is common in patients with Alzheimer’s disease (AD), we evaluated nutritional status and body composition of patients with AD, mild cognitive impairment (MCI) and controls, and studied associations of AD biomarkers and cognitive performance with nutritional status and body composition. We included 552 participants, of which 198 patients had AD, 135 patients had MCI and 219 controls. We assessed nutritional status (mini nutritional assessment (MNA)) and body composition (body mass index (BMI), fat-free mass (FFM) and waist circumference). Linear regression analyses (adjusted for age, gender and education where appropriate) were applied to test associations of AD biomarkers and cognitive performance on five domains with nutritional parameters (dependent). Patients with MCI and AD had a lower BMI and MNA score than controls. Worse performance in all cognitive domains was associated with lower MNA score, but not with body composition. AD biomarkers were associated with MNA score, BMI and waist circumference, and associations with MNA score remained after adjustment for cognitive performance. Both AD biomarkers and cognitive performance were associated with nutritional status, associations with AD biomarkers remained after adjustment for cognition. Our data suggest that malnutrition is not only related to impaired cognition but also to AD pathology.
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274
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Wilkins J, Sakrikar D, Petterson XM, Lanza IR, Trushina E. A comprehensive protocol for multiplatform metabolomics analysis in patient-derived skin fibroblasts. Metabolomics 2019; 15:83. [PMID: 31123906 PMCID: PMC7928486 DOI: 10.1007/s11306-019-1544-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 05/18/2019] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Patient-derived skin fibroblasts offer a unique translational model to study molecular mechanisms of multiple human diseases. Metabolomics profiling allows to track changes in a broad range of metabolites and interconnected metabolic pathways that could inform on molecular mechanisms involved in disease development and progression, and on the efficacy of therapeutic interventions. Therefore, it is important to establish standardized protocols for metabolomics analysis in human skin fibroblasts for rigorous and reliable metabolic assessment. OBJECTIVES We aimed to develop an optimized protocol for concurrent measure of the concentration of amino acids, acylcarnitines, and components of the tricarboxylic acid (TCA) cycle in human skin fibroblasts using gas (GC) and liquid chromatography (LC) coupled with mass spectrometry (MS). METHODS The suitability of four different methods of cell harvesting on the recovery of amino acids, acylcarnitines, and TCA cycle metabolites was established using GC/MS and LC/MS analytical platforms. For each method, metabolite stability was determined after 48 h, 2 weeks and 1 month of storage at - 80 °C. RESULTS Harvesting cells in 80% methanol solution allowed the best recovery and preservation of metabolites. Storage of samples in 80% methanol up to 1 month at - 80 °C did not significantly impact metabolite concentrations. CONCLUSION We developed a robust workflow for metabolomics analysis in human skin fibroblasts suitable for a high-throughput multiplatform analysis. This method allows a direct side-by-side comparison of metabolic changes in samples collected at different time that could be used for studies in large patient cohorts.
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Affiliation(s)
- Jordan Wilkins
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | | | - Ian R Lanza
- Metabolomics Core Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
- Division of Endocrinology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Eugenia Trushina
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA.
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Guggenheim Bld., Room 1542B, Rochester, MN, 55905, USA.
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275
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Jęśko H, Stępień A, Lukiw WJ, Strosznajder RP. The Cross-Talk Between Sphingolipids and Insulin-Like Growth Factor Signaling: Significance for Aging and Neurodegeneration. Mol Neurobiol 2019; 56:3501-3521. [PMID: 30140974 PMCID: PMC6476865 DOI: 10.1007/s12035-018-1286-3] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 07/25/2018] [Indexed: 12/20/2022]
Abstract
Bioactive sphingolipids: sphingosine, sphingosine-1-phosphate (S1P), ceramide, and ceramide-1-phosphate (C1P) are increasingly implicated in cell survival, proliferation, differentiation, and in multiple aspects of stress response in the nervous system. The opposite roles of closely related sphingolipid species in cell survival/death signaling is reflected in the concept of tightly controlled sphingolipid rheostat. Aging has a complex influence on sphingolipid metabolism, disturbing signaling pathways and the properties of lipid membranes. A metabolic signature of stress resistance-associated sphingolipids correlates with longevity in humans. Moreover, accumulating evidence suggests extensive links between sphingolipid signaling and the insulin-like growth factor I (IGF-I)-Akt-mTOR pathway (IIS), which is involved in the modulation of aging process and longevity. IIS integrates a wide array of metabolic signals, cross-talks with p53, nuclear factor κB (NF-κB), or reactive oxygen species (ROS) and influences gene expression to shape the cellular metabolic profile and stress resistance. The multiple connections between sphingolipids and IIS signaling suggest possible engagement of these compounds in the aging process itself, which creates a vulnerable background for the majority of neurodegenerative disorders.
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Affiliation(s)
- Henryk Jęśko
- Department of Cellular Signalling, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Pawińskiego, 5, 02-106, Poland
| | - Adam Stępień
- Central Clinical Hospital of the Ministry of National Defense, Department of Neurology, Military Institute of Medicine, Warsaw, Szaserów, 128, 04-141, Poland
| | - Walter J Lukiw
- LSU Neuroscience Center and Departments of Neurology and Ophthalmology, Louisiana State University School of Medicine, New Orleans, USA
| | - Robert P Strosznajder
- Laboratory of Preclinical Research and Environmental Agents, Department of Neurosurgery, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Pawińskiego, 5, 02-106, Poland.
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276
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Jiang Y, Zhu Z, Shi J, An Y, Zhang K, Wang Y, Li S, Jin L, Ye W, Cui M, Chen X. Metabolomics in the Development and Progression of Dementia: A Systematic Review. Front Neurosci 2019; 13:343. [PMID: 31031585 PMCID: PMC6474157 DOI: 10.3389/fnins.2019.00343] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 03/25/2019] [Indexed: 12/12/2022] Open
Abstract
Dementia has become a major global public health challenge with a heavy economic burden. It is urgently necessary to understand dementia pathogenesis and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention, monitoring, and treatment. Metabolomics provides a novel approach for the identification of biomarkers of dementia. This systematic review aimed to examine and summarize recent retrospective cohort human studies assessing circulating metabolite markers, detected using high-throughput metabolomics, in the context of disease progression to dementia, including incident mild cognitive impairment, all-cause dementia, and cognitive decline. We systematically searched the PubMed, Embase, and Cochrane databases for retrospective cohort human studies assessing associations between blood (plasma or serum) metabolomics profile and cognitive decline and risk of dementia from inception through October 15, 2018. We identified 16 studies reporting circulating metabolites and risk of dementia, and six regarding cognitive performance change. Concentrations of several blood metabolites, including lipids (higher phosphatidylcholines, sphingomyelins, and lysophophatidylcholine, and lower docosahexaenoic acid and high-density lipoprotein subfractions), amino acids (lower branched-chain amino acids, creatinine, and taurine, and higher glutamate, glutamine, and anthranilic acid), and steroids were associated with cognitive decline and the incidence or progression of dementia. Circulating metabolites appear to be associated with the risk of dementia. Metabolomics could be a promising tool in dementia biomarker discovery. However, standardization and consensus guidelines for study design and analytical techniques require future development.
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Affiliation(s)
- Yanfeng Jiang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Fudan University Taizhou Institute of Health Sciences, Taizhou, China
| | - Zhen Zhu
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China.,Key Laboratory of Public Health Safety of Ministry of Education, Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
| | - Jie Shi
- Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yanpeng An
- State Key Laboratory of Genetic Engineering, Metabonomics and Systems Biology Laboratory, School of Life Sciences, Fudan University, Shanghai, China
| | - Kexun Zhang
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China.,Key Laboratory of Public Health Safety of Ministry of Education, Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
| | - Yingzhe Wang
- Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Shuyuan Li
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Fudan University Taizhou Institute of Health Sciences, Taizhou, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Weimin Ye
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mei Cui
- Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Xingdong Chen
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Fudan University Taizhou Institute of Health Sciences, Taizhou, China.,Human Phenome Institute, Fudan University, Shanghai, China
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277
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Hrubešová K, Fousková M, Habartová L, Fišar Z, Jirák R, Raboch J, Setnička V. Search for biomarkers of Alzheimer's disease: Recent insights, current challenges and future prospects. Clin Biochem 2019; 72:39-51. [PMID: 30953619 DOI: 10.1016/j.clinbiochem.2019.04.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 04/03/2019] [Indexed: 12/12/2022]
Abstract
Due to the trend of prolonged lifespan leading to higher incidence of age-related diseases, the demand for reliable biomarkers of dementia rises. In this review, we present novel biomarkers of high potential, especially those found in blood, urine or saliva, which could lead to a more comfortable patient experience and better time- and cost-effectivity, compared to the currently used diagnostic methods. We focus on biomarkers that might allow for the detection of Alzheimer's disease before its clinical manifestations. Such biomarkers might be helpful for better understanding the etiology of the disease and identifying its risk factors. Moreover, it could be a base for developing new treatment or at least help to prolong the presymptomatic stage in patients suffering from Alzheimer's disease. As potential candidates, we present, for instance, neurofilament light in both cerebrospinal fluid and blood plasma or amyloid β in plasma. Above all, we provide an overview of different approaches to the diagnostics, analyzing patient's biofluids as a whole using molecular spectroscopy. Infrared and Raman spectroscopy and especially chiroptical methods provide information not only on the chemical composition, but also on molecular structure. Therefore, these techniques are promising for the diagnostics of Alzheimer's disease, as the accumulation of amyloid β in abnormal conformation is one of the hallmarks of this disease.
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Affiliation(s)
- Kateřina Hrubešová
- Department of Analytical Chemistry, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Markéta Fousková
- Department of Analytical Chemistry, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Lucie Habartová
- Department of Analytical Chemistry, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Zdeněk Fišar
- Department of Psychiatry, First Faculty of Medicine, Charles University and General University Hospital in Prague, Ke Karlovu 11, 120 00 Prague 2, Czech Republic
| | - Roman Jirák
- Department of Psychiatry, First Faculty of Medicine, Charles University and General University Hospital in Prague, Ke Karlovu 11, 120 00 Prague 2, Czech Republic
| | - Jiří Raboch
- Department of Psychiatry, First Faculty of Medicine, Charles University and General University Hospital in Prague, Ke Karlovu 11, 120 00 Prague 2, Czech Republic
| | - Vladimír Setnička
- Department of Analytical Chemistry, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague 6, Czech Republic.
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278
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Goudey B, Fung BJ, Schieber C, Faux NG. A blood-based signature of cerebrospinal fluid Aβ 1-42 status. Sci Rep 2019; 9:4163. [PMID: 30853713 PMCID: PMC6409361 DOI: 10.1038/s41598-018-37149-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 12/03/2018] [Indexed: 12/22/2022] Open
Abstract
It is increasingly recognized that Alzheimer's disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1-42 (Aβ1-42) may be an earlier indicator of Alzheimer's disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual's CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1-42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1-42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1-42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1-42 levels and that the resulting model also validates reasonably across PET Aβ1-42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1-42 status, the earliest risk indicator for AD, with high accuracy.
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Affiliation(s)
- Benjamin Goudey
- IBM Research Australia, Carlton, Victoria, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia
- Department of Computing and Information System, The University of Melbourne, Parkville, Victoria, Australia
| | - Bowen J Fung
- IBM Research Australia, Carlton, Victoria, Australia
- School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia
| | | | - Noel G Faux
- IBM Research Australia, Carlton, Victoria, Australia.
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia.
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279
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Dorninger F, Moser AB, Kou J, Wiesinger C, Forss-Petter S, Gleiss A, Hinterberger M, Jungwirth S, Fischer P, Berger J. Alterations in the Plasma Levels of Specific Choline Phospholipids in Alzheimer's Disease Mimic Accelerated Aging. J Alzheimers Dis 2019; 62:841-854. [PMID: 29480199 PMCID: PMC5837024 DOI: 10.3233/jad-171036] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Alzheimer’s disease (AD) is the most common neurodegenerative disease and of continuously rising prevalence. The identification of easy-to-measure biomarkers capable to assist in the prediction and early diagnosis of AD is currently a main research goal. Lipid metabolites in peripheral blood of human patients have recently gained major attention in this respect. Here, we analyzed plasma of 174 participants (not demented at baseline; mean age: 75.70±0.44 years) of the Vienna Transdanube Aging (VITA) study, a longitudinal, population-based birth cohort study, at baseline and after 90 months or at diagnosis of probable AD. We determined the levels of specific choline phospholipids, some of which have been suggested as potential biomarkers for the prediction of AD. Our results show that during normal aging the levels of lysophosphatidylcholine, choline plasmalogen, and lyso-platelet activating factor increase significantly. Notably, we observed similar but more pronounced changes in the group that developed probable AD. Thus, our results imply that, in terms of choline-containing plasma phospholipids, the conversion to AD mimics an accelerated aging process. We conclude that age, even in the comparatively short time frame between 75 and 82.5 years, is a crucial factor in the quest for plasma lipid biomarkers for AD that must be carefully considered in future studies and trials.
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Affiliation(s)
- Fabian Dorninger
- Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Ann B Moser
- Peroxisomal Diseases Laboratory, The Hugo W Moser Research Institute, The Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jianqiu Kou
- Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Christoph Wiesinger
- Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Sonja Forss-Petter
- Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Andreas Gleiss
- Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | | | - Susanne Jungwirth
- Ludwig Boltzmann Institute of Aging Research, Danube Hospital, Vienna, Austria
| | - Peter Fischer
- Ludwig Boltzmann Institute of Aging Research, Danube Hospital, Vienna, Austria.,Department of Psychiatry, Medical Research Society Vienna D.C., Danube Hospital, Vienna, Austria
| | - Johannes Berger
- Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria
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280
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Nho K, Kueider-Paisley A, MahmoudianDehkordi S, Arnold M, Risacher SL, Louie G, Blach C, Baillie R, Han X, Kastenmüller G, Jia W, Xie G, Ahmad S, Hankemeier T, van Duijn CM, Trojanowski JQ, Shaw LM, Weiner MW, Doraiswamy PM, Saykin AJ, Kaddurah-Daouk R. Altered bile acid profile in mild cognitive impairment and Alzheimer's disease: Relationship to neuroimaging and CSF biomarkers. Alzheimers Dement 2019; 15:232-244. [PMID: 30337152 PMCID: PMC6454538 DOI: 10.1016/j.jalz.2018.08.012] [Citation(s) in RCA: 177] [Impact Index Per Article: 35.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 08/03/2018] [Accepted: 08/21/2018] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Bile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer's disease (AD) including neuroinflammation and amyloid-β deposition. METHOD Serum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n = 1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF) biomarkers, atrophy (magnetic resonance imaging), and brain glucose metabolism ([18F]FDG PET). RESULTS Of 23 BAs and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1-42 ("A") and three with CSF p-tau181 ("T") (corrected P < .05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy ("N"), respectively (corrected P < .05). DISCUSSION This is the first study to show serum-based BA metabolites are associated with "A/T/N" AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.
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Affiliation(s)
- Kwangsik Nho
- Department of Radiology and Imaging Sciences, Center for Computational Biology and Bioinformatics, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Center for Computational Biology and Bioinformatics, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | | | - Xianlin Han
- University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Wei Jia
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Guoxiang Xie
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, RA Leiden, the Netherlands
| | | | - John Q Trojanowski
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Leslie M Shaw
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, Department of Radiology, San Francisco VA Medical Center/University of California San Francisco, San Francisco, CA, USA
| | - P Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC, USA; Department of Medicine, Duke University, Durham, NC, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Center for Computational Biology and Bioinformatics, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC, USA; Department of Medicine, Duke University, Durham, NC, USA.
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281
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Paley EL, Merkulova-Rainon T, Faynboym A, Shestopalov VI, Aksenoff I. Geographical Distribution and Diversity of Gut Microbial NADH:Ubiquinone Oxidoreductase Sequence Associated with Alzheimer's Disease. J Alzheimers Dis 2019; 61:1531-1540. [PMID: 29376868 DOI: 10.3233/jad-170764] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Earlier we reported induction of neurotoxicity and neurodegeneration by tryptophan metabolites that link the metabolic alterations to Alzheimer's disease (AD). Tryptophan is a product of Shikimate pathway (SP). Human cells lack SP, which is found in human gut bacteria exclusively using SP to produce aromatic amino acids (AAA). This study is a first attempt toward gene-targeted analysis of human gut microbiota in AD fecal samples. The oligonucleotide primers newly-designed for this work target SP-AAA in environmental bacteria associated with human activity. Using polymerase chain reaction (PCR), we found unique gut bacterial sequence in most AD patients (18 of 20), albeit rarely in controls (1 of 13). Cloning and sequencing AD-associated PCR products (ADPP) enables identification of Na(+)-transporting NADH: Ubiquinone reductase (NQR) in Clostridium sp. The ADPP of unrelated AD patients possess near identical sequences. NQR substrate, ubiquinone is a SP product and human neuroprotectant. A deficit in ubiquinone has been determined in a number of neuromuscular and neurodegenerative disorders. Antibacterial therapy prompted an ADPP reduction in an ADPP-positive control person who was later diagnosed with AD-dementia. We explored the gut microbiome databases and uncovered a sequence similarity (up to 97%) between ADPP and some healthy individuals from different geographical locations. Importantly, our main finding of the significant difference in the gut microbial genotypes between the AD and control human populations is a breakthrough.
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Affiliation(s)
- Elena L Paley
- Expert Biomed, Inc. Miami, FL, USA.,Stop Alzheimers Corp, Miami, FL, USA.,Nova Southeastern University, Fort Lauderdale, FL, USA
| | | | | | - Valery I Shestopalov
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL, USA.,Department of Cell Biology, University of Miami Miller School of Medicine, Miami, FL, USA
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282
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Nanowired delivery of cerebrolysin with neprilysin and p-Tau antibodies induces superior neuroprotection in Alzheimer's disease. PROGRESS IN BRAIN RESEARCH 2019; 245:145-200. [DOI: 10.1016/bs.pbr.2019.03.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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283
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Peña-Bautista C, Baquero M, Vento M, Cháfer-Pericás C. Omics-based Biomarkers for the Early Alzheimer Disease Diagnosis and Reliable Therapeutic Targets Development. Curr Neuropharmacol 2019; 17:630-647. [PMID: 30255758 PMCID: PMC6712290 DOI: 10.2174/1570159x16666180926123722] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 08/31/2018] [Accepted: 09/19/2018] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD), the most common cause of dementia in adulthood, has great medical, social, and economic impact worldwide. Available treatments result in symptomatic relief, and most of them are indicated from the early stages of the disease. Therefore, there is an increasing body of research developing accurate and early diagnoses, as well as diseasemodifying therapies. OBJECTIVE Advancing the knowledge of AD physiopathological mechanisms, improving early diagnosis and developing effective treatments from omics-based biomarkers. METHODS Studies using omics technologies to detect early AD, were reviewed with a particular focus on the metabolites/lipids, micro-RNAs and proteins, which are identified as potential biomarkers in non-invasive samples. RESULTS This review summarizes recent research on metabolomics/lipidomics, epigenomics and proteomics, applied to early AD detection. Main research lines are the study of metabolites from pathways, such as lipid, amino acid and neurotransmitter metabolisms, cholesterol biosynthesis, and Krebs and urea cycles. In addition, some microRNAs and proteins (microglobulins, interleukins), related to a common network with amyloid precursor protein and tau, have been also identified as potential biomarkers. Nevertheless, the reproducibility of results among studies is not good enough and a standard methodological approach is needed in order to obtain accurate information. CONCLUSION The assessment of metabolomic/lipidomic, epigenomic and proteomic changes associated with AD to identify early biomarkers in non-invasive samples from well-defined participants groups will potentially allow the advancement in the early diagnosis and improvement of therapeutic interventions.
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Affiliation(s)
| | | | | | - Consuelo Cháfer-Pericás
- Address correspondence to this author at the Health Research Institute La Fe, Avda de Fernando Abril Martorell, 106; 46026 Valencia, Spain;Tel: +34 96 124 66 61; Fax: + 34 96 124 57 46; E-mail:
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284
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Tournissac M, Vandal M, Tremblay C, Bourassa P, Vancassel S, Emond V, Gangloff A, Calon F. Dietary intake of branched-chain amino acids in a mouse model of Alzheimer's disease: Effects on survival, behavior, and neuropathology. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2018; 4:677-687. [PMID: 30560200 PMCID: PMC6290124 DOI: 10.1016/j.trci.2018.10.005] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Introduction High levels of plasmatic branched-chain amino acids (BCAA), commonly used as dietary supplements, are linked to metabolic risk factors for Alzheimer's disease (AD). BCAA directly influence amino acid transport to the brain and, therefore, neurotransmitter levels. We thus investigated the impact of BCAA on AD neuropathology in a mouse model. Methods 3xTg-AD mice were fed either a control diet or a high-fat diet from 6 to 18 months of age. For the last 2 months, dietary BCAA content was adjusted to high (+50%), normal (+0%), or low (−50%). Results Mice fed a BCAA-supplemented high-fat diet displayed higher tau neuropathology and only four out of 13 survived. Mice on the low-BCAA diet showed higher threonine and tryptophan cortical levels while performing better on the novel object recognition task. Discussion These preclinical data underscore a potential risk of combining high-fat and high BCAA consumption, and possible benefits from BCAA restriction in AD.
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Affiliation(s)
- Marine Tournissac
- Faculty of pharmacy, Laval University, Quebec City, QC, Canada.,Neuroscience axis, CHU de Québec-Université Laval Research Center, Quebec City, QC, Canada.,OptiNutriBrain International Associated Laboratory (NutriNeuro France-INAF Canada).,Institute of Nutrition and Functional Foods, Université Laval, Quebec City, QC, Canada
| | - Milene Vandal
- Faculty of pharmacy, Laval University, Quebec City, QC, Canada.,Neuroscience axis, CHU de Québec-Université Laval Research Center, Quebec City, QC, Canada.,OptiNutriBrain International Associated Laboratory (NutriNeuro France-INAF Canada).,Institute of Nutrition and Functional Foods, Université Laval, Quebec City, QC, Canada
| | - Cyntia Tremblay
- Neuroscience axis, CHU de Québec-Université Laval Research Center, Quebec City, QC, Canada
| | - Philippe Bourassa
- Faculty of pharmacy, Laval University, Quebec City, QC, Canada.,Neuroscience axis, CHU de Québec-Université Laval Research Center, Quebec City, QC, Canada.,OptiNutriBrain International Associated Laboratory (NutriNeuro France-INAF Canada).,Institute of Nutrition and Functional Foods, Université Laval, Quebec City, QC, Canada
| | - Sylvie Vancassel
- OptiNutriBrain International Associated Laboratory (NutriNeuro France-INAF Canada).,INRA, NutriNeuro UMR INRA 1286, Université Victor Segalen, Bordeaux, Cedex, France
| | - Vincent Emond
- Neuroscience axis, CHU de Québec-Université Laval Research Center, Quebec City, QC, Canada
| | - Anne Gangloff
- Clinical Research Unit, CHU de Québec Research Centre, QC, Canada
| | - Frederic Calon
- Faculty of pharmacy, Laval University, Quebec City, QC, Canada.,Neuroscience axis, CHU de Québec-Université Laval Research Center, Quebec City, QC, Canada.,OptiNutriBrain International Associated Laboratory (NutriNeuro France-INAF Canada).,Institute of Nutrition and Functional Foods, Université Laval, Quebec City, QC, Canada
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285
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Generation and quality control of lipidomics data for the alzheimer's disease neuroimaging initiative cohort. Sci Data 2018; 5:180263. [PMID: 30457571 PMCID: PMC6244184 DOI: 10.1038/sdata.2018.263] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 10/04/2018] [Indexed: 11/30/2022] Open
Abstract
Alzheimer’s disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/
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286
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Granger MW, Liu H, Fowler CF, Blanchard AP, Taylor MW, Sherman SPM, Xu H, Le W, Bennett SAL. Distinct disruptions in Land's cycle remodeling of glycerophosphocholines in murine cortex mark symptomatic onset and progression in two Alzheimer's disease mouse models. J Neurochem 2018; 149:499-517. [PMID: 30040874 DOI: 10.1111/jnc.14560] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 07/04/2018] [Accepted: 07/20/2018] [Indexed: 12/17/2022]
Abstract
Changes in glycerophosphocholine metabolism are observed in Alzheimer's disease; however, it is not known whether these metabolic disruptions are linked to cognitive decline. Here, using unbiased lipidomic approaches and direct biochemical assessments, we profiled Land's cycle lipid remodeling in the hippocampus, frontal cortex, and temporal-parietal-entorhinal cortices of human amyloid beta precursor protein (ΑβPP) over-expressing mice. We identified a cortex-specific hypo-metabolic signature at symptomatic onset and a cortex-specific hyper-metabolic signature of Land's cycle glycerophosphocholine remodeling over the course of progressive behavioral decline. When N5 TgCRND8 and ΑβPPS we /PSIdE9 mice first exhibited deficits in the Morris Water Maze, levels of lyso-phosphatidylcholines, LPC(18:0/0:0), LPC(16:0/0:0), LPC(24:6/0:0), LPC(25:6/0:0), the lyso-platelet-activating factor (PAF), LPC(O-18:0/0:0), and the PAF, PC(O-22:6/2:0), declined as a result of reduced calcium-dependent cytosolic phospholipase A2 α (cPLA2 α) activity in all cortices but not hippocampus. Chronic intermittent hypoxia, an environmental risk factor that triggers earlier learning memory impairment in ΑβPPS we /PSIdE9 mice, elicited these same metabolic changes in younger animals. Thus, this lipidomic signature of phenoconversion appears age-independent. By contrast, in symptomatic N5 TgCRND8 mice, cPLA2 α activity progressively increased; overall Lyso-phosphatidylcholines (LPC) and LPC(O) and PC(O-18:1/2:0) levels progressively rose. Enhanced cPLA2 α activity was only detected in transgenic mice; however, age-dependent increases in the PAF acetylhydrolase 1b α1 to α2 expression ratio, evident in both transgenic and non-transgenic mice, reduced PAF hydrolysis thereby contributing to PAF accumulation. Taken together, these data identify distinct age-independent and age-dependent disruptions in Land's cycle metabolism linked to symptomatic onset and progressive behavioral decline in animals with pre-existing Αβ pathology. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.
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Affiliation(s)
- Matthew W Granger
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Hui Liu
- Department of Neurology, Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Caitlin F Fowler
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Alexandre P Blanchard
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Matthew W Taylor
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Samantha P M Sherman
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Hongbin Xu
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Weidong Le
- Department of Neurology, Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China.,Center for Clinical Research on Neurological Diseases, the 1st Affiliated Hospital, Dailan Medical University, Dailan, China
| | - Steffany A L Bennett
- Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, Centre for Catalysis Research and Innovation, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
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287
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Morris JC, Petersen RC, Saykin AJ, Shaw LM, Toga AW, Trojanowski JQ. Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement 2018; 15:106-152. [PMID: 30321505 DOI: 10.1016/j.jalz.2018.08.005] [Citation(s) in RCA: 246] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Accepted: 08/21/2018] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. METHODS We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/). RESULTS (1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. DISCUSSION ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.
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Affiliation(s)
- Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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288
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Sapkota S, Huan T, Tran T, Zheng J, Camicioli R, Li L, Dixon RA. Alzheimer's Biomarkers From Multiple Modalities Selectively Discriminate Clinical Status: Relative Importance of Salivary Metabolomics Panels, Genetic, Lifestyle, Cognitive, Functional Health and Demographic Risk Markers. Front Aging Neurosci 2018; 10:296. [PMID: 30333744 PMCID: PMC6175993 DOI: 10.3389/fnagi.2018.00296] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Accepted: 09/10/2018] [Indexed: 12/11/2022] Open
Abstract
Background: Among the neurodegenerative diseases of aging, sporadic Alzheimer’s disease (AD) is the most prevalent and perhaps the most feared. With virtually no success at finding pharmaceutical therapeutics for altering progressive AD after diagnosis, research attention is increasingly directed at discovering biological and other markers that detect AD risk in the long asymptomatic phase. Both early detection and precision preclinical intervention require systematic investigation of multiple modalities and combinations of AD-related biomarkers and risk factors. We extend recent unbiased metabolomics research that produced a set of metabolite biomarker panels tailored to the discrimination of cognitively normal (CN), cognitively impaired and AD patients. Specifically, we compare the prediction importance of these panels with five other sets of modifiable and non-modifiable AD risk factors (genetic, lifestyle, cognitive, functional health and bio-demographic) in three clinical groups. Method: The three groups were: CN (n = 35), mild cognitive impairment (MCI; n = 25), and AD (n = 22). In a series of three pairwise comparisons, we used machine learning technology random forest analysis (RFA) to test relative predictive importance of up to 19 risk biomarkers from the six AD risk domains. Results: The three RFA multimodal prediction analyses produced significant discriminating risk factors. First, discriminating AD from CN was the AD metabolite panel and two cognitive markers. Second, discriminating AD from MCI was the AD/MCI metabolite panel and two cognitive markers. Third, discriminating MCI from CN was the MCI metabolite panel and seven markers from four other risk modalities: genetic, lifestyle, cognition and functional health. Conclusions: Salivary metabolomics biomarker panels, supplemented by other risk markers, were robust predictors of: (1) clinical differences in impairment and dementia and even; (2) subtle differences between CN and MCI. For the latter, the metabolite panel was supplemented by biomarkers that were both modifiable (e.g., functional) and non-modifiable (e.g., genetic). Comparing, integrating and identifying important multi-modal predictors may lead to novel combinations of complex risk profiles potentially indicative of neuropathological changes in asymptomatic or preclinical AD.
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Affiliation(s)
- Shraddha Sapkota
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Tao Huan
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Tran Tran
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Jiamin Zheng
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.,Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Roger A Dixon
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.,Department of Psychology, University of Alberta, Edmonton, AB, Canada
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289
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Next-generation biomarker discovery in Alzheimer's disease using metabolomics - from animal to human studies. Bioanalysis 2018; 10:1525-1546. [PMID: 30198770 DOI: 10.4155/bio-2018-0135] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.
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290
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Alzheimer's disease in the omics era. Clin Biochem 2018; 59:9-16. [DOI: 10.1016/j.clinbiochem.2018.06.011] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Revised: 05/30/2018] [Accepted: 06/15/2018] [Indexed: 12/31/2022]
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291
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Tang Y, Lutz MW, Xing Y. A systems-based model of Alzheimer's disease. Alzheimers Dement 2018; 15:168-171. [PMID: 30102884 DOI: 10.1016/j.jalz.2018.06.3058] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 06/15/2018] [Indexed: 12/21/2022]
Abstract
The new National Institute on Aging and the Alzheimer's Association Research Framework for Alzheimer's disease has been developed to accelerate drug discovery and offer a common structure and language to construct new Alzheimer's disease conceptual models. However, as a "complex" disease, a model based on systems-level understanding is needed to accommodate the complex, interacting etiologic pathways and the system-level changes associated with Alzheimer's disease pathogenesis and interventions that are currently known and which will be identified in the future. To accomplish this, the evolution of the structure of the research framework itself should be encouraged.
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Affiliation(s)
- Yi Tang
- Innovation Center for Neurological Disorders, Department of Neurology, Xuan Wu Hospital, Capital Medical University, Beijing, China.
| | - Michael W Lutz
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - Yi Xing
- Innovation Center for Neurological Disorders, Department of Neurology, Xuan Wu Hospital, Capital Medical University, Beijing, China
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292
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Instability of personal human metabotype is linked to all-cause mortality. Sci Rep 2018; 8:9810. [PMID: 29955084 PMCID: PMC6023858 DOI: 10.1038/s41598-018-27958-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 06/13/2018] [Indexed: 12/17/2022] Open
Abstract
Disruption of metabolic homeostasis is an important factor in many diseases. Various metabolites have been linked to higher risk of morbidity and all-cause mortality using metabolomics in large population-based cohorts. In these studies, baseline metabolite levels were compared across subjects to identify associations with health outcomes, implying the existence of 'healthy' concentration ranges that are equally applicable to all individuals. Here, we focused on intra-individual changes in metabolite levels over time and their link to mortality, potentially allowing more personalized risk assessment. We analysed targeted metabolomics data for 134 blood metabolites from 1409 participants in the population-based CARLA cohort at baseline and after four years. Metabotypes of the majority of participants (59%) were extremely stable over time indicated by high correlation between the subjects' metabolite profiles at the two time points. Metabotype instability and, in particular, decrease of valine were associated with higher risk of all-cause mortality in 7.9 years of follow-up (hazard ratio (HR) = 1.5(95%CI = 1.0-2.3) and 0.2(95%CI = 0.1-0.3)) after multifactorial adjustment. Excluding deaths that occurred in the first year after metabolite profiling showed similar results (HR = 1.8(95%CI = 1.1-2.8)). Lower metabotype stability was also associated with incident cardiovascular disease (OR = 1.2(95%CI = 1.0-1.3)). Therefore, changes in the personal metabotype might be a valuable indicator of pre-clinical disease.
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293
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Wolters FJ, Adams HH, Bos D, Licher S, Ikram MA. Three Decades of Dementia Research: Insights from One Small Community of Indomitable Rotterdammers. J Alzheimers Dis 2018; 64:S145-S159. [DOI: 10.3233/jad-179938] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Frank J. Wolters
- Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Hieab H.H. Adams
- Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Daniel Bos
- Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Silvan Licher
- Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands
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López-López Á, López-Gonzálvez Á, Barker-Tejeda TC, Barbas C. A review of validated biomarkers obtained through metabolomics. Expert Rev Mol Diagn 2018; 18:557-575. [PMID: 29808702 DOI: 10.1080/14737159.2018.1481391] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.
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Affiliation(s)
- Ángeles López-López
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
| | - Ángeles López-Gonzálvez
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
| | - Tomás Clive Barker-Tejeda
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
| | - Coral Barbas
- a Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain
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295
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Tynkkynen J, Chouraki V, van der Lee SJ, Hernesniemi J, Yang Q, Li S, Beiser A, Larson MG, Sääksjärvi K, Shipley MJ, Singh-Manoux A, Gerszten RE, Wang TJ, Havulinna AS, Würtz P, Fischer K, Demirkan A, Ikram MA, Amin N, Lehtimäki T, Kähönen M, Perola M, Metspalu A, Kangas AJ, Soininen P, Ala-Korpela M, Vasan RS, Kivimäki M, van Duijn CM, Seshadri S, Salomaa V. Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer's disease: A prospective study in eight cohorts. Alzheimers Dement 2018; 14:723-733. [PMID: 29519576 PMCID: PMC6082422 DOI: 10.1016/j.jalz.2018.01.003] [Citation(s) in RCA: 163] [Impact Index Per Article: 27.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 07/07/2017] [Accepted: 01/15/2018] [Indexed: 12/11/2022]
Abstract
INTRODUCTION Metabolite, lipid, and lipoprotein lipid profiling can provide novel insights into mechanisms underlying incident dementia and Alzheimer's disease. METHODS We studied eight prospective cohorts with 22,623 participants profiled by nuclear magnetic resonance or mass spectrometry metabolomics. Four cohorts were used for discovery with replication undertaken in the other four to avoid false positives. For metabolites that survived replication, combined association results are presented. RESULTS Over 246,698 person-years, 995 and 745 cases of incident dementia and Alzheimer's disease were detected, respectively. Three branched-chain amino acids (isoleucine, leucine, and valine), creatinine and two very low density lipoprotein (VLDL)-specific lipoprotein lipid subclasses were associated with lower dementia risk. One high density lipoprotein (HDL; the concentration of cholesterol esters relative to total lipids in large HDL) and one VLDL (total cholesterol to total lipids ratio in very large VLDL) lipoprotein lipid subclass was associated with increased dementia risk. Branched-chain amino acids were also associated with decreased Alzheimer's disease risk and the concentration of cholesterol esters relative to total lipids in large HDL with increased Alzheimer's disease risk. DISCUSSION Further studies can clarify whether these molecules play a causal role in dementia pathogenesis or are merely markers of early pathology.
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Affiliation(s)
- Juho Tynkkynen
- Department of Cardiology, Tays Heart Hospital, Tampere University Hospital and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Vincent Chouraki
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; The Framingham Heart Study, Framingham, MA, USA; Lille University, Inserm, Lille University Hospital, Institut Pasteur de Lille, U1167 - RID-AGE - Risk Factors and Molecular Determinants of Aging-Related Diseases, Labex Distalz, Lille, France
| | | | - Jussi Hernesniemi
- Department of Cardiology, Tays Heart Hospital, Tampere University Hospital and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Qiong Yang
- The Framingham Heart Study, Framingham, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Shuo Li
- The Framingham Heart Study, Framingham, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Alexa Beiser
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; The Framingham Heart Study, Framingham, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Martin G Larson
- The Framingham Heart Study, Framingham, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Katri Sääksjärvi
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Martin J Shipley
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, UK; INSERM, U1018, Centre for Research in Epidemiology and Population Health, France
| | - Robert E Gerszten
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thomas J Wang
- Vanderbilt Heart and Vascular Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Aki S Havulinna
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Peter Würtz
- Nightingale Health Ltd, Helsinki, Finland; Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Ayse Demirkan
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Markus Perola
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland; Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland; Estonian Genome Center, University of Tartu, Tartu, Estonia
| | | | | | - Pasi Soininen
- Nightingale Health Ltd, Helsinki, Finland; Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland; Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK; Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Ramachandran S Vasan
- The Framingham Heart Study, Framingham, MA, USA; Department of Medicine, Sections of Preventive Medicine and Cardiology, Boston University School of Medicine, Boston, MA, USA
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Cornelia M van Duijn
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands; Leiden Academic Center for Drug Reseach (LACDR), Leiden University, Leiden, The Netherlands
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; The Framingham Heart Study, Framingham, MA, USA; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA.
| | - Veikko Salomaa
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland.
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296
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Morris JK, Piccolo BD, Shankar K, Thyfault JP, Adams SH. The serum metabolomics signature of type 2 diabetes is obscured in Alzheimer's disease. Am J Physiol Endocrinol Metab 2018; 314:E584-E596. [PMID: 29351484 PMCID: PMC6032067 DOI: 10.1152/ajpendo.00377.2017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 12/07/2017] [Accepted: 12/20/2017] [Indexed: 12/19/2022]
Abstract
There is evidence for systemic metabolic impairment in Alzheimer's disease (AD), and type 2 diabetes (T2D) increases AD risk. Although studies analyzing blood metabolomics signatures have shown differences between cognitively healthy (CH) and AD subjects, these signatures have not been compared with individuals with T2D. We utilized untargeted analysis platforms (primary metabolism and complex lipids) to characterize the serum metabolome of 126 overnight-fasted elderly subjects classified into four groups based upon AD status (CH or AD) and T2D status [nondiabetic (ND) or T2D]. Cognitive diagnosis groups were a priori weighted equally with T2D subjects. We hypothesized that AD subjects would display a metabolic profile similar to cognitively normal elderly individuals with T2D. However, partial least squares-discriminant analysis (PLS-DA) modeling resulted in poor classification across the four groups (<50% classification accuracy of test subjects). Binary classification of AD vs. CH was poor, but binary classification of T2D vs. ND was good, providing >79.5% and >76.9% classification accuracy for held-out samples using primary metabolism and complex lipids, respectively. When modeling was limited to CH subjects, T2D discrimination improved for the primary metabolism platform (>89.5%) and remained accurate for complex lipids (>73% accuracy). Greater abundances of glucose, fatty acids (C20:2), and phosphatidylcholines and lower abundances of glycine, maleimide, octanol, and tryptophan, cholesterol esters, phosphatidylcholines, and sphingomyelins were identified in CH subjects with T2D relative to those without T2D. In contrast, T2D was not accurately discriminated within AD subjects. Results herein suggest that AD may obscure the typical metabolic phenotype of T2D.
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Affiliation(s)
- Jill K Morris
- University of Kansas Department of Neurology, University of Kansas Alzheimer's Disease Center , Kansas City, Kansas
- University of Kansas Alzheimer's Disease Center, Fairway, Kansas
| | - Brian D Piccolo
- Arkansas Children's Nutrition Center , Little Rock, Arkansas
- Department of Pediatrics, University of Arkansas for Medical Sciences , Little Rock, Arkansas
| | - Kartik Shankar
- Arkansas Children's Nutrition Center , Little Rock, Arkansas
- Department of Pediatrics, University of Arkansas for Medical Sciences , Little Rock, Arkansas
| | - John P Thyfault
- University of Kansas Department of Neurology, University of Kansas Alzheimer's Disease Center , Kansas City, Kansas
- University of Kansas Alzheimer's Disease Center, Fairway, Kansas
- University of Kansas Department of Molecular and Integrative Physiology , Kansas City, Kansas
- Kansas City Veterans Affairs Medical Center , Kansas City, Missouri
| | - Sean H Adams
- Arkansas Children's Nutrition Center , Little Rock, Arkansas
- Department of Pediatrics, University of Arkansas for Medical Sciences , Little Rock, Arkansas
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297
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Sun J, Jing S, Jiang R, Wang C, Zhang C, Chen J, Li H. Metabolomics study of the therapeutic mechanism of Schisandra chinensis lignans on aging rats induced by d-galactose. Clin Interv Aging 2018; 13:829-841. [PMID: 29750025 PMCID: PMC5935080 DOI: 10.2147/cia.s163275] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Objective The aim of this study was to evaluate the antiaging effect of Schisandra chinensis lignans (SCL) by analyzing the characteristics in the serum of d-galactose (d-gal)-induced rats. Methods Forty male Wistar rats were randomly divided into control group, d-gal model group, low-dose SCL group (50 mg/kg/d), medium-dose SCL group (100 mg/kg/d), and high-dose SCL group (200 mg/kg/d). A serum metabolomics analysis method based on rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry was carried out to study the characteristics of d-gal-induced aging rats and evaluate the antiaging effects of SCL, and multivariate statistical analysis was performed for pattern recognition and characteristic metabolites identification. The relative levels of p19, p53, and p21 genes in the brain tissue were measured by quantitative real-time polymerase chain reaction for investigating the underlying mechanism. Results Metabolomics analysis showed that 15 biomarkers were identified and 13 of them recovered to the normal levels after the administration of SCL. Based on the pathway analysis, the antiaging mechanisms of SCL might be involved in the following metabolic pathways: energy, amino acid, lipid, and phospholipid metabolism. Furthermore, SCL significantly inhibited the mRNA expression level of p19, p53, and p21 in the brain of aging rats induced by d-gal. Conclusion These results suggest that SCL can delay rat aging induced by d-gal through multiple pathways.
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Affiliation(s)
- Jinghui Sun
- Department of Pharmacology, College of Pharmacy, Beihua University, Jilin, People's Republic of China
| | - Shu Jing
- General Surgery Area, Affiliated Hospital of Beihua University, Jilin, People's Republic of China
| | - Rui Jiang
- Jilin Technology Innovation Center for Chinese Medicine Biotechnology, College of Chemistry and Biology, Beihua University, Jilin, People's Republic of China
| | - Chunmei Wang
- Department of Pharmacology, College of Pharmacy, Beihua University, Jilin, People's Republic of China
| | - Chengyi Zhang
- Department of Pharmacology, College of Pharmacy, Beihua University, Jilin, People's Republic of China
| | - Jianguang Chen
- Department of Pharmacology, College of Pharmacy, Beihua University, Jilin, People's Republic of China
| | - He Li
- Department of Pharmacology, College of Pharmacy, Beihua University, Jilin, People's Republic of China
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298
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Wilkins JM, Trushina E. Application of Metabolomics in Alzheimer's Disease. Front Neurol 2018; 8:719. [PMID: 29375465 PMCID: PMC5770363 DOI: 10.3389/fneur.2017.00719] [Citation(s) in RCA: 151] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 12/13/2017] [Indexed: 12/22/2022] Open
Abstract
Progress toward the development of efficacious therapies for Alzheimer’s disease (AD) is halted by a lack of understanding early underlying pathological mechanisms. Systems biology encompasses several techniques including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Metabolomics is the newest omics platform that offers great potential for the diagnosis and prognosis of neurodegenerative diseases as an individual’s metabolome reflects alterations in genetic, transcript, and protein profiles and influences from the environment. Advancements in the field of metabolomics have demonstrated the complexity of dynamic changes associated with AD progression underscoring challenges with the development of efficacious therapeutic interventions. Defining systems-level alterations in AD could provide insights into disease mechanisms, reveal sex-specific changes, advance the development of biomarker panels, and aid in monitoring therapeutic efficacy, which should advance individualized medicine. Since metabolic pathways are largely conserved between species, metabolomics could improve the translation of preclinical research conducted in animal models of AD into humans. A summary of recent developments in the application of metabolomics to advance the AD field is provided below.
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Affiliation(s)
- Jordan Maximillian Wilkins
- Mitochondrial Neurobiology and Therapeutics Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Eugenia Trushina
- Mitochondrial Neurobiology and Therapeutics Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States.,Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
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299
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Tenenbaum JD, Blach C. Best practices and lessons learned from reuse of 4 patient-derived metabolomics datasets in Alzheimer's disease. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018; 23:280-291. [PMID: 29218889 PMCID: PMC5783180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The importance of open data has been increasingly recognized in recent years. Although the sharing and reuse of clinical data for translational research lags behind best practices in biological science, a number of patient-derived datasets exist and have been published enabling translational research spanning multiple scales from molecular to organ level, and from patients to populations. In seeking to replicate metabolomic biomarker results in Alzheimer's disease our team identified three independent cohorts in which to compare findings. Accessing the datasets associated with these cohorts, understanding their content and provenance, and comparing variables between studies was a valuable exercise in exploring the principles of open data in practice. It also helped inform steps taken to make the original datasets available for use by other researchers. In this paper we describe best practices and lessons learned in attempting to identify, access, understand, and analyze these additional datasets to advance research reproducibility, as well as steps taken to facilitate sharing of our own data.
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Affiliation(s)
- Jessica D. Tenenbaum
- Department of Biostatistics & Bioinformatics, Duke University, Box 2721, Durham, NC 27710, USA,
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Box 104775, Durham, NC 27701, USA,
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300
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Varma VR, Oommen AM, Varma S, Casanova R, An Y, Andrews RM, O’Brien R, Pletnikova O, Troncoso JC, Toledo J, Baillie R, Arnold M, Kastenmueller G, Nho K, Doraiswamy PM, Saykin AJ, Kaddurah-Daouk R, Legido-Quigley C, Thambisetty M. Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study. PLoS Med 2018; 15:e1002482. [PMID: 29370177 PMCID: PMC5784884 DOI: 10.1371/journal.pmed.1002482] [Citation(s) in RCA: 306] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 11/27/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. METHODS AND FINDINGS Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and "asymptomatic Alzheimer's disease" (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes-sphingolipids and glycerophospholipids-that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer's Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of each metabolite to severity of AD pathology and disease progression (Endophenotype Association Score in Early Alzheimer's Disease [EASE-AD]). Finally, we mapped the main metabolite classes emerging from our analyses to key biological pathways implicated in AD pathogenesis. We found that distinct sphingolipid species including sphingomyelin (SM) with acyl residue sums C16:0, C18:1, and C16:1 (SM C16:0, SM C18:1, SM C16:1) and hydroxysphingomyelin with acyl residue sum C14:1 (SM (OH) C14:1) were consistently associated with severity of AD pathology at autopsy and AD progression across prodromal and preclinical stages. Higher log-transformed blood concentrations of all four sphingolipids in cognitively normal individuals were significantly associated with increased risk of future conversion to incident AD: SM C16:0 (hazard ratio [HR] = 4.430, 95% confidence interval [CI] = 1.703-11.520, p = 0.002), SM C16:1 (HR = 3.455, 95% CI = 1.516-7.873, p = 0.003), SM (OH) C14:1 (HR = 3.539, 95% CI = 1.373-9.122, p = 0.009), and SM C18:1 (HR = 2.255, 95% CI = 1.047-4.855, p = 0.038). The sphingolipid species identified map to several biologically relevant pathways implicated in AD, including tau phosphorylation, amyloid-β (Aβ) metabolism, calcium homeostasis, acetylcholine biosynthesis, and apoptosis. Our study has limitations: the relatively small number of brain tissue samples may have limited our power to detect significant associations, control for heterogeneity between groups, and replicate our findings in independent, autopsy-derived brain samples. CONCLUSIONS We present a novel framework to identify biologically relevant brain and blood metabolites associated with disease pathology and progression during the prodromal and preclinical stages of AD. Our results show that perturbations in sphingolipid metabolism are consistently associated with endophenotypes across preclinical and prodromal AD, as well as with AD pathology at autopsy. Sphingolipids may be biologically relevant biomarkers for the early detection of AD, and correcting perturbations in sphingolipid metabolism may be a plausible and novel therapeutic strategy in AD.
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Affiliation(s)
- Vijay R. Varma
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, United States of America
| | - Anup M. Oommen
- Consilience Research Advisors LLP, Bengaluru, Karnataka, India
| | - Sudhir Varma
- HiThru Analytics, Laurel, Maryland, United States of America
| | - Ramon Casanova
- Department of Biostatistical Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Yang An
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, United States of America
| | - Ryan M. Andrews
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Richard O’Brien
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Olga Pletnikova
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Juan C. Troncoso
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Jon Toledo
- Department of Neurology, Houston Methodist Hospital, Houston, Texas, United States of America
| | - Rebecca Baillie
- Rosa & Co LLC, San Carlos, California, United States of America
| | - Matthias Arnold
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Gabi Kastenmueller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | - P. Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, United States of America
- Department of Medicine, Duke University, Durham, North Carolina, United States of America
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, United States of America
- Department of Medicine, Duke University, Durham, North Carolina, United States of America
| | | | - Madhav Thambisetty
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, United States of America
- * E-mail:
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