101
|
Veiga S, Wahrheit J, Rodríguez-Martín A, Sonntag D. Quantitative Metabolomics in Alzheimer's Disease: Technical Considerations for Improved Reproducibility. Methods Mol Biol 2018; 1779:463-470. [PMID: 29886550 DOI: 10.1007/978-1-4939-7816-8_28] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Metabolomics is the comprehensive analysis of small molecules (metabolites) that are intermediates or endpoints of metabolism. Since metabolites change more rapidly to both external and internal stimuli than genes and proteins, metabolomics provides a more sensitive tool to study physiological changes to a wide range of factors such age, medication, or disease status. Therefore, metabolomics is being increasingly used for the study of several pathological states, including complex diseases like Alzheimer's disease (AD).Both untargeted and targeted metabolomics have been applied for AD and both have provided diagnostic algorithms that accurately discriminate healthy patients from patients with AD by combining different metabolites. However, none of these algorithms have been replicated in larger, different cohorts, and a consensus in methodology has been claimed by the scientific community. The AbsoluteIDQ® p180 Kit (Biocrates, Life Science AG, Innsbruck, Austria) is to date the only commercially available, validated, and standardized assay that measures up to 188 metabolites in biological samples. This kit unifies methodology in a common user manual and provides quantitative measurements of metabolites, thus facilitating an easier comparison among studies and reducing the technical variability that might contribute to replication failures. Nevertheless, recent studies showed no replication even when using this kit, suggesting that additional measures should be taken to achieve replication of metabolite-based discriminative algorithms. The aim of this chapter is to provide technical guidance on how to apply quantitative metabolomic data to the definition of discriminative algorithms for the diagnosis of neurodegenerative diseases such as AD. This chapter will provide an overview of technical aspects on the whole process, from blood sampling to raw data handling, and will highlight several technical aspects in the process that could hamper replication attempts even when using validated and standardized assays, such as the AbsoluteIDQ® p180 Kit.
Collapse
|
102
|
Shi L, Baird AL, Westwood S, Hye A, Dobson R, Thambisetty M, Lovestone S. A Decade of Blood Biomarkers for Alzheimer's Disease Research: An Evolving Field, Improving Study Designs, and the Challenge of Replication. J Alzheimers Dis 2018; 62:1181-1198. [PMID: 29562526 PMCID: PMC5870012 DOI: 10.3233/jad-170531] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/11/2017] [Indexed: 12/22/2022]
Abstract
Blood-based biomarkers represent a less invasive and potentially cheaper approach for aiding Alzheimer's disease (AD) detection compared with cerebrospinal fluid and some neuroimaging biomarkers. Acknowledging that many in the field have made great progress, here we review some of the work that our group has pursued to identify and validate blood-based proteomic biomarkers through both case control and AD pathology endophenotype-based approaches. Our focus is primarily to identify a minimally invasive and hopefully cost-effective blood-based biomarker to reduce screen failure in clinical trials where participants have prodromal or even pre-clinical disease. We summarize some of the key findings and approaches taken in these biomarker studies, while addressing the main challenges, including that of limited replication in the field, and discuss opportunities for biomarker development.
Collapse
Affiliation(s)
- Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - Sarah Westwood
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Abdul Hye
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, and NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - Richard Dobson
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, and NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - Madhav Thambisetty
- Unit of Clinical and Translational Neuroscience, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | | |
Collapse
|
103
|
Kiddle SJ, Voyle N, Dobson RJB. A Blood Test for Alzheimer's Disease: Progress, Challenges, and Recommendations. J Alzheimers Dis 2018; 64:S289-S297. [PMID: 29614671 PMCID: PMC6010156 DOI: 10.3233/jad-179904] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Ever since the discovery of APOEɛ4 around 25 years ago, researchers have been excited about the potential of a blood test for Alzheimer's disease (AD). Since then researchers have looked for genetic, protein, metabolite, and/or gene expression markers of AD and related phenotypes. However, no blood test for AD is yet being used in the clinical setting. We first review the trends and challenges in AD blood biomarker research, before giving our personal recommendations to help researchers overcome these challenges. While some degree of consistency and replication has been seen across independent studies, several high-profile studies have seemingly failed to replicate. Partly due to academic incentives, there is a reluctance in the field to report predictive ability, to publish negative findings, and to independently replicate the work of others. If this can be addressed, then we will know sooner whether a blood test for AD or related phenotypes with clinical utility can be developed.
Collapse
Affiliation(s)
- Steven J. Kiddle
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK, SE5 8AF
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
| | - Nicola Voyle
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK, SE5 8AF
| | - Richard JB Dobson
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK, SE5 8AF
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK, SE5 8AF
- Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, London WC1E 6BT, UK
| |
Collapse
|
104
|
Weston PSJ, Poole T, Ryan NS, Nair A, Liang Y, Macpherson K, Druyeh R, Malone IB, Ahsan RL, Pemberton H, Klimova J, Mead S, Blennow K, Rossor MN, Schott JM, Zetterberg H, Fox NC. Serum neurofilament light in familial Alzheimer disease: A marker of early neurodegeneration. Neurology 2017; 89:2167-2175. [PMID: 29070659 PMCID: PMC5696646 DOI: 10.1212/wnl.0000000000004667] [Citation(s) in RCA: 192] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2017] [Accepted: 08/21/2017] [Indexed: 01/10/2023] Open
Abstract
Objectives: To investigate whether serum neurofilament light (NfL) concentration is increased in familial Alzheimer disease (FAD), both pre and post symptom onset, and whether it is associated with markers of disease stage and severity. Methods: We recruited 48 individuals from families with PSEN1 or APP mutations to a cross-sectional study: 18 had symptomatic Alzheimer disease (AD) and 30 were asymptomatic but at 50% risk of carrying a mutation. Serum NfL was measured using an ultrasensitive immunoassay on the single molecule array (Simoa) platform. Cognitive testing and MRI were performed; 33 participants had serial MRI, allowing calculation of atrophy rates. Genetic testing established mutation status. A generalized least squares regression model was used to compare serum NfL among symptomatic mutation carriers, presymptomatic carriers, and noncarriers, adjusting for age and sex. Spearman coefficients assessed associations between serum NfL and (1) estimated years to/from symptom onset (EYO), (2) cognitive measures, and (3) MRI measures of atrophy. Results: Nineteen of the asymptomatic participants were mutation carriers (mean EYO −9.6); 11 were noncarriers. Compared with noncarriers, serum NfL concentration was higher in both symptomatic (p < 0.0001) and presymptomatic mutation carriers (p = 0.007). Across all mutation carriers, serum NfL correlated with EYO (ρ = 0.81, p < 0.0001) and multiple cognitive and imaging measures, including Mini-Mental State Examination (ρ = −0.62, p = 0.0001), Clinical Dementia Rating Scale sum of boxes (ρ = 0.79, p < 0.0001), baseline brain volume (ρ = −0.62, p = 0.0002), and whole-brain atrophy rate (ρ = 0.53, p = 0.01). Conclusions: Serum NfL concentration is increased in FAD prior to symptom onset and correlates with measures of disease stage and severity. Serum NfL may thus be a feasible biomarker of early AD-related neurodegeneration.
Collapse
Affiliation(s)
- Philip S J Weston
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Teresa Poole
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Natalie S Ryan
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Akshay Nair
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Yuying Liang
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Kirsty Macpherson
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Ronald Druyeh
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Ian B Malone
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - R Laila Ahsan
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Hugh Pemberton
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Jana Klimova
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Simon Mead
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Kaj Blennow
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Martin N Rossor
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Jonathan M Schott
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nick C Fox
- From the Dementia Research Centre (P.S.J.W., T.P., N.S.R., A.N., Y.L., K.M., I.B.M., R.L.A., H.P., J.K., M.N.R., J.M.S., N.C.F.) and MRC Prion Unit (R.D., S.M.), Department of Neurodegenerative Diseases, UCL Institute of Neurology; Department of Medical Statistics (T.P.), London School of Hygiene & Tropical Medicine, UK; and Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology (K.B., H.Z.), the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
| |
Collapse
|
105
|
St John-Williams L, Blach C, Toledo JB, Rotroff DM, Kim S, Klavins K, Baillie R, Han X, Mahmoudiandehkordi S, Jack J, Massaro TJ, Lucas JE, Louie G, Motsinger-Reif AA, Risacher SL, Saykin AJ, Kastenmüller G, Arnold M, Koal T, Moseley MA, Mangravite LM, Peters MA, Tenenbaum JD, Thompson JW, Kaddurah-Daouk R. Targeted metabolomics and medication classification data from participants in the ADNI1 cohort. Sci Data 2017; 4:170140. [PMID: 29039849 PMCID: PMC5644370 DOI: 10.1038/sdata.2017.140] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Accepted: 08/08/2017] [Indexed: 02/01/2023] Open
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.
Collapse
Affiliation(s)
- Lisa St John-Williams
- Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC 27701, USA
| | - Jon B Toledo
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Neurology, Houston Methodist Hospital, Houston, TX 77030, USA
| | - Daniel M Rotroff
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC 27607, USA
| | - Sungeun Kim
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA.,Department of Electrical and Computer Engineering, State University of New York, Oswego, NY 13126, USA
| | | | | | - Xianlin Han
- Sanford Burnham Prebys Medical Discovery Institute, Orlando, FL 32827, USA
| | - Siamak Mahmoudiandehkordi
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC 27607, USA
| | - John Jack
- Department of Electrical and Computer Engineering, State University of New York, Oswego, NY 13126, USA
| | - Tyler J Massaro
- Department of Psychiatry and Behavioral Sciences, and the Duke Institute for Brain Sciences, Duke University, Durham, NC 27710, USA
| | - Joseph E Lucas
- Duke Social Sciences Research Institute, Duke University, Durham, NC 27708, USA
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, and the Duke Institute for Brain Sciences, Duke University, Durham, NC 27710, USA
| | - Alison A Motsinger-Reif
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC 27607, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | | | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg D-85764, Germany.,German Center for Diabetes Research, Neuherberg D-85764, Germany
| | - Matthias Arnold
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg D-85764, Germany
| | - Therese Koal
- BIOCRATES Life Sciences AG, Innsbruck 6020, Austria
| | - M Arthur Moseley
- Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA
| | | | | | - Jessica D Tenenbaum
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA
| | - J Will Thompson
- Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, and the Duke Institute for Brain Sciences, Duke University, Durham, NC 27710, USA
| |
Collapse
|
106
|
Karlíková R, Mičová K, Najdekr L, Gardlo A, Adam T, Majerová P, Friedecký D, Kováč A. Metabolic status of CSF distinguishes rats with tauopathy from controls. ALZHEIMERS RESEARCH & THERAPY 2017; 9:78. [PMID: 28934963 PMCID: PMC5609022 DOI: 10.1186/s13195-017-0303-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Accepted: 08/31/2017] [Indexed: 11/17/2022]
Abstract
Background Tauopathies represent heterogeneous groups of neurodegenerative diseases that are characterised by abnormal deposition of the microtubule-associated protein tau. Alzheimer’s disease is the most prevalent tauopathy, affecting more than 35 million people worldwide. In this study we investigated changes in metabolic pathways associated with tau-induced neurodegeneration. Methods Cerebrospinal fluid (CSF), plasma and brain tissue were collected from a transgenic rat model for tauopathies and from age-matched control animals. The samples were analysed by targeted and untargeted metabolomic methods using high-performance liquid chromatography coupled to mass spectrometry. Unsupervised and supervised statistical analysis revealed biochemical changes associated with the tauopathy process. Results Energy deprivation and potentially neural apoptosis were reflected in increased purine nucleotide catabolism and decreased levels of citric acid cycle intermediates and glucose. However, in CSF, increased levels of citrate and aconitate that can be attributed to glial activation were observed. Other significant changes were found in arginine and phosphatidylcholine metabolism. Conclusions Despite an enormous effort invested in development of biomarkers for tauopathies during the last 20 years, there is no clinically used biomarker or assay on the market. One of the most promising strategies is to create a panel of markers (e.g., small molecules, proteins) that will be continuously monitored and correlated with patients’ clinical outcome. In this study, we identified several metabolic changes that are affected during the tauopathy process and may be considered as potential markers of tauopathies in humans. Electronic supplementary material The online version of this article (doi:10.1186/s13195-017-0303-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Radana Karlíková
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Hněvotínská 5, 779 00, Olomouc, Czech Republic.,Department of Clinical Biochemistry, University Hospital Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic
| | - Kateřina Mičová
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Hněvotínská 5, 779 00, Olomouc, Czech Republic.,Department of Clinical Biochemistry, University Hospital Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic
| | - Lukáš Najdekr
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Hněvotínská 5, 779 00, Olomouc, Czech Republic.,Department of Clinical Biochemistry, University Hospital Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic
| | - Alžběta Gardlo
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Hněvotínská 5, 779 00, Olomouc, Czech Republic.,Department of Clinical Biochemistry, University Hospital Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic
| | - Tomáš Adam
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Hněvotínská 5, 779 00, Olomouc, Czech Republic.,Department of Clinical Biochemistry, University Hospital Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic.,Laboratory for Inherited Metabolic Disorders, Faculty of Medicine and Dentistry, Palacký University Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic
| | - Petra Majerová
- Institute of Neuroimmunology, Slovak Academy of Sciences, Dúbravská cesta 9, 84510, Bratislava, Slovak Republic.,AXON Neuroscience R&D, Dvořákovo nábrežie 10, 811 02, Bratislava, Slovak Republic
| | - David Friedecký
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Hněvotínská 5, 779 00, Olomouc, Czech Republic.,Department of Clinical Biochemistry, University Hospital Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic.,Laboratory for Inherited Metabolic Disorders, Faculty of Medicine and Dentistry, Palacký University Olomouc, I. P. Pavlova 6, 775 20, Olomouc, Czech Republic
| | - Andrej Kováč
- Institute of Neuroimmunology, Slovak Academy of Sciences, Dúbravská cesta 9, 84510, Bratislava, Slovak Republic. .,AXON Neuroscience R&D, Dvořákovo nábrežie 10, 811 02, Bratislava, Slovak Republic.
| |
Collapse
|
107
|
de Wilde MC, Vellas B, Girault E, Yavuz AC, Sijben JW. Lower brain and blood nutrient status in Alzheimer's disease: Results from meta-analyses. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2017; 3:416-431. [PMID: 29067348 PMCID: PMC5651428 DOI: 10.1016/j.trci.2017.06.002] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Alzheimer's disease (AD) patients are at risk of nutritional insufficiencies because of physiological and psychological factors. Recently, we showed the results of the meta-analyses indicating lower plasma levels of vitamins A, B12, C, E, and folate in AD patients compared with cognitively intact elderly controls (controls). Now, additional and more extensive literature searches were performed selecting studies which compare blood and brain/cerebrospinal fluid (CSF) levels of vitamins, minerals, trace elements, micronutrients, and fatty acids in AD patients versus controls. METHODS The literature published after 1980 in Cochrane Central Register of Controlled Trials, Medline, and Embase electronic databases was systematically analyzed using Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines to detect studies meeting the selection criteria. Search terms used are as follows: AD patients, Controls, vitamins, minerals, trace elements, micronutrients, and fatty acids. Random-effects meta-analyses using a linear mixed model with correction for age differences between AD patients and controls were performed when four or more publications were retrieved for a specific nutrient. RESULTS Random-effects meta-analyses of 116 selected publications showed significant lower CSF/brain levels of docosahexaenoic acid (DHA), choline-containing lipids, folate, vitamin B12, vitamin C, and vitamin E. In addition, AD patients showed lower circulatory levels of DHA, eicosapentaenoic acid, choline as phosphatidylcholine, and selenium. CONCLUSION The current data show that patients with AD have lower CSF/brain availability of DHA, choline, vitamin B12, folate, vitamin C, and vitamin E. Directionally, brain nutrient status appears to parallel the lower circulatory nutrient status; however, more studies are required measuring simultaneously circulatory and central nutrient status to obtain better insight in this observation. The brain is dependent on nutrient supply from the circulation, which in combination with nutrient involvement in AD-pathophysiological mechanisms suggests that patients with AD may have specific nutritional requirements. This hypothesis could be tested using a multicomponent nutritional intervention.
Collapse
Affiliation(s)
- Martijn C. de Wilde
- Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht, The Netherlands
| | - Bruno Vellas
- Gerontopole and UMR INSERM 1027 University Paul Sabatier, Toulouse University Hospital, Toulouse, France
| | - Elodie Girault
- Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht, The Netherlands
| | | | - John W. Sijben
- Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht, The Netherlands
| |
Collapse
|
108
|
Toledo JB, Arnold M, Kastenmüller G, Chang R, Baillie RA, Han X, Thambisetty M, Tenenbaum JD, Suhre K, Thompson JW, John-Williams LS, MahmoudianDehkordi S, Rotroff DM, Jack JR, Motsinger-Reif A, Risacher SL, Blach C, Lucas JE, Massaro T, Louie G, Zhu H, Dallmann G, Klavins K, Koal T, Kim S, Nho K, Shen L, Casanova R, Varma S, Legido-Quigley C, Moseley MA, Zhu K, Henrion MYR, van der Lee SJ, Harms AC, Demirkan A, Hankemeier T, van Duijn CM, Trojanowski JQ, Shaw LM, Saykin AJ, Weiner MW, Doraiswamy PM, Kaddurah-Daouk R. Metabolic network failures in Alzheimer's disease: A biochemical road map. Alzheimers Dement 2017; 13:965-984. [PMID: 28341160 PMCID: PMC5866045 DOI: 10.1016/j.jalz.2017.01.020] [Citation(s) in RCA: 309] [Impact Index Per Article: 44.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Revised: 01/25/2017] [Accepted: 01/26/2017] [Indexed: 12/11/2022]
Abstract
INTRODUCTION The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance. METHODS Fasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted. RESULTS Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1-42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease. DISCUSSION Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.
Collapse
Affiliation(s)
- Jon B Toledo
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Houston Methodist Hospital, Houston, TX, USA.
| | - Matthias Arnold
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - 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
| | - Rui Chang
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Xianlin Han
- Sanford Burnham Prebys Medical Discovery Institute, Orlando, FL, USA
| | - Madhav Thambisetty
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jessica D Tenenbaum
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Karsten Suhre
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Physiology and Biophysics, Weill Cornell Medical College, Qatar, Doha, Qatar
| | - J Will Thompson
- Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Lisa St John-Williams
- Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Siamak MahmoudianDehkordi
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC, USA
| | - Daniel M Rotroff
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC, USA
| | - John R Jack
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC, USA
| | - Alison Motsinger-Reif
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; The Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Joseph E Lucas
- Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA
| | - Tyler Massaro
- Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA
| | - Gregory Louie
- Department of Psychiatry, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Hongjie Zhu
- Department of Psychiatry, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | | | | | | | - Sungeun Kim
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; The Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; The Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Li Shen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; The Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ramon Casanova
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Sudhir Varma
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | | | - M Arthur Moseley
- Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Kuixi Zhu
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marc Y R Henrion
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Amy C Harms
- Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Ayse Demirkan
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands
| | - Thomas Hankemeier
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands; Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands; Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, Leiden, 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
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; The Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Michael W Weiner
- Department of Radiology, Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco, San Francisco, CA, USA
| | - P Murali Doraiswamy
- Department of Psychiatry, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA; Department of Medicine, Duke University Medical Center, Durham, NC, USA.
| |
Collapse
|
109
|
Dufouil C, Dubois B, Vellas B, Pasquier F, Blanc F, Hugon J, Hanon O, Dartigues JF, Harston S, Gabelle A, Ceccaldi M, Beauchet O, Krolak-Salmon P, David R, Rouaud O, Godefroy O, Belin C, Rouch I, Auguste N, Wallon D, Benetos A, Pariente J, Paccalin M, Moreaud O, Hommet C, Sellal F, Boutoleau-Bretonniére C, Jalenques I, Gentric A, Vandel P, Azouani C, Fillon L, Fischer C, Savarieau H, Operto G, Bertin H, Chupin M, Bouteloup V, Habert MO, Mangin JF, Chêne G. Cognitive and imaging markers in non-demented subjects attending a memory clinic: study design and baseline findings of the MEMENTO cohort. ALZHEIMERS RESEARCH & THERAPY 2017; 9:67. [PMID: 28851447 PMCID: PMC5576287 DOI: 10.1186/s13195-017-0288-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2017] [Accepted: 07/17/2017] [Indexed: 12/14/2022]
Abstract
Background The natural history and disease mechanisms of Alzheimer’s disease and related disorders (ADRD) are still poorly understood. Very few resources are available to scrutinise patients as early as needed and to use integrative approaches combining standardised, repeated clinical investigations and cutting-edge biomarker measurements. Methods In the nationwide French MEMENTO cohort study, participants were recruited in memory clinics and screened for either isolated subjective cognitive complaints (SCCs) or mild cognitive impairment (MCI; defined as test performance 1.5 SD below age, sex and education-level norms) while not demented (Clinical Dementia Rating [CDR] <1). Baseline data collection included neurological and physical examinations as well as extensive neuropsychological testing. To be included in the MEMENTO cohort, participants had to agree to undergo both brain magnetic resonance imaging (MRI) and blood sampling. Cerebral 18F-fluorodeoxyglucose positon emission tomography and lumbar puncture were optional. Automated analyses of cerebral MRI included assessments of volumes of whole-brain, hippocampal and white matter lesions. Results The 2323 participants, recruited from April 2011 to June 2014, were aged 71 years, on average (SD 8.7), and 62% were women. CDR was 0 in 40% of participants, and 30% carried at least one apolipoprotein E ε4 allele. We observed that more than half (52%) of participants had amnestic mild cognitive impairment (17% single-domain aMCI), 32% had non-amnestic mild cognitive impairment (16.9% single-domain naMCI) and 16% had isolated SCCs. Multivariable analyses of neuroimaging markers associations with cognitive categories showed that participants with aMCI had worse levels of imaging biomarkers than the others, whereas participants with naMCI had markers at intermediate levels between SCC and aMCI. The burden of white matter lesions tended to be larger in participants with aMCI. Independently of CDR, all neuroimaging and neuropsychological markers worsened with age, whereas differences were not consistent according to sex. Conclusions MEMENTO is a large cohort with extensive clinical, neuropsychological and neuroimaging data and represents a platform for studying the natural history of ADRD in a large group of participants with different subtypes of MCI (amnestic or not amnestic) or isolated SCCs. Trial registration Clinicaltrials.gov, NCT01926249. Registered on 16 August 2013. Electronic supplementary material The online version of this article (doi:10.1186/s13195-017-0288-0) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Carole Dufouil
- Centre Inserm U1219, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Bordeaux School of Public Health, Université de Bordeaux, 146 rue Léo Saignat, 33076, Bordeaux cedex, France. .,CHU de Bordeaux, Pole de sante publique, F-33000, Bordeaux, France.
| | - Bruno Dubois
- Institute of Memory and Alzheimer's Disease (IM2A) and Brain and Spine Institute (ICM) UMR S 1127, Department of Neurology, AP-HP, Pitié-Salpêtrière University Hospital, Sorbonne Universities, Pierre et Marie Curie University, F-75006, Paris, France
| | - Bruno Vellas
- Memory Resource and Research Centre of Toulouse, CHU de Toulouse, Hôpital La Grave-Casselardit, F-31000, Toulouse, France
| | - Florence Pasquier
- Memory Resource and Research Centre of Lille, CHRU de Lille, Hôpital Roger Salengro, F-59000, Lille, France.,University Lille, INSERM U1171, F-59000, Lille, France
| | - Frédéric Blanc
- Memory Resource and Research Centre of Strasbourg/Colmar, Department of Geriatrics, laboratoire ICube UMR 7357, FMTS, Hôpitaux Universitaires de Strasbourg, F-67000, Strasbourg, France
| | - Jacques Hugon
- Memory Resource and Research Centre of Paris Nord, AP-HP, Groupe Hospitalier Saint-Louis Lariboisière Fernand Widal, F-75010, Paris, France
| | - Olivier Hanon
- Memory Resource and Research Centre of Paris Broca, AP-HP, Hôpital Broca, F-75013, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, EA 4468, Paris, France
| | - Jean-François Dartigues
- Centre Inserm U1219, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Bordeaux School of Public Health, Université de Bordeaux, 146 rue Léo Saignat, 33076, Bordeaux cedex, France.,Memory Resource and Research Centre of Bordeaux, CHU de Bordeaux, Hôpital Pellegrin, F-33000, Bordeaux, France
| | - Sandrine Harston
- Memory Resource and Research Centre of Bordeaux, CHU de Bordeaux, Hôpital Xavier Arnozan, F-33000, Bordeaux, France
| | - Audrey Gabelle
- Memory Resource and Research Centre of Montpellier, CHU de Montpellier, Hôpital Gui de Chauliac, F-34000, Montpellier, France
| | - Mathieu Ceccaldi
- Memory Resource and Research Centre of Marseille, CHU de Marseille, Hôpital La Timone, F-13000, Marseille, France
| | - Olivier Beauchet
- Memory Resource and Research Centre of Angers, CHU d'Angers, F-49000, Angers, France
| | - Pierre Krolak-Salmon
- Memory Resource and Research Centre of Lyon, Hospices Civils de Lyon, Hôpital des Charpennes, F-69000, Lyon, France
| | - Renaud David
- Memory Resource and Research Centre of Nice, CHU de Nice, Institut Claude Pompidou, EA 7276 CoBTeK "Cognition Behaviour Technology", F-06100, Nice, France
| | - Olivier Rouaud
- Memory Resource and Research Centre of Dijon, CHU Dijon Bourgogne, Hôpital du Bocage, Hôpital de Champmaillot, F-21000, Dijon, France
| | - Olivier Godefroy
- Memory Resource and Research of Amiens, CHU Amiens Picardie, Hôpital Nord, F-80000, Amiens, France
| | - Catherine Belin
- Memory Clinic, Hôpital Avicenne, AP-HP, Hôpitaux Universitaires Paris-Seine-Saint-Denis, F-93009, Bobigny, France
| | - Isabelle Rouch
- Memory Resource and Research Centre of Saint-Etienne, CHU de Saint-Etienne, Hôpital Nord, F-42000, Saint-Etienne, France
| | - Nicolas Auguste
- Memory Resource and Research Centre of Saint-Etienne, CHU de Saint-Etienne, Hôpital de la Charité, F-42000, Saint-Etienne, France
| | - David Wallon
- Memory Resource and Research Centre of Rouen, Neurology Department, Rouen University Hospital, F-76031, Rouen, France
| | - Athanase Benetos
- Memory Resource and Research Centre of Nancy, CHU de Nancy, F-54000, Nancy, France
| | - Jérémie Pariente
- Memory Resource and Research Centre of Toulouse, CHU de Toulouse, Hôpital Purpan, F-31000, Toulouse, France
| | - Marc Paccalin
- Memory Resource and Research Centre of Poitiers, CHU de Poitiers, Hôpital de La Milétrie, F-86000, Poitiers, France
| | - Olivier Moreaud
- Memory Resource and Research Centre of Grenoble, CHU de Grenoble Alpes, Hôpital de la Tronche, F-38000, Grenoble, France
| | - Caroline Hommet
- Memory Resource and Research Centre of Center Region, CHRU de Tours, Hôpital Bretonneau, F-37000, Tours, France
| | - François Sellal
- Memory Resource and Research Centre of Strasbourg/Colmar, Hôpitaux Civils de Colmar, F-68000, Colmar, France.,Inserm U-118, Strasbourg University, F-67000, Strasbourg, France
| | | | - Isabelle Jalenques
- Memory Resource and Research Centre of Clermont-Ferrand, CHU de Clermont-Ferrand, F-63000, Clermont-Ferrand, France
| | - Armelle Gentric
- Memory Resource and Research Centre of Brest, CHRU de Brest, F-29000, Brest, France
| | - Pierre Vandel
- Memory Resource and Research Centre of Besançon, CHU de Besançon, Hôpital Jean Minjoz, Hôpital Saint-Jacques, F-25000, Besançon, France
| | - Chabha Azouani
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,Sorbonne Universités, UPMC Université Paris 06, Inserm, CNRS, Institut du cerveau et la moelle (ICM) - Hôpital Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
| | - Ludovic Fillon
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,Sorbonne Universités, UPMC Université Paris 06, Inserm, CNRS, Institut du cerveau et la moelle (ICM) - Hôpital Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
| | - Clara Fischer
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,Sorbonne Universités, UPMC Université Paris 06, Inserm, CNRS, Institut du cerveau et la moelle (ICM) - Hôpital Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
| | - Helen Savarieau
- Centre Inserm U1219, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Bordeaux School of Public Health, Université de Bordeaux, 146 rue Léo Saignat, 33076, Bordeaux cedex, France.,CHU de Bordeaux, Pole de sante publique, F-33000, Bordeaux, France
| | - Gregory Operto
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,Sorbonne Universités, UPMC Université Paris 06, Inserm, CNRS, Institut du cerveau et la moelle (ICM) - Hôpital Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
| | - Hugo Bertin
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,Nuclear Medicine Department, Pitié-Salpêtrière University Hospital, AP-HP, F-75006, Paris, France.,Laboratoire d'Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371, F-75006, Paris, France
| | - Marie Chupin
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,Sorbonne Universités, UPMC Université Paris 06, Inserm, CNRS, Institut du cerveau et la moelle (ICM) - Hôpital Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
| | - Vincent Bouteloup
- Centre Inserm U1219, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Bordeaux School of Public Health, Université de Bordeaux, 146 rue Léo Saignat, 33076, Bordeaux cedex, France.,CHU de Bordeaux, Pole de sante publique, F-33000, Bordeaux, France
| | - Marie-Odile Habert
- Nuclear Medicine Department, Pitié-Salpêtrière University Hospital, AP-HP, F-75006, Paris, France.,Laboratoire d'Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371, F-75006, Paris, France
| | - Jean-François Mangin
- Centre pour l'Acquisition et le Traitement des Images, NeuroSpin, I2BM, Commissariat à l'Energie Atomique, F-91400, Saclay, France.,NeuroSpin, I2BM, Commissariat à l'Energie Atomique, Université Paris-Saclay, F-91400, Saclay, France
| | - Geneviève Chêne
- Centre Inserm U1219, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Bordeaux School of Public Health, Université de Bordeaux, 146 rue Léo Saignat, 33076, Bordeaux cedex, France.,CHU de Bordeaux, Pole de sante publique, F-33000, Bordeaux, France
| | | |
Collapse
|
110
|
Bressler J, Yu B, Mosley TH, Knopman DS, Gottesman RF, Alonso A, Sharrett AR, Wruck LM, Boerwinkle E. Metabolomics and cognition in African American adults in midlife: the atherosclerosis risk in communities study. Transl Psychiatry 2017; 7:e1173. [PMID: 28934192 PMCID: PMC5538110 DOI: 10.1038/tp.2017.118] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Revised: 04/05/2017] [Accepted: 04/20/2017] [Indexed: 12/21/2022] Open
Abstract
Clinical studies have shown alterations in metabolic profiles when patients with mild cognitive impairment and Alzheimer's disease dementia were compared to cognitively normal subjects. Associations between 204 serum metabolites measured at baseline (1987-1989) and cognitive change were investigated in 1035 middle-aged community-dwelling African American participants in the biracial Atherosclerosis Risk in Communities (ARIC) Study. Cognition was evaluated using the Delayed Word Recall Test (DWRT; verbal memory), the Digit Symbol Substitution Test (DSST; processing speed) and the Word Fluency Test (WFT; verbal fluency) at visits 2 (1990-1992) and 4 (1996-1998). In addition, Cox regression was used to analyze the metabolites as predictors of incident hospitalized dementia between baseline and 2011. There were 141 cases among 1534 participants over a median 17.1-year follow-up period. After adjustment for established risk factors, one standard deviation increase in N-acetyl-1-methylhistidine was significantly associated with greater 6-year change in DWRT scores (β=-0.66 words; P=3.65 × 10-4). Two metabolites (one unnamed and a long-chain omega-6 polyunsaturated fatty acid found in vegetable oils (docosapentaenoate (DPA, 22:5 n-6)) were significantly associated with less decline on the DSST (DPA: β=1.25 digit-symbol pairs, P=9.47 × 10-5). Two unnamed compounds and three sex steroid hormones were associated with an increased risk of dementia (all P<3.9 × 10-4). The association of 4-androstene-3beta, 17beta-diol disulfate 1 with dementia was replicated in European Americans. These results demonstrate that screening the metabolome in midlife can detect biologically plausible biomarkers that may improve risk stratification for cognitive impairment at older ages.
Collapse
Affiliation(s)
- J Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - B Yu
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - T H Mosley
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - D S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R F Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - A Alonso
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - A R Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - L M Wruck
- Department of Biostatistics, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - E Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| |
Collapse
|
111
|
Delvaux E, Mastroeni D, Nolz J, Chow N, Sabbagh M, Caselli RJ, Reiman EM, Marshall FJ, Coleman PD. Multivariate analyses of peripheral blood leukocyte transcripts distinguish Alzheimer's, Parkinson's, control, and those at risk for developing Alzheimer's. Neurobiol Aging 2017; 58:225-237. [PMID: 28716532 DOI: 10.1016/j.neurobiolaging.2017.05.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2016] [Revised: 05/12/2017] [Accepted: 05/14/2017] [Indexed: 11/28/2022]
Abstract
The need for a reliable, simple, and inexpensive blood test for Alzheimer's disease (AD) suitable for use in a primary care setting is widely recognized. This has led to a large number of publications describing blood tests for AD, which have, for the most part, not been replicable. We have chosen to examine transcripts expressed by the cellular, leukocyte compartment of blood. We have used hypothesis-based cDNA arrays and quantitative PCR to quantify the expression of selected sets of genes followed by multivariate analyses in multiple independent samples. Rather than a single study with no replicates, we chose an experimental design in which there were multiple replicates using different platforms and different sample populations. We have divided 177 blood samples and 27 brain samples into multiple replicates to demonstrate the ability to distinguish early clinical AD (Clinical Dementia Rating scale 0.5), Parkinson's disease (PD), and cognitively unimpaired APOE4 homozygotes, as well as to determine persons at risk for future cognitive impairment with significant accuracy. We assess our methods in a training/test set and also show that the variables we use distinguish AD, PD, and control brain. Importantly, we describe the variability of the weights assigned to individual transcripts in multivariate analyses in repeated studies and suggest that the variability we describe may be the cause of inability to repeat many earlier studies. Our data constitute a proof of principle that multivariate analysis of the transcriptome related to cell stress and inflammation of peripheral blood leukocytes has significant potential as a minimally invasive and inexpensive diagnostic tool for diagnosis and early detection of risk for AD.
Collapse
Affiliation(s)
- Elaine Delvaux
- ASU-Banner Neurodegenerative Disease Research Center, Biodesign Institute, Arizona State University, Tempe, AZ, USA; Arizona Alzheimer Consortium, Phoenix, AZ, USA; Formerly at Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Diego Mastroeni
- ASU-Banner Neurodegenerative Disease Research Center, Biodesign Institute, Arizona State University, Tempe, AZ, USA; Arizona Alzheimer Consortium, Phoenix, AZ, USA; Formerly at Banner Sun Health Research Institute, Sun City, AZ, USA; Maastricht University, Medical Centre, Maastricht, The Netherlands
| | - Jennifer Nolz
- ASU-Banner Neurodegenerative Disease Research Center, Biodesign Institute, Arizona State University, Tempe, AZ, USA; Arizona Alzheimer Consortium, Phoenix, AZ, USA; Formerly at Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Nienwen Chow
- University of Rochester Medical Center, Rochester, NY, USA
| | | | | | | | | | - Paul D Coleman
- ASU-Banner Neurodegenerative Disease Research Center, Biodesign Institute, Arizona State University, Tempe, AZ, USA; Arizona Alzheimer Consortium, Phoenix, AZ, USA; Formerly at Banner Sun Health Research Institute, Sun City, AZ, USA.
| |
Collapse
|
112
|
Yi L, Liu W, Wang Z, Ren D, Peng W. Characterizing Alzheimer's disease through metabolomics and investigating anti-Alzheimer's disease effects of natural products. Ann N Y Acad Sci 2017. [PMID: 28632966 DOI: 10.1111/nyas.13385] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Lunzhao Yi
- Yunnan Food Safety Research Institute; Kunming University of Science and Technology; Kunming China
| | - Wenbin Liu
- Yunnan Food Safety Research Institute; Kunming University of Science and Technology; Kunming China
| | - Zhe Wang
- Department of Integrated Traditional Chinese & Western Medicine, the Second Xiangya Hospital; Central South University; Changsha Hunan China
| | - Dabing Ren
- Yunnan Food Safety Research Institute; Kunming University of Science and Technology; Kunming China
| | - Weijun Peng
- Department of Integrated Traditional Chinese & Western Medicine, the Second Xiangya Hospital; Central South University; Changsha Hunan China
| |
Collapse
|
113
|
Thambisetty M. Understanding mechanisms and seeking cures for Alzheimer's disease: why we must be "extraordinarily diverse". Am J Physiol Cell Physiol 2017; 313:C353-C361. [PMID: 28615163 DOI: 10.1152/ajpcell.00111.2017] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 06/13/2017] [Indexed: 12/29/2022]
Abstract
After more than a century since Dr. Alois Alzheimer first described the pathological hallmarks accompanying the defining clinical features of the disease, we have yet to deliver any meaningful disease-modifying treatments to our patients. In this article, I present a rationale for the need to be "extraordinarily diverse" in seeking effective ways to treat or prevent this devastating disease. This approach is based on applying a systems-biology perspective at the population level, using a diverse array of "OMICS" methodologies to identify molecular mechanisms associated with well-established AD risk factors including systemic inflammation, obesity, and insulin resistance. We believe that applying this strategy to understand longitudinal changes in human physiology during aging is of paramount importance in identifying meaningful opportunities to intervene effectively in AD.
Collapse
Affiliation(s)
- Madhav Thambisetty
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| |
Collapse
|
114
|
Corso G, Cristofano A, Sapere N, la Marca G, Angiolillo A, Vitale M, Fratangelo R, Lombardi T, Porcile C, Intrieri M, Di Costanzo A. Serum Amino Acid Profiles in Normal Subjects and in Patients with or at Risk of Alzheimer Dementia. Dement Geriatr Cogn Dis Extra 2017. [PMID: 28626469 PMCID: PMC5471778 DOI: 10.1159/000466688] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background/Aims Abnormalities in the plasma amino acid profile have been reported in Alzheimer disease (AD), but no data exist for the prodromal phase characterized by subjective memory complaint (SMC). It was our aim to understand if serum amino acid levels change along the continuum from normal to AD, and to identify possible diagnostic biomarkers. Methods Serum levels of 15 amino acids and 2 organic acids were determined in 4 groups of participants – 29 with probable AD, 18 with mild cognitive impairment (MCI), 24 with SMC, and 46 cognitively healthy subjects (HS) – by electrospray tandem mass spectrometry. Results Glutamate, aspartate, and phenylalanine progressively decreased, while citrulline, argininosuccinate, and homocitrulline progressively increased, from HS over SMC and MCI to AD. The panel including these 6 amino acids and 4 ratios (glutamate/citrulline, citrulline/phenylalanine, leucine plus isoleucine/phenylalanine, and arginine/phenylalanine) discriminated AD from HS with about 96% accuracy. Other panels including 20 biomarkers discriminated SMC or MCI from AD or HS with an accuracy ranging from 88 to 75%. Conclusion Amino acids contribute to a characteristic metabotype during the progression of AD along the continuum from health to frank dementia, and their monitoring in elderly individuals might help to detect at-risk subjects.
Collapse
Affiliation(s)
- Gaetano Corso
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Adriana Cristofano
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Nadia Sapere
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Giancarlo la Marca
- Newborn Screening, Biochemistry and Pharmacology Laboratories, Clinic of Pediatric Neurology, Meyer Children's Hospital, Florence, Italy.,Department of Neurosciences, Psychology, Pharmacology, and Child Health, University of Florence, Florence, Italy
| | - Antonella Angiolillo
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Michela Vitale
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Roberto Fratangelo
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Teresa Lombardi
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Carola Porcile
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Mariano Intrieri
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| | - Alfonso Di Costanzo
- Centre for Research and Training in Medicine for Aging, Department of Medicine and Health Sciences "Vincenzo Tiberio," University of Molise, Campobasso, Italy
| |
Collapse
|
115
|
Abstract
PURPOSE OF REVIEW Alzheimer's disease is the most common cause of dementia. There are still no disease modifying treatments that can cure or slow disease progression. Recently, Alzheimer's disease researchers have attempted to improve early detection and diagnostic criteria for Alzheimer's disease, with the rationale that treatment of disease, or even prevention, may be more successful during the early preclinical stages of Alzheimer's disease when neurodegenerative damage is not as widespread. As the brain has a high lipid content, lipidomics may offer novel insights into the underlying pathogenesis of Alzheimer's disease. This review reports on recent developments in the relatively unexplored field of lipidomics in Alzheimer's disease, including novel biomarkers and pathomechanisms of Alzheimer's disease. RECENT FINDINGS Numerous biomarker panels involving phospholipids and sphingolipids have been proposed, indicating perturbed lipid metabolism in early stages of Alzheimer's disease. Future strategies targeting these metabolic changes through dietary supplementation could have therapeutic benefits in at-risk individuals. SUMMARY Dysregulated lipid metabolism could reflect pathological changes in synaptic function and neuronal membranes, leading to cognitive decline. However, extensive validation in large independent cohorts is required before lipid biomarkers can be used clinically to assess Alzheimer's disease risk and progression.
Collapse
|
116
|
Dysregulation of lipids in Alzheimer's disease and their role as potential biomarkers. Alzheimers Dement 2017; 13:810-827. [PMID: 28242299 DOI: 10.1016/j.jalz.2017.01.008] [Citation(s) in RCA: 128] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2016] [Revised: 11/17/2016] [Accepted: 01/03/2017] [Indexed: 12/14/2022]
Abstract
The brain is highly enriched in lipids, and an intensive study of these lipids may be informative, not only of normal brain function but also of changes with age and in disease. In recent years, the development of highly sensitive mass spectrometry platforms and other high-throughput technologies has enabled the discovery of complex changes in the entire lipidome. This lipidomics approach promises to be a particularly useful tool for identifying diagnostic biomarkers for early detection of age-related neurodegenerative disease, such as Alzheimer's disease (AD), which has till recently been limited to protein- and gene-centric approaches. This review highlights known lipid changes affecting the AD brain and presents an update on the progress of lipid biomarker research in AD. Important considerations for designing large-scale lipidomics experiments are discussed to help standardize findings across different laboratories, as well as challenges associated with moving toward clinical application.
Collapse
|
117
|
Keshavan A, Heslegrave A, Zetterberg H, Schott JM. Blood Biomarkers for Alzheimer's Disease: Much Promise, Cautious Progress. Mol Diagn Ther 2017; 21:13-22. [PMID: 27738910 DOI: 10.1007/s40291-016-0241-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Biomarkers in Alzheimer's disease (AD) have the potential to allow early and more accurate diagnosis, predict disease progression, stratify individuals and track response to candidate therapies in drug trials. The first fluid biomarkers reflecting aspects of AD neuropathology were identified in cerebrospinal fluid (CSF) in the 1990s. Three CSF biomarkers (amyloid-β 1-42, total tau and phospho-tau) have consistently been shown to have diagnostic utility and are incorporated into the new diagnostic criteria for AD. These markers have also been shown in longitudinal studies to predict conversion of mild cognitive impairment to AD. However, a key issue with the use of CSF biomarkers as a screening test is the invasiveness of lumbar puncture. Over the last 20 years there has been an active quest for blood biomarkers, which could be easily acquired and tested repeatedly throughout the disease course. One approach to identifying such markers is to attempt to measure candidates that have already been identified in CSF. Until recently, this approach has been limited by assay sensitivity, but newer platforms now allow single molecule-level detection. Another approach is identification of candidates in large multiplex panels that allow for multiple analytes to be quantified in parallel. While both approaches show promise, to date no blood-based biomarker or combination of biomarkers has sufficient predictive value to have utility in clinical practice. In this review, an overview of promising blood protein candidates is provided, and the challenges of validating and converting these into practicable tests are discussed.
Collapse
Affiliation(s)
- Ashvini Keshavan
- Dementia Research Centre, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Amanda Heslegrave
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, Box 16, Queen Square, London, WC1N 3BG, UK.
| |
Collapse
|
118
|
Du Y, Zheng H, Xia H, Zhao L, Hu W, Bai G, Yan Z, Gao H. Early Effect of Amyloid β-Peptide on Hippocampal and Serum Metabolism in Rats Studied by an Integrated Method of NMR-Based Metabolomics and ANOVA-Simultaneous Component Analysis. BIOMED RESEARCH INTERNATIONAL 2017; 2017:3262495. [PMID: 28243597 PMCID: PMC5294748 DOI: 10.1155/2017/3262495] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 10/27/2016] [Indexed: 11/17/2022]
Abstract
Amyloid β (Aβ) deposition has been implicated in the pathogenesis of Alzheimer's disease. However, the early effect of Aβ deposition on metabolism remains unclear. In the present study, thus, we explored the metabolic changes in the hippocampus and serum during first 2 weeks of Aβ25-35 injection in rats by using an integrated method of NMR-based metabolomics and ANOVA-simultaneous component analysis (ASCA). Our results show that Aβ25-35 injection, time, and their interaction had statistically significant effects on the hippocampus and serum metabolome. Furthermore, we identified key metabolites that mainly contributed to these effects. After Aβ25-35 injection from 1 to 2 weeks, the levels of lactate, N-acetylaspartate, creatine, and taurine were decreased in rat hippocampus, while an increase in lactate and decreases in LDL/VLDL and glucose were observed in rat serum. Therefore, we suggest that the reduction in energy and lipid metabolism as well as an increase in anaerobic glycolysis may occur at the early stage of Aβ25-35 deposition.
Collapse
Affiliation(s)
- Yao Du
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Hong Zheng
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Huanhuan Xia
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Liangcai Zhao
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Wenyi Hu
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Guanghui Bai
- Radiology Department, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Zhihan Yan
- Radiology Department, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Hongchang Gao
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| |
Collapse
|
119
|
Thambisetty M, Casanova R, Varma S, Legido Quigley C. Peril beyond the winner's curse: A small sample size is the bane of biomarker discovery. Alzheimers Dement 2017; 13:606-607. [PMID: 28119051 DOI: 10.1016/j.jalz.2017.01.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Madhav Thambisetty
- Laboratory of Behavioral Neuroscience Clinical and Translational Neuroscience Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
| | | | | | | |
Collapse
|
120
|
Kim M, Nevado-Holgado A, Whiley L, Snowden SG, Soininen H, Kloszewska I, Mecocci P, Tsolaki M, Vellas B, Thambisetty M, Dobson RJ, Powell JF, Lupton MK, Simmons A, Velayudhan L, Lovestone S, Proitsi P, Legido-Quigley C. Association between Plasma Ceramides and Phosphatidylcholines and Hippocampal Brain Volume in Late Onset Alzheimer's Disease. J Alzheimers Dis 2017; 60:809-817. [PMID: 27911300 PMCID: PMC5676755 DOI: 10.3233/jad-160645] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/04/2016] [Indexed: 12/14/2022]
Abstract
Lipids such as ceramides and phosphatidylcholines (PC) have been found altered in the plasma of Alzheimer's disease (AD) patients in a number of discovery studies. For this reason, the levels of 6 ceramides and 3 PCs, with different fatty acid length and saturation levels, were measured in the plasma from 412 participants (AD n = 205, Control n = 207) using mass spectrometry coupled with ultra-performance liquid chromatography. After this, associations with AD status, brain atrophy, and age-related effects were studied. In the plasma of AD participants, cross-sectional analysis revealed elevated levels of three ceramides (Cer16:0 p < 0.01, Cer18:0 p < 0.01, Cer24:1 p < 0.05). In addition, two PCs in AD plasma (PC36:5 p < 0.05, PC38:6 p < 0.05) were found to be depleted compared to the control group, with PC36:5 also associating with hippocampal atrophy (p < 0.01). Age-specific analysis further revealed that levels of Cer16:0, Cer18:0, and Cer20:0 were associated with hippocampal atrophy only in younger participants (age < 75, p < 0.05), while all 3 PCs did so in the older participants (age > 75, p < 0.05). PC36:5 was associated with AD status in the younger group (p < 0.01), while PC38:6 and 40:6 did so in the older group (p < 0.05). In this study, elevated ceramides and depleted PCs were found in the plasma from 205 AD volunteers. Our findings also suggest that dysregulation in PC and ceramide metabolism could be occurring in different stages of AD progression.
Collapse
Affiliation(s)
- Min Kim
- Institute of Pharmaceutical Science, King’s College London, London, UK
| | | | - Luke Whiley
- Institute of Pharmaceutical Science, King’s College London, London, UK
| | - Stuart G. Snowden
- Institute of Pharmaceutical Science, King’s College London, London, UK
| | - Hilkka Soininen
- Department of Neurology, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - Iwona Kloszewska
- Department of Old Age Psychiatry & Psychotic Disorders, Medical University of Lodz, Lodz, Poland
| | - Patrizia Mecocci
- Section of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
| | - Magda Tsolaki
- Third Department of Neurology, Memory and Dementia Centre, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Bruno Vellas
- Department of Internal and Geriatrics Medicine, INSERM U 1027, Gerontopole, Hôpitaux de Toulouse, Toulouse, France
| | - Madhav Thambisetty
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Richard J.B. Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - John F. Powell
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Michelle K. Lupton
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Qld, Australia
| | - Andy Simmons
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) for Mental Health at South London and Maudsley NHS Foundation Trust, UK
| | - Latha Velayudhan
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | | | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | | |
Collapse
|
121
|
Varma VR, Varma S, An Y, Hohman TJ, Seddighi S, Casanova R, Beri A, Dammer EB, Seyfried NT, Pletnikova O, Moghekar A, Wilson MR, Lah JJ, O’Brien RJ, Levey AI, Troncoso JC, Albert MS, Thambisetty M. Alpha-2 macroglobulin in Alzheimer's disease: a marker of neuronal injury through the RCAN1 pathway. Mol Psychiatry 2017; 22:13-23. [PMID: 27872486 PMCID: PMC5726508 DOI: 10.1038/mp.2016.206] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2016] [Revised: 09/16/2016] [Accepted: 10/11/2016] [Indexed: 12/24/2022]
Abstract
Preclinical changes that precede the onset of symptoms and eventual diagnosis of Alzheimer's disease (AD) are a target for potential preventive interventions. A large body of evidence suggests that inflammation is closely associated with AD pathogenesis and may be a promising target pathway for such interventions. However, little is known about the association between systemic inflammation and preclinical AD pathophysiology. We first examined whether the acute-phase protein, alpha-2 macroglobulin (A2M), a major component of the innate immune system, was associated with cerebrospinal fluid (CSF) markers of neuronal injury in preclinical AD and risk of incident AD in the predictors of cognitive decline among normal individuals (BIOCARD) cohort. We find that A2M concentration in blood is significantly associated with CSF concentrations of the neuronal injury markers, tau and phosphorylated tau, and that higher baseline serum A2M concentration is associated with an almost threefold greater risk of progression to clinical symptoms of AD in men. These findings were replicated in the Alzheimer's Disease Neuroimaging (ADNI) study. Then, utilizing a systems level approach combining large multi-tissue gene expression datasets with mass spectrometry-based proteomic analyses of brain tissue, we identified an A2M gene network that includes regulator of calcineurin (RCAN1), an inhibitor of calcineurin, a well-characterized tau phosphatase. A2M gene and protein expression in the brain were significantly associated with gene and protein expression levels of calcineurin. Collectively these novel findings suggest that A2M is associated with preclinical AD, reflects early neuronal injury in the disease course and may be responsive to tau phosphorylation in the brain through the RCAN1-calcineurin pathway.
Collapse
Affiliation(s)
- VR Varma
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | - S Varma
- HiThru Analytics, Laurel, MD, USA
| | - Y An
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | - TJ Hohman
- Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - S Seddighi
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | - R Casanova
- Department of Biostatistical Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - A Beri
- Laboratory of Informatics Development (BTRIS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - EB Dammer
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - NT Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - O Pletnikova
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - A Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - MR Wilson
- School of Biological Sciences, University of Wollongong, Wollongong, NSW, Australia
| | - JJ Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - RJ O’Brien
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - AI Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - JC Troncoso
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - MS Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - M Thambisetty
- Clinical and Translational Neuroscience Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | | |
Collapse
|
122
|
O'Bryant SE, Mielke MM, Rissman RA, Lista S, Vanderstichele H, Zetterberg H, Lewczuk P, Posner H, Hall J, Johnson L, Fong YL, Luthman J, Jeromin A, Batrla-Utermann R, Villarreal A, Britton G, Snyder PJ, Henriksen K, Grammas P, Gupta V, Martins R, Hampel H. Blood-based biomarkers in Alzheimer disease: Current state of the science and a novel collaborative paradigm for advancing from discovery to clinic. Alzheimers Dement 2017; 13:45-58. [PMID: 27870940 PMCID: PMC5218961 DOI: 10.1016/j.jalz.2016.09.014] [Citation(s) in RCA: 192] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Accepted: 09/27/2016] [Indexed: 11/25/2022]
Abstract
The last decade has seen a substantial increase in research focused on the identification of blood-based biomarkers that have utility in Alzheimer's disease (AD). Blood-based biomarkers have significant advantages of being time- and cost-efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood-based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public-private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.
Collapse
Affiliation(s)
- Sid E O'Bryant
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA.
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Health Science Research, Mayo Clinic, Rochester, MN, USA
| | - Robert A Rissman
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, UCSD School of Medicine, La Jolla, CA, USA
| | - Simone Lista
- AXA Research Fund and UPMC Chair, Paris, France; Department de Neurologie, Institut de la Memorie et de la Maladie d'Alzheimer (IM2A) et Institut du Cerveau et du la Moelle epiniere (ICM), Hospital de la Pitie-Salpetriere, Sorbonne Universites, Universite Pierre et Marie Curie, Paris, France
| | | | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gotenburg, Molndal, Sweden; UCL Institute of Neurology, London, UK
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany; Department of Neurodegeneration Diagnostics, Medical University of Bialystok, Bialystok, Poland
| | | | - James Hall
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Leigh Johnson
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Yiu-Lian Fong
- Johnson & Johnson, London Innovation Center, London, UK
| | - Johan Luthman
- Neuroscience Clinical Development, Clinical Neuroscience Eisai, Woodcliff Lake, NJ, USA
| | | | | | - Alcibiades Villarreal
- Centro de Neurociencias y Unidad de Investigacion Clinica, Instituto de Investigaciones Cientificas y Servicios de Alta Tecnologia (INDICASAT AIP), Ciudad del Saber, Panama, Panama
| | - Gabrielle Britton
- Centro de Neurociencias y Unidad de Investigacion Clinica, Instituto de Investigaciones Cientificas y Servicios de Alta Tecnologia (INDICASAT AIP), Ciudad del Saber, Panama, Panama
| | - Peter J Snyder
- Department of Neurology, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, RI, USA
| | - Kim Henriksen
- Neurodegenerative Diseases, Nordic Bioscience Biomarkers and Research, Herlev, Denmark
| | - Paula Grammas
- George and Anne Ryan Institute for Neuroscience, University of Rhode Island, RI, USA
| | - Veer Gupta
- Faculty of Health, Engineering and Sciences, Center of Excellence for Alzheimer's Disease Research and Care, School of Medical Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Ralph Martins
- Faculty of Health, Engineering and Sciences, Center of Excellence for Alzheimer's Disease Research and Care, School of Medical Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Harald Hampel
- AXA Research Fund and UPMC Chair, Paris, France; Department de Neurologie, Institut de la Memorie et de la Maladie d'Alzheimer (IM2A) et Institut du Cerveau et du la Moelle epiniere (ICM), Hospital de la Pitie-Salpetriere, Sorbonne Universites, Universite Pierre et Marie Curie, Paris, France
| |
Collapse
|
123
|
Li D, Misialek JR, Boerwinkle E, Gottesman RF, Sharrett AR, Mosley TH, Coresh J, Wruck LM, Knopman DS, Alonso A. Prospective associations of plasma phospholipids and mild cognitive impairment/dementia among African Americans in the ARIC Neurocognitive Study. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2016; 6:1-10. [PMID: 28054030 PMCID: PMC5198734 DOI: 10.1016/j.dadm.2016.09.003] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Introduction The objective of this study was to investigate whether 10 phospholipids/metabolites previously identified as prospectively predictive of mild cognitive impairment (MCI) or dementia in whites would also be predictive in a mostly African-American cohort. Methods We repeatedly measured 188 phospholipids/metabolites in plasma samples of 221 participants of the Atherosclerosis Risk in Communities study, 97% African American, who were followed between 2004–2006 and 2011–2013. Results After a mean follow-up of 7.3 years, 77 were classified as having MCI and 18 as having dementia. Our study failed to replicate previous findings in this mostly African American cohort, in that the 10 phospholipids/metabolites only achieved a C statistic/AUC of 0.609 in predicting development of MCI or dementia (compared to 0.96) and 0.607 in distinguishing normal from MCI or dementia at the follow-up visit. Conclusion A panel of 10 phospholipids/metabolites previously associated with incident dementia was not predictive of MCI or dementia in an independent cohort.
Collapse
Affiliation(s)
- Danni Li
- Department of Lab Medicine and Pathology, School of Public Health, University of Minnesota, Minneapolis, MN, USA
- Corresponding author. Tel.: 612-626-0299; Fax: 612-625-1121.
| | - Jeffrey R. Misialek
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center, Houston, TX, USA
| | | | | | - Thomas H. Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Josef Coresh
- School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Lisa M. Wruck
- Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, NC, USA
| | | | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| |
Collapse
|
124
|
Winblad B, Amouyel P, Andrieu S, Ballard C, Brayne C, Brodaty H, Cedazo-Minguez A, Dubois B, Edvardsson D, Feldman H, Fratiglioni L, Frisoni GB, Gauthier S, Georges J, Graff C, Iqbal K, Jessen F, Johansson G, Jönsson L, Kivipelto M, Knapp M, Mangialasche F, Melis R, Nordberg A, Rikkert MO, Qiu C, Sakmar TP, Scheltens P, Schneider LS, Sperling R, Tjernberg LO, Waldemar G, Wimo A, Zetterberg H. Defeating Alzheimer's disease and other dementias: a priority for European science and society. Lancet Neurol 2016; 15:455-532. [DOI: 10.1016/s1474-4422(16)00062-4] [Citation(s) in RCA: 1001] [Impact Index Per Article: 125.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Revised: 10/06/2015] [Accepted: 02/09/2016] [Indexed: 12/15/2022]
|