4.7 Article

Metabolic network failures in Alzheimer's disease: A biochemical road map

期刊

ALZHEIMERS & DEMENTIA
卷 13, 期 9, 页码 965-984

出版社

WILEY
DOI: 10.1016/j.jalz.2017.01.020

关键词

Metabolomics; Metabonomics; Pharmacometabolomics; Pharmacometabonomics; Biomarkers; Serum; Metabolism; Systems biology; Biochemical networks; Precision medicine; Alzheimer's disease; Dementia; Branched-chain amino acids; Sphingomyelins; Phospholipids; Acylcarnitines

资金

  1. Eli Lilly
  2. NIH [U01 AG024904, R01 MH 098260, R01 AG 046171, 1RF AG 051550]
  3. MJFox Foundation
  4. Siemens Healthcare
  5. Springer publishing
  6. Avid/Lilly
  7. Anthrotonix
  8. Muses Labs
  9. AstraZeneca
  10. Abbvie
  11. Baxter
  12. Cognoptix
  13. Lundbeck/Takeda
  14. Piramal
  15. Genomind
  16. Sonexa
  17. Targacept
  18. Danone
  19. Neurocog Trials
  20. EnVivo
  21. T3D Therapeutics
  22. Elan
  23. Janssen
  24. Pfizer/Medivation
  25. Neuronetrix
  26. Forum
  27. Alzheimer's Drug Discovery Foundation
  28. Lundbeck
  29. Alzheimer's Association
  30. BiogenErasmus MC University Medical Center
  31. Erasmus University Rotterdam
  32. Netherlands Organisation for Scientific Research (NWO)
  33. Netherlands Organisation for Health Research and Development (ZonMw)
  34. Research Institute for Diseases in the Elderly (RIDE)
  35. Netherlands Genomics Initiative (NGI)
  36. Ministry of Education, Culture and Science
  37. Ministry of Health, Welfare and Sports
  38. European Commission (DG XII)
  39. Municipality of Rotterdam
  40. ZonMw
  41. European Commission FP6 STRP grant [018947, LSHG-CT-2006-01947]
  42. European Community's Seventh Framework Program by the European Commission [HEALTH-F4-2007-201413, QLG2-CT-2002-01254]
  43. ENGAGE consortium
  44. CMSB
  45. Netherlands Organization for Scientific Research
  46. Russian Foundation for Basic Research [NWO-RFBR 047.017.043]
  47. National Institute on Aging [R01AG046171, RF1AG051550, 3U01AG024904-09S4, P50 NS053488, P30 AG10124, K01 AG049050]
  48. NIA [R01 AG19771, P30 AG10133, NLM R01 LM011360]
  49. Helmholtz cross-program topic Metabolic Dysfunction
  50. National Library of Medicine [R00 LM011384, R01 LM011360]
  51. National Institute of Biomedical Imaging and Bioengineering [R01 EB022574]
  52. Indiana Clinical and Translational Science Institute
  53. Indiana University-IU Health Strategic Neuroscience Research Initiative
  54. Biomedical Research Program funds at Weill Cornell Medical College in Qatar, a program - the Qatar Foundation
  55. ADNI (National Institutes of Health) [U01 AG024904]
  56. DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
  57. National Institute of Biomedical Imaging and Bioengineering
  58. Canadian Institutes Health Research

向作者/读者索取更多资源

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 alpha-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 A beta(1-42), 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. (C) 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

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