#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study


Using quantitative and targeted metabolomics, Vijay Varma and colleagues identified metabolites for which brain tissue levels were associated with Alzheimer disease (AD) neuropathology and blood concentrations were associated with AD progression in prodromal and preclinical stages.


Vyšlo v časopise: Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study. PLoS Med 15(1): e32767. doi:10.1371/journal.pmed.1002482
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1002482

Souhrn

Using quantitative and targeted metabolomics, Vijay Varma and colleagues identified metabolites for which brain tissue levels were associated with Alzheimer disease (AD) neuropathology and blood concentrations were associated with AD progression in prodromal and preclinical stages.


Zdroje

1. Trushina E, Mielke MM. Recent advances in the application of metabolomics to Alzheimer's Disease. Biochimica et biophysica acta. 2014;1842(8):1232–9. doi: 10.1016/j.bbadis.2013.06.014 23816564

2. Barba I, Fernandez-Montesinos R, Garcia-Dorado D, Pozo D. Alzheimer's disease beyond the genomic era: nuclear magnetic resonance (NMR) spectroscopy-based metabolomics. Journal of cellular and molecular medicine. 2008;12(5A):1477–85. doi: 10.1111/j.1582-4934.2008.00385.x 18554316

3. Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nature medicine. 2014;20(4):415–8. doi: 10.1038/nm.3466 24608097

4. Kim E, Jung YS, Kim H, Kim JS, Park M, Jeong J, et al. Metabolomic signatures in peripheral blood associated with Alzheimer's disease amyloid-beta-induced neuroinflammation. Journal of Alzheimer's disease: JAD. 2014;42(2):421–33. doi: 10.3233/JAD-132165 24898638

5. Inoue K, Tsuchiya H, Takayama T, Akatsu H, Hashizume Y, Yamamoto T, et al. Blood-based diagnosis of Alzheimer's disease using fingerprinting metabolomics based on hydrophilic interaction liquid chromatography with mass spectrometry and multivariate statistical analysis. Journal of chromatography B, Analytical technologies in the biomedical and life sciences. 2015;974:24–34. doi: 10.1016/j.jchromb.2014.10.022 25463194

6. Ray S, Britschgi M, Herbert C, Takeda-Uchimura Y, Boxer A, Blennow K, et al. Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins. Nature medicine. 2007;13(11):1359–62. doi: 10.1038/nm1653 17934472

7. Casanova R, Varma S, Simpson B, Kim M, An Y, Saldana S, et al. Blood metabolite markers of preclinical Alzheimer's disease in two longitudinally followed cohorts of older individuals. Alzheimers Dement. 2016;12(7):815–22. doi: 10.1016/j.jalz.2015.12.008 26806385

8. Thambisetty M, Lovestone S. Blood-based biomarkers of Alzheimer's disease: challenging but feasible. Biomarkers in medicine. 2010;4(1):65–79. doi: 10.2217/bmm.09.84 20387303

9. Ferrucci L. The Baltimore Longitudinal Study of Aging (BLSA): a 50-year-long journey and plans for the future. The journals of gerontology. 2008;63(12):1416–9. 19126858

10. Shock NW, Gruelich R, Andres R, Arenberg D, Costa PT, Lakatta EG, et al. Normal Human Aging: The Baltimore Longitudinal Study of Aging. Washington, DC, USA: U.S. Government Printing Office; 1984.

11. Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack C, Jagust W, et al. The Alzheimer's disease neuroimaging initiative. Neuroimaging clinics of North America. 2005;15(4):869–77, xi-xii. doi: 10.1016/j.nic.2005.09.008 16443497

12. O'Brien RJ, Resnick SM, Zonderman AB, Ferrucci L, Crain BJ, Pletnikova O, et al. Neuropathologic studies of the Baltimore Longitudinal Study of Aging (BLSA). Journal of Alzheimer's disease: JAD. 2009;18(3):665–75. doi: 10.3233/JAD-2009-1179 19661626

13. Gamaldo A, Moghekar A, Kilada S, Resnick SM, Zonderman AB, O'Brien R. Effect of a clinical stroke on the risk of dementia in a prospective cohort. Neurology. 2006;67(8):1363–9. doi: 10.1212/01.wnl.0000240285.89067.3f 17060561

14. Mirra SS, Heyman A, McKeel D, Sumi SM, Crain BJ, Brownlee LM, et al. The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer's disease. Neurology. 1991;41(4):479–86. 2011243

15. Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta neuropathologica. 1991;82(4):239–59. 1759558

16. Troncoso JC, Zonderman AB, Resnick SM, Crain B, Pletnikova O, O'Brien RJ. Effect of infarcts on dementia in the Baltimore longitudinal study of aging. Annals of neurology. 2008;64(2):168–76. doi: 10.1002/ana.21413 18496870

17. Iacono D, Resnick SM, O'Brien R, Zonderman AB, An Y, Pletnikova O, et al. Mild cognitive impairment and asymptomatic Alzheimer disease subjects: equivalent beta-amyloid and tau loads with divergent cognitive outcomes. Journal of neuropathology and experimental neurology. 2014;73(4):295–304. doi: 10.1097/NEN.0000000000000052 24607960

18. Kawas C, Gray S, Brookmeyer R, Fozard J, Zonderman A. Age-specific incidence rates of Alzheimer's disease: the Baltimore Longitudinal Study of Aging. Neurology. 2000;54(11):2072–7. 10851365

19. APA. Diagnostic and statistical manual of mental disorders: DSM-III-R. Washington, DC: American Psychiatric Association; 1987.

20. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology. 1984;34(7):939–44. 6610841

21. Petersen RC. Mild cognitive impairment as a diagnostic entity. Journal of internal medicine. 2004;256(3):183–94. doi: 10.1111/j.1365-2796.2004.01388.x 15324362

22. Breier M, Wahl S, Prehn C, Fugmann M, Ferrari U, Weise M, et al. Targeted metabolomics identifies reliable and stable metabolites in human serum and plasma samples. PLoS ONE. 2014;9(2):e89728. doi: 10.1371/journal.pone.0089728 24586991

23. Hustad S, Eussen S, Midttun O, Ulvik A, van de Kant PM, Morkrid L, et al. Kinetic modeling of storage effects on biomarkers related to B vitamin status and one-carbon metabolism. Clinical chemistry. 2012;58(2):402–10. doi: 10.1373/clinchem.2011.174490 22194632

24. Snowden SG, Ebshiana AA, Hye A, An Y, Pletnikova O, O'Brien R, et al. Association between fatty acid metabolism in the brain and Alzheimer disease neuropathology and cognitive performance: A nontargeted metabolomic study. PLoS Med. 2017;14(3):e1002266. doi: 10.1371/journal.pmed.1002266 28323825

25. Toledo JB, Arnold M, Kastenmuller G, Chang R, Baillie RA, Han X, et al. Metabolic network failures in Alzheimer's disease: A biochemical road map. Alzheimers Dement. 2017;13(9):965–84. doi: 10.1016/j.jalz.2017.01.020 28341160

26. Jack CR Jr., Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, et al. The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. Journal of magnetic resonance imaging: JMRI. 2008;27(4):685–91. doi: 10.1002/jmri.21049 18302232

27. Davatzikos C, Xu F, An Y, Fan Y, Resnick SM. Longitudinal progression of Alzheimer's-like patterns of atrophy in normal older adults: the SPARE-AD index. Brain. 2009;132(Pt 8):2026–35. doi: 10.1093/brain/awp091 19416949

28. Toledo JB, Da X, Bhatt P, Wolk DA, Arnold SE, Shaw LM, et al. Relationship between plasma analytes and SPARE-AD defined brain atrophy patterns in ADNI. PLoS ONE. 2013;8(2):e55531. doi: 10.1371/journal.pone.0055531 23408997

29. Cortes C, Vapnik V. Support-Vector Networks. Machine Learning. 1995;20:273–97.

30. Pirooznia M, Yang JY, Yang MQ, Deng Y. A comparative study of different machine learning methods on microarray gene expression data. BMC genomics. 2008;9 Suppl 1:S13.

31. Breiman L, Friedman JH, O R.A., Stone CJ. Classification and Regression Trees: Chapman and Hall/CRC; 1984.

32. Breiman L, Friedman JH, Olsen RA, Stone CJ. Classification and Regression Trees: Chapman & Hall/CRC; 1984.

33. Casanova R, Varma S, Simpson B, Kim M, An Y, Saldana S, et al. Blood metabolite markers of preclinical Alzheimer's disease in two longitudinally followed cohorts of older individuals. Alzheimers Dement. 2016.

34. Perneger TV. What's wrong with Bonferroni adjustments. BMJ (Clinical research ed. 1998;316(7139):1236–8. 9553006

35. Pelerin H, Jouin M, Lallemand MS, Alessandri JM, Cunnane SC, Langelier B, et al. Gene expression of fatty acid transport and binding proteins in the blood-brain barrier and the cerebral cortex of the rat: differences across development and with different DHA brain status. Prostaglandins, leukotrienes, and essential fatty acids. 2014;91(5):213–20. doi: 10.1016/j.plefa.2014.07.004 25123062

36. Doege H, Stahl A. Protein-mediated fatty acid uptake: novel insights from in vivo models. Physiology. 2006;21:259–68. doi: 10.1152/physiol.00014.2006 16868315

37. Janssen CI, Kiliaan AJ. Long-chain polyunsaturated fatty acids (LCPUFA) from genesis to senescence: the influence of LCPUFA on neural development, aging, and neurodegeneration. Progress in lipid research. 2014;53:1–17. doi: 10.1016/j.plipres.2013.10.002 24334113

38. Head BP, Patel HH, Insel PA. Interaction of membrane/lipid rafts with the cytoskeleton: impact on signaling and function: membrane/lipid rafts, mediators of cytoskeletal arrangement and cell signaling. Biochimica et biophysica acta. 2014;1838(2):532–45. doi: 10.1016/j.bbamem.2013.07.018 23899502

39. Jazvinscak Jembrek M, Hof PR, Simic G. Ceramides in Alzheimer's Disease: Key Mediators of Neuronal Apoptosis Induced by Oxidative Stress and Abeta Accumulation. Oxidative medicine and cellular longevity. 2015;2015:346783. doi: 10.1155/2015/346783 26090071

40. Osenkowski P, Ye W, Wang R, Wolfe MS, Selkoe DJ. Direct and potent regulation of gamma-secretase by its lipid microenvironment. The Journal of biological chemistry. 2008;283(33):22529–40. doi: 10.1074/jbc.M801925200 18539594

41. Bankaitis VA. The Cirque du Soleil of Golgi membrane dynamics. The Journal of cell biology. 2009;186(2):169–71. doi: 10.1083/jcb.200907008 19635838

42. Stoica BA, Movsesyan VA, Lea PMt, Faden AI. Ceramide-induced neuronal apoptosis is associated with dephosphorylation of Akt, BAD, FKHR, GSK-3beta, and induction of the mitochondrial-dependent intrinsic caspase pathway. Molecular and cellular neurosciences. 2003;22(3):365–82. 12691738

43. Haughey NJ, Bandaru VV, Bae M, Mattson MP. Roles for dysfunctional sphingolipid metabolism in Alzheimer's disease neuropathogenesis. Biochimica et biophysica acta. 2010;1801(8):878–86. doi: 10.1016/j.bbalip.2010.05.003 20452460

44. Mielke MM, Bandaru VV, Haughey NJ, Rabins PV, Lyketsos CG, Carlson MC. Serum sphingomyelins and ceramides are early predictors of memory impairment. Neurobiology of aging. 2010;31(1):17–24. doi: 10.1016/j.neurobiolaging.2008.03.011 18455839

45. van Echten-Deckert G, Herget T. Sphingolipid metabolism in neural cells. Biochimica et biophysica acta. 2006;1758(12):1978–94. doi: 10.1016/j.bbamem.2006.06.009 16843432

46. Hannun YA, Obeid LM. Principles of bioactive lipid signalling: lessons from sphingolipids. Nature reviews Molecular cell biology. 2008;9(2):139–50. doi: 10.1038/nrm2329 18216770

47. Fabelo N, Martin V, Marin R, Moreno D, Ferrer I, Diaz M. Altered lipid composition in cortical lipid rafts occurs at early stages of sporadic Alzheimer's disease and facilitates APP/BACE1 interactions. Neurobiology of aging. 2014;35(8):1801–12. doi: 10.1016/j.neurobiolaging.2014.02.005 24613671

48. Norman E, Cutler RG, Flannery R, Wang Y, Mattson MP. Plasma membrane sphingomyelin hydrolysis increases hippocampal neuron excitability by sphingosine-1-phosphate mediated mechanisms. Journal of neurochemistry. 2010;114(2):430–9. doi: 10.1111/j.1471-4159.2010.06779.x 20456020

49. He X, Huang Y, Li B, Gong CX, Schuchman EH. Deregulation of sphingolipid metabolism in Alzheimer's disease. Neurobiology of aging. 2010;31(3):398–408. doi: 10.1016/j.neurobiolaging.2008.05.010 18547682

50. Soderberg M, Edlund C, Alafuzoff I, Kristensson K, Dallner G. Lipid composition in different regions of the brain in Alzheimer's disease/senile dementia of Alzheimer's type. Journal of neurochemistry. 1992;59(5):1646–53. 1402910

51. Chan RB, Oliveira TG, Cortes EP, Honig LS, Duff KE, Small SA, et al. Comparative lipidomic analysis of mouse and human brain with Alzheimer disease. The Journal of biological chemistry. 2012;287(4):2678–88. doi: 10.1074/jbc.M111.274142 22134919

52. Han X, Rozen S, Boyle SH, Hellegers C, Cheng H, Burke JR, et al. Metabolomics in early Alzheimer's disease: identification of altered plasma sphingolipidome using shotgun lipidomics. PLoS ONE. 2011;6(7):e21643. doi: 10.1371/journal.pone.0021643 21779331

53. Oresic M, Hyotylainen T, Herukka SK, Sysi-Aho M, Mattila I, Seppanan-Laakso T, et al. Metabolome in progression to Alzheimer's disease. Translational psychiatry. 2011;1:e57. doi: 10.1038/tp.2011.55 22832349

54. Li D, Misialek JR, Boerwinkle E, Gottesman RF, Sharrett AR, Mosley TH, et al. Prospective associations of plasma phospholipids and mild cognitive impairment/dementia among African Americans in the ARIC Neurocognitive Study. Alzheimers Dement (Amst). 2017;6:1–10.

55. Kolahdooz Z, Nasoohi S, Asle-Rousta M, Ahmadiani A, Dargahi L. Sphingosin-1-phosphate Receptor 1: a Potential Target to Inhibit Neuroinflammation and Restore the Sphingosin-1-phosphate Metabolism. The Canadian journal of neurological sciences Le journal canadien des sciences neurologiques. 2015;42(3):195–202. doi: 10.1017/cjn.2015.19 25860537

56. Asle-Rousta M, Kolahdooz Z, Oryan S, Ahmadiani A, Dargahi L. FTY720 (fingolimod) attenuates beta-amyloid peptide (Abeta42)-induced impairment of spatial learning and memory in rats. Journal of molecular neuroscience: MN. 2013;50(3):524–32. doi: 10.1007/s12031-013-9979-6 23435938

57. Whiley L, Sen A, Heaton J, Proitsi P, Garcia-Gomez D, Leung R, et al. Evidence of altered phosphatidylcholine metabolism in Alzheimer's disease. Neurobiology of aging. 2014;35(2):271–8. doi: 10.1016/j.neurobiolaging.2013.08.001 24041970

58. Simpson BN, Kim M, Chuang YF, Beason-Held L, Kitner-Triolo M, Kraut M, et al. Blood metabolite markers of cognitive performance and brain function in aging. J Cereb Blood Flow Metab. 2016;36(7):1212–23. doi: 10.1177/0271678X15611678 26661209

59. Zhao Z, Zlokovic BV. Blood-brain barrier: a dual life of MFSD2A? Neuron. 2014;82(4):728–30. doi: 10.1016/j.neuron.2014.05.012 24853933

60. Nguyen LN, Ma D, Shui G, Wong P, Cazenave-Gassiot A, Zhang X, et al. Mfsd2a is a transporter for the essential omega-3 fatty acid docosahexaenoic acid. Nature. 2014;509(7501):503–6. doi: 10.1038/nature13241 24828044

Štítky
Interné lekárstvo

Článok vyšiel v časopise

PLOS Medicine


2018 Číslo 1
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Získaná hemofilie - Povědomí o nemoci a její diagnostika
nový kurz

Eozinofilní granulomatóza s polyangiitidou
Autori: doc. MUDr. Martina Doubková, Ph.D.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#