Skip to main content

Multiplexing Biomarker Methods, Proteomics and Considerations for Alzheimer’s Disease

  • Chapter
  • First Online:
Proteomic Methods in Neuropsychiatric Research

Part of the book series: Advances in Experimental Medicine and Biology ((PMISB,volume 974))

Abstract

Biomarker research for Alzheimer’s disease (AD) has been growing rapidly over recent years especially as the number of persons affected by this disease is nearing approximately 46 million worldwide. Single biomarker assays are challenging to establish since AD is multifactorial and complex. In addition to the classic signs of diminished cognition and memory, AD patients can also exhibit symptoms which may be confused with some psychiatric disorders, such as depression. No molecular biomarkers have been established or translated into clinical tools although recent efforts have resulted in addition of molecular biomarker profiles to the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer’s Disease and Related Disorders Association criteria for research purposes. The three accepted molecular biomarkers are amyloid-βeta peptide 1-42, total tau protein and hyperphosphorylated tau at threonine 181 in human cerebrospinal fluid (CSF). Aside from these three CSF markers, a number of potential candidates have been identified in CSF and other body fluids. In order to identify biomarkers for diagnosis, early prevention, prognosis and response to therapeutic treatment, multiplex biomarker tests will be required. These include multiplex immunoassay and mass spectrometry-based proteomics platforms. Proteomics analyses of bodily fluids such as plasma are growing in number and providing potential targets for further investigation and validation in AD research. This chapter highlights proteomic biomarker assays and their applications and potential use for clinical diagnosis and prognosis of AD.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Hebert LE, Beckett LA, Scherr PA, Evans DA (2001) Annual incidence of Alzheimer disease in the United States projected to the years 2000 through 2050. Alzheimer Dis Assoc Disord 15(4):169–173

    Article  CAS  PubMed  Google Scholar 

  2. Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W, Ferri CP (2013) The global prevalence of dementia: a systematic review and metaanalysis. Alzheimers Dement 9(1):63–75.e62. doi:10.1016/j.jalz.2012.11.007

    Article  PubMed  Google Scholar 

  3. Kitching D (2015) Depression in dementia. Aust Prescr 38:209–211

    Article  PubMed  PubMed Central  Google Scholar 

  4. Murray PS, Kumar S, Demichele-Sweet MA, Sweet RA (2014) Psychosis in Alzheimer’s disease. Biol Psychiatry 75:542–552

    Article  PubMed  Google Scholar 

  5. Baumgart M, Snyder HM, Carrillo MC, Fazio S, Kim H, Johns H (2015) Summary of the evidence on modifiable risk factors for cognitive decline and dementia: a population-based perspective. Alzheimers Dement 11(6):718–726. doi:10.1016/j.jalz.2015.05.016

    Article  PubMed  Google Scholar 

  6. Reitz C, Mayeux R (2014) Alzheimer disease: epidemiology, diagnostic criteria, risk factors and biomarkers. Biochem Pharmacol 88(4):640–651. doi:10.1016/j.bcp.2013.12.024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bateman RJ, Siemers ER, Mawuenyega KG, Wen G, Browning KR, Sigurdson WC et al (2009) A gamma-secretase inhibitor decreases amyloid-beta production in the central nervous system. Ann Neurol 66(1):48–54. doi:10.1002/ana.21623

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Goate A (2006) Segregation of a missense mutation in the amyloid beta-protein precursor gene with familial Alzheimer’s disease. J Alzheimers Dis 9(3 Suppl):341–347

    CAS  PubMed  Google Scholar 

  9. Lemere CA, Lopera F, Kosik KS, Lendon CL, Ossa J, Saido TC et al (1996) The E280A presenilin 1 Alzheimer mutation produces increased A beta 42 deposition and severe cerebellar pathology. Nat Med 2(10):1146–1150

    Article  CAS  PubMed  Google Scholar 

  10. Levy-Lahad E, Wasco W, Poorkaj P, Romano DM, Oshima J, Pettingell WH et al (1995) Candidate gene for the chromosome 1 familial Alzheimer’s disease locus. Science 269(5226):973–977

    Article  CAS  PubMed  Google Scholar 

  11. Rogaev EI, Sherrington R, Rogaeva EA, Levesque G, Ikeda M, Liang Y et al (1995) Familial Alzheimer’s disease in kindreds with missense mutations in a gene on chromosome 1 related to the Alzheimer’s disease type 3 gene. Nature 376(6543):775–778. doi:10.1038/376775a0

    Article  CAS  PubMed  Google Scholar 

  12. Scheuner D, Eckman C, Jensen M, Song X, Citron M, Suzuki N et al (1996) Secreted amyloid beta-protein similar to that in the senile plaques of Alzheimer’s disease is increased in vivo by the presenilin 1 and 2 and APP mutations linked to familial Alzheimer’s disease. Nat Med 2(8):864–870

    Article  CAS  PubMed  Google Scholar 

  13. Sherrington R, Rogaev EI, Liang Y, Rogaeva EA, Levesque G, Ikeda M et al (1995) Cloning of a gene bearing missense mutations in early-onset familial Alzheimer’s disease. Nature 375(6534):754–760. doi:10.1038/375754a0

    Article  CAS  PubMed  Google Scholar 

  14. Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE (2007) Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet 39(1):17–23. doi:10.1038/ng1934

    Article  CAS  PubMed  Google Scholar 

  15. Corder EH, Saunders AM, Strittmatter WJ, Schmechel DE, Gaskell PC, Small GW et al (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261(5123):921–923

    Article  CAS  PubMed  Google Scholar 

  16. Farrer LA, Cupples LA, Haines JL, Hyman B, Kukull WA, Mayeux R et al (1997) Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA 278(16):1349–1356

    Article  CAS  PubMed  Google Scholar 

  17. Giri M, Zhang M, Lu Y (2016) Genes associated with Alzheimer’s disease: an overview and current status. Clin Interv Aging 11:665–681. doi:10.2147/CIA.S105769

    Article  PubMed  PubMed Central  Google Scholar 

  18. Shen L, Jia J (2016) An overview of Genome-Wide Association Studies in Alzheimer’s disease. Neurosci Bull 32(2):183–190. doi:10.1007/s12264-016-0011-3

    Article  CAS  PubMed  Google Scholar 

  19. Motter R, Vigo-Pelfrey C, Kholodenko D, Barbour R, Johnson-Wood K, Galasko D et al (1995) Reduction of beta-amyloid peptide42 in the cerebrospinal fluid of patients with Alzheimer’s disease. Ann Neurol 38(4):643–648. doi:10.1002/ana.410380413

    Article  CAS  PubMed  Google Scholar 

  20. Strozyk D, Blennow K, White LR, Launer LJ (2003) CSF Abeta 42 levels correlate with amyloid-neuropathology in a population-based autopsy study. Neurology 60(4):652–656

    Article  CAS  PubMed  Google Scholar 

  21. Andreasen N, Sjogren M, Blennow K (2003) CSF markers for Alzheimer’s disease: total tau, phospho-tau and Abeta42. World J Biol Psychiatry 4(4):147–155

    Article  PubMed  Google Scholar 

  22. Fagan AM, Shaw LM, Xiong C, Vanderstichele H, Mintun MA, Trojanowski JQ et al (2011) Comparison of analytical platforms for cerebrospinal fluid measures of beta-amyloid 1-42, total tau, and p-tau181 for identifying Alzheimer disease amyloid plaque pathology. Arch Neurol 68(9):1137–1144. doi:10.1001/archneurol.2011.105

    Article  PubMed  PubMed Central  Google Scholar 

  23. Tapiola T, Alafuzoff I, Herukka SK, Parkkinen L, Hartikainen P, Soininen H et al (2009) Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol 66(3):382–389. doi:10.1001/archneurol.2008.596

    Article  PubMed  Google Scholar 

  24. Vandermeeren M, Mercken M, Vanmechelen E, Six J, van de Voorde A, Martin JJ et al (1993) Detection of tau proteins in normal and Alzheimer’s disease cerebrospinal fluid with a sensitive sandwich enzyme-linked immunosorbent assay. J Neurochem 61(5):1828–1834

    Article  CAS  PubMed  Google Scholar 

  25. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM (1984) 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 34(7):939–944

    Article  CAS  PubMed  Google Scholar 

  26. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH et al (2011) The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7(3):263–269. doi:10.1016/j.jalz.2011.03.005

    Article  PubMed  PubMed Central  Google Scholar 

  27. Schaffer C, Sarad N, DeCrumpe A, Goswami D, Herrmann S, Morales J et al (2015) Biomarkers in the diagnosis and prognosis of Alzheimer’s disease. J Lab Autom 20(5):589–600. doi:10.1177/2211068214559979

    Article  CAS  PubMed  Google Scholar 

  28. Knopman DS, DeKosky ST, Cummings JL, Chui H, Corey-Bloom J, Relkin N et al (2001) Practice parameter: diagnosis of dementia (an evidence-based review). Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 56(9):1143–1153

    Article  CAS  PubMed  Google Scholar 

  29. Kier FJ, Molinari V (2003) "Do-it-yourself" dementia testing: issues regarding an Alzheimer’s home screening test. Gerontologist 43(3):295–301

    Article  PubMed  Google Scholar 

  30. Knopman DS, Knudson D, Yoes ME, Weiss DJ (2000) Development and standardization of a new telephonic cognitive screening test: the Minnesota Cognitive Acuity Screen (MCAS). Neuropsychiatry Neuropsychol Behav Neurol 13(4):286–296

    CAS  PubMed  Google Scholar 

  31. Goldman JS, Hahn SE, Catania JW, LaRusse-Eckert S, Butson MB, Rumbaugh M et al (2011) Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors. Genet Med 13(6):597–605. doi:10.1097/GIM.0b013e31821d69b8

    Article  PubMed  PubMed Central  Google Scholar 

  32. Braak H, Braak E (1997) Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiol Aging 18(4):351–357

    Article  CAS  PubMed  Google Scholar 

  33. Villemagne VL, Pike KE, Chetelat G, Ellis KA, Mulligan RS, Bourgeat P et al (2011) Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Ann Neurol 69(1):181–192. doi:10.1002/ana.22248

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Enache D, Winblad B, Aarsland D (2011) Depression in dementia: epidemiology, mechanisms, and treatment. Curr Opin Psychiatry 24:461–472

    PubMed  Google Scholar 

  35. Engedal K, Barca ML, Laks J, Selbaek G (2011) Depression in Alzheimer’s disease: specificity of depressive symptoms using three different clinical criteria. Int J Geriatr Psychiatry 26:944–951

    Article  PubMed  Google Scholar 

  36. Royall DR, Palmer R, Chiodo LK, Polk MJ (2012) Depressive symptoms predict longitudinal change in executive control but not memory. Int J Geriatr Psychiatry 27:89–96

    Article  PubMed  Google Scholar 

  37. Rushing NC, Sachs-Ericsson N, Steffens DC (2014) Neuropsychological indicators of preclinical Alzheimer’s disease among depressed older adults. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 21:99–128

    Article  PubMed  Google Scholar 

  38. Zhao QF, Tan L, Wang HF, Jiang T, Tan MS, Tan L et al (2016) The prevalence of neuropsychiatric symptoms in Alzheimer’s disease: systematic review and meta-analysis. J Affect Disord 190:264–271

    Article  PubMed  Google Scholar 

  39. Zahodne LB, Stern Y, Manly JJ (2014) Depressive symptoms precede memory decline, but not vice versa, in non-demented older adults. J Am Geriatr Soc 62:130–134

    Article  PubMed  PubMed Central  Google Scholar 

  40. Boyle LL, Porsteinsson AP, Cui X, King DA, Lyness JM (2010) Depression predicts cognitive disorders in older primary care patients. J Clin Psychiatry 71:74–79

    Article  PubMed  Google Scholar 

  41. Alzheimer A, Stelzmann RA, Schnitzlein HN, Murtagh FR (1995) An English translation of Alzheimer’s 1907 paper, “Uber eine eigenartige Erkankung der Hirnrinde”. Clin Anat 8:429–431

    Google Scholar 

  42. Steinberg M, Shao H, Zandi P, Lyketsos CG, Welsh-Bohmer KA, Norton MC et al (2008) Point and 5-year period prevalence of neuropsychiatric symptoms in dementia: the Cache County Study. Int J Geriatr Psychiatry 23:170–177

    Article  PubMed  PubMed Central  Google Scholar 

  43. Lyketsos CG (2009) Dementia and milder cognitive syndromes. The American psychiatric publishing textbook of geriatric psychiatry, 4th edn. American Psychiatric Publishing, Virginia

    Google Scholar 

  44. Vilalta-Franch J, López-Pousa S, Calvó-Perxas L, Garre-Olmo J (2013) Psychosis of Alzheimer disease: prevalence, incidence, persistence, risk factors, and mortality. Am J Geriatr Psychiatry 21:1135–1143

    Article  PubMed  Google Scholar 

  45. Shah C, DeMichele-Sweet MA, Sweet RA (2016) Genetics of psychosis of Alzheimer disease. Am J Med Genet B Neuropsychiatr Genet doi: 10.1002/ajmg.b.32413. [Epub ahead of print]

  46. Gupta VB, Sundaram R, Martins RN (2013) Multiplex biomarkers in blood. Alzheimers Res Ther 5(3):31. doi:10.1186/alzrt185

    Article  PubMed  PubMed Central  Google Scholar 

  47. Schneider JA, Arvanitakis Z, Bang W, Bennett DA (2007) Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology 69(24):2197–2204. doi:10.1212/01.wnl.0000271090.28148.24

    Article  PubMed  Google Scholar 

  48. Jicha GA, Abner EL, Schmitt FA, Kryscio RJ, Riley KP, Cooper GE et al (2012) Preclinical AD Workgroup staging: pathological correlates and potential challenges. Neurobiol Aging 33(3):622 e621–622 e616. doi:10.1016/j.neurobiolaging.2011.02.018

    Article  Google Scholar 

  49. Nelson PT, Abner EL, Schmitt FA, Kryscio RJ, Jicha GA, Smith CD et al (2010) Modeling the association between 43 different clinical and pathological variables and the severity of cognitive impairment in a large autopsy cohort of elderly persons. Brain Pathol 20(1):66–79. doi:10.1111/j.1750-3639.2008.00244.x

    Article  PubMed  Google Scholar 

  50. Jack CR Jr, Shiung MM, Weigand SD, O’Brien PC, Gunter JL, Boeve BF et al (2005) Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology 65(8):1227–1231. doi:10.1212/01.wnl.0000180958.22678.91

    Article  PubMed  PubMed Central  Google Scholar 

  51. Knight MJ, McCann B, Kauppinen RA, Coulthard EJ (2016) Magnetic resonance imaging to detect early molecular and cellular changes in Alzheimer’s disease. Front Aging Neurosci 8:139. doi:10.3389/fnagi.2016.00139

    Article  PubMed  PubMed Central  Google Scholar 

  52. Stoub TR, Bulgakova M, Leurgans S, Bennett DA, Fleischman D, Turner DA et al (2005) MRI predictors of risk of incident Alzheimer disease: a longitudinal study. Neurology 64(9):1520–1524. doi:10.1212/01.WNL.0000160089.43264.1A

    Article  CAS  PubMed  Google Scholar 

  53. Stoub TR, Rogalski EJ, Leurgans S, Bennett DA, deToledo-Morrell L (2010) Rate of entorhinal and hippocampal atrophy in incipient and mild AD: relation to memory function. Neurobiol Aging 31(7):1089–1098. doi:10.1016/j.neurobiolaging.2008.08.003

    Article  CAS  PubMed  Google Scholar 

  54. Soares HD, Chen Y, Sabbagh M, Roher A, Schrijvers E, Breteler M (2009) Identifying early markers of Alzheimer’s disease using quantitative multiplex proteomic immunoassay panels. Ann N Y Acad Sci 1180:56–67. doi:10.1111/j.1749-6632.2009.05066.x

    Article  CAS  PubMed  Google Scholar 

  55. Jagust W, Gitcho A, Sun F, Kuczynski B, Mungas D, Haan M (2006) Brain imaging evidence of preclinical Alzheimer’s disease in normal aging. Ann Neurol 59(4):673–681. doi:10.1002/ana.20799

    Article  PubMed  Google Scholar 

  56. Jagust WJ, Bandy D, Chen K, Foster NL, Landau SM, Mathis CA et al (2010) The Alzheimer’s disease neuroimaging initiative positron emission tomography core. Alzheimers Dement 6(3):221–229. doi:10.1016/j.jalz.2010.03.003

    Article  PubMed  PubMed Central  Google Scholar 

  57. Langbaum JB, Chen K, Lee W, Reschke C, Bandy D, Fleisher AS et al (2009) Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neuroimage 45(4):1107–1116. doi:10.1016/j.neuroimage.2008.12.072

    Article  PubMed  PubMed Central  Google Scholar 

  58. Mosconi L (2013) Glucose metabolism in normal aging and Alzheimer’s disease: methodological and physiological considerations for PET studies. Clin Transl Imaging 1(4). doi:10.1007/s40336-013-0026-y

  59. Shah K, Desilva S, Abbruscato T (2012) The role of glucose transporters in brain disease: diabetes and Alzheimer’s disease. Int J Mol Sci 13(10):12629–12655. doi:10.3390/ijms131012629

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Cohen AD, Rabinovici GD, Mathis CA, Jagust WJ, Klunk WE, Ikonomovic MD (2012) Using Pittsburgh Compound B for in vivo PET imaging of fibrillar amyloid-beta. Adv Pharmacol 64:27–81. doi:10.1016/B978-0-12-394816-8.00002-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Mathis CA, Klunk WE, Price JC, DeKosky ST (2005) Imaging technology for neurodegenerative diseases: progress toward detection of specific pathologies. Arch Neurol 62(2):196–200. doi:10.1001/archneur.62.2.196

    Article  PubMed  Google Scholar 

  62. Hansson O, Zetterberg H, Buchhave P, Londos E, Blennow K, Minthon L (2006) Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol 5(3):228–234. doi:10.1016/S1474-4422(06)70355-6

    Article  CAS  PubMed  Google Scholar 

  63. Blennow K, Zetterberg H (2015) The past and the future of Alzheimer’s disease CSF biomarkers-a journey toward validated biochemical tests covering the whole spectrum of molecular events. Front Neurosci 9:345. doi:10.3389/fnins.2015.00345

    Article  PubMed  PubMed Central  Google Scholar 

  64. Craig-Schapiro R, Perrin RJ, Roe CM, Xiong C, Carter D, Cairns NJ et al (2010) YKL-40: a novel prognostic fluid biomarker for preclinical Alzheimer’s disease. Biol Psychiatry 68(10):903–912. doi:10.1016/j.biopsych.2010.08.025

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Perrin RJ, Craig-Schapiro R, Malone JP, Shah AR, Gilmore P, Davis AE et al (2011) Identification and validation of novel cerebrospinal fluid biomarkers for staging early Alzheimer’s disease. PLoS One 6(1):e16032. doi:10.1371/journal.pone.0016032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Cruchaga C, Kauwe JS, Harari O, Jin SC, Cai Y, Karch CM et al (2013) GWAS of cerebrospinal fluid tau levels identifies risk variants for Alzheimer’s disease. Neuron 78(2):256–268. doi:10.1016/j.neuron.2013.02.026

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Kauwe JS, Bailey MH, Ridge PG, Perry R, Wadsworth ME, Hoyt KL et al (2014) Genome-wide association study of CSF levels of 59 alzheimer’s disease candidate proteins: significant associations with proteins involved in amyloid processing and inflammation. PLoS Genet 10(10):e1004758. doi:10.1371/journal.pgen.1004758

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Lee KS, Chung JH, Choi TK, Suh SY, Oh BH, Hong CH (2009) Peripheral cytokines and chemokines in Alzheimer’s disease. Dement Geriatr Cogn Disord 28(4):281–287. doi:10.1159/000245156

    Article  CAS  PubMed  Google Scholar 

  69. Kleinberger G, Yamanishi Y, Suarez-Calvet M, Czirr E, Lohmann E, Cuyvers E et al (2014) TREM2 mutations implicated in neurodegeneration impair cell surface transport and phagocytosis. Sci Transl Med 6(243):243ra286. doi:10.1126/scitranslmed.3009093

    Article  CAS  Google Scholar 

  70. Galasko D (2015) Expanding the repertoire of biomarkers for Alzheimer’s disease: targeted and non-targeted approaches. Front Neurol 6:256. doi:10.3389/fneur.2015.00256

    Article  PubMed  PubMed Central  Google Scholar 

  71. Mattsson N, Andreasson U, Persson S, Carrillo MC, Collins S, Chalbot S et al (2013) CSF biomarker variability in the Alzheimer’s Association quality control program. Alzheimers Dement 9(3):251–261. doi:10.1016/j.jalz.2013.01.010

    Article  PubMed  PubMed Central  Google Scholar 

  72. Vos SJ, Visser PJ, Verhey F, Aalten P, Knol D, Ramakers I et al (2014) Variability of CSF Alzheimer’s disease biomarkers: implications for clinical practice. PLoS One 9(6):e100784. doi:10.1371/journal.pone.0100784

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  73. Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR et al (2006) Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol 59(3):512–519. doi:10.1002/ana.20730

    Article  CAS  PubMed  Google Scholar 

  74. Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A et al (2008) PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging 29(10):1456–1465. doi:10.1016/j.neurobiolaging.2007.03.029

    Article  CAS  PubMed  Google Scholar 

  75. Hampel H, Buerger K, Zinkowski R, Teipel SJ, Goernitz A, Andreasen N et al (2004) Measurement of phosphorylated tau epitopes in the differential diagnosis of Alzheimer disease: a comparative cerebrospinal fluid study. Arch Gen Psychiatry 61(1):95–102. doi:10.1001/archpsyc.61.1.95

    Article  CAS  PubMed  Google Scholar 

  76. Struyfs H, Van Broeck B, Timmers M, Fransen E, Sleegers K, Van Broeckhoven C et al (2015) Diagnostic accuracy of cerebrospinal fluid amyloid-beta isoforms for early and differential dementia diagnosis. J Alzheimers Dis 45(3):813–822. doi:10.3233/JAD-141986

    CAS  PubMed  Google Scholar 

  77. Visser PJ, Verhey F, Knol DL, Scheltens P, Wahlund LO, Freund-Levi Y et al (2009) Prevalence and prognostic value of CSF markers of Alzheimer’s disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the DESCRIPA study: a prospective cohort study. Lancet Neurol 8(7):619–627. doi:10.1016/S1474-4422(09)70139-5

    Article  PubMed  Google Scholar 

  78. Shaw LM, Vanderstichele H, Knapik-Czajka M, Clark CM, Aisen PS, Petersen RC et al (2009) Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol 65(4):403–413. doi:10.1002/ana.21610

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Lonneborg A (2008) Biomarkers for Alzheimer disease in cerebrospinal fluid, urine, and blood. Mol Diagn Ther 12(5):307–320

    Article  CAS  PubMed  Google Scholar 

  80. Patel S, Shah RJ, Coleman P, Sabbagh M (2011) Potential peripheral biomarkers for the diagnosis of Alzheimer’s disease. Int J Alzheimers Dis 2011:572495. doi:10.4061/2011/572495

    PubMed  PubMed Central  Google Scholar 

  81. De La Monte SM, Wands JR (2001) The AD7c-NTP neuronal thread protein biomarker for detecting Alzheimer’s disease. J Alzheimers Dis 3(3):345–353

    CAS  PubMed  Google Scholar 

  82. de la Monte SM, Wands JR (2002) The AD7c-ntp neuronal thread protein biomarker for detecting Alzheimer’s disease. Front Biosci 7:d989–d996

    PubMed  Google Scholar 

  83. Ma L, Chen J, Wang R, Han Y, Zhang J, Dong W et al (2015) The level of Alzheimer-associated neuronal thread protein in urine may be an important biomarker of mild cognitive impairment. J Clin Neurosci 22(4):649–652. doi:10.1016/j.jocn.2014.10.011

    Article  CAS  PubMed  Google Scholar 

  84. Kang J, Lu J, Zhang X (2015) Metabolomics-based promising candidate biomarkers and pathways in Alzheimer’s disease. Pharmazie 70(5):277–282

    CAS  PubMed  Google Scholar 

  85. Trushina E, Mielke MM (2014) Recent advances in the application of metabolomics to Alzheimer’s disease. Biochim Biophys Acta 1842(8):1232–1239. doi:10.1016/j.bbadis.2013.06.014

    Article  CAS  PubMed  Google Scholar 

  86. Xu XH, Huang Y, Wang G, Chen SD (2012) Metabolomics: a novel approach to identify potential diagnostic biomarkers and pathogenesis in Alzheimer’s disease. Neurosci Bull 28(5):641–648. doi:10.1007/s12264-012-1272-0

    Article  CAS  PubMed  Google Scholar 

  87. Baird AL, Westwood S, Lovestone S (2015) Blood-based proteomic biomarkers of Alzheimer’s disease pathology. Front Neurol 6:236. doi:10.3389/fneur.2015.00236

    Article  PubMed  PubMed Central  Google Scholar 

  88. Perneczky R, Guo LH (2016) Plasma proteomics biomarkers in Alzheimer’s disease: latest advances and challenges. Methods Mol Biol 1303:521–529. doi:10.1007/978-1-4939-2627-5_32

    Article  PubMed  Google Scholar 

  89. Guest FL, Guest PC, Martins-de-Souza D (2016) The emergence of point-of-care blood-based biomarker testing for psychiatric disorders: enabling personalized medicine. Biomark Med 10:431–443

    Article  CAS  PubMed  Google Scholar 

  90. Ray S, Britschgi M, Herbert C, Takeda-Uchimura Y, Boxer A, Blennow K et al (2007) Classification and prediction of clinical Alzheimer’s diagnosis based on plasma signaling proteins. Nat Med 13(11):1359–1362. doi:10.1038/nm1653

    Article  CAS  PubMed  Google Scholar 

  91. Clark LF, Kodadek T (2016) The immune system and neuroinflammation as potential sources of blood-based biomarkers for Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease. ACS Chem Nerosci 7(5):520–527. doi:10.1021/acschemneuro.6b00042

    Article  CAS  Google Scholar 

  92. Chen A, Oakley AE, Monteiro M, Tuomela K, Allan LM, Mukaetova-Ladinska EB et al (2016) Multiplex analyte assays to characterize different dementias: brain inflammatory cytokines in poststroke and other dementias. Neurobiol Aging 38:56–67. doi:10.1016/j.neurobiolaging.2015.10.021

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Choi C, Jeong JH, Jang JS, Choi K, Lee J, Kwon J et al (2008) Multiplex analysis of cytokines in the serum and cerebrospinal fluid of patients with Alzheimer’s disease by color-coded bead technology. J Clin Neurol 4(2):84–88. doi:10.3988/jcn.2008.4.2.84

    Article  PubMed  PubMed Central  Google Scholar 

  94. Delaby C, Gabelle A, Blum D, Schraen-Maschke S, Moulinier A, Boulanghien J et al (2015) Central nervous system and peripheral inflammatory processes in Alzheimer’s disease: biomarker profiling approach. Front Neurol 6:181. doi:10.3389/fneur.2015.00181

    Article  PubMed  PubMed Central  Google Scholar 

  95. Hochstrasser T, Marksteiner J, Defrancesco M, Deisenhammer EA, Kemmler G, Humpel C (2011) Two blood monocytic biomarkers (CCL15 and p21) combined with the mini-mental state examination discriminate Alzheimer’s disease patients from healthy subjects. Dement Geriatr Cogn Dis Extra 1(1):297–309. doi:10.1159/000330468

    Article  PubMed  PubMed Central  Google Scholar 

  96. Blasko I, Kemmler G, Krampla W, Jungwirth S, Wichart I, Jellinger K et al (2005) Plasma amyloid beta protein 42 in non-demented persons aged 75 years: effects of concomitant medication and medial temporal lobe atrophy. Neurobiol Aging 26(8):1135–1143. doi:10.1016/j.neurobiolaging.2005.03.006

    Article  CAS  PubMed  Google Scholar 

  97. Tian Y, Stamova B, Jickling GC, Liu D, Ander BP, Bushnell C et al (2012) Effects of gender on gene expression in the blood of ischemic stroke patients. J Cereb Blood Flow Metab 32(5):780–791. doi:10.1038/jcbfm.2011.179

    Article  CAS  PubMed  Google Scholar 

  98. Kim S, Swaminathan S, Inlow M, Risacher SL, Nho K, Shen L et al (2013) Influence of genetic variation on plasma protein levels in older adults using a multi-analyte panel. PLoS One 8(7):e70269. doi:10.1371/journal.pone.0070269

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Anderson NL, Anderson NG (2002) The human plasma proteome: history, character, and diagnostic prospects. Mol Cell Proteomics 1(11):845–867

    Article  CAS  PubMed  Google Scholar 

  100. Fiandaca MS, Kapogiannis D, Mapstone M, Boxer A, Eitan E, Schwartz JB et al (2015) Identification of preclinical Alzheimer’s disease by a profile of pathogenic proteins in neurally derived blood exosomes: a case-control study. Alzheimers Dement 11(6):600–607.e1. doi:10.1016/j.jalz.2014.06.008

    Article  PubMed  Google Scholar 

  101. Shi M, Liu C, Cook TJ, Bullock KM, Zhao Y, Ginghina C et al (2014) Plasma exosomal alpha-synuclein is likely CNS-derived and increased in Parkinson’s disease. Acta Neuropathol 128(5):639–650. doi:10.1007/s00401-014-1314-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Chiasserini D, van Weering JR, Piersma SR, Pham TV, Malekzadeh A, Teunissen CE et al (2014) Proteomic analysis of cerebrospinal fluid extracellular vesicles: a comprehensive dataset. J Proteomics 106:191–204. doi:10.1016/j.jprot.2014.04.028

    Article  CAS  PubMed  Google Scholar 

  103. Schneider A, Simons M (2013) Exosomes: vesicular carriers for intercellular communication in neurodegenerative disorders. Cell Tissue Res 352(1):33–47. doi:10.1007/s00441-012-1428-2

    Article  CAS  PubMed  Google Scholar 

  104. Garza-Manero S, Arias C, Bermudez-Rattoni F, Vaca L, Zepeda A (2015) Identification of age- and disease-related alterations in circulating miRNAs in a mouse model of Alzheimer’s disease. Front Cell Neurosci 9:53. doi:10.3389/fncel.2015.00053

    Article  PubMed  PubMed Central  Google Scholar 

  105. Zhao Y, Bhattacharjee S, Dua P, Alexandrov PN, Lukiw WJ (2015) microRNA-based biomarkers and the diagnosis of Alzheimer’s disease. Front Neurol 6:162. doi:10.3389/fneur.2015.00162

    Article  PubMed  PubMed Central  Google Scholar 

  106. Olsson A, Vanderstichele H, Andreasen N, De Meyer G, Wallin A, Holmberg B et al (2005) Simultaneous measurement of beta-amyloid(1-42), total tau, and phosphorylated tau (Thr181) in cerebrospinal fluid by the xMAP technology. Clin Chem 51(2):336–345. doi:10.1373/clinchem.2004.039347

    Article  CAS  PubMed  Google Scholar 

  107. Hulstaert F, Blennow K, Ivanoiu A, Schoonderwaldt HC, Riemenschneider M, De Deyn PP et al (1999) Improved discrimination of AD patients using beta-amyloid(1-42) and tau levels in CSF. Neurology 52(8):1555–1562

    Article  CAS  PubMed  Google Scholar 

  108. Biella G, Franceschi M, De Rino F, Davin A, Giacalone G, Brambilla P et al (2013) Multiplex assessment of a panel of 16 serum molecules for the differential diagnosis of Alzheimer’s disease. Am J Neurodegener Dis 2(1):40–45

    PubMed  PubMed Central  Google Scholar 

  109. Lewczuk P, Beck G, Ganslandt O, Esselmann H, Deisenhammer F, Regeniter A et al (2006) International quality control survey of neurochemical dementia diagnostics. Neurosci Lett 409(1):1–4. doi:10.1016/j.neulet.2006.07.009

    Article  CAS  PubMed  Google Scholar 

  110. Del Campo M, Jongbloed W, Twaalfhoven HA, Veerhuis R, Blankenstein MA, Teunissen CE (2015) Facilitating the validation of novel protein biomarkers for dementia: an optimal workflow for the development of sandwich immunoassays. Front Neurol 6:202. doi:10.3389/fneur.2015.00202

    Article  PubMed  PubMed Central  Google Scholar 

  111. Reijn TS, Rikkert MO, van Geel WJ, de Jong D, Verbeek MM (2007) Diagnostic accuracy of ELISA and xMAP technology for analysis of amyloid beta(42) and tau proteins. Clin Chem 53(5):859–865. doi:10.1373/clinchem.2006.081679

    Article  CAS  PubMed  Google Scholar 

  112. Wang LS, Leung YY, Chang SK, Leight S, Knapik-Czajka M, Baek Y et al (2012) Comparison of xMAP and ELISA assays for detecting cerebrospinal fluid biomarkers of Alzheimer’s disease. J Alzheimers Dis 31(2):439–445. doi:10.3233/JAD-2012-120082

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Burnham SC, Faux NG, Wilson W, Laws SM, Ames D, Bedo J et al (2014) A blood-based predictor for neocortical Abeta burden in Alzheimer’s disease: results from the AIBL study. Mol Psychiatry 19(4):519–526. doi:10.1038/mp.2013.40

    Article  CAS  PubMed  Google Scholar 

  114. Guo LH, Alexopoulos P, Wagenpfeil S, Kurz A, Perneczky R, Alzheimer’s Disease Neuroimaging I (2013) Plasma proteomics for the identification of Alzheimer disease. Alzheimer Dis Assoc Disord 27(4):337–342. doi:10.1097/WAD.0b013e31827b60d2

    Article  CAS  PubMed  Google Scholar 

  115. Elshal MF, McCoy JP (2006) Multiplex bead array assays: performance evaluation and comparison of sensitivity to ELISA. Methods 38(4):317–323. doi:10.1016/j.ymeth.2005.11.010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Kang JH, Vanderstichele H, Trojanowski JQ, Shaw LM (2012) Simultaneous analysis of cerebrospinal fluid biomarkers using microsphere-based xMAP multiplex technology for early detection of Alzheimer’s disease. Methods 56(4):484–493. doi:10.1016/j.ymeth.2012.03.023

    Article  CAS  PubMed  Google Scholar 

  117. Shaw LM, Vanderstichele H, Knapik-Czajka M, Figurski M, Coart E, Blennow K et al (2011) Qualification of the analytical and clinical performance of CSF biomarker analyses in ADNI. Acta Neuropathol 121(5):597–609. doi:10.1007/s00401-011-0808-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Petrie EC, Cross DJ, Galasko D, Schellenberg GD, Raskind MA, Peskind ER et al (2009) Preclinical evidence of Alzheimer changes: convergent cerebrospinal fluid biomarker and fluorodeoxyglucose positron emission tomography findings. Arch Neurol 66(5):632–637. doi:10.1001/archneurol.2009.59

    Article  PubMed  PubMed Central  Google Scholar 

  119. Hu WT, Chen-Plotkin A, Arnold SE, Grossman M, Clark CM, Shaw LM et al (2010) Novel CSF biomarkers for Alzheimer’s disease and mild cognitive impairment. Acta Neuropathol 119(6):669–678. doi:10.1007/s00401-010-0667-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Hye A, Riddoch-Contreras J, Baird AL, Ashton NJ, Bazenet C, Leung R et al (2014) Plasma proteins predict conversion to dementia from prodromal disease. Alzheimers Dement 10(6):799–807.e2. doi:10.1016/j.jalz.2014.05.1749

    Article  PubMed  PubMed Central  Google Scholar 

  121. Blennow K, Hampel H (2003) CSF markers for incipient Alzheimer’s disease. Lancet Neurol 2(10):605–613

    Article  CAS  PubMed  Google Scholar 

  122. Humpel C (2011) Identifying and validating biomarkers for Alzheimer’s disease. Trends Biotechnol 29(1):26–32. doi:10.1016/j.tibtech.2010.09.007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Bateman RJ, Xiong C, Benzinger TL, Fagan AM, Goate A, Fox NC et al (2012) Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med 367(9):795–804. doi:10.1056/NEJMoa1202753

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Harari O, Cruchaga C, Kauwe JS, Ainscough BJ, Bales K, Pickering EH et al (2014) Phosphorylated tau-Abeta42 ratio as a continuous trait for biomarker discovery for early-stage Alzheimer’s disease in multiplex immunoassay panels of cerebrospinal fluid. Biol Psychiatry 75(9):723–731. doi:10.1016/j.biopsych.2013.11.032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Beck M, Schmidt A, Malmstroem J, Claassen M, Ori A, Szymborska A et al (2011) The quantitative proteome of a human cell line. Mol Syst Biol 7:549. doi:10.1038/msb.2011.82

    Article  PubMed  PubMed Central  Google Scholar 

  126. Nagaraj N, Wisniewski JR, Geiger T, Cox J, Kircher M, Kelso J et al (2011) Deep proteome and transcriptome mapping of a human cancer cell line. Mol Syst Biol 7:548. doi:10.1038/msb.2011.81

    Article  PubMed  PubMed Central  Google Scholar 

  127. Yin GN, Lee HW, Cho JY, Suk K (2009) Neuronal pentraxin receptor in cerebrospinal fluid as a potential biomarker for neurodegenerative diseases. Brain Res 1265:158–170. doi:10.1016/j.brainres.2009.01.058

    Article  CAS  PubMed  Google Scholar 

  128. Finehout EJ, Franck Z, Choe LH, Relkin N, Lee KH (2007) Cerebrospinal fluid proteomic biomarkers for Alzheimer’s disease. Ann Neurol 61(2):120–129. doi:10.1002/ana.21038

    Article  CAS  PubMed  Google Scholar 

  129. Puchades M, Hansson SF, Nilsson CL, Andreasen N, Blennow K, Davidsson P (2003) Proteomic studies of potential cerebrospinal fluid protein markers for Alzheimer’s disease. Brain Res Mol Brain Res 118(1–2):140–146

    Article  CAS  PubMed  Google Scholar 

  130. Hu Y, Malone JP, Fagan AM, Townsend RR, Holtzman DM (2005) Comparative proteomic analysis of intra- and interindividual variation in human cerebrospinal fluid. Mol Cell Proteomics 4(12):2000–2009. doi:10.1074/mcp.M500207-MCP200

    Article  CAS  PubMed  Google Scholar 

  131. Zenzmaier C, Marksteiner J, Kiefer A, Berger P, Humpel C (2009) Dkk-3 is elevated in CSF and plasma of Alzheimer’s disease patients. J Neurochem 110(2):653–661. doi:10.1111/j.1471-4159.2009.06158.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Maarouf CL, Andacht TM, Kokjohn TA, Castano EM, Sue LI, Beach TG et al (2009) Proteomic analysis of Alzheimer’s disease cerebrospinal fluid from neuropathologically diagnosed subjects. Curr Alzheimer Res 6(4):399–406

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Finehout EJ, Franck Z, Lee KH (2005) Complement protein isoforms in CSF as possible biomarkers for neurodegenerative disease. Dis Markers 21(2):93–101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Zhang J, Goodlett DR, Quinn JF, Peskind E, Kaye JA, Zhou Y et al (2005) Quantitative proteomics of cerebrospinal fluid from patients with Alzheimer disease. J Alzheimers Dis 7(2):125–133. ;discussion 173-180

    CAS  PubMed  Google Scholar 

  135. Ringman JM, Schulman H, Becker C, Jones T, Bai Y, Immermann F et al (2012) Proteomic changes in cerebrospinal fluid of presymptomatic and affected persons carrying familial Alzheimer disease mutations. Arch Neurol 69(1):96–104. doi:10.1001/archneurol.2011.642

    Article  PubMed  PubMed Central  Google Scholar 

  136. Perrin RJ, Payton JE, Malone JP, Gilmore P, Davis AE, Xiong C et al (2013) Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation. PLoS One 8(5):e64314. doi:10.1371/journal.pone.0064314

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Abdi F, Quinn JF, Jankovic J, McIntosh M, Leverenz JB, Peskind E et al (2006) Detection of biomarkers with a multiplex quantitative proteomic platform in cerebrospinal fluid of patients with neurodegenerative disorders. J Alzheimers Dis 9(3):293–348

    CAS  PubMed  Google Scholar 

  138. Wildsmith KR, Schauer SP, Smith AM, Arnott D, Zhu Y, Haznedar J et al (2014) Identification of longitudinally dynamic biomarkers in Alzheimer’s disease cerebrospinal fluid by targeted proteomics. Mol Neurodegener 9:22. doi:10.1186/1750-1326-9-22

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  139. Hendrickson RC, Lee AY, Song Q, Liaw A, Wiener M, Paweletz CP et al (2015) High resolution discovery proteomics reveals candidate disease progression markers of Alzheimer’s disease in human cerebrospinal fluid. PLoS One 10(8):e0135365. doi:10.1371/journal.pone.0135365

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  140. Qin W, Ho L, Wang J, Peskind E, Pasinetti GM (2009) S100A7, a novel Alzheimer’s disease biomarker with non-amyloidogenic alpha-secretase activity acts via selective promotion of ADAM-10. PLoS One 4(1):e4183. doi:10.1371/journal.pone.0004183

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  141. Oh JH, Pan S, Zhang J, Gao J (2010) MSQ: a tool for quantification of proteomics data generated by a liquid chromatography/matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometry based targeted quantitative proteomics platform. Rapid Commun Mass Spectrom 24(4):403–408. doi:10.1002/rcm.4407

    Article  CAS  PubMed  Google Scholar 

  142. Castano EM, Roher AE, Esh CL, Kokjohn TA, Beach T (2006) Comparative proteomics of cerebrospinal fluid in neuropathologically-confirmed Alzheimer’s disease and non-demented elderly subjects. Neurol Res 28(2):155–163. doi:10.1179/016164106X98035

    Article  CAS  PubMed  Google Scholar 

  143. Portelius E, Dean RA, Gustavsson MK, Andreasson U, Zetterberg H, Siemers E et al (2010) A novel Abeta isoform pattern in CSF reflects gamma-secretase inhibition in Alzheimer disease. Alzheimers Res Ther 2(2):7. doi:10.1186/alzrt30

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  144. Portelius E, Gustavsson MK, Zetterberg H, Andreasson U, Blennow K (2012) Evaluation of the performance of novel Abeta isoforms as theragnostic markers in Alzheimer’s disease: from the cell to the patient. Neurodegener Dis 10(1–4):138–140. doi:10.1159/000334537

    Article  CAS  PubMed  Google Scholar 

  145. Wiltfang J, Esselmann H, Bibl M, Smirnov A, Otto M, Paul S et al (2002) Highly conserved and disease-specific patterns of carboxyterminally truncated Abeta peptides 1-37/38/39 in addition to 1-40/42 in Alzheimer’s disease and in patients with chronic neuroinflammation. J Neurochem 81(3):481–496

    Article  CAS  PubMed  Google Scholar 

  146. Verpillot R, Esselmann H, Mohamadi MR, Klafki H, Poirier F, Lehnert S et al (2011) Analysis of amyloid-beta peptides in cerebrospinal fluid samples by capillary electrophoresis coupled with LIF detection. Anal Chem 83(5):1696–1703. doi:10.1021/ac102828f

    Article  CAS  PubMed  Google Scholar 

  147. Gelfanova V, Higgs RE, Dean RA, Holtzman DM, Farlow MR, Siemers ER et al (2007) Quantitative analysis of amyloid-beta peptides in cerebrospinal fluid using immunoprecipitation and MALDI-Tof mass spectrometry. Brief Funct Genomic Proteomic 6(2):149–158. doi:10.1093/bfgp/elm010

    Article  CAS  PubMed  Google Scholar 

  148. Bibl M, Mollenhauer B, Esselmann H, Lewczuk P, Klafki HW, Sparbier K et al (2006) CSF amyloid-beta-peptides in Alzheimer’s disease, dementia with Lewy bodies and Parkinson’s disease dementia. Brain 129(Pt 5):1177–1187. doi:10.1093/brain/awl063

    Article  PubMed  Google Scholar 

  149. Oe T, Ackermann BL, Inoue K, Berna MJ, Garner CO, Gelfanova V et al (2006) Quantitative analysis of amyloid beta peptides in cerebrospinal fluid of Alzheimer’s disease patients by immunoaffinity purification and stable isotope dilution liquid chromatography/negative electrospray ionization tandem mass spectrometry. Rapid Commun Mass Spectrom 20(24):3723–3735. doi:10.1002/rcm.2787

    Article  CAS  PubMed  Google Scholar 

  150. Simonsen AH, Hansson SF, Ruetschi U, McGuire J, Podust VN, Davies HA et al (2007) Amyloid beta1-40 quantification in CSF: comparison between chromatographic and immunochemical methods. Dement Geriatr Cogn Disord 23(4):246–250. doi:10.1159/000100020

    Article  CAS  PubMed  Google Scholar 

  151. Gerhardsson L, Blennow K, Lundh T, Londos E, Minthon L (2009) Concentrations of metals, beta-amyloid and tau-markers in cerebrospinal fluid in patients with Alzheimer’s disease. Dement Geriatr Cogn Disord 28(1):88–94. doi:10.1159/000233353

    Article  CAS  PubMed  Google Scholar 

  152. Kuhlmann J, Andreasson U, Pannee J, Bjerke M, Portelius E, Leinenbach A et al (2016) CSF Abeta1-42 – an excellent but complicated Alzheimer’s biomarker – a route to standardisation. Clin Chim Acta. doi:10.1016/j.cca.2016.05.014

    PubMed  Google Scholar 

  153. Leinenbach A, Pannee J, Dulffer T, Huber A, Bittner T, Andreasson U et al (2014) Mass spectrometry-based candidate reference measurement procedure for quantification of amyloid-beta in cerebrospinal fluid. Clin Chem 60(7):987–994. doi:10.1373/clinchem.2013.220392

    Article  CAS  PubMed  Google Scholar 

  154. Korecka M, Waligorska T, Figurski M, Toledo JB, Arnold SE, Grossman M et al (2014) Qualification of a surrogate matrix-based absolute quantification method for amyloid-beta(4)(2) in human cerebrospinal fluid using 2D UPLC-tandem mass spectrometry. J Alzheimers Dis 41(2):441–451. doi:10.3233/JAD-132489

    CAS  PubMed  PubMed Central  Google Scholar 

  155. Tagami S, Okochi M, Yanagida K, Kodama T, Arai T, Kuwano R et al (2014) Relative ratio and level of amyloid-beta 42 surrogate in cerebrospinal fluid of familial Alzheimer disease patients with presenilin 1 mutations. Neurodegener Dis 13(2–3):166–170. doi:10.1159/000355258

    CAS  PubMed  Google Scholar 

  156. Jahn H, Wittke S, Zurbig P, Raedler TJ, Arlt S, Kellmann M et al (2011) Peptide fingerprinting of Alzheimer’s disease in cerebrospinal fluid: identification and prospective evaluation of new synaptic biomarkers. PLoS One 6(10):e26540. doi:10.1371/journal.pone.0026540

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Lehmann S, Vialaret J, Combe GG, Bauchet L, Hanon O, Girard M et al (2015) Stable Isotope Labeling by Amino acid in Vivo (SILAV): a new method to explore protein metabolism. Rapid Commun Mass Spectrom 29(20):1917–1925. doi:10.1002/rcm.7289

    Article  CAS  PubMed  Google Scholar 

  158. Biroccio A, Del Boccio P, Panella M, Bernardini S, Di Ilio C, Gambi D et al (2006) Differential post-translational modifications of transthyretin in Alzheimer’s disease: a study of the cerebral spinal fluid. Proteomics 6(7):2305–2313. doi:10.1002/pmic.200500285

    Article  CAS  PubMed  Google Scholar 

  159. Carrette O, Demalte I, Scherl A, Yalkinoglu O, Corthals G, Burkhard P et al (2003) A panel of cerebrospinal fluid potential biomarkers for the diagnosis of Alzheimer’s disease. Proteomics 3(8):1486–1494. doi:10.1002/pmic.200300470

    Article  CAS  PubMed  Google Scholar 

  160. Yin GN, Jeon H, Lee S, Lee HW, Cho JY, Suk K (2009) Role of soluble CD14 in cerebrospinal fluid as a regulator of glial functions. J Neurosci Res 87(11):2578–2590. doi:10.1002/jnr.22081

    Article  CAS  PubMed  Google Scholar 

  161. Kvartsberg H, Duits FH, Ingelsson M, Andreasen N, Ohrfelt A, Andersson K et al (2015) Cerebrospinal fluid levels of the synaptic protein neurogranin correlates with cognitive decline in prodromal Alzheimer’s disease. Alzheimers Dement 11(10):1180–1190. doi:10.1016/j.jalz.2014.10.009

    Article  PubMed  Google Scholar 

  162. Brinkmalm A, Brinkmalm G, Honer WG, Frolich L, Hausner L, Minthon L et al (2014) SNAP-25 is a promising novel cerebrospinal fluid biomarker for synapse degeneration in Alzheimer’s disease. Mol Neurodegener 9:53. doi:10.1186/1750-1326-9-53

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  163. Veitinger M, Oehler R, Umlauf E, Baumgartner R, Schmidt G, Gerner C et al (2014) A platelet protein biochip rapidly detects an Alzheimer’s disease-specific phenotype. Acta Neuropathol 128(5):665–677. doi:10.1007/s00401-014-1341-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Thambisetty M, Tripaldi R, Riddoch-Contreras J, Hye A, An Y, Campbell J et al (2010) Proteome-based plasma markers of brain amyloid-beta deposition in non-demented older individuals. J Alzheimers Dis 22(4):1099–1109. doi:10.3233/JAD-2010-101350

    CAS  PubMed  PubMed Central  Google Scholar 

  165. Hye A, Lynham S, Thambisetty M, Causevic M, Campbell J, Byers HL et al (2006) Proteome-based plasma biomarkers for Alzheimer’s disease. Brain 129(Pt 11):3042–3050. doi:10.1093/brain/awl279

    Article  CAS  PubMed  Google Scholar 

  166. Henkel AW, Muller K, Lewczuk P, Muller T, Marcus K, Kornhuber J et al (2012) Multidimensional plasma protein separation technique for identification of potential Alzheimer’s disease plasma biomarkers: a pilot study. J Neural Transm (Vienna) 119(7):779–788. doi:10.1007/s00702-012-0781-3

    Article  CAS  Google Scholar 

  167. Bakalarski CE, Kirkpatrick DS (2016) A biologist’s field guide to multiplexed quantitative proteomics. Mol Cell Proteomics 15(5):1489–1497. doi:10.1074/mcp.O115.056986

    Article  CAS  PubMed  Google Scholar 

  168. Shih YH, Tsai KJ, Lee CW, Shiesh SC, Chen WT, Pai MC et al (2014) Apolipoprotein C-III is an amyloid-beta-binding protein and an early marker for Alzheimer’s disease. J Alzheimers Dis 41(3):855–865. doi:10.3233/JAD-140111

    CAS  PubMed  Google Scholar 

  169. Muenchhoff J, Poljak A, Song F, Raftery M, Brodaty H, Duncan M et al (2015) Plasma protein profiling of mild cognitive impairment and Alzheimer’s disease across two independent cohorts. J Alzheimers Dis 43(4):1355–1373. doi:10.3233/JAD-141266

    CAS  PubMed  Google Scholar 

  170. Guntert A, Campbell J, Saleem M, O’Brien DP, Thompson AJ, Byers HL et al (2010) Plasma gelsolin is decreased and correlates with rate of decline in Alzheimer’s disease. J Alzheimers Dis 21(2):585–596. doi:10.3233/JAD-2010-100279

    PubMed  Google Scholar 

  171. Watt AD, Perez KA, Faux NG, Pike KE, Rowe CC, Bourgeat P, Salvado O et al (2011) Increasing the predictive accuracy of amyloid-beta blood-borne biomarkers in Alzheimer’s disease. J Alzheimers Dis 24(1):47–59. doi:10.3233/JAD-2010-101722

    CAS  PubMed  Google Scholar 

  172. Yang H, Lyutvinskiy Y, Herukka SK, Soininen H, Rutishauser D, Zubarev RA (2014) Prognostic polypeptide blood plasma biomarkers of Alzheimer’s disease progression. J Alzheimers Dis 40(3):659–666. doi:10.3233/JAD-132102

    CAS  PubMed  Google Scholar 

  173. Kim JS, Ahn HS, Cho SM, Lee JE, Kim Y, Lee C (2014) Detection and quantification of plasma amyloid-beta by selected reaction monitoring mass spectrometry. Anal Chim Acta 840:1–9. doi:10.1016/j.aca.2014.06.024

    Article  CAS  PubMed  Google Scholar 

  174. Kaneko N, Nakamura A, Washimi Y, Kato T, Sakurai T, Arahata Y et al (2014) Novel plasma biomarker surrogating cerebral amyloid deposition. Proc Jpn Acad Ser B Phys Biol Sci 90(9):353–364

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Bennett S, Grant M, Creese AJ, Mangialasche F, Cecchetti R, Cooper HJ et al (2012) Plasma levels of complement 4a protein are increased in Alzheimer’s disease. Alzheimer Dis Assoc Disord 26(4):329–334. doi:10.1097/WAD.0b013e318239dcbd

    Article  CAS  PubMed  Google Scholar 

  176. Lundstrom SL, Yang H, Lyutvinskiy Y, Rutishauser D, Herukka SK, Soininen H et al (2014) Blood plasma IgG Fc glycans are significantly altered in Alzheimer’s disease and progressive mild cognitive impairment. J Alzheimers Dis 38(3):567–579. doi:10.3233/JAD-131088

    PubMed  Google Scholar 

  177. Hare DJ, Doecke JD, Faux NG, Rembach A, Volitakis I, Fowler CJ et al (2015) Decreased plasma iron in Alzheimer’s disease is due to transferrin desaturation. ACS Chem Nerosci 6(3):398–402. doi:10.1021/cn5003557

    Article  CAS  Google Scholar 

  178. Martinez-Morillo E, Hansson O, Atagi Y, Bu G, Minthon L, Diamandis EP et al (2014) Total apolipoprotein E levels and specific isoform composition in cerebrospinal fluid and plasma from Alzheimer’s disease patients and controls. Acta Neuropathol 127(5):633–643. doi:10.1007/s00401-014-1266-2

    Article  CAS  PubMed  Google Scholar 

  179. Shi M, Sui YT, Peskind ER, Li G, Hwang H, Devic I et al (2011) Salivary tau species are potential biomarkers of Alzheimer’s disease. J Alzheimers Dis 27(2):299–305. doi:10.3233/JAD-2011-110731

    CAS  PubMed  PubMed Central  Google Scholar 

  180. Bantscheff M, Kuster B (2012) Quantitative mass spectrometry in proteomics. Anal Bioanal Chem 404(4):937–938. doi:10.1007/s00216-012-6261-7

    Article  CAS  PubMed  Google Scholar 

  181. Bantscheff M, Lemeer S, Savitski MM, Kuster B (2012) Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present. Anal Bioanal Chem 404(4):939–965. doi:10.1007/s00216-012-6203-4

    Article  CAS  PubMed  Google Scholar 

  182. Gallien S, Domon B (2015) Advances in high-resolution quantitative proteomics: implications for clinical applications. Expert Rev Proteomics 12(5):489–498. doi:10.1586/14789450.2015.1069188

    Article  CAS  PubMed  Google Scholar 

  183. Rauniyar N, Yates JR 3rd (2014) Isobaric labeling-based relative quantification in shotgun proteomics. J Proteome Res 13(12):5293–5309. doi:10.1021/pr500880b

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Evans AR, Gu L, Guerrero R Jr, Robinson RA (2015) Global cPILOT analysis of the APP/PS-1 mouse liver proteome. Proteomics Clin Appl 9(9–10):872–884. doi:10.1002/prca.201400149

    Article  CAS  PubMed  Google Scholar 

  185. Evans AR, Robinson RA (2013) Global combined precursor isotopic labeling and isobaric tagging (cPILOT) approach with selective MS(3) acquisition. Proteomics 13(22):3267–3272. doi:10.1002/pmic.201300198

    Article  CAS  PubMed  Google Scholar 

  186. Gu L, Evans AR, Robinson RA (2015) Sample multiplexing with cysteine-selective approaches: cysDML and cPILOT. J Am Soc Mass Spectrom 26(4):615–630. doi:10.1007/s13361-014-1059-9

    Article  CAS  PubMed  Google Scholar 

  187. Dephoure N, Gygi SP (2012) Hyperplexing: a method for higher-order multiplexed quantitative proteomics provides a map of the dynamic response to rapamycin in yeast. Sci Signal 5(217):rs2. doi:10.1126/scisignal.2002548

    Article  PubMed  PubMed Central  Google Scholar 

  188. Heywood WE, Galimberti D, Bliss E, Sirka E, Paterson RW, Magdalinou NK et al (2015) Identification of novel CSF biomarkers for neurodegeneration and their validation by a high-throughput multiplexed targeted proteomic assay. Mol Neurodegener 10:64. doi:10.1186/s13024-015-0059-y

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  189. Sattlecker M, Kiddle SJ, Newhouse S, Proitsi P, Nelson S, Williams S et al (2014) Alzheimer’s disease biomarker discovery using SOMAscan multiplexed protein technology. Alzheimers Dement 10(6):724–734. doi:10.1016/j.jalz.2013.09.016

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the University of Pittsburgh Start-Up Funds, the University of Pittsburgh Alzheimer’s Disease Research Center (P50 AG005133) and the National Institutes of Health’s National Institute of General Medicine Sciences (1R01GM 117191-01) for funds to support this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Renã A. S. Robinson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Robinson, R.A.S., Amin, B., Guest, P.C. (2017). Multiplexing Biomarker Methods, Proteomics and Considerations for Alzheimer’s Disease. In: Guest, P. (eds) Proteomic Methods in Neuropsychiatric Research. Advances in Experimental Medicine and Biology(), vol 974. Springer, Cham. https://doi.org/10.1007/978-3-319-52479-5_2

Download citation

Publish with us

Policies and ethics