Generic placeholder image

Current Pharmaceutical Design

Editor-in-Chief

ISSN (Print): 1381-6128
ISSN (Online): 1873-4286

Review Article

Neuroproteomics Chip-Based Mass Spectrometry and Other Techniques for Alzheimer’s Disease Biomarkers – Update

Author(s): Alicia B. Pomilio*, Arturo A. Vitale and Alberto J. Lazarowski

Volume 28, Issue 14, 2022

Published on: 27 May, 2022

Page: [1124 - 1151] Pages: 28

DOI: 10.2174/1381612828666220413094918

Price: $65

Abstract

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease of growing interest given that there is cognitive damage and symptom onset acceleration. Therefore, it is important to find AD biomarkers for early diagnosis, disease progression, and discrimination of AD and other diseases.

Objective: The objective of this study is to update the relevance of mass spectrometry for the identification of peptides and proteins involved in AD useful as discriminating biomarkers.

Methods: Proteomics and peptidomics technologies that show the highest possible specificity and selectivity for AD biomarkers are analyzed, together with the biological fluids used. In addition to positron emission tomography and magnetic resonance imaging, MALDI-TOF mass spectrometry is widely used to identify proteins and peptides involved in AD. The use of protein chips in SELDI technology and electroblotting chips for peptides makes feasible small amounts (μL) of samples for analysis.

Results: Suitable biomarkers are related to AD pathology, such as intracellular neurofibrillary tangles; extraneuronal senile plaques; neuronal and axonal degeneration; inflammation and oxidative stress. Recently, peptides were added to the candidate list, which are not amyloid-β or tau fragments, but are related to coagulation, brain plasticity, and complement/neuroinflammation systems involving the neurovascular unit.

Conclusion: The progress made in the application of mass spectrometry and recent chip techniques is promising for discriminating between AD, mild cognitive impairment, and matched healthy controls. The application of this technique to blood samples from patients with AD has shown to be less invasive and fast enough to determine the diagnosis, stage of the disease, prognosis, and follow-up of the therapeutic response.

Keywords: Alzheimer's disease, neuroproteomics, cerebrospinal fluid and blood biomarkers, mass spectrometry, chip-mass spectrometry, brain imaging, biosensor.

[1]
Vitale AA, Ciprian-Ollivier J, Vitale MG, et al. Clinical studies of markers of the indolic hypermethylation in human perception alterations. Acta Bioquim Clin Latinoam 2010; 44: 627-42.
[2]
Vitale AA, Pomilio AB, Cañellas CO, Vitale MG, Putz EM, Ciprian-Ollivier J. In vivo long-term kinetics of radiolabeled n,n-dimethyltryptamine and tryptamine. J Nucl Med 2011; 52(6): 970-7.
[http://dx.doi.org/10.2967/jnumed.110.083246] [PMID: 21622895]
[3]
Pomilio AB, Vitale AA, Ciprian Ollivier O. Clinical and radiolabeled studies of biomarkers of the indolic hypermethylation in human perception alterations - Scientific Society Argentina Award in Science. An Soc Cient Argent 2017; 259: 5-20.
[4]
Merelli A, Repetto M, Lazarowski A, Auzmendi J. Hypoxia, oxidative stress, and inflammation: Three faces of neurodegenerative diseases. J Alzheimers Dis 2021; 82(s1): S109-26.
[http://dx.doi.org/10.3233/JAD-201074] [PMID: 33325385]
[5]
Merelli A, Ramos AJ, Lazarowski A, Auzmendi J. Convulsive stress mimics brain hypoxia and promotes the P-Glycoprotein (P-gp) and erythropoietin receptor overexpression. Recombinant human erythropoietin effect on P-gp activity. Front Neurosci 2019; 13: 750.
[http://dx.doi.org/10.3389/fnins.2019.00750] [PMID: 31379495]
[6]
Merelli A, Rodríguez JCG, Folch J, Regueiro MR, Camins A, Lazarowski A. Understanding the role of hypoxia inducible factor during neurodegeneration for new therapeutics opportunities. Curr Neuropharmacol 2018; 16(10): 1484-98.
[http://dx.doi.org/10.2174/1570159X16666180110130253] [PMID: 29318974]
[7]
Blennow K, Zetterberg H, Fagan AM. Fluid biomarkers in Alzheimer disease. Cold Spring Harb Perspect Med 2012; 2(9): a006221.
[http://dx.doi.org/10.1101/cshperspect.a006221] [PMID: 22951438]
[8]
Nir TM, Jahanshad N, Villalon-Reina JE, et al. Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging. Neuroimage Clin 2013; 3: 180-95.
[http://dx.doi.org/10.1016/j.nicl.2013.07.006] [PMID: 24179862]
[9]
Armstrong RA. Risk factors for Alzheimer’s disease. Folia Neuropathol 2019; 57(2): 87-105.
[http://dx.doi.org/10.5114/fn.2019.85929] [PMID: 31556570]
[10]
Akasaka-Manya K, Manya H. The role of APP O-glycosylation in Alzheimer’s disease. Biomolecules 2020; 10(11): 1569.
[http://dx.doi.org/10.3390/biom10111569] [PMID: 33218200]
[11]
Sferra A, Nicita F, Bertini E. Microtubule dysfunction: A common feature of neurodegenerative diseases. Int J Mol Sci 2020; 21(19): 7354.
[http://dx.doi.org/10.3390/ijms21197354] [PMID: 33027950]
[12]
Orr ME, Sullivan AC, Frost B. A brief overview of tauopathy: Causes, consequences, and therapeutic strategies. Trends Pharmacol Sci 2017; 38(7): 637-48.
[http://dx.doi.org/10.1016/j.tips.2017.03.011] [PMID: 28455089]
[13]
Hardy JA, Higgins GA. Alzheimer’s disease: The amyloid cascade hypothesis. Science 1992; 256(5054): 184-5.
[http://dx.doi.org/10.1126/science.1566067] [PMID: 1566067]
[14]
McGrowder DA, Miller F, Vaz K, et al. Cerebrospinal fluid biomarkers of Alzheimer’s disease: Current evidence and future perspectives. Brain Sci 2021; 11(2): 215.
[http://dx.doi.org/10.3390/brainsci11020215] [PMID: 33578866]
[15]
Ricciarelli R, Fedele E. The amyloid cascade hypothesis in Alzheimer’s disease: It’s time to change our mind. Curr Neuropharmacol 2017; 15(6): 926-35.
[http://dx.doi.org/10.2174/1570159X15666170116143743] [PMID: 28093977]
[16]
Nazam F, Shaikh S, Nazam N, Alshahrani AS, Hasan GM, Hassan MI. Mechanistic insights into the pathogenesis of neurodegenerative diseases: Towards the development of effective therapy. Mol Cell Biochem 2021; 476(7): 2739-52.
[http://dx.doi.org/10.1007/s11010-021-04120-6] [PMID: 33687588]
[17]
Femminella GD, Rengo G, Komici K, et al. Autonomic dysfunction in Alzheimer’s disease: Tools for assessment and review of the literature. J Alzheimers Dis 2014; 42(2): 369-77.
[http://dx.doi.org/10.3233/JAD-140513] [PMID: 24898649]
[18]
Verma A, Zabel M. Alzheimer’s disease: Beyond the neuron. In: Dorszewska J, Kozubski W, Eds. Alzheimer’s Disease - The 21st Century Challenge. IntechOpen 2018.
[http://dx.doi.org/10.5772/intechopen.75510]
[19]
van der Velpen V, Teav T, Gallart-Ayala H, et al. Systemic and central nervous system metabolic alterations in Alzheimer’s disease. Alzheimers Res Ther 2019; 11(1): 93.
[http://dx.doi.org/10.1186/s13195-019-0551-7] [PMID: 31779690]
[20]
Kinney JW, Bemiller SM, Murtishaw AS, Leisgang AM, Salazar AM, Lamb BT. Inflammation as a central mechanism in Alzheimer’s disease. Alzheimers Dement (N Y) 2018; 4(1): 575-90.
[http://dx.doi.org/10.1016/j.trci.2018.06.014] [PMID: 30406177]
[21]
Narayanaswami V, Dahl K, Bernard-Gauthier V, Josephson L, Cumming P, Vasdev N. Emerging PET radiotracers and targets for imaging of neuroinflammation in neurodegenerative diseases: Outlook beyond TSPO. Mol Imaging 2018; 17: 1536012118792317.
[http://dx.doi.org/10.1177/1536012118792317] [PMID: 30203712]
[22]
Fleeman RM, Proctor EA. Astrocytic propagation of tau in the context of Alzheimer’s disease. Front Cell Neurosci 2021; 15: 645233.
[http://dx.doi.org/10.3389/fncel.2021.645233] [PMID: 33815065]
[23]
Onyango IG, Jauregui GV, Čarná M, Bennett JP Jr, Stokin GB. Neuroinflammation in Alzheimer’s disease Biomedicines 2021; 9(5): 524.
[http://dx.doi.org/10.3390/biomedicines9050524] [PMID: 34067173]
[24]
Lim D, Rodríguez-Arellano JJ, Parpura V, et al. Calcium signalling toolkits in astrocytes and spatio-temporal progression of Alzheimer’s disease. Curr Alzheimer Res 2016; 13(4): 359-69.
[http://dx.doi.org/10.2174/1567205013666151116130104] [PMID: 26567740]
[25]
Jack CR Jr, Bennett DA, Blennow K, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement 2018; 14(4): 535-62.
[http://dx.doi.org/10.1016/j.jalz.2018.02.018] [PMID: 29653606]
[26]
Reitz C, Rogaeva E, Beecham GW. Late-onset vs nonmendelian early-onset Alzheimer disease: A distinction without a difference? Neurol Genet 2020; 6(5): e512.
[http://dx.doi.org/10.1212/NXG.0000000000000512] [PMID: 33225065]
[27]
Seto M, Weiner RL, Dumitrescu L, Hohman TJ. Protective genes and pathways in Alzheimer’s disease: Moving towards precision interventions. Mol Neurodegener 2021; 16(1): 29.
[http://dx.doi.org/10.1186/s13024-021-00452-5] [PMID: 33926499]
[28]
D’Argenio V, Sarnataro D. New insights into the molecular bases of familial Alzheimer’s disease. J Pers Med 2020; 10(2): 26.
[http://dx.doi.org/10.3390/jpm10020026] [PMID: 32325882]
[29]
Baker E, Escott-Price V. Polygenic risk scores in Alzheimer’s disease: Current applications and future directions. Front Digit Health 2020; 2: 14.
[http://dx.doi.org/10.3389/fdgth.2020.00014] [PMID: 34713027]
[30]
Zhou X, Li YYT, Fu AKY, Ip NY. Polygenic score models for Alzheimer’s disease: From research to clinical applications. Front Neurosci 2021; 15: 650220.
[http://dx.doi.org/10.3389/fnins.2021.650220] [PMID: 33854414]
[31]
Rabinovici GD. Late-onset Alzheimer disease. Continuum (Minneap Minn) 2019; 25(1): 14-33.
[http://dx.doi.org/10.1212/CON.0000000000000700] [PMID: 30707185]
[32]
Kunkle BW, Grenier-Boley B, Sims R, et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ tau, immunity and lipid processing. Nat Genet 2019; 51(3): 414-30.
[http://dx.doi.org/10.1038/s41588-019-0358-2] [PMID: 30820047]
[33]
Schliebs R, Arendt T. The cholinergic system in aging and neuronal degeneration. Behav Brain Res 2011; 221(2): 555-63.
[http://dx.doi.org/10.1016/j.bbr.2010.11.058] [PMID: 21145918]
[34]
Andrews SJ, Fulton-Howard B, Goate A. Protective variants in Alzheimer’s disease. Curr Genet Med Rep 2019; 7(1): 1-12.
[http://dx.doi.org/10.1007/s40142-019-0156-2] [PMID: 33117616]
[35]
Silva MVF, Loures CMG, Alves LCV, de Souza LC, Borges KBG, Carvalho MDG. Alzheimer’s disease: Risk factors and potentially protective measures. J Biomed Sci 2019; 26(1): 33.
[http://dx.doi.org/10.1186/s12929-019-0524-y] [PMID: 31072403]
[36]
Wang Y, Cella M, Mallinson K, et al. TREM2 lipid sensing sustains the microglial response in an Alzheimer’s disease model. Cell 2015; 160(6): 1061-71.
[http://dx.doi.org/10.1016/j.cell.2015.01.049] [PMID: 25728668]
[37]
Andersen SL. Centenarians as models of resistance and resilience to Alzheimer’s disease and related dementias. Adv Geriatr Med Res 2020; 2(3): e200018.
[PMID: 32743561]
[38]
Stern Y, Arenaza-Urquijo EM, Bartrés-Faz D, et al. Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance. Alzheimers Dement 2020; 16(9): 1305-11.
[http://dx.doi.org/10.1016/j.jalz.2018.07.219] [PMID: 30222945]
[39]
Hohman TJ, McLaren DG, Mormino EC, Gifford KA, Libon DJ, Jefferson AL. Asymptomatic Alzheimer disease: Defining resilience. Neurology 2016; 87(23): 2443-50.
[http://dx.doi.org/10.1212/WNL.0000000000003397] [PMID: 27815399]
[40]
Kockx M, Traini M, Kritharides L. Cell-specific production, secretion, and function of apolipoprotein E. J Mol Med (Berl) 2018; 96(5): 361-71.
[http://dx.doi.org/10.1007/s00109-018-1632-y] [PMID: 29516132]
[41]
Abondio P, Sazzini M, Garagnani P, et al. The genetic variability of APOE in different human populations and its implications for longevity. Genes (Basel) 2019; 10(3): 222.
[http://dx.doi.org/10.3390/genes10030222] [PMID: 30884759]
[42]
Finch CE, Kulminski AM. The ApoE locus and COVID-19: Are we going where we have been? J Gerontol A Biol Sci Med Sci 2021; 76(2): e1-3.
[http://dx.doi.org/10.1093/gerona/glaa200] [PMID: 32777042]
[43]
Lanfranco MF, Ng CA, Rebeck GW. ApoE lipidation as a therapeutic target in Alzheimer’s disease. Int J Mol Sci 2020; 21(17): 6336.
[http://dx.doi.org/10.3390/ijms21176336] [PMID: 32882843]
[44]
Jacobo-Albavera L, Domínguez-Pérez M, Medina-Leyte DJ, González-Garrido A, Villarreal-Molina T. The role of the ATP-Binding Cassette A1 (ABCA1) in human disease. Int J Mol Sci 2021; 22(4): 1593.
[http://dx.doi.org/10.3390/ijms22041593] [PMID: 33562440]
[45]
Lazarowski A. ABC-transporters and drug efflux in hematologic cancers In: Sosnik A, Bendayan R, Eds. Drug efflux pumps in cancer resistance pathways From molecular recognition and characterization to possible inhibition strategies in chemotherapy London: Academic Press; Elsevier. 2020; 7: pp. 149-96.
[http://dx.doi.org/10.1016/B978-0-12-816434-1.00006-1]
[46]
Lazarowski A, Czornyj L, Lubienieki F, Girardi E, Vazquez S, D’Giano C. ABC transporters during epilepsy and mechanisms underlying multidrug resistance in refractory epilepsy. Epilepsia 2007; 48(s5)(Suppl. 5): 140-9.
[http://dx.doi.org/10.1111/j.1528-1167.2007.01302.x] [PMID: 17910594]
[47]
Mercader AG, Pomilio AB. (Iso)flav(an)ones, chalcones, catechins, and theaflavins as anticarcinogens: Mechanisms, anti-multidrug resistance and QSAR studies. Curr Med Chem 2012; 19(25): 4324-47.
[http://dx.doi.org/10.2174/092986712802884277] [PMID: 22830339]
[48]
Cui J, Liu X, Chow LMC. Flavonoids as P-gp inhibitors: A systematic review of SARs. Curr Med Chem 2019; 26(25): 4799-831.
[http://dx.doi.org/10.2174/0929867325666181001115225] [PMID: 30277144]
[49]
Vrzal R. Anthocyanidins but not anthocyanins inhibit P-glycoprotein-mediated calcein extrusion - possible implication for orally administered drugs. Fundam Clin Pharmacol 2016; 30(3): 248-52.
[http://dx.doi.org/10.1111/fcp.12183] [PMID: 26821071]
[50]
Pomilio AB, Mercader AG. Natural acylated anthocyanins and other related flavonoids: Structure elucidation of Ipomoea cairica compounds and QSAR studies including multidrug resistance In: Atta-ur-Rahman Studies in Natural Products Chemistry Vol 55: Bioactive Natural Products Chapter 9. 293-322.
[51]
McCormick JW, Ammerman L, Chen G, Vogel PD, Wise JG. Transport of Alzheimer’s associated amyloid-β catalyzed by P-glycoprotein. PLoS One 2021; 16(4): e0250371.
[http://dx.doi.org/10.1371/journal.pone.0250371] [PMID: 33901197]
[52]
Al Rihani SB, Darakjian LI, Deodhar M, Dow P, Turgeon J, Michaud V. Disease-induced modulation of drug transporters at the blood-brain barrier level. Int J Mol Sci 2021; 22(7): 3742.
[http://dx.doi.org/10.3390/ijms22073742] [PMID: 33916769]
[53]
Elmeliegy M, Vourvahis M, Guo C, Wang DD. Effect of P-glycoprotein (P-gp) inducers on exposure of P-gp substrates: Review of clinical drug-drug interaction studies. Clin Pharmacokinet 2020; 59(6): 699-714.
[http://dx.doi.org/10.1007/s40262-020-00867-1] [PMID: 32052379]
[54]
Behl T, Kaur I, Sehgal A, Kumar A, Uddin MS, Bungau S. The interplay of ABC transporters in Aβ translocation and cholesterol metabolism: Implicating their roles in Alzheimer’s disease. Mol Neurobiol 2021; 58(4): 1564-82.
[http://dx.doi.org/10.1007/s12035-020-02211-x] [PMID: 33215389]
[55]
Yassine HN, Feng Q, Chiang J, et al. ABCA1-mediated cholesterol efflux capacity to cerebrospinal fluid is reduced in patients with mild cognitive impairment and Alzheimer’s disease. J Am Heart Assoc 2016; 5(2): e002886.
[http://dx.doi.org/10.1161/JAHA.115.002886] [PMID: 26873692]
[56]
Gugliandolo A, Chiricosta L, Boccardi V, Mecocci P, Bramanti P, Mazzon E. MicroRNAs modulate the pathogenesis of Alzheimer’s disease: An in silico analysis in the human brain. Genes (Basel) 2020; 11(9): 983.
[http://dx.doi.org/10.3390/genes11090983] [PMID: 32846925]
[57]
Samadian M, Gholipour M, Hajiesmaeili M, Taheri M, Ghafouri-Fard S. The eminent role of microRNAs in the pathogenesis of Alzheimer’s disease. Front Aging Neurosci 2021; 13: 641080.
[http://dx.doi.org/10.3389/fnagi.2021.641080] [PMID: 33790780]
[58]
Angelucci F, Cechova K, Valis M, Kuca K, Zhang B, Hort J. MicroRNAs in Alzheimer’s disease: Diagnostic markers or therapeutic agents? Front Pharmacol 2019; 10: 665.
[http://dx.doi.org/10.3389/fphar.2019.00665] [PMID: 31275145]
[59]
Kim J, Yoon H, Horie T, et al. MicroRNA-33 regulates ApoE lipidation and amyloid-β metabolism in the brain. J Neurosci 2015; 35(44): 14717-26.
[http://dx.doi.org/10.1523/JNEUROSCI.2053-15.2015] [PMID: 26538644]
[60]
Jaouen F, Gascon E. Understanding the role of miR-33 in brain lipid metabolism: Implications for Alzheimer’s disease. J Neurosci 2016; 36(9): 2558-60.
[http://dx.doi.org/10.1523/JNEUROSCI.4571-15.2016] [PMID: 26936997]
[61]
Liu CC, Kanekiyo T, Xu H, Bu G. Apolipoprotein E and Alzheimer disease: Risk, mechanisms and therapy. Nat Rev Neurol 2013; 9(2): 106-18.
[http://dx.doi.org/10.1038/nrneurol.2012.263] [PMID: 23296339]
[62]
Kulminski AM, Shu L, Loika Y, et al. APOE region molecular signatures of Alzheimer’s disease across races/ethnicities. Neurobiol Aging 2020; 87: 141.e1-8.
[http://dx.doi.org/10.1016/j.neurobiolaging.2019.11.007] [PMID: 31813627]
[63]
Matsunaga A, Saito T. Apolipoprotein E mutations: A comparison between lipoprotein glomerulopathy and type III hyperlipoproteinemia. Clin Exp Nephrol 2014; 18(2): 220-4.
[http://dx.doi.org/10.1007/s10157-013-0918-1] [PMID: 24570178]
[64]
Riedel BC, Thompson PM, Brinton RD. Age, APOE and sex: Triad of risk of Alzheimer’s disease. J Steroid Biochem Mol Biol 2016; 160: 134-47.
[http://dx.doi.org/10.1016/j.jsbmb.2016.03.012] [PMID: 26969397]
[65]
Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between Apolipoprotein E genotype and Alzheimer disease. A meta-analysis. JAMA 1997; 278(16): 1349-56.
[http://dx.doi.org/10.1001/jama.1997.03550160069041] [PMID: 9343467]
[66]
Huq AJ, Fransquet P, Laws SM, et al. Genetic resilience to Alzheimer’s disease in APOE ε4 homozygotes: A systematic review. Alzheimers Dement 2019; 15(12): 1612-23.
[http://dx.doi.org/10.1016/j.jalz.2019.05.011] [PMID: 31506248]
[67]
Ramanan VK, Lesnick TG, Przybelski SA, et al. Coping with brain amyloid: Genetic heterogeneity and cognitive resilience to Alzheimer’s pathophysiology. Acta Neuropathol Commun 2021; 9(1): 48.
[http://dx.doi.org/10.1186/s40478-021-01154-1] [PMID: 33757599]
[68]
Williams T, Borchelt DR, Chakrabarty P. Therapeutic approaches targeting Apolipoprotein E function in Alzheimer’s disease. Mol Neurodegener 2020; 15(1): 8.
[http://dx.doi.org/10.1186/s13024-020-0358-9] [PMID: 32005122]
[69]
Chew H, Solomon VA, Fonteh AN. Involvement of lipids in Alzheimer’s disease pathology and potential therapies. Front Physiol 2020; 11: 598.
[http://dx.doi.org/10.3389/fphys.2020.00598] [PMID: 32581851]
[70]
Aikawa T, Ren Y, Holm ML, et al. ABCA7 regulates brain fatty acid metabolism during LPS-induced acute inflammation. Front Neurosci 2021; 15: 647974.
[http://dx.doi.org/10.3389/fnins.2021.647974] [PMID: 33897360]
[71]
Dib S, Pahnke J, Gosselet F. Role of ABCA7 in human health and in Alzheimer’s disease. Int J Mol Sci 2021; 22(9): 4603.
[http://dx.doi.org/10.3390/ijms22094603] [PMID: 33925691]
[72]
Podleśny-Drabiniok A, Marcora E, Goate AM. Microglial phagocytosis: A disease-associated process emerging from Alzheimer’s disease genetics. Trends Neurosci 2020; 43(12): 965-79.
[http://dx.doi.org/10.1016/j.tins.2020.10.002] [PMID: 33127097]
[73]
Bhattacherjee A, Rodrigues E, Jung J, et al. Repression of phagocytosis by human CD33 is not conserved with mouse CD33. Commun Biol 2019; 2: 450.
[http://dx.doi.org/10.1038/s42003-019-0698-6] [PMID: 31815204]
[74]
Bhattacherjee A, Jung J, Zia S, et al. The CD33 short isoform is a gain-of-function variant that enhances Aβ1-42 phagocytosis in microglia. Mol Neurodegener 2021; 16(1): 19.
[http://dx.doi.org/10.1186/s13024-021-00443-6] [PMID: 33766097]
[75]
Folch J, Petrov D, Ettcheto M, et al. Masitinib for the treatment of mild to moderate Alzheimer’s disease. Expert Rev Neurother 2015; 15(6): 587-96.
[http://dx.doi.org/10.1586/14737175.2015.1045419] [PMID: 25961655]
[76]
Blennow K, Zetterberg H. Biomarkers for Alzheimer’s disease: Current status and prospects for the future. J Intern Med 2018; 284(6): 643-63.
[http://dx.doi.org/10.1111/joim.12816] [PMID: 30051512]
[77]
Clarke MTM, Brinkmalm A, Foiani MS, et al. CSF synaptic protein concentrations are raised in those with atypical Alzheimer’s disease but not frontotemporal dementia. Alzheimers Res Ther 2019; 11(1): 105.
[http://dx.doi.org/10.1186/s13195-019-0564-2] [PMID: 31847891]
[78]
Abdullah M, Kimura N, Akatsu H, et al. Flotillin is a novel diagnostic blood marker of Alzheimer’s disease. J Alzheimers Dis 2019; 72(4): 1165-76.
[http://dx.doi.org/10.3233/JAD-190908] [PMID: 31683489]
[79]
Bălașa AF, Chircov C, Grumezescu AM. Body fluid biomarkers for Alzheimer’s disease-an up-to-date overview. Biomedicines 2020; 8(10): 421.
[http://dx.doi.org/10.3390/biomedicines8100421] [PMID: 33076333]
[80]
Villa C, Lavitrano M, Salvatore E, Combi R. Molecular and imaging biomarkers in Alzheimer’s disease: A focus on recent insights. J Pers Med 2020; 10(3): 61.
[http://dx.doi.org/10.3390/jpm10030061] [PMID: 32664352]
[81]
Del Prete E, Beatino MF, Campese N, et al. Fluid candidate biomarkers for Alzheimer’s disease: A precision medicine approach. J Pers Med 2020; 10(4): 221.
[http://dx.doi.org/10.3390/jpm10040221] [PMID: 33187336]
[82]
Altuna-Azkargorta M, Mendioroz-Iriarte M. Blood biomarkers in Alzheimer’s disease.Neurol (Engl Ed). 2020.
[http://dx.doi.org/10.1016/j.nrleng.2018.03.006]
[83]
d’Abramo C, D’Adamio L, Giliberto L. Significance of blood and cerebrospinal fluid biomarkers for Alzheimer’s disease: Sensitivity, specificity and potential for clinical use. J Pers Med 2020; 10(3): 116.
[http://dx.doi.org/10.3390/jpm10030116] [PMID: 32911755]
[84]
Manzano S, Agüera L, Aguilar M, Olazarán J. A review on Tramiprosate (homotaurine) in Alzheimer’s disease and other neurocognitive disorders. Front Neurol 2020; 11: 614.
[http://dx.doi.org/10.3389/fneur.2020.00614] [PMID: 32733362]
[85]
Fan Y, Gao Y, Therriault J, Luo J, Ba M, Zhang H. The effects of CSF neurogranin and APOE ε 4 on cognition and neuropathology in mild cognitive impairment and Alzheimer's disease. Front Aging Neurosci 2021; 13: 667899.
[http://dx.doi.org/10.3389/fnagi.2021.667899] [PMID: 33986657]
[86]
Nilsson J, Gobom J, Sjödin S, et al. Cerebrospinal fluid biomarker panel for synaptic dysfunction in Alzheimer’s disease. Alzheimers Dement (Amst) 2021; 13(1): e12179.
[http://dx.doi.org/10.1002/dad2.12179] [PMID: 33969172]
[87]
Cano A, Turowski P, Ettcheto M, et al. Nanomedicine-based technologies and novel biomarkers for the diagnosis and treatment of Alzheimer’s disease: From current to future challenges. J Nanobiotechnology 2021; 19(1): 122.
[http://dx.doi.org/10.1186/s12951-021-00864-x] [PMID: 33926475]
[88]
Jie CVML, Treyer V, Schibli R, Mu L. Tauvid™: The first FDA-approved PET tracer for imaging tau pathology in Alzheimer’s disease. Pharmaceuticals (Basel) 2021; 14(2): 110.
[http://dx.doi.org/10.3390/ph14020110] [PMID: 33573211]
[89]
Bao W, Xie F, Zuo C, Guan Y, Huang YH. PET neuroimaging of Alzheimer’s disease: Radiotracers and their utility in clinical research. Front Aging Neurosci 2021; 13: 624330.
[http://dx.doi.org/10.3389/fnagi.2021.624330] [PMID: 34025386]
[90]
van Waarde A, Marcolini S, de Deyn PP, Dierckx RAJO. PET agents in dementia: An overview. Semin Nucl Med 2021; 51(3): 196-229.
[http://dx.doi.org/10.1053/j.semnuclmed.2020.12.008] [PMID: 33500121]
[91]
West T, Kirmess KM, Meyer MR, et al. A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: Findings from a multi cohort validity analysis. Mol Neurodegener 2021; 16(1): 30.
[http://dx.doi.org/10.1186/s13024-021-00451-6] [PMID: 33933117]
[92]
Russo MJ, Gustafson D, Vázquez S, et al. Creation of the Argentina-Alzheimer’s Disease Neuroimaging Initiative. Alzheimers Dement 2014; 10(1)(Suppl.): S84-7.
[http://dx.doi.org/10.1016/j.jalz.2013.09.015] [PMID: 24864324]
[93]
Hendrix JA, Finger B, Weiner MW, et al. The Worldwide Alzheimer’s Disease Neuroimaging Initiative: An update. Alzheimers Dement 2015; 11(7): 850-9.
[http://dx.doi.org/10.1016/j.jalz.2015.05.008] [PMID: 26194318]
[94]
Leung KK, Bartlett JW, Barnes J, Manning EN, Ourselin S, Fox NC. Cerebral atrophy in mild cognitive impairment and Alzheimer disease: Rates and acceleration. Neurology 2013; 80(7): 648-54.
[http://dx.doi.org/10.1212/WNL.0b013e318281ccd3] [PMID: 23303849]
[95]
Rathore S, Habes M, Iftikhar MA, Shacklett A, Davatzikos C. A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer’s disease and its prodromal stages. Neuroimage 2017; 155: 530-48.
[http://dx.doi.org/10.1016/j.neuroimage.2017.03.057] [PMID: 28414186]
[96]
Guan H, Liu Y, Yang E, Yap PT, Shen D, Liu M. Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification. Med Image Anal 2021; 71: 102076.
[http://dx.doi.org/10.1016/j.media.2021.102076] [PMID: 33930828]
[97]
Nir TM, Jahanshad N, Villalon-Reina JE, et al. Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer’s disease deficits. Magn Reson Med 2017; 78(6): 2322-33.
[http://dx.doi.org/10.1002/mrm.26623] [PMID: 28266059]
[98]
Horgusluoglu-Moloch E, Xiao G, Wang M, et al. Systems modeling of white matter microstructural abnormalities in Alzheimer’s disease. Neuroimage Clin 2020; 26: 102203.
[http://dx.doi.org/10.1016/j.nicl.2020.102203] [PMID: 32062565]
[99]
Bergamino M, Keeling EG, Walsh RR, Stokes AM. Systematic assessment of the impact of DTI methodology on fractional anisotropy measures in Alzheimer’s disease. Tomography 2021; 7(1): 20-38.
[http://dx.doi.org/10.3390/tomography7010003] [PMID: 33681461]
[100]
Márquez F, Yassa MA. Neuroimaging biomarkers for Alzheimer’s disease. Mol Neurodegener 2019; 14(1): 21.
[http://dx.doi.org/10.1186/s13024-019-0325-5] [PMID: 31174557]
[101]
Sheynkman GM, Shortreed MR, Cesnik AJ, Smith LM. Proteogenomics: Integrating next-generation sequencing and mass spectrometry to characterize human proteomic variation. Annu Rev Anal Chem (Palo Alto, Calif) 2016; 9(1): 521-45.
[http://dx.doi.org/10.1146/annurev-anchem-071015-041722] [PMID: 27049631]
[102]
Cui W, Rohrs HW, Gross ML. Top-down mass spectrometry: Recent developments, applications and perspectives. Analyst (Lond) 2011; 136(19): 3854-64.
[http://dx.doi.org/10.1039/c1an15286f] [PMID: 21826297]
[103]
Yates JR III. The revolution and evolution of shotgun proteomics for large-scale proteome analysis. J Am Chem Soc 2013; 135(5): 1629-40.
[http://dx.doi.org/10.1021/ja3094313] [PMID: 23294060]
[104]
Gomes FP, Yates JR III. Recent trends of capillary electrophoresis-mass spectrometry in proteomics research. Mass Spectrom Rev 2019; 38(6): 445-60.
[http://dx.doi.org/10.1002/mas.21599] [PMID: 31407381]
[105]
Raftery D, Ed. Mass Spectrometry in Metabolomics: Methods and Protocols. NY: Springer, Humana Press 2014.
[http://dx.doi.org/10.1007/978-1-4939-1258-2]
[106]
Reddy G, Dalmasso EA. SELDI proteinchip(R) array technology: Protein-based predictive medicine and drug discovery applications. J Biomed Biotechnol 2003; 2003(4): 237-41.
[http://dx.doi.org/10.1155/S1110724303210020] [PMID: 14615631]
[107]
Clarke CH, Bankert McCarthy DL, Eds. SELDI-TOF Mass Spectrometry: Methods and Protocols Series Methods in Molecular Biology. 1st ed. NY: Humana: Springer 2016; p. 818.
[108]
Human Brain Proteome Project (HBPP) In: Human Proteome Organization (HUPO). 2021.Available from: https://www.hupo.org/Human-Brain-Proteome-Project
[109]
Abe K, Shang J, Shi X, et al. A new serum biomarker set to detect mild cognitive impairment and Alzheimer’s disease by peptidome technology. J Alzheimers Dis 2020; 73(1): 217-27.
[http://dx.doi.org/10.3233/JAD-191016] [PMID: 31771070]
[110]
Costerus JM, Brouwer MC, van de Beek D. Technological advances and changing indications for lumbar puncture in neurological disorders. Lancet Neurol 2018; 17(3): 268-78.
[http://dx.doi.org/10.1016/S1474-4422(18)30033-4] [PMID: 29452686]
[111]
Blennow K. Cerebrospinal fluid protein biomarkers for Alzheimer’s disease. NeuroRx 2004; 1(2): 213-25.
[http://dx.doi.org/10.1602/neurorx.1.2.213] [PMID: 15717022]
[112]
Wiltfang J, Esselmann H, Bibl M, et al. 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 2002; 81(3): 481-96.
[http://dx.doi.org/10.1046/j.1471-4159.2002.00818.x] [PMID: 12065657]
[113]
Lewczuk P, Esselmann H, Meyer M, et al. The amyloid-beta (Abeta) peptide pattern in cerebrospinal fluid in Alzheimer’s disease: Evidence of a novel carboxyterminally elongated Abeta peptide. Rapid Commun Mass Spectrom 2003; 17(12): 1291-6.
[http://dx.doi.org/10.1002/rcm.1048] [PMID: 12811752]
[114]
Sunderland T, Linker G, Mirza N, et al. Decreased beta-amyloid1-42 and increased tau levels in cerebrospinal fluid of patients with Alzheimer disease. JAMA 2003; 289(16): 2094-103.
[http://dx.doi.org/10.1001/jama.289.16.2094] [PMID: 12709467]
[115]
Spies PE, Slats D, Sjögren JM, et al. The cerebrospinal fluid amyloid beta42/40 ratio in the differentiation of Alzheimer’s disease from non-Alzheimer’s dementia. Curr Alzheimer Res 2010; 7(5): 470-6.
[http://dx.doi.org/10.2174/156720510791383796] [PMID: 20043812]
[116]
Slaets S, Le Bastard N, Martin JJ, et al. Cerebrospinal fluid Aβ1-40 improves differential dementia diagnosis in patients with intermediate P-tau181P levels. J Alzheimers Dis 2013; 36(4): 759-67.
[http://dx.doi.org/10.3233/JAD-130107] [PMID: 23666174]
[117]
Tariciotti L, Casadei M, Honig LS, et al. Clinical experience with cerebrospinal fluid Aβ42, total and phosphorylated tau in the evaluation of 1,016 individuals for suspected dementia. J Alzheimers Dis 2018; 65(4): 1417-25.
[http://dx.doi.org/10.3233/JAD-180548] [PMID: 30149454]
[118]
Kokkinou M, Beishon LC, Smailagic N, et al. Plasma and cerebrospinal fluid ABeta42 for the differential diagnosis of Alzheimer’s disease dementia in participants diagnosed with any dementia subtype in a specialist care setting. Cochrane Database Syst Rev 2021; 2: CD010945.
[PMID: 33566374]
[119]
Boumenir A, Cognat E, Sabia S, et al. CSF level of β-amyloid peptide predicts mortality in Alzheimer’s disease. Alzheimers Res Ther 2019; 11(1): 29.
[http://dx.doi.org/10.1186/s13195-019-0481-4] [PMID: 30922415]
[120]
Olsson B, Lautner R, Andreasson U, et al. CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: A systematic review and meta-analysis. Lancet Neurol 2016; 15(7): 673-84.
[http://dx.doi.org/10.1016/S1474-4422(16)00070-3] [PMID: 27068280]
[121]
Mattsson N, Zetterberg H, Hansson O, et al. CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA 2009; 302(4): 385-93.
[http://dx.doi.org/10.1001/jama.2009.1064] [PMID: 19622817]
[122]
Kester MI, Teunissen CE, Sutphen C, et al. Cerebrospinal fluid VILIP-1 and YKL-40, candidate biomarkers to diagnose, predict and monitor Alzheimer’s disease in a memory clinic cohort. Alzheimers Res Ther 2015; 7(1): 59.
[http://dx.doi.org/10.1186/s13195-015-0142-1] [PMID: 26383836]
[123]
Babić Leko M, Borovečki F, Dejanović N, Hof PR, Šimić G. Predictive value of cerebrospinal fluid visinin-like protein-1 levels for Alzheimer’s disease early detection and differential diagnosis in patients with mild cognitive impairment. J Alzheimers Dis 2016; 50(3): 765-78.
[http://dx.doi.org/10.3233/JAD-150705] [PMID: 26836160]
[124]
Zhang H, Ng KP, Therriault J, et al. Cerebrospinal fluid phosphorylated tau, visinin-like protein-1, and chitinase-3-like protein 1 in mild cognitive impairment and Alzheimer’s disease. Transl Neurodegener 2018; 7(1): 23.
[http://dx.doi.org/10.1186/s40035-018-0127-7] [PMID: 30311914]
[125]
Dulewicz M. Kulczyńska-Przybik A, Mroczko B. Neurogranin and VILIP-1 as molecular indicators of neurodegeneration in Alzheimer’s disease: A systematic review and meta-analysis. Int J Mol Sci 2020; 21(21): 8335.
[http://dx.doi.org/10.3390/ijms21218335] [PMID: 33172069]
[126]
Narayanan S, Shanker A, Khera T, Subramaniam B. Neurofilament light: A narrative review on biomarker utility. Fac Rev 2021; 10: 46.
[http://dx.doi.org/10.12703/r/10-46] [PMID: 34131656]
[127]
Dhiman K, Gupta VB, Villemagne VL, et al. Cerebrospinal fluid neurofilament light concentration predicts brain atrophy and cognition in Alzheimer’s disease. Alzheimers Dement (Amst) 2020; 12(1): e12005.
[http://dx.doi.org/10.1002/dad2.12005] [PMID: 32211500]
[128]
Brinkmalm A, Brinkmalm G, Honer WG, et al. Targeting synaptic pathology with a novel affinity mass spectrometry approach. Mol Cell Proteomics 2014; 13(10): 2584-92.
[http://dx.doi.org/10.1074/mcp.M114.040113] [PMID: 24973420]
[129]
Brinkmalm A, Brinkmalm G, Honer WG, et al. SNAP-25 is a promising novel cerebrospinal fluid biomarker for synapse degeneration in Alzheimer’s disease. Mol Neurodegener 2014; 9(1): 53.
[http://dx.doi.org/10.1186/1750-1326-9-53] [PMID: 25418885]
[130]
Kvartsberg H, Duits FH, Ingelsson M, et al. Cerebrospinal fluid levels of the synaptic protein neurogranin correlates with cognitive decline in prodromal Alzheimer’s disease. Alzheimers Dement 2015; 11(10): 1180-90.
[http://dx.doi.org/10.1016/j.jalz.2014.10.009] [PMID: 25533203]
[131]
Kvartsberg H, Lashley T, Murray CE, et al. The intact postsynaptic protein neurogranin is reduced in brain tissue from patients with familial and sporadic Alzheimer’s disease. Acta Neuropathol 2019; 137(1): 89-102.
[http://dx.doi.org/10.1007/s00401-018-1910-3] [PMID: 30244311]
[132]
Öhrfelt A, Brinkmalm A, Dumurgier J, et al. The pre-synaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer’s disease. Alzheimers Res Ther 2016; 8(1): 41.
[http://dx.doi.org/10.1186/s13195-016-0208-8] [PMID: 27716408]
[133]
Brosseron F, Krauthausen M, Kummer M, Heneka MT. Body fluid cytokine levels in mild cognitive impairment and Alzheimer’s disease: A comparative overview. Mol Neurobiol 2014; 50(2): 534-44.
[http://dx.doi.org/10.1007/s12035-014-8657-1] [PMID: 24567119]
[134]
Bagyinszky E, Giau VV, Shim K, Suk K, An SSA, Kim S. Role of inflammatory molecules in the Alzheimer’s disease progression and diagnosis. J Neurol Sci 2017; 376: 242-54.
[http://dx.doi.org/10.1016/j.jns.2017.03.031] [PMID: 28431620]
[135]
Shen XN, Niu LD, Wang YJ, et al. Inflammatory markers in Alzheimer’s disease and mild cognitive impairment: A meta-analysis and systematic review of 170 studies. J Neurol Neurosurg Psychiatry 2019; 90(5): 590-8.
[http://dx.doi.org/10.1136/jnnp-2018-319148] [PMID: 30630955]
[136]
Taipa R, das Neves SP, Sousa AL, et al. Proinflammatory and anti-inflammatory cytokines in the CSF of patients with Alzheimer’s disease and their correlation with cognitive decline. Neurobiol Aging 2019; 76: 125-32.
[http://dx.doi.org/10.1016/j.neurobiolaging.2018.12.019] [PMID: 30711675]
[137]
Aksnes M, Aass HCD, Tiiman A, et al. Associations of cerebrospinal fluid amyloidogenic nanoplaques with cytokines in Alzheimer’s disease. Transl Neurodegener 2021; 10(1): 18.
[http://dx.doi.org/10.1186/s40035-021-00244-3] [PMID: 34099032]
[138]
Ismail R, Parbo P, Madsen LS, et al. The relationships between neuroinflammation, beta-amyloid and tau deposition in Alzheimer’s disease: A longitudinal PET study. J Neuroinflammation 2020; 17(1): 151.
[http://dx.doi.org/10.1186/s12974-020-01820-6] [PMID: 32375809]
[139]
Hu WT, Ozturk T, Kollhoff A, et al. Higher CSF sTNFR1-related proteins associate with better prognosis in very early Alzheimer’s disease. Nat Commun 2021; 12(1): 4001.
[http://dx.doi.org/10.1038/s41467-021-24220-7] [PMID: 34183654]
[140]
Ayton S, Faux NG, Bush AI. Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE. Nat Commun 2015; 6(1): 6760.
[http://dx.doi.org/10.1038/ncomms7760] [PMID: 25988319]
[141]
Twohig D, Nielsen HM. α-synuclein in the pathophysiology of Alzheimer’s disease. Mol Neurodegener 2019; 14(1): 23.
[http://dx.doi.org/10.1186/s13024-019-0320-x] [PMID: 31186026]
[142]
Vitale AA, Bernatene EA, Vitale MG, Pomilio AB. New insights of the Fenton reaction using glycerol as experimental model. Effect of O2, inhibition by Mg2+, and oxidation state of Fe. J Phys Chem A 2016; 120(28): 5435-45.
[http://dx.doi.org/10.1021/acs.jpca.6b03805] [PMID: 27340836]
[143]
Liu JL, Fan YG, Yang ZS, Wang ZY, Guo C. Iron and Alzheimer’s disease: From pathogenesis to therapeutic implications. Front Neurosci 2018; 12: 632.
[http://dx.doi.org/10.3389/fnins.2018.00632] [PMID: 30250423]
[144]
Viktorinova A, Durfinova M. Mini-Review: Is iron-mediated cell death (ferroptosis) an identical factor contributing to the pathogenesis of some neurodegenerative diseases? Neurosci Lett 2021; 745: 135627.
[http://dx.doi.org/10.1016/j.neulet.2021.135627] [PMID: 33440237]
[145]
You P, Li X, Wang Z, Wang H, Dong B, Li Q. Characterization of brain iron deposition pattern and its association with genetic risk factor in Alzheimer’s disease using susceptibility-weighted imaging. Front Hum Neurosci 2021; 15: 654381.
[http://dx.doi.org/10.3389/fnhum.2021.654381] [PMID: 34163341]
[146]
Jack CR Jr, Bennett DA, Blennow K, et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology 2016; 87(5): 539-47.
[http://dx.doi.org/10.1212/WNL.0000000000002923] [PMID: 27371494]
[147]
Vigo-Pelfrey C, Lee D, Keim P, Lieberburg I, Schenk DB. Characterization of β-amyloid peptide from human cerebrospinal fluid. J Neurochem 1993; 61(5): 1965-8.
[http://dx.doi.org/10.1111/j.1471-4159.1993.tb09841.x] [PMID: 8229004]
[148]
Sergeant N, Bombois S, Ghestem A, et al. Truncated beta-amyloid peptide species in pre-clinical Alzheimer’s disease as new targets for the vaccination approach. J Neurochem 2003; 85(6): 1581-91.
[http://dx.doi.org/10.1046/j.1471-4159.2003.01818.x] [PMID: 12787077]
[149]
Portelius E, Gustavsson MK, Zetterberg H, Andreasson U, Blennow K. Evaluation of the performance of novel Aβ isoforms as theragnostic markers in Alzheimer’s disease: From the cell to the patient. Neurodegener Dis 2012; 10(1-4): 138-40.
[http://dx.doi.org/10.1159/000334537] [PMID: 22302034]
[150]
Halim A, Brinkmalm G, Rüetschi U, et al. Site-specific characterization of threonine, serine, and tyrosine glycosylations of amyloid precursor protein/amyloid beta-peptides in human cerebrospinal fluid. Proc Natl Acad Sci USA 2011; 108(29): 11848-53.
[http://dx.doi.org/10.1073/pnas.1102664108] [PMID: 21712440]
[151]
Brinkmalm G, Portelius E, Öhrfelt A, et al. An online nano-LC-ESI-FTICR-MS method for comprehensive characterization of endogenous fragments from amyloid β and amyloid precursor protein in human and cat cerebrospinal fluid. J Mass Spectrom 2012; 47(5): 591-603.
[http://dx.doi.org/10.1002/jms.2987] [PMID: 22576872]
[152]
Brinkmalm G, Hong W, Wang Z, et al. Identification of neurotoxic cross-linked amyloid-β dimers in the Alzheimer’s brain. Brain 2019; 142(5): 1441-57.
[http://dx.doi.org/10.1093/brain/awz066] [PMID: 31032851]
[153]
Wang Z, Jackson RJ, Hong W, et al. Human brain-derived Abeta oligomers bind to synapses and disrupt synaptic activity in a manner that requires APP. J Neurosci 2017; 37(49): 11947-66.
[http://dx.doi.org/10.1523/JNEUROSCI.2009-17.2017] [PMID: 29101243]
[154]
Anni D, Weiss EM, Guhathakurta D, et al. Aβ1-16 controls synaptic vesicle pools at excitatory synapses via cholinergic modulation of synapsin phosphorylation. Cell Mol Life Sci 2021; 78(11): 4973-92.
[http://dx.doi.org/10.1007/s00018-021-03835-5] [PMID: 33864480]
[155]
Hong W, Wang Z, Liu W, et al. Diffusible, highly bioactive oligomers represent a critical minority of soluble Aβ in Alzheimer’s disease brain. Acta Neuropathol 2018; 136(1): 19-40.
[http://dx.doi.org/10.1007/s00401-018-1846-7] [PMID: 29687257]
[156]
Tolar M, Hey J, Power A, Abushakra S. Neurotoxic soluble amyloid oligomers drive Alzheimer’s pathogenesis and represent a clinically validated target for slowing disease progression. Int J Mol Sci 2021; 22(12): 6355.
[http://dx.doi.org/10.3390/ijms22126355] [PMID: 34198582]
[157]
Mullard A. Landmark Alzheimer’s drug approval confounds research community. Nature 2021; 594(7863): 309-10.
[http://dx.doi.org/10.1038/d41586-021-01546-2] [PMID: 34103732]
[158]
Hansson O, Zetterberg H, Buchhave P, Londos E, Blennow K, Minthon L. Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: A follow-up study. Lancet Neurol 2006; 5(3): 228-34.
[http://dx.doi.org/10.1016/S1474-4422(06)70355-6] [PMID: 16488378]
[159]
McKhann GM, Knopman DS, Chertkow H, et al. 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 2011; 7(3): 263-9.
[http://dx.doi.org/10.1016/j.jalz.2011.03.005] [PMID: 21514250]
[160]
Wilson H, Pagano G, Politis M. Dementia spectrum disorders: Lessons learnt from decades with PET research. J Neural Transm (Vienna) 2019; 126(3): 233-51.
[http://dx.doi.org/10.1007/s00702-019-01975-4] [PMID: 30762136]
[161]
Therriault J, Benedet AL, Pascoal TA, et al. Determining Amyloid-β positivity using (18)F-AZD4694 PET imaging. J Nucl Med 2021; 62(2): 247-52.
[http://dx.doi.org/10.2967/jnumed.120.245209] [PMID: 32737243]
[162]
Jagust WJ, Landau SM. Temporal dynamics of β-amyloid accumulation in aging and Alzheimer disease. Neurology 2021; 96(9): e1347-57.
[http://dx.doi.org/10.1212/WNL.0000000000011524] [PMID: 33408147]
[163]
Sanchez JS, Becker JA, Jacobs HIL, et al. The cortical origin and initial spread of medial temporal tauopathy in Alzheimer’s disease assessed with positron emission tomography. Sci Transl Med 2021; 13(577): eabc0655.
[http://dx.doi.org/10.1126/scitranslmed.abc0655] [PMID: 33472953]
[164]
Tagai K, Ono M, Kubota M, et al. High-contrast in vivo imaging of tau pathologies in Alzheimer’s and non-Alzheimer’s disease tauopathies. Neuron 2021; 109(1): 42-58.e8.
[http://dx.doi.org/10.1016/j.neuron.2020.09.042] [PMID: 33125873]
[165]
Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol 2004; 55(3): 306-19.
[http://dx.doi.org/10.1002/ana.20009] [PMID: 14991808]
[166]
O’Brien JT, Herholz K. Amyloid imaging for dementia in clinical practice. BMC Med 2015; 13(1): 163.
[http://dx.doi.org/10.1186/s12916-015-0404-6] [PMID: 26170121]
[167]
Mantel E, Williams J. An introduction to newer PET diagnostic agents and related therapeutic radiopharmaceuticals. J Nucl Med Technol 2019; 47(3): 203-9.
[http://dx.doi.org/10.2967/jnmt.118.224022] [PMID: 31019034]
[168]
Cho SH, Choe YS, Park S, et al. Appropriate reference region selection of 18F-florbetaben and 18F-flutemetamol beta-amyloid PET expressed in Centiloid. Sci Rep 2020; 10(1): 14950.
[http://dx.doi.org/10.1038/s41598-020-70978-z] [PMID: 32917930]
[169]
Boccardi M, Altomare D, Ferrari C, et al. Assessment of the incremental diagnostic value of florbetapir F18 imaging in patients with cognitive impairment: The incremental diagnostic value of amyloid PET with [(18)F]-Florbetapir (INDIA-FBP) study. JAMA Neurol 2016; 73(12): 1417-24.
[http://dx.doi.org/10.1001/jamaneurol.2016.3751] [PMID: 27802513]
[170]
Schwarz AJ, Yu P, Miller BB, et al. Regional profiles of the candidate tau PET ligand 18F-AV-1451 recapitulate key features of Braak histopathological stages. Brain 2016; 139(Pt 5): 1539-50.
[http://dx.doi.org/10.1093/brain/aww023] [PMID: 26936940]
[171]
Wolters EE, Ossenkoppele R, Verfaillie SCJ, et al. Regional [18F]flortaucipir PET is more closely associated with disease severity than CSF p-tau in Alzheimer’s disease. Eur J Nucl Med Mol Imaging 2020; 47(12): 2866-78.
[http://dx.doi.org/10.1007/s00259-020-04758-2] [PMID: 32291510]
[172]
Ricci M, Cimini A, Camedda R, Chiaravalloti A, Schillaci O. Tau biomarkers in dementia: Positron Emission Tomography radiopharmaceuticals in tauopathy assessment and future perspective. Int J Mol Sci 2021; 22(23): 13002.
[http://dx.doi.org/10.3390/ijms222313002] [PMID: 34884804]
[173]
FDA (US Food and Drug Administration). FDA approves first drug to image tau pathology in patients being evaluated for Alzheimer’s disease. FDA NEWS Release Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-first-drug-image-tau-pathology-patients-being-evaluated-alzheimers-disease Accessed on May 28 2020
[174]
Mosconi L. Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging 2005; 32(4): 486-510.
[http://dx.doi.org/10.1007/s00259-005-1762-7] [PMID: 15747152]
[175]
Altomare D, Ferrari C, Caroli A, et al. Prognostic value of Alzheimer’s biomarkers in mild cognitive impairment: The effect of age at onset. J Neurol 2019; 266(10): 2535-45.
[http://dx.doi.org/10.1007/s00415-019-09441-7] [PMID: 31267207]
[176]
Sanchez-Catasus CA, Stormezand GN, van Laar PJ, De Deyn PP, Sanchez MA, Dierckx RA. FDG-PET for prediction of AD dementia in mild cognitive impairment. A review of the state of the art with particular emphasis on the comparison with other neuroimaging modalities (MRI and Perfusion SPECT). Curr Alzheimer Res 2017; 14(2): 127-42.
[http://dx.doi.org/10.2174/1567205013666160629081956] [PMID: 27357645]
[177]
Ou YN, Xu W, Li JQ, et al. FDG-PET as an independent biomarker for Alzheimer’s biological diagnosis: A longitudinal study. Alzheimers Res Ther 2019; 11(1): 57.
[http://dx.doi.org/10.1186/s13195-019-0512-1] [PMID: 31253185]
[178]
Kyrtata N, Emsley HCA, Sparasci O, Parkes LM, Dickie BR. A systematic review of glucose transport alterations in Alzheimer’s disease. Front Neurosci 2021; 15: 626636.
[http://dx.doi.org/10.3389/fnins.2021.626636] [PMID: 34093108]
[179]
Jung ME. A Protective role of translocator protein in Alzheimer’s disease brain. Curr Alzheimer Res 2020; 17(1): 3-15.
[http://dx.doi.org/10.2174/1567205017666200217105950] [PMID: 32065102]
[180]
Kreisl WC, Lyoo CH, Liow JS, et al. (11)C-PBR28 binding to translocator protein increases with progression of Alzheimer’s disease. Neurobiol Aging 2016; 44: 53-61.
[http://dx.doi.org/10.1016/j.neurobiolaging.2016.04.011] [PMID: 27318133]
[181]
Kreisl WC, Kim MJ, Coughlin JM, Henter ID, Owen DR, Innis RB. PET imaging of neuroinflammation in neurological disorders. Lancet Neurol 2020; 19(11): 940-50.
[http://dx.doi.org/10.1016/S1474-4422(20)30346-X] [PMID: 33098803]
[182]
Alam MM, Lee J, Lee SY. Recent progress in the development of TSPO PET ligands for neuroinflammation imaging in neurological diseases. Nucl Med Mol Imaging 2017; 51(4): 283-96.
[http://dx.doi.org/10.1007/s13139-017-0475-8] [PMID: 29242722]
[183]
Lagarde J, Sarazin M, Bottlaender M. In vivo PET imaging of neuroinflammation in Alzheimer’s disease. J Neural Transm (Vienna) 2018; 125(5): 847-67.
[http://dx.doi.org/10.1007/s00702-017-1731-x] [PMID: 28516240]
[184]
Zhang L, Hu K, Shao T, et al. Recent developments on PET radiotracers for TSPO and their applications in neuroimaging. Acta Pharm Sin B 2021; 11(2): 373-93.
[http://dx.doi.org/10.1016/j.apsb.2020.08.006] [PMID: 33643818]
[185]
Fiorenza D, Nicolai E, Cavaliere C, Fiorino F, Esposito G, Salvatore M. Fully automated synthesis of novel TSPO PET imaging ligand [(18)F]Fluoroethyltemazepam. Molecules 2021; 26(8): 2372.
[http://dx.doi.org/10.3390/molecules26082372] [PMID: 33921765]
[186]
Carter SF, Schöll M, Almkvist O, et al. Evidence for astrocytosis in prodromal Alzheimer disease provided by 11C-deuterium-L-deprenyl: A multitracer PET paradigm combining 11C-Pittsburgh compound B and 18F-FDG. J Nucl Med 2012; 53(1): 37-46.
[http://dx.doi.org/10.2967/jnumed.110.087031] [PMID: 22213821]
[187]
Kumar A, Koistinen NA, Malarte ML, et al. Astroglial tracer BU99008 detects multiple binding sites in Alzheimer’s disease brain. Mol Psychiatry 2021; 26(10): 5833-47.
[http://dx.doi.org/10.1038/s41380-021-01101-5] [PMID: 33888872]
[188]
Wang C, Schroeder FA, Wey HY, et al. In vivo imaging of histone deacetylases (HDACs) in the central nervous system and major peripheral organs. J Med Chem 2014; 57(19): 7999-8009.
[http://dx.doi.org/10.1021/jm500872p] [PMID: 25203558]
[189]
Wey HY, Gilbert TM, Zürcher NR, et al. Insights into neuroepigenetics through human histone deacetylase PET imaging. Sci Transl Med 2016; 8(351): 351ra106.
[http://dx.doi.org/10.1126/scitranslmed.aaf7551] [PMID: 27510902]
[190]
Tago T, Toyohara J. Advances in the development of PET Ligands targeting histone deacetylases for the assessment of neurodegenerative diseases. Molecules 2018; 23(2): 300.
[http://dx.doi.org/10.3390/molecules23020300] [PMID: 29385079]
[191]
Koole M, Van Weehaeghe D, Serdons K, et al. Clinical validation of the novel HDAC6 radiotracer [18F]EKZ-001 in the human brain. Eur J Nucl Med Mol Imaging 2021; 48(2): 596-611.
[http://dx.doi.org/10.1007/s00259-020-04891-y] [PMID: 32638097]
[192]
Aghourian M, Legault-Denis C, Soucy JP, et al. Quantification of brain cholinergic denervation in Alzheimer’s disease using PET imaging with [18F]-FEOBV. Mol Psychiatry 2017; 22(11): 1531-8.
[http://dx.doi.org/10.1038/mp.2017.183] [PMID: 28894304]
[193]
Coughlin JM, Rubin LH, Du Y, et al. High availability of the α(7)-nicotinic acetylcholine receptor in brains of individuals with mild cognitive impairment: A pilot study using (18)F-ASEM PET. J Nucl Med 2020; 61(3): 423-6.
[http://dx.doi.org/10.2967/jnumed.119.230979] [PMID: 31420499]
[194]
Kendziorra K, Wolf H, Meyer PM, et al. Decreased cerebral α4β2* nicotinic acetylcholine receptor availability in patients with mild cognitive impairment and Alzheimer’s disease assessed with positron emission tomography. Eur J Nucl Med Mol Imaging 2011; 38(3): 515-25.
[http://dx.doi.org/10.1007/s00259-010-1644-5] [PMID: 21069319]
[195]
Sabri O, Meyer PM, Gräf S, et al. Cognitive correlates of α4β2 nicotinic acetylcholine receptors in mild Alzheimer’s dementia. Brain 2018; 141(6): 1840-54.
[http://dx.doi.org/10.1093/brain/awy099] [PMID: 29672680]
[196]
Wong DF, Kuwabara H, Horti AG, et al. Brain PET imaging of α7-nAChR with [(18)F]ASEM: Reproducibility, occupancy, receptor density, and changes in schizophrenia. Int J Neuropsychopharmacol 2018; 21(7): 656-67.
[http://dx.doi.org/10.1093/ijnp/pyy021] [PMID: 29522184]
[197]
Masdeu J, Pascual B, Zanotti-Fregonara P, et al. [(11)C]MK-6884 PET tracer for M4 muscarinic cholinergic receptors in Alzheimer’s disease: Comparison with [(18)F]FDG PET. Neurology 2020; 94: 2640.
[198]
Pain CD, O’Keefe GJ, Ackermann U, Dore V, Villemagne VL, Rowe CC. Human biodistribution and internal dosimetry of 4-[ 18F]fluorobenzyl-dexetimide: A PET radiopharmaceutical for imaging muscarinic acetylcholine receptors in the brain and heart. EJNMMI Res 2020; 10(1): 61.
[http://dx.doi.org/10.1186/s13550-020-00641-1] [PMID: 32533449]
[199]
Scarpa M, Hesse S, Bradley SJ. M1 muscarinic acetylcholine receptors: A therapeutic strategy for symptomatic and disease-modifying effects in Alzheimer’s disease? Adv Pharmacol 2020; 88: 277-310.
[http://dx.doi.org/10.1016/bs.apha.2019.12.003] [PMID: 32416870]
[200]
Tong L, Li W, Lo MM, et al. Discovery of [(11)C]MK-6884: A positron emission tomography (PET) imaging agent for the study of M4 muscarinic receptor positive allosteric modulators (PAMs) in neurodegenerative diseases. J Med Chem 2020; 63(5): 2411-25.
[http://dx.doi.org/10.1021/acs.jmedchem.9b01406] [PMID: 32101422]
[201]
Naganawa M, Nabulsi N, Henry S, et al. First-in-human assessment of (11)C-LSN3172176, an M1 muscarinic acetylcholine receptor PET radiotracer. J Nucl Med 2021; 62(4): 553-60.
[http://dx.doi.org/10.2967/jnumed.120.246967] [PMID: 32859711]
[202]
Stavrakov G, Philipova I, Lukarski A, et al. Discovery of a novel acetylcholinesterase inhibitor by fragment-based design and virtual screening. Molecules 2021; 26(7): 2058.
[http://dx.doi.org/10.3390/molecules26072058] [PMID: 33916760]
[203]
Tiepolt S, Becker GA, Wilke S, et al. (+)-[18F]Flubatine as a novel α4β2 nicotinic acetylcholine receptor PET ligand-results of the first-in-human brain imaging application in patients with β-amyloid PET-confirmed Alzheimer’s disease and healthy controls. Eur J Nucl Med Mol Imaging 2021; 48(3): 731-46.
[http://dx.doi.org/10.1007/s00259-020-05029-w] [PMID: 32935187]
[204]
Moss DE. Improving anti-neurodegenerative benefits of acetylcholinesterase inhibitors in Alzheimer’s disease: Are irreversible inhibitors the future? Int J Mol Sci 2020; 21(10): 3438.
[http://dx.doi.org/10.3390/ijms21103438] [PMID: 32414155]
[205]
Yegla B, Joshi S, Strupp J, Parikh V. Dynamic interplay of frontoparietal cholinergic innervation and cortical reorganization in the regulation of attentional capacities in aging. Neurobiol Aging 2021; 105: 186-98.
[http://dx.doi.org/10.1016/j.neurobiolaging.2021.04.027] [PMID: 34102380]
[206]
Heurling K, Ashton NJ, Leuzy A, et al. Synaptic vesicle protein 2A as a potential biomarker in synaptopathies. Mol Cell Neurosci 2019; 97: 34-42.
[http://dx.doi.org/10.1016/j.mcn.2019.02.001] [PMID: 30796959]
[207]
Bastin C, Bahri MA, Meyer F, et al. In vivo imaging of synaptic loss in Alzheimer’s disease with [18F]UCB-H positron emission tomography. Eur J Nucl Med Mol Imaging 2020; 47(2): 390-402.
[http://dx.doi.org/10.1007/s00259-019-04461-x] [PMID: 31468182]
[208]
Cai Z, Drake L, Naganawa M, et al. First-in-human study of [(18)F]SynVesT-2, a novel SV2A radioligand with fast kinetics and high specific binding signals. J Nucl Med 2020; 61: 462.
[209]
Vanhaute H, Ceccarini J, Michiels L, et al. In vivo synaptic density loss is related to tau deposition in amnestic mild cognitive impairment. Neurology 2020; 95(5): e545-53.
[http://dx.doi.org/10.1212/WNL.0000000000009818] [PMID: 32493717]
[210]
Naganawa M, Li S, Nabulsi N, et al. First-in-human evaluation of (18)F-SynVesT-1, a novel radioligand for PET imaging of synaptic vesicle protein 2A. J Nucl Med 2021; 62(4): 561-7.
[http://dx.doi.org/10.2967/jnumed.120.249144] [PMID: 32859701]
[211]
Janelidze S, Stomrud E, Palmqvist S, et al. Plasma β-amyloid in Alzheimer’s disease and vascular disease. Sci Rep 2016; 6(1): 26801.
[http://dx.doi.org/10.1038/srep26801] [PMID: 27241045]
[212]
Palmqvist S, Janelidze S, Stomrud E, et al. Performance of fully automated plasma assays as screening tests for Alzheimer disease-related β-amyloid status. JAMA Neurol 2019; 76(9): 1060-9.
[http://dx.doi.org/10.1001/jamaneurol.2019.1632] [PMID: 31233127]
[213]
Ashton NJ, Suárez-Calvet M, Karikari TK, et al. Effects of pre-analytical procedures on blood biomarkers for Alzheimer’s pathophysiology, glial activation, and neurodegeneration. Alzheimers Dement (Amst) 2021; 13(1): e12168.
[http://dx.doi.org/10.1002/dad2.12168] [PMID: 34124336]
[214]
Hugon J, Mouton-Liger F, Cognat E, Dumurgier J, Paquet C. Blood-based kinase assessments in Alzheimer’s disease. Front Aging Neurosci 2018; 10: 338.
[http://dx.doi.org/10.3389/fnagi.2018.00338] [PMID: 30487744]
[215]
Dowjat K, Adayev T, Wojda U, et al. Abnormalities of DYRK1A-cytoskeleton complexes in the blood cells as potential biomarkers of Alzheimer’s disease. J Alzheimers Dis 2019; 72(4): 1059-75.
[http://dx.doi.org/10.3233/JAD-190475] [PMID: 31683476]
[216]
Fossati S, Ramos Cejudo J, Debure L, et al. Plasma tau complements CSF tau and P-tau in the diagnosis of Alzheimer’s disease. Alzheimers Dement (Amst) 2019; 11(1): 483-92.
[http://dx.doi.org/10.1016/j.dadm.2019.05.001] [PMID: 31334328]
[217]
Karikari TK, Pascoal TA, Ashton NJ, et al. Blood phosphorylated tau 181 as a biomarker for Alzheimer’s disease: A diagnostic performance and prediction modelling study using data from four prospective cohorts. Lancet Neurol 2020; 19(5): 422-33.
[http://dx.doi.org/10.1016/S1474-4422(20)30071-5] [PMID: 32333900]
[218]
Lewczuk P, Ermann N, Andreasson U, et al. Plasma neurofilament light as a potential biomarker of neurodegeneration in Alzheimer’s disease. Alzheimers Res Ther 2018; 10(1): 71.
[http://dx.doi.org/10.1186/s13195-018-0404-9] [PMID: 30055655]
[219]
Forgrave LM, Ma M, Best JR, DeMarco ML. The diagnostic performance of neurofilament light chain in CSF and blood for Alzheimer’s disease, frontotemporal dementia, and amyotrophic lateral sclerosis: A systematic review and meta-analysis. Alzheimers Dement (Amst) 2019; 11(1): 730-43.
[http://dx.doi.org/10.1016/j.dadm.2019.08.009] [PMID: 31909174]
[220]
Zou K, Abdullah M, Michikawa M. Current biomarkers for Alzheimer’s disease: From CSF to blood. J Pers Med 2020; 10(3): 85.
[http://dx.doi.org/10.3390/jpm10030085] [PMID: 32806668]
[221]
Vishnu VY, Modi M, Sharma S, et al. Role of plasma clusterin in Alzheimer’s disease-a pilot study in a tertiary hospital in northern India. PLoS One 2016; 11(11): e0166369.
[http://dx.doi.org/10.1371/journal.pone.0166369] [PMID: 27861589]
[222]
Hye A, Lynham S, Thambisetty M, et al. Proteome-based plasma biomarkers for Alzheimer’s disease. Brain 2006; 129(Pt 11): 3042-50.
[http://dx.doi.org/10.1093/brain/awl279] [PMID: 17071923]
[223]
Ray S, Britschgi M, Herbert C, et al. Classification and prediction of clinical Alzheimer’s diagnosis based on plasma signaling proteins. Nat Med 2007; 13(11): 1359-62.
[http://dx.doi.org/10.1038/nm1653] [PMID: 17934472]
[224]
Hye A, Riddoch-Contreras J, Baird AL, et al. Plasma proteins predict conversion to dementia from prodromal disease. Alzheimers Dement 2014; 10(6): 799-807.e2.
[http://dx.doi.org/10.1016/j.jalz.2014.05.1749] [PMID: 25012867]
[225]
Mapstone M, Cheema AK, Fiandaca MS, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med 2014; 20(4): 415-8.
[http://dx.doi.org/10.1038/nm.3466] [PMID: 24608097]
[226]
Varma VR, Oommen AM, Varma S, et al. Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study. PLoS Med 2018; 15(1): e1002482.
[http://dx.doi.org/10.1371/journal.pmed.1002482] [PMID: 29370177]
[227]
Thambisetty M, Hye A, Foy C, et al. Proteome-based identification of plasma proteins associated with hippocampal metabolism in early Alzheimer’s disease. J Neurol 2008; 255(11): 1712-20.
[http://dx.doi.org/10.1007/s00415-008-0006-8] [PMID: 19156487]
[228]
Fonseca MI, McGuire SO, Counts SE, Tenner AJ. Complement activation fragment C5a receptors, CD88 and C5L2, are associated with neurofibrillary pathology. J Neuroinflammation 2013; 10(1): 25.
[http://dx.doi.org/10.1186/1742-2094-10-25] [PMID: 23394121]
[229]
Carpanini SM, Torvell M, Morgan BP. Therapeutic inhibition of the complement system in diseases of the central nervous system. Front Immunol 2019; 10: 362.
[http://dx.doi.org/10.3389/fimmu.2019.00362] [PMID: 30886620]
[230]
Pietronigro EC, Della Bianca V, Zenaro E, Constantin G. NETosis in Alzheimer’s disease. Front Immunol 2017; 8: 211.
[http://dx.doi.org/10.3389/fimmu.2017.00211] [PMID: 28303140]
[231]
Zhang M, Han W, Xu Y, Li D, Xue Q. Serum miR-128 serves as a potential diagnostic biomarker for Alzheimer’s disease. Neuropsychiatr Dis Treat 2021; 17: 269-75.
[http://dx.doi.org/10.2147/NDT.S290925] [PMID: 33542630]
[232]
Taylor NP. FDA awards breakthrough status to blood test for Alzheimer’s risk. Medtechdive Available from: https://www.medtechdive.com/news/fda-awards-breakthrough-status-to-blood-test-for-alzheimers-risk/547198/ Accessed on 30 July 2021
[233]
The PrecivityAD(TM). Test: Advanced Diagnostics in Alzheimer’s Disease 2020.Available from: www.PrecivityAD.com Accessed on 30 July 2021
[234]
Kirmess KM, Meyer MR, Holubasch MS, et al. The PrecivityAD™ test: Accurate and reliable LC-MS/MS assays for quantifying plasma amyloid beta 40 and 42 and apolipoprotein E proteotype for the assessment of brain amyloidosis. Clin Chim Acta 2021; 519: 267-75.
[http://dx.doi.org/10.1016/j.cca.2021.05.011] [PMID: 34015303]
[235]
Practical Neurology FDA grants breakthrough device designation for Alzheimer’s disease screening test Available from: http://v2.practicalneurology.com/news/?id=53504&center=43 Accessed on July 30, 2021
[236]
Thijssen EH, Rabinovici GD. Rapid progress toward reliable blood tests for Alzheimer Disease. JAMA Neurol 2021; 78(2): 143-5.
[http://dx.doi.org/10.1001/jamaneurol.2020.4200] [PMID: 33165524]
[237]
Kitamura Y, Usami R, Ichihara S, et al. Plasma protein profiling for potential biomarkers in the early diagnosis of Alzheimer’s disease. Neurol Res 2017; 39(3): 231-8.
[http://dx.doi.org/10.1080/01616412.2017.1281195] [PMID: 28107809]
[238]
Güntert A, Campbell J, Saleem M, et al. Plasma gelsolin is decreased and correlates with rate of decline in Alzheimer’s disease. J Alzheimers Dis 2010; 21(2): 585-96.
[http://dx.doi.org/10.3233/JAD-2010-100279] [PMID: 20571216]
[239]
Thambisetty M, Simmons A, Velayudhan L, et al. Association of plasma clusterin concentration with severity, pathology, and progression in Alzheimer disease. Arch Gen Psychiatry 2010; 67(7): 739-48.
[http://dx.doi.org/10.1001/archgenpsychiatry.2010.78] [PMID: 20603455]
[240]
Park JK, Lee KJ, Kim JY, Kim H. The association of blood-based inflammatory factors IL-1β TGF-β and CRP with cognitive function in Alzheimer’s disease and mild cognitive impairment. Psychiatry Investig 2021; 18(1): 11-8.
[http://dx.doi.org/10.30773/pi.2020.0205] [PMID: 33561929]
[241]
Estrada LD, Oliveira-Cruz L, Cabrera D. Transforming growth factor beta type I role in neurodegeneration: Implications for Alzheimer’s disease. Curr Protein Pept Sci 2018; 19(12): 1180-8.
[http://dx.doi.org/10.2174/1389203719666171129094937] [PMID: 29189146]
[242]
Nakamura A, Kaneko N, Villemagne VL, et al. High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature 2018; 554(7691): 249-54.
[http://dx.doi.org/10.1038/nature25456] [PMID: 29420472]
[243]
Ridler C. Alzheimer disease: Blood amyloid-β successfully signals AD. Nat Rev Neurol 2018; 14(4): 195.
[http://dx.doi.org/10.1038/nrneurol.2018.19] [PMID: 29449699]
[244]
Pekov SI, Ivanov DG, Bugrova AE, et al. Evaluation of MALDI-TOF/TOF mass spectrometry approach for quantitative determination of aspartate residue isomerization in the amyloid-β peptide. J Am Soc Mass Spectrom 2019; 30(7): 1325-9.
[http://dx.doi.org/10.1007/s13361-019-02199-2] [PMID: 31073890]
[245]
Araki Y, Nonaka D, Hamamura K, et al. Clinical peptidomic analysis by a one-step direct transfer technology: Its potential utility for monitoring of pathophysiological status in female reproductive system disorders. J Obstet Gynaecol Res 2013; 39(10): 1440-8.
[http://dx.doi.org/10.1111/jog.12140] [PMID: 24033768]
[246]
Tanaka K, Tsugawa N, Kim YO, Sanuki N, Takeda U, Lee LJ. A new rapid and comprehensive peptidome analysis by one-step direct transfer technology for 1-D electrophoresis/MALDI mass spectrometry. Biochem Biophys Res Commun 2009; 379(1): 110-4.
[http://dx.doi.org/10.1016/j.bbrc.2008.12.016] [PMID: 19073144]
[247]
Le HTN, Park J, Cho S. A probeless capacitive biosensor for direct detection of amyloid beta 1-42 in human serum based on an interdigitated chain-shaped electrode. Micromachines (Basel) 2020; 11(9): 791.
[http://dx.doi.org/10.3390/mi11090791] [PMID: 32825726]
[248]
Syaifullah AH, Shiino A, Kitahara H, Ito R, Ishida M, Tanigaki K. Machine learning for diagnosis of AD and prediction of MCI progression from brain MRI using brain anatomical analysis using Diffeomorphic Deformation. Front Neurol 2021; 11: 576029.
[http://dx.doi.org/10.3389/fneur.2020.576029] [PMID: 33613411]
[249]
Shan G, Bernick C, Caldwell JZK, Ritter A. Machine learning methods to predict amyloid positivity using domain scores from cognitive tests. Sci Rep 2021; 11(1): 4822.
[http://dx.doi.org/10.1038/s41598-021-83911-9] [PMID: 33649452]
[250]
Bellomo G, Indaco A, Chiasserini D, et al. Machine learning driven profiling of cerebrospinal fluid core biomarkers in Alzheimer’s disease and other neurological disorders. Front Neurosci 2021; 15: 647783.
[http://dx.doi.org/10.3389/fnins.2021.647783] [PMID: 33867925]
[251]
Watson LS, Hamlett ED, Stone TD, Sims-Robinson C. Neuronally derived extracellular vesicles: An emerging tool for understanding Alzheimer’s disease. Mol Neurodegener 2019; 14(1): 22.
[http://dx.doi.org/10.1186/s13024-019-0317-5] [PMID: 31182115]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy