CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease.
Alzheimer's disease
biomarkers
cerebrospinal fluid
hippocampal volume
neurodegeneration markers
neurofilament light
neurogranin
pathophysiology
proteomics
Journal
Alzheimer's & dementia : the journal of the Alzheimer's Association
ISSN: 1552-5279
Titre abrégé: Alzheimers Dement
Pays: United States
ID NLM: 101231978
Informations de publication
Date de publication:
06 Jul 2024
06 Jul 2024
Historique:
revised:
05
06
2024
received:
03
04
2024
accepted:
06
06
2024
medline:
6
7
2024
pubmed:
6
7
2024
entrez:
6
7
2024
Statut:
aheadofprint
Résumé
We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : ZonMw (Memorabel program)
ID : 733050502
Organisme : ZonMw (Memorabel program)
ID : 7330505021
Organisme : anonymous foundation
Organisme : EMIF-AD MBD
Informations de copyright
© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.
Références
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):535‐562.
Mielke MM, Syrjanen JA, Blennow K, et al. Comparison of variables associated with cerebrospinal fluid neurofilament, total‐tau, and neurogranin. Alzheimers Dement. 2019;15(11):1437‐1447.
Wang Z, Yang J, Zhu W, Tang Y, Jia J. The synaptic marker neurogranin as a disease state biomarker in Alzheimer's disease: a systematic review and meta‐analysis. Int J Neurosci. 2021:1‐9.
Nilsson J, Cousins KAQ, Gobom J, et al. Cerebrospinal fluid biomarker panel of synaptic dysfunction in Alzheimer's disease and other neurodegenerative disorders. Alzheimer Dement. 2023;19(5):1775‐1784.
Portelius E, Olsson B, Höglund K, et al. Cerebrospinal fluid neurogranin concentration in neurodegeneration: relation to clinical phenotypes and neuropathology. Acta Neuropathol. 2018;136(3):363‐376.
Giacomucci G, Mazzeo S, Bagnoli S, et al. Plasma neurofilament light chain as a biomarker of Alzheimer's disease in Subjective Cognitive Decline and Mild Cognitive Impairment. J Neurol. 2022;269(8):4270‐4280.
Xiong YL, Meng T, Luo J, Zhang H. The potential of neurofilament light as a biomarker in Alzheimer's disease. Eur Neurol. 2021;84(1):6‐15.
Schuff N, Woerner N, Boreta L, et al. MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers. Brain. 2009;132(Pt 4):1067‐1077.
Jahn H. Memory loss in Alzheimer's disease. Dialogues Clin Neurosci. 2013;15(4):445‐454.
Mattsson N, Insel PS, Palmqvist S, et al. Cerebrospinal fluid tau, neurogranin, and neurofilament light in Alzheimer's disease. EMBO Mol Med. 2016;8(10):1184‐1196.
Bucci M, Chiotis K, Nordberg A. Alzheimer's Disease Neuroimaging I. Alzheimer's disease profiled by fluid and imaging markers: tau PET best predicts cognitive decline. Mol Psychiatry. 2021;26(10):5888‐5898.
Boerwinkle AH, Wisch JK, Chen CD, et al. Temporal correlation of CSF and neuroimaging in the amyloid‐tau‐neurodegeneration model of Alzheimer disease. Neurology. 2021;97(1):e76‐e87.
Noor Z, Ahn SB, Baker MS, Ranganathan S, Mohamedali A. Mass spectrometry‐based protein identification in proteomics‐a review. Brief Bioinform. 2021;22(2):1620‐1638.
Delvenne A, Gobom J, Tijms B, et al. Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non‐Alzheimer's disease pathophysiology. Alzheimers Dement. 2023;19:807‐820.
Delmotte K, Schaeverbeke J, Poesen K, Vandenberghe R. Prognostic value of amyloid/tau/neurodegeneration (ATN) classification based on diagnostic cerebrospinal fluid samples for Alzheimer's disease. Alzheimers Res Ther. 2021;13(1):84.
Cummings J. The Role of Biomarkers in Alzheimer's Disease Drug Development. Adv Exp Med Biol. 2019;1118:29‐61.
Cummings J, Kinney J. Biomarkers for Alzheimer's disease: context of use, qualification, and roadmap for clinical implementation. Medicina (Kaunas). 2022;58(7):952.
Cummings J, Ritter A, Zhong K. Clinical trials for disease‐modifying therapies in Alzheimer's disease: a primer, lessons learned, and a blueprint for the future. J Alzheimers Dis. 2018;64(s1):S3‐S22.
Bos I, Verhey FR, Ramakers I, et al. Cerebrovascular and amyloid pathology in predementia stages: the relationship with neurodegeneration and cognitive decline. Alzheimers Res Ther. 2017;9(1):101.
Morris JC, Schindler SE, McCue LM, et al. Assessment of racial disparities in biomarkers for Alzheimer disease. JAMA Neurol. 2019;76(3):264‐273.
Bos I, Vos S, Vandenberghe R, et al. The EMIF‐AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics. Alzheimers Res Ther. 2018;10(1):64.
Grober E, Petersen KK, Lipton RB, et al. Association of stages of objective memory impairment with incident symptomatic cognitive impairment in cognitively normal individuals. Neurology. 2023;100(22):e2279‐e2289.
Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med. 2004;256(3):183‐194.
Magdalinou NK, Noyce AJ, Pinto R, et al. Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics. Parkinsonism Relat Disord. 2017;37:65‐71.
Batth TS, Francavilla C, Olsen JV. Off‐line high‐pH reversed‐phase fractionation for in‐depth phosphoproteomics. J Proteome Res. 2014;13(12):6176‐6186.
Herries EMBN, Sutphen CL, Fagan AM, Ladenson JH. Brain biomarkers: follow‐up of RNA expression discovery approach: CSF assays for neurogranin, SNAP‐25, and VILIP‐1. Neuromethods. 2021;168.
Schindler SE, Li Y, Todd KW, et al. Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer's disease. Alzheimers Dement. 2019;15(5):655‐665.
Aalten P, Ramakers IH, Biessels GJ, et al. The Dutch Parelsnoer Institute – Neurodegenerative diseases; methods, design and baseline results. BMC Neurol. 2014;14:254.
Butt OH, Long JM, Henson RL, et al. Cognitively normal APOE epsilon4 carriers have specific elevation of CSF SNAP‐25. Neurobiol Aging. 2021;102:64‐72.
Visser PJ, Reus LM, Gobom J, et al. Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer's disease. Mol Neurodegener. 2022;17(1):27.
de Rojas I, Moreno‐Grau S, Tesi N, et al. Common variants in Alzheimer's disease and risk stratification by polygenic risk scores. Nat Commun. 2021;12(1):3417.
Deming Y, Li Z, Kapoor M, et al. Genome‐wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers. Acta Neuropathol. 2017;133(5):839‐856.
Del‐Aguila JL, Fernandez MV, Schindler S, et al. Assessment of the genetic architecture of Alzheimer's disease risk in rate of memory decline. J Alzheimers Dis. 2018;62(2):745‐756.
Fischl B. FreeSurfer. Neuroimage. 2012;62(2):774‐781.
Ten Kate M, Redolfi A, Peira E, et al. MRI predictors of amyloid pathology: results from the EMIF‐AD Multimodal Biomarker Discovery study. Alzheimers Res Ther. 2018;10(1):100.
Millar PR, Gordon BA, Luckett PH, et al. Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross‐sectional observational study. eLife. 2023;12:e81869.
Duits FH, Wesenhagen KEJ, Ekblad L, et al. Four subgroups based on tau levels in Alzheimer's disease observed in two independent cohorts. Alzheimers Res Ther. 2021;13(1):2.
Hu H, Bi YL, Shen XN, et al. Application of the amyloid/tau/neurodegeneration framework in cognitively intact adults: the CABLE study. Ann Neurol. 2022;92(3):439‐450.
Unal I. Defining an optimal cut‐point value in ROC analysis: an alternative approach. Comput Math Methods Med. 2017;2017:3762651.
Mi H, Muruganujan A, Huang X, et al. Protocol Update for large‐scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc. 2019;14(3):703‐721.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol). 1995;57:289‐300.
Lewin A, Grieve IC. Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data. BMC Bioinf. 2006;7:426.
Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD. PANTHER version 14: more genomes, a new PANTHER GO‐slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2019;47(D1):D419‐D426.
Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein‐protein association networks with increased coverage, supporting functional discovery in genome‐wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607‐D613.
Bindea G, Mlecnik B, Hackl H, et al. ClueGO: a Cytoscape plug‐in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009;25(8):1091‐1093.
Neumeier M, Weigert J, Buettner R, et al. Detection of adiponectin in cerebrospinal fluid in humans. Am J Physiol Endocrinol Metab. 2007;293(4):E965‐969.
Dayon L, Cominetti O, Wojcik J, et al. Proteomes of paired human cerebrospinal fluid and plasma: relation to blood‐brain barrier permeability in older adults. J Proteome Res. 2019;18(3):1162‐1174.
Rapoport SI, Pettigrew KD. A heterogenous, pore‐vesicle membrane model for protein transfer from blood to cerebrospinal fluid at the choroid plexus. Microvasc Res. 1979;18(1):105‐119.
Hawrylycz MJ, Lein ES, Guillozet‐Bongaarts AL, et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature. 2012;489(7416):391‐399.
Rouillard AD, Gundersen GW, Fernandez NF, et al. The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins. Database (Oxford). 2016;2016:baw100.
Grote S, Prufer K, Kelso J, Dannemann M. ABAEnrichment: an R package to test for gene set expression enrichment in the adult and developing human brain. Bioinformatics. 2016;32(20):3201‐3203.
Vermunt L, Otte M, Verberk IMW, et al. Age‐ and disease‐specific reference values for neurofilament light presented in an online interactive support interface. Ann Clin Transl Neurol. 2022;9(11):1832‐1837.
Hill NL, Kolanowski AM, Gill DJ. Plasticity in early Alzheimer's disease: an opportunity for intervention. Top Geriatr Rehabil. 2011;27(4):257‐267.
Li L, Li Y, Ji X, Zhang B, Wei H, Luo Y. The effects of retinoic acid on the expression of neurogranin after experimental cerebral ischemia. Brain Res. 2008;1226:234‐240.
Agnello L, Lo Sasso B, Vidali M, et al. Neurogranin as a reliable biomarker for synaptic dysfunction in Alzheimer's disease. Diagnostics (Basel). 2021;11:12.
Lun MP, Monuki ES, Lehtinen MK. Development and functions of the choroid plexus‐cerebrospinal fluid system. Nat Rev Neurosci. 2015;16(8):445‐457.
Kratzer I, Ek J, Stolp H. The molecular anatomy and functions of the choroid plexus in healthy and diseased brain. Biochim Biophys Acta Biomembr. 2020;1862(11):183430.
Balusu S, Brkic M, Libert C, Vandenbroucke RE. The choroid plexus‐cerebrospinal fluid interface in Alzheimer's disease: more than just a barrier. Neural Regen Res. 2016;11(4):534‐537.
Snodgrass R, Johanson CE. Choroid Plexus: source of cerebrospinal fluid and regulator of brain development and function. In: Cinalli G, Ozek MM, Sainte‐Rose C, eds. Pediatric Hydrocephalus. Springer International Publishing; 2018:1‐36.
Huang TT, Leu D, Zou Y. Oxidative stress and redox regulation on hippocampal‐dependent cognitive functions. Arch Biochem Biophys. 2015;576:2‐7.
Nunomura A, Perry G, Aliev G, et al. Oxidative damage is the earliest event in Alzheimer disease. J Neuropathol Exp Neurol. 2001;60(8):759‐767.
Huang Y, Wang J, Zhu B, Fu P. CSF VEGF was positively associated with neurogranin independent of beta‐amyloid pathology. Neuropsychiatr Dis Treat. 2020;16:1737‐1744.
Gao Y, Liu J, Wang J, et al. Proteomic analysis of human hippocampal subfields provides new insights into the pathogenesis of Alzheimer's disease and the role of glial cells. Brain Pathol. 2022;32(4):e13047.
Vos SJB, Gordon BA, Su Y, et al. NIA‐AA staging of preclinical Alzheimer disease: discordance and concordance of CSF and imaging biomarkers. Neurobiol Aging. 2016;44:1‐8.
Ingala S, De Boer C, Masselink LA, et al. Application of the ATN classification scheme in a population without dementia: findings from the EPAD cohort. Alzheimers Dement. 2021;17(7):1189‐1204.
Vijayakumar A, Vijayakumar A. Comparison of hippocampal volume in dementia subtypes. ISRN Radiol. 2013;2013:174524.
Riha P, Brabenec L, Marecek R, Rektor I, Rektorova I. The reduction of hippocampal volume in Parkinson's disease. J Neural Transm (Vienna). 2022;129(5‐6):575‐580.
Ebenau JL, Pelkmans W, Verberk IMW, et al. Association of CSF, plasma, and imaging markers of neurodegeneration with clinical progression in people with subjective cognitive decline. Neurology. 2022;98(13):e1315‐e1326.