Novel cerebrospinal fluid biomarkers correlating with shunt responsiveness in patients with idiopathic normal pressure hydrocephalus

BACKGROUND: Idiopathic Normal pressure hydrocephalus (iNPH) is a form of adult hydrocephalus that is clinically characterized by progressive gait impairment, cognitive dysfunction, and urinary incontinence. The current standard method of treatment involves surgical installation of a CSF diversion shunt. However, only a fraction of patients shows an alleviation of symptoms from shunt surgery. Thus, the purpose of this prospective explorative proteomic study was to identify prognostic CSF biomarkers to predict shunt responsiveness in iNPH patients. Further, we evaluated the ability of the core Alzheimer's disease (AD) CSF biomarkers phosphorylated (p)-tau, total (t)-tau, and amyloid-β 1-42 (Aβ1-42) to serve as predictors of shunt response. METHODS: We conducted a tandem mass tag (TMT) proteomic analysis of lumbar CSF from 68 iNPH patients, sampled pre-shunt surgery. Tryptic digests of CSF samples were labelled with TMTpro reagents. The TMT multiplex samples were fractionated in 24 concatenated fractions by reversed-phase chromatography at basic pH and analysed by liquid chromatography coupled to mass spectrometry (LC-MS) on an Orbitrap Lumos mass spectrometer. The relative abundances of the identified proteins were correlated with (i) iNPH grading scale (iNPHGS) and (ii) gait speed change 1 year after surgery from baseline to identify predictors of shunt responsiveness. RESULTS: We identified four CSF biomarker candidates which correlated most strongly with clinical improvement on the iNPHGS and were significantly changed in shunt-responsive compared to shunt-unresponsive iNPH patients 1 year post-surgery: FABP3 (R = - 0.46, log2(fold change (FC)) = - 0.25, p < 0.001), ANXA4 (R = 0.46, log2(FC) = 0.32, p < 0.001), MIF (R = -0.49, log2(FC) =  - 0.20, p < 0.001) and B3GAT2 (R = 0.54, log2(FC) = 0.20, p < 0.001). In addition, five biomarker candidates were selected based on their strong correlation with gait speed change 1 year after shunt installation: ITGB1 (R = - 0.48, p < 0.001), YWHAG (R = - 0.41, p < 0.01), OLFM2 (R = 0.39, p < 0.01), TGFBI (R = - 0.38, p < 0.01), and DSG2 (R = 0.37, p < 0.01). Concentrations of the CSF AD core biomarkers did not differ significantly with shunt responsiveness. CONCLUSION: FABP3, MIF, ANXA4, B3GAT2, ITGB1, YWHAG, OLFM2, TGFBI and DSG2 in CSF are promising prognostic biomarker candidates to predict shunt responsiveness in iNPH patients

CSF biomarkers distinguish idiopathic normal pressure hydrocephalus from its mimics

OBJECTIVE: To examine the differential diagnostic significance of cerebrospinal fluid (CSF) biomarkers reflecting Alzheimer's disease-related amyloid β (Aβ) production and aggregation, cortical neuronal damage, tau pathology, damage to long myelinated axons and astrocyte activation, which hypothetically separates patients with idiopathic normal pressure hydrocephalus (iNPH) from patients with other neurodegenerative disorders. METHODS: The study included lumbar CSF samples from 82 patients with iNPH, 75 with vascular dementia, 70 with Parkinson's disease, 34 with multiple system atrophy, 34 with progressive supranuclear palsy, 15 with corticobasal degeneration, 50 with Alzheimer's disease, 19 with frontotemporal lobar degeneration and 54 healthy individuals (HIs). We analysed soluble amyloid precursor protein alpha (sAPPα) and beta (sAPPβ), Aβ species (Aβ38, Aβ40 and Aβ42), total tau (T-tau), phosphorylated tau, neurofilament light and monocyte chemoattractant protein 1 (MCP-1). RESULTS: Patients with iNPH had lower concentrations of tau and APP-derived proteins in combination with elevated MCP-1 compared with HI and the non-iNPH disorders. T-tau, Aβ40 and MCP-1 together yielded an area under the curve of 0.86, differentiating iNPH from the other disorders. A prediction algorithm consisting of T-tau, Aβ40 and MCP-1 was designed as a diagnostic tool using CSF biomarkers. CONCLUSIONS: The combination of the CSF biomarkers T-tau, Aβ40 and MCP-1 separates iNPH from cognitive and movement disorders with good diagnostic sensitivity and specificity. This may have important implications for diagnosis and clinical research on disease mechanisms for iNPH

Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study

The aim of this study was to assess the agreement between data on cerebral amyloidosis, derived using Pittsburgh compound B positron emission tomography and (i) multi-laboratory INNOTEST enzyme linked immunosorbent assay derived cerebrospinal fluid concentrations of amyloid-β 42 ; (ii) centrally measured cerebrospinal fluid amyloid-β 42 using a Meso Scale Discovery enzyme linked immunosorbent assay; and (iii) cerebrospinal fluid amyloid-β 42 centrally measured using an antibody-independent mass spectrometry-based reference method. Moreover, we examined the hypothesis that discordance between amyloid biomarker measurements may be due to interindividual differences in total amyloid-β production, by using the ratio of amyloid-β 42 to amyloid-β 40 . Our study population consisted of 243 subjects from seven centres belonging to the Biomarkers for Alzheimer’s and Parkinson’s Disease Initiative, and included subjects with normal cognition and patients with mild cognitive impairment, Alzheimer’s disease dementia, frontotemporal dementia, and vascular dementia. All had Pittsburgh compound B positron emission tomography data, cerebrospinal fluid INNOTEST amyloid-β 42 values, and cerebrospinal fluid samples available for reanalysis. Cerebrospinal fluid samples were reanalysed (amyloid-β 42 and amyloid-β 40 ) using Meso Scale Discovery electrochemiluminescence enzyme linked immunosorbent assay technology, and a novel, antibody-independent, mass spectrometry reference method. Pittsburgh compound B standardized uptake value ratio results were scaled using the Centiloid method. Concordance between Meso Scale Discovery/mass spectrometry reference measurement procedure findings and Pittsburgh compound B was high in subjects with mild cognitive impairment and Alzheimer’s disease, while more variable results were observed for cognitively normal and non-Alzheimer’s disease groups. Agreement between Pittsburgh compound B classification and Meso Scale Discovery/mass spectrometry reference measurement procedure findings was further improved when using amyloid-β 42/40 . Agreement between Pittsburgh compound B visual ratings and Centiloids was near complete. Despite improved agreement between Pittsburgh compound B and centrally analysed cerebrospinal fluid, a minority of subjects showed discordant findings. While future studies are needed, our results suggest that amyloid biomarker results may not be interchangeable in some individuals

Preclinical effects of APOE epsilon 4 on cerebrospinal fluid A beta 42 concentrations

Background: From earlier studies it is known that the APOE ε2/ε3/ε4 polymorphism modulates the concentrations of cerebrospinal fluid (CSF) beta-amyloid1–42 (Aβ42) in patients with cognitive decline due to Alzheimer’s disease (AD), as well as in cognitively healthy controls. Here, in a large cohort consisting solely of cognitively healthy individuals, we aimed to evaluate how the effect of APOE on CSF Aβ42 varies by age, to understand the association between APOE and the onset of preclinical AD. // Methods: APOE genotype and CSF Aβ42 concentration were determined in a cohort comprising 716 cognitively healthy individuals aged 17–99 from nine different clinical research centers. // Results: CSF concentrations of Aβ42 were lower in APOE ε4 carriers than in noncarriers in a gene dose-dependent manner. The effect of APOE ε4 on CSF Aβ42 was age dependent. The age at which CSF Aβ42 concentrations started to decrease was estimated at 50 years in APOE ε4-negative individuals and 43 years in heterozygous APOE ε4 carriers. Homozygous APOE ε4 carriers showed a steady decline in CSF Aβ42 concentrations with increasing age throughout the examined age span. // Conclusions: People possessing the APOE ε4 allele start to show a decrease in CSF Aβ42 concentration almost a decade before APOE ε4 noncarriers already in early middle age. Homozygous APOE ε4 carriers might deposit Aβ42 throughout the examined age span. These results suggest that there is an APOE ε4-dependent period of early alterations in amyloid homeostasis, when amyloid slowly accumulates, that several years later, together with other downstream pathological events such as tau pathology, translates into cognitive decline

Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study

Background Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia. Methods In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models—a demographics model, a hippocampal volume model, and a CSF biomarkers model—by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework. Findings We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59–0·65), validated hippocampal volume model (0·67, 0·62–0·72), and updated CSF biomarkers model (0·72, 0·68–0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71–0·76). Interpretation We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour

S-[F-18] THK-5117-PET and [C-11] PIB-PET Imaging in Idiopathic Normal Pressure Hydrocephalus in Relation to Confirmed Amyloid-beta Plaques and Tau in Brain Biopsies

BACKGROUND: Detection of pathological tau aggregates could facilitate clinical diagnosis of Alzheimer’s disease (AD) and monitor drug effects in clinical trials. S-[18F]THK-5117 could be a potential tracer to detect pathological tau deposits in brain. However, no previous study have correlated S-[18F]THK-5117 uptake in PET with brain biopsy verified tau pathology in vivo. OBJECTIVE: Here we aim to evaluate the association between cerebrospinal fluid (CSF) AD biomarkers, S-[18F]THK-5117, and [11C]PIB PET against tau and amyloid lesions in brain biopsy. METHODS: Fourteen patients with idiopathic normal pressure hydrocephalus (iNPH) with previous shunt surgery including right frontal cortical brain biopsy and CSF Aβ1 - 42, total tau, and P-tau181 measures, underwent brain MRI, [11C]PIB PET, and S-[18F]THK-5117 PET imaging. RESULTS: Seven patients had amyloid-β (Aβ, 4G8) plaques, two both Aβ and phosphorylated tau (Pτ, AT8) and one only Pτ in biopsy. As expected, increased brain biopsy Aβ was well associated with higher [11C]PIB uptake in PET. However, S-[18F]THK-5117 uptake did not show any statistically significant correlation with either brain biopsy Pτ or CSF P-tau181 or total tau. CONCLUSION: S-[18F]THK-5117 lacked clear association with neuropathologically verified tau pathology in brain biopsy probably, at least partially, due to off-target binding. Further studies with larger samples of patients with different tau tracers are urgently needed. The detection of simultaneous Aβ and tau pathology in iNPH is important since that may indicate poorer and especially shorter response for CSF shunt surgery compared with no pathology

Recommendations for CSF AD biomarkers in the diagnostic evaluation of MCI

This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) amyloid-β1-42, tau, and phosphorylated tau in the diagnostic evaluation of patients with mild cognitive impairment (MCI). The recommendations were developed by a multidisciplinary working group and based on the available evidence and consensus from focused group discussions for 1) prediction of clinical progression to Alzheimer's disease (AD) dementia, 2) cost-effectiveness, 3) interpretation of results, and 4) patient counseling. The working group recommended using CSF AD biomarkers in the diagnostic workup of MCI patients, after prebiomarker counseling, as an add-on to clinical evaluation to predict functional decline or conversion to AD dementia and to guide disease management. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Furthermore, the working group provided recommendations for interpretation of ambiguous CSF biomarker results and for pre- and post-biomarker counseling

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers

Altres ajuts: European Alzheimer DNA BioBank, EADB; EU Joint Programme, Neurodegenerative Disease Research (JPND); Neurodegeneration research program of Amsterdam Neuroscience; Stichting Alzheimer Nederland; Stichting VUmc fonds; Stichting Dioraphte; JPco-fuND FP-829-029 (ZonMW projectnumber 733051061); Dutch Federation of University Medical Centers; Dutch Government (from 2007-2011); JPND EADB grant (German Federal Ministry of Education and Research (BMBF) grant: 01ED1619A); German Research Foundation (DFG RA 1971/6-1, RA1971/7-1, RA 1971/8-1); Grifols SA; Fundación bancaria 'La Caixa'; Fundació ACE; CIBERNED; Fondo Europeo de Desarrollo Regional (FEDER-'Una manera de hacer Europa'); NIH (P30AG066444, P01AG003991); Alzheimer Research Foundation (SAO-FRA), The Research Foundation Flanders (FWO), and the University of Antwerp Research Fund. FK is supported by a BOF DOCPRO fellowship of the University of Antwerp Research Fund; Siemens Healthineers; Valdecilla Biobank (PT17/0015/0019); Academy of Finland (338182); German Center for Neurodegenerative Diseases (DZNE); German Federal Ministry of Education and Research (BMBF 01G10102, 01GI0420, 01GI0422, 01GI0423, 01GI0429, 01GI0431, 01GI0433, 04GI0434, 01GI0711); ZonMW (#73305095007); Health~Holland, Topsector Life Sciences & Health (PPP-allowance #LSHM20106); Hersenstichting; Edwin Bouw Fonds; Gieskes-Strijbisfonds; NWO Gravitation program BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (NWO: 024.004.012); Swedish Alzheimer Foundation (AF-939988, AF-930582, AF-646061, AF-741361); Dementia Foundation (2020-04-13, 2021-04-17); Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALF 716681); Swedish Research Council (11267, 825-2012-5041, 2013-8717, 2015-02830, 2017-00639, 2019-01096); Swedish Research Council for Health, Working Life and Welfare (2001-2646, 2001-2835, 2001-2849, 2003-0234, 2004-0150, 2005-0762, 2006-0020, 2008-1229, 2008-1210, 2012-1138, 2004-0145, 2006-0596, 2008-1111, 2010-0870, 2013-1202, 2013-2300, 2013-2496); Swedish Brain Power, Hjärnfonden, Sweden (FO2016-0214, FO2018-0214, FO2019-0163); Alzheimer's Association Zenith Award (ZEN-01-3151); Alzheimer's Association Stephanie B. Overstreet Scholars (IIRG-00-2159); Alzheimer's Association (IIRG-03-6168, IIRG-09-131338); Bank of Sweden Tercentenary Foundation; Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALFGBG-81392, ALFGBG-771071); Swedish Alzheimer Foundation (AF-842471, AF-737641, AF-939825); Swedish Research Council (2019-02075); Swedish Research Council (2016-01590); BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (024.004.012); Swedish Research Council (2018-02532); Swedish State Support for Clinical Research (ALFGBG-720931); Alzheimer Drug Discovery Foundation (ADDF), USA (201809-2016862); UK Dementia Research Institute at UCL; Swedish Research Council (#2017-00915); Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615); Swedish Alzheimer Foundation (#AF-742881); Hjärnfonden, Sweden (#FO2017-0243); Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986); National Institute of Health (NIH), USA, (#1R01AG068398-01); Alzheimer's Association 2021 Zenith Award (ZEN-21-848495); National Institutes of Health (R01AG044546, R01AG064877, RF1AG053303, R01AG058501, U01AG058922, RF1AG058501, R01AG064614); Chuck Zuckerberg Initiative (CZI).Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume