12 research outputs found
Combination of plasma amyloid beta(1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology
BACKGROUND: Blood-based biomarkers for Alzheimer's disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity. METHODS: We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET-), mild cognitive impairment (26 PET+, 24 PET-), or AD-dementia (132 PET+). Plasma Abeta(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald's backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman's correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA). RESULTS: Abeta(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p 0.33, p < 0.001). Abeta(1-42/1-40) showed a moderate negative correlation with MTA (Spearman's rho = - 0.24, p = 0.001). DISCUSSION AND CONCLUSIONS: Combination of plasma Abeta(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring
Characterization of pre-analytical sample handling effects on a panel of Alzheimer's disease–related blood-based biomarkers: Results from the Standardization of Alzheimer's Blood Biomarkers (SABB) working group
Introduction: Pre-analytical sample handling might affect the results of Alzheimer's disease blood-based biomarkers. We empirically tested variations of common blood collection and handling procedures. Methods: We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze–thawing. We measured amyloid beta (Aβ)42 and 40 peptides with six assays, and Aβ oligomerization-tendency (OAβ), amyloid precursor protein (APP)699-711, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), total tau (t-tau), and phosphorylated tau181. Results: Collection tube type resulted in different values of all assessed markers. Delayed plasma centrifugation and storage affected Aβ and t-tau; t-tau was additionally affected by centrifugation temperature. The other markers were resistant to handling variations. Discussion: We constructed a standardized operating procedure for plasma handling, to facilitate introduction of blood-based biomarkers into the research and clinical settings
ATN classification and clinical progression in subjective cognitive decline
Objective: To investigate the relationship between the ATN classification system (amyloid, tau, neurodegeneration) and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD).
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Methods: We classified 693 participants with SCD (60 ± 9 years, 41% women, Mini-Mental State Examination score 28 ± 2) from the Amsterdam Dementia Cohort and Subjective Cognitive Impairment Cohort (SCIENCe) project according to the ATN model, as determined by amyloid PET or CSF β-amyloid (A), CSF p-tau (T), and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants, follow-up was available (3 ± 2 years). As a control population, we included 124 participants without SCD.
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Results: Fifty-six (n = 385) participants had normal Alzheimer disease (AD) biomarkers (A–T–N–), 27% (n = 186) had non-AD pathologic change (A–T–N+, A–T+N–, A–T+N+), 18% (n = 122) fell within the Alzheimer continuum (A+T–N–, A+T–N+, A+T+N–, A+T+N+). ATN profiles were unevenly distributed, with A–T+N+, A+T–N+, and A+T+N+ containing very few participants. Cox regression showed that compared to A–T–N–, participants in A+ profiles had a higher risk of dementia with a dose–response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition.
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Conclusions: Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A–T+N+, A+T–N–, A+T+N–, and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A–T–N– individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic
The global Alzheimer's Association round robin study on plasma amyloid β methods
Introduction: Blood-based assays to measure brain amyloid beta (Aβ) deposition are an attractive alternative to the cerebrospinal fluid (CSF)-based assays currently used in clinical settings. In this study, we examined different blood-based assays to measure Aβ and how they compare among centers and assays. Methods: Aliquots from 81 plasma samples were distributed to 10 participating centers. Seven immunological assays and four mass-spectrometric methods were used to measure plasma Aβ concentrations. Results: Correlations were weak for Aβ42 while Aβ40 correlations were stronger. The ratio Aβ42/Aβ40 did not improve the correlations and showed weak correlations. Discussion: The poor correlations for Aβ42 in plasma might have several potential explanations, such as the high levels of plasma proteins (compared to CSF), sensitivity to pre-analytical sample handling and specificity, and cross-reactivity of different antibodies. Different methods might also measure different pools of plasma Aβ42. We, however, hypothesize that greater correlations might be seen in future studies because many of the methods have been refined during completion of this study
Amyloid Pathology is Associated with Semantic Loss in Patients with Subjective Cognitive Decline
Serum neurofilament light chain in genetic frontotemporal dementia: a longitudinal, multicentre cohort study
Effects of pre-analytical procedures on blood biomarkers for Alzheimer's pathophysiology, glial activation, and neurodegeneration
Introduction: We tested how tube types (ethylenediaminetetraacetic acid [EDTA], serum, lithium heparin [LiHep], and citrate) and freeze-thaw cycles affect levels of blood biomarkers for Alzheimer's disease (AD) pathophysiology, glial activation, and neuronal injury. Methods: Amyloid beta (Aβ)42, Aβ40, phosphorylated tau181 (p-tau181), glial fibrillary acidic protein, total tau (t-tau), neurofilament light, and phosphorylated neurofilament heavy protein were measured using single molecule arrays. Results: LiHep demonstrated the highest mean value for all biomarkers. Tube types were highly correlated for most biomarkers (r > 0.95) but gave significantly different absolute concentrations. Weaker correlations between tube types were found for Aβ42/40 (r = 0.63-0.86) and serum t-tau (r = 0.46-0.64). Freeze-thaw cycles highly influenced levels of serum Aβ and t-tau (P 3 should be avoided for p-tau181.MSC received funding from the European Union's Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie action grant agreement No 752310, and currently receives funding from Instituto de Salud Carlos III (PI19/00155) and from the Spanish Ministry of Science, Innovation and Universities (Juan de la Cierva Programme grant IJC2018-037478-I). TKK holds a Brightfocus postdoctoral fellowship (#A2020812F), and was further supported by the Swedish Alzheimer Foundation (Alzheimerfonden), the Swedish Dementia Foundation (Demensförbundet), Parkinsonfonden, Gamla Tjänarinnor, the Aina (Ann) Wallströms and Mary-Ann Sjöbloms Foundation, the Gun and Bertil Stohnes foundation, and the Anna Lisa and Brother Björnsson's Foundation. AS was supported by the Paulo Foundation, and currently receives funding from the Orion Research Foundation sr. KB is supported by the Swedish Research Council (#2017-00915), the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), and the National Institute of Health (NIH), USA, (grant #1R01AG068398-01). HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712), Swedish State Support for Clinical Research (#ALFGBG-720931), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer's Association (#ADSF-21-831376-C, #ADSF-21-831381-C and #ADSF-21-831377-C), the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2019-0228), the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), and the UK Dementia Research Institute at UCL
Serum neurofilament light chain in genetic frontotemporal dementia: a longitudinal, multicentre cohort study
Back ground Neurofilament light chain (NfL) is a promising blood biomarker in genetic frontotemporal dementia, with elevated concentrations in symptomatic carriers of mutations in GRN, C9orf72, and MAPT. A better understanding of NfL dynamics is essential for upcoming therapeutic trials. We aimed to study longitudinal NfL trajectories in people with presymptomatic and symptomatic genetic frontotemporal dementia.Methods We recruited participants from 14 centres collaborating in the Genetic Frontotemporal Dementia Initiative (GENFI), which is a multicentre cohort study of families with genetic frontotemporal dementia done across Europe and Canada. Eligible participants (aged >= 18 years) either had frontotemporal dementia due to a pathogenic mutation in GRN, C9orf72, or MAPT (symptomatic mutation carriers) or were healthy at-risk first-degree relatives (either presymptomatic mutation carriers or non-carriers), and had at least two serum samples with a time interval of 6 months or more. Participants were excluded if they had neurological comorbidities that were likely to affect NfL, including cerebrovascular events. We measured NfL longitudinally in serum samples collected between june 8, 2012, and Dec 8, 2017, through follow-up visits annually or every 2 years, which also included MRI and neuropsychological assessments. Using mixed-effects models, we analysed Nil changes over time and correlated them with longitudinal imaging and clinical parameters, controlling for age, sex, and study site. The primary outcome was the course of NfL over time in the various stages of genetic frontotemporal dementia.Findings We included 59 symptomatic carriers and 149 presymptomatic carriers of a mutation in GRN, C9orf72, or MAPT, and 127 non-carriers. Nine presymptomatic carriers became symptomatic during follow-up (so-called converters). Baseline NfL was elevated in symptomatic carriers (median 52 pg/mL [IQR 24-69]) compared with presymptomatic carriers (9 pg/mL [6-13]; p<0.0001) and non-carriers (8 pg/mL [6-11]; p<0.0001), and was higher in converters than in non-converting carriers (19 pg/mL [17-28] vs 8 pg/mL [6-11]; p=0.0007; adjusted for age). During follow-up, NfL increased in converters (b=0.097 [S E 0. 018]; p<0.0001). In symptomatic mutation carriers overall, NfL did not change during follow-up (b=0.017 [SE 0.010]; p=0.101) and remained elevated. Rates of NfL change over time were associated with rate of decline in Mini Mental State Examination (b=-94.7 [SE 33.9]; p=0.003) and atrophy rate in several grey matter regions, but not with change in Frontotemporal Lobar Degeneration-Clinical Dementia Rating scale score (b=-3.46 [SE 46.3]; p=0.941).Interpretation Our findings show the value of blood NfL as a disease progression biomarker in genetic frontotemporal dementia and suggest that longitudinal NfL measurements could identify mutation carriers approaching symptom onset and capture rates of brain atrophy. The characterisation of NfL over the course of disease provides valuable information for its use as a treatment effect marker. Copyright (C) 2019 Elsevier Ltd. All rights reserved.Neuro Imaging Researc