15 research outputs found

    Plasma amyloid-β levels, cerebral atrophy and risk of dementia: A population-based study

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    Background: Plasma amyloid-β (Aβ) levels are increasingly studied as a potential accessible marker of cognitive impairment and dementia. However, it remains underexplored whether plasma Aβ levels including the novel Aβ peptide 1-38 (Aβ1-38) relate to preclinical markers of neurodegeneration and risk of dementia. We investigated the association of plasma Aβ1-38, Aβ1-40, and Aβ1-42 levels with imaging markers of neurodegeneration and risk of dementia in a prospective population-based study. Methods: We analyzed plasma Aβ levels in 458 individuals from the Rotterdam Study. Brain volumes, including gray matter, white matter, and hippocampus, were computed on the basis of 1.5-T magnetic resonance imaging (MRI). Dementia and its subtypes were defined on the basis of internationally accepted criteria. Results: A total of 458 individuals (mean age, 67.8 ± 7.7 yr; 232 [50.7%] women) with baseline MRI scans and incident dementia were included. The mean ± SD values of Aβ1-38, Aβ1-40, and Aβ1-42 (in pg/ml) were 19.4 ± 4.3, 186.1 ± 35.9, and 56.3 ± 6.2, respectively, at baseline. Lower plasma Aβ1-42 levels were associated with smaller hippocampal volume (mean difference in hippocampal volume per SD decrease in Aβ1-42 levels, - 0.13; 95% CI, - 0.23 to - 0.04; p = 0.007). After a mean follow-up of 14.8 years (SD, 4.9; range, 4.1-23.5 yr), 79 persons developed dementia, 64 of whom were diagnosed with Alzheimer's disease (AD). Lower levels of Aβ1-38 and Aβ1-42 were associated with increased risk of dementia, specifically AD (HR for AD per SD decrease in Aβ1-38 levels, 1.39; 95% CI, 1.00-2.16; HR for AD per SD decrease in Aβ1-42 levels, 1.35; 95% CI, 1.05-1.75) after adjustment for age, sex, education, cardiovascular risk factors, apolipoprotein E ϵ4 allele carrier status, and other Aβ isoforms. Conclusions: Our results show that lower plasma Aβ levels were associated with risk of dementia and incident AD. Moreover, lower plasma Aβ1-42 levels were related to smaller hippocampal volume. These results suggest that plasma Aβ1-38 and Aβ1-42 maybe useful biomarkers for identification of individuals at risk of dementia

    Plasma glial fibrillary acidic protein is elevated in cognitively normal older adults at risk of Alzheimer’s disease

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    © 2021, The Author(s). Glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein, can be measured in blood samples, and has been associated with Alzheimer’s disease (AD). However, plasma GFAP has not been investigated in cognitively normal older adults at risk of AD, based on brain amyloid-β (Aβ) load. Cross-sectional analyses were carried out for plasma GFAP and plasma Aβ1–42/Aβ1–40 ratio, a blood-based marker associated with brain Aβ load, in participants (65–90 years) categorised into low (Aβ−, n = 63) and high (Aβ+, n = 33) brain Aβ load groups via Aβ positron emission tomography. Plasma GFAP, Aβ1–42, and Aβ1–40 were measured using the Single molecule array (Simoa) platform. Plasma GFAP levels were significantly higher (p \u3c 0.00001), and plasma Aβ1–42/Aβ1–40 ratios were significantly lower (p \u3c 0.005), in Aβ+ participants compared to Aβ− participants, adjusted for covariates age, sex, and apolipoprotein E-ε4 carriage. A receiver operating characteristic curve based on a logistic regression of the same covariates, the base model, distinguished Aβ+ from Aβ− (area under the curve, AUC = 0.78), but was outperformed when plasma GFAP was added to the base model (AUC = 0.91) and further improved with plasma Aβ1–42/Aβ1–40 ratio (AUC = 0.92). The current findings demonstrate that plasma GFAP levels are elevated in cognitively normal older adults at risk of AD. These observations suggest that astrocytic damage or activation begins from the pre-symptomatic stage of AD and is associated with brain Aβ load. Observations from the present study highlight the potential of plasma GFAP to contribute to a diagnostic blood biomarker panel (along with plasma Aβ1–42/Aβ1–40 ratios) for cognitively normal older adults at risk of AD

    Elevated plasma sclerostin is associated with high brain amyloid-b load in cognitively normal older adults

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    Osteoporosis and Alzheimer’s disease (AD) mainly affect older individuals, and the possibility of an underlying link contributing to their shared epidemiological features has rarely been investigated. In the current study, we investigated the association between levels of plasma sclerostin (SOST), a protein primarily produced by bone, and brain amyloid-beta (A ) load, a pathological hallmark of AD. The study enrolled participants meeting a set of screening inclusion and exclusion criteria and were stratified into A − (n = 65) and A + (n = 35) according to their brain A load assessed using A -PET (positron emission tomography) imaging. Plasma SOST levels, apolipoprotein E gene (APOE) genotype and several putative AD blood-biomarkers including A 40, A 42, A 42/A 40, neurofilament light (NFL), glial fibrillary acidic protein (GFAP), total tau (t-tau) and phosphorylated tau (p-tau181 and p-tau231) were detected and compared. It was found that plasma SOST levels were significantly higher in the A + group (71.49 ± 25.00 pmol/L) compared with the A − group (56.51 ± 22.14 pmol/L) (P \u3c 0.01). Moreover, Spearman’s correlation analysis showed that plasma SOST concentrations were positively correlated with brain A load (ρ = 0.321, P = 0.001). Importantly, plasma SOST combined with A 42/A 40 ratio significantly increased the area under the curve (AUC) when compared with using A 42/A 40 ratio alone (AUC = 0.768 vs 0.669, P = 0.027). In conclusion, plasma SOST levels are elevated in cognitively unimpaired older adults at high risk of AD and SOST could complement existing plasma biomarkers to assist in the detection of preclinical AD

    Plasma amyloid‐beta levels in a pre‐symptomatic dutch‐type hereditary cerebral amyloid angiopathy pedigree: A cross‐sectional and longitudinal investigation

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    Plasma amyloid‐beta (Aβ) has long been investigated as a blood biomarker candidate for Cerebral Amyloid Angiopathy (CAA), however previous findings have been inconsistent which could be attributed to the use of less sensitive assays. This study investigates plasma Aβ alterations between pre‐symptomatic Dutch‐type hereditary CAA (D‐CAA) mutation‐carriers (MC) and non-carriers (NC) using two Aβ measurement platforms. Seventeen pre‐symptomatic members of a D‐ CAA pedigree were assembled and followed up 3–4 years later (NC = 8;MC = 9). Plasma Aβ1‐40 and Aβ1‐42 were cross‐sectionally and longitudinally analysed at baseline (T1) and follow‐up (T2) and were found to be lower in MCs compared to NCs, cross‐sectionally after adjusting for covari-ates, at both T1(Aβ1‐40: p = 0.001; Aβ1‐42: p = 0.0004) and T2 (Aβ1‐40: p = 0.001; Aβ1‐42: p = 0.016) employing the Single Molecule Array (Simoa) platform, however no significant differences were observed using the xMAP platform. Further, pairwise longitudinal analyses of plasma Aβ1‐40 revealed decreased levels in MCs using data from the Simoa platform (p = 0.041) and pairwise longitudinal analyses of plasma Aβ1‐42 revealed decreased levels in MCs using data from the xMAP platform (p = 0.041). Findings from the Simoa platform suggest that plasma Aβ may add value to a panel of biomarkers for the diagnosis of pre‐symptomatic CAA, however, further validation studies in larger sample sets are required

    Highly specific and ultrasensitive plasma test detects Abeta(1–42) and Abeta(1–40) in Alzheimer’s disease

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    Plasma biomarkers that reflect specific amyloid beta (Abeta) proteoforms provide an insight in the treatment effects of Alzheimer’s disease (AD) therapies. Our aim was to develop and validate ready-to-use Simoa ‘Amyblood’ assays that measure full length Abeta 1-42 and Abeta 1-40 and compare their performance with two commercial assays. Linearity, intra- and inter-assay %CV were compared between Amyblood, Quanterix Simoa triplex, and Euroimmun ELISA. Sensitivity and selectivity were assessed for Amyblood and the Quanterix triplex. Clinical performance was assessed in CSF biomarker confirmed AD (n = 43, 68 ± 6 years) and controls (n = 42, 62 ± 5 years). Prototype and Amyblood showed similar calibrator curves and differentiation (20 AD vs 20 controls, p < 0.001). Amyblood, Quanterix triplex, and ELISA showed similar linearity (96%-122%) and intra-assay %CVs (≤ 3.1%). A minor non-specific signal was measured with Amyblood of + 2.4 pg/mL Abeta 1-42 when incubated with 60 pg/mL Abeta 1-40. A substantial non-specific signal of + 24.7 pg/mL Abeta x-42 was obtained when 40 pg/mL Abeta 3-42 was measured with the Quanterix triplex. Selectivity for Abeta 1-42 at physiological Abeta 1-42 and Abeta 1-40 concentrations was 125% for Amyblood and 163% for Quanterix. Amyblood and Quanterix ratios (p < 0.001) and ELISA Abeta 1-42 concentration (p = 0.025) could differentiate AD from controls. We successfully developed and upscaled a prototype to the Amyblood assays with similar technical and clinical performance as the Quanterix triplex and ELISA, but better specificity and selectivity than the Quanterix triplex assay. These results suggest leverage of this specific assay for monitoring treatment response in trials

    Neuroinflammatory CSF biomarkers MIF, sTREM1, and sTREM2 show dynamic expression profiles in Alzheimer’s disease

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    Abstract Background There is a need for novel fluid biomarkers tracking neuroinflammatory responses in Alzheimer’s disease (AD). Our recent cerebrospinal fluid (CSF) proteomics study revealed that migration inhibitory factor (MIF) and soluble triggering receptor expressed on myeloid cells 1 (sTREM1) increased along the AD continuum. We aimed to assess the potential use of these proteins, in addition to sTREM2, as CSF biomarkers to monitor inflammatory processes in AD. Methods We included cognitively unimpaired controls (n = 67, 63 ± 9 years, 24% females, all amyloid negative), patients with mild cognitive impairment (MCI; n = 92, 65 ± 7 years, 47% females, 65% amyloid positive), AD (n = 38, 67 ± 6 years, 8% females, all amyloid positive), and DLB (n = 50, 67 ± 6 years, 5% females, 54% amyloid positive). MIF, sTREM1, and sTREM2 levels were measured by validated immunoassays. Differences in protein levels between groups were tested with analysis of covariance (corrected for age and sex). Spearman correlation analysis was performed to evaluate the association between these neuroinflammatory markers with AD-CSF biomarkers (Aβ42, tTau, pTau) and mini-mental state examination (MMSE) scores. Results MIF levels were increased in MCI (p  0.05) compared to controls. Levels of sTREM1 were specifically increased in AD compared to controls (p  0.05), while sTREM2 levels were increased specifically in MCI compared to all other groups (all p < 0.001). Neuroinflammatory proteins were highly correlated with CSF pTau levels (MIF: all groups; sTREM1: MCI, AD and DLB; sTREM2: controls, MCI and DLB). Correlations with MMSE scores were observed in specific clinical groups (MIF in controls, sTREM1 in AD, and sTREM2 in DLB). Conclusion Inflammatory-related proteins show diverse expression profiles along different AD stages, with increased protein levels in the MCI stage (MIF and sTREM2) and AD stage (MIF and sTREM1). The associations of these inflammatory markers primarily with CSF pTau levels indicate an intertwined relationship between tau pathology and inflammation. These neuroinflammatory markers might be useful in clinical trials to capture dynamics in inflammatory responses or monitor drug–target engagement of inflammatory modulators

    Differential diagnostic performance of a panel of plasma biomarkers for different types of dementia

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    Introduction: We explored what combination of blood-based biomarkers (amyloid beta [Aβ]1-42/1-40, phosphorylated tau [p-tau]181, neurofilament light [NfL], glial fibrillary acidic protein [GFAP]) differentiates Alzheimer's disease (AD) dementia, frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). Methods: We measured the biomarkers with Simoa in two separate cohorts (n = 160 and n = 152). In one cohort, Aβ1-42/1-40 was also measured with mass spectrometry (MS). We assessed the differential diagnostic value of the markers, by logistic regression with Wald's backward selection. Results: MS and Simoa Aβ1-42/1-40 similarly differentiated AD from controls. The Simoa panel that optimally differentiated AD from FTD consisted of NfL and p-tau181 (area under the curve [AUC] = 0.94; cohort 1) or NfL, GFAP, and p-tau181 (AUC = 0.90; cohort 2). For AD from DLB, the panel consisted of NfL, p-tau181, and GFAP (AUC = 0.88; cohort 1), and only p-tau181 (AUC = 0.81; cohort 2). Discussion: A combination of plasma p-tau181, NfL, and GFAP, but not Aβ1-42/1-40, might be useful to discriminate AD, FTD, and DLB

    Plasma glial fibrillary acidic protein is elevated in cognitively normal older adults at risk of Alzheimer’s disease

    No full text
    Glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein, can be measured in blood samples, and has been associated with Alzheimer’s disease (AD). However, plasma GFAP has not been investigated in cognitively normal older adults at risk of AD, based on brain amyloid-β (Aβ) load. Cross-sectional analyses were carried out for plasma GFAP and plasma Aβ1–42/Aβ1–40 ratio, a blood-based marker associated with brain Aβ load, in participants (65–90 years) categorised into low (Aβ−, n = 63) and high (Aβ+, n = 33) brain Aβ load groups via Aβ positron emission tomography. Plasma GFAP, Aβ1–42, and Aβ1–40 were measured using the Single molecule array (Simoa) platform. Plasma GFAP levels were significantly higher (p < 0.00001), and plasma Aβ1–42/Aβ1–40 ratios were significantly lower (p < 0.005), in Aβ+ participants compared to Aβ− participants, adjusted for covariates age, sex, and apolipoprotein E-ε4 carriage. A receiver operating characteristic curve based on a logistic regression of the same covariates, the base model, distinguished Aβ+ from Aβ− (area under the curve, AUC = 0.78), but was outperformed when plasma GFAP was added to the base model (AUC = 0.91) and further improved with plasma Aβ1–42/Aβ1–40 ratio (AUC = 0.92). The current findings demonstrate that plasma GFAP levels are elevated in cognitively normal older adults at risk of AD. These observations suggest that astrocytic damage or activation begins from the pre-symptomatic stage of AD and is associated with brain Aβ load. Observations from the present study highlight the potential of plasma GFAP to contribute to a diagnostic blood biomarker panel (along with plasma Aβ1–42/Aβ1–40 ratios) for cognitively normal older adults at risk of AD

    Clinical and analytical comparison of six Simoa assays for plasma P-tau isoforms P-tau181, P-tau217, and P-tau231

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    Introduction: Studies using different assays and technologies showed highly promising diagnostic value of plasma phosphorylated (P-)tau levels for Alzheimer’s disease (AD). We aimed to compare six P-tau Simoa assays, including three P-tau181 (Eli Lilly, ADx, Quanterix), one P-tau217 (Eli Lilly), and two P-tau231 (ADx, Gothenburg). Methods: We studied the analytical (sensitivity, precision, parallelism, dilution linearity, and recovery) and clinical (40 AD dementia patients, age 66±8years, 50%F; 40 age- and sex-matched controls) performance of the assays. Results: All assays showed robust analytical performance, and particularly P-tau217 Eli Lilly; P-tau231 Gothenburg and all P-tau181 assays showed robust clinical performance to differentiate AD from controls, with AUCs 0.936–0.995 (P-tau231 ADx: AUC = 0.719). Results obtained with all P-tau181 assays, P-tau217 Eli Lilly assay, and P-tau231 Gothenburg assay strongly correlated (Spearman’s rho > 0.86), while correlations with P-tau231 ADx results were moderate (rho < 0.65). Discussion: P-tau isoforms can be measured robustly by several novel high-sensitive Simoa assays

    Comparison of ELISA- and SIMOA-based quantification of plasma Aβ ratios for early detection of cerebral amyloidosis

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    Background: Blood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages. Methods: In this prospective cross-sectional study, we quantified plasma Aβ 1–42/Aβ 1–40 ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ 1–42/Aβ 1–40 to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer’s disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms. Results: ELISA and SIMOA plasma Aβ 1–42/Aβ 1–40 detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72–0.84; SIMOA: AUC 0.79, 95% CI 0.73–0.85), and both increased the performance of a basic demographic model including only age and APOE-ε4 genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ 1–42/Aβ 1–40 correlated similarly with amyloid-PET for both platforms (Spearman ρ = − 0.32, p < 0.0001), yet correlations with CSF Aβ 1–42/t-tau were stronger for ELISA (ρ = 0.41, p = 0.002) than for SIMOA (ρ = 0.29, p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ 1–42 and Aβ 1–40 measured by SIMOA consistently underestimating those measured by ELISA. Conclusions: ELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ 1–42/Aβ 1–40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment. Trial registration: EudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014, https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE)
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