Introduction
Exosomes are an emerging candidate for biomarkers of Alzheimer's disease (AD). This study investigated whether exosomal synaptic proteins can predict AD at the asymptomatic stage.
...Methods
We conducted a two‐stage‐sectional study (discovery stage: AD, 28; amnestic mild cognitive impairment aMCI, 25; controls, 29; validation stage: AD, 73; aMCI, 71; controls, 72), a study including preclinical AD (160) and controls (160), and a confirmation study in familial AD (mutation carriers: 59; non‐mutation carriers: 62).
Results
The concentrations of growth associated protein 43 (GAP43), neurogranin, synaptosome associated protein 25 (SNAP25), and synaptotagmin 1 were lower in AD than in controls (P < .001). Exosomal biomarker levels were correlated with those in cerebrospinal fluid (R2 = 0.54–0.70). The combination of exosomal biomarkers detected AD 5 to 7 years before cognitive impairment (area under the curve = 0.87–0.89).
Discussion
This study revealed that exosomal GAP43, neurogranin, SNAP25, and synaptotagmin 1 act as effective biomarkers for prediction of AD 5 to 7 years before cognitive impairment.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract
Background
The most common biomarkers of Alzheimer’s disease (AD) are amyloid β (Aβ) and tau, detected in cerebrospinal fluid (CSF) or with positron emission tomography imaging. However, ...these procedures are invasive and expensive, which hamper their availability to the general population. Here, we report a panel of microRNAs (miRNAs) in serum that can predict P-tau/Aβ42 in CSF and readily differentiate AD from other dementias, including vascular dementia (VaD), Parkinson disease dementia (PDD), behavioral variant frontotemporal dementia (bvFTD), and dementia with Lewy body (DLB).
Methods
RNA samples were extracted from the participant’s blood. P-tau/Aβ42 of CSF was examined for diagnostic purposes. A pilot study (controls, 21; AD, 23), followed by second (controls, 216; AD, 190) and third groups (controls, 153; AD, 151), is used to establish and verify a predictive model of P-tau/Aβ42 in CSF. The test is then applied to a fourth group of patients with different dementias (controls, 139; AD,155; amnestic mild cognitive impairment aMCI, 55; VaD, 51; PDD, 53; bvFTD, 53; DLB, 52) to assess its diagnostic capacity.
Results
In the pilot study, 29 upregulated and 31 downregulated miRNAs in the AD group were found. In Dataset 2, these miRNAs were then included as independent variables in the linear regression model. A seven-microRNA panel (miR-139-3p, miR-143-3p, miR-146a-5p, miR-485-5p, miR-10a-5P, miR-26b-5p, and miR-451a-5p) accurately predicted values of P-tau/Aβ42 of CSF. In Datasets 3 and 4, by applying the predicted P-tau/Aβ42, the predictive model successfully differentiates AD from controls and VaD, PDD, bvFTD, and DLB.
Conclusions
This study suggests that the panel of microRNAs is a promising substitute for traditional measurement of P-tau/Aβ42 in CSF as an effective biomarker of AD.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Neuronal- and astrocyte-derived exosomes have been identified as an optimal source for screening biomarkers for Alzheimer's disease (AD). However, few studies focus on the bulk exosome population ...isolated from plasma of AD. This study investigated whether proteins in bulk exosomes can aid in the diagnosis of AD.
The plasma exosomes were collected by ultracentrifuge. Protein samples were extracted from exosomes. Cerebrospinal fluid levels of amyloid β (Aβ)42 and phosphorylated tau (P-tau)181 were measured for diagnostic purposes. A pilot study (controls, 20; AD, 20) followed by a second dataset (controls, 56; AD, 58) was used to establish a diagnostic model of AD. Mass spectrometry-based proteomics was performed to profile the plasma exosomal proteome. Parallel reaction monitoring was used to further confirm the differentially expressed proteins.
In total, 328 proteins in plasma exosomes were quantified. Among them, 31 proteins were altered in AD patients, and 12 were validated. The receiver operating characteristic curve analysis revealed a combination of six proteins (upregulated: Ig-like domain-containing protein (A0A0G2JRQ6), complement C1q subcomponent subunit C (C1QC), complement component C9 (CO9), platelet glycoprotein Ib beta chain (GP1BB), Ras suppressor protein 1 (RSU1); downregulated: disintegrin and metalloproteinase domain 10 (ADA10)) has the capacity to differentiate AD patients from healthy controls with high accuracy. Linear correlation analysis showed that the combination was significantly correlated with cognitive performance.
The combination of plasma exosomal proteins A0A0G2JRQ6, C1QC, CO9, GP1BB, RSU1, and ADA10 acts as a novel candidate biomarker to differentiate AD patients from healthy individuals.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Although structural and functional changes of the striatum and hippocampus are present in familial Alzheimer's disease, little is known about the effects of specific gene mutation or disease ...progression on their related neural circuits. This study was to evaluate the effects of known pathogenic gene mutation and disease progression on the striatum- and hippocampus-related neural circuits, including frontostriatal and hippocampus-posterior cingulate cortex (PCC) pathways.
A total of 102 healthy mutation non-carriers, 40 presymptomatic mutation carriers (PMC), and 30 symptomatic mutation carriers (SMC) of amyloid precursor protein (APP), presenilin 1 (PS1), or presenilin 2 gene, with T1 structural MRI, diffusion tensor imaging, and resting-state functional MRI were included. Representative neural circuits and their key nodes were obtained, including bilateral caudate-rostral middle frontal gyrus (rMFG), putamen-rMFG, and hippocampus-PCC. Volumes, diffusion indices, and functional connectivity of circuits were compared between groups and correlated with neuropsychological and clinical measures.
In PMC, APP gene mutation carriers showed impaired diffusion indices of caudate-rMFG and putamen-rMFG circuits; PS1 gene mutation carriers showed increased fiber numbers of putamen-rMFG circuit. SMC showed increased diffusivity of the left hippocampus-PCC circuit and volume reduction of all regions as compared with PMC. Imaging measures especially axial diffusivity of the representative circuits were correlated with neuropsychological measures.
APP and PS1 gene mutations affect frontostriatal circuits in a different manner in familial Alzheimer's disease; disease progression primarily affects the structure of hippocampus-PCC circuit. The structural connectivity of both frontostriatal and hippocampus-PCC circuits is associated with general cognitive function. Such findings may provide further information about the imaging biomarkers for early identification and prognosis of familial Alzheimer's disease, and pave the way for early diagnosis, gene- or circuit-targeted treatment, and even prevention.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Blood tests would be much easier to implement in the clinical diagnosis of Alzheimer's disease (AD) as minimally invasive measurements. Multiple inspection technologies promoted AD-associated blood ...biomarkers' exploration. However, there was a lack of further screening and validation for these explored blood-based biomarkers. We selected four potential biomarkers to explore their plasma levels in AD and amnestic mild cognitive impairment (aMCI) and developed a composite panel for AD and aMCI screening.
The plasma concentrations of soluble low-density lipoprotein receptor-associated protein 1 (sLRP1), Gelsolin (GSN), Kallikrein 4 (KLK4) and Caspase 3 were measured in the discovery and validation cohort. The receiver operating characteristic (ROC) curve was generated to assess the classification panel with the area under the curve (AUC).
A total of 233 participants (26 CN, 27 aMCI, and 26 AD in the discovery cohort, and 51 CN, 50 aMCI, and 53 AD in the validation cohort) with complete data were included in the study. The plasma concentrations of sLRP1 and Caspase 3 were significantly decreased in AD and aMCI when compared with those in the CN group. Compared with the CN group, the concentrations of KLK4 and GSN were increased in AD, but not in MCI. Interestingly, one of four proteins, sLRP1 in plasma level was higher in Apolipoprotein E (APOE) ε4 non-carriers than that in APOE ε4 carriers, especially among CN and MCI. No significant difference was found between females and males in the plasma levels of four proteins. The composite panel is based on four blood biomarkers accurately classifying AD from CN (AUC = 0.903-0.928), and MCI from CN (AUC = 0.846-0.865). Moreover, dynamic changes in the plasma levels of four proteins exhibited a significant correlation with cognitive assessment.
Altogether, these findings indicate that the plasma levels of sLRP1, KLK4, GSN and Caspase 3 changed with the progression of AD. And their combination could be used to develop a panel for classifying AD and aMCI with high accuracy, which would provide an alternative approach for developing a blood-based test for AD and aMCI screening.
Background Accelerated long-term forgetting has been identified in preclinical Alzheimer's disease (AD) and is attributed to a selective impairment of memory consolidation in which the hippocampus ...plays a key role. As blood may contain multiple senescence-related factors that involved in neurogenesis and synaptic plasticity in the hippocampus, we tested whether there is an association between blood-borne factors and accelerated long-term forgetting in asymptomatic individuals from families with autosomal dominant AD (ADAD). Methods We analyzed data of 39 asymptomatic participants (n = 18 ADAD mutation carriers, n = 21 non-carriers) from the Chinese Familial Alzheimer's Disease Network (CFAN) study. Long-term forgetting rates were calculated based on recall or recognition of two materials (word list and complex figure) at three delays comprising immediate, 30 min, and 7 days. Peripheral blood concentrations of candidate pro-aging factors (CC chemokine ligand 11 CCL11 and monocyte chemotactic protein 1 MCP1) and rejuvenation factors (growth differentiation factor 11 GDF11, thrombospondin-4 THBS4, and secreted protein acidic and rich in cysteine like 1 SPARCL1) were evaluated in all participants. Results Despite normal performance on standard 30-min delayed testing, mutation carriers exhibited accelerated forgetting of verbal and visual material over 7 days in comparison with matched non-carriers. In the whole sample, lower plasma THBS4 was associated with accelerated long-term forgetting in list recall (beta = -0.46, p = 0.002), figure recall (beta = -0.44, p = 0.004), and list recognition (beta = -0.37, p = 0.010). Additionally, higher plasma GDF11 and CCL11 were both associated with accelerated long-term forgetting (GDF11 versus figure recall: beta = 0.39, p = 0.007; CCL11 versus list recognition: beta = 0.44, p = 0.002). Conclusions Accelerated long-term forgetting is a cognitive feature of presymptomatic AD. Senescence-related blood-borne factors, especially THBS4, GDF11, and CCL11, may be promising biomarkers for the prediction of accelerated long-term forgetting. Keywords: Alzheimer's disease, Accelerated long-term forgetting, Blood-borne factors, Senescence, Biomarkers
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
To evaluate the diagnostic value of plasma β-amyloid (Aβ) seeding activity measured using a newly developed instrument to distinguish Alzheimer's disease (AD) from other forms of dementia.
...Seventy-nine AD patients, 64 non-AD dementia (NADD) patients, and 75 cognitively normal (NC) subjects were recruited in the study. To measure the levels of Aβ seeding activity in the plasma samples, we have developed an AD-seeds protein analyzer. We used receiver operating characteristic (ROC) curves to quantify the ability of plasma Aβ seeding activity to distinguish between AD and NADD or NC individuals. Spearman's correlation was used to examine the associations between plasma Aβ seeding activity and global cognitive function or conventional AD biomarkers.
The Aβ seeding activities were 0.83 (0.58-1.16) A.U. in AD, 0.42 (0.04-0.74) A.U. in NADD and 0.42 (0.09-0.69) A.U. in NC, respectively. The Aβ seeding activity was able to identify AD patients and distinguish them from NC or NADD with high accuracy (AUC = 0.85-0.86). In addition, the plasma Aβ seeding activity showed a strong correlation with cognitive performance (mini-mental state examination, r = - 0.188; Montreal cognitive assessment, r = - 0.189; clinical dementia rating, r = 0.205) and conventional biomarkers (cerebrospinal fluid CSF Aβ42/40, r = -0.227; CSF T-tau/Aβ42, r = 0.239; CSF P-tau/Aβ42, r = 0.259).
Our results confirmed that plasma Aβ seeding activity is an antibody-free and low-cost biomarker for the diagnosis of AD.
Trial registration number NCT04850053.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Neuronal-derived exosomal Aβ42, T-tau, and P-T181-tau have been demonstrated to be biomarkers of Alzheimer's disease (AD). However, no study has assessed the association of Aβ42, T-tau, and ...P-T181-tau between exosomes and CSF.
This was a multicenter study with two-stage design. The subjects included 28 AD patients, 25 aMCI patients, and 29 controls in the discovery stage; the results of which were confirmed in the validation stage (73 AD, 71 aMCI, and 72 controls).
The exosomal concentrations of Aβ42, T-tau, and P-T181-tau in AD group were higher than those in aMCI and control groups (all P < .001). The level of each exosomal biomarker was highly correlated with that in CSF.
This study verified the agreement between CSF and blood exosomal biomarkers and confirmed that exosomal Aβ42, T-tau, and P-T181-tau have the same capacity as those in CSF for the diagnosis of AD and aMCI.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Exosomal microRNAs (miRNAs) have been demonstrated to be biomarkers of Alzheimer’s disease (AD). However, whether exosomal miRNAs can predict AD at the asymptomatic stage remains unclear.
This study ...is a multicenter study with four independent datasets to verify the capacity of exosomal miRNAs to identify preclinical AD. Subjects were recruited from a Beijing center in the pilot study (dataset 1: subjects with AD, n = 20; control subjects, n = 20), from other centers across China (dataset 2: subjects with AD, n = 95; control subjects, n = 93), a longitudinal cohort (dataset 3: subjects with preclinical AD, n = 101; control subjects, n = 102), and a confirmation study on familial AD (dataset 4: mutation carriers, n = 56; nonmutation carriers, n = 57).
A panel of miRNAs was changed in subjects with AD and can detect preclinical AD 5 to 7 years before the onset of cognitive impairment (areas under the curve = 0.85−0.88).
Exosomal miRNAs can be effective biomarkers for predicting AD 5 to 7 years prior to cognitive impairment onset.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Introduction
Alzheimer's disease (AD) is associated with altered metabolites. This study aimed to determine the validity of using circulating metabolites to differentiate AD from other dementias.
...Methods
Blood metabolites were measured in three data sets. Data set 1 (controls, 27; AD, 28) was used for analyzing differential metabolites. Data set 2 (controls, 93; AD, 92) was used to establish a diagnostic AD model with use of a metabolite panel. The model was applied to Data set 3 (controls, 76; AD, 76; other dementias, 205) to verify its capacity for differentiating AD from other dementias.
Results
Data set 1 revealed 7 upregulated and 77 downregulated metabolites. In Data set 2, a panel of 11 metabolites was included in a model that could distinguish AD from controls. In Data set 3, this panel was used to successfully differentiate AD from other dementias.
Discussion
This study revealed an AD‐specific panel of 11 metabolites that may be used for AD diagnosis.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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