Spatial organization of protein aggregates on red blood cells as physical biomarkers of Alzheimer's disease pathology.
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ABSTRACT:
SUBMITTER: Nirmalraj PN
PROVIDER: S-EPMC8462905 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The complexity of Alzheimer's disease (AD) and its long prodromal phase poses challenges for early diagnosis and yet allows for the possibility of the development of disease modifying treatments for secondary prevention. It is, therefore, of importance to develop biomarkers, in particular, in the preclinical or early phases that reflect the pathological characteristics of the disease and, moreover, could be of utility in triaging subjects for preventative therapeutic clinical trials. Much research has sought biomarkers for diagnostic purposes by comparing affected people to unaffected controls. However, given that AD pathology precedes disease onset, a pathology endophenotype design for biomarker discovery creates the opportunity for detection of much earlier markers of disease. Blood-based biomarkers potentially provide a minimally invasive option for this purpose and research in the field has adopted various "omics" approaches in order to achieve this. This review will, therefore, examine the current literature regarding blood-based proteomic biomarkers of AD and its associated pathology.
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Project description:Red blood cells (RBCs) (erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we define a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validate protein complexes through electron microscopy and chemical crosslinking and, with these data, build 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-like compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.
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Project description:Eukaryotes have evolved multiple strategies for maintaining cellular protein homeostasis. One such mechanism involves neutralization of deleterious protein aggregates via their defined spatial segregation. Here, using the molecular disaggregase Hsp104 as a marker for protein aggregation, we describe the spatial and temporal dynamics of protein aggregates in the filamentous fungus Aspergillus nidulans. Filamentous fungi, such as A. nidulans, are a diverse group of species of major health and economic importance and also serve as model systems for studying highly polarized eukaryotic cells. We find that microtubules promote the formation of Hsp104-positive aggregates, which coalesce into discrete subcellular structures in a process dependent on the microtubule-based motor cytoplasmic dynein. Finally, we find that impaired clearance of these inclusions negatively impacts retrograde trafficking of endosomes, a conventional dynein cargo, indicating that microtubule-based transport can be overwhelmed by chronic cellular stress.
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Project description:Background: At present, the main diagnostic methods for Alzheimer's disease (AD) are positron emission tomography (PET) scanning of the brain and analysis of cerebrospinal fluid (CSF) sample, but these methods are expensive and harmful to patients. Recently, more researchers focus on diagnosing AD by detecting biomarkers in blood, which is a cheaper and harmless way. Therefore, identifying AD-related proteins in blood can help treatment and diagnosis. Methods: We proposed a hypothesis that similar diseases share similar proteins. Diseases with similar symptoms are caused by abnormalities of similar proteins. Assuming that the similarities between AD and other diseases obey the normal distribution, we developed an iterative method based on disease similarity (IBDS). We combined Elastic Network (EN) with Minimum angle regression (MAR) to find the optimal solution. Finally, we used case studies and Summary data Mendelian Random (SMR) to verify our method. Results: We selected 39 diseases which are highly related to AD. They correspond 1,481 kinds of proteins. One hundred and eighty-four proteins are reported to be related to AD in Uniprot and the number would be 284 with our method. The AUC of our method by cross-validation is 0.9251 which is much higher than previous methods. Conclusion: In this paper, we presented a novel method for prioritizing AD-related proteins. Seven proteins have tissue specificity in blood among these 284 proteins, which could be used to diagnose AD in future. Case studies and SMR have been used to prove the relationship between these 7 proteins and AD. Availability and Implementation: https://github.com/zty2009/Identifying-Protein-Biomarkers-in-Blood-for-Alzheimer-s-Disease.
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Project description:Co-fractionation mass spectrometry and crosslinking mass spectrometry of hemolysate, white ghosts, and other blood cell types.
2021-11-29 | MSV000088471 | MassIVE
Project description:BackgroundPrevious studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown.ObjectiveWe aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes.MethodsWe first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677).ResultsWe identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts.ConclusionsOur results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.
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Project description:Post-operative delirium (POD) is the most common complication following major surgery in non-demented older (>65 y/o) patients. Patients experiencing POD show increased risk for future cognitive decline, including mild cognitive impairment (MCI) and Alzheimer's disease (AD) and, conversely, patients with cognitive decline at surgery show increased risk for POD. Here, we demonstrate that a previously established panel of AD-driven MCI (ADMCI) autoantibody (aAB) biomarkers can be used to detect prodromal AD pre-surgically in individuals admitted into the hospital for hip fracture repair (HFR) surgery. Plasma from 39 STRIDE (STRIDE: A Strategy to Reduce the Incidence of Postoperative Delirium in Elderly Patients) HFR patients and sera from 25 age- and sex-matched non-demented and non-surgical controls were screened using human protein microarrays to measure expression of a panel of 44 previously identified MCI aAB biomarkers. The predictive classification accuracy of the aAB biomarker panel was evaluated using Random Forest (RF). The ADMCI aAB biomarkers successfully distinguished 21 STRIDE HFR patients (CDR = 0.5) from 25 matched non-surgical controls with an overall accuracy of 91.3% (sensitivity = 95.2%; specificity = 88.0%). The ADMCI aAB panel also correctly identified six patients with preoperative CDR = 0 who later converted to CDR = 0.5 or >1 at one-year follow-up. Lastly, the majority of cognitively normal (CDR = 0) STRIDE HFR subjects that were positive for CSF AD biomarkers based on the A/T/N classification system were likewise classified as ADMCI aAB-positive using the biomarker panel. Results suggest that pre-surgical detection of ADMCI aAB biomarkers can readily identify HFR patients with likely early-stage AD pathology using pre-surgery blood samples, opening up the potential for early, blood-based AD detection and improvements in peri- and postoperative patient management.
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Project description:Preventive measures, prognosis, or selected therapy in multifactorial maladies, including Alzheimer's disease (AD), require the application of a wide range of diagnostic assays. There is a large unmet need for relatively simple, blood-based biomarkers in this regard. We have recently developed a rapid and reliable flow cytometry and antibody-based method for the quantitative measurement of various red blood cell (RBC) membrane proteins from a drop of blood. Here, we document that the RBC expression of certain membrane proteins, especially that of the GLUT1 transporter and the insulin receptor (INSR), is significantly higher in AD patients than in age-matched healthy subjects. The observed differences may reflect long-term metabolic alterations relevant in the development of AD. These findings may pave the way for a diagnostic application of RBC membrane proteins as relatively stable and easily accessible personalized biomarkers in AD.
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Project description:Potential biomarkers for Alzheimer's disease (AD) include amyloid β1-42 (Aβ1-42), t-Tau, p-Tau181, neurofilament light chain (NFL), and neuroimaging biomarkers. Their combined use is useful for diagnosing and monitoring the progress of AD. Therefore, further development of a combination of these biomarkers is essential. We investigated whether plasma NFL/Aβ1-42 can serve as a plasma-based primary screening biomarker reflecting brain neurodegeneration and amyloid pathology in AD for monitoring disease progression and early diagnosis. We measured the NFL and Aβ1-42 concentrations in the CSF and plasma samples and performed correlation analysis to evaluate the utility of these biomarkers in the early diagnosis and monitoring of AD spectrum disease progression. Pearson's correlation analysis was used to analyse the associations between the fluid biomarkers and neuroimaging data. The study included 136 participants, classified into five groups: 28 cognitively normal individuals, 23 patients with preclinical AD, 22 amyloid-negative patients with amnestic mild cognitive impairment, 32 patients with prodromal AD, and 31 patients with AD dementia. With disease progression, the NFL concentrations increased and Aβ1-42 concentrations decreased. The plasma and CSF NFL/Aβ1-42 were strongly correlated (r = 0.558). Plasma NFL/Aβ1-42 was strongly correlated with hippocampal volume/intracranial volume (r = 0.409). In early AD, plasma NFL/Aβ1-42 was associated with higher diagnostic accuracy than the individual biomarkers. Moreover, in preclinical AD, plasma NFL/Aβ1-42 changed more rapidly than the CSF t-Tau or p-Tau181 concentrations. Our findings highlight the utility of plasma NFL/Aβ1-42 as a non-invasive plasma-based biomarker for early diagnosis and monitoring of AD spectrum disease progression.
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Project description:Neurodegenerative disorders such as Alzheimer's disease (AD) represent a mounting public health challenge. As these diseases are difficult to diagnose clinically, biomarkers of underlying pathophysiology are playing an ever-increasing role in research, clinical trials, and in the clinical work-up of patients. Though cerebrospinal fluid (CSF) and positron emission tomography (PET)-based measures are available, their use is not widespread due to limitations, including high costs and perceived invasiveness. As a result of rapid advances in the development of ultra-sensitive assays, the levels of pathological brain- and AD-related proteins can now be measured in blood, with recent work showing promising results. Plasma P-tau appears to be the best candidate marker during symptomatic AD (i.e., prodromal AD and AD dementia) and preclinical AD when combined with Aβ42/Aβ40. Though not AD-specific, blood NfL appears promising for the detection of neurodegeneration and could potentially be used to detect the effects of disease-modifying therapies. This review provides an overview of the progress achieved thus far using AD blood-based biomarkers, highlighting key areas of application and unmet challenges.
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