Assessment of immunoprecipitation with subsequent immunoassays for the blood-based diagnosis of Alzheimer's disease.

The Aß42/40 ratio and the concentration of phosphorylated Tau181 in blood plasma represent attractive biomarkers for Alzheimer's disease. As a means for reducing potential matrix effects, which may interfere with plasma immunoassays, we have previously developed a pre-analytical sample workup by semi-automated immunoprecipitation. Here we test the compatibility of pre-analytical immunoprecipitations with automated Aß1-40, Aß1-42 and phosphorylated Tau181 immunoassays on the Lumipulse platform and compare the diagnostic performance of the respective immunoprecipitation immunoassay approaches with direct plasma measurements. 71 participants were dichotomized according to their Aß42/40 ratios in cerebrospinal fluid into the diagnostic groups amyloid-positive (n = 32) and amyloid-negative (n = 39). The plasma Aß1-42/1-40 ratio and phosphorylated Tau181 levels were determined on the Lumipulse G600II platform (Fujirebio) by direct measurements in EDTA-plasma or after Aß- or Tau-immunoprecipitation, respectively. Pre-analytical immunoprecipitation of Aß turned out to be compatible with the Lumipulse Aß assays and resulted in a numerical, yet statistically not significant increase in the area under the ROC curve for plasma Aß1-42/1-40. Additionally, we observed a significant increase in the standardised effect size (Cohen's D). Pre-analytical immunoprecipitation of Tau resulted in increased differences between the diagnostic groups in terms of median and mean phosphorylated Tau 181 levels. Furthermore, we observed a greater Cohen's d (p < 0.001) and a larger area under the ROC curve (p = 0.038) after Tau-IP. Our preliminary findings in a small, preselected sample indicate that pre-analytical immunoprecipitation may have the potential to improve the diagnostic performance of plasma biomarker immunoassays for Aß1-42/1-40 and phosphorylated Tau181 to predict brain amyloid deposition.

Plasma amyloid beta X-42/X-40 ratio and cognitive decline in suspected early and preclinical Alzheimer's disease.

INTRODUCTION: Blood-based biomarkers are a cost-effective and minimally invasive method for diagnosing the early and preclinical stages of amyloid positivity (AP). Our study aims to investigate our novel immunoprecipitation-immunoassay (IP-IA) as a test for predicting cognitive decline. METHODS: We measured levels of amyloid beta (Aß)X-40 and AßX-42 in immunoprecipitated eluates from the DELCODE cohort. Receiver-operating characteristic (ROC) curves, regression analyses, and Cox proportional hazard regression models were constructed to predict AP by Aß42/40 classification in cerebrospinal fluid (CSF) and conversion to mild cognitive impairment (MCI) or dementia. RESULTS: We detected a significant correlation between AßX-42/X-40 in plasma and CSF (r = 0.473). Mixed-modeling analysis revealed a substantial prediction of AßX-42/X-40 with an area under the curve (AUC) of 0.81 for AP (sensitivity: 0.79, specificity: 0.74, positive predictive value [PPV]: 0.71, negative predictive value [NPV]: 0.81). In addition, lower AßX-42/X-40 ratios were associated with negative PACC5 slopes, suggesting cognitive decline. DISCUSSION: Our results suggest that assessing the plasma AßX-42/X-40 ratio via our semiautomated IP-IA is a promising biomarker when examining patients with early or preclinical AD. HIGHLIGHTS: New plasma Aß42/Aß40 measurement using immunoprecipitation-immunoassay Plasma Aß42/Aß40 associated with longitudinal cognitive decline Promising biomarker to detect subjective cognitive decline at-risk for brain amyloid positivity.

Don't forget about tau: the effects of ApoE4 genotype on Alzheimer's disease cerebrospinal fluid biomarkers in subjects with mild cognitive impairment-data from the Dementia Competence Network.

ApoE4, the strongest genetic risk factor for Alzheimer's disease (AD), has been shown to be associated with both beta-amyloid (Aß) and tau pathology, with the strongest evidence for effects on Aß, while the association between ApoE4 and tau pathology remains inconsistent. This study aimed to investigate the associations between ApoE4 with CSF Aß42, total tau (t-tau), phospho-tau181 (p-tau), and with the progression of decline in a large cohort of MCI subjects, both progressors to AD and other dementias, as well as non-progressors. We analyzed associations of CSF Aß42, p-tau and t-tau with ApoE4 allele frequency cross-sectionally and longitudinally over 3 years of follow-up in 195 individuals with a diagnosis of MCI-stable, MCI-AD converters and MCI progressing to other dementias from the German Dementia Competence Network. In the total sample, ApoE4 carriers had lower concentrations of CSF Aß42, and increased concentrations of t-tau and p-tau compared to non-carriers in a gene dose-dependent manner. Comparisons of these associations stratified by MCI-progression groups showed a significant influence of ApoE4 carriership and diagnostic group on all CSF biomarker levels. The effect of ApoE4 was present in MCI-stable individuals but not in the other groups, with ApoE4 + carriers having decreased CSF Aß 42 levels, and increased concentration of t-tau and p-tau. Longitudinally, individuals with abnormal t-tau and Aß42 had a more rapid progression of cognitive and clinical decline, independently of ApoE4 genotype. Overall, our results contribute to an emerging framework in which ApoE4 involves mechanisms associated with both CSF amyloid-ß burden and tau aggregation at specific time points in AD pathogenesis.

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types.

BACKGROUND: There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. METHODS: In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. RESULTS: We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap . CONCLUSIONS: Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.

Validation of a prototype tau Thr231 phosphorylation CSF ELISA as a potential biomarker for Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the presence of extracellular amyloid plaques (senile plaques) and intracellular neurofibrillary tangles formed by hyperphosphorylated tau protein. This process leads to neuronal degradation and neuronal death. Phosphorylation of tau protein at threonine 231 (p-tau231) has been shown to be characteristic in post-mortem brain tissue of patients with AD and it can be sensitively detected in cerebrospinal fluid (CSF). Therefore, it may serve as a biomarker to support the diagnosis of AD. In this study, we analysed how well p-tau231 could differentiate between patients suffering from dementia either due or not due to AD by a sandwich enzyme immunoassay. CSF p-tau231 was significantly higher in patients with dementia due to AD than in those with dementia due to other causes. In addition, we studied different factors affecting p-tau231 levels in CSF. We found that apolipoprotein E genotype influences p-tau231 CSF levels. Gender and age did not affect p-tau231 levels in CSF. Our findings indicate that p-tau231 levels in CSF can be a valuable marker for the clinical diagnosis of AD.

Identification of Novel Nuclear Factor of Activated T Cell (NFAT)-associated Proteins in T Cells.

Transcription factors of the nuclear factor of activated T cell (NFAT) family are essential for antigen-specific T cell activation and differentiation. Their cooperative DNA binding with other transcription factors, such as AP1 proteins (FOS, JUN, and JUNB), FOXP3, IRFs, and EGR1, dictates the gene regulatory action of NFATs. To identify as yet unknown interaction partners of NFAT, we purified biotin-tagged NFATc1/αA, NFATc1/ßC, and NFATc2/C protein complexes and analyzed their components by stable isotope labeling by amino acids in cell culture-based mass spectrometry. We revealed more than 170 NFAT-associated proteins, half of which are involved in transcriptional regulation. Among them are many hitherto unknown interaction partners of NFATc1 and NFATc2 in T cells, such as Raptor, CHEK1, CREB1, RUNX1, SATB1, Ikaros, and Helios. The association of NFATc2 with several other transcription factors is DNA-dependent, indicating cooperative DNA binding. Moreover, our computational analysis discovered that binding motifs for RUNX and CREB1 are found preferentially in the direct vicinity of NFAT-binding motifs and in a distinct orientation to them. Furthermore, we provide evidence that mTOR and CHEK1 kinase activity influence NFAT's transcriptional potency. Finally, our dataset of NFAT-associated proteins provides a good basis to further study NFAT's diverse functions and how these are modulated due to the interplay of multiple interaction partners.

Global quantification of mammalian gene expression control.

Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here we simultaneously measured absolute mRNA and protein abundance and turnover by parallel metabolic pulse labelling for more than 5,000 genes in mammalian cells. Whereas mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Using a quantitative model we have obtained the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stability shared functional properties, indicating that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression provides a rich resource and helps to provide a greater understanding of the underlying design principles.

Transcription factor co-occupied regions in the murine genome constitute T-helper-cell subtype-specific enhancers.

Transcription factors (TFs) regulate cell-type-specific gene expression programs by combinatorial binding to cis-genomic elements, particularly enhancers, subsequently leading to the recruitment of cofactors, and the general transcriptional machinery to target genes. Using data integration of genome-wide TF binding profiles, we defined regions with combinatorial binding of lineage-specific master TFs (T-BET, GATA3, and ROR-γt) and STATs (STAT1 and STAT4, STAT6, and STAT3) in murine T helper (Th) 1, Th2, and Th17 cells, respectively. Stringently excluding promoter regions, we revealed precise genomic elements which were preferentially associated with the enhancer marks p300 and H3K4me1. Furthermore, closely adjacent TF co-occupied regions constituted larger enhancer domains in the respective Th-cell subset (177 in Th1, 141 in Th2, and 266 in Th17 cells) with characteristics of so-called super-enhancers. Importantly, 89% of these super-enhancer regions were Th-cell subtype-specific. Genes associated with super-enhancers, including relevant Th-cell genes (such as Ifng in Th1, Il13 in Th2, and Il17a in Th17 cells), showed strong transcriptional activity. Altogether, the discovered catalog of enhancers provides information about crucial Th-cell subtype-specific regulatory hubs, which will be useful for revealing cell-type-specific gene regulation processes.

ProfileDB: a resource for proteomics and cross-omics biomarker discovery.

The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Analysis of amino-terminal variants of amyloid-ß peptides by capillary isoelectric focusing immunoassay.

Here we present a novel assay for the separation and detection of amino-terminal amyloid-ß (Aß) peptide variants by capillary isoelectric focusing (CIEF) immunoassay. Specific amino-terminally truncated Aß peptides appear to be generated by ß-secretase (BACE1)-independent mechanisms and have previously been observed in cerebrospinal fluid (CSF) after BACE1 inhibitor treatment in an animal model. CIEF immunoassay sensitivity is sufficient to detect total Aß in CSF without preconcentration. To analyze low-abundance amino-terminally truncated Aß peptides from cell culture supernatants, we developed a CIEF-compatible immunoprecipitation protocol, allowing for selective elution of Aß peptides with very low background. CIEF immunoassay and immunoprecipitation mass spectrometry analysis identified peptides starting at residue Arg(5) as the main amino-terminal Aß variants produced in the presence of tripartite BACE1 inhibitor in our cell culture model. The CIEF immunoassay allows for robust relative quantification of Aß peptide patterns in biological samples. To assess the future possibility of absolute quantification, we have prepared the Aß peptides Aß(x-10), Aß(x-16), and Aß(5-38(D23S)) by using solid phase peptide synthesis as internal standards for the CIEF immunoassay.

Is there a typical germinal center? A large-scale immunohistological study on the cellular composition of germinal centers during the hapten-carrier-driven primary immune response in mice.

Germinal centers (GCs) are complex, multicell-type, transient structures that form in secondary lymphatic tissues in response to T cell-dependent stimulation. This process is crucial to the adaptive immune response because it is the source of affinity maturation and long-lived B cell memory. Our previous studies showed that the growth of murine splenic GCs is nonsynchronized, involving broad-volume distributions of individual GCs at any time. This raises the question whether such a thing as a typical GC exists. To address this matter, we acquired large-scale confocal data on GCs throughout the course of the 2-phenyl-5-oxazolone chicken serum albumin-driven primary immune response in BALB/c mice. Semiautomated image analysis of 3457 GC sections revealed that, although there is no typical GC in terms of size, GCs have a typical cellular composition in that the cell ratios of resident T cells, macrophages, proliferating cells, and apoptotic nuclei are maintained during the established phase of the response. Moreover, our data provide evidence that the dark zone (DZ) and light zone (LZ) compartments of GCs are about the same size and led us to estimate that the minimal cell loss rate in GCs is 3% per hour. Furthermore, we found that the population of GC macrophages is larger and more heterogeneous than previously thought, and that despite enrichment of T cells in the LZ, the DZ of murine splenic GCs is not poor in T cells. DZ and LZ differ in the T cell-to-macrophage ratio rather than in the density of T cells.

Risk of chronic kidney disease in patients with acute kidney injury following a major surgery: a US claims database analysis.

Background: Acute kidney injury (AKI) is a common complication after major surgery. This study assessed the risk of developing or worsening of chronic kidney disease (CKD) and other clinical outcomes in patients experiencing AKI after major surgery. Methods: This retrospective observational study used Optum's de-identified Clinformatics Data Mart Database to investigate cardiorenal outcomes in adult patients at the first AKI event following major surgery. The primary outcome was CKD stage ≥3; secondary outcomes included myocardial infarction (MI), stroke, heart failure, all-cause hospitalization, end-stage kidney disease, need for dialysis or kidney transplant and composite measures. Follow-up was up to 3 years. Additionally, the effect of intercurrent events on the risk of clinical outcomes was assessed. Results: Of the included patients (N = 31 252), most were male (61.9%) and White (68.9%), with a median age of 72 years (interquartile range 64-79). The event rates were 25.5 events/100 patient-years (PY) for CKD stage ≥3, 3.1 events/100 PY for end-stage kidney disease, 3.0 events/100 PY for dialysis and 0.1 events/100 PY for kidney transplants. Additionally, there were 6.9 events/100 PY for MI, 8.7 events/100 PY for stroke and 49.8 events/100 PY for all-cause hospitalization during follow-up. Patients with AKI relapses as intercurrent events were more likely to develop CKD stage ≥3 than those with just one AKI event after major surgery. Conclusion: This analysis demonstrated that patients experiencing AKI following major surgery are at high risk of developing severe CKD or worsening of pre-existing CKD and other cardiorenal clinical outcomes such as MI and stroke.

Clinical characteristics and disease outcomes in non-diabetic chronic kidney disease: retrospective analysis of a US healthcare claims database.

BACKGROUND: The observational, real-world evidence FLIEDER study aimed to describe patient clinical characteristics and investigate clinical outcomes in non-diabetic patients with chronic kidney disease (CKD) using data collected from routine clinical practice in the United States. METHODS: Between 1 January, 2008-31 December, 2018, individuals aged ≥ 18 years, with non-diabetic, stage 3-4 CKD were indexed in the Optum® Clinformatics® Data Mart US healthcare claims database using International Classification of Diseases-9/10 codes for CKD or by laboratory values (estimated glomerular filtration rate [eGFR] 15-59 mL/min/1.73 m2). The primary outcomes were hospitalization for heart failure, a composite kidney outcome of end-stage kidney disease/kidney failure/need for dialysis and worsening of CKD stage from baseline. The effects of the intercurrent events of a sustained post-baseline decline in eGFR ≥ 30%, ≥ 40%, and ≥ 57% on the subsequent risk of the primary outcomes were also assessed. RESULTS: In the main study cohort (N = 504,924), median age was 75.0 years, and 60.5% were female. Most patients (94.7%) had stage 3 CKD at index. Incidence rates for hospitalization for heart failure, the composite kidney outcome, and worsening of CKD stage from baseline were 4.0, 10.3, and 4.4 events/100 patient-years, respectively. The intercurrent event analysis demonstrated that a relative decline in kidney function from baseline significantly increased the risk of cardiorenal events. CONCLUSIONS: This real-world study highlights that patients with non-diabetic CKD are at high risk of serious adverse clinical outcomes, and that this risk is amplified in patients who experienced greater post-baseline eGFR decline.

PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios.

BACKGROUND: Recent development of novel technologies paved the way for quantitative proteomics. One of the most important among them is iTRAQ, employing isobaric tags for relative or absolute quantitation. Despite large progress in technology development, still many challenges remain for derivation and interpretation of quantitative results. One of these challenges is the consistent assignment of peptides to proteins. RESULTS: We have developed Peptide Profiling Guided Identification of Proteins (PPINGUIN), a statistical analysis workflow for iTRAQ data addressing the problem of ambiguous peptide quantitations. Motivated by the assumption that peptides uniquely derived from the same protein are correlated, our method employs clustering as a very early step in data processing prior to protein inference. Our method increases experimental reproducibility and decreases variability of quantitations of peptides assigned to the same protein. Giving further support to our method, application to a type 2 diabetes dataset identifies a list of protein candidates that is in very good agreement with previously performed transcriptomics meta analysis. Making use of quantitative properties of signal patterns identified, PPINGUIN can reveal new isoform candidates. CONCLUSIONS: Regarding the increasing importance of quantitative proteomics we think that this method will be useful in practical applications like model fitting or functional enrichment analysis. We recommend to use this method if quantitation is a major objective of research.

A minimal model of peptide binding predicts ensemble properties of serum antibodies.

BACKGROUND: The importance of peptide microarrays as a tool for serological diagnostics has strongly increased over the last decade. However, interpretation of the binding signals is still hampered by our limited understanding of the technology. This is in particular true for arrays probed with antibody mixtures of unknown complexity, such as sera. To gain insight into how signals depend on peptide amino acid sequences, we probed random-sequence peptide microarrays with sera of healthy and infected mice. We analyzed the resulting antibody binding profiles with regression methods and formulated a minimal model to explain our findings. RESULTS: Multivariate regression analysis relating peptide sequence to measured signals led to the definition of amino acid-associated weights. Although these weights do not contain information on amino acid position, they predict up to 40-50% of the binding profiles' variation. Mathematical modeling shows that this position-independent ansatz is only adequate for highly diverse random antibody mixtures which are not dominated by a few antibodies. Experimental results suggest that sera from healthy individuals correspond to that case, in contrast to sera of infected ones. CONCLUSIONS: Our results indicate that position-independent amino acid-associated weights predict linear epitope binding of antibody mixtures only if the mixture is random, highly diverse, and contains no dominant antibodies. The discovered ensemble property is an important step towards an understanding of peptide-array serum-antibody binding profiles. It has implications for both serological diagnostics and B cell epitope mapping.

Broad volume distributions indicate nonsynchronized growth and suggest sudden collapses of germinal center B cell populations.

Immunization with a T cell-dependent Ag leads to the formation of several hundred germinal centers (GCs) within secondary lymphoid organs, a key process in the maturation of the immune response. Although prevailing perceptions about affinity maturation intuitively assume simultaneous seeding, growth, and decay of GCs, our previous mathematical simulations led us to hypothesize that their growth might be nonsynchronized. To investigate this, we performed computer-aided three-dimensional reconstructions of splenic GCs to measure size distributions at consecutive time points following immunization of BALB/c mice with a conjugate of 2-phenyl-oxazolone and chicken serum albumin. Our analysis reveals a broad volume distribution of GCs, indicating that individual GCs certainly do not obey the average time course of the GC volumes and that their growth is nonsynchronized. To address the cause and implications of this behavior, we compared our empirical data with simulations of a stochastic mathematical model that allows for frequent and sudden collapses of GCs. Strikingly, this model succeeds in reproducing the empirical average kinetics of GC volumes as well as the underlying broad size distributions. Possible causes of GC B cell population collapses are discussed in the context of the affinity-maturation process.

Is plasma amyloid-ß 1-42/1-40 a better biomarker for Alzheimer's disease than AßX-42/X-40?

BACKGROUND: A reduced amyloid-ß (Aß)42/40 peptide ratio in blood plasma represents a peripheral biomarker of the cerebral amyloid pathology observed in Alzheimer's disease brains. The magnitude of the measurable effect in plasma is smaller than in cerebrospinal fluid, presumably due to dilution by Aß peptides originating from peripheral sources. We hypothesized that the observable effect in plasma can be accentuated to some extent by specifically measuring Aß1-42 and Aß1-40 instead of AßX-42 and AßX-40. METHODS: We assessed the plasma AßX-42/X-40 and Aß1-42/1-40 ratios in an idealized clinical sample by semi-automated Aß immunoprecipitation followed by closely related sandwich immunoassays. The amyloid-positive and amyloid-negative groups (dichotomized according to Aß42/40 in cerebrospinal fluid) were compared regarding the median difference, mean difference, standardized effect size (Cohen's d) and receiver operating characteristic curves. For statistical evaluation, we applied bootstrapping. RESULTS: The median Aß1-42/1-40 ratio was 20.86% lower in amyloid-positive subjects than in the amyloid-negative group, while the median AßX-42/X-40 ratio was only 15.56% lower. The relative mean difference between amyloid-positive and amyloid-negative subjects was -18.34% for plasma Aß1-42/1-40 compared to -15.50% for AßX-42/X-40. Cohen's d was 1.73 for Aß1-42/1-40 and 1.48 for plasma AßX-42/X-40. Unadjusted p-values < 0.05 were obtained after .632 bootstrapping for all three parameters. Receiver operating characteristic analysis indicated very similar areas under the curves for plasma Aß1-42/1-40 and AßX-42/X-40. CONCLUSIONS: Our findings support the hypothesis that the relatively small difference in the plasma Aß42/40 ratio between subjects with and without evidence of brain amyloidosis can be accentuated by specifically measuring Aß1-42/1-40 instead of AßX-42/X-40. A simplified theoretical model explaining this observation is presented.

Diagnostic performance of automated plasma amyloid-ß assays combined with pre-analytical immunoprecipitation.

BACKGROUND: Measurements of the amyloid-ß (Aß) 42/40 ratio in blood plasma may support the early diagnosis of Alzheimer's disease and aid in the selection of suitable participants in clinical trials. Here, we compared the diagnostic performance of fully automated prototype plasma Aß42/40 assays with and without pre-analytical sample workup by immunoprecipitation. METHODS: A pre-selected clinical sample comprising 42 subjects with normal and 38 subjects with low cerebrospinal fluid (CSF) Aß42/40 ratios was studied. The plasma Aß42/40 ratios were determined with fully automated prototype Elecsys® immunoassays (Roche Diagnostics GmbH, Penzberg, Germany) by direct measurements in EDTA plasma or after pre-analytical Aß immunoprecipitation. The diagnostic performance for the detection of abnormal CSF Aß42/40 was analyzed by receiver operating characteristic (ROC) analysis. In an additional post hoc analysis, a biomarker-supported clinical diagnosis was used as a second endpoint. RESULTS: Pre-analytical immunoprecipitation resulted in a significant increase in the area under the ROC curve (AUC) from 0.73 to 0.88 (p = 0.01547) for identifying subjects with abnormal CSF Aß42/40. A similar improvement in the diagnostic performance by pre-analytical immunoprecipitation was also observed when a biomarker-supported clinical diagnosis was used as a second endpoint (AUC increase from 0.77 to 0.92, p = 0.01576). CONCLUSIONS: Our preliminary observations indicate that pre-analytical Aß immunoprecipitation can improve the diagnostic performance of plasma Aß assays for detecting brain amyloid pathology. The findings may aid in the further development of blood-based immunoassays for Alzheimer's disease ultimately suitable for screening and routine use.