Dataset of why inclusion matters for Alzheimer's disease biomarker discovery in plasma.
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ABSTRACT:
SUBMITTER: Khan MJ
PROVIDER: S-EPMC7988280 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAfrican American/Black adults have a disproportionate incidence of Alzheimer's disease (AD) and are underrepresented in biomarker discovery efforts.ObjectiveThis study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults.MethodsWe conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates.ResultsIn total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD.ConclusionThese results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.
| S-EPMC9126484 | biostudies-literature
Project description:FK506 binding protein 51kDa (FKBP51/FKBP5) is part of a mature heat shock protein 90kDa (Hsp90) chaperone complex that preserves tau. Microarray analysis of human brains reveal that FKBP51 gene expression selectively increased with age and Alzheimer's disease, which correlated with demethylation of the regulatory regions in the FKBP5 gene. Moreover, FKBP51 levels significantly correlated with Braak pathological staging. In addition, we show that in brains devoid of FKBP51, tau levels are reduced. Recombinant FKBP51 and Hsp90 synergize to block tau clearance through the proteasome and produce T22-positive tau oligomers. Overexpression of FKBP51 in a tau transgenic mouse model revealed that FKBP51 preserved tau species, including phosphorylated and oligomeric tau that have been linked to Alzheimer's disease pathogenesis. FKBP51 blocked amyloid formation and decreased tangle load in the brain. These alterations in tau turnover and aggregate structure culminated in enhanced neurotoxicity. We propose a model where age-associated increases in FKBP51 levels can out-compete the association of other pro-degradation Hsp90 co-chaperones, resulting in neurotoxic tau accumulation. Thus, strategies aimed at attenuating FKBP51 levels or its interaction with Hsp90 could be therapeutically relevant for Alzheimer's disease and other tauopathies. These AD cases were processed simultaneously with the control cases (young and aged) included in GSE11882 Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available
2014-04-21 | E-GEOD-48350 | biostudies-arrayexpress
Project description:Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.
| S-EPMC7680793 | biostudies-literature
Project description:This dataset contains microarray data from normal controls (aged 20-99 yrs) and Alzheimer's disease cases, from 4 brain regions: hippocampus, entorhinal cortex, superior frontal cortex, post-central gyrus. Changes in expression of synaptic and immune related genes were analyzed, investigating age-related changes and AD-related changes, and region-specific patterns of change. These AD cases were processed simultaneously with the control cases (young and aged) included in GSE11882 (GSE11882 dataset contains data exclusively from normal control brains).
2014-04-21 | GSE48350 | GEO
Project description:Alzheimer's disease (AD) is the most frequent neurodegenerative disease with an increasing prevalence in industrialized, aging populations. AD susceptibility has an established genetic basis which has been the focus of a large number of genome-wide association studies (GWAS) published over the last decade. Most of these GWAS used dichotomized clinical diagnostic status, i.e., case vs. control classification, as outcome phenotypes, without the use of biomarkers. An alternative and potentially more powerful study design is afforded by using quantitative AD-related phenotypes as GWAS outcome traits, an analysis paradigm that we followed in this work. Specifically, we utilized genotype and phenotype data from n = 931 individuals collected under the auspices of the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study to perform a total of 19 separate GWAS analyses. As outcomes we used five magnetic resonance imaging (MRI) traits and seven cognitive performance traits. For the latter, longitudinal data from at least two timepoints were available in addition to cross-sectional assessments at baseline. Our GWAS analyses revealed several genome-wide significant associations for the neuropsychological performance measures, in particular those assayed longitudinally. Among the most noteworthy signals were associations in or near EHBP1 (EH domain binding protein 1; on chromosome 2p15) and CEP112 (centrosomal protein 112; 17q24.1) with delayed recall as well as SMOC2 (SPARC related modular calcium binding 2; 6p27) with immediate recall in a memory performance test. On the X chromosome, which is often excluded in other GWAS, we identified a genome-wide significant signal near IL1RAPL1 (interleukin 1 receptor accessory protein like 1; Xp21.3). While polygenic score (PGS) analyses showed the expected strong associations with SNPs highlighted in relevant previous GWAS on hippocampal volume and cognitive function, they did not show noteworthy associations with recent AD risk GWAS findings. In summary, our study highlights the power of using quantitative endophenotypes as outcome traits in AD-related GWAS analyses and nominates several new loci not previously implicated in cognitive decline.
| S-EPMC8979334 | biostudies-literature
Project description:We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ?4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.
| S-EPMC7175945 | biostudies-literature
Project description:We sought to identify a usable biomarker from blood samples to characterize early-stage Alzheimer's disease (AD) patients, in order to facilitate rapid diagnosis, early therapeutic intervention, and monitoring of clinical trials. We compared metabolites from blood plasma in early-stage Alzheimer's disease patients with blood plasma from healthy controls using two different analytical platforms: Amino Acid Analyzer and Tandem Mass-Spectrometer. Early-stage Alzheimer's patient blood samples were obtained during an FDA-approved Phase IIa clinical trial (Clinicaltrial.gov NCT03062449). Participants included 25 early-stage Alzheimer's patients and 25 healthy controls in the United States. We measured concentrations of 2-aminoethyl dihydrogen phosphate and taurine in blood plasma samples. We found that plasma concentrations of a phospholipid metabolite, 2-aminoethyl dihydrogen phosphate, normalized by taurine concentrations, distinguish blood samples of patients with early-stage AD. This possible new Alzheimer's biomarker may supplement clinical diagnosis for early detection of the disease.
| S-EPMC9022864 | biostudies-literature
Project description:The project aims to find diagnostic biomarkers for Alzheimer's disease in plasma. We applied discovery based proteomics was used to detect changes in proteins due to Alzheimer's disease using plasma samples collected from four study groups (African American Alzheimer's disease & cognitively normal, non-Hispanic-White Alzheimer's disease & cognitively normal). The data emphesizes the need for inclusion in Alzheimer's disease research.
2021-03-07 | PXD022265 | Pride
Project description:BackgroundRecent Alzheimer's disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD.Methods and findingsWe focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3 × 10(-13)). We applied a multivariate approach based on combinatorial optimization ((?,?)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering "meta-features," representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%.ConclusionsApplying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of plasma biomarkers for pre-clinical AD. While studies of independent test sets are required to validate the signatures, these analyses provide a starting point for developing a cost-effective and minimally invasive test capable of diagnosing AD in its pre-clinical stages.
| S-EPMC3317783 | biostudies-literature
Project description:Although Alzheimer's disease (AD) is the most common neurodegenerative disease, there are still no drugs available to treat or prevent AD effectively. Here, we examined changes in levels of selected proteins implicated in the pathogenesis of AD using plasma samples of control subjects and patients with cognition impairment. To precisely categorize the disease, fifty-six participants were examined with clinical cognitive tests, amyloid positron emission tomography (PET) scan, and white matter hyperintensities scored by magnetic resonance imaging. Plasma cathepsin D levels of the subjects were examined by immunoblotting and enzyme-linked immunosorbent assay (ELISA). Correlation of plasma cathepsin D levels with AD-related factors and clinical characteristics were examined by statistical analysis. By analyzing quantitative immunoblot and ELISA, we found that the plasma level of cathepsin D, a major lysosomal protease, was decreased in the group with amyloid plaque deposition at the brain compared to the control group. The level of plasma cathepsin D was negatively correlated with clinical dementia rating scale sum of boxes (CDR-SB) scores. In addition, our integrated multivariable logistic regression model suggests the high performance of plasma cathepsin D level for discriminating AD from non-AD. These results suggest that the plasma cathepsin D level could be developed as a diagnostic biomarker candidate for AD.
| S-EPMC7827175 | biostudies-literature