A predictive microarray-based biomarker for early detection of Alzheimer's disease intended for clinical diagnostic application.

OBJECTIVE: Microarray-based signatures for clinical application are often plagued by processing variability or batch effects that compromise the robustness of the test performance. METHODS: A splice variant array-based signature for early detection of Alzheimer's disease (AD) was developed using 315 AD or normal subjects processed in three disparate microarray batches. RESULTS: A modified top scoring pair classifier using the signature, is robust to batch effects and outperforms other common classifiers, with sensitivity and specificity of 88.3% (95% CI:81.2%, 93.4%) and 88.9% (95% CI:65.3%, 98.6%), respectively, on an independent cohort. CONCLUSIONS: This splice-variant array-based signature shows promise for clinical diagnostic use in AD.

Toward an Alzheimer's disease diagnosis via high-resolution blood gene expression.

BACKGROUND: There is a significant need for reliable molecular biomarkers to aid in Alzheimer's disease (AD) clinical diagnosis. METHODS: We performed a genome-wide investigation of the human transcriptome, taking into account the discriminatory power of splice variations from the blood of 80 AD patients and 70 nondemented control (NDC) individuals. RESULTS: We characterized a blood RNA signature composed of 170 oligonucleotide probe sets associated with 133 genes that can correctly distinguish AD patients from NDC with a sensitivity of 100% and specificity of 96%. Functionally, this signature highlights genes involved in pathways that were associated with macrophages and lymphocytes within AD patients: Transforming growth factor (TGF-beta) signaling, oxidative stress, innate immunity and inflammation, cholesterol homeostasis, and lipid-raft perturbation, whereas other genes may also provide new insights in the biology of AD. CONCLUSIONS: This study provides proof-of-concept that whole-blood profiling can generate an AD-associated classification signature via the specific relative expression of biologically relevant RNAs. Such a signature will need to be validated with extended patient cohorts, and evaluated to learn whether it can differentiate AD from others types of dementia.

Blood transcriptomic biomarkers of Alzheimer's disease patients treated with EHT 0202.

Monitoring the genomic expression of patients in clinical trials for Alzheimer's disease (AD) can assist trial design and treatment response analysis. Here, we report on the identification in AD patients of blood-based transcriptomic signatures associated with treatment response of EHT 0202, a new compound with potential disease-modifying and symptomatic properties, in a 3-month, placebo-controlled, Phase IIA study aimed at determining the clinical safety, tolerability, and exploratory efficacy of EHT 0202 (40 and 80 mg bid) as adjunctive therapy to one cholinesterase inhibitor in mild to moderate AD patients. Genome-wide transcriptomic profiling was performed on blood samples taken prior to treatment and at study completion in a subpopulation of 60 AD patients selected as either the 10 worst disease decliners or the 10 best improvers of each treatment group, using ADAS-Cog scores as measure of disease severity. In the patients responding to EHT 0202, a pre-treatment (baseline) transcriptomic signature showed activation of pathways related to AD, CNS disorders, diabetes, inflammation, and autoimmunity, while a post-treatment signature indicated reduced activation of these pathways with induced metabolic and transcription stimulation. This pilot study demonstrates the utility of blood transcriptomic signatures used as biomarkers for predicting patient response or monitoring efficacy, for an administered therapeutic drug in a complex disease such as AD. For EHT 0202 or other AD drugs, such biomarkers may help to improve strategies to better identify appropriate patient populations for treatment, understand the drug mechanism of efficacy, and/or clarify the inherent subjectivity in most clinical endpoints used in this disease.

Validation of AclarusDx™, a blood-based transcriptomic signature for the diagnosis of Alzheimer's disease.

Biomarkers have gained an increased importance in the past years in helping physicians to diagnose Alzheimer's disease (AD). This study was designed to identify a blood-based, transcriptomic signature that can differentiate AD patients from control subjects. The performance of the signature was then evaluated for robustness in an independent blinded sample population. RNA was extracted from 177 blood samples (90 AD patients and 87 controls) and gene expression profiles were generated using the human Genome-Wide Splice Array™. These profiles were used to establish a signature to differentiate AD patients from controls. Subsequently, prediction results were optimized by establishing grey zone boundaries that discount prediction scores near the disease status threshold. Signature validation was then performed on a blinded independent cohort of 209 individuals (111 AD and 98 controls). The AclarusDx™ signature consists of 170 probesets which map to 136 annotated genes, a significant number of which are associated with inflammatory, gene expression, and cell death pathways. Additional signature genes are known to interact with pathways involved in amyloid and tau metabolism. The validation sample set, after removal of 45 individuals with prediction profile scores within the grey zone, consisted of 164 subjects. The AclarusDx™ performance on this validation cohort had a sensitivity of 81.3% (95% CI: [73.3%; 89.3%]); and a specificity of 67.1% (95% CI: [56.3%; 77.9%]). AclarusDx™ is a non-invasive blood-based transcriptomic test that, in combination with standard assessments, can provide physicians with objective information to support the diagnosis of AD.