A Gene Expression Pattern in Blood for the Early Detection of Alzheimer's Disease

Abstract

A whole genome screen was performed using oligonucleotide microarray analysis on blood from a large clinical cohort of Alzheimer's disease (AD) patients and control subjects as clinical sample. Blood samples for total RNA extraction were collected in PAXgene tubes, and gene expression analysis performed on the AB1700 Whole Genome Survey Microarrays. When comparing the gene expression of 94 AD patients and 94 cognitive healthy controls, a Jackknife gene selection based method and Partial Least Square Regression (PLSR) was used to develop a disease classifier algorithm, which gives a test score indicating the presence (positive) or absence (negative) of AD. This algorithm, based on 1239 probes, was validated in an independent test set of 63 subjects comprising 31 AD patients, 25 age-matched cognitively healthy controls, and 7 young controls. This algorithm correctly predicted the class of 55/63 (accuracy 87%), including 26/31 AD samples (sensitivity 84%) and 29/32 controls (specificity 91%). The positive likelihood ratio was 8.9 and the area under the receiver operating characteristic curve (ROC AUC) was 0.94. Furthermore, the algorithm also discriminated AD from Parkinson's disease in 24/27 patients (accuracy 89%). We have identified and validated a gene expression signature in blood that classifies AD patients and cognitively healthy controls with high accuracy and show that alterations specific for AD can be detected distant from the primary site of the disease.

Prediction of Mild Cognitive Impairment that Evolves into Alzheimer's Disease Dementia within Two Years using a Gene Expression Signature in Blood: A Pilot Study

“…This test detects the blood-based gene expression signature in blood samples and adopts a combination of multiple gene expression assays to obtain a prediction value for disease classification. Alterations in a gene expression signature in peripheral blood are postulated as a result of a systemic disease response in AD as verified by many previous studies [34][35][36][37][38].…”

“…For product development, further adaptation of the qPCR protocol for regulatory approval purposes is planned prior to locking of the algorithm; moreover a larger number of assays into the optimization phase is preferred. However, in this study we wanted to investigate a subset of 20 informative assays that we have previously identified in independent in-house studies (results not shown) during the development of ADtect ® [34,35]. The identification of these assays was based on the discrimination of AD and cognitively healthy controls.…”

“…A total of 1,239 gene probes have previously been selected [35] and served as a basis for the identification of informative genes. The 1,239 gene probes were selected based on an AD classifier developed following a whole genome screen comprising in total 126 clinically diagnosed AD patients, 98 age-matched cognitively healthy controls, 28 young controls, 28 Parkinson's disease patients, and 10 subjects with MCI.…”

“…The development and validation of this 96-assay gene expression signature has been described in Booij et al and Rye et al [34,35]. This test detects the blood-based gene expression signature in blood samples and adopts a combination of multiple gene expression assays to obtain a prediction value for disease classification.…”

The intellectual disability of trisomy 21: differences in gene expression in a case series of patients with lower and higher IQ

“…Such approach was already tested in DS and different pathologies. [9][10][11][12] The low number of patients, especially in the IQ À group, was secondary to the fact that we wanted to restrict this study only to the T21 patients that we could discriminate by IQ test. Interestingly, the group IQ À was predominantly males, whereas the IQ þ group was frequently females with a sex ratio of 2/3.…”