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.

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.

Commentary on "Developing a national strategy to prevent dementia: Leon Thal Symposium 2009." Developing a blood test for Alzheimer's disease using advanced genomic expression technology.

There is a significant need for reliable molecular biomarkers to aid in Alzheimer's disease (AD) clinical diagnosis. RNA transcriptional profiling, although extensively applied for biomarker development in other diseases, is first defining its role in AD. Application of this technology has the sensitivity and power to provide sufficient information for the development of tests to determine disease severity, progression, heterogeneity, and potential for therapeutic response in the AD population. In order to bring forth the potential of this technology, however, the community needs to make a concerted effort to begin sample collection as soon as patients/subjects are identified. Only then can these powerful technologies be applied in a well controlled study for the development of novel diagnostics.

Developing a national strategy to prevent dementia: Leon Thal Symposium 2009.

Among the major impediments to the design of clinical trials for the prevention of Alzheimer's disease (AD), the most critical is the lack of validated biomarkers, assessment tools, and algorithms that would facilitate identification of asymptomatic individuals with elevated risk who might be recruited as study volunteers. Thus, the Leon Thal Symposium 2009 (LTS'09), on October 27-28, 2009 in Las Vegas, Nevada, was convened to explore strategies to surmount the barriers in designing a multisite, comparative study to evaluate and validate various approaches for detecting and selecting asymptomatic people at risk for cognitive disorders/dementia. The deliberations of LTS'09 included presentations and reviews of different approaches (algorithms, biomarkers, or measures) for identifying asymptomatic individuals at elevated risk for AD who would be candidates for longitudinal or prevention studies. The key nested recommendations of LTS'09 included: (1) establishment of a National Database for Longitudinal Studies as a shared research core resource; (2) launch of a large collaborative study that will compare multiple screening approaches and biomarkers to determine the best method for identifying asymptomatic people at risk for AD; (3) initiation of a Global Database that extends the concept of the National Database for Longitudinal Studies for longitudinal studies beyond the United States; and (4) development of an educational campaign that will address public misconceptions about AD and promote healthy brain aging.

Drug treatment of Alzheimer's disease patients leads to expression changes in peripheral blood cells.

BACKGROUND: Increasing cholinergic activity has been the primary mechanism for treating dementia due to Alzheimer's disease. However, the effectiveness of cholinesterase inhibitors (ChEIs) is still widely debated. The identification of specific biomarkers capable of identifying patients more likely to respond to these treatments could potentially provide specific evidence to clearly address this controversy through patient stratification. The goal of this study was to determine the feasibility of discovering biomarkers specific for the treatment of Alzheimer's disease. METHODS: Peripheral blood was collected from a cohort of patients treated with different ChEIs. Total RNA was isolated and profiled on the human Genome-Wide SpliceArray (GWSA) to test the feasibility of discriminating the different treatment subgroups of subjects based on the expression patterns generated from the Genome-Wide SpliceArray. RESULTS: Specific expression differences were identified for the various treatment groups that lead to a clear separation between patients treated with ChEIs versus naïve patients when Principal Component Analysis was performed on probe sets selected for differential expression. In addition, specific probe sets were identified to be dependent on the inhibitor used among the treated patients. CONCLUSIONS: Distinct separation between non-treated, galantamine, donepezil, and rivastigmine-treated patients was clearly identified based on small sets of expression probes. The ability to identify drug-specific treatment expression differences strengthens the potential for using peripheral gene signatures for the identification of individuals responding to drug treatment.

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.

High resolution analysis of the human transcriptome: detection of extensive alternative splicing independent of transcriptional activity.

BACKGROUND: Commercially available microarrays have been used in many settings to generate expression profiles for a variety of applications, including target selection for disease detection, classification, profiling for pharmacogenomic response to therapeutics, and potential disease staging. However, many commercially available microarray platforms fail to capture transcript diversity produced by alternative splicing, a major mechanism for driving proteomic diversity through transcript heterogeneity. RESULTS: The human Genome-Wide SpliceArray(TM) (GWSA), a novel microarray platform, utilizes an existing probe design concept to monitor such transcript diversity on a genome scale. The human GWSA allows the detection of alternatively spliced events within the human genome through the use of exon body and exon junction probes to provide a direct measure of each transcript, through simple calculations derived from expression data. This report focuses on the performance and validation of the array when measured against standards recently published by the Microarray Quality Control (MAQC) Project. The array was shown to be highly quantitative, and displayed greater than 85% correlation with the HG-U133 Plus 2.0 array at the gene level while providing more extensive coverage of each gene. Almost 60% of splice events among genes demonstrating differential expression of greater than 3 fold also contained extensive splicing alterations. Importantly, almost 10% of splice events within the gene set displaying constant overall expression values had evidence of transcript diversity. Two examples illustrate the types of events identified: LIM domain 7 showed no differential expression at the gene level, but demonstrated deregulation of an exon skip event, while erythrocyte membrane protein band 4.1 -like 3 was differentially expressed and also displayed deregulation of a skipped exon isoform. CONCLUSION: Significant changes were detected independent of transcriptional activity, indicating that the controls for transcript generation and transcription are distinct, and require novel tools in order to detect changes in specific transcript quantity. Our results demonstrate that the SpliceArray(TM) design will provide researchers with a robust platform to detect and quantify specific changes not only in overall gene expression, but also at the individual transcript level.

Alternative splicing of the G protein-coupled receptor superfamily in human airway smooth muscle diversifies the complement of receptors.

G protein-coupled receptors (GPCRs) are the largest signaling family in the genome, serve an expansive array of functions, and are targets for approximately 50% of current therapeutics. In many tissues, such as airway smooth muscle (ASM), complex, unexpected, or paradoxical responses to agonists/antagonists occur without known mechanisms. We hypothesized that ASM express many more GPCRs than predicted, and that these undergo substantial alternative splicing, creating a highly diversified receptor milieu. Transcript arrays were designed detecting 434 GPCRs and their predicted splice variants. In this cell type, 353 GPCRs were detected (including 111 orphans), with expression levels varying by approximately 900-fold. Receptors used for treating airway disease were expressed lower than others with similar signaling properties, indicating potentially more effective targets. A disproportionate number of Class-A peptide-group receptors, and those coupling to G(q)/(11) or G(s) (vs. G(i)), was found. Importantly, 192 GPCRs had, on average, five different expressed receptor isoforms because of splicing events, including alternative splice donors and acceptors, novel introns, intron retentions, exon(s) skips, and novel exons, with the latter two events being most prevalent. The consequences of splicing were further investigated with the leukotriene B4 receptor, known for its aberrant responsiveness in lung. We found transcript expression of three variants because of alternative donor and acceptor splice sites, representing in-frame deletions of 38 and 100 aa, with protein expression of all three isoforms. Thus, alternative splicing, subject to conditional, temporal, and cell-type regulation, is a major mechanism that diversifies the GPCR superfamily, creating local recepteromes with specialized environments.

Methods and platforms for the quantification of splice variants' expression.

The relatively limited number of human protein encoding genes highlights the importance of the diversity generated at the level of the mRNA transcripts. As alternative RNA splicing plays a key role in mediating this diversity, it becomes critical to develop the tools and platforms that will deliver quantitative information on the specific expression levels associated with splice isoforms. This chapter describes the constraints generated by this global transcriptome analysis and the state-of-the-art techniques and products available to the scientific community.

Alternative isoform discrimination by the next generation of expression profiling microarrays.

Microarray expression profiling has revolutionised the way that many therapeutic targets have been identified over the past 10 years. High-density microarrays have allowed scientists to simultaneously scrutinise the expression of all genes encoded on a given genome. Although the data collected from classically designed microarrays greatly enriched the pool of information available to help guide the selection and design of new therapeutic strategies, they were unable to tell the complete story. The major limitation with most array designs is that they can only produce a global expression value for all transcripts produced from a specific locus and cannot monitor each individual alternative isoform produced from the interrogated locus. Recently, new array designs have been described, and become commercially available, that can efficiently monitor individual alternatively spliced isoforms produced from a single locus, allowing the research community to get a more accurate picture of the biological landscape of the expressed transcripts.