ArticleJournal of Alzheimer's disease : JAD2016
A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis.
Article in Journal of Alzheimer's disease : JAD, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-Analysis of Transcriptomic Studies of Blood and Six Brain Regions Identifies a Consensus of 15 Cross-Tissue Mechanisms in Alzheimer's Disease and Suggests an Origin of Cross-Study Heterogeneity.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025Pooled it
- A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data.Journal of Alzheimer's disease : JAD · 2019Pooled it
- A new era of genome-wide association studies in the field of Alzheimer's disease and overlapping co-pathologies: lessons learned from a neuropathology-centered approach.Acta neuropathologica · 2026Review
- Diagnosis of Alzheimer's disease with high accuracy via Petri net modeling of signaling pathways.Scientific reports · 2026Article
- Exploring Primary and Interaction Effects of Minor Physical Anomalies: Development and Validation of Prediction Models Using Explainable Machine Learning Algorithms for Early-Onset Schizophrenia.Schizophrenia bulletin · 2026Article
- A new ANMerge-based blood transcriptomic resource to support Alzheimer's disease research.medRxiv : the preprint server for health sciences · 2025Article
- Hypothesis-based investigation of known AD risk variants reveals the genetic underpinnings of neuropathological lesions observed in Alzheimer's-type dementia.Acta neuropathologica · 2024Article
- A multi-cohort study of the hippocampal radiomics model and its associated biological changes in Alzheimer's Disease.Translational psychiatry · 2024Article
- Molecular Gene Expression Testing to Identify Alzheimer's Disease with High Accuracy from Fingerstick Blood.Journal of Alzheimer's disease : JAD · 2024Article
- Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model.Frontiers in oncology · 2024Article
- A New Approach for Multimodal Usage of Gene Expression and Its Image Representation for the Detection of Alzheimer's Disease.Biomolecules · 2023Article
- Identifying Effective Feature Selection Methods for Alzheimer's Disease Biomarker Gene Detection Using Machine Learning.Diagnostics (Basel, Switzerland) · 2023Article
- Blood Transcript Biomarkers Selected by Machine Learning Algorithm Classify Neurodegenerative Diseases including Alzheimer's Disease.Biomolecules · 2022Article
- Longitudinal Data to Enhance Dynamic Stroke Risk Prediction.Healthcare (Basel, Switzerland) · 2022Article
- Prediction of Alzheimer's Disease by a Novel Image-Based Representation of Gene Expression.Genes · 2022Article
- Immune abnormalities and differential gene expression in the hippocampus and peripheral blood of patients with Alzheimer's disease.Annals of translational medicine · 2022Article
- Alzheimer's Disease Blood Biomarkers Associated With Neuroinflammation as Therapeutic Targets for Early Personalized Intervention.Frontiers in digital health · 2022Article
- Applications and Challenges of Machine Learning Methods in Alzheimer's Disease Multi-Source Data Analysis.Current genomics · 2021Review
- Dysregulated expression levels of APH1B in peripheral blood are associated with brain atrophy and amyloid-β deposition in Alzheimer's disease.Alzheimer's research & therapy · 2021Article
- ANMerge: A Comprehensive and Accessible Alzheimer's Disease Patient-Level Dataset.Journal of Alzheimer's disease : JAD · 2021Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
backgroundRecent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer's disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust.
objectivesThis study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts.
methodsOur study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis.
resultsGene and pathway level models performed similarly to each other and to a model based on demographic information only.
conclusionsAny potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.
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