ArticleEBioMedicine2019
Multi-omics signature of brain amyloid deposition in asymptomatic individuals at-risk for Alzheimer's disease: The INSIGHT-preAD study.
Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.
- Lipids as Early and Minimally Invasive Biomarkers for Alzheimer's Disease.Current neuropharmacology · 2022Pooled it
- Unravelling Synaptic and Metabolic Mechanisms of Cognitive Resilience in Asymptomatic Alzheimer's Disease Across Two Alzheimer's Disease Cohorts.Cellular and molecular neurobiology · 2026Article
- Exposome influences: a multi-omics perspective on the combined toxic effects of pharmaceuticals and personal care products in Alzheimer's disease.Frontiers in toxicology · 2026Review
- Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions.Acta pharmaceutica Sinica. B · 2025Review
- Assessing polyomic risk to predict Alzheimer's disease using a machine learning model.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease.Cell reports. Medicine · 2024Review
- Cerebral Amyloidosis in Individuals with Subjective Cognitive Decline: From Genetic Predisposition to Actual Cerebrospinal Fluid Measurements.Biomedicines · 2024Article
- Tackling neurodegenerationFrontiers in molecular neuroscience · 2024Review
- mFrontiers in cell and developmental biology · 2024Review
- Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives.Ageing research reviews · 2023Review
- Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective.Journal of pharmaceutical analysis · 2023Review
- A guide to multi-omics data collection and integration for translational medicine.Computational and structural biotechnology journal · 2023Review
- An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response.Frontiers in psychiatry · 2023Article
- Multi-omics analysis revealed the role of CYP1A2 in the induction of mechanical allodynia in type 1 diabetes.Frontiers in genetics · 2023Article
- Brain lipidomics: From functional landscape to clinical significance.Science advances · 2022Review
- Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Review
- The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease.Frontiers in aging neuroscience · 2022Review
- Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.Frontiers in genetics · 2022Article
- Potential Mechanisms Underlying Resistance to Dementia in Non-Demented Individuals with Alzheimer's Disease Neuropathology.Journal of Alzheimer's disease : JAD · 2022Review
Corrections and comments
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Authors and funding
15 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOne of the biggest challenge in Alzheimer's disease (AD) is to identify pathways and markers of disease prediction easily accessible, for prevention and treatment. Here we analysed blood samples from the INveStIGation of AlzHeimer's predicTors (INSIGHT-preAD) cohort of elderly asymptomatic individuals with and without brain amyloid load.
methodsWe performed blood RNAseq, and plasma metabolomics and lipidomics using liquid chromatography-mass spectrometry on 48 individuals amyloid positive and 48 amyloid negative (SUVr cut-off of 0·7918). The three data sets were analysed separately using differential gene expression based on negative binomial distribution, non-parametric (Wilcoxon) and parametric (correlation-adjusted Student't) tests. Data integration was conducted using sparse partial least squares-discriminant and principal component analyses. Bootstrap-selected top-ten features from the three data sets were tested for their discriminant power using Receiver Operating Characteristic curve. Longitudinal metabolomic analysis was carried out on a subset of 22 subjects.
findingsUnivariate analyses identified three medium chain fatty acids, 4-nitrophenol and a set of 64 transcripts enriched for inflammation and fatty acid metabolism differentially quantified in amyloid positive and negative subjects. Importantly, the amounts of the three medium chain fatty acids were correlated over time in a subset of 22 subjects (p < 0·05). Multi-omics integrative analyses showed that metabolites efficiently discriminated between subjects according to their amyloid status while lipids did not and transcripts showed trends. Finally, the ten top metabolites and transcripts represented the most discriminant omics features with 99·4% chance prediction for amyloid positivity.
interpretationThis study suggests a potential blood omics signature for prediction of amyloid positivity in asymptomatic at-risk subjects, allowing for a less invasive, more accessible, and less expensive risk assessment of AD as compared to PET studies or lumbar puncture. FUND: Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epiniere (IHU-A-ICM), French Ministry of Research, Fondation Alzheimer, Pfizer, and Avid.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.