ReviewBrain pathology (Zurich, Switzerland)2020
Considerations for integrative multi-omic approaches to explore Alzheimer's disease mechanisms.
Review in Brain pathology (Zurich, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Progress in toxicogenomics to protect human health.Nature reviews. Genetics · 2025Review
- Brain-wide alterations revealed by spatial transcriptomics and proteomics in COVID-19 infection.Nature aging · 2024Article
- Article
- Batch Correction and Harmonization of -Omics Datasets with a Tunable Median Polish of Ratio.Frontiers in systems biology · 2023Article
- Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing.Brain communications · 2023Article
- Bioinformatics pipeline to guide late-onset Alzheimer's disease (LOAD) post-GWAS studies: Prioritizing transcription regulatory variants within LOAD-associated regions.Alzheimer's & dementia (New York, N. Y.) · 2022Article
- Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models.Neurobiology of disease · 2021Review
- Applying gene-editing technology to elucidate the functional consequence of genetic and epigenetic variation in Alzheimer's disease.Brain pathology (Zurich, Switzerland) · 2020Article
- The molecular etiology of Alzheimer's disease.Brain pathology (Zurich, Switzerland) · 2020Article
- Epigenome-wide association studies in Alzheimer's disease; achievements and challenges.Brain pathology (Zurich, Switzerland) · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The past decade has seen the maturation of multiple different forms of high-dimensional molecular profiling to the point that these methods could be deployed in initially hundreds and more recently thousands of human samples. In the field of Alzheimer's disease (AD), these profiles have been applied to the target organ: the aging brain. In a growing number of cases, the same samples were profiled with multiple different approaches, yielding genetic, transcriptomic, epigenomic and proteomic data. Here, we review lessons learned so far as we move beyond quantitative trait locus (QTL) analyses which map the effect of genetic variation on molecular features to integrate multiple levels of "omic" data in an effort to identify the molecular drivers of AD. One thing is clear: no single layer of molecular or "omic" data is sufficient to capture the variance of AD or aging-related cognitive decline. Nonetheless, reproducible findings are emerging from current efforts, and there is evidence of convergence using different approaches. Thus, we are on the cusp of an acceleration of truly integrative studies as the availability of large numbers of well-characterized brain samples profiled in three or more dimensions enables the testing, comparison and refinement of analytic methods with which to dissect the molecular architecture of the aging brain.
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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.