ArticlePLoS genetics2020
Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology.
Article in PLoS genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.
- Evaluation of Toll-like Receptor 4 (TLR4) Involvement in Human Atrial Fibrillation: A Computational Study.Genes · 2024Pooled it
- Article
- Multi-region brain transcriptomes uncover two subtypes of aging individuals with differences in Alzheimer risk and the impact ofiScience · 2026Article
- Identifying transcriptomic signatures that mediate the causal effect of genotype on Alzheimer's disease.Frontiers in neuroscience · 2026Article
- Trem2bioRxiv : the preprint server for biology · 2025Article
- Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions.Acta pharmaceutica Sinica. B · 2025Review
- TPClust: Temporal Profile-Guided Subtyping Using High-Dimensional Omics Data.bioRxiv : the preprint server for biology · 2025Article
- Transcriptomic signatures of oxytosis/ferroptosis are enriched in Alzheimer's disease.BMC biology · 2025Article
- TMEM106B Knockdown Exhibits a Neuroprotective Effect in Parkinson's Disease via Decreasing Inflammation and Iron Deposition.Molecular neurobiology · 2025Article
- Network dynamics-based subtyping of Alzheimer's disease with microglial genetic risk factors.Alzheimer's research & therapy · 2024Article
- A TrkB and TrkC partial agonist restores deficits in synaptic function and promotes activity-dependent synaptic and microglial transcriptomic changes in a late-stage Alzheimer's mouse model.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- In vivo validation of late-onset Alzheimer's disease genetic risk factors.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Characterizing molecular and synaptic signatures in mouse models of late-onset Alzheimer's disease independent of amyloid and tau pathology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Physiological and pathological functions of TMEM106B in neurodegenerative diseases.Cellular and molecular life sciences : CMLS · 2024Review
- Whole genome-wide sequence analysis of long-lived families (Long-Life Family Study) identifies MTUS2 gene associated with late-onset Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- E674Q (ShanghaiGenes & diseases · 2024Article
- Preclinical translational platform of neuroinflammatory disease biology relevant to neurodegenerative disease.Journal of neuroinflammation · 2024Article
- Article
- Characterizing Molecular and Synaptic Signatures in mouse models of Late-Onset Alzheimer's Disease Independent of Amyloid and Tau Pathology.bioRxiv : the preprint server for biology · 2023Article
- Moving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer's disease.Trends in neurosciences · 2023Review
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
Abstract
Late-Onset Alzheimer's disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5×10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.
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