Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases
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Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non‐demented controls, we investigated global disruptions in the co‐regulation of genes in two neurodegenerative diseases, late‐onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co‐expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242‐gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter‐connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A , of which we predicted the former but not latter as a key regulator. To validate the inter‐connection of these two processes and our key regulator prediction, we generated two brain‐specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork ( P = 3.1 × 10 −12 ), while Dnmt3a KO signature does not ( P = 0.017).
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Conditional knockout of DNMT1 (M54) in the mouse brain activates a set of DEGs that significantly overlapped (padj = 1.4 × 10−11) with human module IFGblue, enriched for unfolded protein response and DNA repair pathway genes.
“For example, conditional knockout of the DNA methyltransferase, DNMT1 (M54), in the mouse brain (Narayanan et al., 2014) activates a set of DEGs that significantly overlapped (padj = 1.4 × 10−11) with a human module, IFGblue, enriched for unfolded protein response and DNA repair pathway genes.”
From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Narayanan et al., 2014
The Results section (‘Validating epigenetic regulation…’; page not provided) reports 388 differentially expressed genes in Dnmt1 conditional-knockout mice and significant overlap with the paper’s 242-gene disease subnetwork. It does not identify that subnetwork as IFGblue or report the claimed adjusted P value of 1.4 × 10−11; the reported overlap P value is 3.1 × 10−12. The cited passages also do not support the stated enrichment for unfolded protein response and DNA repair genes. (LLM, conf=0.88)
Experimental — accuracy not yet measuredAmong the DEGs identified in snRNA-seq, 1,113 and 764 genes were significantly differentially expressed in the microarray data from the prefrontal cortex and temporal cortex, respectively (adjusted P < 0.05).
“Among the DEGs identified in our snRNA-seq analysis, 1,113 and 764 genes were significantly differentially expressed in the microarray data from the prefrontal cortex and temporal cortex, respectively (adjusted P < 0.05) (SI Appendix, Table S4).”
From Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease (2020) · cites this paper as [18]
The Narayanan et al. dataset (GEO GSE33000) is a bulk transcriptome microarray analysis of prefrontal cortical tissues in a large cohort (AD: n = 310; NC: n = 157).
“We also obtained the dataset from a study by Narayanan et al. (Gene Expression Omnibus [GEO] accession no. GSE33000), who performed bulk transcriptome microarray analysis of prefrontal cortical tissues in a large cohort (AD: n = 310; NC: n = 157) (18).”
From Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease (2020) · cites this paper as [18]
The 20 transcriptome modules closely correspond to the originally reported network.
“A total of 20 distinct transcriptome modules were identified (Fig. 5A, right panel; and Table S8) that closely correspond to the originally reported network (Narayanan et al., 2014).”
From A Multi-network Approach Identifies Protein-Specific Co-expression in Asymptomatic and Symptomatic Alzheimer’s Disease (2017) · cites this paper as Narayanan et al., 2014
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- Authors
- Narayanan, M., Huynh, J. L., Wang, K., Yang, X., Yoo, S., McElwee, J., Zhang, B., Zhang, C., Lamb, J. R., Xie, T., Suver, C., Molony, C., Melquist, S., Johnson, A. D., Fan, G., Stone, D. J., Schadt, E. E., Casaccia, P., Emilsson, V., & Zhu, J.
- Affiliations
- National Institutes of Health (US)
- Icahn School of Medicine at Mount Sinai (US)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- University of California, Los Angeles (US)
- Sage Bionetworks (US)
- National Heart, Lung, and Blood Institute (US)
- University of Iceland (IS)
- Corresponding author
- Narayanan, Manikandan
- Zhu, Jun
- ORCID
- Venue
- Molecular Systems Biology
- Published
- 2014-07-01
- Volume
- 10
- Issue
- 7
- Pages
- 743-743
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC4299500
- OpenAlex
- W2111219940
- Cited by
- 208
- References
- 76
- Citations by year
- 2026: 22 · 2025: 17 · 2024: 24 · 2023: 17 · 2022: 25 · 2021: 20 · 2020: 20 · 2019: 16 · 2018: 17 · 2017: 16 · 2016: 10 · 2015: 3 · 2014: 1
- FWCI
- 6.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Funders
- NIH (R01AG0461701)
- NIH‐NIMH (R01MH090948‐01)
- NIH‐NINDS (R37NS042925‐10, F31NS077504)
- PHS (R24 MH068855)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- late-onset Alzheimer's disease, Huntington's disease, prefrontal cortex, gene co-expression network, chromatin organization, neuronal differentiation, DNA methyltransferases, DNMT1, DNMT3A, gene regulatory networks, postmortem brain, aging
- MeSH terms
- DNA (Cytosine-5-)-Methyltransferase 1, DNA Methyltransferase 3A, Alzheimer Disease, Animals, Autopsy, Chromatin, Dementia, DNA (Cytosine-5-)-Methyltransferases, Gene Expression Regulation, Humans, Huntington Disease, Reproducibility of Results, Case-Control Studies, Prefrontal Cortex, Mice, Knockout, Gene Expression Profiling, Mice, Gene Regulatory Networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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