Multiscale causal networks identify VGF as a key regulator of Alzheimer’s disease
Open accessAbstract
Though discovered over 100 years ago, the molecular foundation of sporadic Alzheimer’s disease (AD) remains elusive. To better characterize the complex nature of AD, we constructed multiscale causal networks on a large human AD multi-omics dataset, integrating clinical features of AD, DNA variation, and gene- and protein-expression. These probabilistic causal models enabled detection, prioritization and replication of high-confidence master regulators of AD-associated networks, including the top predicted regulator, VGF. Overexpression of neuropeptide precursor VGF in 5xFAD mice partially rescued beta-amyloid-mediated memory impairment and neuropathology. Molecular validation of network predictions downstream of VGF was also achieved in this AD model, with significant enrichment for homologous genes identified as differentially expressed in 5xFAD brains overexpressing VGF. Our findings support a causal role for VGF in protecting against AD pathogenesis and progression.
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Previous studies using transgenic mouse models of AD have identified various mechanisms that lead to synaptic impairment in AD, including the accumulation of soluble amyloid-beta, Tau hyperphosphorylation, loss of VGF signaling, and glial state dysregulation.
“For example, previous studies using transgenic mouse models of AD have identified various mechanisms that lead to synaptic impairment in AD, including the accumulation of soluble amyloid-beta, Tau hyperphosphorylation, loss of VGF signaling, and glial state dysregulation (e.g., the induction of disease-associated microglia and disease-associated astrocytes) (9, 23–30).”
From Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease (2020) · cites this paper as [30]
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Self-citationModulation of Amyloid-β Protein Precursor Expression by HspB1
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Flagged first, then by citations
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Self-citation
- Authors
- Beckmann, N. D., Lin, W.-J., Wang, M., Cohain, A. T., Charney, A. W., Wang, P., Ma, W., Wang, Y.-C., Jiang, C., Audrain, M., Comella, P. H., Fakira, A. K., Hariharan, S. P., Belbin, G. M., Girdhar, K., Levey, A. I., Seyfried, N. T., Dammer, E. B., Duong, D., Lah, J. J., Haure-Mirande, J.-V., Shackleton, B., Fanutza, T., Blitzer, R., Kenny, E., Zhu, J., Haroutunian, V., Katsel, P., Gandy, S., Tu, Z., Ehrlich, M. E., Zhang, B., Salton, S. R., & Schadt, E. E.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Sun Yat-sen University (CN)
- Emory University (US)
- Sema4 (United States) (US)
- James J. Peters VA Medical Center (US)
- Corresponding author
- Salton, Stephen R.
- Schadt, Eric E.
- ORCID
- Beckmann, Noam D.
- Lin, Wei-Jye
- Wang, Minghui
- Cohain, Ariella T.
- Charney, Alexander W.
- Wang, Pei
- Ma, Weiping
- Wang, Ying-Chih
- Jiang, Cheng
- Audrain, Mickael
- Comella, Phillip H.
- Fakira, Amanda K.
- Hariharan, Siddharth P.
- Belbin, Gillian M.
- Girdhar, Kiran
- Levey, Allan I.
- Seyfried, Nicholas T.
- Dammer, Eric B.
- Duong, Duc
- Lah, James J.
- Haure-Mirande, Jean-Vianney
- Fanutza, Tomas
- Blitzer, Robert
- Kenny, Eimear
- Zhu, Jun
- Haroutunian, Vahram
- Katsel, Pavel
- Gandy, Sam
- Tu, Zhidong
- Ehrlich, Michelle E.
- Zhang, Bin
- Salton, Stephen R.
- Schadt, Eric E.
- Venue
- Nature Communications
- Published
- 2020-08-07
- Volume
- 11
- Issue
- 1
- Pages
- 3942-3942
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7414858
- OpenAlex
- W3048036301
- Cited by
- 172
- References
- 86
- Citations by year
- 2026: 20 · 2025: 29 · 2024: 34 · 2023: 26 · 2022: 35 · 2021: 18 · 2020: 7 · 2019: 3
- FWCI
- 13.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Alzheimer's Drug Discovery Foundation
- BrightFocus Foundation
- Icahn School of Medicine at Mount Sinai
- Cure Alzheimer's Fund
- National Natural Science Foundation of China (81972967, 2017B030314026)
- Natural Science Foundation of Guangdong Province (2019A1515011754, 2017B030314026)
- National Institutes of Health (5r01ag055501-05)
- National Institute on Aging (R01AG057907, R01AG046170, U01AG046170, RF1AG054014, RF1AG057440, R01-AG055501, RF1AG062661, RF1AG057443, RF1AG059319, R01AG062355, U01AG046161, P50AG025688, R01AG067312, R01AG053960, P30AG066514)
- National Institute of Mental Health (R21MH083496, R01MH086499, R33MH083496)
- National Institute on Drug Abuse (HHSN271201300031C)
- National Cancer Institute (U24CA210993)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK117504)
- National Institute of Neurological Disorders and Stroke (P30NS055077)
- 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
- Alzheimer's disease, VGF, neuropeptide precursors, causal networks, probabilistic causal models, master regulators, multi-omics integration, 5xFAD mice, amyloid-beta, memory impairment, neuropathology, gene expression, DNA variation
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Animals, Brain, Disease Models, Animal, Female, Humans, Male, Mice, Transgenic, Nerve Growth Factors, Amyloid beta-Peptides, Gene Expression Profiling, Protein Interaction Mapping, Proteomics, Mice, Gene Regulatory Networks, Genome-Wide Association Study, Protein Interaction Maps, Datasets as Topic
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.
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