# Network Medicine for Alzheimers Disease: Functional Dissection and Pharmacologic Perturbation of a Human Brain Synaptic Regulatory Expression Signature > **NIH NIH RF1** · BAYLOR COLLEGE OF MEDICINE · 2022 · $1,509,105 ## Abstract PROJECT SUMMARY Analyses of transcriptomic profiles from human brains constitute a powerful strategy for highlighting biological networks associated with Alzheimer’s disease (AD) pathophysiology. In collaboration with the Accelerating Medicines Partnership (AMP)-AD Consortium, we have defined promising molecular networks dysregulated in AD based on analyses of RNA-sequencing from ~2,000 human brain autopsy samples. In order to translate these results for “network therapies”, computational predictions must be rigorously tested in experimental animal models. In order to pinpoint causal drivers among AD-associated coexpression networks, 357 conserved targets were systematically screened using transgenic Drosophila, identifying 144 modifiers of human amyloid-beta (Aß)- and/or tau-triggered neuronal dysfunction. Our results highlight a promising 167- gene synaptic regulatory network (SRN) linked to glutamate excitatory signaling that is both (i) significantly down-regulated in AD and (ii) enriched for suppressors of neurodegeneration based on knockdown in Drosophila. Moreover, GRIN2B, an NMDA receptor subunit and target of the approved AD drug, memantine, is a “hub” suppressor. We hypothesize that SRN represents a highly conserved and coordinated transcriptional protective response that compensates for excitotoxic neuronal injury in AD, consistent with evidence that hyperexcitability and impaired synaptic plasticity are important contributors to disease pathogenesis and clinical manifestations. We propose here to deploy our powerful cross-species strategy to refine this mechanistic hypothesis and develop a pharmacologic approach to boost SRN and thereby support brain resilience in AD. First, (AIM1), we will perform systematic genetic manipulations to simulate up- or down- regulation in hundreds of SRN genes and screen for enhancers and suppressors of tau- or Aß-induced, age- dependent neuronal dysfunction. Promising hits will be validated using independent assays, and Mendelian randomization will confirm the causal impact of SRN human gene expression changes on AD risk or protection. Next (AIM2), we will perform genetic manipulations of GRIN2B and other identified SRN causal drivers in Drosophila models of excitotoxic neuronal injury, along with complementary studies in mouse primary hippocampal neuron cultures. Lastly (AIM3), we will experimentally probe fine-scale SRN architecture, assaying transcriptional signatures following genetic perturbations of inferred nodal driver genes in both the presence or absence of excitotoxicity and other AD pathologic triggers. We will then nominate small molecule perturbagens for experimental validation in human neuronal cultures. IMPACT: Our integrative, cross-species approach will functionally dissect a promising transcriptional regulatory network using powerful, in vivo assays, mapping the complex molecular architecture of AD excitotoxic neuronal injury and pinpointing vulnerable nodes for pharmacologic reprogra... ## Key facts - **NIH application ID:** 10503884 - **Project number:** 1RF1AG078660-01 - **Recipient organization:** BAYLOR COLLEGE OF MEDICINE - **Principal Investigator:** Joshua M Shulman - **Activity code:** RF1 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $1,509,105 - **Award type:** 1 - **Project period:** 2022-08-15 → 2025-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10503884 ## Citation > US National Institutes of Health, RePORTER application 10503884, Network Medicine for Alzheimers Disease: Functional Dissection and Pharmacologic Perturbation of a Human Brain Synaptic Regulatory Expression Signature (1RF1AG078660-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10503884. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*