Search DIAN Tissue Requests
Ji Yeun Hur
Characterization of gamma-secretase complexes in fibroblasts and iPSCs from PS1 or PS2 FAD mutations
06/27/2023
approved
DIAN-T2306
Characterize gamma-secretase complexes in fibroblasts and iPSCs
Characterize the gamma-secretase activity in fibroblasts and iPSCs
Sally Temple
Assessing neurovascular interactions due to ADRD mutations
08/15/2023
approved
DIAN-T2307
We will differentiate iPSCs with ADRD mutations versus controls into cerebral organoids and blood vessel cells. The goal is to examine the impact of the APP mutation on the organoids and blood vessel cells separately and interacting in a vascularized organoid.
The vascularized organoids will be sectioned and stained for Abeta, p-tau and the staining in different cell types will be quantified.
The conditioned medium produced by the vascularized organoids will be assessed for pathological markers and inflammatory factors.
The vascularized organoids will be dissociated for single cell -omics studies.
Laurent Roybon
Models and therapies for Alzheimer's disease
08/16/2023
approved
DIAN-T2308
Generate humanized models of early and advanced AD cellular pathogenesis
Use humanized models to explore a gene therapy for disease progression in AD
David Gate
Spatial transcriptomics on vaccinated AD brains
09/18/2023
pending approval
DIAN-T2309
Identify spatial transcriptomic changes associated with Aβ vaccination
Josef Penninger
Generation of human AD lymphatic vessels
01/09/2024
approved
DIAN-T2401
Generation of human lymphatic vessel organoids using AD iPSC lines
scRNA sequencing and profiling of lymphatic AD iPSC-derived organoids
Functional characterization of lymphatic AD organoids under microfluidic draining systems
Kenneth Shepard
Hybrid CMOS/Brain-Organoid Reservoir Computing
04/25/2024
approved
DIAN-T2402
Aim 1. Integration of organoids onto wireless CMOS multielectrode arrays (MEAs). This task is about getting the hardware working for a prototype CMOS-organoid processor. This will rely heavily on the existing BISC hardware, a wireless 65k channel neural interface device, which communicates with an external wireless relay station. The BISC hardware allows organoids to be cultured directly on top of the interface chips, which should improve the quality of the recording and stimulating interface
Aim 2. Demonstrate hybrid CMOS-organoid reservoir computing with the MNIST benchmark.
Randall Bateman
Accuracy and value of mid-throughput technology for biomarker measurement in the context of DIAN
05/07/2024
approved
DIAN-T2403
Comparison of mid-throughput to one at a time measurements
Comparison of mid-throughput to high-throughput measurements
Non-inferiority assessment of mid-throughput performance to assess amyloid positivity
P. Gleeson
Impact of familial Alzheimer’s disease mutations on APP trafficking and processing, and neuronal function
06/23/2024
approved
DIAN-T2404
To compare the trafficking pathways of wild type APP and familial Swedish APP mutant in human iPSC derived neurons
To define the role of the Golgi in the processing of the familial Swedish APP mutant in the secretory pathway of iPSC-derived neurons
To assess the impact of Golgi fragmentation, mediated by APP processing, on neuronal function
Sally Temple
Human iPSC model of Cerebro-Vascular Interactions in ADRD
07/09/2024
approved
DIAN-T2405
Generate and optimize a human cerebro-vascular model of PSEN1 and APP mutation
Validation of the PSEN1 and APP cerebro-vascular model, including measures of face, construct, and predictive validity
Professor Katie Lunnon
The first systematic study to identify miRNAs, and corresponding gene regulatory networks, which influence familial Alzheimer's disease manifestation
08/08/2024
pending approval
DIAN-T2406
To quantify miRNAs in FAD and control PFC samples, relating this to neuropathological and clinical assessments. This will allow us to identify miRNAs that are implicated in disease, and its clinical heterogeneity and compare to miRNA profiled in SAD.
To explore the downstream effect of differential miRNA expression at both the transcriptional and protein levels in the same samples. This will allow us to identify downstream pathways and effectors that are altered in FAD as a result of miRNA alterations, including characterising novel transcripts.
To identify the competing endogenous RNA networks that regulate the expression of disease-associated miRNAs. We will construct co-expression networks of nominated miRNAs with lncRNAs and circRNAs in the same samples identifying specific lncRNA and cirRNAs that act as upstream molecular sponges to regulate miRNA and subsequently gene/protein expression in FAD.
To investigate other (non-RNA based) epigenetic mechanisms that regulate gene expression and their relationship to FAD-associated miRNA-mRNA pairs in the same samples. This will allow us to understand the complete epigenetic landscape regulating the expression of nominated genes in FAD.