ROSMAP DLPFC Glycoproteomics
Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) DLPFC glycoproteomics (N-glycosylation proteomics).
Please refer to this document for an overview of the ROSMAP project.
Access
Controlled access. Request data access for ROSMAP on the AD Knowledge Portal; you need a Synapse account. See How to get the data.
| Where | ID | Access | What you get |
|---|---|---|---|
| Synapse | syn17015098 | Controlled | Files described below |
Other Synapse IDs on this page syn69670592 syn69670597 syn69670600 syn69670611 syn69670630 syn69865816
pip install synapseclient
synapse login
synapse get -r syn17015098Contact
FunGen-xQTL Analysis Working Group
Study Overview
- PI: David A. Bennett (Rush University Medical Center, Chicago, IL, USA)
- Grant numbers: U01AG046152, R01AG048015, U01AG061356, R01AG15819, U01AG061359
- Publication: PMID: 30084846
- Genetics publication: PMID: 40407102
- Acknowledgement: Study data were generated from postmortem brain tissue provided by the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) cohort at Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago.
- Omics data: syn17015098
- Genetics data: ng00067
- Disease: Alzheimer’s Disease
Dataset Details
Overview
Glycoproteomics data profiling N-glycosylation of proteins from dorsolateral prefrontal cortex (DLPFC) tissue of ROSMAP participants. Protein glycosylation is quantified alongside standard protein abundance to characterize post-translational modifications relevant to Alzheimer’s disease pathology.
- Brain region: Dorsolateral prefrontal cortex (DLPFC)
- Data type: Glycoproteomics (N-glycosylation mass spectrometry)
- Platform: Tandem mass tag (TMT) isobaric labeling mass spectrometry
Molecular Phenotype Matrices
Glycopeptide abundance matrices normalized from TMT-based mass spectrometry data. Available through the AD Knowledge Portal at syn17015098.
QTL Analysis
QTL analysis for this dataset is documented in ../../qtl/glycoQTL/ROSMAP_DLPFC_glycoproteomics_qtl.md.
Flagship paper analyses:
- Fine-mapping (SuSiE-RSS): syn69670592
- TWAS weight models: syn69670600
- Quantile TWAS (qTWAS) models: syn69670611
- Multi-context colocalization (ColocBoost): syn69670597
- AD GWAS–xQTL colocalization results: syn69865816
- AD GWAS–xQTL colocalization models: syn69670630