CONP Portal | Dataset
PREVENT-AD registered data
Dimensions: | age at MRI, test language, handedness interpretation, handedness score, structural MRI, functional MRI, AD8 dementia screening interview, central auditory processing evaluation, clinical information, CSF protein levels, demographics, cardiovascular risk factors, aging, and incidence of dementia (CAIDE) dementia risk score, clinical dementia rating, Montreal cognitive assessment (MOCA), medical history, genetics, lab results, medication user, repeatable battery for the assessment of neuropsychological status (RBANS), smell identification |
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Is About: | Alzheimer's disease, Homo sapiens, older adult |
Acknowledges: | Fonds de Recherche du Québec - Santé, McGill University, Pfizer Canada, Douglas Hospital Research Centre and Foundation, Fondation Lévesque, Canada Fund for Innovation |
Spatial Coverage: | Québec (province) |
Other Dates: | Release Date: 2020-11-30 -- Last Update Date: 2021-02-11 -- Start Date: 2011-11-01 -- End Date: 2020-03-10 |
Description:
Dataset README information
PREVENT-AD Registered Dataset
Overview
The PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer Disease) cohort is composed of cognitively healthy participants over 55 years old, at risk of developing Alzheimer Disease (AD) as their parents and/or siblings were/are affected by the disease. These ‘at-risk’ participants have been followed for a naturalistic study of the presymptomatic phase of AD since 2011 using multimodal measurements of various disease indicators. One clinical trial intended to test a pharmaco-preventive agent has also been conducted.
This PREVENT-AD dataset is available to researchers around the world with the intention to contribute to the community’s growing understanding of AD pathogenesis.
More detailed information about the study design can be found in the LORIS instance of Registered PREVENT-AD (https://registeredpreventad.loris.ca).
Data organization
A DATS.json
is present at the root of the dataset and describes the content of the dataset.
The dataset is organized in three different parts:
clinical-data
: clinical data spreadsheets and data dictionaryimages-in-BIDS
: images orgnized according to the BIDS standard in theBIDS_dataset
directory. Specifications of the BIDS standard are available here.images-in-MINC
: images provided in MINC format. In this portion of the dataset,candidate.json
contains demographic information regarding the candidate in question;visit.json
contains visit level information,handedness.json
when present, contains results of the Handedness Edinburgh Inventory
Note: the two images folders contain the same modalities and number of subjects/visits.
preventad-registered
|__DATS.json
|__README.md
|__clinical-data
|__AD8_Registered_PREVENTAD.csv
|__APS_Registered_PREVENTAD.csv
|__Auditory_processing_Registered_PREVENTAD.csv
|__BP_Pulse_Weight_Registered_PREVENTAD.csv
|__CSF_proteins_Registered_PREVENTAD.csv
|__Data_Dictionary_Registered_PREVENTAD.csv
|__Demographics_Registered_PREVENTAD.csv
|__EL_CAIDE_Registered_PREVENTAD.csv
|__EL_CDR_MoCA_Registered_PREVENTAD.csv
|__EL_Medical_history_Registered_PREVENTAD.csv
|__Genetics_Registered_PREVENTAD.csv
|__Lab_Registered_PREVENTAD.csv
|__List_of_participants_switched_back_to_cohort.txt
|__List_of_participants_with_only_1_sibling.txt
|__Med_categories.txt
|__Med_use_Registered_PREVENTAD.csv
|__RBANS_Registered_PREVENTAD.csv
|__Smell_identification_Registered_PREVENTAD.csv
|__images-in-BIDS
|__BIDS_dataset
|__dataset_description.json
|__participants.json
|__participants.tsv
|__README
|__sub-<candidate_id>
|__ses-<visit_label>
|__sub-<candidate_id>_ses-<visit_label>_scans.json
|__sub-<candidate_id>_ses-<visit_label>_scans.tsv
|__anat
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
...
|__asl
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
...
|__dwi
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.bval
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.bvec
...
|__fmap
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
...
|__func
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
|__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>_events.txt
...
|__images-in-MINC
|__candidate_id
|__candidate.json
|__visit_label
|__visit.json
|__handedness.json
|__images
|__image_1.mnc
|__image_2.mnc
|__image_3.mnc
...
For more information:
- LORIS registered database instance with the PREVENT-AD dataset: https://registeredpreventad.loris.ca
- PREVENT-AD study web site: https://prevent-alzheimer.net/
- PREVENT-AD Twitter account: https://twitter.com/prevent_ad
- Dataset DOI:
Links to the open dataset of PREVENT-AD (basic demographics and MRIs):
- LORIS open database instance with the PREVENT-AD dataset: https://openpreventad.loris.ca
- Open PREVENT-AD dataset: https://portal.conp.ca/dataset?id=projects/preventad-open
- Open PREVENT-AD BIDS dataset: https://portal.conp.ca/dataset?id=projects/preventad-open-bids
The following instructions require a basic understanding of UNIX/LINUX command lines. Future portal functionality may include downloads directly from the web browser. Dataset download is currently enabled through DataLad.
Note: The conp-dataset
requires version >=0.12.5 of DataLad
and version >=8.20200309 of git-annex.
To install DataLad on your system, please refer to the install section of the DataLad Handbook (installation via miniconda is recommended in order to obtain the latest version of DataLad).
1) Initiate the CONP dataset
To initiate the CONP dataset (conp-dataset
), run the following
command in the directory where you want CONP datasets to be installed:
datalad install https://github.com/CONP-PCNO/conp-dataset.git
2) Install the preventad-registered dataset
To install the dataset, go into the created conp-dataset directory and run
datalad install
on the dataset preventad-registered
:
cd conp-dataset
datalad install projects/preventad-registered
3) Download the preventad-registered dataset
Now that the DataLad dataset has been installed, go into the dataset
directory under projects/preventad-registered
.
cd projects/preventad-registered
Note that files visible in the dataset are symlinks and will need to be
downloaded manually using the
datalad get
command in the dataset directory:
datalad get <filepath>
Note, if you run datalad get *
command, all the files present
in the dataset directory will be downloaded.