CONP Portal | PREVENT-AD registered data


Version: 2.0

Source: https://registeredpreventad.loris.ca

Authors: StoP-AD Center - Douglas Mental Health University Institute

Contact: Jennifer Tremblay-Mercier, jennifer.tremblay-mercier@douglas.mcgill.ca

Description: Longitudinal study of pre-symptomatic Alzheimer's Disease. Longitudinal data from 348 participants are available. This includes multi-modal MRI images, neuropsychological tests, neurosensory assessments, general medical history, genetics and cerebrospinal fluid proteins levels.

Licenses: https://registeredpreventad.loris.ca/images/PREVENT-AD_Terms_of_Use.png

Primary Publication: Rationale and Structure for a new Centre for Studies on Prevention of Alzheimer's Disease (StoP-AD). John C.S. Breitner et al. The Journal of Prevention of Alzheimer's Disease - JPAD Volume 3, Number 4, 2016. http://dx.doi.org/10.14283/jpad.2016.121

Dataset Download Instructions

CircleCI status

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.

For more information on how DataLad works, please visit the DataLad Handbook documentation .

Dataset README information

README.md

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 dictionary
  • images-in-BIDS: images orgnized according to the BIDS standard in the BIDS_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:

Links to the open dataset of PREVENT-AD (basic demographics and MRIs):