Open Science Datasets from PREVENT-AD, a Longitudinal Cohort of Pre-symptomatic Alzheimer’s Disease

Abstract

To move Alzheimer Disease (AD) research forward it is essential to collect data from large cohorts, but also make such data available to the global research community. We describe the creation of an open science dataset from the PREVENT-AD (PResymptomatic EValuation of Experimental or Novel Treatments for AD) cohort, composed of cognitively unimpaired older individuals with a parental or multiple-sibling history of AD. From 2011 to 2017, 386 participants were enrolled (mean age 63 years old ± 5) for sustained investigation among whom 349 have retrospectively agreed to share their data openly. Repositories are findable through the unified interface of the Canadian Open Neuroscience Platform and contain up to five years of longitudinal imaging data, cerebral fluid biochemistry, neurosensory capacities, cognitive, genetic, and medical information. Imaging data can be accessed openly at https://openpreventad.loris.ca while most of the other information, sensitive by nature, is accessible by qualified researchers at https://registeredpreventad.loris.ca. In addition to being a living resource for continued data acquisition, PREVENT-AD offers opportunities to facilitate understanding of AD pathogenesis.

Full text

NeuroImage: Clinical 31 (2021) 102733
Available online 17 June 2021
2213-1582/© 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Open science datasets from PREVENT-AD, a longitudinal cohort of
pre-symptomatic Alzheimer’s disease
Jennifer Tremblay-Mercier
a
,
2
, C´
ecile Madjar
a
,
b
,
2
, Samir Das
b
, Alexa Pichet Binette
a
,
e
,
Stephanie O.M. Dyke
b
,
e
,
h
, Pierre ´
Etienne
a
,
e
, Marie-Elyse Lafaille-Magnan
a
,
d
,
e
, Jordana Remz
a
,
Pierre Bellec
c
,
f
, D. Louis Collins
e
,
h
, M. Natasha Rajah
a
,
e
, Veronique Bohbot
a
,
e
,
Jeannie-Marie Leoutsakos
g
, Yasser Iturria-Medina
b
,
e
,
h
, Justin Kat
a
,
b
, Richard D. Hoge
b
,
e
,
f
,
h
,
Serge Gauthier
a
,
e
,
i
, Christine L. Tardif
e
,
h
, M. Mallar Chakravarty
a
,
e
, Jean-Baptiste Poline
b
,
e
,
h
,
Pedro Rosa-Neto
a
,
e
,
h
,
i
, Alan C. Evans
a
,
b
,
h
,
e
, Sylvia Villeneuve
a
,
b
,
h
,
e
, Judes Poirier
a
,
e
,
*
, John C.
S. Breitner
a
,
e
, the PREVENT-AD Research Group
1
a
StoP-AD Centre, Douglas Mental Health Institute Research Centre, Montr´
eal, QC, Canada
b
McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montr´
eal, QC, Canada
e
McGill University, Montr´
eal, QC, Canada
h
McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montr´
eal, QC, Canada
d
Centre for Child Development and Mental Health, Jewish General Hospital. Montr´
eal, QC, Canada
c
CRIUGM - Universit´
e de Montr´
eal, Montr´
eal, QC, Canada
f
Universit´
e de Montr´
eal, Montr´
eal, QC, Canada
g
John Hopkins University School of Medicine, Baltimore, MD, USA,
i
McGill University Research Centre for Studies in Aging, McGill University, Montr´
eal, QC, Canada
ARTICLE INFO
Keywords:
Pre-symptomatic Alzheimer Disease
Biomarkers
Observational cohort
Open Science
Neuroimaging
Cerebrospinal Fluid proteins
ABSTRACT
To move Alzheimer Disease (AD) research forward it is essential to collect data from large cohorts, but also make
such data available to the global research community. We describe the creation of an open science dataset from the
PREVENT-AD (PResymptomatic EValuation of Experimental or Novel Treatments for AD) cohort, composed of
cognitively unimpaired older individuals with a parental or multiple-sibling history of AD. From 2011 to 2017, 386
participants were enrolled (mean age 63 years old ±5) for sustained investigation among whom 349 have retro-
spectively agreed to share their data openly. Repositories are ndable through the unied interface of the Canadian
Open Neuroscience Platform and contain up to ve years of longitudinal imaging data, cerebral uid biochemistry,
neurosensory capacities, cognitive, genetic, and medical information. Imaging data can be accessed openly at
https://openpreventad.loris.ca while most of the other information, sensitive by nature, is accessible by qualied
researchers at https://registeredpreventad.loris.ca. In addition to being a living resource for continued data
acquisition, PREVENT-AD offers opportunities to facilitate understanding of AD pathogenesis.
* Corresponding author at: 6875 boul. Lasalle, Montreal H4H 1R3, Canada.
E-mail addresses: Jennifer.tremblay-mercier@douglas.mcgill.ca (J. Tremblay-Mercier), cecile.madjar@mcin.ca (C. Madjar), samir.das@mcgill.ca (S. Das), alexa.
pichetbinette@mail.mcgill.ca (A. Pichet Binette), stephanie.dyke@mcgill.ca (S.O.M. Dyke), pierre.emile.etienne.med@ssss.gouv.qc.ca (P. ´
Etienne), elyse.lafaille-
magnan@mail.mcgill.ca (M.-E. Lafaille-Magnan), jordana.remz.comtl@ssss.gouv.qc.ca (J. Remz), pierre.bellec@criugm.qc.ca (P. Bellec), louis.collins@mcgill.ca
(D. Louis Collins), maria.rajah@mcgill.ca (M. Natasha Rajah), veronique.bohbot@mcgill.ca (V. Bohbot), jeannie-marie@jhu.edu (J.-M. Leoutsakos), yasser.
iturriamedina@mcgill.ca (Y. Iturria-Medina), justin.kat@mail.mcgill.ca (J. Kat), rick.hoge@mcgill.ca (R.D. Hoge), serge.gauthier@mcgill.ca (S. Gauthier),
christine.tardif@mcgill.ca (C.L. Tardif), mallar.chakravarty@douglas.mcgill.ca (M. Mallar Chakravarty), jean-baptiste.poline@mcgill.ca (J.-B. Poline), pedro.
rosa@mcgill.ca (P. Rosa-Neto), alan.evans@mcgill.ca (A.C. Evans), sylvia.villeneuve@mcgill.ca (S. Villeneuve), judes.poirier@mcgill.ca (J. Poirier), john.
breitner@mcgill.ca (J.C.S. Breitner).
1
Data used in preparation of this article were obtained from the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease
(PREVENT-AD) program (https://prevent-alzheimer.net/?page_id=42&lang=en). A complete listing of the PREVENT-AD Research Group can be found at:
https://preventad.loris.ca/acknowledgements/acknowledgements.php?date=[2017-12-01].
2
these authors contributed equally to this work.
Contents lists available at ScienceDirect
NeuroImage: Clinical
journal homepage: www.elsevier.com/locate/ynicl
https://doi.org/10.1016/j.nicl.2021.102733
Received 1 March 2021; Received in revised form 11 June 2021; Accepted 14 June 2021

NeuroImage: Clinical 31 (2021) 102733
2
1. Background and Summary
Dementia is the nal stage of Alzheimer’s disease (AD), representing
the culmination of a process that begins decades before onset of symp-
toms (Dubois, 2016; Iturria-Medina, 2016; Villemagne, 2013). Charac-
terizing and tracking the pre-symptomatic stage of AD requires methods
sensitive to the disease’s early manifestations. These may include not
only subtle cognitive decline, but also biochemical changes and struc-
tural or functional brain alterations. Studying these pre-symptomatic
changes is crucial to a full understanding of AD, and their precise
measurement is critical for trials of interventions that seek to prevent
symptom onset.
To meet this challenge, in 2010 investigators at McGill University
and the Douglas Mental Health University Institute Research Centre
created a Centre for Studies on Prevention of Alzheimer’s Disease (StoP-
AD Centre). The Centre’s prime objective was to pursue innovative
studies of pre-symptomatic AD, with efforts to provide relatively
enriched samples for prevention trials requiring individuals at-risk of
developing the disease (Breitner, 2016). To this end, the StoP-AD Centre
developed an observational cohort for PRe-symptomatic EValuation of
Experimental or Novel Treatments for AD (PREVENT-AD). To increase
the probability that participants would harbor the earliest changes
associated with pre-symptomatic AD, entry criteria required intact
cognition and a parental or multiple-sibling family history of AD. It is
well-documented that populations with such a family history of AD-like
dementia have a 2–3 fold relative increase in risk of AD dementia
(Breitner, 1999; Huang, 2004).
The cohort was genotyped and followed by naturalistic studies of
cognition, neurosensory capacities, cerebrospinal uid (CSF) biochem-
istry, magnetic resonance neuroimaging (MRI) and by medical and
clinical evaluations. The goal was to test a vast array of well-known
biomarkers of AD pathology (amyloid and tau level in CSF) and neu-
rodegeneration (cortical thickness and volume), but also to include more
experimental measurements (e.g. episodic memory task fMRI) and other
promising biomarkers (e.g. neurosensory measures). Precise measure-
ment of the biomarkers mentioned above was required not only to
monitor the progression of asymptomatic AD, but also to assess the ef-
fects of preventive interventions years before symptom onset. The main
StoP-AD Centre clinical trial investigated the impact of naproxen so-
dium, a non-steroid anti-inammatory drug, on the trajectory of a
composite score of AD biomarkers (INTREPAD trial - NCT0270281).
Data collection protocols remained the same between 2011 and 2017
with only a few additions. The data repositories and related methods
described here refer to the data collected at the StoP-AD Centre, in the
observational cohort and the INTREPAD trial from November 2011 to
November 2017, the so-called PREVENT-AD ‘Stage 1′. During this in-
terval, a total of 425 participants completed their baseline visit (BL),
with 195 participants initially enrolled in the INTREPAD trial. A total of
386 met criteria for sustained investigation and 349 retrospectively
agreed to share their data openly (Fig. 1).
PREVENT-AD data are now broadly available as an open science
resource (Das, 2017; McKiernan, 2016; Wilkinson, 2016), providing
opportunities for a larger number of researchers to analyze this rich
dataset. Because the original PREVENT-AD ethics approval and consent
process did not fully address open science data sharing plans, several
steps related to ethics were required and are described below. Storage,
Fig. 1. PREVENT-AD candidates enrolled between November 2011 and November 2017. 425 participants performed a baseline visit (BL) among which the
datasets of 386 participants were shared with internal collaborators for analysis. 349 of these participants agreed to have their data openly shared, while one of them
specically refused to share data in the registered repository. MCI =Mild Cognitive Impairment, MRI =Magnetic Resonance Imaging.
J. Tremblay-Mercier et al.

NeuroImage: Clinical 31 (2021) 102733
3
management, quality control (QC), validation and distribution of
PREVENT-AD data were performed in LORIS, a system designed for
linking heterogeneous data (e.g. behavioral, clinical, imaging, geno-
mics) within a longitudinal context (Das, 2016, 2012). Up to 5 years of
longitudinal follow-up are shared as part of this Stage 1, which includes
a total of 1300 cognitive evaluations, 476 CSF sample analyses, 1559
MRI sessions and 1283 neurosensory tests, from 349 consenting
participants.
As this research program is evolving, new biomarkers are being
added. In February 2018, the data collection regimen was notably
modied after a short period of inactivity and is now focused mainly on
longitudinal cognitive, behavioral and lifestyle assessments as well as
new neuroimaging modalities. These additional variables will be
described in a PREVENT-AD ‘Stage 2′companion paper.
The multi-modal approach, the depth of the neurocognitive pheno-
typing of this population at increased risk of AD dementia along with the
longitudinal nature of this single-site study render this dataset excep-
tional. The methods section will describe the PREVENT-AD cohort
characteristics, data acquisition methods, and the approach used to
create the data repositories for dissemination to the wider research
community. Additional information about the PREVENT-AD program
can be found at http://prevent-alzheimer.net/.
2. Methods
2.1. Development of open science data sharing
Making the PREVENT-AD dataset available for open science was a
multi-step process achieved over approximately 2 years. The steps
required to prepare the dataset before its dissemination on an open
science platform included: ethical considerations (discussed below),
data preparation in a structured and standardized way, dataset docu-
mentation (data dictionary, label convention, etc) and development of
two LORIS databases for 1) Open and 2) Registered Access data
dissemination. Signicant efforts were needed to obtain additional
ethics approval for the open science plans and proceed with a re-consent
process for all participants. Most of the participants had remained
actively involved in StoP-AD Centre activities, and this greatly facili-
tated the re-consent process. We also attempted to contact participants
who were no longer associated with the Centre. We failed to reach only
13 participants out of 386 with data potentially to share. Even though
partially de-identied data had been prepared for sharing with collab-
orating research teams, additional dataset de-identication steps were
required to share data with a much larger community of researchers. For
example, all brain images were “scrubbed” to remove any potentially
identifying elds from their headers, and structural imaging modalities
were defaced to prevent facial re-identication using 3D rendering
(Fonov et al., 2018). Details about the procedure are described in the
Data Record section. Brain images presenting incidental ndings have
the potential of presenting unique features that could increase the risk of
potential re-identication. We decided to share these neuroimaging
scans with an additional level of protection. The initial PREVENT-AD
study codes were assigned a new “public” alphanumeric code (e.g.:
CONP0000000), to which a participant’s identity cannot directly be
linked; the ability to do so remaining exclusively with the StoP-AD team.
Decisions were made by PREVENT-AD investigators regarding the
choice of variables to be shared (based on quality, reliability, and level
of standardization) and their level of access (Open or Registered Access,
based on data sensitivity and the risk of potential re-identication or
misuse). Datasets were prepared for two different LORIS platforms
depending on the level of access. Open data are available to anyone who
requests an account, whereas a broader dataset is available through
Registered Access, available only to bona de researchers (Dyke, 2018).
Registration is approved by the StoP-AD team upon verication of the
applicant’s account information. Both repositories are discoverable
through the unied interface of the Canadian Open Neuroscience
Platform (CONP). Although costly, we expect that these efforts to pre-
pare shared resources will increase the rate of scientic discovery in
dementia research; this being our ultimate hope for people living with
AD and their families.
2.2. Eligibility and enrollment assessments
A study nurse conducted preliminary eligibility screening over the
phone or via an online questionnaire. Participants had to be 60 years of
age or older, with an exception that individuals between 55 and 59 years
old were eligible if their own age was within 15 years of symptom onset
of their youngest-affected rst-degree relative. Participants’ family
history of “AD-like dementia” was ascertained either by a compelling AD
diagnosis from an experienced clinician or, if such a report was not
available, by use of a structured questionnaire developed for the Cache
County Study (Breitner, 1999). The questionnaire was intended to
establish memory or concentration issues sufciently severe to cause
disability or loss of function, having an insidious onset and gradual
progression (as opposed to typical consequences of a stroke or other
sudden insult).
An on-site eligibility visit (visit label EL00) then included more
specic questions on family history of AD dementia, medical and sur-
gical history, pharmacological prole, lifestyle habits, as well as phys-
ical and neurological examinations, blood and urine sampling. The
blood sample was used for genotyping (see section 3.1) only after an
individual was declared eligible to the program. The CAIDE score
(Cardiovascular Risk Factors, Aging, and Incidence of Dementia risk
score) was derived using data collected at entry into the program (age,
sex, education, systolic blood pressure, body mass index (BMI), choles-
terol, physical activity and APOE
ε
4 status) (Kivipelto, 2006). Two
cognitive screening instruments assessed integrity of cognition: the
Table 1
Inclusion and Exclusion Criteria.
Inclusion criteria
→ Self-reported parental or multiple-sibling (2 or more*) history of Alzheimer-like
dementia
→ Age 60 years or older (persons aged 55–59 years and <15 years younger than their
affected index relative were also eligible)
→ Minimum of 6 years of formal education
→ Study partner available to provide information on cognitive status
→ Sufcient uency in spoken and written French and/or English
→ Ability and intention to participate in regular visits
→ Agreement for periodic donation of blood and urine samples
→ Agreement to participate in periodic multimodal assessments via MRI and LP for
CSF collection (LP optional at rst, then mandatory (in 2017) for participation)
→ Agreement to limit use of medicines as required by clinical trial protocols, if
applicable
→ Provision of informed consent of the different protocols
Exclusion criteria
→ Cognitive disorders - Known or identied during eligibility assessments (MoCA
and CDR or exhaustive neuropsychological evaluation when needed)
→ Use of acetyl-cholinesterase inhibitors including tacrine, donepezil, rivastigmine,
galantamine
→ Use of memantine or other approved prescription cognitive enhancer
→ Use of vitamin E at>600 i.u. / day or aspirin at >325 mg / day
→ Use of opiates (oxycodone, hydrocodone, tramadol, meperidine, hydromorphone)
→ Use of NSAIDs or regular use of systemic or inhalation corticosteroids
→ Clinically signicant hypertension (accepted if controlled medically), anemia,
signicant liver or kidney disease
→ Concurrent use of warfarin, ticlopidine, clopidrogel, or similar anti-coagulant
→ Current plasma Creatinine >1.5 mg/dl (132 mmol/l)
→ Current alcohol, barbiturate or benzodiazepine abuse/dependence
Inclusion and exclusion criteria for the PREVENT-AD observational cohort.
INTREPAD trial inclusion/exclusion criteria are specied in the publication
describing the results (18). *8 participants had only 1 sibling affected with AD-
like dementia. Refer to ‘List_participants_family_history_1_sibling_v1.0.txt’ le.
MRI: magnetic resonance imaging; LP: lumbar puncture; CSF: cerebrospinal
uid; MoCA: Montreal Cognitive Assessment; CDR: Clinical Dementia Rating;
NSAID: non-steroidal anti-inammatory drug.
J. Tremblay-Mercier et al.

NeuroImage: Clinical 31 (2021) 102733
4
Montreal Cognitive Assessment (MoCA) and the Clinical Dementia
Rating (CDR) Scale (Morris, 1993; Nasreddine, 2005) including its brief
cognitive test battery. When cognitive status was in doubt (MoCA
typically ≤26/30 or CDR >0), a complete evaluation (2.5 h of testing)
was performed by a certied neuropsychologist. The aim of this
assessment was to determine if the cognitive decits detected by the
screening tests fell within the range of mild cognitive impairment (MCI),
did not meet MCI criteria or were simply circumstantial, see section
‘Management of cognitive decline’ for more details.
Subsequently, during the enrollment visit (visit label EN00), a ~ 30-
minute Magnetic Resonance Imaging (MRI) session was acquired to rule
out structural brain disease, while simultaneously ensuring participants’
familiarity with the MRI environment. Handedness was determined
using the Edinburgh Handedness Inventory (Oldeld, 1971), and an
electrocardiogram was performed. Enrollment also required further
documentation of stable general health, availability of a study partner to
provide information on daily functioning, and willingness to comply
with study protocols (Table 1 for detailed inclusion/exclusion criteria).
Specic INTREPAD clinical trial inclusion/exclusion criteria are in the
publication describing results of the trial (Meyer, 2019). In brief, they
were similar except for additional criteria related to gastrointestinal
tract problems and specic contraindicated concomitant medication.
Final determination of eligibility for PREVENT-AD program was made
by clinical consensus between one or more study physicians, a research
nurse, and a neuropsychologist. All consent procedures fullled modern
requirements for human subjects’ protection, while avoiding excess
participant burden. Consent forms were carefully crafted to use simple
but comprehensive language (typically at an 8th grade reading level).
Protocols, consent forms and study procedures were approved by McGill
Institutional Review Board and/or Douglas Mental Health University
Institute Research Ethics Board. Specic consent forms were presented
prior to each experimental procedure.
2.3. Data collection overview
Eligible participants were enrolled either in the observational cohort
or in the INTREPAD trial as both started enrollment around the same
time. For both groups, the rst annual visit is called baseline, labeled
BL00, and follow-up (FU) visits are labeled FU12, FU24, FU36 and FU48,
corresponding to the number of months after the baseline visit.
Fig. 2. Timelines of observational cohort, INTREPAD trial. EL: eligibility visit; EN: enrolment visit; BL: Baseline visit; M: months.
J. Tremblay-Mercier et al.

NeuroImage: Clinical 31 (2021) 102733
5
Telephone follow-ups were conducted between on-site annual visits to
keep contact with the participant and to update clinical information.
Participants in the INTREPAD trial had more frequent on-site visits and
telephone follow-ups for safety purposes. See Fig. 2 for the data
collection timelines of the observational and trial cohorts.
2.3.1. Annual evaluations
During each longitudinal visit (BL00, FU12, FU24, FU36 and FU48)
for both observational and trial cohorts, a standardized cognitive eval-
uation, neurosensory tests, and an MRI scanning session (1 to 1.5 h)
were performed. On a separate day, participants who consented to the
procedure donated CSF samples via lumbar puncture (LP). Medical
conditions, pharmacological prole and various in-house health ques-
tionnaires were updated annually while blood and urine sampling,
neurological and physical examinations were also performed. Routine
laboratory results were obtained from a central medical laboratory in
the Montreal area while ten milliliters of blood were centrifuged, ali-
quoted (plasma and red blood cells) and stored for further analysis in Dr.
J. Poirier’s laboratory.
Details about each experimental procedure are described in section
4.
2.3.2. INTREPAD trial
INTREPAD (Investigation of Naproxen TReatment Effects in Pre-
symptomatic Alzheimer’s Disease; clinicaltrials.gov - NCT02702817) was
a randomized, double-blinded, placebo-controlled two-year trial of low
dose naproxen sodium (220 mg b.i.d.) conducted in 195 PREVENT-AD
participants. Trial recruitment began in March 2012 and ended in
March 2015. Treatment (active or placebo) duration was 24 months.
Standard annual PREVENT-AD evaluations were supplemented with an
additional identical session three months after randomization (FU03).
The 3-month assessment was intended to determine whether treatment-
related changes, if any, occurred gradually or had rapid onset. It also
served as a run-in period, with a modied Intent-to-Treat analysis design
that considered only those participants who remained on treatment
through this initial interval. The primary outcome of the trial was a
composite Alzheimer Progression Score (APS) derived using item
response theory from various cognitive and biomarker measures
(Leoutsakos, 2016). For other trial data (such as study drug compliance,
adverse events, etc), please refer to our results paper (Meyer et. al.,
2019) (Meyer, 2019).
2.3.3. Summary of the open science sub-sample
Among the 425 participants who underwent baseline visits, 386 were
conrmed as appropriate for nal data analysis (see Fig. 1 for reasons for
exclusion of the 39 others). From these, 349 participants (90.4%) con-
sented retrospectively to have their data included in the shared data
repositories under the principles of open science (one participant spe-
cically asked to only share data in the open repository leaving a
number of 348 in the registered repository). Ethnicity and genetic
background of the cohort are relatively homogeneous. The majority of
participants in the shared dataset come from the greater Montreal area
in Qu´
ebec, Canada; 98.9% are Caucasian and 86% have French as
mother tongue. Women are somewhat over-represented (102 men, 247
women) while the proportion of APOE
ε
4 carriers (4/4 =2.0%; 4/3 =
32.2%; 4/2 =4.3%) is slightly higher than the general Caucasian pop-
ulation (Farrer, 1997), in keeping with participants’ family history of
AD. PREVENT-AD participants are on average, younger than those in
most aging or AD studies, (mean age at baseline =63.6 ±5.1 years old),
are highly educated (15.4 ±3.3 years of education) and cognitively
unimpaired (MoCA score of 28.0 ±1.6 out of 30). Up to four years of
follow-ups are available (median 36-months of follow-up, IQR 36).
Twelve-month data (FU12) are available for 278 participants, 24-month
data (FU24) are available for 236 participants, 36-month (FU36) data
are available for 177 participants and 48-month (FU48) data are avail-
able for 116 participants. Three-month (FU03) are available for 150
INTREPAD participants.
2.4. Data collection methods (related to shared data only)
2.4.1. Genotyping
DNA was isolated from 200
μ
l whole blood using a QIASymphony
apparatus and the DNA Blood Mini QIA Kit (Qiagen, Valencia, CA, USA).
The standard QIASymphony isolation program was used following the
manufacturer’s instructions. Allelic variants of seven genes associated
with AD (De Beaumont, 2016; Gosselin, 2016; Leduc, 2015; Miron
(Preprint):, 2018; Miron, 2019, 2018) (APOE: rs429358 and rs7412,
BDNF: rs6265, HMGCR: rs3846662 BCHE: rs1803274, TLR4: rs4986790,
PPP2R1A: rs10406151, CDK5RAP2: rs10984186) were determined
using pyrosequencing (PyroMark24 or PyroMark96) or DNA microarray
(Illumina) and are shared in the registered repository.
2.4.2. Cognition
Cognitive performance over time was assessed using the ~ 30 min
Repeatable Battery for Assessment of Neuropsychological Status
(RBANS) (Randolph, 1998) at baseline and each subsequent follow-up
visit. This battery consists of 12 subtests (list learning, story learning,
gure copy, line orientation, picture naming, semantic uency, digit
span, coding, list recall, list recognition, story recall, gure recall) that
yield 5 Index scores (immediate memory, delayed memory, language,
attention and visuospatial capacities) and a total score. The battery is
available in both French and English in 4 equivalent versions to reduce
practice effects in longitudinal assessment. In the observational cohort,
the versions were administered in chronologic order A, B, C, D. For
participants enrolled in the INTREPAD trial, version A was administered
at baseline, and alternate forms were used in random order at follow-up
visits. The data were scored following the RBANS manual, which results
in age-adjusted Index scores with a mean of 100 and standard deviation
of 15. Subtest scores have a mean of 10 and standard deviation of 3.
Additionally, we scored all participants using norms specied for in-
dividuals aged 60–69 years, thereby allowing detection of potential
decline with advancing age. Both scores (age-adjusted and graded
exclusively using age 60–69 norms) are available in the registered data
repository.
At these annual visits, we also administered the AD8 questionnaire to
the study partner (a family member or friend in regular contact with the
study participant). The AD8 comprises 8 questions evaluating changes in
the participant’s memory and functional abilities, and is intended to
discriminate normal aging from very mild dementia (Galvin, 2005). AD8
total score and answers to each question are shared in the registered
repository.
2.4.2.1. Management of cognitive decline. Once the MoCA and CDR
performed at eligibility conrmed that the research participants were
cognitively intact at entry, we performed the baseline RBANS and fol-
lowed their cognition annually (+3-month FU in INTREPAD trial).
However, at each visit, if the cognitive test results were lower than ex-
pected and the cognitive status was in doubt (MoCA less than 26 or CRD
>0 (for screening tests at eligibility) or RBANS index score >1 SD below
the mean in two different cognitive domains (for the follow-ups)), a
complete cognitive evaluation was requested by the study physician and
was performed by a certied neuropsychologist. Suspicion of probable
mild cognitive impairment (MCI) after this neuropsychological evalua-
tion led to the exclusion (or ineligibility) of the research participant from
the research program and referral to an afliated memory clinic, as
needed. This procedure was implemented to ensure our cohort was
purely asymptomatic. An exception was made for participants from the
INTREPAD trial since we needed to monitor potential adverse events, so
INTREPAD participants showing cognitive decline were invited to pur-
sue their annual visit at our Center. Notably, a signicant portion of the
comprehensive neuropsychological evaluations, triggered by low test
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NeuroImage: Clinical 31 (2021) 102733
6
results, turned out to be reassuring and did not reveal any cognitive
decits. In these cases, the participants were invited to continue their
annual follow-up in our cohort as their low scores were considered
‘circumstantial’. From 2016, an extension to the PREVENT-AD protocol
was approved to allow the follow-up of PREVENT-AD participants who
developed MCI or dementia. Thus, the time point of conversion to
probable MCI is documented in the data sharing repository and data
related to this conversion point are also provided. This is described in
more detail in the Stage 2 data sharing companion paper, in preparation.
2.4.3. Neurosensory
2.4.3.1. Smell identication. Odor identication (OI) abilities were
tested in a 30-minute session in a well-ventilated room, using the stan-
dardized University of Pennsylvania Smell Identication Test (UPSIT)
(Doty et al., 1984). This test uses “scratch-and-sniff” stimuli of 40 items
(4 randomized booklets of 10 odorants each). Although the test can be
self-administered, a trained examiner administered the test to improve
reliability. The UPSIT was administered at baseline and each follow-up
visit, and total score and selected data are shared in the registered re-
pository. Additional information on the use of the UPSIT in PREVENT-
AD and related results are detailed in two publications (Lafaille-
Fig. 3. Workow of the MRI acquisition protocol. Images from 308 scanning sessions are available in the open LORIS instance (https://openpreventad.loris.ca),
while additional images of participants with incidental ndings (from n =37 participants) are shared in the registered LORIS instance (https://registeredpreventad.
loris.ca). A: The observational cohort participants (PRE) and the INTREPAD trial participants (NAP) enrolled between 2011 and May 2016 underwent the same
protocol with the exception that INTREPAD trial participants performed an additional 3-month time point. The task fMRI (referred as Encoding (Enc.) and Retrieval)
was performed at enrollment for practice, with the actual task performed at baseline and follow-up visits at 12, 24 and 48 months. MRI coil:12-channel. B: Workow
of the MRI data acquisition protocol for the observational cohort enrolled in and after June 2016 (n =48 participants). The task fMRI protocol was replaced by a
Multi-echo qT2* at enrollment and by a high-resolution T2W, GRE T2 star and a MP2RAGE at baseline. The MRI coil was upgraded to a 32-channel for this protocol.
T1W =MPRAGE (Magnetization Prepared Rapid Acquisition Gradient Echo); FLAIR =FLuid Attenuated Inversion Recovery; DWI =Diffusion Weighted Imaging;
ASL =Pseudo-Continuous Arterial Spin Labeling: RSN =Resting State BOLD (Blood Oxygen Level Determination); GRE T2 star =GRadient Echo T2*; Multi-echo
qT2* =12-Echo T2*; T2W =T2 -weighted.
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NeuroImage: Clinical 31 (2021) 102733
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Magnan, 2018, 2017).
2.4.3.2. Auditory processing. Central auditory processing (CAP) evalu-
ations were added to the study in 2014. This instrument is therefore not
available at all time points for every participant and was available only
in French. We used both the Synthetic Sentence Identication with
Ipsilateral Competing Message (SSI-ICM) test and the Dichotic Stimulus
Identication (DSI) test (Fifer, 1983; Speaks et al., 1967). After having
rst been assessed for simple auditory acuity (with monosyllabic
words), participants were asked to identify spoken “pseudo-sentences,”
either with various sound levels of a distracting background narrative
(SSI-ICM) or with dichotic binaural presentation (DSI). A session
including these two auditory tests could typically be completed in less
than 45 min. Selected auditory processing data are available in the
registered repository. Additional information on the use of the auditory
processing test in PREVENT-AD and related results are detailed in two
publications (Tuwaig, 2016, 2017).
2.4.4. Neuroimaging
All participants were scanned on a Siemens TIM Trio 3 Tesla Mag-
netic Resonance Imaging (MRI) scanner at the Brain Imaging Centre of
the Douglas Mental Health University Institute using a Siemens standard
12 or 32-channel coil (Siemens Medical Solutions, Erlangen, Germany).
The duration of MRI sessions varied between the different visits from 0.5
to 1.5 h and included structural and functional modalities (Fig. 3A).
Modalities acquired included T1-weighted, T2-weighted and Fluid-
attenuated inversion recovery (FLAIR) images, diffusion MRI, arterial
spin labeling (ASL), resting-state functional MRI and task functional MRI
to assess episodic memory (see Table 2 for parameters of each sequence).
After June 2016, new enrollees (n =48) underwent a slightly different
protocol where the task fMRI acquisitions were removed and the
following acquisitions added: a MP2RAGE for T1 maps, a multi-echo
gradient echo for T2* maps, and a high in-plane resolution T2-
weighted image to assess hippocampal subelds and brain microstruc-
ture. The 12-channel coil was replaced by a 32-channel coil for all ac-
quisitions with this new session protocol (Fig. 3B). The same images are
shared in the open and the registered repositories, but images of par-
ticipants presenting potentially identifying incidental ndings are pro-
vided through the registered LORIS instance only.
2.4.4.1. Episodic memory task fMRI. Episodic memory tasks for object-
location associations were performed by participants longitudinally,
but not part of the protocol at the 36 M visit. As previously mentioned,
those enrolled after June 2016 did not perform this task while the
existing cohort continued to complete it annually. The study design is
presented in a recent publication (Rabipour, 2020). In brief, participants
were scanned as they encoded an object and its left/right spatial location
on the screen. Forty-eight encoding stimuli were presented one at a time
for 2000 msec with a variable inter-trial interval (ITI). A twenty-minute
break followed encoding, during which time structural MRIs were ac-
quired. After this break, participants were presented with the associative
Table 2
PREVENT-AD MRI parameters.
Scan type Sequence Acquisition
parameters
Resolution
(mm3)
Scan
time
(min)
T1-weighted
anatomical
MPRAGE 3D sagittal; TR =
2300 ms; TE =2.98
ms; TI =900 ms; a
=9◦; FOV =
256x240x176 mm;
phase encode A-P;
BW =240 Hz/px;
GRAPPA 2.
1x1x1 5.12
Fluid
attenuated
T2-weighted
image
FLAIR 3D sagittal; TR =
5000 ms; TE =388
ms; TI =1800; FOV
=256x256x176
mm; phase encode
A-P; BW =781 Hz/
px; GRAPPA 2.
1x1x1 6.27
T2*-weighted
anatomical
GRE 3D transversal; TR
=650 ms; TE =20
ms; a =20◦; FOV =
350x263x350 mm;
phase encode R-L;
BW =200 Hz/px.
0.8x0.8x2 5.34
Multi-echo
T2*-
weighted
anatomical
Multi-echo
GRE
3D transversal; TR
=44 ms; TE =[2.84,
6.2, 9.56, 12.92,
16.28, 19.64, 23,
26.36, 29.72, 33.08,
36.44, 39.8]ms; a =
15◦; FOV =
350x263x350 mm;
phase encode R-L;
BW =500 Hz/px.
1x1x1 9.44
High-
resolution
T2-weighted
anatomical
T2-weighted
SPACE
3D coronal; TR =
2500 ms; TE =198
ms; FOV =
350x263x350 mm;
phase encode R-L;
GRAPPA =2; BW =
710 Hz/px.
0.6x0.6x0.6 10.02
T1 map MP2RAGE 3D sagittal; TR =
5000 ms; TE =2.91
ms; TI =[700,2500]
ms; a =[4◦, 5◦];
FOV =
256x240x176 mm;
phase encode A-P;
BW =240 Hz/px;
GRAPPA 2.
1x1x1x 8.22
Diffusion-
weighted
imaging
(DWI)
EPI 2D transversal; TR
=9300 ms; TE =92
ms; FOV =
192x192x130 mm;
phase encode A-P;
BW =1628 Hz/px.
b =[0,1000] s/mm2
with 1, 64()
directions
2x2x2 10.15
Perfusion
imaging
Pseudo
continuous-
ASL (PCASL)
EPI
TR =4000 ms; TR =
10 ms; a =90◦; FOV
=256x256mm; 16
slices; phase encode
A-P; BW =3004 Hz/
px; GRAPPA 2;
phase PF 7/8.
Label offset =100
mm; post label
delay =900 ms.
4x4x7 5.32
resting-state
functional
MRI (fMRI)
EPI 2D axial; TR =2000
ms; TE =30 ms; a =
90◦; FOV =256x256
mm; 32 slices; phase
encode A-P; BW =
2442/px.
4x4x4 5.04
Table 2 (continued )
Scan type Sequence Acquisition
parameters
Resolution
(mm3)
Scan
time
(min)
Task
functional
MRI (fMRI)
(Encoding
and
Retrieval)
EPI 2D axial; TR =2000
ms; TE =30 ms; a =
90◦; FOV =256x256
mm; 32 slices; phase
encode A-P; BW =
2442/px.
4x4x4 6.10;
15.10
Legend: TR =repetition time; TE =echo time; TI =inversion time; FOV =eld
of view; MPRAGE =magnetization prepared gradient echo; FLAIR =uid
attenuated inversion recovery; PCASL =pseudo-continuous arterial spin
labeling
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retrieval task in which they were presented with 96 objects (48 “old”-
previously encoded objects; 48 “new” objects) and were asked to make a
forced-choice between four-alternative answers: i) “The object is
FAMILIAR but you don’t remember the location”; ii) “You remember the
object and it was previously on the LEFT”; iii) “You remember the object and
it was previously on the RIGHT”; and iv) “The object is NEW”. Different
stimuli were employed at each visit allowing longitudinal data collec-
tion. Images used for the task were taken from a bank of standardized
stimuli (Brodeur, 2010; Brodeur et al., 2014). Six different versions of
the stimulus sets were presented in the following order for both the
observational cohort and the INTREPAD trial: enrolment scan: v1;
baseline scan: v2; follow-up 3 months: v3 (only in INTREAD trial),
follow-up 12 months: v4; follow-up 24 months: v5; follow-up 36 months:
no episodic memory task; follow-up 48 months: v6. The E-Prime
program (version 2) was used to run the experimental protocol and
collect behavioral data (Psychology Software Tools Inc., Pittsburgh, PA,
USA).
2.4.5. Cerebrospinal uid collection
Participants who consented to this procedure donated CSF samples
via lumbar puncture (LP) on a separate day from the main annual visit.
We link the CSF data to a specic time point as the LP procedure was
performed within 6 months of this annual visit (on average 28 days after
the annual visit). Given that serial LPs were initially only performed on
participants enrolled in INTREPAD, the majority of the CSF samples
come from INTREPAD participants (n =99 INTREPAD participants out
of 160 CSF donors who consented to share data with the research
community). In 2016, considering the overall success of the LP program
Table 3
Summary of the main variables available in Stage 1 PREVENT-AD repositories at each time point (n =349).
Dark blue shade: Data available in Open LORIS instance (openpreventad.loris.ca). No shade: Data available in the Registered LORIS instance (registeredpreventad.
loris.ca). BL: Baseline; FU: Follow-up; 03, 12, 24, 36, 48: number of months after baseline. CAIDE: Cardiovascular Risk Factors, Aging, and Incidence of Dementia risk
score; AD: Alzheimer Disease; Med use: Medication use; MRI: Magnetic Resonance Imaging; APOE: apolipoprotein E; MoCA: Montreal Cognitive Assessment; CDR:
Clinical Dementia Rating; RBANS: Repeatable Battery for the Assessment of Neuropsychological Status; AD8: AD8 Dementia Screening score; UPSIT: University of
Pennsylvania Smell Identication Test; CAP: Central Auditory Processing; CSF: Cerebrospinal Fluid; APS: Alzheimer Progression Score. §: FU03 only available for
participants in the INTREPAD clinical trial. * Family history of Alzheimer-like dementia: Self-reported at entry in the program but also updated at regular intervals. **
Blood test (non-fasted): Vitamin B12, glycosylated hemoglobin, thyroid stimulating hormone, total cholesterol, high density lipoprotein, low density lipoprotein.
***Breakdown of the MRI sessions is shown in Table 4; more MRI are available in the registered LORIS instance as it contains the MRI with incidental ndings.
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NeuroImage: Clinical 31 (2021) 102733
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(acceptance, tolerability, and retention through serial repetitions) serial
LPs were also performed in the broader observational cohort. Therefore,
some participants were enrolled in the LP protocol after their baseline
visit and may have CSF data only at later time point(s). In 2017, consent
for such LPs became an inclusion criterion for new participants.
LPs were performed by a neurologist (Dr. P. Rosa-Neto) with an
internationally accepted procedure that typically lasted less than 15
min. A large-bore introducer was inserted at the L3-L4 or L4-L5 inter-
vertebral space, after which the atraumatic Sprotte 24 ga. spinal needle
was used to puncture the dura. Up to 30 ml of CSF were withdrawn in
5.0 ml polypropylene syringes. These samples were centrifuged at room
temperature for 10 min at ~ 2000g, and then aliquoted in 0.5 ml
polypropylene cryotubes, and quick-frozen at −80 ◦C for long-term
storage. A video describing the procedure at the StoP-AD Centre is
available at https://www.youtube.com/watch?v =9kckrlBIR2E.
2.4.5.1. CSF analysis. Biomarkers for amyloid-beta (Aβ), tau and neu-
rodegeneration were analyzed in CSF samples. Typically, levels of Aβ
1-42
(n =475), total tau (t-Tau, n =476) and phosphorylated tau (
181
p-Tau,
n =476) were determined by enzyme-linked immunosorbent assay
using Innotest technology (Fujirebio) following the European
BIOMARK-APD validated and standardized protocol (Lelental, 2016).
Additional proteins and cytokines were also analyzed as part of other
subprojects and data are shared in our registered repository (ApoE ug/
mL n =340, PCSK9 ng/mL n =92, G-CSF pg/mL n =321, IL-15 pg/mL
n =321, IL-8 pg/mL n =321, VEGF pg/mL n =300).
2.5. Data management
The LORIS system was customized for the PREVENT-AD program to
facilitate data entry, storage, and data dissemination. Forms included
customized algorithms developed for aggregating various pieces of data
in a user-friendly manner. Numerous LORIS modules were also used to
facilitate the curation process, including a module to track the status of
the participants, a specic module on family history of AD and another
one on drug compliance, for example. The document repository and data
release modules facilitated the management of data distribution,
documentation and access.
3. Data Record
Basic demographics and longitudinal neuroimaging raw data can be
found in the open LORIS repository (https://openpreventad.loris.ca),
while datasets with more sensitive material such as cognitive, medical
and neurosensory information, genotypes, CSF measurements, etc., are
accessible to qualied researchers only at https://registeredpreventad.
loris.ca. PREVENT-AD repositories are discoverable via the Canadian
Open Neuroscience Platform (CONP) at https://portal.conp.ca.
Table 3 presents the list of Stage 1 PREVENT-AD shared data, their
level of access, the number of participants who provided data and at
which time points. MRI acquisitions available at each time point are
presented in Table 4. In the registered LORIS repository, (https://registe
redpreventad.loris.ca), all PREVENT-AD Stage 1 data are regrouped in
13 different CSV les accompanied by 3 text les and a detailed data
dictionary. The content of each le is described in Table 5.
3.1. Versions
Three releases were part of this Stage 1 data sharing. In April 2019,
we rst released data from 232 participants in the open repository
(OPEN version 1.0). In August 2020, we added 76 subjects into the same
open repository (OPEN version 2.0) for a total of 308 participants. We
are now releasing the registered data related to 348 participants
(Registered version 1.0).
3.2. Neuroimaging specicities
All MRI acquisitions are available in MINC and NIfTI le formats, the
latter being organized according to the Brain Imaging Data Structure
(BIDS) (Gorgolewski, 2016). Brain MRIs can directly be downloaded
following instructions provided in both LORIS instances. MRIs are
available for 308 participants in the open instance, while an additional
37 candidates with MRI presenting potentially identifying incidental
ndings are provided in the registered instance, for a total of 344 par-
ticipants (note: 4 participants did not undergo the MRI protocol and one
Table 4
MRI modalities available at each study visit - Stage 1 .
Scan abbreviations EN BL FU03
§
FU12 FU24 FU36 FU48
T1-weighted n =308*
n =344
n =307*
n =343
n =125*
n =145
n =236*
n =268
n =185*
n =213
n =137*
n =158
n =77*
n =88
ASL n =307*
n =343
n =124*
n =144
n =236*
n =268
n =184*
n =212
n =70*
n =83
n =77*
n =88
DWI n =304*
n =340
n =184*
n =212
n =132*
n =153
n =73*
n =84
FLAIR n =308*
n =344
n =184*
n =212
n =137*
n =158
n =76*
n =87
rs-fMRI n =307*
n =343
n =124*
n =144
n =236*
n =268
n =184*
n =212
n =136*
n =157
n =77*
n =88
task-encoding-BOLD practice n =258*
n =292
n =124*
n =144
n =229*
n =261
n =183*
n =210
n =76*
n =86
task-retrieval-BOLD practice n =257*
n =291
n =124*
n =144
n =229*
n =261
n =183*
n =210
n =76*
n =86
T2*-weighted †n =307*
n =343
n =125*
n =145
n =236*
n =268
n =184*
n =212
n =136*
n =157
n =77*
n =88
MP2RAGE †n =42*
n =44
n =1*
n =1
multi-echo GRE †n =46*
n =48
n =1*
n =1
T1-weigthed =MPRAGE (Magnetization Prepared Rapid Acquisition Gradient Echo); ASL =Pseudo-Continuous Arterial Spin Labeling; DWI =Diffusion Weighted
Imaging with 65 directions; FLAIR =FLuid Attenuated Inversion Recovery; rs-fMRI =Resting State functional Magnetic Resonance Imaging by Blood Oxygen Level
Determination. MRIs are available in Open and Registered LORIS instance (The Registered instance also contains MRI sessions of participants presenting incidental
ndings that are not present in the Open instance).
*open instance (without the scans presenting incidental ndings)
§FU03 only available for people who were in the clinical trial (n =150)
†only performed on a small subset of participants (n =48)
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NeuroImage: Clinical 31 (2021) 102733
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participant refused to share additional data in the registered repository).
3.3. Code availability
In the shared repositories, identifying elds (such as PREVENT-AD
participant’s ID, date of birth, date of MRI, etc) were scrubbed from
the MRI image headers using the DICOM Anonymization Tool (DICAT;
https://github.com/aces/DICAT), while anatomical images were
‘defaced’ using the defacing algorithm developed by Fonov et al. (2018),
which has been shown to not signicantly affect data processing out-
comes (Fonov et al., 2018). While the code for this algorithm was
slightly modied for integration into the LORIS platform, the algorithm
remained unchanged. The version of the script used to deface the
PREVENT-AD datasets is available in Github (https://github.com/cma
djar/Loris-MRI/blob/open_preventad_v20.1.0/uploadNeuroDB/bin/de
face_minipipe.pl).
For the episodic memory task fMRI, data were saved in .edat2 format
(readable by the program only), and as text les to facilitate future data
sharing. De-identication of the text les (scrubbing for dates and
PREVENT-AD study IDs) was performed using a script available on
Github (https://github.com/cmadjar/Loris-MRI/blob/open_preventad_
v20.1.0/tools/scrub_and_relabel_task_events.pl). De-identied data are
available in both repositories.
4. Technical validation
Data were entered in LORIS in duplicate to allow detection of dis-
crepancies between two entries of the same information and systematic
corrections of mistakes by the data entry personnel. In case of signicant
discrepancy, source documentation was reviewed and discussed among
the data entry crew and the clinical team. If needed, information was
reviewed with the participants by phone, or at next follow-up. LORIS has
several internal checks in place to detect any abnormalities and avoid
missing data in required elds, out of range values, etc. Additional QC
checks were implemented during data preparation for sharing.
4.1. Neuroimaging
Visual quality control of the raw anatomical images was performed
by a single rater via the PREVENT-AD LORIS study interface. Quality
control status, predened comments and text comments were saved
directly in LORIS. After the de-identication process, every image was
visually reviewed to ensure proper defacing and the absence of any
potentially identiable information.
5. Usage note
5.1. Terms of use
When accessing the shared data repositories, researchers agree to a
standard set of good data use practices, such as meeting ethics
Table 5
General overview of the content of each le, by alphabetical order, in the Stage
1 registered repository (registeredpreventad.loris.ca).
File names File
type
Description*
AD8_Registered_PREVENTAD CSV A brief informant
interview (8 questions) to
detect dementia (Galvin,
2005).
APS_Registered_PREVENTAD CSV Alzheimer Progression
Score: composite score
calculated in INTREPAD
participants only (
Leoutsakos, 2016).
Auditory_processing_Registered_PREVENTAD CSV Central Auditory
Processing, Test results
from DSI and SSI-ICM (
Fifer, 1983; Speaks et al.,
1967).
BP_Pulse_Weight_Registered_PREVENTAD CSV Blood Pressure, pulse, and
weight.
CSF_proteins_Registered_PREVENTAD CSV Concentration of proteins
related to AD in
cerebrospinal uid (CSF).
(tau, p-tau, amyloid-beta
1–42, ApoE, G-CSF, IL-15,
IL-8, VEGF, PCSK9).
Data_Dictionary_Registered_PREVENTAD CSV Document providing more
detail about the content of
other CSV les and
description of column
names.
Demographics_Registered_PREVENTAD CSV General information about
PREVENT-AD
participants, including
demographics, work
related information,
handedness, family history
of AD and MCI converters.
EL_CAIDE_Registered_PREVENTAD CSV Cardiovascular Risk
Factors, Aging, and
Incidence of Dementia risk
score (Kivipelto, 2006).
Calculated at eligibility.
EL_CDR_MoCA_Registered_PREVENTAD CSV Cognitive Screening tests:
Montreal Cognitive
Assessment & Clinical
Dementia Rating (Morris,
1993; Nasreddine, 2005).
EL_Medical_history_Registered_PREVENTAD CSV Medical History
information.
Genetics_Registered_PREVENTAD CSV Genotypes related to AD.
APOE, BChE, BDNF,
HMGCR, TLR4, PPP2R1A,
CDK5RAP2.
Lab_Registered_PREVENTAD CSV Blood test results.
Glycosylated hemoglobin,
thyroid stimulating
hormone, vitamin B12,
total cholesterol, high
density lipoprotein, low
density lipoprotein.
List_of_participants_with_only_1_sibling TXT List of participants with
only 1 sibling affected by
Alzheimer-like dementia.
List_of_participants_switched_back_to_cohort TXT List of participants who
were initially enrolled in
INTREPAD trial (NAP) but
failed to complete the 3-
month run-in period and
switched back to the
cohort (PRE).
Med_categories TXT List of medications by
categories. If a participant
is taking a medication not
in a category, it is
classied as ’other’.
Table 5 (continued )
File names File
type
Description*
Med_use_Registered_PREVENTAD CSV Self-reported medication
intake information
RBANS_Registered_PREVENTAD CSV Cognitive tracking test.
Repeatable Battery for the
Assessment of
Neuropsychological Status
(Randolph, 1998).
Smell_Identication_Registered_PREVENTAD CSV UPSIT: University of
Pennsylvania smell
identication test.
*More details are available in the Data_Dictionary_Registered.csv le.
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NeuroImage: Clinical 31 (2021) 102733
11
requirements and keeping the data secure. PREVENT-AD data must be
used for neuroscience research as stipulated in the consent forms and in
the Terms of Use. Authors publishing manuscripts using the PREVENT-
AD Stage 1 data must name PREVENT-AD as the source of data in the
abstract and or method section and cite this manuscript. The terms also
include agreements on commercialization and privacy (https://openpr
eventad.loris.ca/login/request-account/).
For reuse of the PREVENT-AD data, researchers need to carefully
read and understand the context of the data collection described in this
paper and in the documentation available in the data repositories.
5.2. Labeling convention
The label convention used in the PREVENT-AD dataset is available
when accessing the data repositories via the data dictionary.
5.2.1. Additional convention for the INTREPAD trial
Data collected for individuals enrolled in the trial are identied as
such in the repositories by the prex ‘NAP’ (e.g.: NAPFU12) in opposi-
tion to ‘PRE’ identifying the PREVENT-AD observational cohort (e.g.:
PREBL00). From the shared sub-group of participants (n =349), 11
initially enrolled in INTREPAD failed to complete the rst 3-months on
study drug (re.: adverse events, low compliance, etc). These cases had
their rsts visit labelled as ‘NAP’ and the rest as ‘PRE’ as they were
switched back to the observational cohort. Any participants who stayed
on the study drug for the minimum ‘run-in period’ of 3-months, kept
their prex ‘NAP’ even if the study drug was discontinued at any time
between FU03 and FU24. Participants’ visits also continued to be
identied as ‘NAP’ even after the end of the trial (Stage1: NAPFU36,
NAPFU48 and Stage 2: up to NAPFU84).
The treatment allocation regimen (naproxen vs placebo) information
is shared in the registered repository, but we suggest that data collected
in the observational cohort and the trial (treated group and placebo
group) can be merged for longitudinal analysis as no treatment effect
was demonstrated in the trial and visit protocols were identical for all
(Meyer, 2019).
6. Conclusion
6.1. Ongoing and future efforts
The StoP-AD Centre continues to collect data. The Stage 2 data
collection regimen includes additional neuroimaging techniques, such
as positron emission tomography (PET), magnetoencephalography
(MEG) and a modied MRI protocol, additional lifestyle, personality
traits and behavioral information as well as information on individuals
who developed MCI. These new acquisitions enhance the information
value of the PREVENT-AD data resource and expand the number of
longitudinal observations up to 96-months of follow-up. PREVENT-AD
Stage 2 datasets are also being prepared to be shared with the research
community. To facilitate data usage, Stage 1 and Stage 2 PREVENT-AD
datasets will be shared in the same data repositories.
At the StoP-AD Centre, our goal is to continue to keep our cohort of
participants engaged in our research program, carefully monitor their
cognition, gather new AD biomarkers using state-of-the-art technologies
and continue our involvements in the McGill University Open Science
Initiatives to make data available to the greater neuroscience research
community.
7. Data and code availability statements
All the information presented below is also provided in the
manuscript.
Data used in preparation of this article were obtained from the Pre-
symptomatic Evaluation of Novel or Experimental Treatments for Alz-
heimer’s Disease (PREVENT-AD) program (https://prevent-alzheimer.
net/?page_id=42&lang=en).
7.1. Data availability
Basic demographics and longitudinal neuroimaging raw data can be
found in the open LORIS repository (https://openpreventad.loris.ca),
while datasets with more sensitive material such as cognitive, medical
and neurosensory information, genotypes, CSF measurements, etc., are
accessible to qualied researchers only at https://registeredpreventad.
loris.ca. PREVENT-AD repositories are discoverable via the Canadian
Open Neuroscience Platform (CONP) at https://portal.conp.ca/.
7.2. Code availability
In the shared repositories, identifying elds (such as PREVENT-AD
participant’s ID, date of birth, date of MRI, etc) were scrubbed from
the MRI image headers using the DICOM Anonymization Tool (DICAT;
https://github.com/aces/DICAT), while anatomical images were
‘defaced’ using the defacing algorithm developed by Fonov and Collins
(2018). While the code for this algorithm was slightly modied for
integration into the LORIS platform, the algorithm remained un-
changed. The version of the script used to deface the PREVENT-AD
datasets is available in Github (https://github.com/cmadjar/Loris
-MRI/blob/open_preventad_v20.1.0/uploadNeuroDB/bin/deface_mini
pipe.pl).
For the episodic memory task functional MRI, data were saved in .
edat2 format (readable by the program only), and as text les to facil-
itate future data sharing. De-identication of the text les (scrubbing for
dates and PREVENT-AD study IDs) was performed using a script avail-
able on Github (https://github.com/cmadjar/Loris-MRI/blob/open_
preventad_v20.1.0/tools/scrub_and_relabel_task_events.pl).
CRediT authorship contribution statement
Jennifer Tremblay-Mercier: Investigation, Writing - original draft,
Data Curation, Visualization, Project administration. C´
ecile Madjar:
Software, Writing - original draft, Data curation, Formal analysis,
Visualization, Project administration. Samir Das: Project administra-
tion, Writing - review & editing, Resources. Alexa Pichet Binette:
Formal analysis, Writing - review & editing, Data curation. Stephanie
O.M. Dyke: Methodology, Writing - review & editing. Pierre ´
Etienne:
Conceptualization, Writing - review & editing, Supervision. Marie-Elyse
Lafaille-Magnan: Investigation, Writing - review & editing, Jordana
Remz, Data curation, Visualization, Software. Pierre Bellec: Method-
ology. D. Louis Collins: Methodology. M. Natasha Rajah: Methodol-
ogy. Veronique Bohbot: Methodology. Jeannie-Marie Leoutsakos:
Methodology. Yasser Iturria-Medina: Methodology. Justin Kat: Soft-
ware. Richard D. Hoge: Methodology. Serge Gauthier: Conceptuali-
zation. Christine L. Tardif: Methodology. M. Mallar Chakravarty:
Methodology, Writing - review & editing. Jean-Baptiste Poline: Su-
pervision, Funding acquisition, Writing - review & editing. Pedro Rosa-
Neto: Methodology, Investigation. Alan C. Evans: Supervision, Funding
acquisition. Sylvia Villeneuve: Writing - review & editing, Supervision.
Judes Poirier: Conceptualization, Writing - review & editing, Supervi-
sion, Funding acquisition. John C. S. Breitner: Conceptualization,
Writing - review & editing, Supervision, Funding acquisition, & the
PREVENT-AD Research Group.
Declaration of Competing Interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
J. Tremblay-Mercier et al.

NeuroImage: Clinical 31 (2021) 102733
12
Acknowledgments
PREVENT-AD was launched in 2011 as a $13.5 million, 7-year
public-private partnership using funds provided by McGill University,
the Fonds de Recherche du Qu´
ebec – Sant´
e (FRQ-S), an unrestricted
research grant from Pzer Canada, the J.L. Levesque Foundation, the
Lemaire Foundation, the Douglas Hospital Research Centre and Foun-
dation, the Government of Canada, and the Canada Fund for Innovation.
Private sector contributions are facilitated by the Development Ofce of
the McGill University Faculty of Medicine and by the Douglas Hospital
Research Centre Foundation (http://www.douglas.qc.ca/). CONP was
launched in 2018 and is funded, in part, by Brain Canada. Thanks to all
the nancial resources.
PREVENT-AD is the result of efforts of many other co-investigators
from a range of academic institutions and private corporations, as well
as an extraordinarily dedicated and talented clinical and technical as-
sistant staff, students, and post-doctoral fellows. Here is listed the entire
PREVENT-AD Research Group: https://preventad.loris.ca/acknowl-
edgements/acknowledgements.php?date =[2017-12-01]. The authors
thank David Fontaine, PhD, who oversaw cognitive testing at enroll-
ment, scored the RBANS cognitive evaluations, and administered addi-
tional cognitive evaluations when indicated. In Dr. Judes Poirier’s
laboratory we wish to mention the good work that has been carried out
by Anne Labont´
e, Doris Dea, Louise Th´
eroux, and Cynthia Picard for CSF
biomarker analyses, genotyping and more. Melissa Appleby, Laura
Mahar, Miranda Tuwaig, Marie-Elyse Lafaille-Magnan, Christina Kaza-
zian, Tanya Lee, Galina Pogossova, Renuka Giles, and Karen Wan
collected cognitive and neurosensory data, assisted with the MRI ses-
sions, entered data in LORIS and worked hard to obtain a high-quality
dataset, thanks to them. Drs. Tharick Ali Pascoal, Marina Tedeshi
Dauar, and Laksanun Cheewakriengkrai, dedicated time and energy to
assist during LPs and performed neurological assessments with the
research participants. Special thanks go to Marianne Dufour, adminis-
trative assistant, and to the clinical team; Ginette Mayrand, Joanne
Frenette, Val´
erie Gervais, Isabelle Vall´
ee, Rana El-Khoury, Leslie-Ann
Daoust and Fabiola Ferdinand, all nurses who met with participants and
were devoted to our participant’s well-being. Not to forget, everyone
working on data analysis, including Jeannie-Marie Leoutsakos for the
development of the APS and Melissa Savard, the PREVENT-AD data
analyst. We thank Benoit Jutras, PhD, from Universit´
e de Montreal, for
gifting us equipment to test central auditory processing. The authors
would like to acknowledge the continued support and participation of
the Canadian Open Neuroscience Platform (CONP) in making the
PREVENT-AD database accessible to the scientic community. Also, the
Healthy Brains for Healthy Lives (HBHL) initiative at McGill provided
platform support for the PREVENT-AD project, through its NeuroHub IT
infrastructure. We give an additional thanks to the LORIS team, at the
Montreal Neurological Institute, who recently accelerated our involve-
ment in broader data sharing, for the benet of the community. The
authors acknowledge the generosity and commitment of all research
participants who volunteered for this work and placed their trusts and
hope in this research program.
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