EMIF-AD

EMIF-AD Project Background

With multiple clinical trials in dementia failing over the past years, attention has recently shifted to subjects with Alzheimer’s disease (AD) who have not reached the stage of dementia yet (i.e., ‘pre-dementia’). Since these subjects have limited brain damage and are suggested to be more likely responsive to treatment than subjects with full-blown dementia, they are an important target group for future treatment studies.

EMIF-AD Project Objectives

Prof Simon Lovestone, Oxford UniversityTrial design in pre-dementia AD, however, is challenging because subjects with pre-dementia AD are difficult to identify and limited information is available on their outcome. The lack of reliable diagnostic and prognostic markers for pre-dementia AD can be explained by the availability of only small-scale ongoing biomarker studies and longitudinal cohorts including these subjects. EMIF has linked this information and unlocked the true potential of these studies.

By connecting relevant cohort studies across Europe, EMIF-AD has set up a pan-European platform for large-scale research on biomarkers and risk factors for neurodegenerative disorders. The biomarker discovery activities in EMIF-AD were driven by an extreme phenotype approach, in which decline or biomarker status was used as the end point for biomarker discovery, rather than a clinical diagnosis. Doing so, EMIF-AD has developed new treatment targets, multimodality/omics diagnostic tools and qualification level biomarker datasets suitable for presentation to regulatory authorities prior to approval for use in clinical trials and practice.

Finally, prediction rules for cognitive decline in presymptomatic and prodromal AD were developed which will not only improve clinical diagnosis and prognosis, but equally support subject selection and stratification in future clinical trials. These achievements have been possible because EMIF-AD combined both large-scale patient cohorts, linkage with EHR data, and cutting edge biomarker discovery expertise.

Work Packages Overview

EMIF-AD

Identify predictors of Alzheimer’s Disease (AD) in the pre-clinical and prodromal phase

EMIF-AD
Work Packages (WP) for EMIF-AD Validate new biomarkers andselect subjects for prevention trials WP4 Biomarker discovery withextreme phenotypes as endpoint WP3 Characterise study populationand define extreme phenotypes WP2 Define study population and data collection WP1
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EMIF-AD Project Achievements

EMIF AD Catalogue

  • Tools developed to support data suitability via cohort selection and patient profile selection for research queries
  • The user-friendly EMIF Catalogue is now publicly available to search for AD cohorts of interest
    • Availability of European AD cohort information in one place will facilitate future research collaboration
  • Several initiatives, such as IMI-EPAD, DPUK, IMI-PRISM, JPND-EADB and INTERDEM have already taken up the EMIF Catalogue
AD Catalogue Statistics

EMIF Biomarker Discovery Study

  • Multi-modal approach for biomarker discovery developed that will be applied in several (sub) populations, ranging from healthy controls over mild cognitive impairment to AD dementia
  • Completed the clinical data harmonization and upload in tranSMART of 1200 subjects participating in the multimodality biomarker discovery study in WP3
  • Blood, CSF and DNA samples as well as scans and clinical data were centrally stored
  • This cohort will allow large-scale data analyses to discover new AD biomarkers
EMIF Biomarker Discovery Study

PreclinAD & EMIF 90+ Cohort Development

  • Establishment of large sample sets (500 & 1000 samples) for biomarker discovery in EMIF-AD by re-using data and samples of existing AD cohorts spread over Europe
  • Detailed AD phenotyping has been performed in 260 cognitively normal subjects, including 196 monozygotic twins
PreclinAD and EMIF 90+ Cohort Development

WP 1 Definition of study population data requirements and data collection

Pieter Jelle Visser (UM) – Michael Arrighi (Janssen)

UM (CO-LEAD), JANSSEN (CO-LEAD), UNIMAN, VUMC, IRCCFS-FBF, MAAT, CAMCOG, BI, PFIZER, ROCHE

GOALS & OBJECTIVES

The main objective is:

The overall aim of this WP is to collect data required for the development and validation of new biomarkers for predementia AD into an overarching EMIF. The data collected will be used for further analysis in WP 2 to WP 4.

The sub-objectives are:

  1. To select cohorts that can be used for biomarker discovery and validation
  2. To pool data from the cohort studies in a Private Remote Research Environment
  3. To link data from research cohorts to EHR
  4. To collect additional data of key AD biomarkers and cognitive markers in subjects from ongoing longitudinal cohort studies

WP 2 Characterisation of the study population and definition of extreme phenotypes

M. Gordon (BI), G. Novak (Janssen), S Engelborghs (UA), B. Dubois (UPMC)

BI, Janssen, UA, UPMC, VTT, VUmc, Maastricht, UM, GSK, Pfizer, Roche, CamCog, Newcastle, KCL, Oxford

GOALS & OBJECTIVES

The main objectives are:

  • To characterize the study population and
  • To define extreme phenotypes based on subjects selected in WP 1

The sub-objectives are:

  1. To provide summary statistics of the cohorts selected in WP 1
  2. To operationalize criteria for pre-symptomatic AD and prodromal AD
  3. To define extreme phenotypes based on rate of decline
  4. To develop a multivariate prediction model for cognitive decline
  5. To define extreme phenotypes based on AD biomarkers
  6. To define extreme phenotypes based on resilience to dementia at old age

WP 3 Biomarker Discovery

Simon Lovestone (UOXF) – Johannes Streffer (Janssen)

UOXF (CO-LEAD), Janssen (CO-LEAD), KCL, VUmc, UGOT, KI, VTT, IRCCS-FBF, PSPLC, VIB, MAAT, UZL, GSK, PFIZER, BI, ROCHE

GOALS & OBJECTIVES

The main objective is:

The objective of this WP is to discover new biomarkers and genetic markers for the diagnosis and prognosis of predementia AD using the ‘extreme phenotypes’ defined in WP 2.

The sub-objectives are:

  1. To perform proteomics in CSF and plasma
  2. To perform GWAS analyses, exome sequencing, assessment of epigenomic profiles, and transcriptome profiling
  3. To perform metabolomics in CSF and plasma
  4. To perform voxel based MRI analyses
  5. To develop multivariate and class prediction algorithms
  6. To generate assays for new biomarkers

WP 4 Validation of new biomarkers and identification and selection of individuals for pharmacological interventions

Hilkka Soininen (UEF) – Piotr Lewczuk (UKER) – Henrik Zetterberg (UGOT) – TBD (Janssen)

UEF (CO-LEAD), Janssen (CO-LEAD), VUmc, UGOT, IRCCS-FBF, UKER, MAAT, UZL, GSK, BI

GOALS & OBJECTIVES

The main objective is:

The main objective of this WP is to cross-validate biomarkers discovered in WP 3 in independent samples and to develop recruitment strategies for AD prevention trials.

The sub-objectives are:

  1. To cross-validate the new plasma, CSF, genetic and MRI markers from WP 3 in an independent cohort
  2. To investigate the relation between genetic risk factors and amyloid pathology on neuropathological examination
  3. To investigate the relation between new AD plasma markers and long-term cognitive decline in the general population
  4. To develop stepwise screening algorithms for recruitment of subjects with presymptomatic AD or prodromal AD
  5. To analyse data from ongoing prodromal AD trials
  6. To select sites for selection and inclusion for subjects in predementia AD trials