Projects
View
| Name | EMIF |
|---|---|
| Long Name | European Medical Information Framework |
| Description | European Medical Information Framework. The EMIF project aims to develop a common information framework of patient-level data that will link up and facilitate access to diverse medical and research data sources, opening up new avenues of research for scientists. To provide a focus and guidance for the development of the framework, the project will focus initially on questions relating to obesity and Alzheimer’s disease. |
| Objectives | 1. To establish an information framework to improve access to human health data by providing tools and workflows to discover, assess, access, and (re)use human health data. 2. To identify predictors and diagnostic biomarkers for Alzheimer’s Disease. 3. To identify predictors of metabolic complications in obesity. |
| Website | http://www.emif.eu/ |
| Start date | 01-01-2013 |
| End date | 30-06-2018 |
| Logo |  |
| Name | Projects | Type of institution | Country | |
|---|---|---|---|---|
| Synapse Research Management Partners SL | EPAD AMYPAD NEURONET EMIF ROADMAP | SME | Spain | |
| Janssen Pharmaceutica NV | EPAD ADAPTED AMYPAD IMPRiND EQIPD NEURONET EMIF IM2PACT PHAGO PRISM RADAR-CNS RADAR-AD ROADMAP IDEA-FAST Pharma-Cog EPND | EFPIA | Belgium | |
| Alzheimer Europe | EPAD AMYPAD MOPEAD AETIONOMY EMIF RADAR-AD ROADMAP NEURONET Pharma-Cog EPND | Patient/carers organisation | Luxembourg | |
| F. Hoffmann-La Roche AG | EPAD EQIPD EMIF PHAGO PRISM ROADMAP NEURONET IDEA-FAST Pharma-Cog EPND | EFPIA | Switzerland | |
| Institut De Recherches Servier | IMPRiND EMIF EQIPD Pharma-Cog | Academia | France | |
| Amgen | EPAD EMIF Mobilise-D | EFPIA | Belgium | |
| Merck Kommanditgesellschaft Auf Aktien | EMIF Mobilise-D Pharma-Cog | EFPIA | Germany | |
| Pfizer Limited | EPAD EQIPD EMIF IM2PACT PRISM Mobilise-D IDEA-FAST | EFPIA | United Kingdom | |
| UCB Biopharma SPRL | EPAD EQIPD AETIONOMY EMIF PD-MitoQUANT RADAR-CNS IDEA-FAST Pharma-Cog EPND | EFPIA | Belgium | |
| Erasmus Universitair Medisch Centrum Rotterdam | PRISM ADAPTED AETIONOMY EMIF ROADMAP EPAD IDEA-FAST | Academia | Netherlands | |
| Karolinska Institutet | EPAD AMYPAD MOPEAD AETIONOMY EMIF RADAR-AD | Academia | Sweden | |
| Glaxosmithkline Research And Development Ltd | EMIF Pharma-Cog | EFPIA | United Kingdom | |
| Novo Nordisk AS | IM2PACT EMIF | EFPIA | Denmark | |
| Aarhus Universitet | IMPRiND IM2PACT ROADMAP EMIF | Academia | Denmark | |
| Agenzia Regionale Di Sanita | EMIF | Academia | Italy | |
| European Institute For Health Records | EMIF | Academia | France | |
| European Molecular Biology Laboratory | EMIF | Academia | Germany | |
| Fondazione PENTA for The Treatment And Care Of Children With HIV-ONLUS | EMIF | Academia | Italy | |
| Fundacio Institut Universitari Per a La Recerca A L'Atencio Primaria De Salut Jordi Gol i Gurina | ROADMAP EMIF | Academia | Spain | |
| Goeteborgs Universitet | PHAGO ROADMAP EMIF EPND | Academia | Sweden | |
| Institut National De La Sante Et De La Recherche Medicale | EPAD EMIF Pharma-Cog | Academia | France | |
| Itä-Suomen Yliopisto/University of Eastern Finland | EMIF | Academia | Finland | |
| King's College London | PHAGO RADAR-CNS RADAR-AD EMIF PD-MIND EPND | Academia | United Kingdom | |
| Kobenhavns Universitet | IM2PACT ROADMAP EMIF | Academia | Denmark | |
| Leibniz-Institut Für Präventionsforschung Und Epidemiologie - BIPS GmbH | EMIF | Academia | Germany | |
| Provincia Lombardo Veneta - Ordineospedaliero Di San Giovanni Di Dio - Fatebenefratelli | RADAR-CNS EMIF Pharma-Cog | Academia | Italy | |
| Sorbonne Université/Université Pierre et Marie Curie | EMIF | Academia | France | |
| VU University Medical Center Amsterdam | EPAD AMYPAD IM2PACT PRISM MOPEAD RADAR-CNS RADAR-AD EMIF PRISM2 Pharma-Cog EPND | Academia | Netherlands | |
| Tartu Ulikool | EMIF | Academia | Estonia | |
| Teknologian Tutkimuskeskus VTT Oy | EMIF IDEA-FAST | Academia | Finland | |
| University Of Exeter | PRISM EMIF PD-MIND Pharma-Cog | Academia | United Kingdom | |
| University Of Manchester | EMIF | Academia | United Kingdom | |
| Universitat Pompeu Fabra | EMIF | Academia | Spain | |
| Universidade De Aveiro | EMIF | Academia | Portugal | |
| Universita di Pisa | EMIF | Academia | Italy | |
| Universitatsklinikum Erlangen | EMIF Mobilise-D | Academia | Germany | |
| Universiteit Antwerpen | EMIF | Academia | Belgium | |
| Universiteit Maastricht | ROADMAP EMIF EPND | Academia | Netherlands | |
| University College London | AMYPAD PD-MitoQUANT PHAGO EMIF | Academia | United Kingdom | |
| University Of Glasgow | EMIF IDEA-FAST | Academia | United Kingdom | |
| University Of Cambridge | EPAD IMPRiND PHAGO EMIF IDEA-FAST | Academia | United Kingdom | |
| University Of Helsinki | EMIF | Academia | Finland | |
| University Of Leicester | EPAD EMIF EPND | Academia | United Kingdom | |
| University Of Luebeck | EMIF | Academia | Germany | |
| University Of Oxford | EPAD IMPRiND IM2PACT RADAR-AD ROADMAP EMIF EPND | Academia | United Kingdom | |
| Universität Leipzig | EMIF Pharma-Cog | Academia | Germany | |
| Vib Center for Brain and Disease Research | IMPRiND EMIF | Academia | Belgium | |
| Cambridge Cognition Ltd | EMIF IDEA-FAST | SME | United Kingdom | |
| Concentris Research Management GmbH | PRISM EQIPD EMIF PRISM2 | SME | Germany | |
| Custodix NV | EMIF | SME | Belgium | |
| Electrophoretics Ltd | EMIF | SME | United Kingdom | |
| Genomedics SRL | EMIF | SME | Italy | |
| MAAT France | EMIF | SME | France | |
| Societa Servizi Telematici SRL | EMIF | SME | Italy | |
| Stichting Informatievoorziening Voor Zorg En Onderzoek | EMIF | SME | Netherlands | |
| Vestische Kinder und Jugendklinik | EMIF | Academia | Germany | |
| PHARMO Institute NV | EMIF | SME | Netherlands | |
| Universite Paul Sabatier Toulouse III | EMIF Pharma-Cog | Academia | France | |
| Universitätsklinikum Schleswig-Holstein | EMIF IDEA-FAST | Academia | Germany | |
| Boehringer Ingelheim International Gmbh | PRISM EPAD EQIPD AETIONOMY EMIF Pharma-Cog PRISM2 | EFPIA | Germany |
| WP number | Description | Project | |
|---|---|---|---|
| WP1 | Definition of study population data requirements and data collection | EMIF | |
| WP2 | Characterisation of the study population and definition of extreme phenotypes | EMIF | |
| WP3 | Biomarker discovery | EMIF | |
| WP4 | Validation of new biomarkers and identification and selection of individuals for pharmacological interventions | EMIF | |
| WP5 | Use carefully characterized extreme phenotypes to identify biomarkers of metabolic risk | EMIF | |
| WP6 | The investigation of heterogeneity in the metabolic consequences of obesity in medium-sized well phenotyped cohort studies | EMIF | |
| WP7 | Validate novel risk factors in general population in adults and children | EMIF | |
| WP8 | Identify and select individuals for pharmacological or non-pharmacological interventions | EMIF | |
| WP9 | Framework requirements and evaluation | EMIF | |
| WP10 | Governance, federation, DB fingerprinting, legal context and ethics | EMIF | |
| WP11 | Harmonisation and semantics | EMIF | |
| WP13 | Analysis, processing and visualisation methods and tools | EMIF | |
| WP14 | Architecture, solution development, security and privacy technologies | EMIF | |
| WP15 | Use and sustainability models, community building and outreach | EMIF | |
| WP16 | Project Management | EMIF | |
| WP12 | Data extraction, benchmarking, Data aggregation and linkage | EMIF |
| Deliverable number | Title | Project | Submission date | Link | Keywords | |
|---|---|---|---|---|---|---|
| D1.1 | Overview of available data sources | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d1_1_overview_available_data_exec_summary_website.pdf | ||
| D1.2 | Private Remote Research database environment with pooled data from research cohorts | EMIF | 30-06-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d1_2_prre_research_cohorts_exec_summary_website.pdf | ||
| D1.3 | Dataset with EHR data linked to research cohort data | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d1.3_dataset-with-ehr-data-linked-to-research-cohort-data.pdf | ||
| D1.4 | Cohort of cognitively normal subjects with AD biomarkers baseline data | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d1.4_cohort-of-cognitively-normal-subjects-with-ad-biomarkers-baseline-data.pdf | ||
| D1.5 | Cohort of cognitively normal subjects with 2-year follow-up data | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d1.5_cohort-of-cognitively-normal-subjects-with-2year-followup-data.pdf | ||
| D2.1 | Summary statistics of cohorts included | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d2_1_summary_statistics_exec_summary_website.pdf | ||
| D2.2 | Validated criteria for presymptomatic AD and prodromal AD | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d2_2_criteria_presymptomatic_prodromal_ad_exec_summary_website.pdf | ||
| D2.3 | Definition of extreme phenotypes based on cognitive decline | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d2_3_extreme_phenotypes_cognitive_decline_exec_summary_website.pdf | ||
| D2.4 | Prediction model for cognitive decline | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d2_4_prediction_model_cognitive_decline_exec_summary_website.pdf | ||
| D2.5 | Definition of extreme phenotypes based on AD biomarkers | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d2_5_extreme_phenotypes_ad_biomarkers_exec_summary_website.pdf | ||
| D2.6 | Definition of extreme phenotypes based on resilience to dementia | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d2.6_definition-of-extreme-phenotypes-based-on-resilience-to-dementia.pdf | ||
| D3.1 | 4 Proteomic based plasma markers for diagnosis | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.1_4-proteomic-based-plasma-markers-for-diagnosis.pdf | ||
| D3.2 | 4 Proteomic based plasma markers for prognosis | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.2_4-proteomic-based-plasma-markers-for-prognosis.pdf | ||
| D3.3 | 2 Proteomic based CSF markers for prognosis | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3_3_2_proteomic_based_csf_markers_for_prognosis-2.pdf | ||
| D3.4 | 2 Metabolomics based plasma markers for diagnosis | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.4_2-metabolomics-based-plasma-markers-for-diagnosis.pdf | ||
| D3.6 | 4 GWAS-identified SNPs for abnormal CSF abeta and tau and hippocampal atrophy | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.6_4-gwasidentified-snps-for-abnormal-csf-abeta-and-tau-and-hippocampal-atrophy.pdf | ||
| D3.8 | 4 Epigenomic profiles associated with abnormal AD CSF biomarkers | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.8_4-epigenomic-profiles-associated-with-abnormal-ad-csf-biomarkers.pdf | ||
| D3.10 | Novel combinatorial MRI marker algorithms for diagnosis | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3_10_novel_combinatorial_mri_marker_algorithms_exec_summary_website.pdf | ||
| D3.11 | 2 novel combinatorial MRI marker algorithms for prognosis | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.11_2-novel-combinatorial-mri-marker-algorithms-for-prognosis.pdf | ||
| D3.12 | Integrative model of biomarkers from different modalities | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.12_integrative-model-of-biomarkers-from-different-modalities.pdf | ||
| D3.13 | 10 Assays of biomarkers for clinical use | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.13_10-assays-of-biomarkers-for-clinical-use.pdf | ||
| D3.14 | Report joint study AD/Metabolic | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d3.14_report-joint-study-admetabolic.pdf | ||
| D4.1 | Report on cross-validated plasma, genetic CSF, MRI markers for predementia AD | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d4.1_report-on-crossvalidated-plasma-genetic-csf-mri-markers-for-diagnosis-for-predementia-of-ad.pdf | ||
| D4.2 | Screening algorithms tested and defined | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d4.2_screening-algorithms-tested-and-defined.pdf | ||
| D9.1 | Initial requirements and benchmarks set | EMIF | 28-02-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d9_1_user_requirements_exec_summary_website.pdf | ||
| D9.2 | Platform requirements v1 and Evaluation Plan | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d9_2_platform_requirements_exec_summary_website.pdf | ||
| D9.3 | Interim framework evaluation results and requirements v2 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d9_3_interim_framework_evaluation_exec_summary_website.pdf | ||
| D9.4 | Second framework evaluation results and requirements v3 | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d9_4_second_framework_evaluation_exec_summary_website.pdf | ||
| D9.5 | Final evaluation results and roadmap for future development | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d9.5_final-evaluation-results-and-roadmap-for-future-development.pdf | ||
| D10.1 | Initial database fingerprinting | EMIF | 31-03-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d10_1_initial_fingerprinting_exec_summary_website.pdf | ||
| D10.2 | First report on federation procedures, ethical and legal issues | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d10_2_federation_procedures_exec_summary_website.pdf | ||
| D10.3 | Full database fingerprinting | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d10_3_full_fingerprinting_exec_summary_website.pdf | ||
| D10.4 | First draft of the EMIF Ethical Code of Practice | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d10_4_first_draft_ethical_code_of_practice_exec_summary_website.pdf | ||
| D10.5 | Final report on federation procedures, legal and ethical issues (including final version of the EMIF Ethical Code of Practice) | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d10.5_-final-version-of-the-emif-code-of-practice.pdf | ||
| D11.1 | Initial specification of the semantic framework of reference | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d11_1_semantic_framework_initial_exec_summary_website.pdf | ||
| D11.2 | First version of common data model and associated terminology mapping | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d11_2_first_version_cdm_exec_summary_website.pdf | ||
| D11.3 | Extended specification of the semantic framework of reference | EMIF | 30-06-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d11_3_semantic_framework_extended_exec_summary_website.pdf | ||
| D11.4 | First complete version of the harmonised information model and associated terminology mapping | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d11_4_complete_version_cdm_exec_summary_website.pdf | ||
| D11.5 | Second version of the harmonised information model and associated terminology mapping | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d11_5_second_version_cdm_exec_summary_website.pdf | ||
| D11.6 | Final report on harmonisation and semantics | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d11.6_final-report-on-harmonisation-and-semantics.pdf | ||
| D12.1 | Data extraction software v1 | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12_1_data_extraction_software_v1_exec_summary_website.pdf | ||
| D12.2 | Data extraction software v2 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12_2_data_extraction_software_v2_exec_summary_website.pdf | ||
| D12.3 | Interim report on primary data flows, benchmarking and quality analyses | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12_3_benchmarking_data_quality_exec_summary_website.pdf | ||
| D12.4 | Report on data linkage | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12_4_report_data_linkage_exec_summary_website.pdf | ||
| D12.5 | Interim report on specialised data extraction, benchmarking, aggregation and processing | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12_5_interim_report_specialised_data_exec_summary_website.pdf | ||
| D12.6 | Final version of data extraction software | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12.6_final-version-data-extraction-software.pdf | ||
| D12.7 | Final report on data flows, data integration, processing and linkage | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d12.7_final-report-on-data-flows-data-integration-processing-and-linkage.pdf | ||
| D13.1 | Evaluation of technologies and tools available for data analysis and visualisation | EMIF | 30-06-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d13_1_tools_for_data_analysis_and_visualisation_full_webiste.pdf | ||
| D13.2 | Data analysis tools for vertical projects v1 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d13_2_data_analysis_tools_for_vertical_projects_v1_full_website.pdf | ||
| D13.3 | Data analysis and visualisation tools, including workflows for linkage with omics data v1 | EMIF | 30-06-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d13_3_data_analysis_visualisation_tools_v1_full_website.pdf | ||
| D13.4 | Data analysis tools for vertical projects v2 | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d13_4_data_analysis_tools_for_vertical_projects_v2_full_webiste.pdf | ||
| D13.5 | Data analysis and visualisation tools, including workflows for linkage with omics data v2 | EMIF | 31-10-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d13_5_data_analysis_visialisation_tools_v2_full_website.pdf | ||
| D13.6 | Final suite of modules and tools for data analysis, visualisation and linkage of EHR data with omics data | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d13.6_final-suite-of-modules-and-tools-for-data-analysis.pdf | ||
| D14.1 | First report on the EMIF-Platform design and architecture including specifications for privacy protection tools and services | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_1_platform_architecture_v1_exec_summary_website.pdf | ||
| D14.2 | A data management solution for vertical projects, version 1 | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_2_data_mgt_verticals_exec_summary_website.pdf | ||
| D14.3 | EMIF-Platform, version 1 | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_3_platform_v1_exec_summary_website.pdf | ||
| D14.4 | System implementation feedback and evaluation report, iteration 1 | EMIF | 30-04-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_4_system_implementation_feedback_v1_exec_summary_website.pdf | ||
| D14.5 | A data management solution for vertical projects, version 2 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_5_data_management_verticals_exec_summary_website.pdf | ||
| D14.6 | EMIF-Platform, version 2 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_6_platform_v2_exec_summary_website.pdf | ||
| D14.7 | First EMIF-Platform architecture stack | EMIF | 31-08-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_7_platform_architecture_stack_exec_summary_website.pdf | ||
| D14.8 | EMIF-Platform, version 3 | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_8_platform_v2_exec_summary_website.pdf | ||
| D14.9 | System implementation feedback and evaluation report, iteration 3 | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_9_system_implementation_feedback_v3_exec_summary_website.pdf | ||
| D14.10 | EMIF-Platform, version 4 | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14_10_platform_v4_exec_summary_website.pdf | ||
| D14.11 | System implementation feedback and evaluation report, iteration 4 | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14.11_system-implementation-feedback-and-evaluation-report-4.pdf | ||
| D14.12 | Update on EMIF-Platform design, architecture and application guidelines, and Final EMIF-Platform | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d14.12_emif-platform.pdf | ||
| D15.1 | Report on business models for data exploitation in biosciences | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15_1_business_models_exec_summary_website.pdf | ||
| D15.2 | Market analysis: usage models and data sources characterisation | EMIF | 31-08-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15_2_market_analysis_exec_summary_website.pdf | ||
| D15.3 | Initial business model description | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15_3_initial_business_model_exec_summary_website.pdf | ||
| D15.4 | First report on outreach activities: leveraging with related initiatives, contacts with external data sources and with key stakeholders | EMIF | 30-04-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15_4_report_outreach_activities_exec_summary_website.pdf | ||
| D15.5 | First Draft business plan | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15_5_draft_business_plan_exec_summary_website.pdf | ||
| D15.6 | Second Draft Business plan | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15_6_second_draft_business_plan_exec_summary_website.pdf | ||
| D15.7 | Final Business plan | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15.7_final-business-plan.pdf | ||
| D15.8 | Final report on outreach activities: leveraging with related initiatives, contacts with external data sources and with key stakeholders | EMIF | 30-06-2018 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d15.8_final-report-on-outreach-activities.pdf | ||
| D16.1 | Operational portal to allow internal team information dissemination, team collaboration, and team document storage. | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_1_operational_portal_exec_summary_website.pdf | ||
| D16.2 | Templates for dissemination materials: logo design, PPT and poster templates, newsletter formats | EMIF | 31-03-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_2_templates_dissemination_exec_summary_website.pdf | ||
| D16.4 | Communication Plan | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_4_communication_plan_exec_summary_website.pdf | ||
| D16.5 | Project Handbook | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_5_project_handbook_exec_summary_website.pdf | ||
| D16.6 | Guidance document for EMIF Scientific Publications | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_6_dissemination_process_exec_summary_website.pdf | ||
| D16.10 | Detailed project and risk plans for WP1‐15 | EMIF | 30-06-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_10_risk_overview_v1_exec_summary_website.pdf | ||
| D16.11 | Updated project and risk plans for WP1‐15 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_11_risk_overview_v2_exec_summary_website.pdf | ||
| D16.12 | Technical and Financial Annual Reports #1 | EMIF | 31-12-2013 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_12_annual_report_year1_exec_summary_website.pdf | ||
| D16.13 | Technical and Financial Annual Reports #2 | EMIF | 31-12-2014 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_13_annual_report_year2_exec_summary_website.pdf | ||
| D16.14 | Interim Assessment of the Project | EMIF | 31-08-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_14_interim_assessment_project_exec_summary_website.pdf | ||
| D16.15 | Technical and Financial Annual Reports #3 | EMIF | 31-12-2015 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_15_annual_report_year3_exec_summary_website.pdf | ||
| D16.16 | Technical and Financial Annual Reports #4 | EMIF | 31-12-2016 | http://www.emif.eu/wp-content/uploads/2019/01/emif_d16_16_annual_report_year4_exec_summary_website.pdf |
| Title | First author last name | Year | Project | Link | Keywords | |
|---|---|---|---|---|---|---|
| Age dependency of risk factors for cognitive decline | Legdeur | 2018 | EMIF | https://doi.org/10.1186/s12877-018-0876-2 | Clinical research paper, cognitive decline, risk factors, aging, oldest-old | |
| Capturing the Alzheimer’s disease pathological cascade | Tijms | 2018 | EMIF | https://doi.org/10.1016/S1474-4422(18)30043-7 | Opinion paper, amyloid, Alzheimer's disease, biomarker, brain imaging, disease progression | |
| Amyloid-β, Tau, and Cognition in Cognitively Normal Older Individuals: Examining the Necessity to Adjust for Biomarker Status in Normative Data | Bos | 2018 | EMIF | https://doi.org/10.3389/fnagi.2018.00193 | Clinical research paper, amyloid, tau, biomarker, cognition, dementia, ADNI | |
| Inter-laboratory Proficiency Processing scheme in CSF aliquoting: Implementation and assessment based on biomarkers of Alzheimer’s Disease | Lewczuk | 2018 | EMIF | http://dx.doi.org/10.1186/s13195-018-0418-3 | Clinical research paper, CSF, biomarker, tau, Amyloid, Alzheimer's disease, training | |
| The EMIF-AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics | Bos | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0396-5 | Clinical research paper, study protocol, study design, biomarker, cognitive, ApoE, dementia, Alzheimer's disease | |
| MRI predictors of amyloid pathology: results from the EMIF-AD multimodal biomarker discovery study | Ten Kate | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0428-1 | Clinical research paper, MRI, amyloid, mild cognitive impairment, ApoE, brain imaging | |
| CSF non-phosphorylated Tau as a biomarker for the discrimination of AD from CJD | Ermann | 2018 | EMIF | https://doi.org/10.1002/acn3.584 | Clinical research paper, biomarker, CSF, Tau, Alzheimer's disease, Creuzfeld-Jacob disease | |
| Diagnostic value of cerebrospinal fluid tau, neurofilament, and progranulin in definite frontotemporal lobar degeneration | Goossens | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0364-0 | Clinical research paper, biomarkers, tau, amyloid, CSF, Alzheimer's disease, frontotemporal lobar degeneration | |
| White paper by the Society for CSF Analysis and Clinical Neurochemistry: Overcoming barriers in biomarker development and clinical translation | Teunissen | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0359-x | White paper, CSF, biomarker, neurological disease, Alzheimer's disease | |
| Neurogranin as Cerebrospinal Fluid Biomarker for Alzheimer Disease: An Assay Comparison Study | Willemse | 2018 | EMIF | https://doi.org/10.1373/clinchem.2017.283028 | Clinical research paper, biomarker, CSF, dementia, frontotemporal dementia, Alzheimer's disease, Dementia with lewy bodies, vascular dementia, diagnosis | |
| Added Diagnostic Value of Cerebrospinal Fluid Biomarkers for Differential Dementia Diagnosis in an Autopsy-Confirmed Cohort | Niemantsverdriet | 2018 | EMIF | https://doi.org/10.3233/JAD-170927 | Clinical research paper, CSF, biomarker, dementia, diagnosis, cohort | |
| Long Non-Coding RNAs Associated with Metabolic Traits in Human White Adipose Tissue. | Gao | 2018 | EMIF | https://doi.org/10.1016/j.ebiom.2018.03.010 | Basic science research paper, clinical research, lncRNA, adipocyte, metabolism, RNA-seq | |
| Gray matter network disruptions and amyloid beta in cognitively normal adults | Ten Kate | 2018 | EMIF | https://doi.org/10.3389/fnagi.2018.00067 | Clinical research paper, amyloid, PET, MRI, Alzheimer's disease | |
| Plasma neurofilament light as a potential biomarker of neurodegeneration in Alzheimer's disease | Lewczuk | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0404-9 | Clinical research paper, biomarker, amyloid, tau, Alzheimer's disease | |
| Amyloid β oligomers (AβOs) in Alzheimer's disease | Mroczko | 2018 | EMIF | https://doi.org/10.1007/s00702-017-1820-x | Review article, biomarkers, amyloid, CSF, Alzheimer's disease | |
| A Specific Reduction in Aβ1-42 vs. a Universal Loss of Aβ Peptides in CSF Differentiates Alzheimer's Disease from Meningitis and Multiple Sclerosis. | Spitzer | 2018 | EMIF | https://doi.org/10.3389/fnagi.2018.00152 | Clinical research paper, biomarker, CSF, amyloid, Alzheimer's disease, meningitis, multiple sclerosis, diagnosis | |
| White matter hyperintensities and vascular risk factors in monozygotic twins | Ten Kate | 2018 | EMIF | https://doi.org/10.1016/j.neurobiolaging.2018.02.002 | Clinical research paper, MRI, brain imaging, risk factor, vascular | |
| Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia | Jansen | 2018 | EMIF | https://doi.org/10.1001/jamapsychiatry.2017.3391 | Clinical research paper, amyloid, cognition, mild cognitive impairment, MMSE, dementia | |
| Screening of Potential Adipokines Identifies S100A4 as a Marker of Pernicious Adipose Tissue and Insulin Resistance | Arner | 2018 | EMIF | https://doi.org/10.1038/s41366-018-0018-0 | Clinical research paper, adipokine, adipose tissue, obesity, diabetes | |
| Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation | Lewczuk | 2018 | EMIF | https://doi.org/10.1080/15622975.2017.1375556 | Consensus paper, biomarker, Alzheimer's disease, dementia, CSF, review | |
| Dementia prevalence and incidence in a federation of European Electronic Health Record databases: The European Medical Informatics Framework resource | Perera | 2018 | EMIF | https://doi.org/10.1016/j.jalz.2017.06.2270 | Clinical research paper, Dementia, Incidence, Prevalence, Electronic Health Records, European Medical Informatics Framework | |
| Cellular Receptors of Amyloid β Oligomers (AβOs) in Alzheimer's Disease | Mroczko | 2018 | EMIF | https://doi.org/10.3390/ijms19071884 | Review article, amyloid beta oligomer, protein aggregation, AβO receptors, Alzheimer’s disease, neurodegeneration | |
| The EMIF-AD PreclinAD study: study design and baseline cohort overview | Konijnenberg | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0406-7 | Clinical research paper, clinical study protocol, Preclinical Alzheimer’s disease, Amyloid, Cognitively normal, Monozygotic twins, [18F]flutemetamol | |
| Key Ethical Challenges in the European Medical Information Framework | Floridi | 2018 | EMIF | https://doi.org/10.1007/s11023-018-9467-4 | Medical ethics paper, data ethics, ethics of algorithms, health ethics, GDPR | |
| MONTRA: An agile architecture for data publishing and discovery | Silva | 2018 | EMIF | https://doi.org/10.1016/j.cmpb.2018.03.024 | Informatics research paper, biomedical databases, data catalogues, patient registries, clinical studies | |
| A methodology for fine-grained access control in exposing biomedical data | Trifan | 2018 | EMIF | https://doi.org/10.3233/978-1-61499-852-5-561 | Methodology paper, bioinformatics, data access, data sharing | |
| Real world data reveal a diagnostic gap in non-alcoholic fatty liver disease | Alexander | 2018 | EMIF | https://doi.org/10.1186/s12916-018-1103-x | Clinical research paper, epidemiology, real world data, electronic health records, population, NAFLD, NASH | |
| A modular workflow management framework | Almeida | 2018 | EMIF | http://doi.org/10.5220/0006583104140421 | Conference proceedings, informatics, task Management, workflow Management, clinical studies. | |
| A methodology to perform semi-automatic distributed EHR database queries | Fajarda | 2018 | EMIF | http://doi.org/10.5220/0006579701270134 | Methodology paper, electronic health records, observational studies, cohorts, clinical research, secondary use of data | |
| A De-Identification Pipeline for Ultrasound Medical Images in DICOM Format. | Monteiro | 2018 | EMIF | https://doi.org/10.1007/s10916-017-0736-1 | Informatics research paper, medical imaging, OCR, neural networks, deep-learning, de-identification | |
| comoRbidity: An R package for the systematic analysis of disease comorbidities. | Gutiérrez-Sacristán | 2018 | EMIF | https://doi.org/10.1093/bioinformatics/bty315 | Informatics research paper, electronic health records, R, software, comorbidity | |
| Identifying temporal patterns in patient disease trajectories using dynamic time warping: A population-based study | Giannoula | 2018 | EMIF | https://doi.org/10.1038/s41598-018-22578-1 | Informatics research paper, clinical research paper, electronic health records, comorbidity, bioinformatics, disease prediction | |
| The frequency and influence of dementia risk factors in prodromal Alzheimer's disease | Bos | 2017 | EMIF | https://doi.org/10.1016/j.neurobiolaging.2017.03.034 | Clinical research paper, Alzheimer's disease, Risk factors, IWG-2 criteria, NIA-AA criteria, Biomarkers, Prognosis | |
| Does genetic risk help to predict amyloid burden in a non-demented population? A Bayesian approach | Voyle | 2017 | EMIF | https://doi.org/10.1101/174995 | Clinical research paper, informatics, amyloid, risk factor, CSF, ApoE, ADNI | |
| Strategic roadmap for an early diagnosis of Alzheimer’s disease based on biomarkers | Frisoni | 2017 | EMIF | https://doi.org/10.1016/S1474-4422(17)30159-X | Opinion paper, biomarkers, Alzheimer's disease, diagnostics, brain imaging | |
| Amyloid-independent atrophy patterns predict time to progression to dementia in MCI | Ten Kate | 2017 | EMIF | https://doi.org/10.1186/s13195-017-0299-x | Clinical research paper, MRI, amyloid, brain imaging, mild cognitive impairment, dementia, CSF | |
| Cerebrovascular and amyloid pathology in predementia stages: the relationship with neurodegeneration and cognitive decline | Bos | 2017 | EMIF | https://doi.org/10.1186/s13195-017-0328-9 | Clinical research paper, MRI, amyloid, cognitive decline, cerebrovascular dysfunction | |
| Clinical validity of medial temporal atrophy as a biomarker for Alzheimer’s disease in the context of a structured 5-phase development framework | Ten Kate | 2017 | EMIF | https://doi.org/10.1016/j.neurobiolaging.2016.05.024 | Review article, recommendations, clinical research, biomarker, MRI, Alzheimer's disease | |
| Cognitive functioning of individuals aged 90 years and older withoutdementia: A systematic review | Legdeur | 2017 | EMIF | https://doi.org/10.1016/j.arr.2017.02.006 | Systematic review, dementia, cognition, aging, MMSE scores | |
| Brain Amyloid Pathology and Cognitive Function - Alzheimer Disease Without Dementia? | Visser | 2017 | EMIF | https://doi.org/10.1001/jama.2017.6895 | Editorial, biomarker, amyloid, Alzheimer's disease, dementia, MRI, brain imaging | |
| Association of blood lipids with Alzheimer’s Disease: a comprehensive lipidomics analysis | Proitsi | 2017 | EMIF | https://doi.org/10.1016/j.jalz.2016.08.003 | Clinical research paper, Alzheimer's disease, Dementia, Brain atrophy, sMRI, Rate of cognitive decline, Lipidomics, Metabolomics, Biomarkers, Machine learning, Multivariate, Classification | |
| Real world big data for clinical research and drug development | Singh | 2017 | EMIF | https://doi.org/10.1016/j.drudis.2017.12.002 | Review article, informatics, big data, real world data, electronic health records, drug development | |
| General guidelines for biomedical software development | Silva | 2017 | EMIF | https://doi.org/10.12688/f1000research.10750.2 | Guidelines, informatics, biomedical software, software development, bioinformatics, Agile, | |
| Data Integration and Sharing Supporting Drug R&D | Sanz | 2017 | EMIF | https://doi.org/10.1016/B978-0-12-409547-2.12297-8 | Review article, Biana, Big data, ChEMBL, ClinicalTrials.gov, Data integration, Data management, Databases, DisGeNET, diXa, Drug Bank, DSSTox, EMIF, eTOX, EU-ADR, EudraCT, EudraPharm, HIPPIE, Human Interactome database, Open PHACTS, Reactome, STRING, SureChEMBL, Text-mining, Tox21, ToxCast | |
| The European Institute for Innovation through Health Data | Kalra | 2016 | EMIF | http://dx.doi.org/10.1002/lrh2.10008 | Commentary, electronic health records, health data, data sharing, clinical research, big data | |
| Using Electronic Health Records to Assess Depression and Cancer Comorbidities | Mayer | 2017 | EMIF | https://doi.org/10.3233/978-1-61499-753-5-236 | Clinical research paper, informatics, electronic health records, depression, cancer, comorbidities | |
| Nine Principles of Semantic Harmonization | Cunningham | 2017 | EMIF | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5333211/ | Recommendations, informatics, clinical cohort data, data harmonisation, EMIF Knowledge Object Library | |
| Mitochondrial genes are altered in blood early in Alzheimer's disease | Lunnon | 2017 | EMIF | https://doi.org/10.1016/j.neurobiolaging.2016.12.029 | Clinical research paper, Mitochondria, Alzheimer's disease, Gene expression, Blood, Biomarker, Mild cognitive impairment, Oxidative phosphorylation | |
| Functional and effective whole brain connectivity using magnetoencephalography to identify monozygotic twin pairs | Demuru | 2017 | EMIF | https://doi.org/10.1038/s41598-017-10235-y | Clinical research paper, PreclinAD, EEG, Neurophysiology, Neuroscience | |
| Cerebrospinal Fluid Aβ42/40 Corresponds Better than Aβ42 to Amyloid PET in Alzheimer's Disease | Lewczuk | 2016 | EMIF | http://dx.doi.org/10.3233/JAD-160722 | Clinical research paper, Alzheimer’s disease, amyloid-β, biomarker, cerebrospinal fluid, positron emission tomography | |
| Complement Biomarkers as predictors of disease progression in Alzheimer’s disease | Hakobyan | 2016 | EMIF | https://dx.doi.org/10.3233/JAD-160420 | Clinical research paper, Alzheimer’s disease, MCI, biomarker, complement, inflammation, plasma | |
| Identificare i casi di diabete tipo 2 in una rete di fonti di dati eterogenee la strategia del progetto EMIF | Roberto | 2016 | EMIF | https://www.ars.toscana.it/files/progetti/informatica_medica/BEN_diabete2_EMIF.pdf | Clinical research paper, electronic health records, diabetes, algorithms | |
| Non-Phosphorylated Tau as a Potential Biomarker of Alzheimer’s Disease: Analytical and Diagnostic Characterization | Lewczuk | 2016 | EMIF | https://dx.doi.org/10.3233/JAD-160448 | Clinical research paper, biomarkers, cerebrospinal fluid, phosphorylation, tau | |
| Genetic risk and plasma tau as markers of amyloid-beta and tau burden in cerebrospinal fluid | Voyle | 2016 | EMIF | https://dx.doi.org/10.3233/JAD-160707 | Clinical research paper, Alzheimer’s disease, biomarker, blood, multi-modal, polygenic risk score, tau | |
| Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project | Roberto | 2016 | EMIF | https://dx.doi.org/10.1371/journal.pone.0160648 | Clinical research paper, diabetes, diagnosis, algorithms, harmonisation | |
| Data Safe Havens and Trust: Toward a Common Understanding of Trusted Research Platforms for Governing Secure and Ethical Health Research | Lea | 2016 | EMIF | https://dx.doi.org/10.2196/medinform.5571 | Opinion paper, clinical research support, data safe havens, genomics research support, health record linkage supported research, legislative and regulatory compliance, public engagement, public involvement, trusted research platforms, trusted researchers | |
| Genetic variations underlying Alzheimer's disease: evidence from genome-wide association studies and beyond | Cuyvers | 2016 | EMIF | https://dx.doi.org/10.1016/S1474-4422(16)00127-7 | Review article, Alzheimer's disease, ApoE, TREM2, risk, GWAS | |
| A Decade of Cerebrospinal Fluid Biomarkers for Alzheimer's Disease in Belgium | Somers | 2016 | EMIF | https://dx.doi.org/10.3233/JAD-151097 | Clinical research paper, Alzheimer’s disease, amyloid, biomarkers, cerebrospinal fluid, dementia, diagnosis, mild cognitive impairment, neuropathology, tau | |
| Validation of microRNAs in Cerebrospinal Fluid as Biomarkers for Different Forms of Dementia in a Multicenter Study | Müller | 2016 | EMIF | https://dx.doi.org/10.3233/JAD-160038 | Clinical research paper, Alzheimer’s disease, Lewy body disease, cerebrospinal fluid, frontotemporal dementia, microRNAs, mild cognitive impairment | |
| sTREM2 cerebrospinal fluid levels are a potential biomarker for microglia activity in early-stage Alzheimer's disease and associate with neuronal injury markers. | Suárez-Calvet | 2016 | EMIF | https://dx.doi.org/10.15252/emmm.201506123 | Clinical research paper, CSF, Alzheimer's disease, TREM2, biomarkers, microglia, neurodegeneration | |
| Gray matter network disruptions and amyloid beta in cognitively normal adults | Tijms | 2016 | EMIF | https://dx.doi.org/10.1016/j.neurobiolaging.2015.10.015 | Clinical research paper, Alzheimer's disease, Amyloid beta, Cognitively normal adults, Graph theory, Gray matter, MRI, Single-subject | |
| Diagnostic Impact of Cerebrospinal Fluid Biomarker (Pre-)Analytical Variability in Alzheimer's Disease | Niemantsverdriet | 2016 | EMIF | https://dx.doi.org/10.3233/JAD-150953 | Clinical research paper, Alzheimer’s disease, MCI, biomarkers, cerebrospinal fluid, diagnostic accuracy, differential dementia diagnosis | |
| Impact of APOE-e4 and family history of dementia on gray matter atrophy in cognitively healthy middle-aged adults | Ten Kate | 2016 | EMIF | https://dx.doi.org/10.1016/j.neurobiolaging.2015.10.018 | Clinical research paper, Alzheimer's disease, Apolipoprotein E, Dementia, Family history, MRI, Voxel-based morphometry | |
| Semantic Knowledge Base Construction from Radiology Reports | Monteiro | 2016 | EMIF | https://dx.doi.org/10.5220/0005709503450352 | Informatics research paper, Semantic Web, Healthcare Information Management, Clinical Reports, Radiology, Text-mining. | |
| Comparison of Different Matrices as Potential Quality Control Samples for Neurochemical Dementia Diagnostics | Lelental | 2016 | EMIF | https://www.ncbi.nlm.nih.gov/pubmed/26967210 | Clinical research paper, Alzheimer’s disease, amyloid-β, biomarkers, cerebrospinal fluid, laboratory diagnostics, quality control, tau | |
| PsyGeNET: a knowledge platform on psychiatric disorders and their genes | Gutiérrez-Sacristán | 2015 | EMIF | https://dx.doi.org/10.1093/bioinformatics/btv301 | Informatics research paper, risk factors, platform, database text mining, depression, addiction | |
| Alzheimer's disease - Recent biomarker developments in relation to updated diagnostic criteria | Höglund | 2015 | EMIF | https://dx.doi.org/10.1016/j.cca.2015.01.041 | Review article, Alzheimer's disease, Biomarker, Cerebrospinal fluid, Diagnosis, Tau, β-Amyloid | |
| Validation of the Erlangen Score Algorithm for the prediction of the development of dementia due to AD in pre-dementia subjects | Lewczuk | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-150342 | Clinical research paper, Alzheimer’s disease, ADNI, diagnosis, biomarkers, cerebrospinal fluid, clinical neurochemistry, results interpretation, validation | |
| Age-stratified prevalence of mild cognitive impairment and dementia in European populations, a systematic review | Alexander | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-150168 | Clinical research paper, short communication, meta-analysis, Dementia, epidemiology, mild cognitive impairment, prevalence | |
| A novel multi-tissue diagnostic of healthy ageing can determine cognitive health status using blood RNA | Sood | 2015 | EMIF | https://dx.doi.org/10.1186/s13059-015-0750-x | Clinical research paper, Alzheimer's disease, genetic profiling, biomarker | |
| Boosting translational research on Alzheimer's disease in Europe: The Innovative Medicine Initiative AD research platform | Vaudano | 2015 | EMIF | https://dx.doi.org/10.1016/j.jalz.2015.02.002 | Review article, opinion paper, Alzheimer's disease, IMI, incidence | |
| No evidence to suggest that the use of acetylcholinesterase inhibitors confounds the results of two blood-based biomarker studies in Alzheimer’s disease | Chiam | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-150289 | Clinical research paper, Alzheimer’s disease, blood, cholinesterase inhibitors, gene expression, microarray, protein, proteomics | |
| Biomarkers for Alzheimer's disease: a controversial topic | Frisoni | 2015 | EMIF | https://dx.doi.org/10.1016/S1474-4422(15)00150-7 | Commentary, Alzheimer's disease, biomarker, CSF, Tau, Amyloid, PET | |
| Generalizability of the disease state index prediction model for identifying patients progressing from mild cognitive impairment to Alzheimer's disease. | Hall | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-140942 | Clinical research paper, Alzheimer's disease, computer-assisted diagnosis, dementia, magnetic resonance imaging (MRI), mild cognitive impairment | |
| Blood protein markers of Neocortical Amyloid Burden: A candidate study using SOMAscan technology | Voyle | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-150020 | Clinical research paper, Alzheimer’s disease, amyloid plaques, blood, positron emission tomography scan, proteomics, biomarker | |
| Cerebrospinal fluid P-tau181P: biomarker for improved differential diagnosis | Struyfs | 2015 | EMIF | https://dx.doi.org/10.3389/fneur.2015.00138 | Clinical research paper, Alzheimer’s disease, biomarkers, cerebrospinal fluid, dementia, differential diagnosis, neuropathology, tau | |
| Plasma protein biomarkers of Alzheimer’s disease endophenotypes in asymptomatic older twins: early cognitive decline and regional brain volumes | Kiddle | 2015 | EMIF | https://dx.doi.org/10.1038/tp.2015.78 | Clinical research paper, Alzheimer's disease, blood, biomarker, proteomics, MAPK | |
| Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis | Jansen | 2015 | EMIF | https://dx.doi.org/10.1001/jama.2015.4668 | Clinical research paper, meta-analysis, Longitudinal, Observational, Biomarkers, Cognitive markers, Alzheimer's disease, Asymptomatic, MCI, Dementia | |
| Importance and impact of pre-analytical variables on Alzheimer’s disease biomarker levels in cerebrospinal fluid | Le Bastard | 2015 | EMIF | https://dx.doi.org/10.1373/clinchem.2014.236679 | Clinical research paper, Alzheimer's disease, biomarker, CSF, amyloid, tau | |
| Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage | Vos | 2015 | EMIF | https://dx.doi.org/10.1093/brain/awv029 | Clinical research paper, Alzheimer’s disease, MCI, biomarkers, diagnostic criteria, IWG-1, IWG-2, prognosis | |
| Linking genetics of brain changes to Alzheimer’s disease: sparse whole genome association scan of regional MRI volumes in the ADNI and AddNeuroMed cohorts | Khondoker | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-142214 | Clinical research paper, Alzheimer's disease, GWAS, imaging quantitative trait loci, magnetic resonance imaging, mild cognitive impairment | |
| An Integrated Workflow for Multiplex CSF Proteomics and Peptidomics-Identification of Candidate Cerebrospinal Fluid Biomarkers of Alzheimer's Disease | Hölttä | 2015 | EMIF | https://dx.doi.org/10.1021/pr501076j | Clinical research paper, Alzheimer’s disease, biomarker discovery, cerebrospinal fluid, clinical proteomics, mass spectrometry, neurodegenerative disease, peptidomics, quantification | |
| TDP-43 as a possible biomarker for frontotemporal lobar degeneration: a systematic review of existing antibodies | Goossens | 2015 | EMIF | https://dx.doi.org/10.1186/s40478-015-0195-1 | Systematic review, TDP-43, Antibodies, Immunoassay, Biomarkers, Frontotemporal lobar degeneration (FTLD) | |
| Overdiagnosing vascular dementia using structural brain imaging for dementia work-up | Niemantsverdriet | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-142103 | Clinical research paper, short communication, Alzheimer's disease, brain imaging, dementia, differential dementia diagnosis, MRI, vascular dementia | |
| Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer’s disease | Proitsi | 2015 | EMIF | https://dx.doi.org/10.1038/tp.2014.127 | Clinical research paper, Alzheimer's disease, MCI, metabolomics, plasma, cholesterol, diagnosis | |
| Diagnostic accuracy of CSF amyloid-β isoforms for early and differential dementia diagnosis | Struyfs | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-141986 | Clinical research paper, Alzheimer's disease, MCI, amyloid, biological markers, cerebrospinal fluid, diagnosis | |
| Reuse of EHRs to Support Clinical Research in a Hospital of Reference | Mayer | 2015 | EMIF | https://dx.doi.org/10.3233/978-1-61499-512-8-224 | Informatics research paper, clinical research, electronic health records, database, diabetes, dementia, platform | |
| Blood protein predictors of brain amyloid for enrichment in clinical trials? | Ashton | 2015 | EMIF | https://doi.org/10.1016/j.dadm.2014.11.005 | Clinical research paper, Alzheimer's disease, Plasma, β amyloid, Proteomics, Biomarker, Fibrinogen γ-chain, ageing | |
| Longitudinal protein changes in blood plasma associated with the rate of cognitive decline in Alzheimer's disease | Sattlecker | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-140669 | Clinical research paper, Alzheimer’s disease, MCI, cognitive decline, complement cascade, cytokine-cytokine receptor interaction, plasma, proteomics | |
| Alzheimer's disease: a report from the 7th Kuopio Alzheimer symposium | Haapasalo | 2015 | EMIF | https://doi.org/10.2217/nmt.15.31 | Conference report, Alzheimer's disease, biomarkers, brain imaging, diagnosis, prediction, prevention, randomized controlled trial | |
| A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis | Voyle | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-150440 | Clinical research paper, Alzheimer’s disease, blood, gene expression, microarray, pathways | |
| Challenges and opportunities for exploring patient-level data | Lopes | 2015 | EMIF | https://dx.doi.org/10.1155/2015/150435 | Review article, personalised medicine, clinical data, genomics, diagnosis | |
| The genetic landscape of Alzheimer's disease: clinical implications and perspectives | Van Cauwenberghe | 2015 | EMIF | https://dx.doi.org/10.1038/gim.2015.117 | Review article, Alzheimer's disease, genetics, ApoE, risk factor, diagnosis, GWAS | |
| Current developments in dementia risk prediction modelling: An updated systematic review | Tang | 2015 | EMIF | https://dx.doi.org/10.1371/journal.pone.0136181 | Systematic review, Alzheimer's disease, clinical, dementia, risk, patient | |
| Café Variome: General-Purpose Software for Making Genotype-Phenotype Data Discoverable in Restricted or Open Access Contexts | Lancaster | 2015 | EMIF | https://dx.doi.org/10.1002/humu.22841 | Informatics research paper, Cafe Variome, Matchmaker Exchange, data discovery, genotype-phenotype, data sharing, software | |
| Architecture to summarize patient-level data across borders and countries | Bastião Silva | 2015 | EMIF | https://dx.doi.org/10.3233/978-1-61499-564-7-687 | Informatics research paper, clinical data, healthcare, database, aggregation | |
| Blood metabolite markers of neocortical amyloid-β burden: Discovery and enrichment using candidate proteins | Voyle | 2015 | EMIF | https://dx.doi.org/10.1038/tp.2015.205 | Clinical research paper, Alzheimer's disease, metabolomics, proteomics, PET, ADNI | |
| C-terminal neurogranin is increased in cerebrospinal fluid but unchanged in plasma in Alzheimer's disease | De Vos | 2015 | EMIF | https://dx.doi.org/10.1016/j.jalz.2015.05.012 | Clinical research paper, Alzheimer's disease, Amyloid, CSF biomarker, ELISA, Mild cognitive impairment, Neurogranin, Plasma biomarker, Prognostic biomarker, Ratio amyloid β, tau, γ-secretase | |
| Prevalence of Amyloid PET Positivity in Dementia Syndromes: A Meta-Analysis | Ossenkoppele | 2015 | EMIF | https://jamanetwork.com/journals/jama/fullarticle/2293296 | Clinical research paper, meta-analysis, Alzheimer's disease, dementia, diagnostic criteria, ApoE, PET, Amyloid | |
| Alzheimer's disease cerebrospinal fluid biomarker in cognitively normal subjects | Toledo | 2015 | EMIF | https://dx.doi.org/10.1093/brain/awv199 | Clinical research paper, Alzheimer’s disease, biomarkers, CSF, cognitive ageing, dementia, imaging | |
| Diffusion kurtosis imaging: a biomarker for early diagnosis of Alzheimer’s disease? | Struyfs | 2015 | EMIF | https://dx.doi.org/10.3233/JAD-150253 | Clinical research paper, Alzheimer’s disease, biomarker, diffusion kurtosis imaging, diffusion tensor imaging, early diagnosis, MRI, MCI | |
| A 22-SNP Alzheimer risk score correlates with family history, onset age and CSF Aβ42 | Sleegers | 2014 | EMIF | https://dx.doi.org/10.1016/j.jalz.2015.02.013 | Clinical research paper, Alzheimer's disease, Genetic risk profile, Genotype-phenotype correlation, CSF Aβ1–42, Onset age, Family history | |
| Diagnostic value of MIBG cardiac scintigraphy for differential dementia diagnosis | Slaets | 2014 | EMIF | https://dx.doi.org/10.1002/gps.4229 | Clinical research paper, Alzheimer's disease, MIBG cardiac scintigraphy, dementia, dementia with Lewy bodies, sensitivity, specificity | |
| Temporal evolution of biomarkers and cognitive markers in the asymptomatic, MCI, and dementia stage of Alzheimer's disease | Bertens | 2014 | EMIF | https://dx.doi.org/10.1016/j.jalz.2014.05.1754 | Clinical research paper, Alzheimer's disease, dementia, MCI, biomarker, amyloid | |
| Circulating Proteomic Signatures of Chronological Age | Menni | 2014 | EMIF | https://dx.doi.org/10.1093/gerona/glu121 | Clinical research paper, aging, aptamers, blood biomarkers, early development, gene expression, proteomics | |
| Depression in mild cognitive impairment is associated with progression to Alzheimer's disease: a longitudinal study | Van der Mussele | 2014 | EMIF | https://dx.doi.org/10.3233/JAD-140405 | Clinical research paper, Alzheimer's disease, BPSD, cox proportional hazard, association, dementia, depression, depressive symptoms, MCI, predictor, prognostic value | |
| Plasma proteins predict conversion to dementia from prodromal disease | Hye | 2014 | EMIF | https://dx.doi.org/10.1016/j.jalz.2014.05.1749 | Clinical research paper, Alzheimer's disease, biomarker, MCI, pathology, plasma, prediction and MRI | |
| Egas: a collaborative and interactive document curation platform | Campos | 2014 | EMIF | https://dx.doi.org/10.1093/database/bau048 | Informatics research paper, platform, text mining, curation, database, biomedical | |
| Validation of the AD-CSF-index in autopsy-confirmed Alzheimer's disease patients and healthy controls | Struyfs | 2014 | EMIF | https://dx.doi.org/10.3233/JAD-131085 | Clinical research paper, Alzheimer's disease, biomarkers, cerebrospinal fluid, diagnostic accuracy, sensitivity, specificity | |
| Advanced glycation end products, dementia and diabetes | Lovestone | 2014 | EMIF | https://dx.doi.org/10.1073/pnas.1402277111 | Editorial, Alzheimer's disease, dementia, diabetes, sirtuin, ageing | |
| Medical imaging archiving: a comparison between several NoSQL solutions | LAB Silva | 2014 | EMIF | https://doi.org/10.1109/BHI.2014.6864305 | Informatics research paper, Platform, DICOM , Picture archiving and communication systems , File systems , Indexing | |
| Normalizing medical imaging archives for dose quality assurance and productivity auditing | LAB Silva | 2014 | EMIF | https://dx.doi.org/10.1007/s10278-015-9805-5 | Informatics research paper, Medical imaging, PACS, ALARA, DICOM, monitoring, quality of service, radiation | |
| Semantic search over DICOM repositories | LAB Silva | 2014 | EMIF | https://doi.org/10.1109/ICHI.2014.41 | Informatics research paper, Platform, Ontologies , DICOM , Standards , Semantics , Picture archiving and communication systems , Medical services | |
| Unresolved questions in Alzheimer's research - will biomarkers help? | Zetterberg | 2013 | EMIF | https://dx.doi.org/10.2217/bmm.13.120 | Opinion, Alzheimer's disease, amyloid, biomarkers, disease-modifying therapy, pathogenesis, tau | |
| Preclinical Alzheimer’s disease and its outcome: a longitudinal cohort study | Vos | 2013 | EMIF | http://dx.doi.org/10.1016/S1474-4422(13)70194-7 | Clinical research paper, Alzheimer's disease, CSF, progression, outcome, longitudinal cohort study | |
| Associations of Brain Pathology Cognitive and Physical Markers With Age in Cognitively Normal Individuals Aged 60–102 Years | Legdeur | 2019 | EMIF | https://doi.org/10.1093/gerona/glz180 | Clinical research paper, Alzheimer's disease, Biomarkers, Brain aging, Cognitive function, Human aging | |
| TASKA: A modular task management system to support health research studies | Almeida | 2019 | EMIF | https://doi.org/10.1186/s12911-019-0844-6 | Informatics research paper, Clinical studies, Task management, Workflow management | |
| White Matter Hyperintensities and Hippocampal Atrophy in Relation to Cognition: The 90+ Study | Legdeur | 2019 | EMIF | https://doi.org/10.1111/jgs.15990 | Clinical research study, cognitive functioning, hippocampal atrophy, oldest-old, white matter hyperintensities | |
| The association of vascular disorders with incident dementia in different age groups | Legdeur | 2019 | EMIF | https://doi.org/10.1186/s13195-019-0496-x | Clinical research paper, Dementia, Primary care, Vascular disorders, Vascular disease, Cardiovascular risk factors, Aging | |
| Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the EMIF-AD biomarker discovery cohort | Kim | 2019 | EMIF | https://doi.org/10.1016/j.jalz.2019.03.004 | Clinical research paper, Alzheimer's disease, Amyloid, Biomarkers, Brain volume measurements, CSF, Cognitive function measurements, Dementia, EMIF-AD, Metabolomics, Tau | |
| Inflammatory biomarkers in Alzheimer's disease plasma | Morgan | 2019 | EMIF | https://doi.org/10.1016/j.jalz.2019.03.007 | Clinical research paper, Alzheimer's disease, Biomarker, Plasma, Inflammation, Complement | |
| EMIF Catalogue: A collaborative platform for sharing and reusing biomedical data | Oliveira | 2019 | EMIF | https://doi.org/10.1016/j.ijmedinf.2019.02.006 | Informatics research paper, Biomedical data integration, Data catalogue, Data discovery, Data reuse, Data sharing, Research study | |
| Advantages and disadvantages of the use of the CSF Amyloid β (Aβ) 42/40 ratio in the diagnosis of Alzheimer’s Disease | Hansson | 2019 | EMIF | https://doi.org/10.1186/s13195-019-0485-0 | Review article, Alzheimer’s Disease, Amyloidβ Peptides, Aβ42/40 ratio, Biomarkers, Cerebrospinal Fluid | |
| Searching for novel cerebrospinal fluid biomarkers of tau pathology in frontotemporal dementia: an elusive quest | Foiani | 2019 | EMIF | https://doi.org/10.1136/jnnp-2018-319266 | Clinical research paper, frontotemporal dementia, CSF, tau | |
| Cerebrospinal fluid biomarkers of neurodegeneration, synaptic integrity, and astroglial activation across the clinical Alzheimer's disease spectrum | Bos | 2019 | EMIF | https://doi.org/10.1016/j.jalz.2019.01.004 | Clinical research paper, APOE, Alzheimer's disease, Amyloid-β, Cerebrospinal fluid, Cognition, Neurofilament light, Neurogranin, YKL-40 | |
| Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [18F]-Flutemetamol PET Scan Result | Westwood | 2018 | EMIF | https://doi.org/10.3389/fnagi.2018.00409 | Clinical research paper, Alzheimer’s disease, amyloid, tau, biomarkers, proteomics, plasma, blood, ficolin-2 | |
| Erlangen Score as a tool to predict progression from mild cognitive impairment to dementia in Alzheimer's disease | Baldeiras | 2018 | EMIF | https://doi.org/10.1186/s13195-018-0456-x | Clinical research paper, Alzheimer’s disease, Biomarker, Cerebrospinal fluid, MCI, progression | |
| Resilience to cognitive impairment in the oldest-old: design of the EMIF-AD 90+ study | Legdeur | 2018 | EMIF | https://doi.org/10.1186/s12877-018-0984-z | Clinical study protocol, Alzheimer’s disease, Amnestic mild cognitive impairment, Amyloid, Cognitive impairment, Dementia, Magnetoencephalography (MEG), Oldest-old, Positron emission tomography, Resilience | |
| Retinal and Cerebral Microvasculopathy: Relationships and Their Genetic Contributions | ven de Kreeke | 2018 | EMIF | https://doi.org/10.1167/iovs.18-25341 | Clinical research study, small vessel disease, retina, vascular, MRI, twins | |
| The European Medical Information Framework: A Novel Ecosystem for Sharing Healthcare Data Across Europe | Lovestone | 2019 | EMIF | https://doi.org/10.1002/lrh2.10214 | Review article, EMIF, EMIF‐AD, EMIF‐MET, catalogue, use case, Alzheimer's disease | |
| Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort | Westwood | 2020 | EMIF | https://pubmed.ncbi.nlm.nih.gov/31985466/ | Clinical research paper, Alzheimer’s disease, amyloid-β, biomarkers, plasma, proteomics. | |
| A Metabolite-Based Machine Learning Approach to Diagnose Alzheimer-type Dementia in Blood: Results From the EMIF-AD Biomarker Discovery Cohort | Stamate | 2019 | EMIF | https://doi.org/10.1016/j.trci.2019.11.001 | Clinical research paper, Alzheimer's disease, Biomarkers, EMIF-AD, Machine-Learning, Metabolomics. | |
| Associations of Brain Pathology, Cognitive and Physical Markers With Age in Cognitively Normal Individuals Aged 60-102 Years | Legdeur | 2019 | EMIF | https://pubmed.ncbi.nlm.nih.gov/31411322/ | Clinical research paper, biomarkers, brain aging, cognitive function, human aging. | |
| APOE ε4 Genotype-Dependent Cerebrospinal Fluid Proteomic Signatures in Alzheimer's Disease | Konijnenberg | 2020 | EMIF | https://doi.org/10.1186/s13195-020-00628-z | Clinical research paper, Alzheimer's disease, APOE genotype, Amyloid aggregation, CSF proteomics. | |
| Ocular Biomarkers for Cognitive Impairment in Nonagenarians; A Prospective Cross-Sectional Study | van der Kreeke | 2020 | EMIF | https://doi.org/10.1186/s12877-020-01556-1 | Clinical research paper, Cognitive impairment, Fundus photography, Nonagenarians;,Ocular biomarkers, Optical coherence tomography, Retina, Alzheimer's disease | |
| Biomarker-based Prognosis for People With Mild Cognitive Impairment (ABIDE): A Modelling Study | van Maurik | 2019 | EMIF | https://doi.org/10.1016/S1474-4422(19)30283-2 | Clinical research paper, MCI, biomarker, risk, dementia, Alzheimer's disease, CSF | |
| Longitudinal retinal layer changes in preclinical Alzheimer's disease | van de Kreeke | 2020 | EMIF | https://doi.org/10.1111/aos.14640 | OCT, ocular biomarkers, preclinical Alzheimer’s disease, retina, twins | |
| Methotrexate and relative risk of dementia amongst patients with rheumatoid arthritis: a multi-national multi-database casecontrol study | Newby | 2020 | EMIF | https://doi.org/10.1186/s13195-020-00606-5 | Dementia, Rheumatoid arthritis, Inflammation, Anti-inflammatory drugs, DMARDs, Methotrexate, Sulfasalazine, Case-control study, European Medical Information Framework, EMIF | |
| Pathophysiological subtypes of Alzheimer’s disease based on cerebrospinal fluid proteomics | Tijms | 2020 | EMIF | https://doi.org/10.1093/brain/awaa325 | Alzheimer’s disease, cerebrospinal fluid, proteomics, subtypes, amyloid, tau, proteins, cerebrospinal fluid, genetics | |
| Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset | Hong | 2020 | EMIF | https://doi.org/10.1038/s41398-020-01074-z | Genome-wide association study, Alzheimer's disease , CSF biomarkers , Multimodal Biomarker Discovery dataset, | |
| What determines cognitive functioning in the oldest-old? The EMIF-AD 90+ Stud | Legdeur | 2020 | EMIF | https://doi.org/10.1093/geronb/gbaa152 | Alzheimer’s disease, brain pathology biomarkers, cognitive aging, oldest-old, risk factors. | |
| Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer’s Disease Pathology | Shi | 2020 | EMIF | https://doi.org/10.3233/jad-200208 | ATN framework, Dickkopf-1, SomaScan, Wnt signaling, replication. | |
| Treatment pathway analysis of newly diagnosed dementia patients in four electronic health record databases in Europe | James | 2020 | EMIF | https://doi.org/10.1007/s00127-020-01872-2 | Alzheimer’s disease, Dementia, Epidemiology, Real-world data. | |
| Amyloid-β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old | Pelkmans | 2021 | EMIF | https://onlinelibrary.wiley.com/doi/full/10.1002/acn3.51273 | cortex., pathology, atrophy, cortical thickness, individuals, cognition, functioning, decline, EMIF-AD 90+ study, Aβ | |
| Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics | Tijms | 2020 | EMIF | https://doi.org/10.1093/brain/awaa325 | Alzheimer’s disease; cerebrospinal fluid; proteomics; subtypes. | |
| Brain-derived neurotrophic factor in cerebrospinal fluid and plasma is not a biomarker for Huntington’s disease | Ou | 2021 | EMIF | https://doi.org/10.1038/s41598-021-83000-x | plasma, csf, bdnf, mutation, huntington's disease, elisa, HD-CSF cohort, biomarker, cerebrospinal fluid, | |
| Onset of Preclinical Alzheimer Disease in Monozygotic Twins | Konijnenberg | 2021 | EMIF | https://doi.org/10.1002/ana.26048 | csf, amyloid, aggregation, markers, tau, pet, levels, analyses, correlations | |
| White matter microstructure disruption in early stage amyloid pathology | Colij | 2021 | EMIF | https://doi.org/10.1002/dad2.12124 | Amyloid beta (Aβ); diffusion tensor imaging (DTI); magnetic resonance imaging (MRI); positron emission tomography (PET); preclinical Alzheimer's disease (AD); white matter microstructure. | |
| Replication study of plasma proteins relating to Alzheimer's pathology | Shi | 2021 | EMIF | https://doi.org/10.1002/alz.12322 | ATN framework, Alzheimer's disease, biomarker, dementia, network analysis, plasma proteomics, replication | |
| Test-Retest Variability of Relative Tracer Delivery Rate as Measured by [11C]PiB | Heeman | 2021 | EMIF | https://doi.org/10.1007/s11307-021-01606-z | [11C]PiB, Alzheimer’s disease, Cerebral blood flow, Relative tracer delivery, Test-retest variability | |
| TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels | Hong | 2021 | EMIF | https://doi.org/10.1002/alz.12330 | Alzheimer's disease; biomarker; cerebrospinal fluid; chitinase-3-like protein 1; genome-wide association study; neurofilament light; neurogranin. | |
| Cerebrospinal fluid α synuclein concentrations in patients with positive AD biomarkers and extrapyramidal symptoms | Winkel | 2021 | EMIF | https://doi.org/10.1007/s00702-021-02351-x | α Synuclein, Alzheimer’s disease, Cerebrospinal fluid, Extrapyramidal symptoms, Biomarker | |
| Plasma amyloid-β oligomerization assay as a pre-screening test for amyloid status | Mofard | 2021 | EMIF | https://doi.org/10.1186/s13195-021-00873-w | Blood-based biomarker, Plasma Aβ oligomer, Amyloid status, Multimer detection system, Long-term storage | |
| Sex-Specific Metabolic Pathways Were Associated with Alzheimer’s Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort | Xu | 2021 | EMIF | https://doi.org/10.3390/biomedicines9111610 | Alzheimer’s disease; blood; metabolic pathway; metabolomics; sex; tryptophan betaine; vanillylmandelate. | |
| Characteristics of subjective cognitive decline associated with amyloid positivity | Janssen | 2021 | EMIF | https://doi.org/10.1002/alz.12512 | Alzheimer's disease; amyloid; cerebrospinal fluid; positron emission tomography; subjective cognitive decline. | |
| Magnetoencephalography Brain Signatures Relate to Cognition and Cognitive Reserve in the Oldest-Old: The EMIF-AD 90 + Study | Griffa | 2021 | EMIF | https://doi.org/10.3389/fnagi.2021.746373 | cognition; cognitive reserve; functional connectivity; magnetoencephalography; oldest-old. | |
| Genetically identical twins show comparable tau PET load and spatial distribution | Coomans | 2022 | EMIF | https://doi.org/10.1093/brain/awac004 | Alzheimer’s disease, tau, PET, twins, genetics, alzheimer's disease, tau, proteins, monozygotic twins, genetics, pathology | |
| Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer’s disease CSF profile of neuronal injury and inflammation | Neumann | 2022 | EMIF | https://doi.org/10.1038/s41380-022-01437-6 | Diagnostic markers, Genetics, Rare variants, IFFO1, DTNB, NLRC3, SLC22A10, Alzheimer's disease, CSF, neuronal injury, inflammation | |
| CSF proteomic signature predicts progression to Alzheimer's disease dementia | Vromen | 2022 | EMIF | https://doi.org/10.1002/trc2.12240 | Alzheimer's disease, cerebrospinal fluid, mild cognitive impairment, prognosis, proteomics | |
| Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer’s disease | Visser | 2022 | EMIF | https://doi.org/10.1186/s13024-022-00521-3 | Alzheimer's disease, Molecular mechanisms, Biomarker discovery, Heterogeneity, Neuronal plasticity, Cerebrospinal fluid proteomics | |
| Genome-Wide Association Study of Alzheimer’s Disease Brain Imaging Biomarkers and Neuropsychological Phenotypes in the European Medical Information Framework for Alzheimer’s Disease | Homann | 2022 | EMIF | https://doi.org/10.3389/fnagi.2022.840651 | genome-wide association study, GWAS, X chromosome, Alzheimer’s disease (AD), MRI, imaging, cognitive function | |
| Optimized sample preparation and data analysis for TMT proteomic analysis of cerebrospinal fluid applied to the identification of Alzheimer's disease biomarkers | Weiner | 2022 | EMIF | https://doi.org/10.1186/s12014-022-09354-0 | Alzheimer’s disease; Biomarkers; Cerebrospinal fluid; Labeling efficiency; Mass spectrometry; Normalization; Sample preparation; Tandem mass tag. | |
| Effects of age, amyloid, sex, and APOE ε4 on the CSF proteome in normal cognition | Wesenhagen | 2022 | EMIF | https://doi.org/10.1002/dad2.12286 | age, amyloid, sex, APOE ε4, CSF, proteome, cognition | |
| Predicting AT(N) pathologies in Alzheimer’s disease from blood-based proteomic data using neural networks | Zhang | 20222 | EMIF | https://doi.org/10.3389/fnagi.2022.1040001 | Alzheimer’s disease, plasma proteomics, amyloid β, tau, neurodegeneration, machine learning, artificial neural networks | |
| Amyloid-β and APOE genotype predict memory decline in cognitively unimpaired older individuals independently of Alzheimer's disease polygenic risk score | Tomassen | 2022 | EMIF | https://doi.org/10.1186/s12883-022-02925-6 | APOE genotype; Amyloid-β; Cognitive decline; Longitudinal design; Neuropsychology; Polygenic risk score; Preclinical Alzheimer’s disease. | |
| NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data | Jieqing | 2023 | EMIF | https://doi.org/10.1007/s12021-022-09616-0 | NiftyPAD, PET, Pharmacokinetic analysis, Reference input-based modelling, Python package |
| Title | Description | Type | Project | |
|---|---|---|---|---|
| EMIF-AD multimodal biomarker discovery study (MBD) | The EMIF-AD MBD study aimed to accelerate the discovery of novel diagnostic and prognostic biomarkers for AD and to unravel the underlying pathophysiological mechanisms using existing data and samples. The EMIF-AD MBD includes harmonized and pooled clinical data from 11 cohort studies across Europe and samples (cerebrospinal fluid, plasma, DNA) and MRI scans which were centrally analyzed using different omics techniques (proteomics, metabolomics, genomics). In total, material from 1221 participants was included (n=492 control, n=527 MCI, n=202 AD dementia). Data requests can be submitted via the EMIF-AD Catalogue. For more information, please visit: |
cohort-clinical-emif-4 | EMIF | |
| EMIF-AD 90+ study | The EMIF-AD 90+ study aimed to identify factors associated with resilience to cognitive impairment in the oldest-old. The study was conducted at the Amsterdam University Medical Center and at the University of Manchester. At baseline, neuropsychological and clinical data (vascular comorbidities, mood, sleep, physical performance, genetic factors) were collected from 129 participants (n=84 with normal cognition and n=38 with cognitive deficits). Regarding imaging measures: baseline MRI (n=92), Amyloid-PET (n=103) and MEG (n=92) have been collected. In addition, skin biopsies (n=99) and ultrasound of the carotid artery (n=102) are also collected. Currently (Oct 2019), the first annual follow-up measurements have completed in n=129 as of November 2019, with plans for a second annual follow-up 2020. Data requests can be submitted via the EMIF-AD catalogue. For more information, please visit: |
cohort-clinical-emif-5 | EMIF | |
| EMIF-AD PreclinAD study | The EMIF-AD PreclinAD study aimed to indentify new risk factors and diagnostic markers for both amyloid pathology and cognitive decline in cognitively normal subjects with or without amyloid pathology. To investigate this, monozygotic twin pairs were included such that genetic and environmental pathways can be identified. For the baseline measurement n=204 cognitively healthy elderly monozygotic twins aged 60 years and older were included from the Manchester and Newcastle Age and Cognitive Performance Research Cohort and the Netherlands Twin Register. At baseline the following measurements were done: neuropsychological examination (n=204), blood sampling (n=204), CSF collection (n=127), ultrasound of the carotid artery (n=102), magnetoencephalography (n=190) and collection of ophthalmological markers (n=198). In n=192 (94%) the following follow-up measures were done after two years: containing a neuropsychological examination (n=191), blood collection (n=192) and CSF sampling (n=103). A second follow-up will be conducted in 2020. Data requests can be submitted via the EMIF-AD catalogue. For more information, please visit: |
cohort-clinical-emif-6 | EMIF | |
| EMIF Catalogue | The EMIF Catalogue is designed to allow researchers to find databases which fulfil their particular research study requirements in a quick and easy way. This portal is a dynamic and flexible system which can be easily customised for different purposes and research interests. The catalogue compromises several neurodegenerative research projects such as: EMIF-Alzheimer’s Disease (EMIF-AD), European Prevention of Alzheimer's Disease (EPAD) and Multiple Sclerosis Data Alliance (MSDA). EMIF-AD itself contains clinical, neuroimaging and -omics datasets from EMIF-AD MBD, 90+ and PreClinAD studies. All databases are accessible from the link below. |
dataset-clinical-emif-10 | EMIF | |
| Plasma, DNA and CSF from participants of the EMIF-AD Multimodal biomarker discovery study (MBD) | The EMIF-AD MBD study aimed to accelerate the discovery of novel diagnostic and prognostic biomarker for AD and to unravel the underlying pathophysiological mechanisms using existing data and samples. In total, 1221 participants were recruited to the MBD study(n=492 control, n=527 MCI, n=202 AD dementia). Plasma from 1189 participants, DNA from 929 participants and CSF from 775 participants was obtained. For more information please visit: |
biological-samples-clinical-emif-3 | EMIF | |
| Blood samples, CSF and skin biopsies from participants of the EMIF-AD 90+ study | The EMIF-AD 90+ study aimed to identify factors associated with resilience to cognitive impairment in the oldest-old, including 84 participants with normal cognition and 38 with cognitive deficits. The first annual follow-up measurements were completed in n=129 as of November 2019, with plans for a second annual follow-up 2020. Biological samples collected are as follows: 104 blood samples, 99 skin biopsies and 36 samples of CSF. For more information, please visit: |
biological-samples-clinical-emif-4 | EMIF | |
| Blood and CSF from participants of the EMIF-AD PreclinAD study | The EMIF-AD PreclinAD study aimed to indentify new risk factors and diagnostic markers for both amyloid pathology and cognitive decline in cognitively normal subjects with or without amyloid pathology. To investigate this monozygotic twin pairs were included such that genetic and environmental pathways can be identified. At baseline the following samples were obtained: blood (n=204), CSF (n=127). In n=192 (94%) the following follow-up measures were done after two years: blood collection (n=192) and CSF sampling (n=103). A second follow-up will be conducted in 2020. For more information please visit: |
biological-samples-clinical-emif-5 | EMIF | |
| EMIF-AD data Catalogue | The EMIF Platform is an IT platform that allows access to multiple, diverse data sources. The EMIF Catalogue, part of the EMIF platform, allows users to explore population-based and cohort-derived (predominately AD) data sources who have consented to provide such information for the purposes of bona fide researchers wanting to explore potential data partners for studies. The EMIF Platform makes this data available for browsing and allows exploitation in multiple ways by the end user. The EMIF Platform has leveraged data on more then 62 million European adults and children by means of federation of healthcare databases and cohorts from 7 different countries (DK, IT, NL, UK, ES, EE), designed to be representative of the different types of existing data sources (population-based registries, hospital-based databases, cohorts, national registries, biobanks, etc.). For more information, please visit: |
platform-clinical-emif-1 | EMIF | |
| Tools for federated EHR analysis | The EMIF-Platform has leveraged data on more then 62 Million European adults and children by means of federation of healthcare databases and cohorts from 7 different countries (DK, IT, NL, UK, ES, EE), designed to be representative of the different types of existing data sources (population-based registries, hospital-based databases, cohorts, national registries, biobanks, etc.). The data is represented in the EMIF Data Catalogue. For more information, please visit: |
platform-clinical-emif-2 | EMIF | |
| Procedures for federated data management | IMI have produced a framework to address challenges raised by local governance rules and potential emerging commercial and academic conflicts across the different EMIF contributing EHR databases. Such a framework will involve all database holders/organisations as participants of the EMIF horizontal layer and has the sole aim to identify governance issues of conflicts of interest that require adaptation of technical functionalities. This in turn will help build a framework focussed on enabling health care providers as well as researchers to re-use patient data in such a way it is acceptable to all partners. For more information, please visit: |
tools-clinical-emif-2 | EMIF | |
| Risk factors for amyloid pathology, predictors for cognitive decline: clinical biology of AD | Trial design in pre-dementia AD 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. For more information, please visit: |
tools-clinical-emif-3 | EMIF |
| Website: http://www.emif.eu/ |
Back to list