EPIC4ND-European Prospective Investigation into Cancer and Nutrition follow-up for neurodegenerative diseases.
EPIC4ND-European Prospective Investigation into Cancer and Nutrition follow-up for neurodegenerative diseases.
Where did the research take place?
The study site has not been established. Author addresses may differ from where the research occurred.
Münster, DE · Author affiliation
Translational Epidemiology Unit, Institute of Epidemiology and Social Medicine, University of Münster, Domagkstr. 3, Münster, Germany. christina.lill@uni-muenster.de.Location evidence
London, GB · Author affiliation
Ageing and Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK. christina.lill@uni-muenster.de.Location evidence
Oxford, GB · Author affiliation
Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.Location evidence
Lyon, FR · Author affiliation
International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, Lyon, France.Location evidence
Murcia, ES · Author affiliation
Department of Epidemiology, Murcia Regional Health Council-IMIB, Murcia, Spain.Location evidence
Madrid, ES · Author affiliation
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.Location evidence
Villejuif, FR · Author affiliation
Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, CESP, Villejuif, France.Location evidence
Utrecht, NL · Author affiliation
Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.Location evidence
Cambridge, GB · Author affiliation
Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK.Location evidence
Lübeck, DE · Author affiliation
Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.Location evidence
ES · Author affiliation · country only
Epidemiology and Public Health Area, Biodonostia Health Research Institute, San Sebastián, Spain.Location evidence
Pamplona, ES · Author affiliation
Instituto de Salud Pública y Laboral de Navarra, Pamplona, Spain.Location evidence
Centro, ES · Author affiliation
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.Location evidence
Granada, ES · Author affiliation
Escuela Andaluza de Salud Pública (EASP), Granada, Spain.Location evidence
Umeå, SE · Author affiliation
Department of Clinical Sciences, Neurosciences, Umeå University, Umeå, Sweden.Location evidence
Heidelberg, DE · Author affiliation
Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.Location evidence
Mannheim, DE · Author affiliation
1st Medical Clinic, University Hospital Mannheim, Mannheim, Germany.Location evidence
Medellín, CO · Author affiliation
9 Enero Research Group On Demography and Health, National Faculty of Public Health, University of Antioquia, Medellin, Colombia.Location evidence
DE · Author affiliation · country only
Department of Neurology, Saarland University Clinic, Saarland, Germany.Location evidence
Copenhagen, DK · Author affiliation
Danish Cancer Institute, Danish Cancer Society, Copenhagen, Denmark.Location evidence
Milan, IT · Author affiliation
Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.Location evidence
Florence, IT · Author affiliation
Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence, Florence, Italy.Location evidence
Gothenburg, SE · Author affiliation
Department of Psychiatry and Neurochemistry, University of Gothenburg, Molndal, Sweden.Location evidence
Mölndal, SE · Author affiliation
Department of Psychiatry and Neurochemistry, University of Gothenburg, Molndal, Sweden.Location evidence
Hong Kong, HK · Author affiliation
Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China.Location evidence
US · Author affiliation · country only
Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, University of Wisconsin-Madison, Madison, WI, USA.Location evidence
Kiel, DE · Author affiliation
Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.Location evidence
Novara, IT · Author affiliation
Department of Health Sciences, University of Eastern Piedmont, Novara, Italy.Location evidence
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Original abstract
The 'European Prospective Investigation into Cancer and Nutrition' cohort (EPIC) is a prospective study including ~ 520,000 participants recruited across Europe (1991-2000) with in-depth baseline data on nutritional, lifestyle, medical, and anthropometric variables, and baseline blood samples. Here we introduce EPIC4ND, a case-cohort study within EPIC designed to identify biomarkers predicting a future onset of dementia, Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). EPIC4ND comprises 6415 initially non-diseased participants (aged 35-80 years, mean age at baseline: 54 ± 9, 64% women) including 1899 incident cases with up to 30 years of follow-up and data on at least one omics domain available from pre-disease blood samples. EPIC4ND includes 4604 subcohort members (4441 non-cases and 163 incident cases) and 1811 additional incident cases ascertained from the broader EPIC cohort. Among the incident cases, there are 1190 dementia cases (818 AD), 610 PD cases, and 199 ALS cases. Additionally, 72 prevalent PD cases and 118 incident Parkinsonism cases are available for comparison. Molecular data generated encompass proteomics, genome-wide DNA methylation, and SNP genotyping with 4127 EPIC4ND participants (including 1635 incident cases) having data on all three domains. Smaller studies include data on metals, metabolites, and environmental chemicals, while ongoing efforts focus on ultrasensitive targeted biomarker measurements and small RNA sequencing. Genome-wide association studies and analyses of epidemiological risk factors validate the dataset by confirming many known risk factors. Leveraging these extensive pre-disease multi-layered omics data offers a unique opportunity to identify biomarker signatures predicting neurodegenerative diseases and to explore their interplay with epidemiological risk factors.