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Project Topic
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Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS) are progressive
neurodegenerative disorders (NDs) showing growing prevalence in industrialized, aging populations. Despite all
three disorders having a genetic basis, it is becoming increasingly evident that variants of the DNA sequence alone
do not fully explain the phenotypic picture of these NDs. This means that non-genetic mechanisms, such as
environmental/lifestyle factors and other factors related to transcriptional regulation of gene expression likely make
substantial contributions to disease development. Specifically, this relates to epigenetic markers in blood, e.g., DNA
methylation, which likely reflect the combined effects of disease-specific pathophysiological processes,
exposure to environmental and lifestyle factors, and genetics. Thus, the investigation of their potential to
serve as molecular biomarkers for AD, PD, and ALS is highly promising. However, while epigenetics research
has gained momentum in recent years owing to the advent of high-throughput technologies, thus far, DNA
methylation biomarker studies in AD, PD or ALS are typically limited to testing prevalent disease cases, which does
not allow inferences on pathophysiological processes or risk prediction due to potential reverse causation. The only
remedy is to conduct large prospective studies where biosamples of unaffected individuals are collected at baseline
and these individuals are then followed longitudinally over many years. This is difficult to achieve and, as a result,
there is a severe lack of sufficiently sized and appropriately characterized datasets with available pre
disease biomaterials for systematic biomarker identification.
In this project, we propose to make use of one of the largest prospective cohorts ever assembled worldwide
(i.e., the European Prospective Investigation into Cancer and Nutrition, EPIC) for biomarker identification in
pre-disease blood samples of future AD, PD and ALS patients. In EPIC, blood samples were collected at baseline
in 521,000 healthy individuals in a highly standardized fashion, then aliquoted and stored in liquid nitrogen. During
the more than 20 years of follow-up, a substantial fraction of the participants has been diagnosed with
neurodegenerative diseases, including AD, PD, and ALS. The main aim of our project (“EPIC4ND“) will be to
assess whether DNA methylome profiles derived from blood samples prior to disease onset in EPIC
participants (n=6,900) can predict a later conversion to AD, PD and ALS. To this end, we will generate DNA
methylation profiles in pre-disease biosamples of EPIC individuals who later developed AD (n=900), PD (n=900) or
ALS (n=300) and will compare them to equivalent profiles of matched controls (n=4,800) randomly drawn from
within the EPIC cohort. These data will be analyzed together with other “-omics” data generated in separate
projects from the same individuals (i.e. genome-wide SNP genotyping, transcriptomics, and proteomics) as
well as variables from the extensive EPIC database, including questionnaire-based pre-disease
exposure/lifestyle and medical data. In a subset of individuals (n~100 AD patients), we will assess longitudinal
changes of methylation markers possibly reflecting pathological processes. In summary, EPIC4ND is in the unique
position to use pre-disease biosamples to build novel multivariate and multi-omics disease prediction models
allowing for an earlier detection, therapy and ultimately prevention of these three devastating diseases.
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