Abstract
| Original language | English |
|---|---|
| Journal | Interface Focus |
| Volume | 3 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2013 |
| MoE publication type | A1 Journal article-refereed |
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Keywords
- alzheimer's disease
- clinical decision support system
- early diagnosis
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The PredictAD project : Development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease. / Antila, Kare; Lötjönen, Jyrki; Thurfjell, L; Laine, J.; Massimini, M.; Rueckert, D.; Zubarev, R.A.; Oresic, Matej; van Gils, Mark; Mattila, Jussi; Simonsen, A.H.; Waldemar, G.; Soininen, H.
In: Interface Focus, Vol. 3, No. 2, 2013.Research output: Contribution to journal › Article › Scientific › peer-review
TY - JOUR
T1 - The PredictAD project
T2 - Development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease
AU - Antila, Kare
AU - Lötjönen, Jyrki
AU - Thurfjell, L
AU - Laine, J.
AU - Massimini, M.
AU - Rueckert, D.
AU - Zubarev, R.A.
AU - Oresic, Matej
AU - van Gils, Mark
AU - Mattila, Jussi
AU - Simonsen, A.H.
AU - Waldemar, G.
AU - Soininen, H.
PY - 2013
Y1 - 2013
N2 - Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.
AB - Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.
KW - alzheimer's disease
KW - clinical decision support system
KW - early diagnosis
U2 - 10.1098/rsfs.2012.0072
DO - 10.1098/rsfs.2012.0072
M3 - Article
VL - 3
JO - Interface Focus
JF - Interface Focus
SN - 2042-8898
IS - 2
ER -