The PredictAD project

Development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease

Kare Antila, Jyrki Lötjönen, L Thurfjell, J. Laine, M. Massimini, D. Rueckert, R.A. Zubarev, Matej Oresic, Mark van Gils, Jussi Mattila, A.H. Simonsen, G. Waldemar, H. Soininen

Research output: Contribution to journalArticleScientificpeer-review

19 Citations (Scopus)

Abstract

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.
Original languageEnglish
JournalInterface Focus
Volume3
Issue number2
DOIs
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

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Biomarkers
Early Diagnosis
Alzheimer Disease
Software
Brain
Health Priorities
Population Dynamics
Neurology
Statistical Models
Research
Developed Countries
Nervous System
Dementia
Health
Delivery of Health Care
Drug Therapy
Pharmaceutical Preparations
Population

Keywords

  • alzheimer's disease
  • clinical decision support system
  • early diagnosis

Cite this

Antila, K., Lötjönen, J., Thurfjell, L., Laine, J., Massimini, M., Rueckert, D., ... Soininen, H. (2013). The PredictAD project: Development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease. Interface Focus, 3(2). https://doi.org/10.1098/rsfs.2012.0072
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. / The PredictAD project : Development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease. In: Interface Focus. 2013 ; Vol. 3, No. 2.
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Antila, K, Lötjönen, J, Thurfjell, L, Laine, J, Massimini, M, Rueckert, D, Zubarev, RA, Oresic, M, van Gils, M, Mattila, J, Simonsen, AH, Waldemar, G & Soininen, H 2013, 'The PredictAD project: Development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease', Interface Focus, vol. 3, no. 2. https://doi.org/10.1098/rsfs.2012.0072

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 journalArticleScientificpeer-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 -