Systems medicine and the integration of bioinformatic tools for the diagnosis of Alzheimer's disease

Matej Orešič (Corresponding Author), Jyrki Lötjönen, Hilkka Soininen

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

Abstract

Because of the changes in demographic structure, the prevalence of Alzheimer's disease is expected to rise dramatically over the next decades. The progression of this degenerative and terminal disease is gradual, with the subclinical stage of illness believed to span several decades. Despite this, no therapy to prevent or cure Alzheimer's disease is currently available. Early disease detection is still important for delaying the onset of the disease with pharmacological treatment and/or lifestyle changes, assessing the efficacy of potential therapeutic agents, or monitoring disease progression more closely using medical imaging. Sensitive cerebrospinal-fluid-derived marker candidates exist, but given the invasiveness of sample collection their use in routine diagnostics may be limited. The pathogenesis of Alzheimer's disease is complex and poorly understood. There is thus a strong case for integrating information across multiple physiological levels, from molecular profiling (metabolomics, lipidomics, proteomics and transcriptomics) and brain imaging to cognitive assessments. To facilitate the integration of heterogeneous data, such as molecular and image data, sophisticated statistical approaches are needed to segment the image data and study their dependencies on molecular changes in the same individuals. Molecular profiling, combined with biophysical modeling of molecular assemblies associated with the disease, offer an opportunity to link the molecular pathway changes with cell- and tissue-level physiology and structure. Given that data acquired at different levels can carry complementary information about early Alzheimer's disease pathology, it is expected that their integration will improve early detection as well as our understanding of the disease.
Original languageEnglish
Article number83
Number of pages6
JournalGenome Medicine
Volume2
DOIs
Publication statusPublished - 2010
MoE publication typeA1 Journal article-refereed

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Systems Integration
Systems Analysis
Computational Biology
Alzheimer Disease
Metabolomics
Diagnostic Imaging
Neuroimaging
Proteomics
Cerebrospinal Fluid
Disease Progression
Life Style
Early Diagnosis
Demography
Pharmacology
Pathology
Therapeutics

Cite this

Orešič, Matej ; Lötjönen, Jyrki ; Soininen, Hilkka. / Systems medicine and the integration of bioinformatic tools for the diagnosis of Alzheimer's disease. In: Genome Medicine. 2010 ; Vol. 2.
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abstract = "Because of the changes in demographic structure, the prevalence of Alzheimer's disease is expected to rise dramatically over the next decades. The progression of this degenerative and terminal disease is gradual, with the subclinical stage of illness believed to span several decades. Despite this, no therapy to prevent or cure Alzheimer's disease is currently available. Early disease detection is still important for delaying the onset of the disease with pharmacological treatment and/or lifestyle changes, assessing the efficacy of potential therapeutic agents, or monitoring disease progression more closely using medical imaging. Sensitive cerebrospinal-fluid-derived marker candidates exist, but given the invasiveness of sample collection their use in routine diagnostics may be limited. The pathogenesis of Alzheimer's disease is complex and poorly understood. There is thus a strong case for integrating information across multiple physiological levels, from molecular profiling (metabolomics, lipidomics, proteomics and transcriptomics) and brain imaging to cognitive assessments. To facilitate the integration of heterogeneous data, such as molecular and image data, sophisticated statistical approaches are needed to segment the image data and study their dependencies on molecular changes in the same individuals. Molecular profiling, combined with biophysical modeling of molecular assemblies associated with the disease, offer an opportunity to link the molecular pathway changes with cell- and tissue-level physiology and structure. Given that data acquired at different levels can carry complementary information about early Alzheimer's disease pathology, it is expected that their integration will improve early detection as well as our understanding of the disease.",
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Systems medicine and the integration of bioinformatic tools for the diagnosis of Alzheimer's disease. / Orešič, Matej (Corresponding Author); Lötjönen, Jyrki; Soininen, Hilkka.

In: Genome Medicine, Vol. 2, 83, 2010.

Research output: Contribution to journalArticleScientificpeer-review

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