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Personalised Medicine

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Attention for Chapter 4: The Emerging Role of Proteomics in Precision Medicine: Applications in Neurodegenerative Diseases and Neurotrauma
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Chapter title
The Emerging Role of Proteomics in Precision Medicine: Applications in Neurodegenerative Diseases and Neurotrauma
Chapter number 4
Book title
Personalised Medicine
Published in
Advances in experimental medicine and biology, January 2017
DOI 10.1007/978-3-319-60733-7_4
Pubmed ID
Book ISBNs
978-3-31-960731-3, 978-3-31-960733-7
Authors

Rana Alaaeddine, Mira Fayad, Eliana Nehme, Hisham F. Bahmad, Firas Kobeissy

Abstract

Inter-individual variability in response to pharmacotherapy has provoked a higher demand to personalize medical decisions. As the field of pharmacogenomics has served to translate personalized medicine from concept to practice, the contribution of the "omics" disciplines to the era of precision medicine seems to be vital in improving therapeutic outcomes. Although we have observed significant advances in the field of genomics towards personalized medicine , the field of proteomics-with all its capabilities- is still in its infancy towards the area of personalized precision medicine. Neurodegenerative diseases and neurotrauma are among the areas where the implementation of neuroproteomics approaches has enabled neuroscientists to broaden their understanding of neural disease mechanisms and characteristics. It has been shown that the influence of epigenetics, genetics and environmental factors were among the recognized factors contributing to the diverse presentation of a single disease as well as its treatment establishing the factor-disease interaction. Thus, management of these variable single disease presentation/outcome necessitated the need for factoring the influence of epigenetics, genetics, epigenetics, and other factors on disease progression to create a custom treatment plan unique to each individual. In fact, neuroproteomics with its high ability to decipher protein alterations along with their post translational modifications (PTMs) can be an ideal tool for personalized medicine goals including: discovery of molecular mechanisms underlying disease pathobiology, development of novel diagnostics, enhancement of pharmacological neurotherapeutic approaches and finally, providing a "proteome identity" for patients with certain disorders and diseases. So far, neuroproteomics approaches have excelled in the areas of biomarker discovery arena where several diagnostic, prognostic and injury markers have been identified with a direct impact on the neurodegenerative diseases and neurotrauma. However, other applications in proteomics such as "individual" proteome sequencing with its signature PTMs, have not been fully investigated as compared to the achievements in the genomics discipline This infers that proteomics research work has promising potential, yet to be discovered, in the precision medicine and comprises a major component of the personalized medicine infrastructure as it allows individual characterization of disease at the protein level. To conclude, the field of proteomics-based personalized medicine is still in its infancy compared to genomics field due to several technical and instrumentation-based obstacles; however, we anticipate to have this initiative leading in the coming future. This chapter will discuss briefly how neuroproteomics can impact personalized medicine in the fields of neurodegenerative disorders particularly in Alzheimer's disease and brain injury .

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 25%
Student > Doctoral Student 5 16%
Student > Master 4 13%
Researcher 4 13%
Student > Bachelor 4 13%
Other 5 16%
Unknown 2 6%
Readers by discipline Count As %
Neuroscience 6 19%
Medicine and Dentistry 5 16%
Biochemistry, Genetics and Molecular Biology 3 9%
Computer Science 2 6%
Chemistry 2 6%
Other 8 25%
Unknown 6 19%