TY - JOUR
T1 - Revealing clusters of connected pathways through multisource data integration in huntington's disease and spastic ataxia
AU - Kakouri, Andrea C.
AU - Christodoulou, Christiana C.
AU - Zachariou, Margarita
AU - Oulas, Anastasis
AU - Minadakis, George
AU - Demetriou, Christiana A.
AU - Votsi, Christina
AU - Zamba-Papanicolaou, Eleni
AU - Christodoulou, Kyproula
AU - Spyrou, George M.
N1 - Funding Information:
Manuscript received January 19, 2018; revised May 17, 2018 and July 2, 2018; accepted August 5, 2018. Date of publication August 29, 2018; date of current version January 2, 2019. The work of A. C. Kakouri, C. C. Christodoulou, M. Zachariou, A. Oulas, G. Minadakis, and G. M. Spyrou are supported by the European Commission Research Executive Agency (REA) under Grant BIORISE 669026, under the Spreading Excellence, Widening Participation, Science with and for Society Framework. This work was supported in part by H2020-WIDESPREAD-04-2017-Teaming Phase 1, under Grant 763781, Integrated Precision Medicine Technologies. (Andrea C. Kakouri and Christiana C. Christo-doulou are co-first authors.) (Corresponding author: George M. Spyrou.) A. C. Kakouri is with the Neurogenetics Department and Bioinformatics Group, the Cyprus Institute of Neurology and Genetics, Nicosia 1683, Cyprus (e-mail:,[email protected]).
Publisher Copyright:
© 2013 IEEE.
PY - 2019/1
Y1 - 2019/1
N2 - The advancement of scientific and medical research over the past years has generated a wealth of experimental data from multiple technologies, including genomics, transcriptomics, proteomics, and other forms of -omics data, which are available for a number of diseases. The integration of such multisource data is a key component toward the success of precision medicine. In this paper, we are investigating a multisource data integration method developed by our group, regarding its ability to drive to clusters of connected pathways under two different approaches: first, a disease-centric approach, where we integrate data around a disease, and second, a gene-centric approach, where we integrate data around a gene. We have used as a paradigm for the first approach Huntington's disease (HD), a disease with a plethora of available data, whereas for the second approach the GBA2, a gene that is related to spastic ataxia (SA), a phenotype with sparse availability of data. Our paper shows that valuable information at the level of disease-related pathway clusters can be obtained for both HD and SA. New pathways that classical pathway analysis methods were unable to reveal, emerged as necessary 'connectors' to build connected pathway stories formed as pathway clusters. The capability to integrate multisource molecular data, concluding to something more than the sum of the existing information, empowers precision and personalized medicine approaches.
AB - The advancement of scientific and medical research over the past years has generated a wealth of experimental data from multiple technologies, including genomics, transcriptomics, proteomics, and other forms of -omics data, which are available for a number of diseases. The integration of such multisource data is a key component toward the success of precision medicine. In this paper, we are investigating a multisource data integration method developed by our group, regarding its ability to drive to clusters of connected pathways under two different approaches: first, a disease-centric approach, where we integrate data around a disease, and second, a gene-centric approach, where we integrate data around a gene. We have used as a paradigm for the first approach Huntington's disease (HD), a disease with a plethora of available data, whereas for the second approach the GBA2, a gene that is related to spastic ataxia (SA), a phenotype with sparse availability of data. Our paper shows that valuable information at the level of disease-related pathway clusters can be obtained for both HD and SA. New pathways that classical pathway analysis methods were unable to reveal, emerged as necessary 'connectors' to build connected pathway stories formed as pathway clusters. The capability to integrate multisource molecular data, concluding to something more than the sum of the existing information, empowers precision and personalized medicine approaches.
KW - GBA-2 related diseases
KW - Huntington's disease (HD)
KW - Network integration
KW - precision medicine
KW - spastic ataxia (SA)
KW - systems bioinformatics
UR - http://www.scopus.com/inward/record.url?scp=85052663358&partnerID=8YFLogxK
U2 - 10.1109/JBHI.2018.2865569
DO - 10.1109/JBHI.2018.2865569
M3 - Article
C2 - 30176611
AN - SCOPUS:85052663358
SN - 2168-2194
VL - 23
SP - 26
EP - 37
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 1
M1 - 8451872
ER -