TY - JOUR
T1 - Non-coding rnas in the brain-heart axis
T2 - The case of parkinson’s disease
AU - Acharya, Shubhra
AU - Salgado-Somoza, Antonio
AU - Stefanizzi, Francesca Maria
AU - Lumley, Andrew I.
AU - Zhang, Lu
AU - Glaab, Enrico
AU - May, Patrick
AU - Devaux, Yvan
N1 - Funding Information:
This work is supported by COST (European Cooperation in Science and Technology) Action EU-CardioRNA CA17129, the National Research Fund of Luxembourg (grants # C14/BM/8225223 and C17/BM/11613033), the Ministry of Higher Education and Research of Luxembourg, and the Heart Foundation?Daniel Wagner.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/9/2
Y1 - 2020/9/2
N2 - Parkinson’s disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.
AB - Parkinson’s disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.
KW - Artificial intelligence
KW - Biomarkers
KW - Brain
KW - Data science
KW - Heart
KW - Non-coding RNAs
KW - Parkinson’s disease
KW - Systems biomedicine
UR - http://www.scopus.com/inward/record.url?scp=85090195995&partnerID=8YFLogxK
U2 - 10.3390/ijms21186513
DO - 10.3390/ijms21186513
M3 - Review article
C2 - 32899928
AN - SCOPUS:85090195995
SN - 1661-6596
VL - 21
SP - 1
EP - 27
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 18
M1 - 6513
ER -