Evidence map›Paper›PMID 32899928›Full record

ReviewInternational journal of molecular sciences2020

Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease.

Shubhra Acharya, Antonio Salgado-Somoza, Francesca Maria Stefanizzi, Andrew I Lumley, Lu Zhang, Enrico Glaab, Patrick May, Yvan Devaux

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 34 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Shubhra AcharyaCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.ORCID 0000-0003-2904-6566
Antonio Salgado-SomozaCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.
Francesca Maria StefanizziCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.ORCID 0000-0001-5029-9491
Andrew I LumleyCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.ORCID 0000-0001-5935-3327
Lu ZhangCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.
Enrico GlaabLuxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg.
Patrick MayLuxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg.ORCID 0000-0001-8698-3770
Yvan DevauxCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.ORCID 0000-0002-5321-8543
Luxembourg Institute of Health · LUUniversity of Luxembourg · LU

Funding

European Cooperation in Science and Technology Action EU-CardioRNA CA17129Fonds National de la Recherche Luxembourg C14/BM/8225223Fonds National de la Recherche Luxembourg C17/BM/11613033Heart Foundation - Daniel Wagner naMinistère de l'Enseignement Supérieur et de la Recherche, Luxembourg na
6 · The paper itself

Abstract

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.

Indexed as

AnimalsBrainCell CommunicationHeartHumansMicroRNAsMyocardiumParkinson DiseaseRNA, CircularRNA, Long NoncodingRNA, UntranslatedSignal TransductionMicroRNAsRNA, CircularRNA, Long NoncodingRNA, Untranslatedartificial intelligencebiomarkersbraindata scienceheartnon-coding RNAsParkinson’s diseasesystems biomedicine

Identifiers

PMID32899928
PMCPMC7555192
OpenAlexW3083527819

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.