Evidence map›Paper›PMID 31037649›Full record

ArticleMolecular neurobiology2019

Panoramic Visualization of Circulating MicroRNAs Across Neurodegenerative Diseases in Humans.

Samuel Brennan, Matthew Keon, Bing Liu, Zheng Su, Nitin K Saksena

Open access · hybridAbstract read
In one paragraph

Article in Molecular neurobiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Profiling Secreted miRNA Biomarkers of Chemical-Induced Neurodegeneration in Human iPSC-Derived Neurons.Toxicological sciences : an official journal of the Society of Toxicology · 2022
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. MicroRNAs Related to Cognitive Impairment After Hearing Loss.Clinical and experimental otorhinolaryngology · 2021
    Article
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

5 authors at 1 institution in 1 country.

Samuel BrennanNeurodegenerative Disease section, Iggy Get Out, 19a Boundary Street, Darlinghurst NSW 2010, Sydney, Australia.
Matthew KeonNeurodegenerative Disease section, Iggy Get Out, 19a Boundary Street, Darlinghurst NSW 2010, Sydney, Australia.
Bing LiuNeurodegenerative Disease section, Iggy Get Out, 19a Boundary Street, Darlinghurst NSW 2010, Sydney, Australia.
Zheng SuNeurodegenerative Disease section, Iggy Get Out, 19a Boundary Street, Darlinghurst NSW 2010, Sydney, Australia.
Nitin K SaksenaNeurodegenerative Disease section, Iggy Get Out, 19a Boundary Street, Darlinghurst NSW 2010, Sydney, Australia. nitin@iggygetout.com.
Institut für Geologie und Umwelt (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and dementia pose one of the greatest health challenges this century. Although these NDs have been looked at as single entities, the underlying molecular mechanisms have never been collectively visualized to date. With the advent of high-throughput genomic and proteomic technologies, we now have the opportunity to visualize these diseases in a whole new perspective, which will provide a clear understanding of the primary and secondary events vital in achieving the final resolution of these diseases guiding us to new treatment strategies to possibly treat these diseases together. We created a knowledge base of all microRNAs known to be differentially expressed in various body fluids of ND patients. We then used several bioinformatic methods to understand the functional intersections and differences between AD, PD, ALS, and MS. These results provide a unique panoramic view of possible functional intersections between AD, PD, MS, and ALS at the level of microRNA and their cognate genes and pathways, along with the entities that unify and separate them. While the microRNA signatures were apparent for each ND, the unique observation in our study was that hsa-miR-30b-5p overlapped between all four NDS, and has significant functional roles described across NDs. Furthermore, our results also show the evidence of functional convergence of miRNAs which was associated with the regulation of their cognate genes represented in pathways that included fatty acid synthesis and metabolism, ECM receptor interactions, prion diseases, and several signaling pathways critical to neuron differentiation and survival, underpinning their relevance in NDs. Envisioning this group of NDs together has allowed us to propose new ways of utilizing circulating miRNAs as biomarkers  and in visualizing diverse NDs more holistically . The critical molecular insights gained through the discovery of ND-associated miRNAs, overlapping miRNAs, and the functional convergence of microRNAs on vital pathways strongly implicated in neurodegenerative processes can prove immensely valuable in the identifying new generation of biomarkers, along with the development of miRNAs into therapeutics.

Indexed as

Circulating MicroRNADown-RegulationGene Expression ProfilingGene OntologyGenome, HumanHumansNeurodegenerative DiseasesPhylogenyCirculating MicroRNABiomarkerMiRNANeurodegenerative diseaseNeuropathology

Identifiers

PMID31037649
PMCPMC6815273
OpenAlexW2942919108

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.