Evidence map›Paper›PMID 33192262›Full record

ReviewFrontiers in neuroscience2020

From Multi-Omics Approaches to Precision Medicine in Amyotrophic Lateral Sclerosis.

Giovanna Morello, Salvatore Salomone, Velia D'Agata, Francesca Luisa Conforti, Sebastiano Cavallaro

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in neuroscience, 2020. 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
3.1field-weighted citation impact, top 6% 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, 54 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

5 authors at 4 institutions in 1 country.

Giovanna MorelloInstitute for Research and Biomedical Innovation (IRIB), Italian National Research Council (CNR), Catania, Italy.
Salvatore SalomoneSection of Pharmacology, Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy.
Velia D'AgataHuman Anatomy and Histology, University of Catania, Catania, Italy.
Francesca Luisa ConfortiDepartment of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy.
Sebastiano CavallaroInstitute for Research and Biomedical Innovation (IRIB), Italian National Research Council (CNR), Catania, Italy.
University of Catania · ITInstitute for Biomedical Research and Innovation · ITNational Research Council · ITUniversity of Calabria · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyotrophic lateral sclerosis (ALS) is a devastating and fatal neurodegenerative disorder, caused by the degeneration of upper and lower motor neurons for which there is no truly effective cure. The lack of successful treatments can be well explained by the complex and heterogeneous nature of ALS, with patients displaying widely distinct clinical features and progression patterns, and distinct molecular mechanisms underlying the phenotypic heterogeneity. Thus, stratifying ALS patients into consistent and clinically relevant subgroups can be of great value for the development of new precision diagnostics and targeted therapeutics for ALS patients. In the last years, the use and integration of high-throughput "omics" approaches have dramatically changed our thinking about ALS, improving our understanding of the complex molecular architecture of ALS, distinguishing distinct patient subtypes and providing a rational foundation for the discovery of biomarkers and new individualized treatments. In this review, we discuss the most significant contributions of omics technologies in unraveling the biological heterogeneity of ALS, highlighting how these approaches are revealing diagnostic, prognostic and therapeutic targets for future personalized interventions.

Indexed as

ALS-FTDamyotrophic lateral sclerosismolecular taxonomymulti-omicspersonalized medicinesystems biology

Identifiers

PMID33192262
PMCPMC7661549
OpenAlexW3096501554

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.