Evidence map›Paper›PMID 34062930›Full record

ReviewInternational journal of molecular sciences2021

Omics Data and Their Integrative Analysis to Support Stratified Medicine in Neurodegenerative Diseases.

Valentina La Cognata, Giovanna Morello, Sebastiano Cavallaro

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Valentina La CognataInstitute for Biomedical Research and Innovation (IRIB), Italian National Research Council (CNR), 95126 Catania, Italy.
Giovanna MorelloInstitute for Biomedical Research and Innovation (IRIB), Italian National Research Council (CNR), 95126 Catania, Italy.
Sebastiano CavallaroInstitute for Biomedical Research and Innovation (IRIB), Italian National Research Council (CNR), 95126 Catania, Italy.ORCID 0000-0001-7590-1792

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca CTN01_00177_817708
6 · The paper itself

Abstract

Molecular and clinical heterogeneity is increasingly recognized as a common characteristic of neurodegenerative diseases (NDs), such as Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. This heterogeneity makes difficult the development of early diagnosis and effective treatment approaches, as well as the design and testing of new drugs. As such, the stratification of patients into meaningful disease subgroups, with clinical and biological relevance, may improve disease management and the development of effective treatments. To this end, omics technologies-such as genomics, transcriptomics, proteomics and metabolomics-are contributing to offer a more comprehensive view of molecular pathways underlying the development of NDs, helping to differentiate subtypes of patients based on their specific molecular signatures. In this article, we discuss how omics technologies and their integration have provided new insights into the molecular heterogeneity underlying the most prevalent NDs, aiding to define early diagnosis and progression markers as well as therapeutic targets that can translate into stratified treatment approaches, bringing us closer to the goal of personalized medicine in neurology.

Indexed as

GenomicsMetabolomicsProteomicsAlzheimer DiseaseAmyotrophic Lateral SclerosisBiomarkersComputational BiologyHumansNeurodegenerative DiseasesParkinson DiseasePrecision MedicineBiomarkersmulti-omicsneurodegenerative diseasesstratified medicine

Identifiers

PMID34062930
PMCPMC8125201

What OpenQuestion holds

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Registered trials

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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.