Evidence map›Paper›PMID 38891059›Full record

ReviewCells2024

Chronological and Biological Aging in Amyotrophic Lateral Sclerosis and the Potential of Senolytic Therapies.

Anna Roshani Dashtmian, Fereshteh B Darvishi, William David Arnold

Abstract readReview
In one paragraph

Review in Cells, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Kinase-substrate prediction using an autoregressive model.Computational and structural biotechnology journal · 2025
    Article
  8. Review
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.

Anna Roshani DashtmianNextGen Precision Health, University of Missouri, Columbia, MO 65211, USA.
Fereshteh B DarvishiNextGen Precision Health, University of Missouri, Columbia, MO 65211, USA.
William David ArnoldNextGen Precision Health, University of Missouri, Columbia, MO 65211, USA.ORCID 0000-0001-9889-7036

Funding

national institute of health 1R01AG067758, R01AG078129, and R01AG067758-02S2
6 · The paper itself

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a group of sporadic and genetic neurodegenerative disorders that result in losses of upper and lower motor neurons. Treatment of ALS is limited, and survival is 2-5 years after disease onset. While ALS can occur in younger individuals, the risk significantly increases with advancing age. Notably, both sporadic and genetic forms of ALS share pathophysiological features overlapping hallmarks of aging including genome instability/DNA damage, mitochondrial dysfunction, inflammation, proteostasis, and cellular senescence. This review explores chronological and biological aging in the context of ALS onset and progression. Age-related muscle weakness and motor unit loss mirror aspects of ALS pathology and coincide with peak ALS incidence, suggesting a potential link between aging and disease development. Hallmarks of biological aging, including DNA damage, mitochondrial dysfunction, and cellular senescence, are implicated in both aging and ALS, offering insights into shared mechanisms underlying disease pathogenesis. Furthermore, senescence-associated secretory phenotype and senolytic treatments emerge as promising avenues for ALS intervention, with the potential to mitigate neuroinflammation and modify disease progression.

Indexed as

AgingAmyotrophic Lateral SclerosisAnimalsCellular SenescenceDNA DamageHumansMitochondriaSenotherapeuticsSenotherapeuticsagingmotor neuronsarcopeniasenescence

Identifiers

PMID38891059
PMCPMC11171952

What OpenQuestion holds

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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.