Evidence map›Paper›PMID 42643998›Full record

ReviewFrontiers in aging neuroscience2026

Proteostasis breakdown and aggregate diversity in aging and neurodegenerative disease.

Zohaib Nisar Khan

Abstract readReview
In one paragraph

Review in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Zohaib Nisar KhanDepartment of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein aggregation and proteostasis decline are central features of aging and neurodegenerative disease, arising from progressive impairment of protein quality-control systems and transitions into aggregation-prone states. During aging, diverse proteins, including metabolic and proteostasis-related factors, gradually accumulate in aggregated forms as proteostasis capacity declines. Although these aggregates often remain compatible with cellular function, increasing aggregate burden progressively challenges proteostasis resilience. Neurodegenerative diseases are characterized by the emergence and amplification of highly toxic, structurally ordered protein assemblies, including amyloid-β (Aβ) and tau, which exist along a continuum with broader age-associated proteome instability rather than as entirely distinct phenomena. Oxidative and metabolic imbalances promote non-enzymatic post-translational modifications (PTMs), including cysteine oxidation, S-nitrosylation, and carbonylation, which alter protein structure, impair degradation pathways, and facilitate misfolding and aggregation. Here, we compare oxidative PTM-driven aggregates observed during aging with disease-associated protein assemblies, highlighting both shared biophysical mechanisms and distinct pathological outcomes. We propose a threshold model in which the cumulative burden of oxidative PTMs, protein misfolding, and impaired clearance progressively erodes proteostasis capacity, increasing susceptibility to the emergence of selective, self-amplifying aggregates. By integrating intracellular quality-control systems with extracellular clearance pathways, including glymphatic and meningeal lymphatic networks, this framework provides a mechanistic perspective on how aggregate diversity evolves toward disease-associated pathology and suggests therapeutic strategies that combine aggregate-specific targeting with restoration of global proteostasis and clearance capacity.

Indexed as

agingamyloid-β and tauglymphatic systemneurodegenerative diseaseprotein aggregationproteostasis

Identifiers

PMID42643998
PMCPMC13504540

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.