Evidence map›Paper›PMID 32743556›Full record

ReviewNeuroscience insights2020

DNA Methylation Clocks and Their Predictive Capacity for Aging Phenotypes and Healthspan.

Tessa Bergsma, Ekaterina Rogaeva

Registry-linked trialAbstract readReview
In one paragraph

Review in Neuroscience insights, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06529744 (Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling), which is not on this map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing 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.

NCT06529744 recruitingnot on this mapstarted 2023, after this paper: background citation

Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling

Typeobservational_patient_registrySponsorUniversity Health Network, TorontoRan2023 to 2027Enrolled500ConditionsDementia, Alzheimer Disease, Dementia With Lewy Bodies, Vascular Dementia
3 · Its place in the literature

Who cites it

74 citing papers in PubMed.

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  5. Extracellular vesicles and epigenetic aging clocks in tissue aging: an exosome-focused conceptual framework with a focus on skin.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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14 more citing papers are in PubMed but not listed here.

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

2 authors.

Tessa BergsmaTanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada.
Ekaterina RogaevaTanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-2852-0329

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of age predictors based on DNA methylation (DNAm) profile is rising due to their potential in predicting healthspan and application in age-related illnesses, such as neurodegenerative diseases. The cumulative assessment of DNAm levels at age-related CpGs (DNAm clock) may reflect biological aging. Such DNAm clocks have been developed using various training models and could mirror different aspects of disease/aging mechanisms. Hence, evaluating several DNAm clocks together may be the most effective strategy in capturing the complexity of the aging process. However, various confounders may influence the outcome of these age predictors, including genetic and environmental factors, as well as technical differences in the selected DNAm arrays. These factors should be taken into consideration when interpreting DNAm clock predictions. In the current review, we discuss 15 reported DNAm clocks with consideration for their utility in investigating neurodegenerative diseases and suggest research directions towards developing a more optimal measure for biological aging.

Indexed as

age-related diseasebiological agechronological ageDNA methylationneurodegenerative disorders

Identifiers

PMID32743556
PMCPMC7376380

What OpenQuestion holds

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Registered trials

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.