Evidence map›Paper›PMID 36304118›Full record

ArticleiScience2022

A set of common buccal CpGs that predict epigenetic age and associate with lifespan-regulating genes.

Adiv A Johnson, Nicole S Torosin, Maxim N Shokhirev, Trinna L Cuellar

Open access · goldAbstract read
In one paragraph

Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. A Sex-Specific Minimal CpG-Based Model for Biological Aging UsingInternational journal of molecular sciences · 2025
    Article
  4. Quantification of Epigenetic Aging in Public Health.Annual review of public health · 2025
    Review
  5. Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease.International journal of molecular sciences · 2024
    Review
  6. Article
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

4 authors at 1 institution in 1 country.

Adiv A JohnsonLongevity Sciences, Inc. (dba Tally Health), Greenwich, CT, USA.
Nicole S TorosinLongevity Sciences, Inc. (dba Tally Health), Greenwich, CT, USA.
Maxim N ShokhirevLongevity Sciences, Inc. (dba Tally Health), Greenwich, CT, USA.
Trinna L CuellarLongevity Sciences, Inc. (dba Tally Health), Greenwich, CT, USA.
Longevity Biotech (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epigenetic aging clocks are computational models that use DNA methylation sites to predict age. Since cheek swabs are non-invasive and painless, collecting DNA from buccal tissue is highly desirable. Here, we review 11 existing clocks that have been applied to buccal tissue. Two of these were exclusively trained on adults and, while moderately accurate, have not been used to capture health-relevant differences in epigenetic age. Using 130 common CpGs utilized by two or more existing buccal clocks, we generate a proof-of-concept predictor in an adult methylomic dataset. In addition to accurately estimating age (r = 0.95 and mean absolute error = 3.88 years), this clock predicted that Down syndrome subjects were significantly older relative to controls. A literature and database review of CpG-associated genes identified numerous genes (e.g.,

Indexed as

Artificial intelligenceBioinformaticsChronobiologyEpigenetics

Identifiers

PMID36304118
PMCPMC9593711
OpenAlexW4303444765

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.