Evidence map›Paper›PMID 38187520›Full record

ArticlebioRxiv : the preprint server for biology2023

Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion.

Hunter L Porter, Victor A Ansere, Ram Babu Undi, Walker Hoolehan, Cory B Giles, Chase A Brown, David Stanford, Mark M Huycke, Willard M Freeman, Jonathan D Wren

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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

5 · Who and what money

Authors and funding

10 authors.

Hunter L PorterOklahoma Medical Research Foundation.
Victor A AnsereOklahoma Medical Research Foundation.
Ram Babu UndiUniversity of Oklahoma Health Sciences Center.
Walker HoolehanOklahoma Medical Research Foundation.
Cory B GilesOklahoma Medical Research Foundation.
Chase A BrownOklahoma Medical Research Foundation.
David StanfordOklahoma Medical Research Foundation.
Mark M HuyckeUniversity of Oklahoma Health Sciences Center.
Willard M FreemanOklahoma Medical Research Foundation.
Jonathan D WrenOklahoma Medical Research Foundation.

Funding

Targeted DNA Methylation and Mitochondrial Heteroplasmy CoreP30AG050911 · NIA · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI Matthew John Hart · 2015 to 2026
$13.9M
Pilot Projects ProgramP30GM149376 · NIGMS · OKLAHOMA MEDICAL RESEARCH FOUNDATION · PI Linda F Thompson · 2023 to 2026
$7.4M
Sex divergence and cell specificity of age-related hippocampal DNA modificationsR01AG059430 · NIA · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI FREEMAN, WILLARD M · 2019 to 2023
$2.7M
Microbiome-triggered reprogramming and mutation of colon epithelial cells leading to tumor stem-like cellsR01CA230641 · NCI · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI HUYCKE, MARK M · 2019 to 2023
$2.3M
BLRD VA IK6 BX006033NCI NIH HHS R01 CA230641NIA NIH HHS P30 AG050911NIA NIH HHS R01 AG059430NIGMS NIH HHS P30 GM149376
6 · The paper itself

Abstract

DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.

Identifiers

PMID38187520
PMCPMC10769286

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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.