Evidence map›Paper›PMID 39003492›Full record

ArticleCardiovascular diabetology2024

DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes.

Jacopo Sabbatinelli, Angelica Giuliani, Katarzyna Malgorzata Kwiatkowska, Giulia Matacchione, Alessia Belloni, Deborah Ramini, Francesco Prattichizzo, Valeria Pellegrini, Francesco Piacenza, Elena Tortato and 6 more

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Review
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  7. Extrachromosomal Circular DNA and Transposable Elements in Type 2 Diabetes.International journal of molecular sciences · 2025
    Review
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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

16 authors.

Jacopo SabbatinelliDepartment of Clinical and Molecular Sciences (DISCLIMO), Università Politecnica delle Marche, Ancona, Italy.
Angelica GiulianiIstituti Clinici Scientifici Maugeri IRCCS, Cardiac Rehabilitation Unit of Bari Institute, Bari, Italy. angelica.giuliani@staff.univpm.it.
Katarzyna Malgorzata KwiatkowskaDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Giulia MatacchioneClinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.
Alessia BelloniDepartment of Clinical and Molecular Sciences (DISCLIMO), Università Politecnica delle Marche, Ancona, Italy.
Deborah RaminiClinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.
Francesco PrattichizzoIRCCS Multimedica, Milan, Italy.
Valeria PellegriniIRCCS Multimedica, Milan, Italy.
Francesco PiacenzaAdvanced Technology Center for Aging Research, IRCCS INRCA, Ancona, Italy.
Elena TortatoDepartment of Metabolic Diseases and Diabetology, IRCCS INRCA, Ancona, Italy.
Anna Rita BonfigliScientific Direction, IRCCS INRCA, Ancona, Italy.
Davide GentiliniDepartment of Brain and Behavioral Sciences, Università di Pavia, Pavia, Italy.
Antonio Domenico ProcopioDepartment of Clinical and Molecular Sciences (DISCLIMO), Università Politecnica delle Marche, Ancona, Italy.
Paolo GaragnaniDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy. paolo.garagnani2@unibo.it.
Fabiola Olivieri *Department of Clinical and Molecular Sciences (DISCLIMO), Università Politecnica delle Marche, Ancona, Italy.
Giuseppe Bronte *Department of Clinical and Molecular Sciences (DISCLIMO), Università Politecnica delle Marche, Ancona, Italy.

Funding

European Commission Age-It: "Ageing Well in an Ageing Society"Ministero della Salute Ricerca corrente
6 · The paper itself

Abstract

backgroundIndividuals with type 2 diabetes (T2D) face an increased mortality risk, not fully captured by canonical risk factors. Biological age estimation through DNA methylation (DNAm), i.e. the epigenetic clocks, is emerging as a possible tool to improve risk stratification for multiple outcomes. However, whether these tools predict mortality independently of canonical risk factors in subjects with T2D is unknown.

methodsAmong a cohort of 568 T2D patients followed for 16.8 years, we selected a subgroup of 50 subjects, 27 survived and 23 deceased at present, passing the quality check and balanced for all risk factors after propensity score matching. We analyzed DNAm from peripheral blood leukocytes using the Infinium Human MethylationEPIC BeadChip (Illumina) to evaluate biological aging through previously validated epigenetic clocks and assess the DNAm-estimated levels of selected inflammatory proteins and blood cell counts. We tested the associations of these estimates with mortality using two-stage residual-outcome regression analysis, creating a reference model on data from the group of survived patients.

resultsDeceased subjects had higher median epigenetic age expressed with DNAmPhenoAge algorithm (57.49 [54.72; 60.58] years. vs. 53.40 [49.73; 56.75] years; p = 0.012), and accelerated DunedinPoAm pace of aging (1.05 [1.02; 1.11] vs. 1.02 [0.98; 1.06]; p = 0.012). DNAm PhenoAge (HR 1.16, 95% CI 1.05-1.28; p = 0.004) and DunedinPoAm (HR 3.65, 95% CI 1.43-9.35; p = 0.007) showed an association with mortality independently of canonical risk factors. The epigenetic predictors of 3 chronic inflammation-related proteins, i.e. CXCL10, CXCL11 and enRAGE, C-reactive protein methylation risk score and DNAm-based estimates of exhausted CD8 + T cell counts were higher in deceased subjects when compared to survived.

conclusionsThese findings suggest that biological aging, as estimated through existing epigenetic tools, is associated with mortality risk in individuals with T2D, independently of common risk factors and that increased DNAm-surrogates of inflammatory protein levels characterize deceased T2D patients. Replication in larger cohorts is needed to assess the potential of this approach to refine mortality risk in T2D.

Indexed as

Diabetes Mellitus, Type 2DNA MethylationEpigenesis, GeneticAgedAge FactorsAgingFemaleGenetic MarkersHumansInflammation MediatorsMaleMiddle AgedPredictive Value of TestsPrognosisRisk AssessmentRisk FactorsGenetic MarkersInflammation MediatorsDNA methylationDunedinPoAmEpigenetic clocksPhenoAgeType 2 diabetes

Identifiers

PMID39003492
PMCPMC11245869

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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.