Evidence map›Paper›PMID 28058805›Full record

ArticleAging cell2017

Biomarker signatures of aging.

Paola Sebastiani, Bharat Thyagarajan, Fangui Sun, Nicole Schupf, Anne B Newman, Monty Montano, Thomas T Perls

Open access · goldAbstract read
In one paragraph

Article in Aging cell, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
127citing papers in PubMed, 1 pooled it
13.2field-weighted citation impact, top 1% 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

127 citing papers in PubMed, 1 synthesis or guideline pooled it, 234 citations in OpenAlex.

  1. Pooled it
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  4. Change in the Rate of Biological Aging in Response to Caloric Restriction: CALERIE Biobank Analysis.The journals of gerontology. Series A, Biological sciences and medical sciences · 2017
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  19. Epigenetic age acceleration in idiopathic pulmonary fibrosis revealed by DNA methylation clocks.American journal of physiology. Lung cellular and molecular physiology · 2025
    Article
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67 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

7 authors at 5 institutions in 1 country.

Paola SebastianiDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02118, USA.
Bharat ThyagarajanDepartment of Laboratory Medicine and Pathology, University of Minnesota Medical School, MMC 609 Mayo, 420 Delaware, Minneapolis, MN, 55455, USA.
Fangui SunDepartment of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02118, USA.
Nicole SchupfDepartment of Epidemiology, Sergievsky Center, Columbia University Mailman School of Public Health, 630 West 168th Street, New York, NY, 10032, USA.
Anne B NewmanDepartment of Epidemiology, University of Pittsburgh, A527 Crabtree Hall, 130 DeSoto Street, Pittsburgh, PA, 15261, USA.
Monty MontanoDepartment of Medicine, Harvard Medical School, Brigham and Women's Hospital, 221 Longwood Avenue, Boston, MA, 02115, USA.
Thomas T PerlsDepartment of Medicine, Geriatrics Section, Boston University School of Medicine and Boston Medical Center, Robinson 2400, 88 E Newton St, Boston, MA, 02118, USA.
Boston University · USColumbia University · USHarvard University · USUniversity of Minnesota Medical Center · USUniversity of Pittsburgh · US

Funding

Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI JODI A LAPIDUS · 2004 to 2026
$102.6M
THE FRAMINGHAM HEART STUDYN01HC25195 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI RAMACHANDRAN, VASAN S · 2007 to 2014
$83.8M
Long Life Family Study: Data Management and Coordinating CenterU01AG023746 · NIA · WASHINGTON UNIVERSITY · PI PROVINCE, MICHAEL A. · 2004 to 2018
$29.2M
VARIABILITY, STABILITY & SMOOTHNESS OF WALKINGP30AG024827 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JENNIFER S BRACH · 2004 to 2026
$28.6M
UTMB OAIC Research Education Component (REC)P30AG024832 · NIA · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI JAMES S. GOODWIN, MD, MELISSA M. MORROW · 2005 to 2026
$26.7M
The Long Life Family StudyU01AG023755 · NIA · BOSTON MEDICAL CENTER · PI PERLS, THOMAS T · 2004 to 2018
$13.2M
Plasma beta-amyloid in long lived families: genetics and risk of ADU01AG023749 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI COSENTINO, STEPHANIE ANN, LEE, JOSEPH HYUNGWOO · 2004 to 2018
$13.0M
Multicenter Study on Exceptional Survival in Families: The Long Life Family StudyU01AG023744 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI NEWMAN, ANNE B., ZMUDA, JOSEPH M. · 2004 to 2018
$12.0M
Long Life Family Study: Duke Univ./Univ. of Southern Denmark Field CenterU01AG023712 · NIA · DUKE UNIVERSITY · PI CHRISTENSEN, KAARE · 2004 to 2018
$10.4M
Biomarkers for Muscle Function and Aging in Chronic HIV InfectionR01AI108541 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI MONTANO, MONTY A · 2014 to 2018
$3.7M
Biomarker Profiles of Sickle Cell DiseaseR21HL128871 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI SEBASTIANI, PAOLA · 2016 to 2017
$247k
NHLBI NIH HHS N01HC25195NHLBI NIH HHS R21 HL128871NIAID NIH HHS R01 AI108541NIA NIH HHS P30 AG024827NIA NIH HHS P30 AG024832NIA NIH HHS U01 AG023712NIA NIH HHS U01 AG023744NIA NIH HHS U01 AG023746NIA NIH HHS U01 AG023749NIA NIH HHS U01 AG023755NIA NIH HHS U19 AG023122
6 · The paper itself

Abstract

Because people age differently, age is not a sufficient marker of susceptibility to disabilities, morbidities, and mortality. We measured nineteen blood biomarkers that include constituents of standard hematological measures, lipid biomarkers, and markers of inflammation and frailty in 4704 participants of the Long Life Family Study (LLFS), age range 30-110 years, and used an agglomerative algorithm to group LLFS participants into clusters thus yielding 26 different biomarker signatures. To test whether these signatures were associated with differences in biological aging, we correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type 2 diabetes, and mortality using longitudinal data collected in the LLFS. Signature 2 was associated with significantly lower mortality, morbidity, and better physical function relative to the most common biomarker signature in LLFS, while nine other signatures were associated with less successful aging, characterized by higher risks for frailty, morbidity, and mortality. The predictive values of seven signatures were replicated in an independent data set from the Framingham Heart Study with comparable significant effects, and an additional three signatures showed consistent effects. This analysis shows that various biomarker signatures exist, and their significant associations with physical function, morbidity, and mortality suggest that these patterns represent differences in biological aging. The signatures show that dysregulation of a single biomarker can change with patterns of other biomarkers, and age-related changes of individual biomarkers alone do not necessarily indicate disease or functional decline.

Indexed as

AdultAgedAged, 80 and overAge DistributionAgingBiomarkersCalibrationFamilyFemaleHumansLongevityMaleMiddle AgedMortalityReproducibility of ResultsBiomarkersbiological agingbiomarkershealthy agingmorbidity and mortality

Identifiers

PMID28058805
PMCPMC5334528
OpenAlexW2568684118

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.