Evidence map›Paper›PMID 33235214›Full record

ArticleNature communications2020

Common diseases alter the physiological age-related blood microRNA profile.

Tobias Fehlmann, Benoit Lehallier, Nicholas Schaum, Oliver Hahn, Mustafa Kahraman, Yongping Li, Nadja Grammes, Lars Geffers, Christina Backes, Rudi Balling and 18 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
3.6field-weighted citation impact, top 5% 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

61 citing papers in PubMed, 110 citations in OpenAlex.

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  20. MicroRNA Gets a Mighty Award.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review

1 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

28 authors at 10 institutions in 4 countries.

Tobias FehlmannChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany.ORCID 0000-0003-1967-2918
Benoit LehallierDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA.ORCID 0000-0001-7452-3785
Nicholas SchaumDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA.
Oliver HahnDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA.
Mustafa KahramanChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany.ORCID 0000-0002-5536-048X
Yongping LiChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany.
Nadja GrammesChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany.
Lars GeffersLuxembourg Center for Systems Biomedicine, 4362, Esch-sur-Alzette, Luxemburg.ORCID 0000-0001-6800-4305
Christina BackesChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany.ORCID 0000-0001-9330-9290
Rudi BallingLuxembourg Center for Systems Biomedicine, 4362, Esch-sur-Alzette, Luxemburg.ORCID 0000-0003-2902-5650
Fabian KernChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany.
Rejko KrügerLuxembourg Center for Systems Biomedicine, 4362, Esch-sur-Alzette, Luxemburg.
Frank LammertInternal Medicine, Saarland University, 66421, Homburg, Germany.ORCID 0000-0003-4450-7201
Nicole LudwigHuman Genetics, Saarland University, 66421, Homburg, Germany.
Benjamin MederInternal Medicine, University Hospital Heidelberg, 69120, Heidelberg, Germany.
Bastian FrommDepartment of Molecular Biosciences, Stockholm University, 11418, Stockholm, Sweden.ORCID 0000-0003-0352-3037
Walter MaetzlerDepartment of Neurology, Christian-Albrechts-Universität zu Kiel, 24105, Kiel, Germany.
Daniela BergDepartment of Neurology, Christian-Albrechts-Universität zu Kiel, 24105, Kiel, Germany.
Kathrin BrockmannTREND study center Tübingen, Tübingen, Germany.
Christian DeuschleTREND study center Tübingen, Tübingen, Germany.
Anna-Katharina von ThalerTREND study center Tübingen, Tübingen, Germany.ORCID 0000-0001-8161-5813
Gerhard W EschweilerGeriatric Center and the Department of Psychiatry and Psychotherapy, University Hospital Tübingen, 72076, Tübingen, Germany.
Sofiya MilmanThe Institute for Aging Research, Albert Einstein College of Medicine, New York, NY, 10461, USA.
Nir BarziliaiThe Institute for Aging Research, Albert Einstein College of Medicine, New York, NY, 10461, USA.
Matthias ReichertInternal Medicine, Saarland University, 66421, Homburg, Germany.ORCID 0000-0002-8192-0575
Tony Wyss-CorayDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA.ORCID 0000-0001-5893-0831
Eckart MeeseHuman Genetics, Saarland University, 66421, Homburg, Germany.
Andreas KellerChair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany. andreas.keller@ccb.uni-saarland.de.ORCID 0000-0002-5361-0895
Saarland University · DEStanford University · USBernstein Center for Computational Neuroscience Tübingen · DEAlbert Einstein College of Medicine · USCentre Hospitalier de Luxembourg · LUChristian-Albrechts-Universität zu Kiel · DEArbed (Luxembourg) · LUHeidelberg University · DEStockholm University · SEUniversity Children's Hospital Tübingen · DE

Funding

Translational Research CoreP30DK020541 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI STREAMSON C CHUA · 2015 to 2026
$27.7M
Einstein's Nathan Shock Center of Excellence in Basic Biology of AgingP30AG038072 · NIA · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI HUFFMAN, DEREK MAJOR · 2010 to 2024
$10.8M
NIA NIH HHS P30 AG038072NIDDK NIH HHS P30 DK020541
6 · The paper itself

Abstract

Aging is a key risk factor for chronic diseases of the elderly. MicroRNAs regulate post-transcriptional gene silencing through base-pair binding on their target mRNAs. We identified nonlinear changes in age-related microRNAs by analyzing whole blood from 1334 healthy individuals. We observed a larger influence of the age as compared to the sex and provide evidence for a shift to the 5' mature form of miRNAs in healthy aging. The addition of 3059 diseased patients uncovered pan-disease and disease-specific alterations in aging profiles. Disease biomarker sets for all diseases were different between young and old patients. Computational deconvolution of whole-blood miRNAs into blood cell types suggests that cell intrinsic gene expression changes may impart greater significance than cell abundance changes to the whole blood miRNA profile. Altogether, these data provide a foundation for understanding the relationship between healthy aging and disease, and for the development of age-specific disease biomarkers.

Indexed as

BiomarkersAdultAgedAgingDiseaseFemaleGene ExpressionGene Expression ProfilingHealthy AgingHumansMaleMicroRNAsRNA-SeqBiomarkersMicroRNAs

Identifiers

PMID33235214
PMCPMC7686493
OpenAlexW3110637034

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.