Evidence map›Paper›PMID 34815556›Full record

ReviewNature reviews. Immunology2022

Immune ageing at single-cell resolution.

Denis A Mogilenko, Irina Shchukina, Maxim N Artyomov

Open access · bronzeAbstract readReview
In one paragraph

Review in Nature reviews. Immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 228 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
228citing papers in PubMed, 3 pooled it
21.6field-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

228 citing papers in PubMed, 3 syntheses or guidelines pooled it, 369 citations in OpenAlex.

  1. Pooled it
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  10. The long-lived immune system of centenarians.Nature reviews. Immunology · 2026
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168 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

3 authors at 1 institution in 1 country.

Denis A Mogilenko *Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA.ORCID http://orcid.org/0000-0001-5427-5243
Irina Shchukina *Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA.
Maxim N ArtyomovDepartment of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA. martyomov@wustl.edu.ORCID http://orcid.org/0000-0002-1133-4212
Washington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ageing leads to profound alterations in the immune system and increases susceptibility to some chronic, infectious and autoimmune diseases. In recent years, widespread application of single-cell techniques has enabled substantial progress in our understanding of the ageing immune system. These comprehensive approaches have expanded and detailed the current views of ageing and immunity. Here we review a body of recent studies that explored how the immune system ages using unbiased profiling techniques at single-cell resolution. Specifically, we discuss an emergent understanding of age-related alterations in innate and adaptive immune cell populations, antigen receptor repertoires and immune cell-supporting microenvironments of the peripheral tissues. Focusing on the results obtained in mice and humans, we describe the multidimensional data that align with established concepts of immune ageing as well as novel insights emerging from these studies. We further discuss outstanding questions in the field and highlight techniques that will advance our understanding of immune ageing in the future.

Indexed as

AgingAutoimmune DiseasesAnimalsHumansImmune SystemImmunity, InnateMice

Identifiers

PMID34815556
PMCPMC8609266
OpenAlexW3215796337

What OpenQuestion holds

Textmetadata
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.