Evidence map›Paper›PMID 32694606›Full record

ReviewNature metabolism2020

Single-cell omics in ageing: a young and growing field.

Xiaojuan He, Sebastian Memczak, Jing Qu, Juan Carlos Izpisua Belmonte, Guang-Hui Liu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

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8 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

5 authors.

Xiaojuan HeAdvanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China.
Sebastian MemczakGene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.ORCID http://orcid.org/0000-0001-9518-7135
Jing QuState Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China. qujing@ioz.ac.cn.ORCID http://orcid.org/0000-0002-3988-5067
Juan Carlos Izpisua BelmonteGene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA. belmonte@salk.edu.ORCID http://orcid.org/0000-0003-0557-8875
Guang-Hui LiuAdvanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China. ghliu@ioz.ac.cn.ORCID http://orcid.org/0000-0001-9289-8177

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organismal ageing results from interlinked molecular changes in multiple organs over time. The study of ageing at the molecular level is complicated by varying decay characteristics and kinetics-both between and within organs-driven by intrinsic and extracellular factors. Emerging single-cell omics methods allow for molecular and spatial profiling of cells, and probing of regulatory states and cell-fate determination, thus providing promising tools for unravelling the heterogeneous process of ageing and making it amenable to intervention. These new strategies are enabled by advances in genomic, epigenomic and transcriptomic technologies. Combined with methods for proteome and metabolome analysis, single-cell techniques provide multidimensional, integrated data with unprecedented detail and throughput. Here, we provide an overview of the current state, and perspectives on the future, of this emerging field. We discuss how single-cell approaches can advance understanding of mechanisms underlying organismal ageing and aid in the development of interventions for ageing and ageing-associated diseases.

Indexed as

TranscriptomeAgingEpigenomicsGenomicsHumansMetabolomicsProteomicsSingle-Cell Analysis

Identifiers

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.