Evidence map›Paper›PMID 35357430›Full record

ArticleHuman molecular genetics2022

Genetic and phenotypic links between obesity and extracellular vesicles.

Ranran Zhai, Lu Pan, Zhijian Yang, Ting Li, Zheng Ning, Yudi Pawitan, James F Wilson, Di Wu, Xia Shen

Open access · hybridAbstract read
In one paragraph

Article in Human molecular genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

9 authors at 3 institutions in 3 countries.

Ranran ZhaiBiostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.ORCID 0000-0002-5834-9120
Lu PanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden.
Zhijian YangBiostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.
Ting LiBiostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.
Zheng NingDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden.
Yudi PawitanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden.
James F WilsonCentre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH8 9AG, UK.
Di WuVesicode AB, Stockholm 17165, Sweden.
Xia ShenBiostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.ORCID 0000-0003-4390-1979
Sun Yat-sen University · CNKarolinska Institutet · SEInstitute of Genetics and Cancer · GB

Funding

Chief Scientist Office CZB/4/276Medical Research Council MC_UU_00007/10
6 · The paper itself

Abstract

Obesity has a highly complex genetic architecture, making it difficult to understand the genetic mechanisms, despite the large number of discovered loci via genome-wide association studies (GWAS). Omics techniques have provided a better resolution to view this problem. As a proxy of cell-level biology, extracellular vesicles (EVs) are useful for studying cellular regulation of complex phenotypes such as obesity. Here, in a well-established Scottish cohort, we utilized a novel technology to detect surface proteins across millions of single EVs in each individual's plasma sample. Integrating the results with established obesity GWAS, we inferred 78 types of EVs carrying one or two of 12 surface proteins to be associated with adiposity-related traits such as waist circumference. We then verified that particular EVs' abundance is negatively correlated with body adiposity, while no association with lean body mass. We also revealed that genetic variants associated with protein-specific EVs capture 2-4-fold heritability enrichment for blood cholesterol levels. Our findings provide evidence that EVs with specific surface proteins have phenotypic and genetic links to obesity and blood lipids, respectively, guiding future EV biomarker research.

Indexed as

Extracellular VesiclesObesityGenome-Wide Association StudyHumansMembrane ProteinsPhenotypeMembrane Proteins

Identifiers

PMID35357430
PMCPMC9616576
OpenAlexW4220923927

What OpenQuestion holds

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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.