Evidence map›Paper›PMID 35279219›Full record

ArticleClinical epigenetics2022

Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes.

Denis Seyres, Alessandra Cabassi, John J Lambourne, Frances Burden, Samantha Farrow, Harriet McKinney, Joana Batista, Carly Kempster, Maik Pietzner, Oliver Slingsby and 25 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical epigenetics, 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
2.2field-weighted citation impact, top 12% 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, 14 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
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

35 authors at 7 institutions in 4 countries.

Denis SeyresNational Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK. ds777@medschl.cam.ac.uk.ORCID 0000-0002-2066-6980
Alessandra CabassiMRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
John J LambourneNational Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK.
Frances BurdenNational Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK.
Samantha FarrowNational Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK.
Harriet McKinneyDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Joana BatistaDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Carly KempsterDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Maik PietznerMRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Oliver SlingsbyDepartment of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK.
Thong Huy CaoDepartment of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK.
Paulene A QuinnDepartment of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK.
Luca StefanucciDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Matthew C SimsDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Karola RehnstromDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Claire L AdamsMetabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK.
Amy FraryDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Bekir ErgüenerCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
Roman KreuzhuberDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Gabriele MocciaroDepartment of Biochemistry and the Cambridge Systems Biology Centre, University of Cambridge, The Sanger Building, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.
Simona D'AmoreAddenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Albert KoulmanMRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Luigi GrassiNational Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK.
Julian L GriffinDepartment of Biochemistry and the Cambridge Systems Biology Centre, University of Cambridge, The Sanger Building, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.
Leong Loke NgDepartment of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK.
Adrian ParkAddenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
David B SavageMetabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK.
Claudia LangenbergMRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Christoph BockCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
Kate DownesNational Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK.
Nicholas J WarehamMRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Michael AllisonAddenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Michele VaccaMetabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK.
Paul D W KirkMRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK. paul.kirk@mrc-bsu.cam.ac.uk.
Mattia FrontiniDepartment of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK. mf471@cam.ac.uk.
University of Cambridge · GBNHS Blood and Transplant · GBUniversity of Leicester · GBCambridge University Hospitals NHS Foundation Trust · GBAustrian Academy of Sciences · ATEuropean Bioinformatics Institute · GBMRC Human Nutrition Research · GB

Funding

British Heart Foundation FS/18/53/33863Medical Research Council MC_UU_00002/13Medical Research Council MC_UU_00006/1Medical Research Council MC_UU_12012/1Medical Research Council MR/R002363/1Wellcome TrustWellcome Trust WT 107064
6 · The paper itself

Abstract

backgroundThis work is aimed at improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis by generating a multi-omic disease signature. METHODS/

resultsWe combined classic plasma biochemistry and plasma biomarkers with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (morbidly obese and lipodystrophy) and lean individuals to identify the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells. Our analyses showed that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, 6 months after bariatric surgery, revealed the loss of the abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurred via the establishment of novel gene expression landscapes. NETosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention.

conclusionsWe showed that the morbidly obese and lipodystrophy groups, despite some differences, shared a common cardiometabolic syndrome signature. We also showed that this could be used to discriminate, amongst the normal population, those individuals with a higher likelihood of presenting with the disease, even when not displaying the classic features.

Indexed as

LipodystrophyMetabolic SyndromeObesity, MorbidDNA MethylationEpigenesis, GeneticHumansPhenotypeBariatric surgeryCardiometabolic syndromeClassificationEpigeneticsInnate immune cellsLipidsLipodystrophyMetabolitesMulti-omicsObesity

Identifiers

PMID35279219
PMCPMC8917653
OpenAlexW4220953695

What OpenQuestion holds

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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.