Evidence map›Paper›PMID 32150548›Full record

SynthesisPLoS genetics2020

The influence of rare variants in circulating metabolic biomarkers.

Fernando Riveros-Mckay, Clare Oliver-Williams, Savita Karthikeyan, Klaudia Walter, Kousik Kundu, Willem H Ouwehand, David Roberts, Emanuele Di Angelantonio, Nicole Soranzo, John Danesh and 5 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PLoS genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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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

15 authors at 3 institutions in 2 countries.

Fernando Riveros-MckayWellcome Sanger Institute, Cambridge, United Kingdom.ORCID 0000-0002-6671-1177
Clare Oliver-WilliamsMRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-3573-2426
Savita KarthikeyanMRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-4798-5746
Klaudia WalterWellcome Sanger Institute, Cambridge, United Kingdom.ORCID 0000-0003-4448-0301
Kousik KunduWellcome Sanger Institute, Cambridge, United Kingdom.ORCID 0000-0002-1019-8351
Willem H OuwehandWellcome Sanger Institute, Cambridge, United Kingdom.ORCID 0000-0002-7744-1790
David RobertsThe National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Emanuele Di AngelantonioWellcome Sanger Institute, Cambridge, United Kingdom.
Nicole SoranzoWellcome Sanger Institute, Cambridge, United Kingdom.
John DaneshWellcome Sanger Institute, Cambridge, United Kingdom.
INTERVAL Study
Eleanor WheelerWellcome Sanger Institute, Cambridge, United Kingdom.
Eleftheria ZegginiWellcome Sanger Institute, Cambridge, United Kingdom.
Adam S ButterworthWellcome Sanger Institute, Cambridge, United Kingdom.
Inês BarrosoWellcome Sanger Institute, Cambridge, United Kingdom.ORCID 0000-0001-5800-4520
University of Cambridge · GBWellcome Sanger Institute · GBNHS Blood and Transplant · GB

Funding

British Heart Foundation RE/13/6/30180British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946British Heart Foundation SP/09/002Chief Scientist OfficeDepartment of Health BTRU-2014-10024Medical Research Council MC_UU_00006/1Medical Research Council MC_UU_12015/1Medical Research Council MR/L003120/1Wellcome TrustWellcome Trust 206194Wellcome Trust WT206194
6 · The paper itself

Abstract

Circulating metabolite levels are biomarkers for cardiovascular disease (CVD). Here we studied, association of rare variants and 226 serum lipoproteins, lipids and amino acids in 7,142 (discovery plus follow-up) healthy participants. We leveraged the information from multiple metabolite measurements on the same participants to improve discovery in rare variant association analyses for gene-based and gene-set tests by incorporating correlated metabolites as covariates in the validation stage. Gene-based analysis corrected for the effective number of tests performed, confirmed established associations at APOB, APOC3, PAH, HAL and PCSK (p<1.32x10-7) and identified novel gene-trait associations at a lower stringency threshold with ACSL1, MYCN, FBXO36 and B4GALNT3 (p<2.5x10-6). Regulation of the pyruvate dehydrogenase (PDH) complex was associated for the first time, in gene-set analyses also corrected for effective number of tests, with IDL and LDL parameters, as well as circulating cholesterol (pMETASKAT<2.41x10-6). In conclusion, using an approach that leverages metabolite measurements obtained in the same participants, we identified novel loci and pathways involved in the regulation of these important metabolic biomarkers. As large-scale biobanks continue to amass sequencing and phenotypic information, analytical approaches such as ours will be useful to fully exploit the copious amounts of biological data generated in these efforts.

Indexed as

BiomarkersCardiovascular DiseasesCholesterolCholesterol, LDLFemaleGenetic VariationGenome-Wide Association StudyHumansLipoproteinsMalePhenotypeTriglyceridesBiomarkersCholesterolCholesterol, LDLLipoproteinsTriglycerides

Identifiers

PMID32150548
PMCPMC7108731
OpenAlexW3009409673

What Socratic 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 Socratic graph.