Evidence map›Paper›PMID 34307452›Full record

ArticleFrontiers in molecular biosciences2021

A Comparison of Serum and Plasma Blood Collection Tubes for the Integration of Epidemiological and Metabolomics Data.

Jennie Sotelo-Orozco, Shin-Yu Chen, Irva Hertz-Picciotto, Carolyn M Slupsky

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
4.9field-weighted citation impact, top 3% 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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 73 citations in OpenAlex.

  1. Clinical lipidomics in bacterial sepsis: a systematic review of serum and plasma evaluations.Metabolomics : Official journal of the Metabolomic Society · 2026
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  6. Recent Trends in Metabolomics by NMR Spectroscopy.Angewandte Chemie (International ed. in English) · 2026
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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

4 authors at 1 institution in 1 country.

Jennie Sotelo-OrozcoDepartment of Public Health Sciences, University of California Davis, Davis, CA, United States.
Shin-Yu ChenDepartment of Food Science and Technology, University of California Davis, Davis, CA, United States.
Irva Hertz-PicciottoDepartment of Public Health Sciences, University of California Davis, Davis, CA, United States.
Carolyn M SlupskyDepartment of Food Science and Technology, University of California Davis, Davis, CA, United States.
University of California, Davis · US

Funding

UC Davis Environmental Health Sciences Core CenterP30ES023513 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Ameer Taha · 2015 to 2026
$26.0M
THE CHARGE STUDY: CHILDHOOD AUTISM RISKS FROM GENETICS AND THE ENVIRONMENT - ADMINISTRATIVE SUPPLEMENTR01ES015359 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI HERTZ-PICCIOTTO, IRVA · 2007 to 2019
$13.8M
NIEHS NIH HHS P30 ES023513NIEHS NIH HHS R01 ES015359
6 · The paper itself

Abstract

Blood is a rich biological sample routinely collected in clinical and epidemiological studies. With advancements in high throughput -omics technology, such as metabolomics, epidemiology can now delve more deeply and comprehensively into biological mechanisms involved in the etiology of diseases. However, the impact of the blood collection tube matrix of samples collected needs to be carefully considered to obtain meaningful biological interpretations and understand how the metabolite signatures are affected by different tube types. In the present study, we investigated whether the metabolic profile of blood collected as serum differed from samples collected as ACD plasma, citrate plasma, EDTA plasma, fluoride plasma, or heparin plasma. We identified and quantified 50 metabolites present in all samples utilizing nuclear magnetic resonance (NMR) spectroscopy. The heparin plasma tubes performed the closest to serum, with only three metabolites showing significant differences, followed by EDTA which significantly differed for five metabolites, and fluoride tubes which differed in eleven of the fifty metabolites. Most of these metabolite differences were due to higher levels of amino acids in serum compared to heparin plasma, EDTA plasma, and fluoride plasma. In contrast, metabolite measurements from ACD and citrate plasma differed significantly for approximately half of the metabolites assessed. These metabolite differences in ACD and citrate plasma were largely due to significant interfering peaks from the anticoagulants themselves. Blood is one of the most banked samples and thus mining and comparing samples between studies requires understanding how the metabolite signature is affected by the different media and different tube types.

Indexed as

anticoagulantsepidemiological studiesmetabolic profilemetabolomicsNMR spectroscopyplasmaserum

Identifiers

PMID34307452
PMCPMC8295687
OpenAlexW3177973742

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.