Evidence map›Paper›PMID 39330481›Full record

ReviewMetabolites2024

An Overview of Pre-Analytical Factors Impacting Metabolomics Analyses of Blood Samples.

Amy Thachil, Li Wang, Rupasri Mandal, David Wishart, Tom Blydt-Hansen

Abstract readReview
In one paragraph

Review in Metabolites, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Clinical lipidomics in bacterial sepsis: a systematic review of serum and plasma evaluations.Metabolomics : Official journal of the Metabolomic Society · 2026
    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

5 authors.

Amy ThachilDepartment of Pediatrics, BC Children's Hospital, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Li WangDepartment of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.ORCID 0000-0002-3460-2080
Rupasri MandalFaculty of Science-Biological Sciences, The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB T6G 2R3, Canada.
David WishartDepartment of Laboratory Medicine & Pathology, Faculty of Science-Biological Sciences, The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB T6G 2R3, Canada.ORCID 0000-0002-3207-2434
Tom Blydt-HansenDivision of Nephrology, Department of Pediatrics, BC Children's Hospital, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Discrepant sample processing remains a significant challenge within blood metabolomics research, introducing non-biological variation into the measured metabolome and biasing downstream results. Inconsistency during the pre-analytical phase can influence experimental processes, producing metabolome measurements that are non-representative of in vivo composition. To minimize variation, there is a need to create and adhere to standardized pre-analytical protocols for blood samples intended for use in metabolomics analyses. This will allow for reliable and reproducible findings within blood metabolomics research. In this review article, we provide an overview of the existing literature pertaining to pre-analytical factors that influence blood metabolite measurements. Pre-analytical factors including blood tube selection, pre- and post-processing time and temperature conditions, centrifugation conditions, freeze-thaw cycles, and long-term storage conditions are specifically discussed, with recommendations provided for best practices at each stage.

Indexed as

bloodmetabolomicspre-analyticalprotocolsample processing

Identifiers

PMID39330481
PMCPMC11433674

What OpenQuestion 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 OpenQuestion graph.