Evidence map›Paper›PMID 31889938›Full record

ArticleClinical proteomics2019

Clinical method evaluation of hemoglobin S and C identification by top-down selected reaction monitoring and electron transfer dissociation.

Olivier Lassout, Ralf Hartmer, Wolfgang Jabs, Lorella Clerici, Yury O Tsybin, Kaveh Samii, Nicolas Vuilleumier, Denis Hochstrasser, Alexander Scherl, Pierre Lescuyer and 1 more

Abstract read
In one paragraph

Article in Clinical proteomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
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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

11 authors.

Olivier Lassout1Department of Medical Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Ralf HartmerBruker Daltonics, Bremen, Germany.
Wolfgang JabsBruker Daltonics, Bremen, Germany.
Lorella Clerici2Division of Laboratory Medicine, Department of Laboratory Medicine, Genetics and Pathology, Geneva University Hospitals, 4 Rue Gabrielle-Perret-Gentil, 1205 Geneva, Switzerland.
Yury O Tsybin4Spectroswiss, EPFL Innovation Park, Lausanne, Switzerland.
Kaveh Samii2Division of Laboratory Medicine, Department of Laboratory Medicine, Genetics and Pathology, Geneva University Hospitals, 4 Rue Gabrielle-Perret-Gentil, 1205 Geneva, Switzerland.
Nicolas Vuilleumier1Department of Medical Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Denis Hochstrasser1Department of Medical Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Alexander Scherl1Department of Medical Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Pierre Lescuyer1Department of Medical Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Didia Coelho Graça1Department of Medical Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland.ORCID 0000-0002-2677-7884

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiological diagnosis of hemoglobin disorders is a complex process relying on the combination of several analytical techniques to identify Hb variants in a particular sample. Currently, hematology laboratories usually use high-performance liquid chromatography (HPLC), capillary electrophoresis and gel-based methods to characterize Hb variants. Co-elution and co-migration may represent major issues for precise identification of Hb variants, even for the most common ones such as Hb S and C.

methodsWe adapted a top-down selected reaction monitoring (SRM) electron transfer dissociation (ETD) mass spectrometry (MS) method to fit with a clinical laboratory environment. An automated analytical process with semi-automated data analysis compatible with a clinical practice was developed. A comparative study between a reference HPLC method and the MS assay was performed on 152 patient samples.

resultsThe developed workflow allowed to identify with high specificity and selectivity the most common Hb variants (Hb S and Hb C). Concordance of the MS-based approach with HPLC was 71/71 (100%) for Hb S and 11/11 (100%) for Hb C.

conclusionsThis top-down SRM ETD method can be used in a clinical environment to detect Hb S and Hb C.

Indexed as

Electron transfer dissociationETDHemoglobinHemoglobin disordersHemoglobin variantIntact proteinSelected reaction monitoringSRMTop-down

Identifiers

PMID31889938
PMCPMC6915975

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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.