Evidence map›Paper›PMID 37199141›Full record

ArticleProteomics2023

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum.

Nagib Ahsan, Luca Fornelli, Fares Z Najar, Sanjeewa Gamagedara, Mohammad Robiul Hossan, R Shyama Prasad Rao, Ujwal Punyamurtula, Andrew Bauer, Zhibo Yang, Steven B Foster and 1 more

Open access · greenAbstract read
In one paragraph

Article in Proteomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  5. Review
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  8. Deciphering Acute Coronary Syndromes Pathobiology Through Proteomics.Journal of cardiovascular development and disease · 2025
    Review
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  10. 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 at 7 institutions in 2 countries.

Nagib AhsanDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA.ORCID 0000-0002-6813-7527
Luca FornelliDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA.
Fares Z NajarHigh-Performance Computing Center (HPCC), Oklahoma State University, Stillwater, Oklahoma, USA.
Sanjeewa GamagedaraDepartment of Chemistry, University of Central Oklahoma, Edmond, Oklahoma, USA.
Mohammad Robiul HossanSchool of Engineering, University of Central Oklahoma, Edmond, Oklahoma, USA.
R Shyama Prasad RaoCenter for Bioinformatics, NITTE deemed to be University, Mangaluru, Karnataka, India.
Ujwal PunyamurtulaDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Andrew BauerDepartment of Neurosurgery, University of Oklahoma-Health Science Center, Oklahoma, Oklahoma, USA.
Zhibo YangDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA.
Steven B FosterDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA.
Maureen A KaneDepartment of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland, USA.
University of Oklahoma · USUniversity of Central Oklahoma · USDana-Farber Cancer Institute · USNitte University · INOklahoma State University · USUniversity of Maryland, Baltimore · USUniversity of Oklahoma Health Sciences Center · US

Funding

Proteomics CoreP20GM103447 · NIGMS · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI David W Dyer · 2012 to 2026
$60.2M
A multi-level mass spectrometry pipeline for the analysis of whole proteoforms and their complexesR35GM147397 · NIGMS · UNIVERSITY OF OKLAHOMA · PI Luca Fornelli · 2022 to 2026
$1.9M
NIGMS NIH HHS P20 GM103447NIGMS NIH HHS R35 GM147397
6 · The paper itself

Abstract

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Indexed as

Blood ProteinsProteomicsBiomarkersBiomarkers, TumorHumansImmunoglobulin GBiomarkersBiomarkers, TumorBlood ProteinsImmunoglobulin Gabundant protein depletionbiomarkersbloodcomparative proteomicspathogenesisserum

Identifiers

PMID37199141
PMCPMC11166006
OpenAlexW4377011024

What OpenQuestion holds

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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.