Evidence map›Paper›PMID 39813278›Full record

ArticlePloS one2025

Development and optimization of a new competitive ELISA using recombinant (rPSA D15 and rCag11) antigens for the detection of Helicobacter pylori infection.

Biniam Moges Eskeziyaw, Naomi Maina, Rebecca Waihenya, Matthew Mutinda Munyao, Tonny Teya Nyandwaro, Shingo Inoue, Samson Muuo Nzou

Abstract read
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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

7 authors.

Biniam Moges EskeziyawPan African University for Basic Science, Technology and Invocation (PAUSTI), Nairobi, Kenya.ORCID 0000-0002-3219-305X
Naomi MainaDepartment of Biochemistry, Jomo Kenyatta University of Agriculture and Technology, (JKUAT), Juja, Kenya.
Rebecca WaihenyaDepartment of Zoology, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, Kenya.
Matthew Mutinda MunyaoKenya Medical Research Institute, Centre for Microbiology Research, Nairobi, Kenya.
Tonny Teya NyandwaroKenya Medical Research Institute, Centre for Microbiology Research, Nairobi, Kenya.
Shingo InoueNagasaki University Institute of Tropical Medicine-Kenya Medical Research Institute Project, Nairobi, Kenya.
Samson Muuo NzouKenya Medical Research Institute, Centre for Microbiology Research, Nairobi, Kenya.ORCID 0000-0002-5789-4434

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

H. pylori (Hp) is highly causative agent of chronic gastritis, gastric cancer and human death worldwide. To address the challenge of H. pylori infection, numerous immunological assays have been developed for its diagnosis and management. However, the limited availability of these assays in certain laboratories, coupled with their high cost, inconsistent specificity, and sensitivity, has hampered their widespread adoption, particularly in developing countries where H. pylori infection is prevalent. Therefore, this study aimed to develop and validate a competitive enzyme-linked immunosorbent assay (cELISA) assay for detecting H. pylori infections by targeting the Protective Surface Antigen (PSA) and Cytotoxic-Associated Gene Pathogenesis Island (Cag11) proteins in H. pylori stool antigen sample. In the current study, the optimal conditions including the dilution of anti-rPSA D15 and anti-rCag11 antibodies at 1:1000, coating antigens (rPSA D15 and rCag11) at a concentration of 1 μg/well, the dilution of HRP-labelled antibody at 1:5000 and H. pylori stool antigen dilution at 1:1000 with a 1hour incubation and color development time of 30 minutes for cELISA were determined using an ELISA checkerboard titration assay. Based on the optimized conditions, novel rPSA D15-cELISA and rCag11-cELISA assays with a respective optimum cut-off value of 20.80% PI and 24.16% PI were developed. According to the receiver operating characteristic (ROC) curve analysis on the diagnostic performance of the newly developed rPSA D15-cELISA and rCag11-cELISA assays using 60 clinical H. pylori stool samples, the rPSA D15-cELISA test assay established an optimum cut-off point of 20.80% with sensitivity and specificity of 90% (95% confidence of interval (CI) 74.38-96.54), Area under the curve (AUC) of 0.9556 (95% CI = 0.896-1.000) and P value <0.0001. Similarly, the rCag11-cELISA assay revealed optimum cut-off value of 24.16% with sensitivity of 93.33% (95% CI 78.68-98.82), specificity of 90% (95% CI 74.38-96.54), AUC of 0.986 (95% CI = 0.967-1.000) and P <0.0001. Furthermore, the reproducibility assay coefficients of variation (CV) of the newly developed rPSA D15-cELISA and rCag11-cELISA assay were less than 10%, indicating that the two cELISA assays exhibits excellent reproducibility and reliability. To validate their clinical diagnostic application, the comparative study results of rPSA D15-cELISA and rCag11-cELISA showed a high agreement (k = 0.766 and 0.799) with the commercially available H. pylori antigen test immunochromatographic kit and more accurate than the reference kit by detecting stool antigen of H. pylori strain, indicating it is promising for clinical testing. In conclusion, these results indicated that the newly developed rPSA D15-cELISA and rCag11-cELISA H. pylori stool antigen test assays were a potential reliable and a clinically useful assay for rapid, specifically, sensitively and accurately diagnosis and large-scale epidemiological investigation of H. pylori infection.

Indexed as

Antigens, BacterialBacterial ProteinsHelicobacter InfectionsHelicobacter pyloriEnzyme-Linked Immunosorbent AssayFecesHumansRecombinant ProteinsROC CurveSensitivity and SpecificityAntigens, BacterialBacterial ProteinsRecombinant Proteins

Identifiers

PMID39813278
PMCPMC11734991

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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.