1887

Journal of Medical Microbiology logo

Volume 72, Issue 6

Evaluation and validation of a commercial ELISA versus the toxin neutralization assay for determination of diphtheria anti-toxin in human serum Open Access

Abstract

Diphtheria is a potentially life-threatening infection and remains endemic in many low- and middle-income countries (LMICs). A reliable, low-cost method for serosurveys in LMICs is warranted to estimate the accurate population immunity to control diphtheria.

The correlation between the ELISA results against diphtheria toxoid and the gold standard diphtheria toxin neutralization test (TNT) values is poor when ELISA values are <0.1 IU ml, which results in inaccurate estimates of susceptibility in populations when ELISA is used for measuring antibody levels.

To explore methods to accurately predict population immunity and TNT-derived anti-toxin titres from ELISA anti-toxoid results.

A total of 96 paired serum and dried blood spot (DBS) samples collected in Vietnam were used for comparison of TNT and ELISA. The diagnostic accuracy of ELISA measurement with reference to TNT was assessed by area under the receiver operating characteristic (ROC) curve (AUC) and other parameters. Optimal ELISA cut-off values corresponding to TNT cut-off values of 0.01 and 0.1 IU ml were identified by ROC analysis. A method based on the multiple imputation approach was also applied to estimate TNT measurements in a dataset that only included ELISA results. These two approaches were then applied to ELISA results previously generated from 510 subjects in a serosurvey in Vietnam.

The ELISA results on DBS samples showed a good diagnostic performance compared to TNT. The cut-off values for ELISA measurement corresponding to the TNT cut-off values of 0.01 IU ml were 0.060 IU ml in serum samples, and 0.044 IU ml in DBS samples. When a cut-off value of 0.06 IU ml was applied to the 510 subject serosurvey data, 54 % of the population were considered susceptible (<0.01 IU ml). The multiple imputation-based approach estimated that 35 % of the population were susceptible. These proportions were much larger than the susceptible proportion estimated by the original ELISA measurements.

Testing a subset of sera by TNT combined with ROC analysis or a multiple imputation approach helps to adjust ELISA thresholds or values to assess population susceptibility more accurately. DBS is an effective low-cost alternative to serum for future serological studies for diphtheria.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): assay validation , diphtheria , dried blood spots , enzyme-linked immunosorbent assay , multiple imputation and toxin neutralization assay
Funding
This study was supported by the:
  • Japan Society for the Promotion of Science Overseas Research Fellowships
    • Principle Award Recipient: EndoAkira
  • Nagasaki University
    • Principle Award Recipient: KitamuraNoriko
  • Ministry of Education, Culture, Sports, Science, and Technology, Japan
    • Principle Award Recipient: KitamuraNoriko
  • Japan Society for the Promotion of Science, KAKENHI (Award JP20K18905)
    • Principle Award Recipient: ToizumiMichiko
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/jmm/10.1099/jmm.0.001721
2023-06-20
2024-05-02
Loading full text...

Full text loading...

/deliver/fulltext/jmm/72/6/jmm001721.html?itemId=/content/journal/jmm/10.1099/jmm.0.001721&mimeType=html&fmt=ahah

References

  1. Center for Disease Control and Prevention Epidemiology and Prevention of Vaccine-Preventable Diseases Washington, DC: Public Health Foundation; 2015 pp 107–118
     [Google Scholar]
  2. World Health Organization Diphtheria Vaccine WHO Position Paper August 2017 – Recommendations Geneva: WHO; 2017
     [Google Scholar]
  3. World Health Organization Diphtheria reported cases and incidence. https://immunizationdata.who.int/pages/incidence/DIPHTHERIA.html?CODE=Global&YEAR=
  4. World Health Organization Vaccine-Preventable Disease Update: Reported Diphtheria Cases in the WHO European Region (10 October 2022) Geneva: WHO; 2022
     [Google Scholar]
  5. Polonsky JA, Ivey M, Mazhar MdKA, Rahman Z, le Polain de Waroux O et al. Epidemiological, clinical, and public health response characteristics of a large outbreak of diphtheria among the Rohingya population in Cox’s Bazar, Bangladesh, 2017 to 2019: a retrospective study. PLoS Med 2017; 18:e1003587 [View Article]
     [Google Scholar]
  6. Page KR, Doocy S, Reyna Ganteaume F, Castro JS, Spiegel P et al. Venezuela’s public health crisis: a regional emergency. The Lancet 2019; 393:1254–1260 [View Article]
     [Google Scholar]
  7. Badell E, Alharazi A, Criscuolo A, Almoayed KAA, Lefrancq N et al. Ongoing diphtheria outbreak in Yemen: a cross-sectional and genomic epidemiology study. Lancet Microbe 2021; 2:e386–e396 [View Article] [PubMed]
     [Google Scholar]
  8. European Centre for Disease Prevention and Control Increase of Reported Diphtheria Cases Among Migrants in Europe Due to Corynebacterium diphtheriae, 2022 (6 October 2022) Stockholm: ECDC; 2022
     [Google Scholar]
  9. Clarke KEN, MacNeil A, Hadler S, Scott C, Tiwari TSP et al. Global epidemiology of diphtheria, 2000–2017. Emerg Infect Dis 2019; 25:1834–1842 [View Article]
     [Google Scholar]
  10. Metcalf CJE, Farrar J, Cutts FT, Basta NE, Graham AL et al. Use of serological surveys to generate key insights into the changing global landscape of infectious disease. The Lancet 2016; 388:728–730 [View Article]
     [Google Scholar]
  11. European Centre for Disease Prevention and Control Evaluation and Assessment of Serological Immunity Methods and EQA Scheme of Diphtheria Stockholm: ECDC; 2014
     [Google Scholar]
  12. World Health Organization The Immunological Basis for Immunization Series Module 2: Diphtheria Geneva: WHO; 2009
     [Google Scholar]
  13. Cutts FT, Hanson M. Seroepidemiology: an underused tool for designing and monitoring vaccination programmes in low‐ and middle‐income countries. Trop Med Int Health 2016; 21:1086–1098 [View Article]
     [Google Scholar]
  14. McDade TW, Williams S, Snodgrass JJ. What a drop can do: dried blood spots as a minimally invasive method for integrating biomarkers into population-based research. Demography 2007; 44:899–925 [View Article] [PubMed]
     [Google Scholar]
  15. Schiffer JM, Maniatis P, Garza I, Steward-Clark E, Korman LT et al. Quantitative assessment of anthrax vaccine immunogenicity using the dried blood spot matrix. Biologicals 2013; 41:98–103 [View Article]
     [Google Scholar]
  16. von Hunolstein C, Ralli L, Pinto A, Stickings P, Efstratiou A et al. Relevance and criticality in an external quality assessment for the determination of diphtheria antitoxin. J Immunol Clin Res 2014; 2:1022
     [Google Scholar]
  17. World Health Organization WHO Laboratory Manual for the Diagnosis of Diphtheria and Other Related Infections Geneva: WHO; 2021
     [Google Scholar]
  18. Di Giovine P, Pinto A, Olander R-M, Sesardic D, Stickings P et al. External quality assessment for the determination of diphtheria antitoxin in human serum. Clin Vaccine Immunol 2010; 17:1282–1290 [View Article] [PubMed]
     [Google Scholar]
  19. von Hunolstein C, Aggerbeck H, Andrews N, Berbers G, Fievet-Groyne F et al. European sero-epidemiology network: standardisation of the results of diphtheria antitoxin assays. Vaccine 2000; 18:3287–3296 [View Article]
     [Google Scholar]
  20. Walory J, Grzesiowski P, Hryniewicz W. Comparison of four serological methods for the detection of diphtheria anti-toxin antibody. J Immunol Methods 2000; 245:55–65 [View Article] [PubMed]
     [Google Scholar]
  21. Kitamura N, Le LT, Le TTT, Nguyen H-AT, Edwards T et al. The seroprevalence, waning rate, and protective duration of anti-diphtheria toxoid IgG antibody in Nha Trang, Vietnam. Int J Infect Dis 2022; 116:273–280 [View Article] [PubMed]
     [Google Scholar]
  22. Schou C, Simonsen O, Heron I. Determination of tetanus and diphtheria antitoxin content in dried samples of capillary blood: a convenient method applied to infants. Scand J Infect Dis 1987; 19:445–451 [View Article] [PubMed]
     [Google Scholar]
  23. Lu MJ, Zhong WH, Liu YX, Miao HZ, Li YC et al. Sample size for assessing agreement between two methods of measurement by Bland−Altman method. Int J Biostat 2016; 12:20150039 [View Article]
     [Google Scholar]
  24. Guthrie R. The origin of newborn screening. Screening 1992; 1:5–15 [View Article]
     [Google Scholar]
  25. NCCLS Blood Collection on Filter Paper for Neonatal Screening Programs: Approved Standard Wayne, PA: National Committee for Clinical Laboratory Standards; 1997
     [Google Scholar]
  26. Jenjaroen K, Phetsouvanh R, Day NPJ, Newton PN, Blacksell SD. Comparison of indirect immunofluorescence assays for diagnosis of scrub typhus and murine typhus using venous blood and finger prick filter paper blood spots. Am J Trop Med Hyg 2009; 80:837–840 [View Article]
     [Google Scholar]
  27. Kattenberg JH, Erhart A, Truong MH, Rovira-Vallbona E, Vu KAD et al. Characterization of Plasmodium falciparum and Plasmodium vivax recent exposure in an area of significantly decreased transmission intensity in Central Vietnam. Malar J 2018; 17:180 [View Article]
     [Google Scholar]
  28. Riddell MA, Leydon JA, Catton MG, Kelly HA. Detection of measles virus-specific immunoglobulin M in dried venous blood samples by using a commercial enzyme immunoassay. J Clin Microbiol 2002; 40:5–9 [View Article] [PubMed]
     [Google Scholar]
  29. Power M, Fell G, Wright M. Principles for high-quality, high-value testing. Evid Based Med 2013; 18:5–10 [View Article] [PubMed]
     [Google Scholar]
  30. Šimundić AM. Measures of diagnostic accuracy: basic definitions. EJIFCC 2009; 19:203–211 [PubMed]
     [Google Scholar]
  31. Lopez AL, Adams C, Ylade M, Jadi R, Daag JV et al. Determining dengue virus serostatus by indirect IgG ELISA compared with focus reduction neutralisation test in children in Cebu, Philippines: a prospective population-based study. Lancet Glob Health 2021; 9:e44–e51 [View Article] [PubMed]
     [Google Scholar]
  32. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33:159–174 [PubMed]
     [Google Scholar]
  33. Mukaka MM. Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Med J 2012; 24:69–71 [PubMed]
     [Google Scholar]
  34. Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics 1989; 45:255–268 [PubMed]
     [Google Scholar]
  35. Youden WJ. Index for rating diagnostic tests. Cancer 1950; 3:32–35 [View Article] [PubMed]
     [Google Scholar]
  36. Rubin DB. Multiple Imputation for Nonresponse in Surveys Hoboken, NJ: Wiley; 1987 [View Article]
     [Google Scholar]
  37. StataCorp Stata Statistical Software: release 15 College Station, TX: StataCorp LLC; 2017
     [Google Scholar]
  38. R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria; 2020 https://www.R-project.org/
  39. Berbers G, van Gageldonk P, Kassteele J van de, Wiedermann U, Desombere I et al. Circulation of pertussis and poor protection against diphtheria among middle-aged adults in 18 European countries. Nat Commun 2021; 12:2871 [View Article] [PubMed]
     [Google Scholar]
  40. Kitamura N, Le TTT, Le LT, Nguyen LD, Dao AT et al. Diphtheria outbreaks in schools in Central Highland districts, Vietnam, 2015–2018. Emerg Infect Dis 2020; 26:596–600 [View Article]
     [Google Scholar]
  41. Murakami H, Phuong NM, Thang HV, Chau NV, Giao PN et al. Endemic diphtheria in Ho Chi Minh City; Viet Nam: a matched case-control study to identify risk factors of incidence. Vaccine 2010; 28:8141–8146 [View Article] [PubMed]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/jmm/10.1099/jmm.0.001721
Loading
Evaluation and validation of a commercial ELISA versus the in vitro toxin neutralization assay for determination of diphtheria anti-toxin in human serum
J. Med. Microbiol. 72, 001721 (2023); https://doi.org/10.1099/jmm.0.001721
/content/journal/jmm/10.1099/jmm.0.001721
/content/journal/jmm/10.1099/jmm.0.001721
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error