Interference of Antinuclear Antibody (ANA) in Indirect Immunofluorescence Assay (IIFA)-Based Perinuclear Antineutrophil Cytoplasmic Antibody (pANCA) Interpretation.


Journal

Autoimmune diseases
ISSN: 2090-0422
Titre abrégé: Autoimmune Dis
Pays: United States
ID NLM: 101546750

Informations de publication

Date de publication:
2022
Historique:
received: 16 03 2022
revised: 02 09 2022
accepted: 14 09 2022
entrez: 7 11 2022
pubmed: 8 11 2022
medline: 8 11 2022
Statut: epublish

Résumé

Indirect immunofluorescence assay (IIFA) based on antineutrophil cytoplasmic antibody (ANCA) testing is a commonly employed test for diagnosing autoimmune vasculitis. Antinuclear antibody (ANA) can give rise to a false interpretation of perinuclear-ANCA (pANCA) in ethanol-fixed granulocyte substrates. Analytical interference could frequently occur in setups where ethanol-fixed substrates are used alone. Here, we intend to investigate this ANA interference in pANCA interpretation. In this retrospective study, we studied anti-MPO-negative but ANA-positive and pANCA (IIFA based) samples. We also correlated immunoblot results (where data were available) and checked the association between grades of blot positivity (an indicator of the concentration of ANA) and frequency of pANCA interpretation. Data were analyzed by appropriate statistical techniques (Chi-square and kappa statistics). About 19.2% of ANA blot (ENA-blot) positive samples displayed a pANCA positive pattern in the ethanol-fixed substrate, while this positivity in ENA-blot negatives was 6.5%. In positive ANA-IIFA samples, about 14.7% yielded pANCA patterns (on ethanol fixed substrates). Out of this, nuclear homogenous pattern yielding samples gave the highest frequency pANCA, that is, in 31.5% followed by speckled (11.1%), DFS (10.3%), and centromere (6.7%).The association of the nuclear homogenous pattern was statistically significant. ANA-positive results may interfere with the interpretation of pANCA as observed in ANA-IIFA and ENA-blot positive samples. ANA-IIFA patterns like nuclear homogenous may strongly associate this pANCA interpretation. This can help laboratories perform ANCA testing more effectively, ruling out ANA interference in ANCA screening.

Sections du résumé

Background UNASSIGNED
Indirect immunofluorescence assay (IIFA) based on antineutrophil cytoplasmic antibody (ANCA) testing is a commonly employed test for diagnosing autoimmune vasculitis. Antinuclear antibody (ANA) can give rise to a false interpretation of perinuclear-ANCA (pANCA) in ethanol-fixed granulocyte substrates. Analytical interference could frequently occur in setups where ethanol-fixed substrates are used alone. Here, we intend to investigate this ANA interference in pANCA interpretation.
Methods UNASSIGNED
In this retrospective study, we studied anti-MPO-negative but ANA-positive and pANCA (IIFA based) samples. We also correlated immunoblot results (where data were available) and checked the association between grades of blot positivity (an indicator of the concentration of ANA) and frequency of pANCA interpretation. Data were analyzed by appropriate statistical techniques (Chi-square and kappa statistics).
Results UNASSIGNED
About 19.2% of ANA blot (ENA-blot) positive samples displayed a pANCA positive pattern in the ethanol-fixed substrate, while this positivity in ENA-blot negatives was 6.5%. In positive ANA-IIFA samples, about 14.7% yielded pANCA patterns (on ethanol fixed substrates). Out of this, nuclear homogenous pattern yielding samples gave the highest frequency pANCA, that is, in 31.5% followed by speckled (11.1%), DFS (10.3%), and centromere (6.7%).The association of the nuclear homogenous pattern was statistically significant.
Conclusions UNASSIGNED
ANA-positive results may interfere with the interpretation of pANCA as observed in ANA-IIFA and ENA-blot positive samples. ANA-IIFA patterns like nuclear homogenous may strongly associate this pANCA interpretation. This can help laboratories perform ANCA testing more effectively, ruling out ANA interference in ANCA screening.

Identifiants

pubmed: 36338545
doi: 10.1155/2022/1343805
pmc: PMC9629954
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1343805

Informations de copyright

Copyright © 2022 Sangeeta Deka et al.

Déclaration de conflit d'intérêts

The author(s) declare that they have no conflicts of interest.

Références

Autoimmun Rev. 2021 Mar;20(3):102759
pubmed: 33476813
J Immunol Methods. 2018 Jul;458:1-7
pubmed: 29486145
J Lab Physicians. 2021 Sep;13(3):286-290
pubmed: 34602797
Arthritis Rheum. 1998 Sep;41(9):1521-37
pubmed: 9751084
J Appl Lab Med. 2022 Jan 5;7(1):75-80
pubmed: 34996078
Ann Rheum Dis. 2014 Jan;73(1):17-23
pubmed: 24126457
Clin Rev Allergy Immunol. 2022 Oct;63(2):124-137
pubmed: 34491531
Mediterr J Rheumatol. 2018 Mar 19;29(1):17-20
pubmed: 32185292
Reumatol Clin. 2015 Jan-Feb;11(1):17-21
pubmed: 24913965
J Immunol Res. 2014;2014:315179
pubmed: 24868563
Reumatol Clin (Engl Ed). 2020 Nov - Dec;16(6):473-479
pubmed: 30704921
Autoimmun Rev. 2013 Feb;12(4):487-95
pubmed: 22921790
Rinsho Byori. 2010 May;58(5):480-9
pubmed: 20560457
Am J Clin Pathol. 2013 Aug;140(2):184-92
pubmed: 23897253
Kidney Dis (Basel). 2016 Mar;1(4):205-15
pubmed: 27536680
Clin Rev Allergy Immunol. 2022 Oct;63(2):107-123
pubmed: 34460071
Am J Clin Pathol. 2014 Sep;142(3):325-30
pubmed: 25125622
Nat Rev Rheumatol. 2017 Nov;13(11):683-692
pubmed: 28905856
Ann Rheum Dis. 2019 Oct;78(10):e113
pubmed: 30185413

Auteurs

Sangeeta Deka (S)

All India Institute of Medical Sciences, Rishikesh, India.

Deepjyoti Kalita (D)

All India Institute of Medical Sciences, Rishikesh, India.

Udaykumar Sasi Rekha (US)

All India Institute of Medical Sciences, Rishikesh, India.

Putul Mahanta (P)

Assam Medical College, Dibrugarh, India.

Diksha Rani (D)

All India Institute of Medical Sciences, Rishikesh, India.

Ravi Shankar (R)

All India Institute of Medical Sciences, Rishikesh, India.

Anusha Krishna Raj (AK)

All India Institute of Medical Sciences, Rishikesh, India.

Mithilesh Kumar Jha (MK)

All India Institute of Medical Sciences, Rishikesh, India.

Gaurav Badoni (G)

All India Institute of Medical Sciences, Rishikesh, India.

Manisha Paul (M)

All India Institute of Medical Sciences, Rishikesh, India.

Shailesh Kumar Gupta (SK)

All India Institute of Medical Sciences, Rishikesh, India.

Shailender Negi (S)

All India Institute of Medical Sciences, Rishikesh, India.

Anshu Singh (A)

All India Institute of Medical Sciences, Rishikesh, India.

Kuhu Chatterjee (K)

All India Institute of Medical Sciences, Rishikesh, India.

Classifications MeSH