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Publicly Available Published online by De Gruyter November 4, 2022

Preanalytical stability of SARS-CoV-2 anti-nucleocapsid antibodies

Tobias Niedrist ORCID logo , Lisa Kriegl , Christoph J Zurl , Felix Schmidt , Nicole Perkmann-Nagele , Patrick Mucher , Manuela Repl , Ines Flieder , Astrid Radakovics , Daniela Sieghart , Helga Radner , Daniel Aletaha , Christoph J. Binder , Christian Gülly , Robert Krause , Markus Herrmann , Oswald F. Wagner , Thomas Perkmann and Helmuth Haslacher ORCID logo EMAIL logo

Abstract

Objectives

Anti-nucleocapsid (NC) antibodies are produced in response to SARS-CoV-2 infection. Therefore, they are well suited for the detection of a previous infection. Especially in the case of seroprevalence studies or during the evaluation of a novel in-vitro diagnostic test, samples have been stored at <−70 °C (short- and long-term) or 2–10 °C (short-term) before analysis. This study aimed to assess the impact of different storage conditions relevant to routine biobanking on anti-NC antibodies.

Methods

The preanalytical impact of short-term storage (84 [58–98] days) on <−70 °C and for 14 days at 2–10 °C was evaluated using samples from 111 donors of the MedUni Vienna Biobank. Long-term effects (443 [409–468] days) were assessed using 208 samples from Biobank Graz and 49 samples from Biobank Vienna. Anti-Nucleocapsid antibodies were measured employing electrochemiluminescence assays (Roche Anti-SARS-CoV-2).

Results

After short-term storage, the observed changes did not exceed the extent that could be explained by analytical variability. In contrast, results after long-term storage were approximately 20% higher and seemed to increase with storage duration. This effect was independent of the biobank from which the samples were obtained. Accordingly, the sensitivity increased from 92.6 to 95.3% (p=0.008). However, comparisons with data from Anti-Spike protein assays, where these deviations were not apparent, suggest that this deviation could also be explained by the analytical variability of the qualitative Anti-NC assay.

Conclusions

Results from anti-NC antibodies are stable during short-term storage at <−70 °C and 2–10 °C. After long-term storage, a slight increase in sensitivity could not be ruled out.

Introduction

In response to infection with SARS-CoV-2, most immunocompetent individuals produce antibodies against different viral epitopes [1, 2]. Not all these antibodies neutralize the virus, e.g., those directed against the viral nucleocapsid (NC) [3]. Nevertheless, anti-NC antibodies can be used as reliable markers for previous infections with SARS-CoV-2 [4]. Since those antibodies are not formed after vaccination with mRNA-, vector- or peptide vaccines based on spike protein, anti-NC antibodies can be employed to detect natural infections in vaccinated individuals [4, 5]. Even after vaccination with the inactivated virus (e.g., CoronaVac), only part of the vaccinees develop anti-NC antibodies [5, 6]. Therefore, the measurement of these antibodies is particularly relevant for epidemiological studies in vaccinated cohorts.

For this purpose, biobanks typically store samples frozen at <70 °C for the long term. When thawed for planned analyses, they are often kept at 2–10 °C for several days until studies are completed. Some analytes might be sensitive to specific storage temperatures, freeze/thaw cycles, or undergo degradation even at ultra-low temperatures [7, 8]. Moreover, sublimation due to improper storage or incomplete sealing can lead to an unwanted concentration of specific analytes [9]. Also, the freezing and thawing process may change epitopes of analytes or antigen-binding sites of antibodies and can, therefore, unintentionally affect the sensitivity of applied tests [10].

According to international standards, laboratory assays must be appropriately validated before they are used in routine diagnostics [9, 11]. The same quality criteria are necessary for generating reproducible research data. Validation experiments should cover the entire analytical process, including preanalytical procedures, which are known to be the primary source of inaccurate results [12]. This might be especially true for samples stored for several months or years before being analyzed.

We, therefore, aimed to assess the impact of different storage conditions relevant to routine biobanking on anti-NC antibodies detected by the Roche SARS-CoV-2 (Roche, Rotkreuz, Switzerland) electrochemiluminescence assay (ECLIA).

Materials and methods

Study design and population

This multicentric retrospective observational study includes samples from both the Biobank of the Medical University of Vienna (MedUni Wien Biobank) [13] and the Medical University of Graz (Biobank Graz) [14]. Inclusion criteria were a documented SARS-CoV-2 infection >14 days before blood withdrawal or seropositivity for anti-nucleocapsid antibodies and written informed consent to donate blood to either of the biobanks. Age <18 years was defined as an exclusion criterion. The study conforms to the Declaration of Helsinki and was reviewed and approved by the Ethics Committees of the Medical University of Vienna (No. 2257/2020) and the Medical University of Graz (No. 1663/2020).

This study consists of two arms. First, we simulated the typical short-term storage of samples during a recruitment phase (at <−70 °C for ∼3 months) followed by a sample analysis phase (14 days of interim storage at 2–10 °C). Therefore, n=111 samples from vaccinated individuals with confirmed previous SARS-CoV-2 infection were used (MedUni Wien Biobank).

Second, a total of n=257 samples from both biobanks, stored for 443 (409–468) days at <−70 °C, were used to evaluate the long-term preanalytical effects. Samples from the COVID-19 Convalescent Cohort of the Biobank Graz were described previously [15]. A flowchart of the study design is shown in Figure 1.

Figure 1: 
Study flow chart. (A) Evaluation of short-term effects, (B) evaluation of long-term effects.
Figure 1:

Study flow chart. (A) Evaluation of short-term effects, (B) evaluation of long-term effects.

Antibody detection

Both study sites processed samples according to standard operating procedures in ISO 9001:2015 certified environments [13, 14]. Before storage, samples were kept at 2–10 °C and analyzed within 24 h.

The Roche Elecsys® SARS-CoV-2 test detects total anti-nucleocapsid antibodies in blood serum or lithium heparin plasma through an electrochemiluminescence immunoassay (ECLIA). According to the manufacturer, a cut-off index (COI) ≥1.0 is considered positive. Three weeks after infection, the test sensitivity ranges between 89 and 97%, depending on the cohort studied [4, 16, 17]. Although this test has been certified by the manufacturer as a qualitative test, COIs are available as measurement results that can be determined repeatedly with high precision (mean=3.4% between-assay precision acc. to package insert for human sera).

For comparison purposes, SARS-CoV-2 anti-spike antibodies were quantified, again using a Roche ECLIA (Roche Elecsys SARS-CoV-2 S). All tests were performed in medical laboratories with a certified quality management system (ISO 9001:2015 and partly ISO 15189:2012).

Statistical analysis

Continuous data are presented as median (interquartile range), and categorical data as counts (percentages). The agreement between diagnostic test results was evaluated by Passing-Bablok regression and Spearman’s rank correlation. Unless otherwise mentioned, differences between groups or time points are assessed by repeated measurement ANOVAs with Bonferroni-corrected post-hoc t-tests. Degrees of Freedom of repeated measurement ANOVAs were adjusted according to Greenhouse-Geisser. p-Values <0.01 were considered statistically significant. All calculations were performed using MedCalc v20 (MedCalc bvba, Ostend, Belgium) or Analyse-it v5.66 (Analyse-it Software, Leeds, UK).

Results

Short-term storage effects on the detection of anti-nucleocapsid antibodies

One hundred 11 serum samples from individuals with confirmed SARS-CoV-2 infection and SARS-COV-2 vaccination were analyzed for anti-NC antibody levels before and after storage for a median of 84 (58–98) days at <−70 °C. Subsequently, samples were kept at 2–10 °C for 14 days before finally being analyzed again. Anti-NC antibodies were compared between time points by ANOVA for repeated measurements (F=3.94, df1=1.09, df2=119.91, p=0.046).

After ∼3 months at <−70 °C, anti-NC antibody levels decreased slightly but not statistically significantly from 37.2 ± 5.5 COI to 34.7 ± 4.6 COI (−2.4 ± 1.2 COI, p=0.119). After another two weeks at 2–10 °C, values returned to baseline (37.3 ± 4.1, pvs baseline≥0.999, pvs −70 °C<0.0001). All deviations were within the limits set by the RCV (reference change value) which would explain a variability of 9.4% or ±3.5 COI due to analytical uncertainty. The corresponding Passing-Bablok regressions and Bland-Altmann Plots are shown in Figure 2A, B.

Figure 2: 
Passing-Bablok regression lines (left) and Bland-Altman plots (right) of anti-NC antibodies after short-term storage at <−70 °C (A) and 2–10 °C (B), as well as after long-term storage at <−70 °C. NC, nucleocapsid; COI, cut-off index.
Figure 2:

Passing-Bablok regression lines (left) and Bland-Altman plots (right) of anti-NC antibodies after short-term storage at <−70 °C (A) and 2–10 °C (B), as well as after long-term storage at <−70 °C. NC, nucleocapsid; COI, cut-off index.

To verify whether the observed pattern was related to preanalytical changes, we additionally measured antibodies against the spike protein. An opposite pattern was seen for anti-spike antibodies (F=6.41, df1=1.13, df2=124.29, p=0.010). The levels increased after storage from initially 6,273.0 ± 673.7 U/mL to 6,902.5 ± 695.3 U/mL (+629.5 ± 64.6, p<0.0001), after another 14 days at 2–10 °C values returned to 6,478.7 ± 681.4 (−423.8 ± 207.3, p=0.130). The difference after storage at <−70 °C exceeded the RCV (8.4%, ±524.1 U/mL) before regression to the mean was again seen after subsequent storage at 2–10 °C.

Long-term storage effects on anti-nucleocapsid antibodies

Two hundred eight samples from Biobank Graz and 49 samples from MedUni Wien Biobank (total n=257) were analyzed before and after storage for a median of 443 (409–468) days at <−70 °C. Median COI levels rose by ∼20% from 18.4 (5.1–79.8) COI to 24.2 (5.6–97.7) COI (p<0.0001), which exceeded the maximum RCV of 9.4%. Passing-Bablok regression revealed a significant proportional systematic error, as post-storage measurements appeared to be 1.19 times higher than pre-storage values (Figure 2C).

Biospecimens stored in Graz and in Vienna both showed a non-significant interaction in an ANOVA with repeated measurements (F=0.07, df1=1, df2=255, p=0.789), indicating a site- and matrix-independent (Vienna/serum, Graz/lithium heparin plasma) increase in anti-NC antibody results (Graz: 10.2 ± 16.1 COI, Vienna: 9.5 ± 16.0 COI).

In the next step, relative changes of anti-NC antibody levels [calculated as (after storage – pre-storage)/(pre-storage)] were correlated with storage time in days at <−70 °C resulting in a Spearman’s ρ of 0.34 (p<0.0001, Figure 3A), suggesting an increase of anti-NC antibody levels with storage duration.

Figure 3: 
Correlation of proportional deviation between baseline- and long-term storage results with storage duration (A) and rank-scaled collection date (B). (C) Passing-Bablok regression line of anti-Spike antibodies after long-term storage and relationship between variability (expressed as the proportional deviation between baseline- and long-term storage results) and storage duration. n.s., not significantly different from 0 (intercept) or 1 (slope). (E) Comparison of proportional changes from baseline and post-storage measurements between different lots of the analysis kit. ***p<0.001, ****p<0.0001.
Figure 3:

Correlation of proportional deviation between baseline- and long-term storage results with storage duration (A) and rank-scaled collection date (B). (C) Passing-Bablok regression line of anti-Spike antibodies after long-term storage and relationship between variability (expressed as the proportional deviation between baseline- and long-term storage results) and storage duration. n.s., not significantly different from 0 (intercept) or 1 (slope). (E) Comparison of proportional changes from baseline and post-storage measurements between different lots of the analysis kit. ***p<0.001, ****p<0.0001.

However, as not all samples were collected simultaneously, we related the time of baseline measurement to the calculated proportional deviation. As seen in Figure 3B, the measured levels fluctuate over time, possibly indicating lot-to-lot variations in the reagents used. Thus, these analytically induced variations could be causally linked to the observed increase in anti-NC antibodies as a function of storage time. So, we calculated the proportional changes between three different lots at baseline (50941000, 51597600, 52091600) and the post-storage results (all measured with lot number 61899000). The results of lot 51597600 differed significantly compared to each of the other two lots (p<0.001, Mann Whitney U, Figure 3E).

Above that, we tested whether long-term storage might also impact other SARS-CoV-2-specific antibodies. We included 58 samples from the MedUni Wien Biobank with known anti-spike antibody concentrations at baseline. Samples were thawed and re-evaluated after a median of 274 (253–294) days. Passing-Bablok regression did not show significant additive or proportional differences (intercept: −0.4 [−1.5 to 3.2], slope 1.017 [0.995–1.040], Figure 3C), nor was a storage-time dependent deviation detected (ρ=−0.123, p=0.356, Figure 3D). This finding further corroborates the hypothesis that the storage-time dependent increase in anti-NC antibody levels may be due to analytical rather than preanalytical variability.

Impact of short- and long-term storage on qualitative interpretation of results

Qualitative classification of the results (values ≥1.0 COI are considered positive) showed a slightly but statistically not significantly increased test sensitivity after short-term storage at <−70 °C (from 91.9 to 92.8%). After additional 14 days at 2–10 °C, sensitivity further increased to 93.7%. Similarly, we observed an increase in sensitivity from 92.6 to 95.3% after long-term storage, but in this case, changes were statistically significant (z=2.65, p=0.008).

Discussion

Precise knowledge of the performance data of the measurement methods used is essential to enhance the reliability of research results. In particular, biobanks should not underestimate the preanalytical phase as a factor influencing the variability of the measured values. In the present study, we demonstrated that anti-NC antibodies exhibit little or no variability when stored at <−70 °C (∼3 months) or 2–10 °C (14 days) for short periods. After long-term storage (∼1.5 years at <−70 °C), relevant deviations from the initial readings were observed. We found no consistent deviations from baseline values exceeding the RCV after short-term storage at <−70 °C or 2–10 °C. This observation is supported by previous results of Kanji et al., reporting good stability of SARS-CoV-2 antibodies for various serological assays. However, the authors stored the samples for less than two weeks and emphasized that studies applying prolonged periods would be necessary [18]. Regarding storage at refrigerator temperatures, Stadlbauer et al. reported stable titers in convalescent plasma for ≥6 weeks at 4 °C for anti-spike protein antibodies determined by ELISA [19].

Numerous studies have addressed the biological changes of anti-NC antibodies after SARS-CoV-2 infection [20], [21], [22], [23]. It was recognized early on that anti-NC antibodies can be affected by a rapid and significant decline, depending in part on the analytical test system used [24]. In contrast, the preanalytical stability of SARS-COV-2 specific anti-NC antibodies has not been adequately investigated.

In the present study, we found a ∼20% rise in anti-NC levels after a median of 443 days. This increase was site-and material independent, occurring at both involved biobanks, in serum and heparin plasma samples. In more detail, antibody levels increased with storage time (ρ=0.34). However, a closer look revealed that this correlation was not linear, and deviations fluctuated dependent on the date of sample collection. Anti-spike antibodies assessed in samples stored for a median of 274 days at the MedUni Wien Biobank did not exhibit any storage-time-dependent increases. So, these results are less indicative of true preanalytical variability than analytical imprecision. This problem is not inherent to SARS-CoV-2 serology; it is instead the main obstacle in the evaluation of long-lasting preanalytical periods. Minor changes in measurement accuracy of a test system accumulate over time and lead to altered sensitivities [9]. In our case, the changes in anti-NC antibody levels were not disadvantageous because the stored samples showed significantly higher sensitivity.

A limitation of the present study is that the Roche SARS-CoV-2 ECLIA is designed as a qualitative test system. Thus, the COIs do not indicate a specific antibody concentration but rather a specific reactivity as a multiple of a value that depends on two calibrators provided by the manufacturer. However, we could previously show that the COI-values correlate well with quantitative U/mL determined by the IVD-CE-labelled Technozym® anti-nucleoprotein ELISA (n=29 post-COVID individuals, Spearman’s ρ=0.78; for performance data of the ELISA see Ref. [25]). In addition, COI are regularly reported as numerical values in the literature and excellent linearity performance has been described for the Roche test [26].

In conclusion, SARS-CoV-2 anti-NC antibodies measured from stored samples by the Roche Elecsys Anti-SARS-CoV-2 assay are very stable at short-term storage at 2–10 °C and <−70 °C. In contrast, the impact of longer storage intervals on antibody results is inconsistent and, according to our data, could slightly increase the positivity rates in samples from COVID-19 convalescent individuals. Of note, it cannot be ruled out that the observed preanalytical variability is due to an underestimated analytical variability caused by lot-to-lot variation. This can be seen as an inherent problem when it comes to quantifying preanalytical long-term variability.


Corresponding author: Priv.-Doz. Mag. DDr. Helmuth Haslacher, BSc BA, Department of Laboratory Medicine, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria, Phone: +43 1 40400 53190, Fax: +43 1 40495 15547, E-mail:
Thomas Perkmann and Helmuth Haslacher contributed equally to this work.

Acknowledgments

We thank all participants for their valuable contributions! This study was performed in cooperation with the MedUni Wien Biobank and Biobank Graz (Cohort 5003_20, COVID-19 Convalescent Cohort), which are participating in the Austrian biobanking consortium BBMRI.at. We also thank Chiara Banfi for her support concerning data management.

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The Department of Laboratory Medicine, Medical University of Vienna, received compensations for advertisement on scientific symposia from Roche and holds a grant for evaluating an in-vitro diagnostic device from Roche.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: The study was reviewed and approved by the ethics committees of the Medical University of Vienna (No. 2257/2020) and the Medical University of Graz (No. 1663/2020).

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Received: 2022-09-05
Accepted: 2022-10-26
Published Online: 2022-11-04

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