SARS-CoV-2 reliably detected in frozen saliva samples stored up to one year.

Viability of saliva samples stored for longer than 28 days has not been reported in the literature. The COVID-19 pandemic has spawned new research evaluating various sample types, thus large biobanks have been started. Residual saliva samples from university student surveillance testing were retested on SalivaDirect and compared with original RT-PCR (cycle threshold values) and quantitative antigen values for each month in storage. We conclude that saliva samples stored at -80°C are still viable in detecting SARS-CoV-2 after 12 months of storage, establishing the validity of these samples for future testing.

Introduction

Saliva samples are utilized in various diagnostic assays, including COVID-19 [1-4]. During the COVID-19 pandemic, large biobanks were started to provide clinical samples for several different studies, including pivotal validation assays needed to obtain regulatory clearance for new diagnostic tests. Clinical samples (i.e., nasopharyngeal, anterior nares and mid turbinate swabs, and saliva) collected from patients with known viral status are used as positive and negative controls in the evaluation of test performance, such as sensitivity and specificity. These samples are collected within a standardized timeframe of symptom onset and are often stored and shipped prior to use in the evaluation of a new diagnostic test under controlled conditions.

However, several factors, such as the longitudinal stability of patient samples, remain uncertain. In this study we focus on human saliva as a frequently utilized sample type for the evaluation of emerging COVID-19 diagnostic tests.

The results of sample testing are closely evaluated by regulators as part of the evaluation process for determining if a new test is safe for public use. In the U.S., these data are reviewed by the FDA prior to awarding an Emergency Use Authorization or other approval for public utilization. However, it is currently unknown if sample quality, defined as the reliability of a previously positive sample to remain positive after storage, is affected by storage time. The goal of this study is therefore to evaluate the longitudinal stability of saliva samples collected from patients with SARS-CoV-2 in hopes of determining if storage time influences the quality of the collected sample.

Methods

Sample collection and analysis

Deidentified residual samples were originally collected from Emory University faculty, staff, and students (asymptomatic surveillance testing) beginning in November of 2020. This study was in compliance with all research guidelines and due to the nature of residual samples did not require IRB submission. Specimens were collected using the SalivaDirect unsupervised collection kit (Yale School of Public Health, New Haven, CT, USA) [5, 6], including a short straw Salimetrics Saliva Collection Aid,(Salimetrics, LLC, Carlsbad, CA, USA, catalog #5016.02) and a sterile 2 mL plastic tube containing 3 ceramic beads. For ease of pipetting, samples were homogenized at 4.5 m/s for 5 seconds using the Omni International Bead Ruptor Elite (Omni International, owned by Perkin Elmer, Kennesaw, GA, USA). Specimens were screened for nucleocapsid antigen via Quanterix HD-X using the SARS-CoV-2 N Protein Advantage assay (Quanterix Corporation, Billerica, MA, USA). Saliva residuals were stored at 4°C during Quanterix antigen screening. Samples resulting positive for antigen (cutoff >/ = 3.00pg/mL) were then reflexed to confirmatory PCR. Saliva samples were tested according to the SalivaDirect dual-plexed RT-qPCR protocol. This testing was performed on the QuantStudio platform (ThermoFisher Scientific, Waltham, MA, USA) [7], using reagents and materials qualified for the SalivaDirect procedure. PCR+ specimens were reported, stored at -80°C, then archived using OpenSpecimen software (Krishnagi LLC, St. Louis, MO, USA). When retesting sample residuals for this study, the same protocols were repeated. All samples went through a single freeze-thaw cycle with completion of re-testing in November 2021.

Sample selection

We selected 10 random samples from each month, December 2020 to October 2021. If a month had less than 10 samples available, then all samples were used. If a month had more than 10 samples available, we selected an additional 4–5 random samples to be used if any of the original chosen 10 could not be re-tested. There was one case where the original sample selected nor any alternate was available due to lack of volume in the residual sample. Some months did not have any positive samples due to most students living off campus at the time for either the entire month or part of the month (i.e., May and June 2021). In some cases, the residual amount was only enough for PCR retesting and antigen testing was not completed. All samples were re-tested on the same day (11/18/21) and therefore we are evaluating the viability from one month old up to 12 months old.

Statistical analysis

Participants who had an “undetermined” N1 cycle threshold (Ct) test result due to having a Ct above a detectable threshold were considered to have an N1 Ct of 40, the detectable threshold, for the main analysis. Likewise, participants with an antigen concentration below the detectable limit were assigned an antigen concentration of 0.098 pg/mL, directly below the limit of detection, for the main analysis. Participants with other non-numerical results were excluded from the main analysis. Participants who were given an imputed Ct value of 40 and/or an imputed antigen concentration of 0.098 pg/mL for the main analysis were removed for subsequent sensitivity analyses.

The test and re-test N1 Ct values and antigen concentrations were compared over the entire study period and by month. To gauge the differences between the test and re-test values, the average absolute difference (re-test minus test) and percent change (re-test minus test divided by test) were calculated. A coefficient of variation for test and re-test values were calculated for each month to increase comparability between samples. Pearson correlation was also measured to determine the correlation between test values. Intraclass correlations (ICC) were calculated to determine the reliability between results. An ICC close to one represents high reliability while an ICC close to zero represents low reliability and indicates freezing degrades the samples and distorts true N1 Ct values and/or antigen concentrations. All analyses we re-performed in sensitivity analyses excluding imputed observations. Data management and correlation measures were performed in SAS 9.4 (Cary, NC). Intraclass correlation was calculated with SPSS version 28 (IBM, Armonk, NY). Graphs were created in R v4.1.3 (Vienna, Austria).

Results

A total of 87 de-identified Emory-affiliated participants were included in study analysis.

Overall, the mean re-test N1 Ct decreased from the test value but maintained high correlation and reliability in the main analysis (Mean Ct value from original test 95% CI 27.7 [26.6, 28.8]; mean re-test Ct value 95% CI 26.9 [25.6, 28.2]; -2.9% change; Pearson correlation 95% CI 0.92 [0.87, 0.94]; Intraclass Correlation (ICC) 95% CI 0.90 [0.84, 0.94]) (Table 1). In a sensitivity analysis including only participants with complete N1 Ct data, the correlation and reliability decreased to moderate values (Mean Ct value from original test 26.7; mean re-test Ct value 25.6; -4.1% change; Pearson correlation 95% CI 0.89 [0.84, 0.93]; ICC 95% CI 0.87 [0.72, 0.93]) (S1 Table). As shown in Fig 1, most thawed specimens maintained a similar Ct to that seen in the original sample. Eight out of nine months demonstrated high correlation and reliability (0.75–0.90), with six of those months displaying excellent reliability (>0.90), indicating that saliva samples can maintain stability even with several months of storage at -80 (Fig 2). January, the second oldest samples, displayed low correlation and reliability. This same trend was observed in the sensitivity analysis since no January observations were removed in the sensitivity analysis (Mean Ct value from original test 28.2; mean re-test Ct value 26.3; -6.7% change; Pearson correlation 95% CI 0.42 [-0.43, 0.86]; ICC 95% CI 0.37 [-0.25, 0.82]). Through visual assessment, ICC appears to remain relatively stable across the year, except for January, indicating that ICC does not decrease with increasing time and that swabs can maintain the same level of stability with increasing time.

Table 1

Test and re-test Ct value differences by month.

Month	N	Mean Test N1 CT (95% CI)	Mean Re-test N1 CT (95% CI)	Absolute Difference (95% CI)	Test Coefficient of Variation	Re-test Coefficient of Variation	Percent Change	Pearson Correlation (95% CI)	Intraclass Correlation (95% CI)
Overall	87	27.7 (26.6, 28.8)	26.9 (25.6, 28.2)	-0.8 (-1.3, -0.3)	19.2	22.5	-2.9%	0.92 (0.87, 0.94)	0.90 (0.84, 0.94)
December ‘20	10	30.8 (26.7, 34.8)	29.5 (24.9, 34.2)	-1.3 (-3.4, 0.9)	18.5	22.1	-4.2%	0.89 (0.56, 0.97)	0.87 (0.59, 0.97)
January ‘21	8	28.2 (25.4, 30.9)	26.3 (24.1, 28.5)	-1.8 (-4.5, 0.9)	11.6	10.1	-6.7%	0.42 (-0.43, 0.86)	0.37 (-0.25, 0.82)
February ‘21	10	27.9 (23.7, 32.2)	27.9 (22.6, 33.3)	0.0 (-2.6, 2.5)	21.3	26.8	0.0%	0.88 (0.54, 0.97)	0.87 (0.57, 0.97)
March ‘21	10	29.0 (25.9, 32.1)	28.4 (24.7, 32.1)	-0.6 (-1.8, 0.6)	14.8	18.0	-2.1%	0.95 (0.80, 0.99)	0.94 (0.79, 0.98)
April ‘21	10	27.8 (24.7, 30.9)	27.3 (23.3, 31.2)	-0.5 (-1.9, 0.9)	15.7	20.2	-1.8%	0.95 (0.76, 0.99)	0.92 (0.74, 0.98)
July ‘21	9	26.3 (22.7, 30.0)	25.5 (21.1, 29.8)	-0.8 (-2.5, 0.7)	18.1	22.2	-3.0%	0.93 (0.67, 0.98)	0.91 (0.68, 0.98)
August ‘21	10	25.7 (21.2, 30.2)	25.1 (20.5, 29.6)	-0.6 (-2.3, 1.1)	24.5	25.5	-2.3%	0.93 (0.69, 0.98)	0.93 (0.76, 0.98)
September ‘21	10	25.0 (20.9, 29.0)	24.5 (19.9, 29.1)	-0.5 (-1.9, 1.1)	22.7	26.3	-2.0%	0.95 (0.77, 0.99)	0.94 (0.80, 0.99)
October ‘21	10	28.5 (24.2, 32.9)	27.3 (22.0, 32.6)	-1.2 (-2.5, 0.1)	21.2	27.1	-4.2%	0.98 (0.93, 0.996)	0.95 (0.78, 0.99)

Fig 1

Plot of original and thawed specimen Ct values with lines connecting observations from the same individual.

Panel A includes all participants involved in the main analysis while Panel B shows only those individuals included in the sensitivity analysis by excluding those with a Ct above 40. Most samples maintained a similar re-thaw Ct to that seen in the original sample.

Fig 2

Test and re-test Ct values vary over time but remain highly correlated, except for January.

A) The mean Ct values were highest in December 2020 and then decreased over the next 8 months before rising again in September 2021. B) The coefficient of variation across the study period stayed consistently below 30 and were similar within each month. C) The test and re-test Ct values are strongly correlated (Pearson correlation > 0.70) and demonstrate good reliability (Intraclass correlation > 0.75) across the entire study period except for January, indicating that frozen saliva swabs can remain reliable over long periods of time.

Antigen concentrations displayed variable correlations and reliability with no clear trend over time (Mean antigen concentration from original test 95% CI 333.3 [-42.7, 709.3]; mean re-test antigen concentration 95% CI 178.9 [88.0, 269.8]; -43.3% change; Pearson correlation 95% CI 0.80 [0.68, 0.88]; Intraclass correlation (ICC) 95% CI 0.37 [0.11, 0.58]) (Table 2). It should be noted that the mean concentrations, although all considered positive, changed widely from month to month which could explain the lack of a clear trend. Sensitivity analyses excluding observations that were below the limit of detection showed similar results (Mean antigen concentration from original test 95% CI 352.6 [-45.5, 750.8]; mean re-test antigen concentration 95% CI 189.5 [93.9, 285.1]; -46.3% change; Pearson correlation 95% CI 0.81 [0.68, 0.88]; Intraclass correlation (ICC) 95% CI 0.37 [0.10, 0.58]) (S2 Table). While N1 Ct values appear to remain stable over long periods of being frozen, antigen concentrations seem to lack that same reliability. However, test and re-test antigen concentrations maintain a positive correlation throughout time and at some points display moderate agreement.

Table 2

Test and re-test antigen concentration differences by month.

Month	N	Mean Test Antigen Concentration (95% CI)	Mean Re-test Antigen Concentration (95% CI)	Absolute Difference (95% CI)	Test Coefficient of Variation	Re-test Coefficient of Variation	Percent Change	Pearson Correlation (95% CI)	Intraclass Correlation (95% CI)
Overall	54	333.3 (-42.7, 709.3)	178.9 (88.0, 269.8)	-154.4 (-462.0, 153.2)	413.3	186.2	-43.3%	0.80 (0.68, 0.88)	0.37 (0.11, 0.58)
December ‘20	8	27.4 (-4.9, 59.7)	59.1 (-15.9, 134.2)	31.7 (-12.7, 76.2)	141.2	151.8	115.7%	0.97 (0.81, 0.99)	0.66 (0.07, 0.92)
January ‘21	7	1726.8 (-1648.7, 5102.4)	555.3 (-28.0, 1138.6)	-1171.5 (-4022.6, 1679.6)	146.6	94.7	-67.8%	0.92 (0.47, 0.99)	0.31 (-0.47, 0.83)
February ‘21	9	244.2 (-30.9, 519.3)	151.3 (41.2, 261.4)	-92.9 (-286.3, 100.4)	135.7	200.1	-38.0%	0.83 (0.33, 0.96)	0.57 (-0.05, 0.88)
March ‘21	8	32.3 (-4.3, 68.8)	45.0 (-30.3, 120.3)	12.7 (-66.4, 91.9)	135.7	200.1	39.3%	0.13 (-0.64, 0.76)	0.12 (-0.73, 0.74)
April ‘21	9	53.6 (10.5, 96.8)	47.2 (15.7, 78.7)	-6.4 (-39.4, 26.5)	104.7	86.8	-11.9%	0.65 (-0.06, 0.91)	0.64 (-0.01, 0.91)
July ‘21	5	102.6 (-44.4, 249.5)	280.5 (-207.0, 768.0)	177.9 (-191.4, 547.2)	115.4	140.0	173.4%	0.86 (-0.21, 0.99)	0.44 (-0.37, 0.92)
August ‘21	7	318.3 (-365.4, 1001.9)	236.3 (-157.9, 630.5)	-82.0 (-403.1, 239.1)	232.3	180.4	-25.8%	0.96 (0.74, 0.99)	0.85 (0.37, 0.97)
October ‘21	1	12.0 (--)	97.0 (--)	85 (--)	--	--	708.3%	--	--

NOTE: Because there was 1 observation in October ‘21, it was not possible to calculate certain values which is denoted by --.

Discussion

This study is the first to examine the validity of saliva samples after long term storage for detection of SARS-CoV-2. Positivity remained stable up to 12 months at -80°C. While nasopharyngeal samples are the gold standard, saliva has become a more prominent sample type for its ease of collection and storage possibilities. While there is not an approved lateral flow assay for saliva currently in the US, this is an active area of research, and several are available globally.

Most studies of saliva stability for diagnostic test validation have examined the stability of cold chain operations from time of collection to time of analysis, therefore using one week to one month time frames. For comparison, Perchetti et.al. studied the stability of nasopharyngeal samples transported in phosphate-buffered saline at various temperatures over 28 days. All samples remained stable at -80°C, while concentrations varied more with lower temperatures (i.e., room temperature, 4°C, and -20°C) [8]. Ahannach et.al. and Alfaro-Núñez et.al. both determined viability of saliva swab samples, dipped in a collected saliva or inoculated from an oropharyngeal sample, respectively [9, 10]. Ahannach et.al. stored samples at -4°C for 3 weeks, then for 3 days at either room temperature, -20°C, or -80°C before DNA extraction for microbiome analysis. Taxonomic composition did not differ between storage temperature [9]. Alfaro-Núñez et.al. tested saliva samples kept at room temperature, 4°C and -20°C for SARS-CoV-2 at 25 days from collection. Ct values were more stable within 9 days and out to 25 days at -20°C. In summary, lower temperatures -20°C and -80°C increase stability over time and in our study, -80°C storage was able to guarantee positivity at 12 months post collection. Ott et al focused on nonsupplemented saliva samples at -80°C, ~19°C, and 30°C for anywhere between 3 and 92 days and found all saliva samples remained stable [11]. Here we studied only -80°C storage of nonsupplemented saliva, as this is our standard protocol for all biobanked samples.

Strengths and weaknesses

The strengths of this study include the full year time period. Previous studies only include a few months after collection where we investigate a full year. The limitations of this study include the small sample size at each month. Since these were deidentified residuals we were limited in times where positivity rates were low. In the case of January, we feel this is a statistical issue of small sample size and not a sample handling issue. All documentation for those samples show that the handling of the January samples were correct and the same as the other months. However, since those lab technicians are no longer in the lab, we can only rely on documentation. From a statistical standpoint, January has the smallest number of samples and therefore less precision than other months. Intraclass correlation is a ratio of the variance of interest to the total variance so when there is more variance between the different participant samples due to a lower sample size than between the test and re-test samples, then the ICC is lower. However, one experiment out of nine could be a reflection of noise. Overall results where all months were combined, which allowed us to decrease the statistical noise, showed high reliability and should be given more emphasis than the smallest individual experiment.

Conclusion

The implication of this research enables COVID-19 researchers and others in the microbiology and virology fields to utilize biobanked saliva samples up to one year for detection of SARS-CoV-2 and possibly other viruses, although further research is needed.

Deidentified dataset.

(PDF)

Click here for additional data file.

Test and re-test Ct value differences by month from samples with complete data.

(DOCX)

Click here for additional data file.

Test and re-test antigen concentration differences by month excluding observations that were below the limit of detection.

(DOCX)

Click here for additional data file.

20 May 2022

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Reviewer #1: This is an interesting paper which presents some criticisms that should be fixed before its eventual publication

Major criticisms

No data are clearly presented regarding the analytical coefficient of variation of the assay used. Therefore, the eventual decrease after storage cannot be completely evaluated. This issue should be clarified

The figure should be improved as some variations should be better specified according to the previous criticism

Introduction:

the initial sentence seems inappropriate. The assay used is not a POCT and therefore, the real need is to develop accurate laboratory tests, not only POCT

References to be added, if possible:

a) Basso D, Aita A, Padoan A, Cosma C, Navaglia F, Moz S, Contran N, Zambon CF, Maria Cattelan A, Plebani M. Salivary SARS-CoV-2 antigen rapid detection: A prospective cohort study. Clin Chim Acta. 2021 Jun;517:54-59. doi: 10.1016/j.cca.2021.02.014.

b) Basso D, Aita A, Navaglia F, Mason P, Moz S, Pinato A, Melloni B, Iannelli L, Padoan A, Cosma C, Moretto A, Scuttari A, Mapelli D, Rizzuto R, Plebani M. The University of Padua salivary-based SARS-CoV-2 surveillance program minimized viral transmission during the second and third pandemic wave. BMC Med. 2022 Feb 23;20(1):96. doi: 10.1186/s12916-022-02297-1.

Reviewer #2: Abstract, line 65 – I would update that viability has not been reported on, rather than not studied as it is quite possible that it has been studied on in a number of settings but not specifically reported on.

Line 75 – I feel this opening sentence is not well aligned with the overall theme/message of the paper. The investigations in this paper do not involve POC technologies and apply to diagnostic development broader than just POC. I suggest that this introduction be reframed to better introduce the work and message in the paper.

Line 105 – please cite the paper on unsupervised collection devices mentioned here (https://doi.org/10.1186/s12879-022-07285-7)

Line 112 – please cite the paper, EUA or protocols.io on SalivaDirect for reference to this method (or more the#5 citation to the first mention of SalivaDirect on line 112 rather than after the PCR instrument).

Line 164/165 – remove gap between “- 6.7%”

Being a dualplex qPCR, it would be interesting for the authors to also report results for RP over time and how this compares to SARS-CoV-2 detection.

The authors are missing perhaps the earliest work on stability of unsupplemented raw saliva and SARS-CoV-2 detection and are likely more relevant than those currently included in the discussion: doi: 10.3201/eid2704.204199

The citation recommended for line 105 also reports on stability of SARS-CoV-2 RNA when cycled through various temperatures, and demonstrating that cold chain transport is not required.

The figures would be more informative, if in addition to the averages depicted, if the results for each pair could also be depicted. This would allow the reader to more robustly analyses how the pairs performed.

The authors fail to reflect on some of the large changes in Ct values between some of the pairs. Were re-tests double checked? Could anything different have happened during that time (primers, MMX)? Could any samples have not been tested properly the first time? Are any discrepancies more consistent per month perhaps further indicating a slight difference in that first test month?

Line 2 of the supplementary table shows an initial result of 0 – that doesn’t seem to be accurate. It could be helpful to have table either by month or by initial Ct.

Reviewer #3: The authors evaluated the reliability of the detection of SARS-CoV-2 RNA and antigen in frozen saliva samples stored for up to one year. The stability of saliva for the detection of SARS-CoV-2 RNA has been intensively investigated by researchers; however, the methods of preparation, preservation, and examination differed among the laboratories and high-quality investigations are still desired. Unfortunately, the current studies only showed the correlation between the first and second evaluations in a small number of samples, mainly in asymptomatic individuals with a single PCR assay and antigen testing.

Useful information as scientific data for universalization

(1) Sufficient number of samples for evaluation

(2) Stratified data

1) High viral load samples, moderate viral load samples, and low viral load samples

2) Conditions of preservation (4, -20, -80)

3) Data of several molecular assays, including commonly available assays

4) Difference of variants

Overall, the current research is insufficient to use as scientific data. Also, the quality of manuscript is low for an original article.

Minor point

CT ---> Ct

Line 112: Yale’s SalivaDirect dual-plexed RT-qPCR protocol: please add the reference or link

Line 115: -80C -�  -80ºC

Reviewer #4: Enough information is presented (either in the paper or in cited references) to enable other investigators to replicate the work.

The presentation of the results could be improved in several ways, most notably by placing the numerical comparisons in a table, rather than presenting them as text.

The authors have drawn some strange conclusions based on the Ct values for the assays. IN comparing mean Ct values over time, they have not presented confidence intervals for the means, and have made statements about changes which seem likely to me to be “noise.” Furthermore, they seem to suggest that lower Ct values represent lower reliability, which isn’t true at all. They state that “January, the second oldest samples, displayed low correlation and reliability.” While the figure supports this conclusion, the authors provide no explanation for this odd behavior (error in assay performance? Specimen mishandling?).

The Figure could be significantly improved. There is no justification for the lines connecting the point estimates. Each point estimate should be accompanied by confidence intervals.

The authors have described antigen concentration assessment, and presented some verbiage in the results section, without presenting any sort of formal analysis. I suppose the comments are supported by data in the supplementary Excel spreadsheet, but I would be much happier if there were to be a more formal presentation of what the data say.

Reviewer #5: The paper is concise and straightforward, the conclusions are valid. The only part that is missing is alignment with MIQE guidelines for quantitative real-time PCR (DOI: 10.1373/clinchem.2008.112797). Understandably, the authors used commercial kits. However, if the information on validation of the kits is available, it is worth including it into the manuscript.

Another comment, the mean values in Figure 1 are given without error bars and n values for the number of samples. From supplementary data it is hard to understand how many samples were available for retesting for each month.The significance of the difference in the January sample should be reported by p-value.

Reviewer #6: The manuscript submitted by Dr. Frediani and entitled “SARS-CoV-2 reliably detected in frozen saliva samples stored up to one year” evaluates the long-term stability of frozen saliva specimens for the detection of SARS-CoV-2. In this work 87 specimens that were previously positive for SARS-CoV-2 and frozen and -80C were retested. The results of the specimens were then compared to the initial run to look at specimen stability. In general they found stable specimens for PCR with average decreases after the freeze thaw. The results of the study are useful as saliva for respiratory diagnostics is becoming more common due to the pandemic and understanding the matrix’s long-term stability will be valuable for laboratories and industry to validate novel assays when the viral target is low. However, in its current state there are some clarifications needed and re-writing necessary for publication. Here are my suggestions:

Major Comments

Ln132: Why would you create a CT value when no value was obtained. These should just not be run on statistical analysis since giving them a point value. When observing your data in figure 1 and in the averages, the freeze thaw seemed to improve detection based on the lower CT. Would this be more pronounced if the negative specimens were removed. It is also important to discuss these missed samples and the CT from the initial test. Were they near the LoD.

From the data trend, it almost appears that a freeze thaw improves the sensitivity of the assay, which has been a discussion in the field and possible concern for the FDA in evaluating retrospecitive specimens. It would be beneficial if a small subset of new specimens could be frozen and tested after 24 hours of freeze thaw to determine if

Ln124 and throughout: I would suggest reviewing the manuscript for conversational and indirect language. As an example, ln 124 states” the original chosen 10 could not be re-tested for some reason”. I would remove “for some reason” and add a sentence of the numbers that were not tested and reasons. This continues into more of the methods, which make it a bit unclear of how the specimens were tested. For example, n the sample selection when 10 were taken from December and 10 from January are these tested at the same time so one batch is X-months frozen and the January batch is X-1 months old or were they all stored for 12 months prior to testing?

Minor comments

Ln104: What is meant by compliance (i.e. was this approval via the institutions IRB)?

I would consider changing the term re-test to thawed specimens or something similar. When I read re-test I am thinking of a possible repeat for a test that was invalid.

Link figures in text when indicated and presenting data.

As there is only 87 data points I think it would be interesting to see the N1 CT values as a dots where the samples are on X axis CT on Y and 2 points for each sample so we can see the spread of CT values for individual samples and not as an average.

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5 Jul 2022

Reviewer Comments Author comments

Editor comments Check style requirements (file naming) Completed

Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information. This has been clarified in the text, due to the nature of these de-identified archived samples no IRB was required.

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“This work was supported by the National Institute of Biomedical Imaging and Bioengineering RADx program, [Grant Number: 54 EB027690 02S1] WL,https://www.nibib.nih.gov/, and the National Center for Advancing Translational Sciences [Grant Number: UL1 TR002378](PI not an author),https://ncats.nih.gov/”

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” This work was supported by the National Institute of Biomedical Imaging and Bioengineering RADx program, [Grant Number: 54 EB027690 02S1] WL,https://www.nibib.nih.gov/, and the National Center for Advancing Translational Sciences [Grant Number: UL1 TR002378](PI not an author),https://ncats.nih.gov/

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Reviewer 1 No data are clearly presented regarding the analytical coefficient of variation of the assay used. Therefore, the eventual decrease after storage cannot be completely evaluated. This issue should be clarified

The figure should be improved as some variations should be better specified according to the previous criticism We have substantially updated the figure to address concerns from all reviewers. In this updated figure, you will find that we have added a panel for the coefficient of variation for both the original and re-test values for each month. The coefficient of variation was consistently below 30 for all months and was similar for the original and re-test values within a month.

Introduction:

the initial sentence seems inappropriate. The assay used is not a POCT and therefore, the real need is to develop accurate laboratory tests, not only POCT Reworded to reflect the objective of the paper.

References to be added, if possible:

a) Basso D, Aita A, Padoan A, Cosma C, Navaglia F, Moz S, Contran N, Zambon CF, Maria Cattelan A, Plebani M. Salivary SARS-CoV-2 antigen rapid detection: A prospective cohort study. Clin Chim Acta. 2021 Jun;517:54-59. doi: 10.1016/j.cca.2021.02.014.

b) Basso D, Aita A, Navaglia F, Mason P, Moz S, Pinato A, Melloni B, Iannelli L, Padoan A, Cosma C, Moretto A, Scuttari A, Mapelli D, Rizzuto R, Plebani M. The University of Padua salivary-based SARS-CoV-2 surveillance program minimized viral transmission during the second and third pandemic wave. BMC Med. 2022 Feb 23;20(1):96. doi: 10.1186/s12916-022-02297-1.

These have been included in the introduction.

Reviewer 2 Abstract, line 65 – I would update that viability has not been reported on, rather than not studied as it is quite possible that it has been studied on in a number of settings but not specifically reported on.

This has been changed.

Line 75 – I feel this opening sentence is not well aligned with the overall theme/message of the paper. The investigations in this paper do not involve POC technologies and apply to diagnostic development broader than just POC. I suggest that this introduction be reframed to better introduce the work and message in the paper.

Reworded to reflect the objective of the paper.

Line 105 – please cite the paper on unsupervised collection devices mentioned here (https://doi.org/10.1186/s12879-022-07285-7)

Added

Line 112 – please cite the paper, EUA or protocols.io on SalivaDirect for reference to this method (or more the#5 citation to the first mention of SalivaDirect on line 112 rather than after the PCR instrument). Added

Line 164/165 – remove gap between “- 6.7%” There isn’t a gap between the – and 6.7%.

Being a dualplex qPCR, it would be interesting for the authors to also report results for RP over time and how this compares to SARS-CoV-2 detection. For the SalivaDirect protocol, the RP signal is only used to verify that amplification occurred before reporting a negative result. While the authors agree that the RP trends may be interesting, the analysis required to collect and analyze the internal control values would be substantial and the inferences to be made only tangential to our exploration of SARS-CoV-2 sample stability. We feel that the N2 amplification data supersedes the RP result trends.

The authors are missing perhaps the earliest work on stability of unsupplemented raw saliva and SARS-CoV-2 detection and are likely more relevant than those currently included in the discussion: doi: 10.3201/eid2704.204199 We have added this to the discussion.

The citation recommended for line 105 also reports on stability of SARS-CoV-2 RNA when cycled through various temperatures, and demonstrating that cold chain transport is not required. We agree.

The figures would be more informative, if in addition to the averages depicted, if the results for each pair could also be depicted. This would allow the reader to more robustly analyses how the pairs performed.

Thank you for the suggestion. We have added a before-after plot to show the original and re-test Ct value for each individual. Panel A includes individuals who had an “undetermined” re-test value that was imputed as 40 for the purposes of analyses while panel B removes these individuals entirely.

The authors fail to reflect on some of the large changes in Ct values between some of the pairs. Were re-tests double checked? Could anything different have happened during that time (primers, MMX)? Could any samples have not been tested properly the first time? Are any discrepancies more consistent per month perhaps further indicating a slight difference in that first test month?

The laboratory team strives to maintain quality in both sample handling and data integrity. A large change in Ct values could be defined as +/- 3 Ct’s. The great majority of our Ct deltas were within this threshold. A Ct value difference of 3 could be caused by variance in pipetting, heterogeneity of saliva, freeze/thaw cycling, or lot-to-lot variation of kit reagents. Retests were double-checked and reviewed before being reported, mastermix and primer/probe sets were from the same manufacturer, and differences from month-to-month were investigated with no root cause found to bias the data.

Line 2 of the supplementary table shows an initial result of 0 – that doesn’t seem to be accurate. It could be helpful to have table either by month or by initial Ct. We appreciate your diligent checking of our data. The 0 was inaccurate and has been updated to the correct number (27.8). All other entries have also been checked and no other errors were found. We have also updated the data so that the observations are sorted by date.

Reviewer 3 CT ---> Ct Changed

Line 112: Yale’s SalivaDirect dual-plexed RT-qPCR protocol: please add the reference or link Added

Reviewer 4 Line 115: -80C -�  -80ºC Changed

The presentation of the results could be improved in several ways, most notably by placing the numerical comparisons in a table, rather than presenting them as text.

Thank you for the suggestion. We have added several tables summarizing the numerical results.

The authors have drawn some strange conclusions based on the Ct values for the assays. IN comparing mean Ct values over time, they have not presented confidence intervals for the means, and have made statements about changes which seem likely to me to be “noise.” Furthermore, they seem to suggest that lower Ct values represent lower reliability, which isn’t true at all. They state that “January, the second oldest samples, displayed low correlation and reliability.” While the figure supports this conclusion, the authors provide no explanation for this odd behavior (error in assay performance? Specimen mishandling?). We have added 95% confidence intervals to the figures, tables, and texts for better transparency. Our statements regarding reliability were not derived from the raw Ct values but from the intraclass correlation (ICC) analyses that were mentioned in the methods and results section. We considered the test and re-test to act as sort of raters. An ICC allows us to gauge the reliability of two raters, in this case, the test and re-testing periods. Because the only difference between the test and re-test periods should be that the sample underwent being frozen and stored, we assume that a low ICC, which corresponds to low reliability, is attributable to being frozen and stored. It is from this analysis that we made statements regarding reliability.

The Figure could be significantly improved. There is no justification for the lines connecting the point estimates. Each point estimate should be accompanied by confidence intervals. We have added 95% confidence intervals to the means and have removed the lines connecting the points.

The authors have described antigen concentration assessment, and presented some verbiage in the results section, without presenting any sort of formal analysis. I suppose the comments are supported by data in the supplementary Excel spreadsheet, but I would be much happier if there were to be a more formal presentation of what the data say. We have added tables and verbiage to represent the analyses involving antigen concentrations.

Reviewer 5 The paper is concise and straightforward, the conclusions are valid. The only part that is missing is alignment with MIQE guidelines for quantitative real-time PCR (DOI: 10.1373/clinchem.2008.112797). Understandably, the authors used commercial kits. However, if the information on validation of the kits is available, it is worth including it into the manuscript. Added the following citation to the methods section Vogels et al., Med 2, 263–280 March 12, 2021 ª 2020 Elsevier Inc. https://doi.org/10.1016/j.medj.2020.12.010

Another comment, the mean values in Figure 1 are given without error bars and n values for the number of samples. From supplementary data it is hard to understand how many samples were available for retesting for each month. The significance of the difference in the January sample should be reported by p-value. We have added confidence intervals to the means displayed in figure 1 and have added the number of samples (N) for each month on the x-axis for clarity.

We appreciate the utility of hypothesis testing, but the study was designed with the intent to focus on reliability through intraclass correlation analyses. As such, we did not select a sample size appropriate for testing the difference in means and do not feel that assigning a p-value to the difference adds any significant meaning to the report. Keeping in line with the American Statistical Association’s suggestions (cited below), we have added confidence intervals to the calculated means and differences in means which we believe adds more value than p-values.

Citation: Ronald L. Wasserstein & Nicole A. Lazar (2016) The ASA Statement on p-Values: Context, Process, and Purpose, The American Statistician, 70:2, 129-133, DOI: 10.1080/00031305.2016.1154108

Reviewer 6 Ln132: Why would you create a CT value when no value was obtained. These should just not be run on statistical analysis since giving them a point value. See response below

When observing your data in figure 1 and in the averages, the freeze thaw seemed to improve detection based on the lower CT. Would this be more pronounced if the negative specimens were removed. It is also important to discuss these missed samples and the CT from the initial test. Were they near the LoD.

Response to this comment and the one above: When a sample had an “undetermined” Ct test value, it had a Ct above the instrument’s detectable limit which was ~40. Instead of excluding these observations that had a high, albeit unknown, Ct value, we chose to impute these values with the maximum Ct, 40. We recognized the potential bias that can be introduced with this mention which is why we conducted sensitivity analyses excluding these observations, as mentioned in the methods and results. We have altered the methods and results section to make it clearer that all analyses using imputed values were followed by sensitivity analyses where those same observations were removed.

From the data trend, it almost appears that a freeze thaw improves the sensitivity of the assay, which has been a discussion in the field and possible concern for the FDA in evaluating retrospecitive specimens. It would be beneficial if a small subset of new specimens could be frozen and tested after 24 hours of freeze thaw to determine if The authors concur that this would be an important factor when evaluating retrospective specimens. The observations from this study may contribute to later publications of a robust study designed to look specifically at sample stability after multiple short-term freeze/thaws.

Ln124 and throughout: I would suggest reviewing the manuscript for conversational and indirect language. As an example, ln 124 states” the original chosen 10 could not be re-tested for some reason”. I would remove “for some reason” and add a sentence of the numbers that were not tested and reasons. This continues into more of the methods, which make it a bit unclear of how the specimens were tested. For example, n the sample selection when 10 were taken from December and 10 from January are these tested at the same time so one batch is X-months frozen and the January batch is X-1 months old or were they all stored for 12 months prior to testing? Language has been changed throughout. In the instance that a sample could not be re-tested, it was because there was not enough volume leftover to conduct a re-test. We have clarified this in the methods. We used a random sampling scheme when there were more than 10 available samples for any given month to choose the original 10 and 4-5 backup samples so that chances of selection bias were minimized. All samples were re-tested on the same day (11/18/21) with the idea that we could test viability UP to 12 months. We have added a sentence explaining this to the Sample Selection section.

Ln104: What is meant by compliance (i.e. was this approval via the institutions IRB)? This has been reworded, these were residuals from surveillance testing, completely deidentified stored residuals, no IRB required.

I would consider changing the term re-test to thawed specimens or something similar. When I read re-test I am thinking of a possible repeat for a test that was invalid.

We have changed “re-test” to “thawed specimens” in figures 1 and 2.

Link figures in text when indicated and presenting data. Done

As there is only 87 data points I think it would be interesting to see the N1 CT values as a dots where the samples are on X axis CT on Y and 2 points for each sample so we can see the spread of CT values for individual samples and not as an average. Thank you for the suggestion. Per yours and other reviewers’ requests, we have added a before-after plot to show the original and re-test Ct value for each individual. Panel A includes individuals who had an “undetermined” re-test value that was imputed as 40 for the purposes of analyses while panel B removes these individuals entirely.

Submitted filename: Response to Reviewers.docx

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22 Jul 2022

28 Jul 2022

Please see Response to Reviewers document

Submitted filename: Response to Reviewers 072822.docx

Click here for additional data file.

1 Aug 2022

SARS-CoV-2 reliably detected in frozen saliva samples stored up to one year

PONE-D-22-12527R2

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2 Aug 2022

PONE-D-22-12527R2

SARS-CoV-2 reliably detected in frozen saliva samples stored up to one year

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