Article Text

Evaluating the long-term biological stability of cytokine biomarkers in ocular fluid samples
  1. Tina Felfeli1,2,
  2. Jeff Park3,
  3. Bret Nestor4,
  4. Filiberto Altomare1,5,
  5. Amandeep S Rai1,6,
  6. Efrem D Mandelcorn1,7,
  7. David R Chow1,5,
  8. David T Wong1,5
  1. 1Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada
  2. 2Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
  3. 3Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
  4. 4Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, USA
  5. 5Department of Ophthalmology, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
  6. 6Kensington Eye Institute, University of Toronto, Toronto, Ontario, Canada
  7. 7Department of Ophthalmology, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
  1. Correspondence to Dr Tina Felfeli; tina.felfeli{at}mail.utoronto.ca; Dr David T Wong; david.wong{at}unityhealth.to

Abstract

Purpose The quality of biological fluid samples is vital for optimal preanalytical procedures and a requirement for effective translational biomarker research. This study aims to determine the effects of storage duration and freeze-thawing on the levels of various cytokines in the human aqueous humour and vitreous samples.

Methods and analysis Human ocular aqueous humour and vitreous samples were obtained from 25 eyes and stored at −80°C for analysis. All samples were assayed for 27 cytokine biomarker concentrations (pg/mL) using a multiplex assay. Four sample storage durations following sample collection were evaluated (1 week, 3 months, 9 months and 15 months). Additionally, samples underwent up to three freeze-thaw cycles within the study period.

Results Among the 27 cytokine biomarkers, concentrations of four cytokines (Interleukin (IL)−2, IL-10, IL-12 and platelet-derived growth factor-BB) were significantly decreased by storage duration at all time points, as early as 3 months following sample collection (range of 9%–37% decline between 1 week and 15 months, p<0.001). Freeze-thawing of up to three cycles did not significantly impact the cytokine biomarker concentrations in aqueous humour or vitreous. Separability of patient-specific cytokine biomarker profiles in the principal component analysis remained relatively the same over the 15 months of storage duration.

Conclusion The findings from this study suggest that several intraocular cytokine biomarkers in human aqueous humour and vitreous samples may be susceptible to degradation with long-term storage, as early as 3 months after collection. The overall patient-specific cytokine biomarker profiles are more stable than concentrations of individual cytokines. Future studies should focus on developing guidelines for optimal and standardised sample handling methods to ensure correct research findings about intraocular biomarkers are translated into clinical practice.

  • Aqueous humour
  • Inflammation
  • Tears
  • Vitreous

Data availability statement

Data are available on reasonable request. Dara are available on request from the corresponding author.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Cytokines play a crucial role in ocular research, serving as vital indicators for disease understanding and treatment assessment. Inaccurate and unreliable cytokine quantification methods could lead to erroneous research conclusions and clinical decisions.

WHAT THIS STUDY ADDS

  • This study unveils concentration changes in some of the cytokine biomarkers due to storage duration. Sampling type did not offer a significant advantage in mitigating concentration deterioration. Patient-specific cytokine biomarker profiles exhibited remarkable stability over time, indicating their reliability as potential biomarkers.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • These findings underscore the need for standardised protocols for sample handling in ocular cytokine analysis. Optimising sample handling procedures will enhance the accuracy and reliability of cytokine research, providing valuable insights for ocular biomarker studies.

Introduction

Cytokines are low-molecular-weight glycoprotein molecules produced by both immune and non-immune cells that serve as indicators of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention.1 Recently, there has been a growing interest in using cytokines in aqueous humour and vitreous collected via anterior chamber (AC) paracentesis and vitreous sampling, respectively, as surrogate markers to understand disease pathogenesis, monitor disease progression and assess treatment response.2–12 Given the emerging research and clinical practices based on cytokine analysis, it is imperative to ensure that methodologies to measure cytokines are robust. Any conclusions drawn from poor handling of the ocular samples and unreliable method of cytokine quantification could potentially result in misled clinical decisions with negative outcomes.

Cytokines are inherently delicate structures that are thermally labile and are prone to proteolytic degradation over time.13 They are also found in ultra-low levels in fluid samples, which means small variations in handling can have significant impact on quantification.14 Several factors must be considered when handling ocular samples containing cytokines. First, aqueous humour and vitreous samples are rarely analysed immediately following their collection, and they are generally stored long-term at −80°C. de Jager et al previously demonstrated that levels of cytokines in blood samples fluctuate as early as 1 year of storage with most cytokines degrading after 2 years.15 Second, samples may undergo multiple freeze-thaw cycles for analysis as cytokine activity is monitored. Previous studies on cytokines in non-ocular samples have shown that each cytokine responds differently to freeze-thawing.15–17 Overall, most studies reporting on the stability of cytokines have been conducted in non-ocular samples and there is currently no consensus on the collection and handling methods to optimise accurate quantification.

Biological fluid sample quality is a crucial prerequisite for translational biomarker research and identification of optimal preanalytical procedures. An investigation highlighting the significance of preanalytical parameters when measuring cytokines in ocular fluids including the effects of different storage timings on cytokines in the aqueous humour and vitreous samples may inform future efforts to standardise sample handling protocols. Here, we aimed to determine the effects of sample storage duration and freeze-thaw cycles on the levels of various cytokine biomarkers in the human aqueous humour and vitreous samples.

Methods

Subjects

We recruited 25 adult patients (≥18 years old) who underwent cataract surgery, pars plana vitrectomy (PPV) or scleral buckle surgery at Kensington Eye Institute, St. Michael’s Hospital, Toronto, Canada and Toronto Western Hospital, Toronto, Canada. Exclusion criteria included (1) previous vitrectomy of the index eye and (2) dense vitreous haemorrhage at the time of initial assessment for recruitment. Informed consent was obtained for each patient following a detailed explanation of the study purpose and potential risks of participation. For each patient, demographic and clinical data on age, gender, index eye, diagnosis, type of procedure, lens status (phakic or pseudophakic), medications and preoperative visual acuity were obtained from electronic medical records. Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research

Sample collection and storage

Samples of aqueous humour were obtained from the eyes undergoing cataract surgery, PPV and scleral buckle surgery through AC paracentesis. We used a needle on a syringe with the plunger removed and inserted the needle on the nasal limbus to obtain 0.1–0.3 mL of the aqueous humour. Vitreous fluid samples were only obtained from the eyes undergoing PPV. Undiluted vitreous fluid (0.3 mL) was aspirated using the vitrector via one of the standard scleral incisions created for the surgery.

Once an aqueous humour or vitreous sample was obtained, and each sample was immediately aliquoted to multiple sterile 1.5 mL screw cap tubes under laminar air flow conditions. For aqueous humour samples, the aliquots were made into 2–3 tubes depending on the volume of the fluid obtained. The undiluted vitreous samples were aliquoted into four tubes with approximately 0.075 mL available for each analysis. All samples were stored in 4°C for 5 hours following sample collection and then transferred to a –80°C freezer following distribution into aliquot tubes. For evaluation of cytokine stability following storage duration at different time points, aliquots were retrieved and thawed at 1-week, 3-month, 9-month and 15-month time points after collection. For evaluation of cytokine stability following freeze-thaw cycles, each aliquot was thawed and refrozen up to three times for the duration of study period, with the last freeze-thaw cycle taking place at 15 months.

Quantification of cytokine biomarkers

To prepare for cytokine analysis, frozen samples were retrieved from –80°C freezer and thawed. Cytokine levels of all aqueous humour and vitreous samples were measured using the Bioplex Pro-Human Cytokine Grp I Panel 27-Plex 96-well assay kit (Cat# M500KCAF0Y, Bio-Rad, USA). The multiplex bead assay allowed simultaneous measurement of multiple cytokine biomarkers analysed in the study: fibroblast growth factors, eotaxin, granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage CSF (GM-CSF), interferon gamma (IFN-γ), interleukin (IL)-1β, IL-1ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p70), IL-13, IL-15, IL-17A, inducible protein (IP)-10, monocyte chemoattractant protein (MCP)-1, macrophage inflammatory proteins (MIPs)-1α, MIP-1β, platelet-derived growth factor (PDGF)-BB, regulated on activation, normal T cell expressed and presumably secreted (RANTES), tumour necrosis factor alpha (TNF)-α and VEGF. Each assay was performed according to the manufacturer’s instructions. First, aqueous humour and vitreous samples were diluted using the standard diluent buffer in 1:2 and 1:1 concentration, respectively. To each well of a 96-well microplate, 50 µL of fluorescently dyed magnetic microspheres diluted in assay buffer and 50 µL of diluted aqueous humour or vitreous samples, standards or blanks were added. After incubation, the plate was washed and detection antibodies as well as the final detection complex, streptavidin-phycoerythrin conjugate, were added to each well. Addition of each reagent required subsequent intubation and buffer wash. Lastly, the microspheres were resuspended by addition of buffer solution, and the Bio-Plex Manager Software was used to calculate median fluorescence intensity, and concentration of biomarkers (pg/mL) based on a standard curve calibrated for each biomarker. Based on standard protocol, all concentrations were reported as transformations of logarithm with base 10.

Statistical analysis

An analysis of variance (ANOVA) was run to assess the impact of storage time (1 week, 3 months, 9 months and 15 months), sampling type (aqueous humour vs vitreous), and the interaction between storage time and sampling type for each biomarker. Measurements where the relative abundance was more than an order of magnitude greater than other measurements from the equivalent samples were considered to be outliers and were discarded. The corresponding effect size was reported for these significant factors. The effect sizes were calculated as per cent decline since initial concentration. When the sample p value was less than the Bonferroni corrected threshold,18 then the null hypothesis was rejected. The original p value was set at 0.05. The corrected p value for both storage duration and the freeze-thaw analyses was 0.00185 (based on 27 biomarkers).

Samples tested at 1-week, 3-month, 9-month and 15-month duration times were embedded using principal component analysis (PCA) to view the proximity between time points for each sample. It is expected that samples which do not deteriorate beyond usefulness will remain nearby to their sample at all three time points of analysis.

The effect of multiple freeze thaw cycles was tested with eight independent samples. A one-way ANOVA was used to assess the effect of freeze-thaw cycles. One patient’s samples were eliminated due to an outlying value.

All statistical analyses were performed using Python. The Code for the analysis has been made available at github.com/bnestor/ophthalmology_biomarker_freeze.

Results

A total of 15 aqueous humour specimens and 20 vitreous specimens were obtained from 25 eyes of 25 patients. Five patients (20%) were diagnosed with rhegmatogenous retinal detachment, and 21 patients (84%) underwent PPV. Eleven patients (44%) were on antihypertensive agents. Baseline characteristics of the patients are summarised in table 1.

Table 1

Summary of patient baseline characteristics

Among the 27 cytokine biomarkers, 4 were noted to have a significantly different concentration due to storage duration at all time points, including IL-2 (effect size as per cent decline since 1 week: −15.7% at 3 months, −27.2% at 9 months and −13.7% at 15 months, p<0.001), IL-10 (effect size as per cent decline since 1 week: −7.6% at 3 months, −17.2% at 9 months and −9.0% at 15 months, p<0.001), IL-12 (effect size as per cent decline since 1 week: −13.8% at 3 months, −22.6% at 9 months and −12.5% at 15 months, p<0.001), and (PDGF-BB, effect size as per cent decline since 1 week: −30.8% at 3 months, −33.8% at 3 months and −37.6% at 15 months, p<0.001, table 2).

Table 2

Summary statistical analysis for storage duration, sample type and interaction between the two for each of the cytokine analytes

In terms of the between time interval analyses, IL-2 displayed a notable decrease of 13.7% between months 3 and 9, followed by an increase of 2.8% between months 3 and 15, and a substantial increase of 19.1% between months 9 and 15 (online supplemental table 2). IL-10 showed a decline of 10.4% between months 3 and 9, followed by a lesser decline of 1.6% between months 3 and 15. However, a subsequent increase of 9.9% was observed between months 9 and 15. Similarly, IL-12 showed a decrease of 10.2% from months 3 to 9, followed by an increase of 1.1% between months 3 and 15, and a notable rise of 12.6% between months 9 and 15. Conversely, PDGF-BB demonstrated a decrease of 4.3% between months 3 and 9, a larger decrease of 9.9% between months 3 and 15 and a subsequent decrease of 5.9% between months 9 and 15.

Neither sampling type (aqueous humour or vitreous) offered a significant advantage of mitigating sample concentration deterioration with storage duration. The individual cytokine biomarker analyte concentrations at the various time points are outlined in online supplemental figure 1.

The freeze-thaw analysis suggested that based on Bonferroni corrected p values, there was no significant effect of freeze-thaw cycles among the eight independent samples included in this analysis (table 3).

Table 3

Summary statistical analysis for freeze thaw cycles for each of the cytokine analytes

The separability of patient-specific cytokine biomarker profiles remained relatively stable at all storage time points in the PCA (figure 1A). Stationarity between primary principal components at different time points indicates that, despite some biomarkers degrading, the biomarker profile is more similar to itself at earlier times, than it is to other patients. No specific patterns were noted for the principal components at different freeze-thaw cycles across samples (figure 1B).

Figure 1

Principal component analysis of samples across 1-week, 3-month, 9-month and 15- month duration times (A) and various freeze-thaw cycles (B).

Discussion

In this study, we investigated the effects of ocular fluid sample storage duration and freeze-thaw cycles on the levels of cytokine biomarkers. Our findings suggest that concentration of cytokine in several ocular cytokine biomarkers IL-2, IL-10, IL-12 and PDGF-BB are affected by storage duration of up to 15 months when compared with 1-week duration time. For biomarkers that are less resistant to degradation, analysis should be undertaken as early as possible to mitigate the effects of sample degradation. Additionally, the analysis of freeze-thaw analyses did not demonstrate any significant changes in cytokine biomarker concentrations of ocular fluids after up to three freeze-thaw cycles. The PCA showed that patient-specific cytokine biomarker profiles remain in close proximity across the different storage duration times.

The current study revealed noteworthy changes in cytokine levels over different time intervals. Notably, PDGF-BB exhibited a significant decline of approximately 37% from the initial 1-week measurement to the 15-month mark. Similarly, IL-2 and IL-12 demonstrated a substantial reduction of 13% from the 1-week measurement to the 15-month measurement. IL-10 also displayed a considerable drop of 9% between the 1-week measurement and the 15-month measurement. The changes between the main study intervals of 3–9 months, 3–15 months and 9–15 months showed similar patterns with some exceptions where the averaged effect sizes were not negative. This may be due to the fact that although the general trend of decline was noted among individual samples from 1 week to 15 months, the averaged effect sizes in shorter time intervals results in more variability in measured concentrations and a less notable decline. When interpreting the data, consideration should be given to the effect sizes as a range (eg, −13% and −27% decline sample loss from freezing over 0–9 months for IL-2) with additional variability coming from sample-processing. It is crucial to acknowledge that these variations may not be solely attributed to time intervals, as factors such as sample handling and processing can contribute to the observed changes. The findings reflect complex interactions between time, sample processing, and the measured cytokines, emphasising the intricacies involved in drawing meaningful conclusions from the data.

We have previously demonstrated that some variability may be noted in replicate analyses of biomarkers most notably in vitreous samples.19 It has been shown that using multiplex assay kits from different companies may show varying cytokine concentrations.20 21 While comparison of quantification is not ideal between multiplex assay kits from differing companies, trend analysis may still be appropriate by evaluating cytokine trends from serial samples.22 23 Alternatively, in cases where there is variability expected in certain analytes, it may be possible to use analytes as surrogates for one another. For example, as retinal Intercellular Adhesion Molecule-1 (ICAM-1) is induced by VEGF,24 25 an increase in ICAM-1 may be able to be interpreted as an increase in VEGF. One of the major advantages of this study is the use of assays from the same lot number analysed within the same laboratory by the same analyst in order to account for instrumental errors and other confounders. Although assay variability may have been minimised in this study, there are other potential sources of variability in biomarker analyses including storage duration, freeze-thaw cycles, sampling type, instrumental variations and more that should be taken into consideration when interpreting results of inflammatory ocular fluid sample analyses. These findings highlight the dynamic changes in specific cytokine levels over the course of the study.

The only study to date on effects of storage on ocular cytokine biomarkers has demonstrated that aqueous VEGF concentrations are significantly decreased after 21 days of storage in –80°C.26 This contrasts with our findings, which demonstrate that VEGF levels were stable even after 15 months of storage. The effects of long-term storage on cytokine biomarkers have been previously shown in studies involving storage of samples over several years. A study by de Jager et al demonstrated variable changes to the levels of cytokines up to 4 years of storage in –80°C in serum and plasma samples.15 In their study, de Jager et al observed degradation in IL-13, IL-15, IL-17 and CXCL8 within 1 year of storage, with IL-2, IL-4, IL-12 and IL-18 being stable for up to 3 years.15 They also noted that other cytokines, such as IL-1α, IL-1β, IL-5, IL-6 and IL-10 degraded up to 50% or less of baseline values within 2–3 years of storage.15 This is similar to our study findings which showed a significant change in IL-2 and IL-12 by 15 months of storage time. Butterfield et al, also demonstrated significant changes in cytokine concentrations of serum samples after 5 years of storage at –80°C.27 The samples in their study were not previously thawed, and thus suggests the effects of storage duration independent of freeze-thaw.27 They found that among the 10 analytes studied, IL-4 concentrations remained relatively stable, while IL-6, TNFa decreased and IL-8 and MCP-1 increased over time.27 Other studies have found no evidence that cytokines IL2, IL10, IL12, PDGF are sensitive to degradation.28 The degradation patterns are not consistent across different studies and the literature is insufficient for us to draw conclusions regarding the stability of specific biomarkers found in ocular fluids. Comparisons across different studies are limited due to differences in specimens used, the number of participants from which the samples were collected and the disease states of the participants. Before research findings about intraocular biomarkers are translated into clinical practice, results across different studies should be made comparable by developing guidelines or protocols that ensure collection methods and sample handling are standardised.

The literature on the effect of freeze-thaw cycles on the stability of cytokines obtained from ocular samples is limited to date. In serum samples, multiple freeze-thaw cycles have been shown to have limited effect on cytokine levels, increase levels or decrease levels based on the specific cytokine biomarker.16 17 With regard to specific cytokines, it is suggested that IFN-γ is significantly reduced by the third thaw cycle, while a slight increase of IL-5 and IL-10 is observed after multiple freeze-thaw cycles.29 IL-1 and IL-8 have a significant decrease in levels after two freeze-thaw cycles,30 while IL6, IL10 and IL2 levels are stable when plasma samples undergo three free-thaw cycles.14 IL-9, CXCL10 and Eotaxin-1 are noted to be the most thermally stable cytokine biomarkers.28 Several studies have also highlighted that levels of cytokines are significantly affected only after three freeze-thaw cycles,14 15 31 32 which is consistent with the results of our study, where we did not see significant changes to cytokine levels up to three freeze-thaw cycles.

Our findings from the PCA demonstrated that the overall patient-specific cytokine biomarker profiles remained relatively the same over time. This suggests that with changes in individual biomarkers over storage duration time, the overall combination of biomarkers is a more reliable measure of disease status and should be used instead for classifying patients. The focus on individual biomarkers for clinical decision making may lead to false conclusions given the susceptibility of individual biomarkers to deterioration over time. In a study by Sato et al, PCA was used to determine the cytokines contributing to macular atrophy in neovascular age-related macular degeneration.33 The application of PCA in cytokine biomarker analyses has been widely shown across other studies and may serve as a valuable tool in biomarker analyses in future studies.34 35

The authors would like to acknowledge that the relationships between the ocular fluid cytokine biomarkers may be affected by disease states. A wide range of diseases were included in this study in order to account for heterogeneity of the cytokine biomarkers and increase generalisability of the findings. Due to the sample size, we did not conduct any further subgroup analyses on the patients with retinal detachment that can affect the blood retinal barrier in order to determine if these patients had a larger degree of degradation at 3 months. Future studies may look into stability of biomarkers over time in specific disease groups. The analysis for the freeze-thaw cycles, although demonstrated similar findings to previous studies, did have a small sample size and may be investigated further in future studies. There are important aspects of sample collection procedures such as the use of small gauge needles and vitrector, which may influence stability or integrity of ocular fluid cytokines biomarkers. Lastly, there was variability noted in the degree of decline in biomarker analytes at each of the time points. Despite having a standard protocol and analysis method, we cannot rule out the possibility of some differences in standardisation of experimental techniques across the various time points.

Conclusions

The findings from this study suggest that several ocular cytokine biomarkers are susceptible to degradation in ocular samples with long-term storage starting at 3 months. There is no evidence to suggest degradation in cytokine levels with up to three freeze-thaw cycles. In all cases, the overall patient-specific cytokine biomarker profiles remained relatively the same over time. Standardised guidelines and protocols for optimal and standardised sample handling methods are essential for ensuring correct research findings about intraocular biomarkers are translated into clinical practice.

Data availability statement

Data are available on reasonable request. Dara are available on request from the corresponding author.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and this prospective experimental study was performed in accordance with the Declaration of Helsinki and Health Insurance Portability and Accountability Act, and was approved by the Unity Health Toronto (REB# 20-142), University Health Network (REB# 20-6211) and University of Toronto (RIS# 40230) Research Ethics Boards. Participants gave informed consent to participate in the study before taking part.

References

Supplementary material

  • Supplementary Data

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Footnotes

  • Contributors Conception and design: TF and DTW. Acquisition of data: all authors. Data analysis: TF and BN. Interpretation of data: TF, BN and DTW. First draft of the article: TF and JP. Critical revision: All authors. Final approval of the version to be published: all authors. Act as guarantor of the work: TF and DTW.

  • Funding This work was supported by the Unity Health Toronto Department of Ophthalmology Research Fund under DTW and the Fighting Blindness Canada Clinician-Scientist Emerging Leader Award given to TF.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.