Serum miRNA-based signature indicates radiation exposure and dose in humans: a multicenter diagnostic biomarker study

  1. Zuzanna Nowicka
  2. Bartłomiej Tomasik
  3. David Kozono
  4. Konrad Stawiski
  5. Thomas Johnson
  6. Daphne Haas-Kogan
  7. Marek Ussowicz
  8. Dipanjan Chowdhury
  9. Wojciech Fendler

  • Curated by eLife

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    Evaluation Summary:

    Nowicka et al., evaluated radiation dose and time dependent changes in the levels of selected serum miRNAs in human patients who received partial or complete myeloablative total body irradiation (TBI) and propose a panel of circulating miRNAs as potential radiation biodoismeters. The team employed next generation sequencing approach for discovery (or rediscovery) and quantification of selected responders by qRT-PCR using non-responsive miRNAs purified from exosomes in serum for evaluation of relative changes. Excellent bioinformatics and bio statistical methods are employed. However, critical biomarkers they propose as radiation biodosimeters have already been identified and published earlier. There is little novelty here and the translational significance of the study is moderate.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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Abstract

Mouse and non-human primate models showed that serum miRNAs may be used to predict the biological impact of radiation doses. We hypothesized that these results can be translated to humans treated with total body irradiation (TBI), and that miRNAs may be used as clinically feasible biodosimeters. To test this hypothesis, serial serum samples were obtained from 25 patients who underwent allogeneic stem-cell transplantation and profiled for miRNA expression using next-generation sequencing. Circulating exosomes were extracted, their miRNA content sequenced and cross-referenced with the total miRNA fraction. Finally, miRNAs with diagnostic potential were quantified with qPCR and an artificial neural network model was created and validated on an independent group of 12 patients with samples drawn under the same protocol. Differential expression results were largely consistent with previous studies and allowed us to build an 8-miRNA-based model that showed AUC of 0.97 (95%CI 0.89-1.00) and validate it using qPCR in an independent validation set where it showed accuracy >91% for detecting exposure and 87.5% for differentiating between lethal and non-lethal doses. MiRNAs used in the model were miR-150-5p, miR-126-5p, miR-375, miR-215-5p, miR-144-5p, miR-122-5p, miR-320d and miR-10b-5p. Additionally, miRNAs with detectable expression in this and two prior animal sets almost perfectly separated the irradiated from non-irradiated samples in mice, macaques and humans, validating the miRNAs as radiation-responsive through evolutionarily conserved transcriptional regulation mechanisms. We conclude that serum miRNAs reflect radiation exposure and dose for humans undergoing TBI and may be used as functional biodosimeters for precise identification of people exposed to clinically significant radiation doses.

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  1. eLife

    Author Response

    Reviewer #1 (Public Review):

    Strength: Excellent statistical methods are employed. Specimens collected from two centers are used.

    Weakness: It is not clear what new knowledge this follow-up study bring to the audience. The critical biomarker, miR150 they propose for development of biodosimetry assay was already discovered. There are close to dozen publications showing the dose response of miR50, in mouse, rats, non-human primates and humans (including two research papers and and several reviews from authors). The dose response shown in 4b is not appreciable. Introduction and discussion talk about clinical utility for triage after nuclear disaster. Is analysis of miRNAs purified from exosome a viable approach for triage and clinical decision making? If so, please provide convincing argument showing practicality.

    We appreciate that the reviewer and the editor believe that “excellent bioinformatics and biostatistical methods are employed”. We apologize for the confusion regarding miR-150 and its utility as a radiation exposure biomarker. Indeed we and others have shown the importance of miR-150 and other miRNAs in detecting radiation exposure in mice and macaques. We had inferred that the resulting evolutionarily conserved radiation-inducible microRNAs were very likely to translate well to humans due to the high conservation of their promoter regions and transcription factor binding sites. However, in this study validating microRNA-based test for radiation detection using actual samples , we demonstrate that while most of the predictions grounded in animal models held true, solely through the analysis of human data were we able to develop a model that reached clinically-useful performance. And most importantly there are key differences in humans suggesting that for clinical application the primary source of data has to be human. For example, a key miRNA for radiation detection noted in macaques – miR-133 – was absent in human patient sera. The miR-30 family, important for dose separation in mice was redundant in the human test. The results from animal studies of miR-150-5p are not directly translatable for the use in humans. In animals, particularly isogenic mice, miR-150-5p kinetics enable perfect separation of the irradiated from non-irradiated samples, even after low dose exposure. The dose response in humans, that have different genetic and clinical background, is much less appreciable and therefore a simple, single- or two-miRNA-based test is insufficient. To overcome this, we employed artificial neural networks reliant on the expression of 8 miRNAs and 2 normalizers, which assure robustness to differences in sample material content. Therefore, we are bringing significantly new knowledge to the field, and providing a template for how miRNA signatures derived from animal models need robust validation in human samples before we even conceive a human application. The analysis of miRNAs purified from exosomes constitutes an exploratory component of our work and is not part of the proposed diagnostic procedure for triage and clinical decision making. We introduced necessary changes to make the division between the main and exploratory parts of our work more evident (lines 116-127).

    Major comments:

    1. Longitudinal evaluation of specimens from human patients who received TBI is a plus. However, baseline readings in specimens collected from leukemia patients need to be compared with that in healthy humans. Why several specimens were excluded from analysis?

    Since the irradiation of healthy humans would not be ethically acceptable, we cross-referenced the results from patients with leukemia with our earlier results of radiation-responsive miRNAs in healthy mice and non-human primates as a surrogate of healthy humans undergoing TBI. As outlined in the “Preprocessing of profiling data” section of Materials and Methods, we implemented quality control based on the number of detected miRNAs per sample. For the miRNA-seq based experiment, samples with less than 350 miRNAs with non-zero reads detected (4A and 7A in Figure 1 – supplementary figure 1) and respective paired samples were removed from the analysis. Additionally, sample DFCI.13A was an outlier in hierarchical clustering and in Principal Component Analysis (Figure 1 – supplementary figure 2) and therefore this sample, together with paired samples from other timepoints, were excluded from the analysis. We incorporated this information in the main part of the manuscript (lines 146-148).

    1. Dose response noted is moderate. Biodosimetry refers retrospective evaluation of absorbed dose and the analysis should include validation using specimens of unknown exposure.

    As outlined above, the moderate dose responsiveness of miRNAs used in our proposed signature is the primary reason why we believe that a simple diagnostic procedure based on a single miRNA, e.g. miR-150-5p, will not be feasible for use in humans. The final model was evaluated on an independent group of 12 patients with samples drawn under the same protocol (for which exposure and dose was unknown, to validate the model diagnostic accuracy).

    1. Authors says that 1 Gy exposure in humans can cause ARS (paragraph 1, introduction). However their approach do not resolve dose under 4 Gy (around the LD50 value in humans).

    The TBI protocol does not allow for irradiation with doses lower than 2Gy in a single fraction, which was the reason behind the definition of low-dose exposure group (2 or 4Gy) in our study. However, localized irradiation with higher doses provokes response reflected by changes in miRNA levels in serum (Malachowska et al. Int. J Radiation Oncol Biol Phys), suggesting that the irradiation signature are likely to hold true and identify individuals exposed to smaller doses.

    Reviewer #2 (Public Review):

    The study first compared the profiles of serum miRNA in patients before and after irradiation treatment. Then they selected 8 miRNA markers that showed significant changes in levels for further analysis. Then, they showed that the analysis of these markers by real-time PCR can differentiate the pre- and post-irradiation samples in 12 additional patients. The objective of the study is unclear.

    We rephrased the appropriate sections of the manuscript accordingly to elucidate the objective of the study (lines 105-106 and 131-132).

    The study only demonstrates that the 8 miRNA markers are useful to differentiate serum samples collected before and after irradiation. This information is not useful as the blood picture would be more accurate and cheap to accomplish this task.

    The currently used diagnostic screening tests for radiation exposure, including time to onset of radiation sickness, kinetics of lymphocyte depletion and chromosomal abnormalities analysis, are time-consuming and do not allow definite conclusions, as outlined by the lack of FDA-approved biodosimeter. The nadirs of peripheral blood cell counts may reflect high dose exposure but do not allow for prediction of the eventual outcome. Moreover, as evidenced in our prior experimental studies, the dynamics of the blood cell counts are significantly slower than those of circulating miRNAs. For example, the differences in outcome, that is probability of survival of an animal after acute radiation exposure, is not evident by any blood counts or other measures for weeks after radiation, and is predicted by a blood based-microRNA signature with ~90% accuracy assessed 24 hours after radiation exposure (Acharya et al, Science Translational Medicine, 2015). Therefore, although we acknowledge that a blood cell count would be cheaper, we respectfully disagree that it would be more accurate in rapidly providing the necessary information to implement countermeasures safeguarding from the absorbed radiation dose. Furthermore, qPCR-based assays are also inexpensive and increasingly available, owing to the COVID-19 pandemic and the great need to expand PCR-based testing capabilities that it gave rise to. We acknowledge that this information was not presented in sufficient detail and we expanded relevant sections of the manuscript (lines 64-76, 401-402).

    The authors also propose that these markers are useful for the identification of subjects exposed to irradiation. As this study has not addressed the specificity of these miRNA markers to irradiation, the claim of having a signature for radiation exposure is not justified.

    We had shown in previous, experimental exposure studies (“Serum microRNAs are early indicators of survival after radiation-induced hematopoietic injury”, Science Translational Medicine, 2015 and “Evolutionarily conserved serum microRNAs predict radiation-induced fatality in nonhuman primates”, Science Translational Medicine, 2017), performed using animal models that miRNAs with radiation-dependent alterations of expression show association with bone marrow depletion, correlate with survival in amifostine rescue experiment, and that miRNA expression changes are supressed by the use of radiation-mitigating agents like gamma-3-tocotrienol. These arguments act in favour of specificity towards irradiation as the inciting stimulus of the expression patterns. The cross-referencing of results from animal studies and from our miRNA-seq experiment on human samples was aimed to account for this issue, as similar experiments on healthy humans would not be ethical, and to identify high-confidence miRNAs from which a signature could be built. We now added these explanations (lines 112-115, 164-167, 344-350).

    Although patients with irrevocable damage of bone marrow due to other factors would be an interesting comparative group, we struggle to find an ethically acceptable scenario that would match the TBI in terms of the timeline and repeatability of the bone marrow depletion. A feasible alternative may be high dose chemotherapy conducted in preparation for bone marrow transplant, but the dynamics of that procedure are vastly different making the group more adequate for analyses of bone marrow regeneration rather than a control for TBI-initiated damage.

    The key new experiments in this study are the profiling of the serum miRNA in the patients undergoing total body irradiation. The results on mouse model and macaques have been published previously. The consistency of the changes of the miRNA markers is not surprising.

    The consistency of the radiation-inducible miRNAs between mice, non-human primates and humans was expected, given the high conservation of their promoter regions and transcription factor binding sites, as we showed previously (Fendler et al., 2017). This step was important to assure that the miRNA level changes observed in humans result from radiation exposure, as this could not be determined directly, as mentioned in the response to previous remark. However, the creation of the clinically-applicable test would not be possible without a true study in humans presented in the manuscript. Notably, miRNAs crucial for the radiation exposure models in our macaque model (miR-133b) was surprisingly absent in human sera, and the miR-30 family, important for dose separation in mice was redundant in the human test. This serves as a cautionary tale for “translational” studies without true validation in humans and underlines the importance of our findings in terms of the first human-specific and adequately validated diagnostic and prognostic test for radiation exposure.

    Reviewer #3 (Public Review):

    1. Appropriate bioinformatics discussions and functional pathway analysis are necessary for the key differentially expressed miRNAs that have been screened out. It is boring to only discuss the differences of miRNA data.

    We appreciate the suggestion to back the results of differential miRNA expression with a more in-depth bioinformatic discussion. We discussed the results of functional enrichment analysis, presented in Fig. 3C, in more detail, and appended the bioinformatic analysis (lines 218-222, 360-364, 546-549). A graph of miRNA-gene interactions, created using miRTargetLink 2.0 for miRNAs differentially expressed in exosomes after high dose irradiation has been added as figure supplement 1 to Figure 3.

    1. In page 5, "We used logistic regression to create such a model in the low-dose setting (N=22 sample pairs). The resulting classifier was based on the expression of miR-150-5p, miR-126-5p and miR-375" , Why the three miRNAs in the low-dose radiation group were selected for modeling instead of the seven overlapping miRNAs in the high and low dose radiation group to classificate the irradiated- and non-irradiated samples ? Please explain in detail.

    The expression of miR-150-5p, miR-126-6p and miR-375 was used in our previous animal studies to determine radiation exposure and we used similar approach at this stage of the project to evaluate whether their expression measured using RNA sequencing in human sera can reliably distinguish between the irradiated and non-irradiated samples. We acknowledge that it is not clearly stated. The primary purpose of this analysis was to visually present similarities in radiation-inducible miRNA expression changes across species, and the logistic regression model in question was not used any further. Following the Reviewer suggestion, we built a model using the seven miRNAs overlapping in the high and low dose radiation comparisons to classify the irradiated- and non-irradiated samples, obtaining AUC of 0.95 (95%CI: 0.89-1.0); however, we believe adding this information to the main part of the manuscript is not necessary.

    1. In page 5, "Therefore, the expression of miR-126-5p, miR-150-5p and miR-375 enabled efficient classification of the irradiated- and non-irradiated samples in both settings (Fig. S6C)";

    In page 6, "Interestingly, a set of 3 miRNAs quantified by qPCR in all of our previous experiments clearly visually distinguished irradiated from non-irradiated samples in the human analysis (Fig. 5A)",

    Which three of miRNAs，miR-150-5p，miR-375，miR-126-5p mentioned before or miR-150-5p，miR-375，miR-215-5p？Please clarify clearly.

    Thank you for the suggestion. We rephrased this fragment (lines 289-290).

    1. In page 4, "Since miRNA-containing exosomes.......high dose irradiation", Do you think that the differently expression of serum miRNAs partly results from exosomes? Low dose irradiation is also able to change exosomal miRNA profile，why only high dose irradiation is taken into account in paper while low dose irradiation is not？

    We believe that serum miRNA expression results in part from exosomes and, as an exploratory component of our work, aimed to verify whether the magnitude of changes in exosomal miRNA expression exceeded that in serum, improving the potential biomarker specificity to the extent that would justify the development of an arguably more complex and labour-intensive test utilizing exosome isolation. The sequencing of exosomal miRNA content was therefore performed as an exploratory analysis only after high radiation exposure. However, the lower amount of exosomal miRNA than obtained through the total miRNA extraction protocol offsets any benefit stemming from higher cellular specificity of the former, and, based on the results that were comparable with those obtained from sera, decided to not explore this concept further. We added this explanation to our manuscript as this issue was not clarified previously (lines 116-127 and 339-343).

    1. Are there any miRNAs that can clearly distinguish between high and low dose groups? If so, please clarify them in text.

    We now clarified this issue in discussion (lines 415-417).

    1. In page 7,"Importantly, similarities were observed in the level of both individual miRNAs and miRNA families", What part of result Comes to this conclusion？Please explain clearly.

    When describing similarities between human and animal studies, we refer to our previous work describing radiation-responsive miRNAs in mice and non-human primates. These similarities (and differences) are described in detail in Table 1. We added relevant references to Table 1 and to the cited sentence (line 352).

    1. In page 7, "We found that the most common putative tissue sources for differentially expressed miRNAs were hematopoietic and endothelial cells", Which part of result shows this sentence? Please point it out.

    This statement is not validated in our work explicitly but based on the results from references: Ludwig et al., 2016, de Rie et al., 2017 and Landgraf et al., 2007. Since Ludwig et al., de Rie et al. and Landgraf et al. generated excellent data of miRNA expression across human and mouse tissues and cell types that showed overlapping results for the miRNAs of interest, as detailed in Table 1, we did not perform additional confirmatory experiments.

    1. Were the patients suffering from cancer or other diseases? How to ensure that the differential expression of miRNA was caused by radiation exposure rather than their own disease? Please explain.

    As described above, initial experimental studies performed in animal models (mouse and macaque) in preparation for this study showed the specificity of miRNA (including ones in the signature) towards radiation exposure in different animal models. This was evidenced on multiple layers of validation and rescue experiments. Admittedly, a demonstration that additional diseases with a phenotype similarity with ARS affect study performance is an interesting concept, but it would be extremely unlikely to impair the performance of the test in an individual after radiation exposure. Namely, even if the examined patient has a hematologic malignancy or myelofibrosis potentially affecting the performance of the test, identification of such individuals as potentially irradiated would lead to them being followed-up adequately. Failure of the test to detect radiation exposure will likely not be severe risk, since such individuals will already be severely ill and under proper care with regular monitoring of bone marrow function. We are aware that some unforeseen and not discussed clinical factors may affect some facets of the test but the built-in robustness derived from having multiple miRNAs mitigates the risk of non-specificity.

  2. eLife

    Evaluation Summary:

    Nowicka et al., evaluated radiation dose and time dependent changes in the levels of selected serum miRNAs in human patients who received partial or complete myeloablative total body irradiation (TBI) and propose a panel of circulating miRNAs as potential radiation biodoismeters. The team employed next generation sequencing approach for discovery (or rediscovery) and quantification of selected responders by qRT-PCR using non-responsive miRNAs purified from exosomes in serum for evaluation of relative changes. Excellent bioinformatics and bio statistical methods are employed. However, critical biomarkers they propose as radiation biodosimeters have already been identified and published earlier. There is little novelty here and the translational significance of the study is moderate.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    Strength: Excellent statistical methods are employed. Specimens collected from two centers are used.
    Weakness: It is not clear what new knowledge this follow-up study bring to the audience. The critical biomarker, miR150 they propose for development of biodosimetry assay was already discovered. There are close to dozen publications showing the dose response of miR50, in mouse, rats, non-human primates and humans (including two research papers and and several reviews from authors). The dose response shown in 4b is not appreciable. Introduction and discussion talk about clinical utility for triage after nuclear disaster. Is analysis of miRNAs purified from exosome a viable approach for triage and clinical decision making? If so, please provide convincing argument showing practicality.

    Major comments:
    1. Longitudinal evaluation of specimens from human patients who received TBI is a plus. However, baseline readings in specimens collected from leukemia patients need to be compared with that in healthy humans. Why several specimens were excluded from analysis?
    2. Dose response noted is moderate. Biodosimetry refers retrospective evaluation of absorbed dose and the analysis should include validation using specimens of unknown exposure.
    3. Authors says that 1 Gy exposure in humans can cause ARS (paragraph 1, introduction). However their approach do not resolve dose under 4 Gy (around the LD50 value in humans).

  4. eLife

    Reviewer #2 (Public Review):

    The study first compared the profiles of serum miRNA in patients before and after irradiation treatment. Then they selected 8 miRNA markers that showed significant changes in levels for further analysis. Then, they showed that the analysis of these markers by real-time PCR can differentiate the pre- and post-irradiation samples in 12 additional patients.

    The objective of the study is unclear.
    The study only demonstrates that the 8 miRNA markers are useful to differentiate serum samples collected before and after irradiation. This information is not useful as the blood picture would be more accurate and cheap to accomplish this task.
    The authors also propose that these markers are useful for the identification of subjects exposed to irradiation. As this study has not addressed the specificity of these miRNA markers to irradiation, the claim of having a signature for radiation exposure is not justified.

    The key new experiments in this study are the profiling of the serum miRNA in the patients undergoing total body irradiation. The results on mouse model and macaques have been published previously. The consistency of the changes of the miRNA markers is not surprising.

  5. eLife

    Reviewer #3 (Public Review):

    1. Appropriate bioinformatics discussions and functional pathway analysis are necessary for the key differentially expressed miRNAs that have been screened out. It is boring to only discuss the differences of miRNA data.

    2. In page 5, "We used logistic regression to create such a model in the low-dose setting (N=22 sample pairs). The resulting classifier was based on the expression of miR-150-5p, miR-126-5p and miR-375" , Why the three miRNAs in the low-dose radiation group were selected for modeling instead of the seven overlapping miRNAs in the high and low dose radiation group to classificate the irradiated- and non-irradiated samples ? Please explain in detail.

    3. In page 5, "Therefore, the expression of miR-126-5p, miR-150-5p and miR-375 enabled efficient classification of the irradiated- and non-irradiated samples in both settings (Fig. S6C)"; In page 6, "Interestingly, a set of 3 miRNAs quantified by qPCR in all of our previous experiments clearly visually distinguished irradiated from non-irradiated samples in the human analysis (Fig. 5A)",
      Which three of miRNAs, miR-150-5p miR-375 miR-126-5p mentioned before or miR-150-5p miR-375 miR-215-5p？Please clarify clearly.

    4. In page 4, "Since miRNA-containing exosomes.......high dose irradiation", Do you think that the differently expression of serum miRNAs partly results from exosomes? Low dose irradiation is also able to change exosomal miRNA profile，why only high dose irradiation is taken into account in paper while low dose irradiation is not？

    5. Are there any miRNAs that can clearly distinguish between high and low dose groups? If so, please clarify them in text.

    6. In page 7,"Importantly, similarities were observed in the level of both individual miRNAs and miRNA families", What part of result Comes to this conclusion？Please explain clearly.

    7. In page 7, "We found that the most common putative tissue sources for differentially expressed miRNAs were hematopoietic and endothelial cells", Which part of result shows this sentence? Please point it out.

    8. Were the patients suffering from cancer or other diseases? How to ensure that the differential expression of miRNA was caused by radiation exposure rather than their own disease? Please explain.

  6. Version published to 10.1101/2021.08.23.21262229v1 on medRxiv