Validating a Four-gene Set for H-ARS Severity Prediction in Peripheral Blood Samples of Irradiated Rhesus Macaques

Increased radiological and nuclear threats require preparedness. Our earlier work identified a set of four genes (DDB2, FDXR, POU2AF1 and WNT3), which predicts severity of the hematological acute radiation syndrome (H-ARS) within the first three days postirradiation In this study of 41 Rhesus macaques (Macaca mulatta, 27 males, 14 females) irradiated with 5.8-7.2 Gy (LD29-50/60), including some treated with gamma-tocotrienol (GT3, a radiation countermeasure) we independently validated these genes as predictors in both sexes and examined them after three days. At the Armed Forces Radiobiology Research Institute/Uniformed Services University of the Health Sciences, peripheral whole blood (1 ml) of Rhesus macaques was collected into PAXgene® Blood RNA tubes pre-irradiation after 1, 2, 3, 35 and 60 days postirradiation, stored at -80°C for internal experimental analyses. Leftover tubes from these already ongoing studies were kindly provided to Bundeswehr Institute of Radiobiology. RNA was isolated (QIAsymphony), converted into cDNA, and for further gene expression (GE) studies quantitative RT-PCR was performed. Differential gene expression (DGE) was measured relative to the pre-irradiation Rhesus macaques samples. Within the first three days postirradiation, we found similar results to human data: 1. FDXR and DDB2 were up-regulated, FDXR up to 3.5-fold, and DDB2 up to 13.5-fold in the median; 2. POU2AF1 appeared down regulated around tenfold in nearly all Rhesus macaques; 3. Contrary to human data, DDB2 was more up-regulated than FDXR, and the difference of the fold change (FC) ranged between 2.4 and 10, while the median fold changes of WNT3, except days 1 and 35, were close to 1. Nevertheless, 46% of the Rhesus macaques showed down-regulated WNT3 on day one postirradiation, which decreased to 12.2% on day 3 postirradiation. Considering the extended phase, there was a trend towards decreased fold changes at day 35, with median-fold changes ranging from 0.7 for DDB2 to 0.1 for POU2AF1, and on day 60 postirradiation, DGE in surviving animals was close to pre-exposure values for all four genes. In conclusion, the diagnostic significance for radiation-induced H-ARS severity prediction of FDXR, DDB2, and POU2AF1 was confirmed in this Rhesus macaques model. However, DDB2 showed higher GE values than FDXR. As shown in previous studies, the diagnostic significance of WNT3 could not be reproduced in Rhesus macaques; this could be due to the choice of animal model and methodological challenges.

Validating Radiosensitivity with Pre-Exposure Differential Gene Expression in Peripheral Blood Predicting Survival and Non-Survival in a Second Irradiated Rhesus Macaque Cohort

Radiosensitivity differs in humans and possibly in closely related nonhuman primates. The reasons for variation in radiosensitivity are not well known. In an earlier study, we examined gene expression (GE) pre-radiation in peripheral blood among male (n = 62) and female (n = 60) rhesus macaques (n = 122), which did or did not survive (up to 60 days) after whole-body exposure of 7.0 Gy (LD66/60). Eight genes (CHD5, CHI3L1, DYSF, EPX, IGF2BP1, LCN2, MBOAT4, SLC22A4) revealed significant associations with survival. Access to a second rhesus macaque cohort (males = 40, females = 23, total n = 63) irradiated with 5.8-7.2 Gy (LD29-50/60) and some treated with gamma-tocotrienol (GT3, a radiation countermeasure) allowed us to validate these gene expression changes independently. Total RNA was isolated from whole blood samples and examined by quantitative RT-PCR on a 96-well format. cycle threshold (Ct)-values normalized to 18S rRNA were analyzed for their association with survival. Regardless of the species-specific TaqMan assay, similar results were obtained. Two genes (CHD5 and CHI3L1) out of eight revealed a significant association with survival in the second cohort, while only CHD5 (involved in DNA damage response and proliferation control) showed mean gene expression changes in the same direction for both cohorts. No expected association of CHD5 GE with dose, treatment, or sex could be established. Instead, we observed significant associations for those comparisons comprising pre-exposure samples with CHD5 Ct values ≤ 11 (total n = 17). CHD5 Ct values ≤ 11 in these comparisons were mainly associated with increased frequencies (61-100%) of non-survivors, a trend which depending on the sample numbers, reached significance (P = 0.03) in males and, accordingly, in females. This was also reflected by a logistic regression model including all available samples from both cohorts comprising CHD5 measurements (n = 104, odds ratio 1.38, 95% CI 1.07-1.79, P = 0.01). However, this association was driven by males (odds ratio 1.62, 95% CI 1.10-2.38, P = 0.01) and CHD5 Ct values ≤ 11 since removing low CHD5 Ct values from this model, converted to insignificance (P = 0.19). A second male subcohort comprising high CHD5 Ct values ≥ 14.4 in both cohorts (n = 5) appeared associated with survival. Removing these high CHD5 Ct values converted the model borderline significant (P = 0.051). Based on the probability function of the receiver operating characteristics (ROC) curves, 8 (12.3%) and 5 (7.7%) from 65 pre-exposure RNA measurements in males, death and survival could be predicted with a negative and positive predictive value ranging between 85-100%. An associated odds ratio reflected a 62% elevated risk for dying or surviving per unit change (Ct-value) in gene expression, considering the before-mentioned CHD5 thresholds in RNA copy numbers. In conclusion, we identified two subsets of male animals characterized by increased (Ct values ≤ 11) and decreased (Ct values ≥ 14.4) CHD5 GE copy numbers before radiation exposure, which independently of the cohort, radiation exposure or treatment appeared to predict the death or survival in males.

Applicability of Gene Expression in Saliva as an Alternative to Blood for Biodosimetry and Prediction of Radiation-induced Health Effects

As the great majority of gene expression (GE) biodosimetry studies have been performed using blood as the preferred source of tissue, searching for simple and less-invasive sampling methods is important when considering biodosimetry approaches. Knowing that whole saliva contains an ultrafiltrate of blood and white blood cells, it is expected that the findings in blood can also be found in saliva. This human in vivo study aims to examine radiation-induced GE changes in saliva for biodosimetry purposes and to predict radiation-induced disease, which is yet poorly characterized. Furthermore, we examined whether transcriptional biomarkers in blood can also be found equivalently in saliva. Saliva and blood samples were collected in parallel from radiotherapy (RT) treated patients who suffered from head and neck cancer (n = 8) undergoing fractioned partial-body irradiations (1.8 Gy/fraction and 50-70 Gy total dose). Samples were taken 12-24 h before first irradiation and ideally 24 and 48 h, as well as 5 weeks after radiotherapy onset. Due to the low quality and quantity of isolated RNA samples from one patient, they had to be excluded from further analysis, leaving a total of 24 saliva and 24 blood samples from 7 patients eligible for analysis. Using qRT-PCR, 18S rRNA and 16S rRNA (the ratio being a surrogate for the relative human RNA/bacterial burden), four housekeeping genes and nine mRNAs previously identified as radiation responsive in blood-based studies were detected. Significant GE associations with absorbed dose were found for five genes and after the 2nd radiotherapy fraction, shown by, e.g., the increase of CDKN1A (2.0 fold, P = 0.017) and FDXR (1.9 fold increased, P = 0.002). After the 25th radiotherapy fraction, however, all four genes (FDXR, DDB2, POU2AF1, WNT3) predicting ARS (acute radiation syndrome) severity, as well as further genes (including CCNG1 [median-fold change (FC) = 0.3, P = 0.013], and GADD45A (median-FC = 0.3, P = 0.031)) appeared significantly downregulated (FC = 0.3, P = 0.01-0.03). A significant association of CCNG1, POU2AF1, HPRT1, and WNT3 (P = 0.006-0.04) with acute or late radiotoxicity could be shown before the onset of these clinical outcomes. In an established set of four genes predicting acute health effects in blood, the response in saliva samples was similar to the expected up- (FDXR, DDB2) or downregulation (POU2AF1, WNT3) in blood for up to 71% of the measurements. Comparing GE responses (PHPT1, CCNG1, CDKN1A, GADD45A, SESN1) in saliva and blood samples, there was a significant linear association between saliva and blood response of CDKN1A (R2 = 0.60, P = 0.0004). However, the GE pattern of other genes differed between saliva and blood. In summary, the current human in vivo study, (I) reveals significant radiation-induced GE associations of five transcriptional biomarkers in salivary samples, (II) suggests genes predicting diverse clinical outcomes such as acute and late radiotoxicity as well as ARS severity, and (III) supports the view that blood-based GE response can be reflected in saliva samples, indicating that saliva is a "mirror of the body" for certain but not all genes and, thus, studies for each gene of interest in blood are required for saliva.

PUM1 and PGK1 are Favorable Housekeeping Genes over Established Biodosimetry-related Housekeeping Genes such as HPRT1, ITFG1, DPM1, MRPS5, 18S rRNA and Others after Radiation Exposure

In gene expression (GE) studies, housekeeping genes (HKGs) are required for normalization purposes. In large-scale inter-laboratory comparison studies, significant differences in dose estimates are reported and divergent HKGs are employed by the teams. Among them, the 18S rRNA HKG is known for its robustness. However, the high abundance of 18S rRNA copy numbers requires dilution, which is time-consuming and a possible source of errors. This study was conducted to identify the most promising HKGs showing the least radiation-induced GE variance after radiation exposure. In the screening stage of this study, 35 HKGs were analyzed. This included selected HKGs (ITFG1, MRPS5, and DPM1) used in large-scale biodosimetry studies which were not covered on an additionally employed pre-designed 96-well platform comprising another 32 HKGs used for different exposures. Altogether 41 samples were examined, including 27 ex vivo X-ray irradiated blood samples (0, 0.5, 4 Gy), six X-irradiated samples (0, 0.5, 5 Gy) from two cell lines (U118, A549), as well as eight non-irradiated tissue samples to encompass multiple biological entities. In the independent validation stage, the most suitable candidate genes were examined from another 257 blood samples, taking advantage of already stored material originating from three studies. These comprise 100 blood samples from ex vivo X-ray irradiated (0-4 Gy) healthy donors, 68 blood samples from 5.8 Gy irradiated (cobalt-60) Rhesus macaques (RM) (LD29/60) collected 0-60 days postirradiation, and 89 blood samples from chemotherapy-(CTx) treated breast tumor patients. CTx and radiation-induced GE changes in previous studies appeared comparable. RNA was isolated, converted into cDNA, and GE was quantified employing TaqMan assays and quantitative RT-PCR. We calculated the standard deviation (SD) and the interquartile range (IQR) as measures of GE variance using raw cycle threshold (Ct) values and ranked the HKGs accordingly. Dose, time, age, and sex-dependent GE changes were examined employing the parametrical t-test and non-parametrical Kruskal Wallis test, as well as linear regression analysis. Generally, similar ranking results evolved using either SD or IQR GE measures of variance, indicating a tight distribution of GE values. PUM1 and PGK1 showed the lowest variance among the first ten most suitable genes in the screening phase. MRPL19 revealed low variance among the first ten most suitable genes in the screening phase only for blood and cells, but certain comparisons indicated a weak association of MRPL19 with dose (P = 0.02-0.09). In the validation phase, these results could be confirmed. Here, IQR Ct values from, e.g., X-irradiated blood samples were 0.6 raw Ct values for PUM1 and PGK1, which is considered to represent GE differences as expected due to methodological variance. Overall, when compared, the GE variance of both genes was either comparable or lower compared to 18S rRNA. Compared with the IQR GE values of PUM1 and PGKI, twofold-fivefold increased values were calculated for the biodosimetry HKG HPRT1, and comparable values were calculated for biodosimetry HKGs ITFG1, MRPS5, and DPM1. Significant dose-dependent associations were found for ITFG1 and MRPS5 (P = 0.001-0.07) and widely absent or weak (P = 0.02-0.07) for HPRT1 and DPM1. In summary, PUM1 and PGK1 appeared most promising for radiation exposure studies among the 35 HKGs examined, considering GE variance and adverse associations of GE with dose.

Validation of genes for H-ARS severity prediction in leukemia patients - interspecies comparison, challenges, and promises

PURPOSE

In a previous baboon-study, a total of 29 genes were identified for clinical outcome prediction of the hematologic, acute, radiation, syndrome (H-ARS) severity. Among them, four genes (FDXR, DDB2, POU2AF1, WNT3) appeared promising and were validated in five leukemia patients. Within this study, we sought further in-vivo validation in a larger number of whole-body irradiated patients.

MATERIAL AND METHODS

Peripheral blood was drawn from 10 leukemia patients before and up to 3 days during a fractionated (2 Gy/day) total-body irradiation (TBI) with 2-12Gy. After RNA-isolation, gene expression (GE) was evaluated on 31 genes widely used in biodosimetry and H-ARS prediction employing qRT-PCR. A customized low-density-array (LDA) allowed simultanously analyzing all genes, the 96-well format further examined the four most promising genes. Fold-changes (FC) in GE relative to pre-irradiation were calculated.

RESULTS

Five patients suffering from acute-lymphoblastic-leukemia (ALL) respectively non-Hodgkin-lymphoma (NHL) revealed sufficient RNA-amounts and corresponding lymphocyte and neutrophile counts for running qRT-PCR, while acute-myeloid-leukemia (AML) and one myelofibrosis patient could not supply enough RNA. Generally, 1-2µg total RNA was isolated, whereas up to 10-fold differences in RNA-quantities (associated suppressed GE-changes) were identified among pre-exposure and exposure samples. From 31 genes, 23 were expressed in at least one of the pre-exposure samples. Relative to pre-exposure, the number of expressed genes could halve at 48 and 72h after irradiation. Using the LDA, 13 genes were validated in human samples. The four most promising genes (vid. sup.) were either undetermined or too close to pre-exposure. However, they were measured using the more sensitive 96-well format, except WNT3, which wasn´t detectable. As in previous studies, an opposite regulation in GE for FDXR in leukemia patients (up-regulated) relative to baboons (down-regulated) was reconfirmed. Radiation-induced GE-changes of DDB2 (up-regulated) and POU2AF1 (down-regulated) behaved similarly in both species. Hence, 16 out of 23 genes of two species showed GE-changes in the same direction, and up-regulated FDXR as in human studies were revalidated.

CONCLUSION

Identified genes for H-ARS severity prediction, previously detected in baboons, were validated in ALL but not in AML patients. Limitations related to leukemia type, associated reduced RNA amounts, suppressed GE changes, and methodological challenges must be considered as factors negatively affecting the total number of validated genes. Based on that, we propose additional controls including blood cell counts and preferably fluorescence-based RNA quantity measurements for selecting promising samples and using a more sensitive 96-well format for candidate genes with low baseline copy numbers.

Ex-vivo dose response characterization of the recently identified EDA2R gene after low level radiation exposures and comparison with FDXR gene expression and the γH2AX focus assay

OBJECTIVE

Recently, promising radiation-induced EDA2R gene expression (GE) changes after low level radiation could be shown. Stimulated by that, in this study, we intended to independently validate these findings and to further characterize dose-response relationships in comparison to FDXR and the γH2AX-DNA double-strand break (DSB) focus assay, since both assays are already widely used for biodosimetry purposes.

MATERIALS AND METHODS

Peripheral blood samples from six healthy human donors were irradiated ex vivo (dose: ranging from 2.6 to 49.7 mGy). Subsequently, the fold-differences relative to the sham irradiated reference group were calculated. Radiation-induced changes in GE of FDXR and EDA2R were examined using the quantitative real-time polymerase-chain-reaction (qRT-PCR). DSB foci were quantified in 100 γH2AX + 53BP1 immunostained cells employing fluorescence microscopy. Examinations were performed at single time points enabling sufficient detection of both endpoints.

RESULTS

A significant increase in EDA2R GE relative to the unexposed control was observed in the range of 2.6 mGy (1.6-fold, p = .045) to 5.4 mGy (2.2-fold, p = .0002), whereas the copy numbers increased linearly up to 13.1-fold at 49.7 mGy. On the contrary, FDXR upregulation (2.2-fold) became significant after a 22.6 mGy exposure (p ≤ .02) and increased linearly up to 4-fold at 49.7 mGy. A significant increase in radiation-induced foci (relative to unexposed, RIF-fd) was observed after 11.3 mGy (RIF-fd: 1.5 ± 0.5, p ≤ .03), while the foci increased linearly up to 3-fold at 49.7 mGy. From this, the FDXR and RIF-fd slopes have shown comparability, while the EDA2R slope was five times higher. Nevertheless, the coefficient of variation (CV) of EDA2R was about 30% higher than for RIF-fd.

CONCLUSION

Higher radiation-induced EDA2R GE changes and a lower radiation detection level compared to RIF-fd and FDXR GE changes examined under optimal conditions ex vivo on human samples appear promising. Yet, our results represent just the beginning of further studies to be conducted in animal models for further time- and dose-dependent evaluation and additional examinations on radiologically examined patients to evaluate the impact of confounder, such as age, sex, social behavior, or diseases.

RENEB Inter-Laboratory Comparison 2021: The Gene Expression Assay

Early and high-throughput individual dose estimates are essential following large-scale radiation exposure events. In the context of the Running the European Network for Biodosimetry and Physical Dosimetry (RENEB) 2021 exercise, gene expression assays were conducted and their corresponding performance for dose-assessment is presented in this publication. Three blinded, coded whole blood samples from healthy donors were exposed to 0, 1.2 and 3.5 Gy X-ray doses (240 kVp, 1 Gy/min) using the X-ray source Yxlon. These exposures correspond to clinically relevant groups of unexposed, low dose (no severe acute health effects expected) and high dose exposed individuals (requiring early intensive medical health care). Samples were sent to eight teams for dose estimation and identification of clinically relevant groups. For quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray analyses, samples were lysed, stored at 20°C and shipped on wet ice. RNA isolations and assays were run in each laboratory according to locally established protocols. The time-to-result for both rough early and more precise later reports has been documented where possible. Accuracy of dose estimates was calculated as the difference between estimated and reference doses for all doses (summed absolute difference, SAD) and by determining the number of correctly reported dose estimates that were defined as ±0.5 Gy for reference doses <2.5 Gy and ±1.0 Gy for reference doses >3 Gy, as recommended for triage dosimetry. We also examined the allocation of dose estimates to clinically/diagnostically relevant exposure groups. Altogether, 105 dose estimates were reported by the eight teams, and the earliest report times on dose categories and estimates were 5 h and 9 h, respectively. The coefficient of variation for 85% of all 436 qRT-PCR measurements did not exceed 10%. One team reported dose estimates that systematically deviated several-fold from reported dose estimates, and these outliers were excluded from further analysis. Teams employing a combination of several genes generated about two-times lower median SADs (0.8 Gy) compared to dose estimates based on single genes only (1.7 Gy). When considering the uncertainty intervals for triage dosimetry, dose estimates of all teams together were correctly reported in 100% of the 0 Gy, 50% of the 1.2 Gy and 50% of the 3.5 Gy exposed samples. The order of dose estimates (from lowest to highest) corresponding to three dose categories (unexposed, low dose and highest exposure) were correctly reported by all teams and all chosen genes or gene combinations. Furthermore, if teams reported no exposure or an exposure >3.5 Gy, it was always correctly allocated to the unexposed and the highly exposed group, while low exposed (1.2 Gy) samples sometimes could not be discriminated from highly (3.5 Gy) exposed samples. All teams used FDXR and 78.1% of correct dose estimates used FDXR as one of the predictors. Still, the accuracy of reported dose estimates based on FDXR differed considerably among teams with one team's SAD (0.5 Gy) being comparable to the dose accuracy employing a combination of genes. Using the workflow of this reference team, we performed additional experiments after the exercise on residual RNA and cDNA sent by six teams to the reference team. All samples were processed similarly with the intention to improve the accuracy of dose estimates when employing the same workflow. Re-evaluated dose estimates improved for half of the samples and worsened for the others. In conclusion, this inter-laboratory comparison exercise enabled (1) identification of technical problems and corrections in preparations for future events, (2) confirmed the early and high-throughput capabilities of gene expression, (3) emphasized different biodosimetry approaches using either only FDXR or a gene combination, (4) indicated some improvements in dose estimation with FDXR when employing a similar methodology, which requires further research for the final conclusion and (5) underlined the applicability of gene expression for identification of unexposed and highly exposed samples, supporting medical management in radiological or nuclear scenarios.

Gene Expression Changes in a Prefinal Health Stage of Lethally Irradiated Male and Female Rhesus Macaques

Radiation-induced gene expression (GE) changes can be used for early and high-throughput biodosimetry within the first three days postirradiation. However, is the method applicable in situations such as the Alexander Litvinenko case or the Goiania accident, where diagnosis occurred in a prefinal health stage? We aimed to characterize gene expression changes in a prefinal health stage of lethally irradiated male and female rhesus macaques. Peripheral blood was drawn pre-exposure and at the prefinal stage of male and female animals, which did not survive whole-body exposure with 700 cGy (LD66/60). RNA samples originated from a blinded randomized Good Laboratory Practice study comprising altogether 142 irradiated rhesus macaques of whom 60 animals and blood samples (15 samples for both time points and sexes) were used for this analysis. We evaluated GE on 34 genes widely used in biodosimetry and prediction of the hematological acute radiation syndrome severity (H-ARS) employing quantitative real-time polymerase chain reaction (qRT-PCR). These genes were run in duplicate and triplicate and altogether 96 measurements per time point and sex could be performed. In addition, 18S ribosomal RNA (rRNA) was measured to depict the ribosome/transcriptome status as well as for normalization purposes and 16S rRNA was evaluated as a surrogate for bacteremia. Mean differential gene expression (DGE) was calculated for each gene and sex including all replicate measurements and using pre-exposure samples as the reference. From 34 genes, altogether 27 genes appeared expressed. Pre-exposure samples revealed no signs of bacteremia and 18S rRNA GE was in the normal range in all 30 samples. Regarding prefinal samples, 46.7% and 40% of animals appeared infected in females and males, respectively, and for almost all males this was associated with out of normal range 18S rRNA values. The total number of detectable GE measurements was sixfold (females) and 15-fold (males) reduced in prefinal relative to pre-exposure samples and about tenfold lower in 80% of prefinal compared to pre-exposure samples (P < 0.0001). An overall 11-fold (median) downregulation in prefinal compared to pre-exposure samples was identified for most of the 27 genes and even FDXR appeared 4-14-fold downregulated in contrast to a pronounced up-regulation according to cited work. This pattern of overall downregulation of almost all genes and the rapid reduction of detectable genes at a prefinal stage was found in uninfected animals with normal range 18S rRNA as well. In conclusion, in a prefinal stage after lethal radiation exposure, the ribosome/transcriptome status remains present (based on normal range 18S rRNA values) in 60-67% of animals, but the whole transcriptome activity in general appears silenced and cannot be used for biodosimetry purposes, but probably as an indicator for an emerging prefinal health stage.

The association between hypertensive arteriopathy and cerebral amyloid angiopathy in spontaneously hypertensive stroke-prone rats

We aimed to test the hypothesis that in spontaneously hypertensive stroke‐prone rats (SHRSP), non‐amyloid cerebral small vessel disease/hypertensive arteriopathy (HA) results in vessel wall injury that may promote cerebral amyloid angiopathy (CAA). Our study comprised 21 male SHRSP (age 17–44 weeks) and 10 age‐ and sex‐matched Wistar control rats, that underwent two‐photon (2PM) imaging of the arterioles in the parietal cortex using Methoxy‐X04, Dextran and cerebral blood flow (CBF) measurements. Our data suggest that HA in SHRSP progresses in a temporal and age‐dependent manner, starting from small vessel wall damage (stage 1A), proceeding to CBF reduction (stage 1B), non‐occlusive (stage 2), and finally, occlusive thrombi (stage 3). Wistar animals also demonstrated small vessel wall damage, but were free of any of the later HA stages. Nearly half of all SHRSP additionally displayed vascular Methoxy‐X04 positivity indicative of cortical CAA. Vascular β‐amyloid deposits were found in small vessels characterized by thrombotic occlusions (stage 2 or 3). Post‐mortem analysis of the rat brains confirmed the findings derived from intravital 2PM microscopy. Our data thus overall suggest that advanced HA may play a role in CAA development with the two small vessel disease entities might be related to the same pathological spectrum of the aging brain.