Glycogen storage disease subtypes I and III (GSD I and GSD III) are monogenic inherited disorders of metabolism that disrupt glycogen metabolism. Unavailability of glucose in GSD I and induction of gluconeogenesis in GSD III modify energy sources and possibly, mitochondrial function. Abnormal mitochondrial structure and function were described in mice with GSD Ia, yet significantly less research is available in human cells and ketotic forms of the disease. We hypothesized that impaired glycogen storage results in distinct metabolic phenotypes in the extra- and intracellular compartments that may contribute to pathogenesis. Herein, we examined mitochondrial organization in live cells by spinning-disk confocal microscopy and profiled extra- and intracellular metabolites by targeted LC-MS/MS in cultured fibroblasts from healthy controls and from patients with GSD Ia, GSD Ib, and GSD III. Results from live imaging revealed that mitochondrial content and network morphology of GSD cells are comparable to that of healthy controls. Likewise, healthy controls and GSD cells exhibited comparable basal oxygen consumption rates. Targeted metabolomics followed by principal component analysis (PCA) and hierarchical clustering (HC) uncovered metabolically distinct poises of healthy controls and GSD subtypes. Assessment of individual metabolites recapitulated dysfunctional energy production , reduced creatinine export in GSD Ia and GSD III, and reduced antioxidant defense of the cysteine and glutathione systems. Our study serves as proof-of-concept that extra- and intracellular metabolite profiles distinguish glycogen storage disease subtypes from healthy controls. We posit that metabolite profiles provide hints to disease mechanisms as well as to nutritional and pharmacological elements that may optimize current treatment strategies. Glycogen storage diseases (GSDs) are a group of inborn errors of metabolism that result from defects in any of the enzymes involved either in glycogen synthesis or glycogen degradation , 2. GSDsG6PC gene (OMIM 613742)  (AGL gene (OMIM 610860)  en enG6PC g 613742) . Glycoge 602671) , which e 602671) . The maj 602671) , 12. Gly 610860)  that enc 610860) , 16. Pat 610860) , the mosde novo lipogenesis and a reduction in fatty acid oxidation  .Evidence of mitochondrial impairment was also provided in a study that measured enzymatic activities in lymphocytes of patients with GSD I, GSD III, GSD VI, and GSD IX . ResultsWhile previous studies point to a role of mitochondria in the pathogenesis of GSD Ia in mice, no studies have been performed in the other subtypes of hepatic GSDs or with human cells. This has prompted us to investigate mitochondrial morphology and function in skin fibroblasts from healthy controls, patients with GSD subtypes Ia and GSD Ib (both non-ketotic), and patients with GSD III, representing the most severe of the ketotic liver GSDs. Herein, we employ targeted metabolomics to gather information about energy producing pathways in GSD and to gain insights into underlying pathomechanisms.Our studies with human skin fibroblasts reveal that: a) Mitochondrial networks, volume and oxygen consumption rates are comparable in healthy controls and GSD types Ia, Ib, and III; b) Principal Component Analysis (PCA) and Hierarchical Clustering (HC) analysis of extracellular and intracellular metabolites permits the clustering of healthy controls versus GSD subtypes suggesting distinct metabolic poise in health and disease; and c) The concentration of metabolites of energy producing pathways  and antioxidant defense  suggest dysfunctional electron transfer in the respiratory chain, consistent with impaired mitochondrial function in GSD compared to healthy controls.Culture media, antibiotics, fetal bovine serum (FBS), reagents, solvents and buffers were used as directed by the respective manufacturers without further processing. Water (product Nr. 39253) and methanol (product Nr. 34966) for mass spectrometry were purchased from Honeywell . Stable isotopes for metabolomic analysis were purchased from Sigma-Millipore .Skin fibroblasts from healthy subjects were used and characterized in two previous studies , 23. Hea2 incubator at 37°C. Although dermal fibroblasts possess high metabolic activity even in their quiescent state  were cultured in DMEM low glucose supplemented with GlutaMax  for 3–5 days, trypsinized and 1000 cells were seeded in glass bottom cell culture dishes . Cells were grown overnight under standard conditions. Live cell staining was applied using MitoView™ 650  for mitochondria and Calcein™ AM  for cell body. Three independent batches of cells at three independent locations were imaged on three different days (one batch per day), for three healthy controls and the five GSD fibroblasts described in Analysis of mitochondrial organization and volume was performed by spinning-disk confocal microscopy . Cells were grown under standard conditions  and 60 z-planes (distance 0.31 µm) was recorded. Tile images were stitched together and deconvolved with Huygens software . The volume of mitochondria was estimated using the surface and statistics module of the software Imaris .Images from live cells were recorded using the ZEISS ZEN blue software  with the following conditions: incubation at 37°C with 5% COOxygen consumption rates were determined with a cell-impermeable phosphorescent oxygen probe . 96-well plates were seeded at a density of 50,000 cells per well. The cells were grown for 18 h in standard DMEM supplemented with 10% FBS. Measurement of fluorescence was performed with excitation set at 380 nm and emission at 650 nm, a delay time of 30 µs and a read time of 100 µs on a Tecan Infinite Pro plate reader set at 37°C. All samples were run in triplicates. Results from this measurement are shown in via de reaction of lactate dehydrogenase (LDH) in a sample of conditioned culture medium . Cells were seeded at a density of 30,000 cells per well. The cells were grown for 4 h in standard DMEM supplemented with 10% FBS (to enable cell attachment), and the medium was then replaced with DMEM supplemented with 1% FBS (reduction of FBS concentration minimizes the contribution of LDH in FBS). The assay was performed as directed by the manufacturer. Quantification was performed with a calibration curve with pure lactate 0–10 mM. All samples were run in triplicates. Secondly, lactate was identified and quantified by liquid chromatography mass spectrometry using a targeted metabolomic method for organic acids . Results of lactate concentration determined from colorimetric and LC-MS/MS methods are shown in Lactate is a marker metabolite of glycolytic activity that undergoes export into the extracellular medium. Production of lactate was monitored by two separate methods. Firstly, a colorimetric detection of lactate was carried out enzymatically x g for 10 min to remove dead cells and debris. Cleared conditioned medium was transferred into a clean 1.5 ml Eppendorf microcentrifuge tube and stored at -80°C for further processing, as described  for 5 days without medium exchange, harvested by trypsinization, and washed once with PBS by centrifugation. Dry cell pellets were frozen in dry ice and stored at -80°C for further processing, as described . On the escribed .2O (non-reducing conditions) or 20 µl DTT 0.5 M (reducing conditions), vortexed, and incubated at room temperature for 10 minutes. An aliquot of internal standard was added (20 µl) and metabolites were extracted by addition of 100 µl of 0.1% formic acid in MeOH .Mass spectrometry data was analyzed with the AnalystWe first examined the data by applying PCA, a multivariate statistical method that captures not only changes in individual metabolites between different groups, but it also assesses dependency between single metabolites , 28. PCASamples were also clustered accordingly to their metabolic profiles using HC. HC was also performed to cluster metabolites accordingly to their sample profiles.Oxygen consumption rates were estimated by fitting a double exponential curve to the measures of oxygen consumption over time.PCA and HC were carried out in R 3.6.3 . Curve fitting and boxplots were created using MATLAB version R2019b .Individual comparisons of absolute metabolite concentrations between healthy controls and GSD disease groups were performed with one-way ANOVA. The significance level was set to α = 0.05.Inherited diseases of glycogen metabolism are complex disorders characterized by systemic energy deficiency. In certain GSDs, specific organs such as liver and kidney exhibit structural abnormalities due to excessive glycogen deposition. While human hepatocytes and renal cells from patients with GSD are unavailable for research purposes, a few research laboratories and the Coriell Institute for Medical Research  have possession of dermal fibroblasts from patients with GSD. This precious source of primary cells from patients derives from an era prior to molecular genetic diagnostics, whereby performing skin biopsies was a routine procedure to diagnose patients . Herein,The organization of mitochondria in cultured fibroblasts was examined by spinning-disk confocal microscopy using a live-cell staining protocol that retained the fluorescent dyes for up to 72 h as described in methods. Under our culture conditions, mitochondrial network morphology was comparable between healthy controls and GSD cells  and conditioned culture medium (extracellular metabolites). Carbohydrate metabolism fuels major pathways of energy production in cells, so we examined glycolysis end product lactate, Krebs cycle intermediates, the methionine cycle and folate metabolites, the transsulfuration pathway and glutathione metabolism. Previous studies performed with animal models of GSD suggested increased oxidative stress in GSD. Therefore, we herein examined the two major low-molecular antioxidants in cells, namely, cysteine and glutathione in their oxidized and reduced forms, as well as their corresponding precursor metabolites that derive from the methionine cycle and the trans-sulfuration pathway. Because renal injury is a clinical feature of GSD I, we also determined creatinine. A total of 20 extracellular metabolites and 31 intracellular metabolites were measured by LC-MS/MS in a fully quantitative manner.The results of PCA for extracellular and intracellular metabolites are shown in To further identify common and distinct features between healthy controls and GSD disease groups, we carried out hierarchical clustering on the metabolite data. GSD metabolites grouped together to a common cluster that is mostly separated from the healthy control group , energy production (Krebs cycle), and redox homeostasis  among others. A total of 20 extracellular and 31 intracellular metabolites were measured in this study. PCA of metabolites enabled the clustering of control and GSD groups, which was further observed after HC of these datasets. Intracellular metabolite profiles provided a clearer grouping between healthy controls and GSD subtypes compared to extracellular metabolites. These findings reveal for the first time, that the cellular and extracellular metabolic compartments of GSD subtypes differ from that of healthy controls in humans.Analysis of metabolites that were ranked as major contributors to the first three principal components of PCA showed that the major elements impacted by GSD-causing mutations are glycolysis, Krebs cycle at the point of succinate, the entry substrate of mitochondrial respiratory complex II, and the status of the major intracellular antioxidant thiols cysteine and glutathione. This metabolic combination suggests increased demands for energy production with concomitant generation of reactive species that exhaust the antioxidant Cys and GSH systems, a scenario that reminisces futile redox cycling, i.e. electron leakage from the respiratory chain  reduces the transport of creatinine out of the cell. Besides its previous identification in fibroblasts  and its In sum, our study serves as proof-of-concept to further profile metabolism in GSD patients in cells, tissue and biological fluids. Gaining insights into the metabolic adjustments that occur upon disrupted glycogen metabolism may permit the dissection of profound consequences of pathogenic mutations that manifest essentially in all cell types, such is seen in fibroblasts, versus derangements that are specific to and modifiable in disease-relevant organs only, which could therefore be targeted for therapeutic purposes. Furthermore, access to quantitative metabolomics tools to investigate the response of cells and biological fluids to dietary management and current therapies opens new opportunities for personalized and optimized treatment of the complex and heterogeneous manifestations observed in GSD patients. In addition, this tool may be of great value to distinguish milder and severe disease phenotypes.Use of fibroblasts as cell type. While the usefulness of fibroblasts to study metabolic disorders is substantiated by the wide conservation of all pathways of energy metabolism in this cell type, and more specifically, of preserved glycogen storage phenotypes in early studies performed with human fibroblasts from GSD patients , furtherSize of cohort. This study examined one patient with GSD Ia, one patient with GSD Ib and three patients with GSD III. The small sample size of the study serves only as proof-of-concept to examine the metabolic behavior of the different impairments of glycogen storage metabolism in humans. Further studies with greater number of cells per clinical condition are necessary to validate our findings and extend conclusions at the population level.Cell culture conditions. Experimental cell culture conditions do not perfectly represent dietary exposure and glycemic control of GSD patients. Further analysis of metabolomic features in cultured cells that more closely mimic nutritional and physiologically relevant glycemic control in GSD are currently underway, using our herein established experimental conditions as a starting point.Targeted versus discovery “omics”. Our targeted metabolic profiling focused on known and predicted alterations of disrupted glycogen storage. It is possible that other metabolic pathways not covered in this study also contribute to pathogenesis for which untargeted “omics” approaches are desirable.The investigation of defective glycogen storage in human skin fibroblasts recapitulated features consistent with, albeit not identical to, mitochondrial dysfunction identified in animal models of the disease. The lack of structural defects in the mitochondria of GSD human skin fibroblasts may be related to organ specificity: previous studies performed in animal models examined the organelle in hepatocytes, representing the major organ affected by hepatic GSDs. Our findings together with results from the literature imply that systemic consequences of monogenic diseases of metabolism may have distinct impact on different cell types and organs, a proposal that is substantiated by the clinical manifestations of the disorders. Our studies identified metabolite features consistent with dysfunctional electron transport through the respiratory chain and dampened concentrations of cysteine and glutathione, the major low molecular weight antioxidants of the cell suggestive of increased oxidative stress. This proof-of-concept study opens opportunities for larger cohort studies with GSD patients where cells, tissue biopsies and biological fluids could be examined jointly to reconstruct the metabolic landscape of the disease and to possibly refine dietary and pharmacological treatment of the patients.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.LH, SG, and US conceived and planned the study. JT, VW, KK, IB, and LH performed experiments. LH supervised experimental work. LH, SG, IB, RN and US performed data analysis and wrote the manuscript. All authors contributed to the article and approved the submitted version.This work was funded with intramural support from the Department for Pediatrics, Center for Metabolism, Faculty of Medicine, Medical Center, University of Freiburg. SG acknowledges a research funding donation from Nutricia Metabolics. The article processing charge was funded by the Baden-Wuerttemberg Ministry of Science, Research and Art and the University of Freiburg in the funding programme Open Access Publishing.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Taken together, the study shows a novel perspective on high‐yield MVA virus production in conventional bioreactor systems linked to various cell retention devices and addresses options for process intensification including fully single‐use perfusion platforms.Modified Vaccinia Ankara (MVA) virus is a promising vector for vaccination against various challenging pathogens or the treatment of some types of cancers, requiring a high amount of virions per dose for vaccination and gene therapy. Upstream process intensification combining perfusion technologies, the avian suspension cell line AGE1.CR.pIX and the virus strain MVA‐CR19 is an option to obtain very high MVA yields. Here the authors compare different options for cell retention in perfusion mode using conventional stirred‐tank bioreactors. Furthermore, the authors study hollow‐fiber bioreactors and an orbital‐shaken bioreactor in perfusion mode, both available for single‐use. Productivity for the virus strain MVA‐CR19 is compared to results from batch and continuous production reported in literature. The results demonstrate that cell retention devices are only required to maximize cell concentration but not for continuous harvesting. Using a stirred‐tank bioreactor, a perfusion strategy with working volume expansion after virus infection results in the highest yields. Overall, infectious MVA virus titers of 2.1–16.5 × 10 Modified Vaccinia Ankara (MVA) virus is a viral vector used for gene therapies. Here, MVA virus is produced with AGE1.CR.pIX suspension cells using different platform technologies . The authors then compared and discussed the pros and cons between the different platform technologies, based on the virus production yields and other criteria such as scalability and process robustness. However, vaccine design is complex and challenging, and viruses are often difficult to produce. Viruses are obligate parasites and require a second biological entity, a host, for replication. As one consequence, for vaccine production, naïve host cells are required at high concentrations for infection with the respective virus strain, and both (naïve and infected cell) must be amenable for biotechnological manipulation. In addition, some viruses have an extremely narrow host range and require a special or even unique cell substrate. These properties call for the design and optimization of sophisticated process trains with carefully adjusted parameters in upstream (USP) and downstream processing (DSP).Viral vaccines are among the most cost‐effective medical interventions1 and  In addition, there are increasing demands for viral vectors that either express surface proteins for immunization or deliver foreign genomic information into their target cells for gene therapy. Viruses are ideal vehicles for delivery of genetic information, both for vaccine purposes and gene therapy. Issues that may affect synthetic DNA or RNA such as packaging and delivery of the payload, amplification at the target site, and expression of foreign genetic information in the face of cellular defenses are already inherent properties of the infectious cycle. Modified Vaccinia Ankara (MVA) virus is a promising viral vector for use against various infectious pathogens such as coronavirus, or for immunotherapy and the treatment of some types of cancers. MVA virus has been generated by adaptation to chicken embryo fibroblasts (CEF) and cannot replicate in human recipients. Because of this strong attenuation it is currently estimated that about 108 infectious units per dose are required for full vaccine efficacy. For large vaccine programs, the necessary yields are difficult to obtain with the conventional production substrate that was also used for stepwise MVA virus attenuation: CEF cultures consist of anchorage‐dependent primary cells with a limited lifespan and require animal‐derived components for growth in culture media. The latter involves, however, the risk of contamination with adventitious agents and should be avoided for use in current good manufacturing practice production. To circumvent this concern for production of MVA virus, an avian suspension cell line (AGE1.CR.pIX) has been developed previously, together with chemically defined media for batch production. The biphasic process is initiated with a cell seed train in true suspension culture to build up high cell concentrations for infection with virus seed at the final process scale. The subsequent virus production phase involves the addition of a  medium to induce suspended cell aggregates to facilitate virus spreading, as a large fraction of the infectious poxviruses are disseminated by direct cell‐to‐cell contact. Induction of aggregates improves virus yields and has been shown recently to enable safe and cost‐efficient production of vaccine candidates. To facilitate process intensification and enable continuous virus harvesting an MVA virus strain with reduced dependency on direct cell‐to‐cell contacts would be beneficial. Such a strain, MVA‐CR19, has been obtained with help of the avian suspension cells that are used in the present study.Conventional viral vaccine production relies on the production of wild‐type or attenuated viruses for vaccination.4, 56 cells mL−1), and on continuous cultivations at low cell concentrations . High cell concentrations reached in the bioreactor through the use of perfusion systems potentially allows for higher virus titers, as long as the cell‐specific virus yield (CSVY) is kept high. In this regard, many studies have already been conducted in academic groups for virus production in perfusion cultures. More specifically, Vazquez et al. (2018) showed that AGE1.CR.pIX cells proliferate to high cell concentrations in perfusion mode using a system that consisted of a stirred‐tank bioreactor (STR) coupled to a membrane‐based alternating tangential flow (ATF) device (STR‐ATF system). This system led to successful production of the MVA‐CR19 virus strain. In addition, it was shown that pseudo perfusion in shake‐flasks (SFs) was possible and virus yields comparable to the production in the ATF system. With this scale‐down model, screening and optimization of different feeding strategies improved virus productivity. A follow‐up study showed that this optimized strategy could successfully be transferred into a bioreactor set‐up leading to a hybrid perfusion process combining a perfusion strategy at HCD (>25 × 106 cells mL−1) during the whole run with working volume (Vw) expansion after virus infection (STR‐ATF hybrid perfusion system).Based on these developments, new options for process intensification were available. In this study we focused on cell cultures at high viable cell density (HCD) using fed‐batch or perfusion strategies (above 25 × 10ls mL−1),21 and However, it has been hypothesized that virus retention can potentially decrease the productivity through unspecific virus degradation. Hence, a continuous virus harvesting during the perfusion process should reduce virus inactivation. To test this hypothesis, we investigated two options for cell retention that are not membrane‐based, known as acoustic settler (AS) and inclined settler (IS), and coupled them to a STR (STR‐AS and STR‐IS system). Both systems were operated under optimized process parameters determined previously for influenza A virus production. Compared to the membrane‐based STR‐ATF system, STR‐AS and STR‐IS systems enabled continuous virus harvesting.Although a successful membrane‐based perfusion system for MVA virus production was established, various other aspects needed to be addressed to further improve productivity. The first aspect was the possibility to harvest continuously the virions released. With an average MVA virus diameter of about 450 nm, the choice of the membrane cut‐off was crucial, as most membranes were designed for removal of recombinant proteins with relatively low molecular weight. Therefore, when using ATF systems, MVA virus retention inside the bioreactor was typically the resulting scenario, even when using polysulfone (PS) and polyethersulfone (PES) hollow‐fiber (HF) membranes with pore sizes going up to 0.65 μm in perfusion mode.27 How The second system involved a small‐scale hollow‐fiber bioreactor (HFBR), again operated with process parameters based on a previous study for influenza A virus production allowing here, as well, MVA virus production in perfusion mode. As both studies were designed only as scouting experiments without further optimization a fair comparison of productivities is difficult. Nevertheless, these platforms are available and show a high potential for success after further optimization.The second aspect concerned the option of MVA virus production in perfusion mode using exclusively single‐use material. Considering production of MVA vectors for timely vaccine development against emerging diseases or pandemics such as COVID‐19, it would be very important to quickly set‐up high‐yield production facilities at the place of highest need. In addition, single‐use disposable components could easily be installed in laboratory containers or within hospital settings. We therefore established two different perfusion systems that are commercially available in single‐use and evaluated their performance in a few, non‐optimized scouting runs. The first system involved a single‐use orbital‐shaken bioreactor (OSB) coupled to a single‐use ATF system (OSB‐ATF system). Process conditions were adapted for MVA virus propagation in AGE1.CR.pIX cells following a previous study for influenza A virus production.30 TheFinally, the various options for intensification of MVA virus production are compared. For reasons of comparability, we focused on AGE1.CR.pIX cell‐based processes to identify the most promising cultivation strategy. To allow for a fair comparison, virus production yields and virus titers were calculated following the same method. Overall, a whole set of process options is now available, not all fully optimized, but all with high potential to establish a large‐scale manufacturing platform for intensified MVA virus production.2 Here, two different cell retention devices (AS and IS) were tested for continuous virus harvesting, and options for fully single‐use perfusion operation were also evaluated. Based on the newly generated data and recently published data, virus yields were calculated and compared to different intensified MVA virus production modes , run 2 and 3 (STR‐AC), and run 4 (STR‐IS). After infection, the perfusion rate was kept constant at an average of 1.65 (± 0.25) day−1 for runs 1–4. The process parameters selected, corresponded to optimized parameters for the specific cell retention device reported earlier for MVA virus production in perfusion mode, see Section 4.Cells were cultivated in a STR coupled to either an ATF system, an AS or an IS. To allow for a better comparison, the same cell line (AGE1.CR.pIX) with the same virus seed (MVA‐CR19.GFP) were used, and cultures were always infected at a cell concentration between 20 × 10ion mode,33 seeFigure 6 cells mL−1 for the STR‐ATF versus 36 and 33 × 106 cells mL−1 for the STR‐AS and STR‐IS, respectively). A decrease of cell concentrations and cell viabilities was observed about 36 h post infection (hpi) for all the three different cell retention devices  and ammonium levels (<2 mm), which are the two main by‐products of cellular metabolism, were observed. No limitation in glucose concentration (>10 mm) was observed for runs 1, 2, and 4 , CSVY, and volumetric virus productivity (Pv) were determined  were detected. The maximum Cvir, tot was observed for all the runs between 48 and 72 hpi  assays (±0.3 log10 (virions mL−1)), the differences are not significant. The same trend was observed for the Pv, where a yield of 1 × 109 virions L−1 day−1 was obtained for the ATF, again with a variation in yield for the other cell retention devices within the error of the assay , which corresponded to the time between the start of virus release into the supernatant and the maximum Cvir, tot  coupled to an ATF system (run 5), and the HFBR (PRIMER system from Biovest Intern. Inc.) (runs 6–7). The single‐use OSB was connected to an ATF system as no advantage regarding a virus yield, CSVY or Pv was observed with other cell retention devices as shown above  using the same cell line (AGE1.CR.pIX) and same virus strain (MVA‐CR19)  reached a maximum cell concentration after infection above 40 × 106 cells mL−1 while a lower cell concentration was obtained for the STR‐ATF system . However, a low maximum Cvir, tot of 6.0 × 107 virions mL−1 was achieved for the OSB‐ATF compared to the STR‐ATF control runs 8–9 (5.6–8.0 × 109 virions mL−1)  Figure . This le1 Figure .6 cells mL−1 except at the end of the run where cell concentrations in the range 22–38 × 106 cells mL−1 were reached due to thorough flushing of the HFBR system, detaching a large quantity of the cells adherently growing on the hollow‐fiber (HF) membrane , cell growth dynamics differed clearly compared to the control runs 8–9. The cell concentration remained constant after infection up to 5 × 10e Figure . Therefos Figure . Similars Figure . As the r Figure .2.3Figure  obtained for other production platforms and production modes , and the total number of cells present during the virus infection phase.s Figure  to compavir, tot was achieved for MVA virus production in batch culture, although virus concentrations increased as soon as eight days post infection  for the large‐scale hybrid perfusion system compared to the pseudo hybrid perfusion system in SFs. A fourfold decrease in Cvir, tot was observed when scaling‐up from the two‐stage semi‐continuous SF cultivation system to the two‐stage continuous STR cultivation system, also after 90 days of process time  was observed for the use of AS or IS cell retention devices allowing continuous harvesting  was achieved. Non‐toxic levels of released metabolites (<20 mm lactate and <3 mm ammonium) were observed regardless of the cell retention device, demonstrating a healthy state of the cells allowing high productivity after infection as already observed in previous studies , no decrease in Cvir, tot was observed 72 hpi for the AS or the IS based processes, which might offer a larger flexibility regarding the time of harvest compared to the ATF run , the specific growth rate of AGE1.CR.pIX cells in OSB‐ATF was equal to that in conventional STRs coupled to an ATF system. However, for the scouting experiment performed here with the OSB‐ATF system, only low titers were obtained. Furthermore, the cell concentration increased strongly after infection when using the OSB (42 vs 28 × 106 cells mL−1). This might indicate that only a small percentage of cells was infected by the MVA virus—probably due to the non‐optimal multiplicity of infection (MOI) caused by the lack of seed virus for the chosen Vw of the OSB  in single‐use systems, but that further optimization would be needed to achieve titers comparable to STR‐ATF system.The establishment of single‐use virus production systems in perfusion mode presents many advantages over traditional batch processes in stainless steel bioreactors, that is, reduced operating and validation costs coupled with the avoidance of clean‐in‐place and steam‐in‐place methods.,42 FB Figure . This is6 cells mL−1 based on the known cell concentration per cm2 of confluent T‐flasks, and measured a cell concentration of 28 × 106 cells mL−1 in the same HFBR system (in the same range as here: 22–38 × 106 cells mL−1). A similar comparison could be performed for AGE1.CR.pIX cells. An increase of the CSVY was, however, expected in our case as adherent cells tend to allow for higher CSVY in general.The CSVYs obtained with the HFBR seemed comparable to control runs Figure  althoughls mL−1).31 A s and virus production in perfusion mode is that the virus cannot be produced over extended periods as virus infection involves apoptosis and cell lysis. For the establishment of a truly continuous system, two interconnected bioreactors are needed, one for cell growth and one for virus production. This raises the question if the footprint of a plant can also be reduced when production requires several consecutive runs in perfusion mode to harvest an equal number of virions (compared to a run in continuous mode or consecutive runs in batch). In order to evaluate the various options for virus production, not only the increase in Cvir, tot and Virtot over time should be considered, but also many other aspects such as process complexity or robustness, as listed in Table One major difference between recombinant protein production,,44Batch cultures and cultivations in the STR‐ATF system show most advantages regarding MVA virus production as illustrated in Table vir, tot compared to the batch, perfusion, and continuous systems were obtained with the HFBR, making this production platform one of the best options in terms of Cvir, tot after 19 days  are available. This is, however, only a scale‐up factor 42 compared to the tested HFBR bioreactors could circumvent scale‐up issues.50Cultivations using the OSB‐ATF system resulted in rather low production yields Figure . Furtherv, Virtot, or CSVY have to be rather large to be considered significant. Accordingly, our investigation (and other similar studies on virus production) can only serve as a first orientation regarding the set‐up of process platforms for large‐scale manufacturing. Nevertheless, it can serve as a first orientation regarding the pros and cons of a large number of process options, and provide a solid basis for a more detailed process intensification approach.A limitation of our approach is the limited number of cultivations performed for each set‐up. As it is often the case for complex biotechnological processes, reproducibility can be an issue. In addition, due to the rather large error of infectivity assays used for virus quantification (Section 4), differences in P However, to our knowledge, no such study was performed for virus production, so far. Also, besides large‐scale production of MVA virus based vaccines, smaller scale applications in gene therapy should be considered in future studies. Software like SuperPro Designer  could support this and allow to identify key factors limiting the use of particular production systems. Finally, for a complete analysis, DSP should also be integrated, which would further increase the level of complexity.Another limitation of the present study is the lack of a cost‐effectiveness analysis when evaluating the different process options. Various studies have used static or dynamic models to compare costs of fed‐batch and perfusion strategies in recombinant protein production.54 How However, in this case, neither the DSP technique and DSP yield nor DSP costs per dose were influenced by the intensification of the USP. Thus, the overall impact of DSP on the economical modelling was considered to be negligible.Intensified USP with increased MVA virus titers can have a significant impact on the DSP. Depending on unit operations established for conventional MVA virus‐based processes, it might be required to modify DSP, that is, cell clarification and product concentration steps before chromatography‐based operations are used. In fact, DSP efficiency might be the criterion for the selection of the appropriate USP platform for an end‐to‐end virus production process. For example, lower yields in virus clarification or a higher number of DSP unit operations might be needed, potentially reducing the overall production yield and the economical attractiveness of the selected USP production platform. A recent study evaluating different production platforms for adeno‐associated virus estimated DSP costs to be equal to about 40% of the overall cost of good per dose for a 1000 L suspension cell culture in batch.55 How In particular, the presence of such large‐sized aggregates might impair clarification and subsequent chromatography steps developed for normal batch USP conditions. As dilution by continuous harvesting decreases proteins, host‐cell DNA and the virus concentration in the medium, STR‐AS perfusion and STR‐IS perfusion might facilitate DSP in general. For the two‐stage continuous STR, the purification yield is expected to be similar to batch STR as similar virus titers are obtained in the harvest. Regarding the amount of process‐related impurities per produced dose, it was observed for influenza A virus production that the amount of host‐cell DNA and total protein per virions was not changed when producing the virus with a STR batch, a STR‐ATF perfusion, or a STR‐AS perfusion. Further studies would be needed to tackle the purification processing following intensified USP.Scouting experiments performed by our group did not result in a significant decrease in yields for the purification of MVA virus from STR‐AS perfusion harvests or STR batch cultivations using steric exclusion chromatography (data not shown). However, a recent study of our group indicated possible issues with influenza A virus production in a STR‐ATF system where higher titers and product accumulation in the bioreactor resulted in the formation of large virus aggregates in contrast to a STR‐AS perfusion system allowing continuous harvesting.28 In v, scalability, process robustness, and options for single‐use manufacturing. Once optimized, however, a two‐stage continuous STR cultivation system might offer the highest potential for production of large volumes as it allowed to achieve the highest number of cells during the infection phase, which is necessary for obtaining maximum virus yields. Batch processes have still various advantages compared to cultivations performed in STR‐ATF systems , 2 mm L‐alanine , and 10 ng mL−1 recombinant insulin‐like growth factor .The virus strains MVA‐CR19 and MVA‐CR19.GFP were provided by ProBioGen AG (Germany). For virus propagation, the immortalized avian suspension cell line AGE1.CR.pIX  was cultivated in CD‐U3 medium  supplemented with 2 m Glucose, glutamine, lactate, and ammonium concentrations were measured using a Bioprofile 100 plus .Viable suspension cell concentration and percentage viability were determined using a Vi‐CELL XR . Cells in the HFBR system, not growing in true suspension, were counted as described earlier.31 Glu50 assay was performed as described by Nikolay et al. (2020) with a standard deviation of ± 0.3 log10(virions mL−1). For virus titration of the MVA‐CR19 virus strain, the TCID50 was performed as previously described with a standard deviation of ± 0.4 log10(virions mL−1). ThePv in virions L−1 day−1 and the CSVY in virions per cell were calculated as described previously by Granicher et al. (2020). For the specific case of the HFBR system, the CSVY was calculated taking into account the total number of cells produced as described previously for influenza A virus production with MDCK cells. The concentration of infectious MVA virions produced  was calculated as follows:tot, the total number of virions produced in the harvest vessel and in the bioreactor  as described by Granicher et al. (2020) and Vw, the working volume. For continuous processes, Virtot values were added up over time. Note, on a linear scale and considering only the error of the TCID50 assay for the MVA‐CR19.GFP virus strain, an error of 100% for the upper value and 50% for the lower value has to be taken into account for Cvir, tot, Virtot, CSVY, and Pv.For virus titration of the MVA‐CR19.GFP virus strain, a TCIDl. (2020)26 wit Briefly, cells were cultivated until a cell concentration of 4 × 106 cells mL−1 was reached. The cell culture was then diluted by a factor of two with fresh medium and infected at a MOI of 0.05 virions per cell. The virus was treated before infection in a sonication water bath for 1 min at 45 kHz to avoid aggregate formation.For an optimal MVA virus production in batch mode, a strategy described previously was used.57 Bri6 cells mL−1. During the cell growth phase, a constant cell‐specific perfusion rate of 0.06 nL cell−1 day−1 was manually adjusted via the perfusion rate . At the time of infection, the cell culture medium was renewed with fresh cell culture medium by increasing the perfusion flow rate for 3 h before infection. As for batch processes, an MOI of 0.05 was used with a sonicated seed virus, except for the large‐scale OSB‐ATF system. Due to seed virus limitation, an MOI of 0.01 was used in this case.Cells were cultivated to a viable cell concentration of 25–50 × 10n day−1).26 At w  were used as described previously. The cell culture was centrifuged each time and the cell culture free supernatant was removed and replaced with fresh CD‐U3 medium.For small‐scale pseudo perfusion cultivations in HCD, baffled SFs with 50 mL Veviously.26 The A polyethylene sulfone HF membrane  was used for the ATF mode. The exchanged volume flow rate was equal to 0.9 L min−1. When producing the MVA virus with an AS , perfusion was performed as previously described for influenza A virus production in perfusion mode. An acoustic power of 3 W was applied for efficient cell retention. In another setting, an IS  was used as described by Coronel et al. (2020). The IS was operated at a recirculation rate of 35 mL min−1, intermittent vibration  and with 30° angle. Water at a temperature of 27 °C was recirculated for heat exchange. The ATF, AS, or IS cell retention devices were coupled to a 1 L STR . Settings for cultivations were pH 7.2, dissolved oxygen (DO) 40% and 120–180 rpm (pitched blade impeller). DO and pH were controlled by sparging of O2 and CO2, respectively.For membrane‐based perfusion, an ATF2 system  was used as described previously for MVA virus production.33 A pw: 10 L, Adolf Kühner AG) was operated as described previously for HCD influenza A virus production. For perfusion operation, an ATF2 controller (Repligen) together with a single‐use PES HF membrane  was used. In order to maximize productivity, a hybrid perfusion mode approach was adopted as described by Vazquez et al. (2019). Briefly, the Vw was increased from 5000 to 6300 mL during the infection phase while keeping the perfusion at steady‐state. In a second set‐up, a HFBR  was used and operated as described previously by Tapia et al. (2014) for influenza A virus production. Medium was recirculated constantly in the HFBR and multiple virus harvests inside of the bioreactor were performed. Temperature was kept at 37 °C, and the pH was monitored and manually controlled between 7.2 and 7.4.For the scouting experiments regarding single‐use perfusion bioprocesses at laboratory scale, the OSB‐ATF system . The TCID50 titer was measured after 6, 12, and 24 h, in triplicate.To investigate the MVA virus stability, cell culture supernatant with an initial virus titer of 3.06 × 10G.G., F.T., I.B., Y.G., and U.R. declare that they have no conflict of interest. I.J. is an employee of ProBioGen AG which has established the AGE1.CR.pIX cell line and developed the MVA‐CR19 virus strain.GG, FT, IJ, YG and UR contributed conception and design of the study. GG, FT and IB performed the experiments. GG, FT and YG analyzed the data. GG, IJ and YG wrote the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.


Plant viruses are biologically safe for mammals and can be successfully used as a carrier/platform to present foreign epitopes in the course of creating novel putative vaccines. However, there is mounting evidence that plant viruses, their virus-like and structurally modified particles may also have an immunopotentiating effect on antigens not bound with their surface covalently. Here, we present data on the adjuvant properties of plant viruses with various shapes  and structurally modified TMV spherical particles (SPs). We have analysed the effectiveness of immune response to individual model antigens  and to OVA/HEL in compositions with plant viruses/SPs, and have shown that CaMV, TMV and SPs can effectively induce total IgG titers to model antigen. Some intriguing data were obtained when analysing the immune response to the plant viruses/SPs themselves. Strong immunity was induced to CaMV, BMMV and PVX, whereas TMV and SPs stimulated considerably lower self-IgG titers. Our results provide new insights into the immunopotentiating properties of plant viruses and can be useful in devising adjuvants based on plant viruses. In recent decades, possible applications of plant virus particles and their virus-like particles (VLP) in vaccine development have been studied intensively5. Some features of plant virus particles’/VLPs’ structural organisation and size allow them to effectively stimulate the immune system7. Plant virus particles’ immunostimulatory properties can be explained by the fact that they consist of proteins, which are phylogenetically distant and immunologically alien to the mammalian immune system8. However, an organised regular spatial structure is considered to be even more important8. In a number of studies, disassembled coat protein (CP) has been demonstrated to be less immunogenic than virions and VLP11. Effective uptake by professional antigen-presenting cells (APCs) and transportation to lymph nodes has been shown for TMV, wherein its particulate structure has been a key factor13. Therefore, it is likely that CP polymers of plant viruses and their VLP act as pathogen-assoсiated molecular patterns, which are recognised by innate immune receptors11. Thus, plant virus can mediate the uptake of target antigen by APCs and thereby promoting the following induction of humoral and cell immune response to that antigen6. Nucleic acid, as a constituent part of a plant virus, and some virus-like particles may also contribute to an immune response by stimulating innate immunity receptors, 16.The unique properties of plant viruses, including their ability to self-assemble and biosafety for mammals and humans, make them an exceptionally attractive and versatile tool for biotechnology3. However, there is some evidence that the plant viruses/VLP and the plant virus structurally modified particles can possess adjuvant properties without covalently binding of an antigen/epitope to their surface21.In the majority of studies focused on the design of plant virus-based vaccine candidates, plant viruses/VLP are used as a carrier/platform for the multiple presentation of a desired antigen/epitope onto the particle surface as part of a CP. In this case the foreign amino acid sequence is fused to the viral CP and attachment is usually achieved by means of genetic engineering or chemical conjugation27. The heating of a rod-shaped tobacco mosaic virus (TMV) leads to the transition of virions into spherical particles (SPs). Adjusting the initial concentration of TMV enables SPs of a given size to be obtained24. We have shown that the SPs can form complexes with proteins, polymers or even small viral particles by simple adsorption alone30. One of the most interesting properties of SPs is their ability to enhance the immune response to the antigen adsorbed onto their surface21. Notably, SPs have been reported to improve the protectivity of the inactivated rabies vaccine. This effect has been demonstrated to be comparable with the effect of an incomplete Freund’s adjuvant on the same vaccine31. In another work, we have demonstrated that SPs had no toxicological effects on mice, rats and rabbits33.Our group has been intensively studying the properties of structurally modified particles formed by the thermal remodelling of helical plant viruses34. As discussed above, the plant viruses/VLP and SPs could be promising candidates for contributing to the design of novel adjuvants.Modern vaccinology focuses on searching for effective, safe and low-cost adjuvants35. Ovalbumin (OVA) and hen egg lysozyme (HEL) were selected as model antigens. These proteins are non-infectious antigens and are widely used in studies of adjuvants and delivery systems38. OVA is also known as a poor immunogen37. In our research, we decided to administer relatively low doses of antigens (5 μg per dose), for better discrimination of the differences between potential adjuvants, and so that the total protein dose in immunogenic compositions would be clinically acceptable.Here, we present the first comparative study of the adjuvant properties of plant viruses with different structure, size and shape, and TMV SPs. We used two helical RNA plant viruses, rod-like TMV and filamentous potato virus X (PVX), and two icosahedral viruses, cauliflower mosaic virus  and bean mild mosaic virus . The dose of plant viral particles (100 μg) was selected according to the previous studies on the immunostimulant properties of plant viruses and SPs39, pI 4.6–4.940) and OVA-plant virus/SPs compositions , five  and five  times, respectively, in comparison with free OVA , with PBS, OVA  with a lower molecular weight (14 kDa)42 and a higher pI (11.35)43. As the potential adjuvants, we used the following viruses: CaMV, which showed high immunostimulation efficiency with OVA; PVX, as we expected that it would reveal adjuvant potential with HEL; BMMV, a virus which has a similar shape and size to CaMV. However, unlike CaMV, the genome of BMMV is represented by RNA. The mice were inoculated at days 0, 15, 29 s.c. with PBS, HEL and HEL-plant virus compositions . PVX again did not exhibit any effective adjuvant properties.Adjuvants may have different immunostimulating effects on various antigensons Fig.  and the ons Fig. , Fig S3eons Fig. . Blood wr pI 11.343. As thRegardless of the effectiveness of anti-HEL IgG stimulation, sera from groups 9, 10 and 11 were analysed for the presence of plant virus self-IgG. In this experiment, all viruses elicited a relatively high self-immunity after immunisations in composition with HEL: IgG titers to BMMV – 287668 Fig. ; IgG tit45. The necessity to have safer and more effective vaccines drives the development of novel non-replicating forms. However, this type of vaccines often has an insufficient immunogenicity and requires the addition of various adjuvants, which play an essential role in improving the immune response to vaccine components46.Vaccines are powerful tools to control and prevent infectious diseases in humans and animals47. However, these adjuvants are relatively weak in the antibody induction to certain antigens and in the induction of the Th1-immune response necessary to combat intracellular pathogens. Aluminum adjuvants have been reported to affect the physical and chemical stability of vaccine antigens over time and even to accelerate protein degradation49. Furthermore, aluminum salts are able to decrease the immunogenicity of vaccines but increase local reactogenicity50. In this regard, the search for both safe and effective adjuvants is a pressing issue worldwide.Aluminum compounds are the most widely used adjuvants in human vaccines52. The adjuvant properties after simple mixing with antigens have already been shown for papaya mosaic virus virions and VLP, and for the structurally modified spherical particles of tobacco mosaic virus (SPs)21. Here we report on the adjuvant potential of plant viruses of various shapes, sizes and structure using OVA and HEL as the model antigens.Plant viruses, their VLP and structurally modified virus particles are promising candidates for the development of new generation adjuvantsTobamovirus, Virgaviridae), filamentous PVX  and spherical CaMV  as potential adjuvants and OVA as a model antigen. SPs were applied as a platform and potential adjuvant, whose immunostimulating properties have been shown previously31. In our preceding works we have described the adjuvant properties for SPs of size 100, 300 and 500 nm21. We have not revealed any distinctions in the immunostimulating properties of SPs of different sizes18. Here, we have used SPs with a mean diameter of 611 nm. It is important to emphasise that TMV and PVX are widely used to obtain chimeric virus particles (ChVP) displaying the epitopes of different pathogens53. For TMV and PVX ChVP, the immunostimulating effect has been demonstrated on fused epitopes58 even without any additional adjuvants60. Athough OVA is a relatively weak immunogen, here, we have demonstrated TMV, CaMV and SPs increasing anti-OVA IgG titers by nine, 13 and 15 times respectively, in comparison with the OVA alone. Unexpectedly, no differences in IgG titers between mice immunised with individual OVA and a composition of OVA + PVX were revealed. Thus, in addition to SPs, whose ability of which to improve immune response to non-covalently bound antigens has already been described, an effective adjuvant potential was shown for CaMV and TMV simply mixed with OVA.In our first experiment, we used rod-shaped TMV (61. Some carriers (for example poxviruses and adenoviruses) can suffer from self-antibodies, in particular from pre-existing antibodies which can cause a clearance of virus/protein-based carriers by neutralising antibodies64. However, it has been shown for chimeric TMV, PapMV, cowpea mosaic virus and flagellin, that the existence of specific antibodies does not interfere with their immunostimulating properties65. Thereby, we found it necessary to evaluate IgG titers to adjuvants we examined. In the sera from group 3 (OVA + SPs), IgG titers to SPs were low, but showed a statistically significant difference with titers in the group immunised with PBS . Probably, the low titers to SPs associated with the formation of SPs complexes with OVA , with high IgG titers to OVA, anti-TMV IgG were considerably low and did not differ statistically from the sera titers of group 1 (PBS). Interestingly, in contrast to TMV, another helical plant virus, PVX, induced a relatively high self-immune response in the absence of effective stimulation of IgG to OVA. In group 5 (OVA + CaMV), there was a fairly strong humoral response against CaMV. Thus, we did not identify any linkage between the effectiveness of the immune response to a model antigen and self-immunity. However, CaMV was the only virus for which we did not detect any visible interaction with OVA 17. In our experiment with HEL, CaMV was selected as a potentially effective adjuvant. We also chose another icosahedral virus, bean mild mosaic virus , which has a similar size of virions to CaMV, but different genomic nucleic acid  and BMMV 68. For group 11, being immunised with HEL + PVX no significant differences in sera IgG titers were detected in comparison with group 8, which was immunised by individual HEL. In comparison with CaMV, PVX induced 22 times lower anti-HEL IgG titers. In this experiment, all viruses induced a relatively high self-immunity: TEM allows to suppose, that the considerably high immune response to CaMV was attributable in part to the absence of observable binding between HEL and CaMV  was used for size calculations.The samples were obtained and analysed, as described previously, by TEM microscopes JEOL JEM-1400, JEM-1400Flash and JEM-1011, and 2% uranyl acetate was used as a contrast agent. Samples of free SPs did not contrastAll mice experiments were conducted in accordance with experimental practices and standards accepted by the Ethics Committee of the Institute of Gene Biology, Russian Academy of Sciences. Groups of CD1 mice (n = 6) were immunised s.c. with either 5 μg of OVA  or 5 μg of OVA with 100 μg of SPs/TMV/PVX/СaMV in a total volume of 0.2 ml. The control group of CD1 mice (n = 5) was immunised with PBS. In a separate experiment, groups of CD1 mice n = 4–7) were immunised s.c. with either PBS, 5 μg of HEL  or 5 μg of HEL with 100 μg of СaMV/BMMV/PVX in a total volume of 0.2 ml. The schedule of immunisation and blood collection is presented in the Fig. –7 were i2SO4, OD measured at 450 nm. A positive titer was defined as three standard deviations above the mean value of the block. The geometric mean titers were calculated for each group.Microplates  were coated with 10 μg/mL of OVA/ SPs/TMV/PVX/BMMV, 150 μg/mL of HEL or 1 μg/mL of CaMV and then blocked with a PBS containing 1% skimmed milk. Murine sera were diluted in PBS with 1% skimmed milk and titrated with 1:3 dilutions. Anti-mouse HRP conjugates  against IgG (ab6728), IgG1(ab97240), IgG2a (ab97245) and IgG2b (ab97250) were used in a dilution of 1:10000 and anti-mouse HRP conjugate against IgG3 (ab97260) was used in a dilution of 1:5000. Staining was performed using 3,3′,5,5′-tetramethylbenzidine substrate . The reaction was quenched by the addition of 2 M H72. The statistical tests used in each individual experiment have been indicated in the captions to the figures. Probability values  of less than 0.05 were considered to be significant.For multiple comparisons, the Kruskal-Wallis test and a post hoc Dunn’s test were used. The Exact Wilcoxon-Mann-Whitney Test Calculator was used to compare differences between two groups and when comparing the non-adjuvanted group with the other groupsSupplementary Information.


Despite the rapid uptake of genomic technologies within cancer care, few studies provide detailed information on the costs of sequencing across different applications. The objective of the study was to examine and categorise the complete costs involved in genomic sequencing for a range of applications within cancer settings.We performed a cost-analysis using gross and micro-costing approaches for genomic sequencing performed during 2017/2018 across different settings in Brisbane, Australia. Sequencing was undertaken for patients with lung, breast, oesophageal cancers, melanoma or mesothelioma. Aggregated resource data were captured for a total of 1433 patients and point estimates of per patient costs were generated. Deterministic sensitivity analyses addressed the uncertainty in the estimates. Estimated costs to the public health system for resources were categorised into seven distinct activities in the sequencing process: sampling, extraction, library preparation, sequencing, analysis, data storage and clinical reporting. Costs were also aggregated according to labour, consumables, testing, equipment and ‘other’ categories.The per person costs were AU$347–429 (2018 US$240–297) for targeted panels, AU$871–$2788 (2018 US$604–1932) for exome sequencing, and AU$2895–4830 (2018 US$2006-3347) for whole genome sequencing. Cost proportions were highest for library preparation/sequencing materials , sample extraction (8.1%), data analysis (9.2%) and data storage (2.6%). Capital costs for the sequencers were an additional AU$34–197 (2018 US$24–67) per person.Total costs were most sensitive to consumables and sequencing activities driven by commercial prices. Per person sequencing costs for cancer are high when tumour/blood pairs require testing. Using the natural steps involved in sequencing and categorising resources accordingly, future evaluations of costs or cost-effectiveness of clinical genomics across cancer projects could be more standardised and facilitate easier comparison of cost drivers. Sequencing the human genome using the first-generation Sanger sequencing techniques from 1977 took nearly 15 years, required extensive collaboration between hundreds of laboratories around the world and was reported to cost US$100 million , 3. GenoThere is significant interest in genomic sequencing in oncology due to its potential to advance diagnostics and personalise treatments, as well as to improve our understanding of treatment responses and the causes and mechanisms of tumour development. Clinical genetic testing for gene panels is routinely occurring in melanoma of the skin, colorectal cancers, and breast cancers . The natGenomic sequencing for medical diagnosis and decision-making is often considered for public funding within an economic evaluation framework –11. EconExamining the costs of genomic sequencing in patients with cancer is important because the process is more complex in cancer than in other diseases. Cancer genomics often involves sequencing both tumour and germline  samples to identify pathogenic variants. A recent Canadian study analysed patient-level data over 3 years on a mixed cancer cohort and found whole genome sequencing costs of CA$34,886  per patient  while coWith the improvements in genomic sequencing technologies, automation processes and computing, the price of genomic sequencing is falling and some claim it has reached the ‘$1000 genome’ level . Recent In light of the variation in cost-analysis reporting and due to the limited number of studies available, we undertook a cost-analysis on genomic sequencing currently occurring for patients with cancer. By reporting costs in a more standardised way, the aim of our analysis was to compare costs of sequencing across different genomic technologies and identify the main drivers of per-patient costs.Six genomic sequencing cancer applications were selected for this analysis, based on data availability. Selected applications were comprised of targeted panel, exome and whole genome sequencing technologies. Using six applications of genomic sequencing and different cancer types helps to assess the variability by cancer type. We employed a combination of gross costing (aggregated resource use for a group and separated into per patient units) with micro-costing (units per patient) and valued using a bottom-up approach  . Micro-cA cost-analysis has three steps: 1) identifying the resources used; 2) measuring, counting or allocating them to units of output and; 3) applying monetary estimates. Included in this analysis were the costs of obtaining the tissue sample through to providing the test information to the clinician , melanoma or lung cancer (745 tumour samples), oesophageal cancer (100 blood/tumour matched samples), lung cancer (10 blood tumour matched samples) breast cancer (192 blood samples) or mesothelioma (3 blood/tumour matched samples). For each setting, we collected data from laboratory staff, project records and public hospital databases  sampling, 2) DNA extraction, 3) library preparation, 4) sequencing, 5) analysis, 6) data storage and; 7) reporting to clinicians. Generation of a final report summarising the results of sequencing was included in step 5 ‘analysis’. We estimated short-term storage of sequencing data  on the basis of ‘near line’ or infrequent use of cloud storage at USD 0.01 per gigabyte (GB) and we tested for ‘regional’ or frequent use at USD 0.025 per GB and ‘coldline’ or very infrequent use USD 0.007 per GB in sensitivity analysis. Due to library preparation and sequencing steps being outsourced to commercial providers in three projects, no breakdown of these costs were possible and therefore, steps 3 and 4 were combined. Library preparation and sequencing costs of the lung/melanoma project were combined.To detect insertions, deletions and large genomic rearrangements that are strongly associated with hereditary breast cancer, multiplex ligation-dependent probe amplification was required as an additional step in the breast cancer project. This was included in step 4 ‘sequencing’. It was not required for the lung/melanoma cancer project because they did not aim to detect these types of genetic variants and the other projects involved exome/genome sequencing technologies which cover these variants.www.xe.com).All analyses were undertaken in Excel™. The main unit of analysis was ‘per patient’ as opposed to per sample where matched blood and tumour samples are required per case. Costs were assigned and aggregated for each project by the seven broad categories. Costs were also aggregated according to labour, consumables, testing, equipment and ‘other’ categories. One-way sensitivity analyses on items with known variation or were provided in ranges  were performed and tornado diagrams produced. For capital equipment, we obtained the annual equivalent cost calculated by the estimated sequencer acquisition divided by an annuity factor and accounting for useful life (5 years) and interest rate (3%) . This anDetails of the projects’ baseline sequencing specifications are provided in Table Per patient costs were AU$871 for melanoma (exome sequencing), AU$2788 for lung cancer (exome sequencing), AU$4830 for oesophageal cancer (genome sequencing), AU$429 for lung cancer/melanoma (targeted panel), AU$347 for breast cancer (targeted panel) and AU$2895 for mesothelioma (genome sequencing) , three-quarters were for the combined library preparation and sequencing steps , while the other steps were small by comparison; DNA extraction , data analysis  and data storage   to AU$1917 within exome, and AU$1935 within whole genome sequencing methods. Our findings suggest that the purpose and extent of sequencing (whether tumour and matched blood DNA samples were needed) along with the commercial prices offered were the main points of difference across the projects. Future work is needed to assess costs by different cancer types as we did not have sufficient cases and cancer types here to inform this. Documenting baseline sequencing specifications and categorising resources into seven logical steps aided comparisons and could be used by others in future work. As there are many factors that determine the resources and costs involved in sequencing, projects need to be sufficiently detailed to ensure operating costs are captured to allow for informed assessments.Several others have published studies on micro-costing approaches for genomic sequencing , 23, 24.In practice, there are instances where the quality of the DNA from the sample fails to meet the high standards required for genomic sequencing. The resulting need for sample retrieval and re-sequencing, impacts on resource use and costs. For example, 30% of the oesophageal cancer samples did not have the minimum 40% tumour content required so another tumour biopsy was retrieved . Since this is typical, costs were appropriately included for the DNA to be re-extracted and quality control re-done. However, better biopsy samples present an opportunity for cost savings. For the melanoma project, there were no instances of saliva samples having insufficient DNA to perform the extraction however the quality of some formalin-fixed paraffin-embedded material was poor and 30 samples had to be prepared again, re-sent to the sequencing laboratory and re-sequenced. This incurs extra costs for the commercial provider but did not affect their fee charged.The two whole genome applications, mesothelioma and oesophageal cancer, were pre-clinical while melanoma and lung cancer applications were clinical demonstration projects using exome sequencing. The lung/melanoma and breast cancer panel applications are routinely implemented within the health system. Four of the six projects involved research which presents difficulties in quantifying and valuing resources that need research and clinical activities to be separated. Separating research from clinical sequencing activity may be problematic for genomic technologies when researchers are closely involved in the bioinformatics stages and are discovering new important variants for clinical attention. While the social value of genomic research may be significant, it is likely to remain difficult to measure and value. Gene discovery is rapidly evolving and could be viewed as a necessary consideration for costing with re-analysis of stored data likely to be more commonplace and will give rise to higher costs per patient than presented here.Our findings improve the understanding of the many cost components of genomic sequencing, highlight the difficulties in measuring costs in a highly commercialized area and should assist health economists who are undertaking cost-effectiveness analyses of clinical genomics. Costs and cost proportions (both in terms of cost categorization and cost type) were compared across and within technologies which provided some stark and interesting contrasts. It should be emphasized that the costs presented here reflect the commercial prices involved in sequencing activities where there is limited market competition. The bulk pricing of the melanoma setting, where 383 salvia samples were tested in one batch, may be closer to the actual cost of library preparation and sequencing. While in the lung cancer setting with only 10 patients, there were very detailed quantities of resource use for exome sequencing. It is perhaps a combination of these two settings that provide a reliable indication of the cost of exome sequencing and may be useful for budget impact analyses. Ultimately, in the context of a cost-effectiveness analysis, the value of genomic sequencing is the goal for decision makers and capturing the implications on patient management is critical.This study has some limitations. Virtually all the monetary values reported are ‘prices’ rather than true costs because there is no other practical way of valuing them. While we have assumed prices are a reasonable proxy for costs, with competition in the market increasing, these prices are likely to still overestimate true costs because they include mark-ups and other fees. There are significant disparities between the number of patients within the exome sequencing estimates (melanoma and lung cancer) and whole genome sequencing  and caution is required when comparing between these technologies. Some monetary costs were difficult to estimate as hospital or laboratory records did not have these readily available , or laboratory funding was not organised on a per project basis for straight-forward calculation. For example, in one setting scientists are allocated laboratory consumables over a set term irrespective of caseload and specific projects. Furthermore, costs of data storage were valued from online cloud-based pricing, but the required storage duration is unclear, and prices are determined by how often the data would need to be re-analysed, if at all. The estimation of capital equipment is problematic with sequencing costs since new systems are being developed every other year and estimating useful life for amortization may be overestimated (which underestimates costs). Our sensitivity analyses showed different inputs to calculating capital equipment had a minor impact on total costs. Genomic medicine in Brisbane is emerging and further capacity for full implementation is required. It is likely the costs may change as projects use local sequencing systems, workforce capacity grows, and sequencing becomes more streamlined. Finally, we were not able to assess marginal costs or variation across individuals via bootstrapping methods as data was not collected at the individual level but rather was deterministic. Ideally, a stronger design would capture individual-level data that could be statistically analysed, although it may still be challenging to obtain accurate per patient resource units.Claims of sequencing now dropping to US$1000 per genome have arisen with more powerful sequencing platforms but there is little evidence to support this claim . It is uGenomic sequencing costs within cancer vary with the purpose of testing such as risk prediction or personalised treatment (dictating the need for germline only or matched germline and tumour samples per patient), and the commercial sequencing rates offered, among others. Using the natural steps involved in sequencing and categorising resources accordingly, future evaluations of sequencing costs could be more standardised and facilitate easier comparison of cost drivers. Future work assessing individual-level costs for the same sequencing approach by different cancer types are required.Additional file 1. Full details of costing estimates.Additional file 2. Features of sequencing that will influence costs.Additional file 3. Calculation of annual per person cost of sequencers.


Post-traumatic stress disorders (PTSD) pose a high burden for individuals and societies. Although prevalence rates are rather low, high co-occurrence rates and overall impairments cause deleterious suffering and significant costs. Still, no long-term data on costs and trends in cost developments are available.Claims data from a German research database were analysed regarding direct and indirect costs occurring for individuals with incident diagnoses of PTSD. Results were compared to non-exposed average insurants matched on age and gender. Costs were analysed over a 5-year period from 2 years preceding until 3 years following an incident diagnosis of PTSD.Overall costs for PTSD account for approximately 43,000 EUR per individual, which is three times higher than costs for non-exposed controls. Of these costs, 59% are caused by mental disorders, 18% specifically by PTSD. In the control group, costs for mental disorders account for 19% of total costs. Costs increase by 142% in the year after an incident diagnosis of PTSD but return to the initial level 2 years later. Still, costs are at least twice as high in every year as in those for the comparison group.Individuals with PTSD seem to suffer from far more impairments in their general health conditions and incur many more costs than average insurants. Most of these seem to be caused by co-occurring mental disorders and show their maximum in the index year. Nevertheless, as costs decrease to their initial level, treatments seem to have counterbalanced the impairments due to PTSD. Thus, treatments for PTSD can be considered as beneficial and their cost-effectiveness should be further investigated. Post-traumatic stress disorders (PTSD) are a critical public health issue with significant impacts on affected individuals, health care systems, and societies. Despite comparatively low prevalence rates of 1.1–2.9% in the European population  and showIn general, mental disorders pose a serious burden to the European population. The overall 12-month prevalence rate of having any mental disorder is estimated at 25.7–38.2%, and their impact on global health impairments continues to increase . DespiteFor PTSD, little is known about the costs that come along with the disorder’s impairments. As to our knowledge, only a few studies have investigated health care costs due to PTSD. Based on US-American private insurance and Medicaid data, one study estimated direct health care costs of 10,960–18,753 USD per patient per year . A bottoThus, this study sought to add evidence regarding the quantity of monetary losses due to PTSD and to compare these costs to those incurred by non-exposed average insurants using a large database of anonymised German statutory health care claims data from the nationwide InGef research database. Data was analysed via all the available outcome measures of direct and indirect costs to estimate incremental costs and potential savings. Trends for cost developments were described to gain a broader view of PTSD and its course of illness before and after the onset of the disorder. Concluding the empirical evidence on the high individual and health burden associated with PTSD, we hypothesised that costs for individuals with PTSD exceed the costs resulting in non-exposed typical insurants after an incident diagnosis.The study was based on anonymised claims data from approximately 70 nationwide statutory health insurance (SHI) providers and more than 8 million individuals included in the InGef research database. In addition to demographic data, the database contains information on dispensed drug prescriptions, outpatient and inpatient services, incapacities to work, and diagnoses. In 2013, the database showed good accordance with the overall German population regarding measures of morbidity, mortality, and drug use . InformaWe conducted a retrospective cohort study of individuals with newly diagnosed PTSD, including data from 2010 until 2017. In a first step, individuals with a prevalent PTSD (ICD-10-GM F43.1) between 2012 and 2014 were identified by the following criteria: individuals had to have either (a) one or more inpatient diagnoses coded as ‘main diagnosis’, (b) two or more outpatient diagnoses stated as ‘secure diagnosis’, or (c) at least one ‘secure’ outpatient diagnosis by a specialist for mental disorders, e.g., a psychotherapist, a psychiatrist, or a neurologist. Incidence was defined as not having had a PTSD diagnosis, according to the abovementioned criteria, 2 years prior to the first PTSD diagnosis (index date) between 2012 and 2014. Only individuals who were fully observable in the database 2 years prior to the first PTSD diagnosis and in the 3 years following their index date or until their death were included. In addition, only individuals aged 18–65 at index date were included in the study population. Individuals were excluded from further analysis if they suffered from (a) organic, including symptomatic, mental disorders, (b) schizophrenia, schizotypal and delusional disorders, or (c) mental retardation  in the period 2 years prior to or in the quarter of their index date.To estimate the incremental costs that arise due to PTSD, a no-PTSD affected control group (No-PTSD CG) was identified. The same inclusion and exclusion criteria as for the PTSD-group were applied with the exception of the PTSD diagnosis. We assigned random index dates between 2012 and 2014 to all individuals that had no PTSD diagnosis. Only individuals who were fully observable 2 years prior to the assigned random index date and 3 years after their index date or until their death and who were aged 18–65 were included. Additionally, individuals were excluded if for a F0, F2, or F7 diagnosis in the 2 years preceding or in the quarter of their index diagnosis had been documented. A 1:4 matching by age and gender of individuals with PTSD and non-exposed individuals was conducted, and the resulting sample was used for further analysis.Sociodemographic data such as gender, age, and insurance status were analysed. Comorbidities in the 2 years prior to the index date according to the ICD-10-GM chapters were assessed to gain a broader view of the overall health status of the study populations. Furthermore, Charlson comorbidity indices (CCI)  were detAs a primary outcome, the overall amount of costs resulting from health care service utilisation and indirect costs for the German welfare state were analysed. Included were filed medication prescriptions, inpatient and outpatient treatments, sickness benefit payments, and costs due to losses of gross value per day absent. For the latter, average amounts of costs per day absent for every year from 2010 until 2017 as reported by the Federal Institute for Occupational Safety and Health  were useIn the second step, data were analysed for all costs due to mental disorders. Only services which were billed due to a documented mental disorder (ICD-10 GM chapter F) within the same hospital case or ambulatory treatment case were included in the cost analysis, as well as sickness benefit payments and reports of incapacities to work. For drug therapies, all prescriptions of ATC-codes beginning with ‘N05’ (psycholeptics) or ‘N06’  were considered as mental disorder-specific prescriptions in the calculation of mental disorder-related health care costs. Again, costs were compared between groups to analyse differences in costs caused by mental disorders as an estimate for other co-occurring disorders in individuals’ mental health status.Vice versa, costs that could be identified as not caused by mental disorders were reported using the same method. All services and treatments in which no mental disorder was documented were included in this sub-analysis. Analysis followed the same procedure as for the other outcomes, and costs were compared between groups.Furthermore, the PTSD-group was analysed for any cost factors due to PTSD after its onset to gain an overview of trends in disorder-specific cost developments for an incident PTSD. Following the same procedure as abovementioned, all services containing a diagnosis of PTSD (ICD-10-GM F43.1) were included in this analysis. As drug therapies cannot be identified as being prescribed explicitly for PTSD or other mental disorders, no PTSD-specific drug costs were estimated.Data were extracted, aggregated, and analysed using R version 3.5.0. Analyses were conducted separately for every year during the 2 years preceding an index diagnosis, for the year following an index diagnosis, and for the 2 years after, as well as for the whole 5-year observation period. All descriptive and statistical analyses were conducted regarding total sample sizes, respectively. Differences in totals, i.e., for insurance status and for monetary values, can occur due to multiple data for a respective analysis period, or due to accumulation of overlapping intervals for continuous services.V or Cohen’s d. For completeness, we also reported Chi-square tests for categorical variables and Student’s t tests with Bonferroni correction for continuous variables. Considering the large sample sizes, differences were considered significant at a level of p < 0.001.In accordance with current research trends , 31, we Between 2010 and 2017, anonymised data for approximately 8.4 million individuals were available in the research database. Of these, 103,727 received a diagnosis of PTSD (F43.1) at any time, while 8,248,433 did not. In the PTSD-cohort, 40,186 were identified as prevalent, and 26,686 as an incident between 2012 and 2014. Of these, 17,056 were fully observable in the whole analysis period, and 14,096 were aged 18 to 65. A total of 1,209 individuals were excluded due to a diagnosis of F0, F2, or F7 within 2 years prior to or in the quarter of their index date, which resulted in a final study sample of 12,887 individuals with PTSD. For the No-PTSD CG, after assigning randomised index dates between 2012 and 2014, a total of 4,619,992 individuals fulfilled the criterion for being fully observable 2 years prior until 2 years after the assigned random index year or until their death. Of these, 3,123,575 were aged 18–65, and 3,059,008 remained after exclusion of individuals with an F0, F2, or F7 diagnosis 2 years prior to or in the quarter of their index date. After a 1:4 matching by gender and age, a final sample of 51,548 individuals in the No-PTSD CG remained for further analysis. The flowchart in Fig. SD = 11.8) and 73.4% are female. The PTSD-group includes fewer individuals ‘with dependent coverage’ over family members  but more individuals with insurance status ‘retired’ . Average CCIs are higher in the PTSD-group . χ2-tests for insurance status ‘with dependent coverage’ and ‘retired’ as well as the t test for CCI show significant differences, with small effect sizes for insurance status ‘retired’ (V = 0.10) and CCI .Table Table Table In contrast, the No-PTSD CG shows a continuous slight upward trend in costs over the course of the study period. Mean costs increase constantly and in every analysed outcome variable for each of the subsequent years. For mean total costs, an increased rate of 45% can be estimated from 2 years prior to 2 years after the index year . Median costs for drug therapies, outpatient treatments, and total costs follow the same trend; medians for the other outcome variables remain zero for all years. In total, the No-PTSD CG causes costs of 13,942 EUR  per individual over the entire observation period.d of 0.73 (CI 0.71–0.75) shows an upper mediate effect size. Differences are highest in the index year where the PTSD-group incurs costs five times higher than the No-PTSD CG , with a large effect size of 0.92 (CI 0.90–0.94). For the years preceding and following the index year, costs are consistently more than twice as high for individuals with PTSD in relation to the non-exposed controls (means 5767–8026 EUR versus 2341–3384 EUR), with small effect sizes for the 2 years preceding  as well as the 2 years following , and medium effect sizes for 1 year preceding  and following  the index year. The same results can be seen for all respective outcomes, with the largest effect sizes for outpatient treatments. Only drug therapies show not even small effect sizes, such that differences here can be gauged as very small.Comparisons between groups show significant differences after Bonferroni correction for nearly all outcomes and years. In total, costs for individuals with PTSD are more than three times higher over the total 5-year period compared to those for the No-PTSD CG. A Cohen’s Table The same trend as for total costs can also be seen for the No-PTSD CG. In all outcome variables, costs increase constantly in every year. Total costs due to mental disorders increase by 78% from 2 years preceding  until 2 years after the index year . Average mental disorder-specific costs of 2624 EUR (CI 2521–2727) in total per individual account for 19% of all occurring health care costs which accumulated over the whole analysis period.t tests that were conducted between the PTSD and the No-PTSD CG show significant results. Compared to total costs, differences show even higher discrepancies for mental disorder-specific health care costs. In total, the PTSD-group causes costs 9.6 times higher as compared to the No-PTSD CG, with a large effect size . In the year of index diagnosis, costs due to mental disorders are 20.7 times higher in the PTSD-group , with a large effect size of d = 1.02 (CI 1.00–1.04). For all other analysed periods, yearly total costs are between five to nine times higher in the PTSD-group (means 2374–4782 EUR versus 392–698 EUR), with small to medium effect sizes (d = 0.39–0.61). The same findings can be seen for all respective outcome variables, with the largest effect sizes for outpatient treatments (d = 0.59–1.77).All In Table Again, the same trends can be seen in all outcome variables for the No-PTSD CG with respect to total and mental disorder-specific costs. Mean costs increase constantly in every year, in total by 38%, from 1951 EUR (CI 1883–2019) 2 years prior to 2685 EUR (CI 2581–2790) 2 years after the index year. In total, mean costs not due to mental disorders accumulate to 11,317 EUR , which accounts for 81% of total health care costs over the whole analysis period.d = 0.06–0.26). In total, the PTSD-group incurs non-mental disorder-specific costs that are 1.6 times higher.Comparisons between groups show significant differences for nearly all outcomes and periods and the PTSD-group causes higher costs for every year as well. In any event, differences are far lower compared to total and mental disorder-specific costs. Ratios for total costs range only from 1.3 to 1.9 per year, and with very up to slightly small effect sizes . Costs for the PTSD-group are at least twice as high in every year preceding and following index diagnosis. Hence, individuals with PTSD seem to suffer from more complex disorder conditions and more severe preceding and continuing overall health impairments.Most of these impairments and incremental costs seem to be caused by PTSD itself and co-occurring mental disorders. This is supported by the analyses on costs and cost developments as well as by the results for co-occurring disorders. CCIs are slightly higher and co-occurrence rates are nearly overall increased in the PTSD-group but are the highest by far for mental and behavioural disorders, with an odds ratio of 7.1. In terms of costs, mental disorder-specific health care costs account for 59% of overall costs in the PTSD-group, but only for 19% in the No-PTSD CG. In the No-PTSD CG, costs increase constantly year by year at a small rate, which can be explained by overall increases in health care expenditures within the German statutory health care system . AbsolutOverall, individuals with PTSD cause around 29,000 EUR more in costs over a 5-year period compared to non-exposed average insurants. Of these, incremental costs specifically due to PTSD only can be estimated at roughly 8000 EUR, equal to 27% of total incremental costs; 73% of these costs seem to be due to other disorders, mainly other mental disorders. However, total costs show a proportionally lower increase rate from 2 years preceding the index year until 2 years after for individuals with PTSD compared to the No-PTSD CG (23% versus 45%). Taking these trends into account, we could assume that treatments covered in the statutory health care system lead to a decline of symptom severity and could counterbalance an outbreak of PTSD in the long run. International guidelines highly recommend psychotherapy with additional pharmacotherapy if necessary as the treatment option of choice for PTSD , 34 and Previous research on costs due to mental disorders shows different results, along with a lack of standardised procedures. Due to different methodological approaches, comparability with other research on costs stemming from PTSD and other mental disorders is restricted. Compared to one US-American study on Medicaid and private insurance data, our results correspond with the findings. The study estimated direct costs due to PTSD at 10,960–18,753 USD per patient per year , which iCompared to these findings, costs due to PTSD turn out to be higher than for other mental disorders. Considering the complexity and severity of PTSD and high co-occurrence rates for mental and physical disorders, high costs for PTSD seem reasonable. Due to the large sample size and conservative estimation approaches, our results can be considered good estimates for costs due to PTSD. Moreover, this study describes cost developments over a long analysis period preceding and following incident PTSD. In addition, the results add evidence as to the high financial and economic burden that PTSD causes for a welfare state, along with the immersive health restrictions for affected individuals.Several limitations should be considered for this study. First, studies on claims data are generally associated with restrictions in data quality compared to the quality of primary data. Especially relevant for this study is the fact that no statements on the validity of diagnoses can be made. We tried to face these issues by defining strict inclusion and exclusion criteria; e.g., only secure diagnoses by inpatient services, or two or more outpatient diagnoses or one by a mental disorder specialist. Furthermore, due to data constraints, we could only include part of the cost factors that might be relevant. Because information is only available from the perspective of health insurers, data for other direct and indirect expenses—e.g., out-of-pocket expenses, early retirements, life quality, and thus, quality-adjusted life years—as well as reliable information on disease remissions for assessing whether or not treatments were successful could not be included. Additionally, data for short-term incapacities to work are probably not covered by claims data  so that Differences in sociodemographic data could also restrict comparability between groups; one could also argue that we should have expanded our matching procedure to characteristics beyond gender and age, or applied Propensity Score Matchings . ConsideThis study provides estimates for incremental costs due to incident PTSD and describes trends of cost developments arising for the health care system and welfare state over a 5-year period. Individuals with PTSD cause costs of approximately 43,000 EUR in total, three times higher than for non-exposed average insurants. All in all, incremental costs can be estimated at roughly 29,000 EUR and lead back mostly to PTSD and to other co-occurring mental and behavioural disorders. Furthermore, the findings support evidence on the complexity and severity of health restrictions caused by PTSD due to co-occurring disorders, especially accompanying mental disorders, which account for double the costs in relation to PTSD-specific costs only. Taking the overall reduction rates in cost developments after an onset of PTSD into account, this study suggests that treatments for PTSD are efficacious and benefit affected individuals. Thus, health policies should focus overall on enhancing and encouraging early evidence-based treatments and prevention approaches. Further research should investigate precise cost–benefit estimates for treatment approaches for PTSD and other mental disorders in general on claims data.