Deposition of energy leading to occurrence of bone loss

Snehpal Sandhu¹, Mitchell Keyworth¹, Syna Karimi-Jashni¹, Dalya Alomar¹, Benjamin Smith¹, Tatiana Kozbenko¹, Robyn Hocking², Carole Yauk³, Ruth C. Wilkins¹, Vinita Chauhan¹

(1) Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Ontario, Canada

(2) Learning and Knowledge and Library Services, Health Canada, Ottawa, Ontario, Canada

(3) Department of Biology, University of Ottawa, Ottawa, Ontario, Canada

Consultants

Stephen Doty¹, Nobuyuki Hamada², Robert Reynolds³ , Ryan T. Scott⁴, Sylvain V. Costes⁵, Afshin Beheshti^6,7

(1) Hospital for Special Surgery Research Institute, New York City, New York, USA

(2) Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Tokyo, Japan

(3) KBR, NASA Johnson Space Center, Houston, TX 77058 USA; 

(4) KBR, NASA Ames Research Center, Moffett Field, CA 94035 USA; 

(5) NASA Ames Research Center, Space Biosciences Research Branch, Mountain View, CA, USA;  

(6) KBR, NASA Ames Research Center, Space Biosciences Division, Moffett Field, CA 94035, USA;  

(7) Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA;

The present AOP describes Key Events (KEs) from deposition of energy, the moleculare initiating event (MIE), to bone loss, the adverse outcome (AO) and is part of a broader network to three other AOs relevant to radiation exposures: impaired learning and memory, cataracts, and vascular remodeling. The AOP begins with the deposition of energy (KE#1686) that can lead directly to oxidative stress (KE#1392), defined as an imbalance of oxidants and antioxidants. Oxidation of key functional amino acids can alter signaling proteins, resulting in downstream effects in bone-regulating signaling pathways (KE#2066), specifically the Wnt/β-catenin pathway and the receptor activator of nuclear factor kappa B ligand (RANK-L) pathway. Concurrently, oxidative damage to vital cellular components, such as the nucleus, mitochondria or cell membrane, can induce oxidative stress-driven cell death (KE#1825), such as apoptosis, autophagy, and necrosis. Cell death can reduce osteocyte and osteoblast cell numbers or initiate the secretion of osteoclast-stimulatory molecules that can alter bone cell homeostasis (KE#2089). Impaired activity and differentiation of osteoblasts decreases bone formation, while increased activity and differentiation of osteoclasts increases bone destruction. Subsequent bone remodeling (KE#2090) is then altered, defined by bone resorption being increased above bone formation. Bone density and quality can then be changed, leading to bone loss (KE#2091), the AO. The overall evidence for this AOP is moderate based on the literature to support the pathway. Although biological plausibility is well established and the evidence supporting the essentiality of most KEs is high or moderate, the quantitative understanding of the AOP is weak. Modulating factors for this relationship include age and genotype. Overall, the AOP identifies data gaps that can inform new experiments to improve quantitative understanding and could serve as a basis for developing strategies mitigating the risks of long duration spaceflight and radiotherapy treatments. 

Bone loss, as observed in a variety of conditions such as osteopenia and osteoporosis, is a skeletal disorder characterized by decreased bone density and quality resulting in porous, fracture-prone bones (Rachner, Khosla, and Hofbauer, 2011). In the United States, it has been estimated that 2 million fractures per year are due to osteoporosis, costing $57 billion per year from direct medical costs combined with productivity losses and informal caregiving (Lewiecki et al., 2019). Bone loss is more common in Caucasians, women, and older people (Sozen, Ozisik, and Basaran, 2017). Risk factors for fractures include low body mass index, previous fractures, glucocorticoid treatment, and other conditions like rheumatoid arthritis and type 1 diabetes mellitus (Sozen, Ozisik, and Basaran, 2017).  

Growing evidence suggests that acute and chronic radiation exposure can contribute to the loss of bone mass (Donaubauer et al., 2020; Willey et al., 2011; Wissing, 2015). Clinical studies have shown that skeletal sites receiving high doses of ionizing radiation (25 Gy or higher) have increased fracture risk (Baxter et al., 2005; Oeffinger et al., 2006; Willey et al., 2011). For example, radiotherapy for pelvic malignancies causes an increased risk of hip fractures (Baxter et al., 2005; Williams and Davies, 2006). Similarly, radiotherapy for breast cancer or rectal carcinoma has been shown to increase the risk of fracture to the ribs or pelvis/femoral neck, respectively (Holm et al., 1996; Overgaard, 1988). Low to moderate doses of radiation as received during long-term spaceflight contribute to bone loss (Stavnichuk et al., 2020; Willey et al., 2011), but is the focus of fewer studies. Therefore, identifying essential early endpoints relevant to radiation-induced bone loss through the development of AOPs can inform mitigation strategies to reduce the risks from radiation exposures. 

The MIE, "deposition of energy," can originate from any form of ionizing and non-ionizing radiation and defines the first measurable interaction that physically initiates or promotes the AOP in an organism. KEs were selected based on the mechanistic understanding of bone loss identified from recent relevant review articles and through expert consultation. Not all biological perturbations from deposited energy to bone loss are represented in the AOP; only routinely and readily measured KEs with abundant empirical evidence were included. References to support the AOP were retrieved and screened using the protocol detailed by Kozbenko et al. (2022). Briefly, a structured literature search was undertaken to initiate the data collection process, followed by screening, prioritization of selected references and then manual data extraction. In addition to comprehensive searches that collected references for the MIE and AO, focused searches were also undertaken for each of the KERs in the pathway using keyword combinations associated with the KEs involved. KERs that lacked evidence were supplemented by non-adjacent KERs originating from the MIE, as there was abundant evidence to support MIE to each of the KEs. The results of the literature searches were first analyzed in two stages to determine their inclusion in the pathway. First, a Population, Exposure, Outcome, and Endpoint (PEOE) statement formed the basis of the inclusion and exclusion criteria for studies at all stages of screening. The articles that were included were then passed onto the next stage of screening. The second stage of screening required articles to specify a population (e.g., humans, mice, rats), exposure (i.e., stressor such as radiation or microgravity), and endpoint (KE) or outcome (AO) of interest to the AOP. 

Consideration was given to all studies at all levels of biological organization, regardless of the species, life stage, or sex. The abstracts of non-English studies were included if the data were explicit in the abstract. Theses/dissertations, presentations, posters, and conference abstracts were all eliminated, along with studies that solely contained abstracts and no full texts. Studies that lacked sufficient details regarding the stressor type, dose range, tissue, timepoints, model, and experimental protocols were also excluded. The modified Bradford Hill Criteria (informed by biological plausibility, time concordance, dose concordance, incidence concordance, and essentiality of KEs) were used to determine each study’s eligibility to support the AOP. To manage the large volume of studies, a pre-filtering step was included using the SWIFT-Review program. Software-generated tags to specific field entities as outlined in Kozbenko et al. (2022), aided in prioritizing relevant references. Studies that passed through SWIFT were collected and uploaded into DistillerSR, where a three-stage screening protocol was used to further refine the body of evidence. Screeners in Distiller examined studies at the level of Title and Abstract (Level 1), Full-Text (Level 2), and Data Extraction (Level 3) screening stages; here, screeners incorporated references in accordance with the PEOE statement and additionally extracted important information supporting modified Bradford Hill criteria, taxonomic, and life stage applicability. Data extraction of relevant studies was managed in Microsoft Excel 2010. All KE and KER descriptions were reviewed by consultants. 

This AOP collates peer-reviewed published data in the space field and studies from other radiation exposure scenarios that are not encountered during space travel to strengthen the evidence. The search priotized chronic low- to moderate-dose radiation emitted from high linear energy transfer (LET) particles, which is most applicable to long-term spaceflight. High doses from low-LET acute radiation studies were included as well; thus, AOP is also relevant to bone loss from radiotherapy. Other stressors that are space-relevant but not radiation-related like microgravity are also used to strengthen the AOP. However, not all KERs are equally supported by the multitude of stressors encountered during space travel, as some KERs have different responses dependent on the stressor. A few studies show additive effects when combining radiation and microgravity stressors in animal models, demonstrating that these stressors may encourage bone loss through separate pathways (Willey et al., 2021). However, particularly in studies using chronic or fractionated exposures, radiation did not exacerbate the effects of microgravity (Kondo et al., 2010; Willey et al., 2021). This could be because the identical components of each mechanism are saturated by the individual stressor (Kondo et al., 2010). 

Biological Plausibility 

Overall, each KER in the AOP is well understood mechanistically and biological plausibility is high. Mechanisms such as altered bone cell homeostasis and bone remodeling are well accepted biological events contributing to bone loss (details provided in tables). The deposition of energy (MIE) causes the ionization of water molecules within cells, producing free radicals that combine to more stable reactive oxygen species (ROS) (Eaton, 1994; Padgaonkar et al., 2015; Rehman et al., 2016; Varma et al., 2011). Additionally, deposited energy can directly upregulate enzymes involved in reactive oxygen and nitrogen species (RONS) production (de Jager, Cockrell and Du Plessis, 2017). This, along with positive feedback loops that further generate RONS, contributes to oxidative stress as RONS overwhelm the cells’ antioxidant defense systems and subsequently damage macromolecules and organelles (Balasubramanian, 2000; Ganea and Harding, 2006; Karimi et al., 2017; Zigman et al., 2000). 

It is well established that oxidative damage can cause both cell death and altered signaling. Oxidation of key amino acids in proteins from major signaling pathways will cause conformational and functional changes to these signaling molecules, inducing changes in the activity of the entire pathway (Ping et al., 2020; Schmidt-Ullrich et al., 2000; Valerie et al., 2007). Oxidative stress can indirectly affect signaling through oxidative DNA damage, which influences the expression and activity of signaling molecules, such as the molecules involved in the MAPK pathway (Nagane et al., 2021; Ping et al., 2020; Schmidt-Ullrich et al., 2000; Valerie et al., 2007). Additionally, extensive damage to DNA, mitochondria, or the cell membrane can induce cell death (Jilka, Noble and Weinstein, 2013). 

In bones, the combined influence of altered signaling pathways and increased cell death will alter bone cell homeostasis, characterized by an increase in osteoclasts (bone resorbing cells) and a decrease in osteoblasts (bone forming cells). Upregulated signaling from the RANK-L pathway will increase osteoclastogenesis, while impaired Wnt/β-catenin signaling will decrease osteoblastogenesis (Arfat et al., 2014; Bellido, 2014; Boyce and Xing, 2007; Chatziravdeli, Katsaras and Lambrou, 2019; Chen, Deng and Li, 2012; Donaubauer et al., 2020; Maeda et al., 2019; Manolagas and Almeida, 2007; Smith, 2020a; Smith, 2020b; Willey et al., 2011). Osteoblast death will reduce osteoblast numbers, while osteocyte death will free osteoclast-stimulating molecules (Jilka, Noble, and Weinstein, 2013; Komori, 2013; Li et al., 2015; O’Brien, Nakashima, and Takayanagi, 2013; Plotkin, 2014; Wang et al., 2020; Xiong and O’Brien, 2012). As bone cells are dysregulated, subsequent bone remodeling results in a greater rate of resorption than formation of bone (Bikle and Halloran, 1999; Donaubauer et al., 2020; Morey-Holton et al., 1991; Smith, 2020b; Tian et al., 2017). Consequently, bones exhibit reduced volume, density, mineralization, and strength as bone loss occurs (Bikle and Halloran, 1999; Donaubauer et al., 2020; Morey-Holton and Arnaud, 1991; Tian et al., 2017). A complete understanding of the relationship across taxonomy and sex is lacking at the time of AOP development; this is an area that requires further research. 

Temporal, Dose, and Incidence Concordance 

Evidence for time, dose, and incidence concordance in this AOP is moderate, as evidence to support the modified Bradford Hill criteria is often limited due to space travel conditions, where there are restrictions on the number of animals, doses and timepoints represented. For this reason, data from other exposure scenarios are used to help strengthen the adjacent relationships, in keeping with the principles of AOP development. In contrast, there was a larger evidence base for the non-adjacent relationships that were directly linked to the MIE, as there is much radiobiological research to support MIE’s causal association to each of the KEs in the AOP. 

In general, many studies demonstrated that the upstream KEs occurred earlier than the downstream KEs in time course experiments. It is well accepted that deposition of energy occurs immediately following irradiation, and downstream changes will always occur later in a time course. The subsequent radical formation occurs within microseconds (Azzam, Jay-Gerin, and Pain, 2012), and studies have observed the resulting oxidative stress as early as 2 minutes post-irradiation (Wortel et al., 2019). Altered signaling is a molecular-level KE like oxidative stress, and both KEs occur with a similar time course, making the assessment of time concordance difficult between these KEs. However, oxidative stress can still be observed slightly earlier than altered signaling (Wortel et al., 2019). The ensuing cell death due to oxidative stress often occurs within days post-irradiation, while altered bone cell homeostasis owing to both altered signaling and cell death is subsequently observed about a week after irradiation (Liu et al., 2018). Then, from multiple weeks to a month post-irradiation, bone remodeling is observed to favor resorption over formation (Alwood et al., 2010; Chandra et al., 2017; Chandra et al., 2014; Zhai et al., 2019). The resulting bone loss presents after this, with the greatest bone loss and risk of fractures observed months to years following irradiation (Holm et al., 1996; Nishiyama et al., 1992; Oest et al., 2018; Zou et al., 2016). 

Radiation at any dose and dose rate will deposit energy. Extensive evidence shows that upstream KEs can be observed at the same doses or lower doses as downstream KEs. For example, Kondo et al. (2009) and Kondo et al. (2010) showed that ROS levels and osteoclastogenesis were increased by both 1 and 2 Gy of gamma radiation, while bone loss and remodeling endpoints occurred at 2 Gy but not 1 Gy. In another study, X-ray irradiation at both 2 and 24 Gy led to increased osteoclast activity, while only 24 Gy led to consistent decreases in areal bone mineral density (aBMD) and mineral apposition rate (MAR) (Zhai et al., 2019). Dose concordance is not consistently observed across studies, but this may be due to different models, timepoints, and radiation types used. 

A few studies support incidence concordance. Although many studies demonstrate equal changes between the two KEs, less than half of the studies across KERs show that the upstream KE produces a greater change than the downstream KE following a stressor. One KER showing strong incidence concordance is altered signaling leading to altered bone cell homeostasis. For example, Sambandam et al. (2016) showed that tumor necrosis factor receptor-associated factor 6 (TRAF6) and tumor necrosis factor-related apoptosis inducing ligand (TRAIL) signaling molecules were increased 6 and 14.5-fold, respectively, while tartrate-resistant acid phosphatase (TRAP) staining (indicative of bone cell homeostasis) was just increased 1.7-fold by microgravity. 

Uncertainties and Inconsistencies

There are some notable knowledge gaps in the understanding of the biological mechanism involved in the deposition of energy leading to bone loss. In the space environment, both microgravity and radiation stressors are present. However, the differences in the underlying molecular changes following each stressor are currently uncertain (Willey et al., 2021). More research should be focused on understanding differential effects of microgravity and radiation on bone loss. Furthermore, studies using multi-ion radiation and chronic radiation exposure in addition to microgravity could better represent the space environment (Willey et al., 2021). 

Some studies also show conflicting results. For example, a few studies demonstrate bone cell differentiation and activity at doses of ionizing radiation at 2 Gy or below (Li et al., 2020b), while others show no effects (Kook et al., 2015; He et al., 2019). Differences may be due to experimental designs related to timepoints, histology measurements, models, radiation quality, doses, and dose rates. This often complicates the ability to evaluate the strength of the evidence due to inconsistent results. Studies were also limited in the range of doses or timepoints used, which challenged the identification of dose and time concordance data. Often studies measured KEs at a single dose or timepoint. Furthermore, no single study evaluated all KEs in the AOP, which would have provided ideal evidence to determine the weight of evidence supporting this AOP. 

Other aspects for consideration are interspecies differences. During the first few months of spaceflight, bone resorption increases greatly in humans (Stavnichuk et al., 2020). In rats, however, resorption does not change during spaceflight (Fu et al., 2021). Mouse models are more representative of the altered bone cell homeostasis KE than rat models, as they show consistent increases in resorption during spaceflight (Vico and Hargens, 2018). In addition, there are differences in measurements used to assess the resorption of bone in humans and experimental animals (Fu et al., 2021). 

Lastly, the bone remodeling KE includes endpoints to measure changes in the bone formation rate but has fewer endpoints to measure bone resorption. Resorption endpoints are often cell-level and are included in the altered bone cell homeostasis KE. Changes to resorption in the bone remodeling KE are determined indirectly through changes to bone formation and bone volume. Consequently, it is difficult to quantify bone resorption in the bone remodeling KE, even though it is an important contributor to bone loss. Further efforts could be directed to developing mthods that are able to assess bone resorption at the tissue level. 

The present AOP is one of four built to describe the causal connectivity of KEs leading to adverse health outcomes relevant to space travel and radiotherapy. In constructing the AOP, critical and well-understood biological events and data gaps in empirical evidence were identified. The evidence summary for this AOP can thus be used to justify areas for future work. For example, studies using multi-ion radiation at sustained deliveries and at chronic low doses under microgravity conditions would better represent the space environment and could clarify uncertainties observed in current studies. In addition, a standard range of stressor doses and measurement timepoints would allow for more dose and time response/concordance data and would facilitate more accurate comparisons of evidence between KEs. This  should include low doses, as existing low-dose evidence is often inconsistent. Quantitative understanding of each KER  could be improved through experiemtns designed to measure mulitple endpoints across dose- and time-ranges. Future studies should also strive to use models that are more applicable for assessing the risks of human space flight, as the proportion of human studies for each KER ranged from 0-33.3%, with only a few KERs containing human studies. In addition, further investigations are needed to consider sex differences in the study design, thereby strengthening  the understanding of the sex differences within the AOP. An uncertainty in the bone remodeling KE is that changes to the rate of resorption are not directly determined and are instead assumed based on changes to the bone formation rate and bone volume. Future work should identify a direct tissue-level measure of the bone resorption rate. The modulating factors and domain of applicability of this AOP can be used to develop risk mitigation strategies.  

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