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AOP: 482

Title

A descriptive phrase which references both the Molecular Initiating Event and Adverse Outcome.It should take the form “MIE leading to AO”. For example, “Aromatase inhibition leading to reproductive dysfunction” where Aromatase inhibition is the MIE and reproductive dysfunction the AO. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE.  More help

Deposition of energy leading to occurrence of bone loss

Short name
A name that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Deposition of energy leading to bone loss
The current version of the Developer's Handbook will be automatically populated into the Handbook Version field when a new AOP page is created.Authors have the option to switch to a newer (but not older) Handbook version any time thereafter. More help
Handbook Version v2.5

Graphical Representation

A graphical representation of the AOP.This graphic should list all KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs. More help
Click to download graphical representation template Explore AOP in a Third Party Tool

Authors

The names and affiliations of the individual(s)/organisation(s) that created/developed the AOP. More help

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 Beheshti6,7

(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;

Point of Contact

The user responsible for managing the AOP entry in the AOP-KB and controlling write access to the page by defining the contributors as described in the next section.   More help
Vinita Chauhan   (email point of contact)

Contributors

Users with write access to the AOP page.  Entries in this field are controlled by the Point of Contact. More help
  • Vinita Chauhan

Coaches

This field is used to identify coaches who supported the development of the AOP.Each coach selected must be a registered author. More help

OECD Information Table

Provides users with information concerning how actively the AOP page is being developed and whether it is part of the OECD Workplan and has been reviewed and/or endorsed. OECD Project: Assigned upon acceptance onto OECD workplan. This project ID is managed and updated (if needed) by the OECD. OECD Status: For AOPs included on the OECD workplan, ‘OECD status’ tracks the level of review/endorsement of the AOP . This designation is managed and updated by the OECD. Journal-format Article: The OECD is developing co-operation with Scientific Journals for the review and publication of AOPs, via the signature of a Memorandum of Understanding. When the scientific review of an AOP is conducted by these Journals, the journal review panel will review the content of the Wiki. In addition, the Journal may ask the AOP authors to develop a separate manuscript (i.e. Journal Format Article) using a format determined by the Journal for Journal publication. In that case, the journal review panel will be required to review both the Wiki content and the Journal Format Article. The Journal will publish the AOP reviewed through the Journal Format Article. OECD iLibrary published version: OECD iLibrary is the online library of the OECD. The version of the AOP that is published there has been endorsed by the OECD. The purpose of publication on iLibrary is to provide a stable version over time, i.e. the version which has been reviewed and revised based on the outcome of the review. AOPs are viewed as living documents and may continue to evolve on the AOP-Wiki after their OECD endorsement and publication.   More help
OECD Project # OECD Status Reviewer's Reports Journal-format Article OECD iLibrary Published Version
This AOP was last modified on May 07, 2023 13:38

Revision dates for related pages

Page Revision Date/Time
Deposition of Energy March 08, 2024 11:49
Oxidative Stress March 08, 2024 12:28
Altered Signaling Pathways February 13, 2024 07:31
Increase, Cell death March 22, 2023 11:07
Altered Bone Cell Homeostasis March 22, 2023 11:28
Increase, Bone Remodeling March 22, 2023 11:40
Occurrence, Bone Loss March 22, 2023 11:49
Energy Deposition leads to Oxidative Stress March 08, 2024 13:28
Oxidative Stress leads to Altered Bone Cell Homeostasis March 22, 2023 15:17
Oxidative Stress leads to Increase, Cell death March 22, 2023 13:45
Energy Deposition leads to Altered Bone Cell Homeostasis March 22, 2023 15:38
Oxidative Stress leads to Altered Signaling February 13, 2024 16:53
Energy Deposition leads to Bone Remodeling March 22, 2023 16:01
Increase, Cell death leads to Altered Bone Cell Homeostasis March 22, 2023 14:05
Energy Deposition leads to Bone Loss March 22, 2023 16:19
Altered Signaling leads to Altered Bone Cell Homeostasis March 22, 2023 14:28
Altered Bone Cell Homeostasis leads to Bone Remodeling March 22, 2023 14:46
Bone Remodeling leads to Bone Loss March 22, 2023 15:00
Ionizing Radiation May 07, 2019 12:12

Abstract

A concise and informative summation of the AOP under development that can stand-alone from the AOP page. The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance. More help

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. 

AOP Development Strategy

Context

Used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development.The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. More help

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. 

Strategy

Provides a description of the approaches to the identification, screening and quality assessment of the data relevant to identification of the key events and key event relationships included in the AOP or AOP network.This information is important as a basis to support the objective/envisaged application of the AOP by the regulatory community and to facilitate the reuse of its components.  Suggested content includes a rationale for and description of the scope and focus of the data search and identification strategy/ies including the nature of preliminary scoping and/or expert input, the overall literature screening strategy and more focused literature surveys to identify additional information (including e.g., key search terms, databases and time period searched, any tools used). More help

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. 

Summary of the AOP

This section is for information that describes the overall AOP.The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help

Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a prototypical stressor and the biological system) of an AOP. More help
Key Events (KE)
A measurable event within a specific biological level of organisation. More help
Adverse Outcomes (AO)
An AO is a specialized KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help
Type Event ID Title Short name
MIE 1686 Deposition of Energy Energy Deposition
KE 1392 Oxidative Stress Oxidative Stress
KE 2066 Altered Signaling Pathways Altered Signaling
KE 1825 Increase, Cell death Increase, Cell death
KE 2089 Altered Bone Cell Homeostasis Altered Bone Cell Homeostasis
KE 2090 Increase, Bone Remodeling Bone Remodeling
AO 2091 Occurrence, Bone Loss Bone Loss

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarizes all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP.Each table entry acts as a link to the individual KER description page. More help

Network View

This network graphic is automatically generated based on the information provided in the MIE(s), KEs, AO(s), KERs and Weight of Evidence (WoE) summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Prototypical Stressors

A structured data field that can be used to identify one or more “prototypical” stressors that act through this AOP. Prototypical stressors are stressors for which responses at multiple key events have been well documented. More help

Life Stage Applicability

The life stage for which the AOP is known to be applicable. More help
Life stage Evidence
All life stages High

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected.In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available. More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI
rhesus monkeys Macaca mulatta Low NCBI

Sex Applicability

The sex for which the AOP is known to be applicable. More help
Sex Evidence
Male High
Female High

Overall Assessment of the AOP

Addressess the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and Weight of Evidence (WoE) for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). More help

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. 

Domain of Applicability

Addressess the relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context. More help

This AOP is relevant to vertebrates, such as humans, mice, and rats. The taxonomic evidence supporting the AOP is derived from studies in human (Homo sapiens) and human-derived cell lines, mouse (Mus musculus), rat (Rattus orvegicus), and rhesus monkey (Macaca mulatta) (Chandra et al., 2014; Nishiyama et al., 1992; Willey et al., 2011; Zerath et al., 2002). Across all species, most available data was from adult and adolescent models with less available data from preadolescent models. 

The AOP is applicable to both sexes, with most studies using either male or female animal models but not both. In humans, spaceflight-induced bone loss has also been observed in both sexes (Smith et al., 2014). 

The AOP is applicable to all life stages, with extensive studies in adult humans and animals and fewer studies in adolescent and preadolescent animals. However, bone loss can be more prevalent in the aging population (>~50 years) (Riggs, Khosla, and Melton, 1998; Pacheco and Stock, 2013).

Essentiality of the Key Events

The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently, evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence. The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs. More help

Modulation of upstream KEs often influences the occurrence or extent of downstream KEs, making the evidence of essentiality moderate for the KEs in the AOP. Below are a few examples showing how downstream KEs are affected by upstream modulation. 

Essentiality of the Deposition of Energy (MIE#1686) 

  • The effect of radiation shielding on altered bone cell homeostasis (KE#2089) 

  • Increased osteoclast numbers were not observed in shielded contralateral bones following irradiation (Wright et al., 2015). However, a few studies show equal changes to osteoblast and osteoclast number in vivo in irradiated and contralateral limbs, possibly due to the abscopal effects of radiation (Zhang et al., 2019; Zou et al., 2016). 

  • The effect of radiation shielding on increased bone remodeling (KE#2090) 

  • Shielded limbs show a higher bone formation rate than directly irradiated limbs (Wright et al., 2015; Zhai et al., 2019). 

  • The effect of radiation shielding on occurrence of bone loss (AO#2091) 

  • Multiple studies measuring bone loss in shielded limbs contralateral to the irradiation show a greater loss of bone in the irradiated limb (Baxter et al., 2005; Oest et al., 2018; Wright et al., 2015). Although a few studies find equal changes in irradiated and contralateral limbs, this may be due to the abscopal effects of radiation (Zhang et al., 2019; Zou et al., 2016). 

Essentiality of Oxidative Stress (KE#1392) 

  • The effect of antioxidants on altered signaling pathways (KE#2066) 

  • Antioxidants including N-acetyl cysteine, curcumin, melatonin, polyphenol S3, and hydrogen water restore signaling in the Wnt/β-catenin pathway and inhibit signaling in the RANK/RANK-L pathway (Diao et al., 2018; Kook et al., 2015; Sun et al., 2013; Xin et al., 2015; Yoo, Han & Kim, 2016). 

  • The effect of antioxidants on increased cell death (KE#1825). 

  • Antioxidants including α-2-macroglobulin (α2M), semaphorin 3A (sema3a), amifostine (AMI), and melatonin reduce apoptosis levels induced by radiation or microgravity (Huang et al., 2019; Huang et al., 2018; Liu et al., 2018; Li et al., 2018a; Yoo, Han and Kim, 2016). 

  • The effect of antioxidants on altered bone cell homeostasis (KE#2089) 

  • Antioxidants including N-acetyl cysteine, α2M, AMI, curcumin, cerium (IV) oxide, and hydrogen water restore osteoblastogenesis and reduce osteoclastogenesis following radiation or microgravity (Diao et al., 2018; Huang et al., 2019; Huang et al., 2018; Kook et al., 2015; Liu et al., 2018; Sun et al., 2013; Wang et al., 2016; Xin et al., 2015; Zhang et al., 2020). 

Essentiality of Altered Signaling Pathways (KE#2066) 

  • The effect of modulated signaling on altered bone cell homeostasis (KE#2089) 

  • Modulation of osteoclastogenesis-related signaling – Inhibitors of the RANK/RANK-L pathway or other osteoclast-stimulating molecules reduce osteoclast activity after it is increased by exposure to gamma rays, X-rays, and microgravity (He et al., 2019; Li et al., 2018b; Rucci et al., 2007; Sambandam et al., 2016; Zhang et al., 2019; Zhou et al., 2008). 

  • Modulation of osteoblastogenesis-related signaling – Activation of pathways leading to runt-related transcription factor 2 (Runx2) activation or the Wnt/β-catenin pathway restored osteoblast activity after it is decreased by exposure to X-rays and microgravity (Chandra et al., 2017; Chen et al., 2020; Li et al., 2020b; Li et al., 2018b; Liu et al., 2018). In contrast, direct inhibition of the Wnt/β-catenin pathway impairs osteoblast activity (Chen et al., 2020). 

Essentiality of Increase, Cell Death (KE#1825) 

  • The effect of modulating cell death on altered bone cell homeostasis (KE#2089) 

  • Osteoblast cell death decreases the number of osteoblasts, while osteocyte cell death can stimulate osteoclastogenesis. Inhibition of cell death by using drugs that promote cell survival or by inhibiting autophagy restores osteoblast numbers and activity as well as reducing osteoclast numbers and activity (Chandra et al., 2014; Huang et al., 2019; Li et al., 2020b; Liu et al., 2018; Wang et al., 2020; Wu et al., 2020; Yang et al., 2020). 

Essentiality of Altered Bone Cell Homeostasis (KE#2089) 

  • No study directly modulating the changes to osteoblasts and osteoclasts and observing the results on downstream KEs was identified in the literature search. 

Essentiality of Increase, Bone Remodeling (KE#2090) 

  • The effect of modulated bone remodeling on bone loss (AO#2091) 

  • Bone remodeling blocked by knockout of osteopontin, a mediator of bone remodeling, restores the bone volume after microgravity (Ishijima et al., 2001). Similarly, inhibition of Calponin h1, an inhibitor of bone formation, increases BMD following microgravity (Yotsumoto, Takeoka, and Yokoyama, 2010). 

Evidence Assessment

Addressess the biological plausibility, empirical support, and quantitative understanding from each KER in an AOP. More help

1. Support for Biological Plausibility of KERs 

Defining Question 

High (Strong) 

Moderate 

Low (Weak) 

Is there a mechanistic relationship between KEupstream and KEdownstream consistent with established biological knowledge? 

Extensive understanding of the KER based on extensive previous documentation and broad acceptance; Established mechanistic basis 

KER is plausible based on analogy to accepted biological relationships, but scientific understanding is not completely established 

There is empirical support for statistical association between KEs, but the structural or functional relationship between them is not understood 

MIE#1686 → KE#1392: 

Deposition of Energy leads to Oxidative Stress 

High 

There is strong evidence of the biological plausibility of deposition of energy leading to oxidative stress. It is well understood that when deposited energy reaches a cell it reacts with water and organic materials to produce free radicals such as ROS. If the ROS cannot be eliminated quickly and efficiently enough by the cell’s defense system, oxidative stress may ensue. 

KE#1392 → KE#1825: 

Oxidative stress leads to Increase, cell death 

High 

It is well known that oxidative stress can lead to cell death. ROS lead to the release of pro-apoptotic factors, and enough ROS accumulation can lead to necrosis. Lipid and protein oxidation of key structures within the cell will also lead to cell death. 

KE#1392 → KE#2066: 

Oxidative stress leads to Altered Signaling Pathways 

High 

There is much evidence demonstrating the biological plausibility of the link between oxidative stress and altered signaling pathways. The direct and indirect mechanisms of oxidative stress leading to altered signaling are well known. Directly, oxidative stress conditions can lead to oxidation of amino acid residues. This can cause conformational changes, protein modifications, protein degradation, and impaired activity, leading to changes in the activity and level of signaling proteins. Indirectly, oxidative stress can damage DNA causing changes in the expression of signaling proteins as well as the activation of DNA damage response signaling. 

Non-adjacent

KE#1392 → KE#2089: 

Oxidative stress leads to → Altered Bone Cell Homeostasis 

High 

It is well understood that an increase in cellular oxidative stress indirectly leads to altered bone cell homeostasis. An increase in oxidative stress and the resulting decrease in osteoblast activity and increase in osteoclast activity have been discussed and well documented, in several reviews. 

KE#1825 → KE#2089: 

Increase, Cell Death leads to Altered Bone Cell Homeostasis 

High 

It is well understood that the induction of different forms of cell death of osteoblasts, osteoclasts, and osteocytes leads to an increase in bone resorption and decrease in bone deposition. Osteocyte apoptosis results in rupture of the plasma membrane as phagocytes are unable to engulf these cells, allowing for the release of osteoclast-stimulatory molecules. Apoptotic osteocytes also signal to viable osteocytes in the vicinity to express osteoclast-stimulatory signals. Osteoblast death reduces the overall pool of active osteoblasts. Autophagy can also lead to cell death, and a few studies associate it with cell death in bone cells. 

KE#2066 → KE#2089: Altered Signaling Pathways leads to Altered Bone Cell Homeostasis 

High 

It is very well understood that changes in osteoblast and osteoclast signaling pathways lead to decreased bone deposition and increased bone resorption. A few highly characterized pathways that are important for osteoblast and osteoclast differentiation are the Wnt/β-catenin pathway and the RANK/RANK-L pathway, respectively. Alterations in signaling from these pathways will alter bone cell numbers and activity. 

KE#2089 → KE#2090: 

Altered Bone Cell Homeostasis leads to Increase, Bone Remodeling 

High 

Review papers strongly support the structural and functional relationship between altered bone cell homeostasis and bone remodeling. Decreased activity and differentiation of osteoblasts and increased activity and differentiation of osteoclasts lead to increased overall destruction of bone. Bone remodeling is therefore imbalanced to favor bone resorption over formation. 

KE#2090 → AO#2091: 

Increase, Bone Remodeling leads to Occurrence, Bone Loss   

High  

The structural and functional relationship between bone remodeling and bone loss is well supported by review articles. Current literature on the subject establishes bone loss due to a decrease in bone formation and an increase in bone resorption by bone remodeling cells. 

Non-adjacent

MIE#1686 → KE#2089: 

Deposition of Energy leads to Altered Bone Cell Homeostasis  

High 

The structural and functional relationships connecting energy deposition to the loss of homeostasis among bone cells is well supported by several reviews on the subject related to space travel and clinical treatment. More specifically, reviews on ionizing radiation exposure have defined the biological mechanisms by which these stressors can indirectly induce the loss of homeostasis among bone cells. 

Non-adjacent

MIE#1686 → KE#2090: 

Deposition of Energy leads to Increase, Bone Remodeling 

High 

The biological plausibility for the indirect relationship between deposition of energy and imbalanced remodeling is strong. Reviews describe the impact of radiation on bone formation and resorption as well as the mechanisms involved. 

Non-adjacent

MIE#1686 → AO#2091: 

Deposition of Energy leads to Bone Loss 

High 

There is a high level of structural and functional evidence for the indirect relationship between deposition of energy and bone loss. 

2. Support for Essentiality of KEs 

Defining Question 

High (Strong) 

Moderate 

Low (Weak) 

Are downstream KEs and/or the AO prevented if an upstream KE is blocked? 

Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs 

Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE 

No or contradictory experimental evidence of the essentiality of any of the KEs 

MIE#1686: Deposition of energy 

Moderate 

Numerous studies show that physical shielding or attenuating the amount of deposited energy can modulate the downstream KEs. However, some studies still show significant bone loss in shielded limbs, possibly due to the abscopal effects of radiation. 

KE#1392: Oxidative Stress 

High 

Essentiality of oxidative stress is well-supported within literature. Many studies have shown that adding or withholding antioxidants such as catalase and glutathione peroxidase will decrease and increase the level of oxidative stress, respectively. Studies using antioxidants to attenuate oxidative stress show restored signaling and bone cell homeostasis, as well as reduced apoptosis. 

KE#2066: Altered Signaling Pathways 

High 

Studies strongly support the essentiality of altered signaling pathways on downstream effects. Studies have used inhibitors or activators of various signaling pathways and observed attenuation of downstream KEs, particularly altered bone cell homeostasis. 

KE#1825: Increase, Cell Death 

High 

Essentiality of increased cell death is well supported within literature through evidence that inhibiting cell death attenuates downstream KEs. Multiple studies inhibit osteoblast and osteocyte cell death by preventing apoptosis or autophagy and find restored osteocyte numbers as well as restored osteoblast numbers and activity. 

KE#2089: Altered Bone Cell Homeostasis 

Low 

There were no studies found on the essentiality of this event; i.e., there were no studies that inhibited the alteration of bone cell homeostasis and measured the downstream KE. 

KE#2090: Increase, Bone Remodeling 

Moderate 

Essentiality of bone remodeling is moderately supported within literature. A small number of studies that inhibit bone resorption or induce bone formation show a reduction in bone loss. 

3. Empirical support for KERs 

Defining Question 

High (Strong) 

Moderate 

Low (Weak) 

Does KEupstream occur at lower doses and earlier timepoints than KEdownstream; is the incidence or frequency of KEupstream greater than that for KEdownstream for the same dose of tested stressor?    

There is a dependent change in both events following exposure to a wide range of specific stressors (extensive evidence for temporal, dose-response and incidence concordance) and no or few data gaps or conflicting data. 

There is demonstrated dependent change in both events following exposure to a small number of specific stressors and some evidence inconsistent with the expected pattern that can be explained by factors such as experimental design, technical considerations, differences among laboratories, etc. 

There are limited or no studies reporting dependent change in both events following exposure to a specific stressor (i.e., endpoints never measured in the same study or not at all), and/or lacking evidence of temporal or dose-response concordance, or identification of significant inconsistencies in empirical support across taxa and species that don’t align with the expected pattern for the hypothesized AOP. 

MIE#1686 → KE#1392: 

Deposition of Energy leads to Oxidative Stress 

High 

There is a large body of evidence that supports an understanding of the time and dose relationship from deposition of energy leading to oxidative stress. The evidence collected to support this relationship was gathered from various studies using in vitro and in vivo rat, mice, rabbit, squirrel, bovine and human models. Various stressors were applied, including ultraviolet (UV) light (UV-B and UV-A) and ionizing radiation (gamma rays, X-rays, protons, photons, neutrons, and heavy ions). Studies that examined the effects of range of ionizing radiation doses (0-10 Gy) discovered that oxidative stress increases in a dose-dependent matter. 

KE#1392 → KE#1825:  

Oxidative Stress leads to Increase, Cell Death 

Moderate 

There is moderate empirical evidence to support the relationship between oxidative stress and increased cell death. Many studies demonstrate incidence concordance, dose concordance, and time concordance. However, there are limited data pertaining to low doses of the radiation stressors (X-rays, gamma rays, 12C ions) used to investigate the relationship. 

KE#1392 → KE#2066:  

Oxidative Stress leads to Altered Signaling Pathways 

High 

There is strong empirical evidence for this relationship. A number of studies demonstrated incidence concordance. Most studies that examined the effects of a range of stressor doses showed dose concordance, and most studies that analyzed oxidative stress and signaling pathways over multiple timepoints supported temporal concordance. This evidence was collected from studies using a variety of stressors, including ionizing radiation in doses as low as 0.125 Gy, in in vitro cell and in vivo mouse, rat, and pig models. 

Non-adjacent

KE#1392 → KE#2089:  

Oxidative Stress leads to Altered Bone Cell Homeostasis 

Moderate 

There is a moderate body of evidence showing concordance between oxidative stress and altered bone cell homeostasis. A few studies demonstrated incidence concordance, most studies that examined the effects of a range of doses demonstrated dose concordance, and most studies that examined oxidative stress and bone cell dysfunction over multiple timepoints provided evidence in support of temporal concordance. However, the evidence for dose concordance is weak as only a single study measured the KEs at multiple doses. Ionizing radiation (X-rays and gamma rays) in doses as low as 1 Gy and microgravity were the stressors used in studies. The models used included in vitro cells and in vivo rats and mice. 

KE#1825 → KE#2089:  

Increase, Cell Death leads to Altered Bone Cell Homeostasis 

High 

There is a large body of evidence indicating concordance between increased cell death to altered bone cell homeostasis. Most studies demonstrated time, dose, and incidence concordance. Ionizing radiation (X-rays and gamma rays) in doses as low as 0.5 Gy and microgravity were the stressors used in studies. The models used included in vitro cells and in vivo rats and mice. 

KE#2066 → KE#2089: Altered Signaling Pathways leads to Altered Bone Cell Homeostasis 

High 

There is strong evidence showing concordance to support the KER. Evidence in most of the studies collected supported time, dose, and incidence concordance. Ionizing radiation (X-rays and gamma rays) at doses as low as 0.5 Gy and microgravity were the stressors used in studies. The models used included in vitro cells and in vivo rats and mice. 

KE#2089 → KE#2090:  

Altered Bone Cell Homeostasis leads to Increase, Bone Remodeling 

Moderate 

Dose and time concordance between altered bone cell homeostasis and bone remodeling are currently supported by moderate evidence. A number of studies demonstrate incidence concordance and most studies that analyzed altered bone cell homeostasis and bone remodeling over multiple timepoints demonstrated time concordance. However, some studies showed changes to one or more endpoints that were inconsistent with the change expected following the stressors. Also, there were no studies that could be used to evaluate the dose concordance of the KEs at multiple doses. The relationship was demonstrated using X-rays at doses as low as 2 Gy and microgravity in in vitro cell and in vivo rat and mouse models. 

KE#2090 → AO#2091:  

Increase, Bone Remodeling leads to Occurrence, Bone Loss 

Moderate 

There is moderate evidence for concordance between bone remodeling and bone loss. Most studies demonstrate time and incidence concordance. However, no studies measured both KEs at multiple doses of the stressor. The relationship was demonstrated using X-rays at doses as low as 2 Gy and microgravity in in vitro cell and in vivo rat, mouse, and monkey models. 

Non-adjacent

MIE#1686 → KE#2089:  

Deposition of Energy leads to Altered Bone Cell Homeostasis 

High 

A strong body of evidence shows dose- and time-response effects of ionizing radiation. Data from studies show that radiation exposure indirectly increases osteoclast activity and decreases osteoblast activity in a dose-dependent manner. X-rays and gamma rays in doses ranging from 0-30 Gy were used to study the effects of radiation on bone cells in in vitro and ex vivo cell models, in vivo mouse and rat models, and human models. About a week after radiation exposure, with increasing radiation doses, numbers and activity of osteoblasts decrease, while numbers of osteoclasts increase. 

Non-adjacent

MIE#1686 → KE#2090:  

Deposition of Energy leads to Increase, Bone Remodeling 

High 

The empirical evidence for deposition of energy leading to bone remodeling is high. Imbalanced bone remodeling caused by ionizing radiation is directly related to the absorbed dose. Bone remodeling is affected after exposure of mice and rats to 0.5-24 Gy of X-ray, gamma ray, proton, and 56Fe ion radiation. Few studies examine the time course of this KER, but changes to bone remodeling occur from 7 to 60 days post-irradiation. 

Non-adjacent

MIE#1686 → AO#2091:  

Deposition of Energy leads to Occurrence, Bone Loss 

High 

There is strong evidence for the deposition of energy leading to bone loss. X-rays, gamma rays, protons, and heavy ions from 0.05 to 64 Gy delivered to rat, mouse, and human models were used to assess this relationship. By comparing the results of studies using either high or low dose radiation, there is a consensus that bone loss from low dose exposure is less than that from high dose exposure. Studies also show that bone loss can be observed from 1 week to years after irradiation but is mostly found in the first few months after exposure. 

Known Modulating Factors

Modulating factors (MFs) may alter the shape of the response-response function that describes the quantitative relationship between two KES, thus having an impact on the progression of the pathway or the severity of the AO.The evidence supporting the influence of various modulating factors is assembled within the individual KERs. More help

Multiple factors can modulate this AOP. A few of the recurring modulators in this AOP are described in the table below. 

It is established that age modulates loss of bone mass and quality following irradiation (Willey et al., 2011) but no consistent evidence was retrieved for specific KEs in the AOP. Age-associated reduced estrogen levels compound the harmful effects of radiotherapy on bone loss in elderly patients (Pacheco and Stock, 2013). Estrogen, which is lower in old age, decreases osteoclast activity and increases osteoblast activity by inhibiting the production of interleukin (IL)-6 in osteoblasts (Pacheco and Stock, 2013). In rats, increased age from 6 to 20 weeks was associated with concurrent cortical bone loss and osteoblast dysfunction during spaceflight (Fu et al., 2021). However, rats of this age have barely reached skeletal maturity and the association was weak. More studies are required to make a definitive conclusion about the effect of age on bone loss from exposure to the space environment (Fu et al., 2021; Moussa, Goldsmith and Komorova, 2022). 

There are limited data on sex related differences in both radiotherapy and spaceflight settings. Spaceflight studies poorly investigate sex differences because of low samples sizes and few model types (Fu et al., 2021; Moussa, Goldsmith and Komorova, 2022), with even less data available for humans (Moussa, Goldsmith and Komorova, 2022). Most human studies demonstrate equal bone loss in males and females after spaceflight, although more evidence is required as females make up less than 20% of astronauts (Lang et al., 2017). The KEs are initiated regardless of the sex of the animals, making this AOP sex-unspecific (Bandstra et al., 2009; Bandstra et al., 2008; Chandra et al., 2017; Chandra et al., 2014; Willey et al., 2010; Zhang et al., 2019). 

Other modulating factors that influence the AOP include drugs and genetics. A few xenobiotics, particularly antioxidants, osteoclast inhibitors, and osteoblast activators, were found to have various effects on bone remodeling activity and ultimately bone loss (Chandra et al., 2014; Huang et al., 2019; Huang et al., 2018; Li et al., 2020a; Li et al., 2020b; Li et al., 2018a; Liu et al., 2018; Lloyd et al., 2015; Yang et al., 2019; Zhang et al., 2020). Also, mutations in the SOST gene for sclerostin have a modulatory effect on the pathway leading to bone loss (Chandra et al., 2017). 

Modulating Factor 

Influence or Outcome 

KER(s) involved 

Osteoblast activators 

Inhibitors of osteoblast apoptosis or activators of pro-osteoclast signaling increase the number or activity of osteoblasts and subsequently increase bone formation. 

Altered signaling pathways to altered bone cell homeostasis 

Increase, cell death to altered bone cell homeostasis 

Altered bone cell homeostasis to increase, bone remodeling 

Increase, bone remodeling to bone loss 

Osteoclast inhibitors 

Inhibitors of osteocyte apoptosis or pro-osteoclast signaling decrease the number or activity of osteoclasts, subsequently decreasing bone resorption. 

Altered signaling pathways to altered bone cell homeostasis 

Increase, cell death to altered bone cell homeostasis 

Altered bone cell homeostasis to increase, bone remodeling 

Increase, bone remodeling to bone loss 

Antioxidants 

Adding or withholding antioxidants decreases or increases the level of oxidative stress respectively. Increased oxidative stress leads to a higher likelihood of bone loss. 

Deposition of energy to oxidative stress 

Oxidative stress to altered signaling pathways 

Oxidative stress to increase, cell death 

Increase, cell death to altered bone cell homeostasis 

Altered bone cell homeostasis to increase, bone remodeling 

Loss of function mutations in the SOST gene (as observed in sclerosteosis and van Buchem disease) 

Loss of function of the SOST gene for sclerostin (sclerostin is a Wnt receptor antagonist that inhibits osteoblastogenesis). Radiation does not affect osteoblast numbers, BMD, and BV/TV in SOST knockout mice (Chandra et al., 2017). Also, SOST knockout mice are more resistant to changes in remodeling markers (Chandra et al., 2017). 

Altered signaling pathways to altered bone cell homeostasis 

Altered bone cell homeostasis to increase, bone remodeling

Increase, bone remodeling to bone loss 

Old age 

Lower estrogen at old age is thought to contribute to the detrimental effects of radiotherapy on bone loss in elderly patients. 

Altered bone cell homeostasis to increase, bone remodeling

Increase, bone remodeling to bone loss 

Quantitative Understanding

Optional field to provide quantitative weight of evidence descriptors.  More help

There is a low quantitative understanding for the KERs in this AOP. Many studies have quantified the changes in consecutive KEs after a specific stressor dose. However, due to varying experimental parameters, including experimental model, radiation type, doses, dose rate, and timepoints, a quantitative relationship is difficult to determine between most adjacent KEs in the pathway. KERs between the MIE and downstream KEs are readily quantified, as changes to the upstream KE, in this case the dose, dose rate, and radiation type applied to the model, are determined in the experimental method and can be more easily standardized across studies. KERs that do not include the MIE are more difficult to quantify, as the perturbation to the upstream KE cannot be standardized to determine its effects on a downstream KE, as it is the product of the applied stressor and the resulting changes to KEs that came before it in the pathway.

Review of the Quantitative Understanding for each KER 

Defining Question 

High (Strong) 

Moderate 

Low (Weak) 

To what extent can a change in KEdownstream be predicted from KEupstream? With what precision can the uncertainty in the prediction of KEdownstream be quantified? To what extent are the known modulating factors of feedback mechanisms accounted for? To what extent can the relationships described be reliably generalized across the applicability domain of the KER?   

Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream; uncertainty in the quantitative prediction can be precisely estimated from the variability in the relevant KEupstream measure. Known modulating factors and feedback/feedforward mechanisms are accounted for in the quantitative description. Evidence that the quantitative relationship between the KEs generalizes across the relevant applicability domain of the KER. 

Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream; uncertainty in the quantitative prediction is influenced by factors other than the variability in the relevant KEupstream measure. Quantitative description does not account for all known modulating factors and/or known feedback/feedforward mechanisms. The quantitative relationship has only been demonstrated for a subset of the overall applicability domain of the KER. 

Only a qualitative or semi-quantitative prediction of the change in KEdown can be determined from a measure of KEup. Known modulating factors and feedback/feedforward mechanisms are not accounted for. Quantitative relationship has only been demonstrated for a narrow subset of the overall applicability domain of the KER. 

MIE#1686 → KE#1392:  

Deposition of Energy leads to Oxidative Stress 

Moderate 

The quantitative understanding of the MIE leading to oxidative stress is moderate. The most common dose of radiation applied to models when examining the effects of energy deposition on oxidative stress is 2 Gy. In general, exposure to 2 Gy of low LET radiation, such as X-rays, gamma rays, or protons, resulted in increased ROS production compared to high LET radiation, such as heavy ions. 2 Gy of low LET radiation results in increases of ~15-200% to ROS production and ~136-433% to levels of other oxidative stress markers, as well as decreases of ~9-70% to levels of antioxidants, with some studies not demonstrating significant changes to any oxidative stress endpoints. 2 Gy of high LET radiation results in increases of ~120-125% to ROS production.  

KE#1392 → KE#1825:  

Oxidative Stress leads to Increase, Cell Death 

Low 

The quantitative understanding of oxidative stress leading to cell death is low. Increases of ~20-400% in ROS levels and ~100% in other oxidative stress markers as well as decreases of ~34-75% in antioxidants cause a ~60-440% increase in apoptosis and a ~125% increase in autophagy. Some studies show significant changes to one or more endpoints that are inconsistent with the expected effect of the stressor. 

KE#1392 → KE#2066:  

Oxidative Stress leads to Altered Signaling Pathways 

Low 

The quantitative understanding of oxidative stress leading to altered signaling pathways is low. A ~35-260% increase in RONS, a ~20-110% increase in oxidative stress markers (such as malondialdehyde (MDA), protein carbonylation, p67 levels), and/or a ~10-76% decrease in antioxidants results in a ~20-500% increase in expression and activity of osteoclast differentiation signaling molecules and/or a ~10-96% decrease in expression and activity of osteoblast differentiation signaling molecules. Some studies show significant changes to one or more endpoints that are inconsistent with the expected effect of the stressor.  

Non-adjacent

KE#1392 → KE#2089:  

Oxidative Stress leads to Altered Bone Cell Homeostasis

Low 

The quantitative understanding of oxidative stress leading to altered bone cell homeostasis is low. Many studies quantify oxidative stress and altered bone cell homeostasis following a stressor; however, studies often measure different endpoints in different experimental models and the change to bone cell homeostasis cannot be precisely predicted from the level of oxidative stress. Furthermore, the effect of modulating factors is not well quantified in studies.

KE#1825 → KE#2089: Increase, Cell Death leads to Altered Bone Cell Homeostasis 

Low 

The quantitative understanding of increased cell death leading to altered bone cell homeostasis is low. Increases of ~100-600% in osteoblast apoptosis and/or ~50-1500% osteocyte apoptosis result in decreases of ~30-63% in osteoblastogenesis markers and ~47-73% in osteoblast/osteocyte number, as well as increases of ~200-250% in osteoclastogenesis markers and ~50-1100% in osteoclast number.  

KE#2066 → KE#2089: Altered Signaling Pathways leads to Altered Bone Cell Homeostasis 

Moderate 

The quantitative understanding of altered signaling pathways leading to altered bone cell homeostasis is moderate. Altered bone cell homeostasis can be roughly predicted from measures of the protein expression and activity of key signaling molecules for osteoblasts and osteoclasts. Decreases of ~40-90% to expression and activity of osteoblast differentiation signaling molecules result in decreases of ~48.2-93.9% in osteoblastogenesis markers. Increases of ~30-300% to expression and activity of osteoclast differentiation signaling molecules result in increases of ~30-460% in osteoclastogenesis markers.   

KE#2089 → KE#2090: Altered Bone Cell Homeostasis leads to Increase, Bone Remodeling 

Low 

The quantitative understanding of altered bone cell homeostasis to bone remodeling is low. Decreases of ~17-75% in osteoblastogenesis markers and/or increases of ~22-300% in osteoclastogenesis markers resulted in decreases of ~16-100% in bone formation and increases of ~6-26% in the structural modeling index (SMI). Both microgravity and ionizing radiation exposure have the same effect on altered bone cell homeostasis and bone remodeling markers. However, these effects are more significant for ionizing radiation exposure. 

KE#2090 → AO#2091: Increase, Bone Remodeling leads to Occurrence, Bone Loss 

Low 

The quantitative understanding of bone remodeling leading to bone loss is low. There is an abundance of quantitative data pertaining to the effects of stressor-induced bone remodeling on bone loss. However, the decreases in bone formation do not precisely predict the resulting bone loss. Decreases of ~20-100% in bone formation and increases of ~6-26% in SMI, cause decreases of ~9-82% in bone structure. Some studies showed changes to one or more endpoints that are inconsistent with the expected effect of the stressor. 

Non-adjacent

MIE#1686 → KE#2089:  

Deposition of Energy leads to Altered Bone Cell Homeostasis

Low 

The quantitative understanding of the deposition of energy leading to altered bone cell homeostasis is low. Many studies quantify altered bone cell homeostasis following radiation exposure; however, it is difficult to compare results and quantify relationships as each study uses different models, stressors, doses and time points. In addition, the influence of modulating factors has not been completely assessed. Thus, no model has been established to predict the changes in bone cell homeostasis after the deposition of energy. 

Non-adjacent

MIE#1686 → KE#2090:  

Deposition of Energy leads to Increase, Bone Remodeling

Low 

The quantitative understanding of the deposition of energy leading to bone remodeling is low. Many studies quantify bone remodeling; however, it is difficult to compare results and quantify relationships as each study uses different stressors, doses and time points. In addition, the influence of modulating factors such as sex have not been completely assessed. Thus, no model has been established to predict the changes in bone remodeling after the deposition of energy. 

Non-adjacent

MIE#1686 → AO#2091:  

Deposition of Energy leads to Occurrence, Bone Loss

Moderate 

The quantitative understanding of the deposition of energy leading to bone loss is moderate. Bone loss can be partially predicted by the dose of deposited energy. For example, a 2 Gy dose of 56Fe ions will consistently reduce BV/TV by about 20-30%. However, these changes depend on the bone studied, the dose, the radiation type, and the time point. No model has been established to precisely predict the changes in bone loss after the deposition of energy.

Considerations for Potential Applications of the AOP (optional)

Addressess potential applications of an AOP to support regulatory decision-making.This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. More help

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.  

References

List of the literature that was cited for this AOP. More help

Alwood, J. S. et al. (2010), "Heavy ion irradiation and unloading effects on mouse lumbar vertebral microarchitecture, mechanical properties and tissue stresses", Bone, Vol. 47/2, Elsevier, Amsterdam, https://doi.org/10.1016/j.bone.2010.05.004 

Arfat, Y. et al. (2014), "Physiological Effects of Microgravity on Bone Cells", Calcified Tissue International, Vol. 94/6, Nature, https://doi.org/10.1007/s00223-014-9851-x 

Azzam, E. I., J. P. Jay-Gerin, and D. Pain. (2012), "Ionizing radiation-induced oxidative stress and prolonged cell injury", Cancer letters, Vol. 327/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/j.canlet.2011.12.012 

Balasubramanian, D (2000), "Ultraviolet radiation and cataract", Journal of ocular pharmacology and therapeutics, Vol. 16/3, Mary Ann Liebert Inc., Larchmont, https://doi.org/10.1089/jop.2000.16.285. 

Bandstra, E. R. et al. (2009), "Musculoskeletal changes in mice from 2050 cGy of simulated galactic cosmic rays", Radiation Research, Vol. 172/1, https://doi.org/10.1667/RR1509.1 

Bandstra, E. R. et al. (2008), "Long-term dose response of trabecular bone in mice to proton radiation", Radiation Research, Vol. 169/6, https://doi.org/10.1667/RR1310.1 

Baxter, N. N. et al. (2005), "Risk of Pelvic Fractures in Older Women Following Pelvic Irradiation", JAMA, Vol. 294/20, https://doi.org/10.1001/jama.294.20.2587

Bellido, T. (2014), "Osteocyte-Driven Bone Remodeling", Calcified Tissue International, Vol. 94/1, Nature, https://doi.org/10.1007/s00223-013-9774-y

Bikle, D. D. and B. P. Halloran. (1999), "The response of bone to unloading", Journal of Bone and Mineral Metabolism, Vol. 17/4, Nature, https://doi.org/10.1007/s007740050090

Boyce, B. F. and L. Xing. (2007), "The RANKL/RANK/OPG pathway", Current Osteoporosis Reports, Vol. 5/3, Nature, https://doi.org/10.1007/s11914-007-0024-y 

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