Apis mellifera), which USEPA considers a surrogate for Apis and non-Apis bees. We compared these toxicity data to explore possible trends. This analysis indicated a significant correlation between acute contact and oral median lethal dose (LD50) values for adult honey bees . Using default EPA modeling assumptions, where exposure for an individual bee is roughly 12x lower through contact than through ingestion, the analysis indicates that the oral LD50 is similarly if not more protective of the contact LD50 for the majority of pesticides and modes of action evaluated. The analysis also provided evidence that compounds with a lower acute toxicity for adults through contact and oral exposure pathways may still be acutely toxic for larvae. The acute toxicity of herbicides and fungicides was higher for larvae relative to oral and contact toxicity for adult honey bees for the same compounds and the no observed adverse effect level (NOAEL) from chronic toxicity studies were lower for larvae relative to adults, indicating increased sensitivity of larvae. When comparing 8-day LD50 values between single dose larval acute studies to those derived from repeat dose 22-day larval chronic toxicity studies, the LD50 values derived from chronic studies were significantly lower than those from acute toxicity tests .Current USEPA ecological risk assessments for pesticide registration include a determination of potential risks to bees. Toxicity data are submitted to support these assessments and the USEPA maintains a large database containing acute and chronic toxicity data on adult and larval honey bees ( Apis mellifera) is frequently used for its pollination services in agriculture [e.g., Varroa destructor), pathogens , pesticides, lack of adequate nutrition [e.g., Insect pollination is required to produce approximately $30 billion worth of agricultural products in the US annually and provides a key ecosystem service within many natural environments , 2. The iculture . Additioiculture , 6. Effoutrition , and pooutrition . Furtherutrition , 8. Noneutrition . Bees caon e.g.,  and the on e.g., .i.e., availability of standardized test method and ready availability) for lab and field-based experimentation [Organizations charged with determining the potential for ecological risks from pesticides including the USEPA  and the EFSA (European Food Safety Agency) have identified pollinator protection goals and require the submission of pollinator toxicity data when registering pesticides. When examining risks towards pollinators, honey bees are often used as a study species because of their agricultural importance and amenability  [The  to Bees  provides to Bees  and OECD to Bees ); adult  to Bees ); the ad to Bees ), larval to Bees ), and la to Bees ). CollecD GD 75)  and fullD GD 75)  level.i.e., lethal dose for 50% of the bees tested; LD50) and chronic toxicity  values are calculated for adult and larval worker honey bees for a given pesticide. The toxicity endpoints generated from Tier 1 toxicity studies can then be compared to model estimates of contact/oral exposure to estimate risk to individual bees .in vitro assays and predictive models  are emerging that leverage existing data and show promise toward more efficient yet equally protective means of evaluating risk across a broader range of taxa . While reduced reliance on whole animal testing is an important benefit of such efforts, the development of predictive models and in vitro assays or possible reductions in data requirements must be based on sound science demonstrating that such tools are relevant and reliable or that other lines of evidence are suitably predictive if they are to gain regulatory acceptance [et seq.). This analysis is intended to examine patterns among these data and assess whether efficiencies can be gained in targeting the specific studies needed for risk assessment.Within the field of toxicology, there is a general interest in reducing, replacing, and refining the current reliance on animal testing , 23. Whiceptance . Over thThis analysis utilizes EPA’s honey bee toxicity database to compare the relative toxicity of insecticides, fungicides and herbicides across acute (single dose) and chronic (repeat dose) tests with adult and larval worker bees. The objective of this analysis was to explore the relative sensitivity of larval bees versus adults and to determine the predictive utility of: acute contact toxicity data relative to acute oral toxicity in adults; of acute toxicity data for chronic toxicity; and of chronic (repeat dose) larval toxicity data for acute (single dose) larval toxicity.i.e., μg ai/larva), USEPA calculates exposure from these studies in terms of daily dose . USEPA recognizes that it is not possible to readily determine the actual volume of diet consumed by the developing larvae each day the organism is dosed. Therefore, daily dose is calculated by dividing the cumulative dose by 4 .This retrospective analysis includes toxicity data from Tier I honey bee toxicity studies conducted in accordance with OECD and/or OCSPP test guidelines/guidance documents including: the adult acute contact , pesticide class , and chemical mode of action (MOA)  using multiple reference databases (See pesticide classification sources in https://irac-online.org/) and the Pesticide Properties Database  . When cobase See . For allbase See . PesticiWhen comparing the relative acute oral toxicity across pesticides for both adults and larvae, we relied upon the following USEPA acute toxicity classification categories :50 ≥ 11 μg a.i./bee);Practically Non-toxic (LD50 < 11 μg a.i./bee); and,Moderately Toxic (2 μg a.i.< LD50 ≤ 2 μg a.i./bee).Highly Toxic  the highest tested dose or are less than (<) the lowest dose level. When classifying toxicity values, we categorized non-definitive endpoints, which had “>” values as if they were definitive. Because of their non-definitive nature, we distinguished these values from the definitive endpoints when representing them visually. If an endpoint value was < 2 μg a.i/bee, we classified it as “highly toxic non-definitive.” If an endpoint had either < or > signs expressed within the range of LDhttps://cfpub.epa.gov/ecotox/). All mortality-based honey bee toxicity endpoints included in this retrospective analysis are extracted from DERs that were completed prior to August 2019. Due to this cut-off date, some chemicals and endpoints were not included in the analysis. During USEPA’s review process, each DER is assigned a specific study classification based on quality and adherence to established guidelines. Studies classified as “acceptable” fully adhere to the standardized testing guidelines while “supplemental” studies deviate somewhat from the standardized testing conditions, but the deviations are not considered serious enough to compromise scientific integrity of the results. In this analysis, we only included studies and their endpoints if they were classified as either “acceptable” or “supplemental.” Studies classified as “invalid” are not scientifically sound and were excluded from further analysis. Additionally, we only included endpoints from studies testing technical grade active ingredients ; therefore, data on typical end-use products  were not included in the analysis. See For data curation and screening, within the USEPA Office of Pesticide Programs (OPP), the Environmental Fate and Effects Division (EFED) routinely produces Data Evaluation Records (DERs), which represent the agency’s independent review, evaluation, and endpoint selection for registrant-submitted (unpublished) and open literature pesticide toxicity studies. The toxicity endpoints and primary study information from the honey bee toxicity studies are available in though EPA’s ECOTOXicology Knowledgebase  from AAO and AAC studies. We excluded pesticides not currently registered for use in the U.S. and toxicity endpoints reported in non-standard units that couldn’t be converted to μg a.i./bee. Available endpoints from these acute adult studies are often non-definitive  because of maximum dose requirements for testing under the guidelines. Despite the uncertainty associated with non-definitive endpoints, they can provide meaningful information for risk assessment [e.g., insecticides). The analysis included non-definitive values in comparisons where there was one definitive value and one non-definitive value (no comparisons were made between two non-definitive endpoints). This analysis also utilized larval LD50 values generated from LAO and LCO study guidelines. For pesticides with multiple toxicity endpoints derived from independent studies, the analysis utilized the lowest or most definitive LD50 value. For example, if two studies resulted in LD50 values of 0.5 and 0.1 μg a.i./bee, we used 0.1 μg a.i./bee as the LD50 value. When both non-definitive values and definitive value(s) were present, the analysis utilized the definitive value. The analysis also excluded acute toxicity data extending beyond the 48-hour time interval to ensure the endpoints represented the same study duration. When performing an analysis of adult bee acute oral and contact toxicity we compared the lethal dose to 50% of the organisms tested (sessment  and thei50 (μg a.i./bee or μg a.i./larva) from both adult and larval acute (single dose) toxicity study guidelines (AAO and LAO) as well as the Day 8 (D8) LD50 estimates from larval chronic (repeat dose) toxicity studies (LCO). Endpoints from chronic studies can be expressed as the cumulative dose consumed during the exposure period (μg a.i./bee) or as the daily dose consumed per individual (μg a.i./bee/day). We compared all endpoints in common units (i.e. μg a.i./bee/day or μg a.i./larva/day) because daily dose is used by the current USEPA exposure model for honey bees during ecological risk assessments [When comparing oral acute and chronic toxicities, we included mortality data from honey bee adult and larval toxicity studies that adhered to four OECD test guidelines: AAO; ACO; LAO and LCO. This included the estimated LDessments  and is t50) and no/lowest observed adverse effect concentration . Although typically reported, we did not use NOAEL and LOAEL values from the acute studies (AAO and LAO) in any analysis. Additionally, we excluded any studies on chemical degradates, studies containing multiple active ingredients, and TEP-based exposures from the analysis. As noted earlier, while ingestion of treated diet  is the primary focus of the larval toxicity studies, it is important to note that larvae are also in direct contact during the bioassay. However, measurement endpoints from the larval studies are evaluated in risk assessment assuming the oral route of exposure is dominant [We excluded endpoints based on dietary concentrations such as median lethal concentration , using LD50 values standardized by μg a.i./bee.When comparing the relative toxicities between oral and contact endpoints for a given pesticide, we employed a relative sensitivity ratio  values. Ratios calculated using both a non-definitive and a definitive endpoint provide a conservative estimate because a non-definitive  endpoint is an underestimation of the actual LD50 and is typically derived from the highest tested dose in an individual study as the actual LD50 is higher than what was actually tested.A value of 1 signifies no difference between oral and contact toxicity; whereas values less than 1 represents higher oral toxicity and values greater than 1 represent higher contact toxicity. The absence of sample variance data corresponding to the reported LD50 value from the acute oral toxicity studies (either AAO or LAO) to the most sensitive mortality NOAEL from the chronic toxicity study (either ACO or LCO):Acute-to-chronic toxicity ratios (ACR) serve as a means to estimate the acute or chronic toxicity of a chemical towards an organism when only acute or chronic toxicity data are available . We calci.e., larval mortality at Day 8; pupal mortality at Day 15; and adult mortality or emergence at Day 22). In this analysis, we focused on the most sensitive mortality NOAEL endpoint when calculating larval ACRs. Additional measurement endpoints  are also provided in these studies and occasionally may represent a more sensitive response than mortality. However, to minimize potential confounding factors, these endpoints are not included in this comparison.The ACO (adult) studies provide only a single mortality NOAEL endpoint; however, the LCO  studies, multiple mortality NOAEL values  oral toxicity studies, LCO studies use a repeat daily dosing  while LAO studies evaluate the effects of a single dose. USEPA recognizes that the likelihood of acute (single dose) exposure for larval honey bees may be limited under natural conditions; however, the LD50 value is useful in characterizing the acute toxicity of a pesticide and is consistent with what is done for other taxa . When both acute and chronic larval toxicity studies were available for a chemical, we compared the single dose larval acute LD50 from the LAO study to the day eight (D8) LD50 estimates from the LCO study. If multiple LD50 values were available for a single active ingredient under either study guideline, we selected the most sensitive LD50 for comparisons. The analysis excludes non-definitive LD50 values. We compared endpoints using a ratio of the LAO to LCO LD50 values:Larval chronic oral toxicity studies (LCO) are primarily aimed at determining NOAEL and LOAEL values; however, an LD50 endpoints in JMP® Pro 14 . We produced additional visualizations using JMP® Pro 14. Lastly, a Wilcoxon Signed Rank Test on matched pairs (α = 0.05) was used to compare the LAO and LCO based LD50 estimates. When comparing experimental endpoints to estimated exposures through food consumption and contact for adults and larvae, we relied upon default exposure factors included in BeeREX v.1.0 (https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/models-pesticide-risk-assessment#beerex) and as described in the USEPA 2014 [The analysis utilized Microsoft Excel to perform calculations and visualizations for sensitivity comparison ratios across study types and pesticide classifications. We used linear regression and a Spearman’s correlation analysis when investigating the relationship between log-transformed definitive AAO and AAC LDEPA 2014 .In total, 1,888 studies in the database were considered for analysis prior to data screening. Then screening criteria were implemented to ensure only the most robust comparisons were generated see . As a rei.e., 33 of 40 fungicides and 50 of 60 herbicides; 50 values for both studies. Based on the requirement of at least one endpoint being definitive, there were 49 chemicals that had endpoints that could be compared. The final dataset for comparing the results of oral and contact studies for the same pesticide, was therefore limited to 31 insecticides, 10 herbicides, 7 fungicides and one nematicide  are used to calculate multiple endpoints. In the available dataset, AAO studies had a relatively low proportion (31%) of definitive toxicity endpoints; however, NOAEL values from ACO tests were all definitive ; however, 65% of the larval LD50 endpoints were definitive (The primary toxicity endpoint from the adult (AAO) and larval (LAO) acute oral toxicity studies is the LDfinitive . For thefinitive . The ana50 data, provided in 50 ≤ 2 μg/bee), moderately toxic (2 < LD50 < 11 μg/bee) or practically non-toxic (LD50 >11 μg/bee) on an acute exposure basis. 50, insecticides are primarily classified as highly- or moderately toxic on an acute exposure basis; however, herbicides and fungicides are predominately classified as practically non-toxic to bees on an acute exposure basis. Non-definitive (ND) endpoints for highly and moderately toxic categories are provided separately; these are combined with definitive endpoints for the practically non-toxic category (defined as LD50 ≥11ug/bee). Larval LD50 values generated from LAO and LCO study guidelines are combined, the most sensitive estimate was plotted for chemicals that had estimates for both. For the larval LD50 values the patterns are similar; however, a greater proportion of herbicides and fungicides were classified as highly to moderately toxic.All available LDOverall, there was a significant positive correlation between AAO and AAC log transformed endpoints  between oral and contact LD50 values there is a generalized pattern that suggests the acute oral LD50 is as sensitive if not more sensitive than the acute contact LD50, as illustrated in 10R ≤ 0. Nine pesticides, 7 neurotoxicant insecticides , one fungicide (captan) and 1 herbicide (bromoxynil), had R values ≤ 0.1  and are depicted in 10R ≤ -1 which signifies a higher degree of oral toxicity (10-fold or more) relative to contact toxicity. Comparatively, eight pesticides had R values ≥ 1, indicating relatively higher acute contact toxicity for these pairs (10-fold or more). These nine pesticides included 6 neurotoxicant insecticides , one respiration inhibitor/regulator insecticide , and two biosynthesis inhibiting fungicides . These are depicted in 10R values ≥ 1.When comparing ratios  and 2 fungicides  with non-definitive oral LD50 values.The USEPA’s pesticide risk assessment process for bees assumes that the estimated environmental concentrations (EECs) for adult contact and oral routes of exposure are approximately 12x different . This i50 values from the larval acute (single dose) oral toxicity studies  and the Day 8 LD50 estimates from the larval chronic (repeat dose) studies . The LD50 values from the LAO studies and those derived from LCO studies were found to be significantly different  with LD50 values derived from chronic tests being significantly lower than those from single exposure larval testing. The LD50 comparisons were made directly between 15 individual pesticide active ingredients derived from 15 different chemical classes spanning 6 different MOAs with several studies representing neurotoxicants and biosynthesis inhibitors. The comparison between the LAO and LCO resulted in only two chemicals  where the single dose LD50 value was more sensitive than the repeat dose LD50 value.Comparisons were made  between 50 values determined in their respective studies. The AAO toxicity data were available for 152 pesticides. Since the LAO studies were more limited in number than any other guideline  studies. The 11 pesticides span 10 different chemical classes, but only include insecticides and one herbicide, and eight of the insecticides are neurotoxicants. Notably, this dataset only includes one neonicotinoid, due to the cut off in timing for DERs and endpoints that were available for this analysis. For each of the comparisons (LAO: AAO or LCO:AAO) 8 pesticides could be compared. The AAO LD50 value was more sensitive than the LAO and LCO based LD50 value in 5 and 1 of the pesticides respectively . There were 69 ACO toxicity studies, with 59% of them having both mortality-based NOAEL and LOAEL values. i.e., more sensitive NOAEL values) of fungicides, herbicides and miticides to larvae relative to adults, while for insecticides the average NOAEL for adults and larvae was within one standard error.The available dataset contains a total of 96 LCO studies, most of which (85%) reported a mortality-based NOAEL and LOAEL from at least one of the time points  in the ACO study; whereas, for the LCO study, only 13 pesticides had non-definitive LOAEL values. For one pesticide  there was no established NOAEL as the study had statistically significant effects at all test levels. The paired NOAEL endpoint comparisons span a variety of MOAs and chemical classes  had a distribution of ratios that predominantly exceeded the red dashed line indicating a generally more sensitive adult NOAEL and a likely larger risk potential for adult bees. The larval NOAEL values were more sensitive than the adult NOAEL counterparts in for 40 (70%) of the 57 chemicals. Under the default exposure assumptions in risk assessment ; based o.50 values and the ACO mortality-based NOAEL values. While there were 49 chemicals with both of these studies, only 14 had definitive values for both. In terms of the chemicals that had a non-definitive LD50 from the AAO study, 13 had reported mortality effects in their ACO studies and defined a LOAEL. For the 14 chemicals that had definitive values for both studies, the ACRs ranged from 0.94 to 38. The only pesticide with an ACR less than 1 was the herbicide bromoxynil, which had an ACR of 0.94. The other two herbicide adult ACRs were 22 and 38 (Acute-to-chronic ratios (ACRs) for adult honey bees were calculated using the AAO LD2 and 38 .50 values relative to the most sensitive larval daily dose mortality or adult emergence-based NOAEL from the LCO study. Larval ACRs ranged from 1.8 to 52 for the 23 chemicals that had definitive acute LD50 values. There were another 17 chemicals with non-definitive LD50 values from the LAO study. Their LCO counterpart studies also did not define an LD50 based on 8-day mortality, and for 9 of them no effects were observed at the highest doses tested. An additional review of the larval ACR based on the LCO-derived LD50 allowed for 31 chemical comparisons  between contact and oral endpoints, this analysis found that only 16% of chemicals had AAC LD50 values ≥12x AAO LD50 and the majority (84%) of compounds had less than a five-fold difference between LD50 values  values introduces some uncertainty into the R values because the true endpoint value is unknown, it permits the inclusion of compounds with vastly different toxicities across exposure pathways  in the analysis. For example, half of the six pesticides had an R value ≥ 1 (indicating relatively higher contact toxicity) were in the pyrethroid insecticide class. This may indicate differences in the adsorption, distribution, metabolism, and/or excretion between contact and dietary exposure for this class of chemicals and may provide useful information when characterizing risks from these compounds. While two fungicides also had R value ≥ 1, they both had non-definitive acute oral LD50 values; therefore, caution should be exercised in interpreting the significance of this ratio for these pesticides. Ultimately, the inclusion of some non-definitive values results in more conservative ratios because the non-definitive endpoint value is an overestimation of toxicity.Despite testing different exposure pathways, this retrospective analysis indicates that adult acute contact (AAC) and adult acute oral (AAO) LDork (See ), the di0 values . This fi50, larval chronic (repeat dose) oral toxicity studies (LCO) have also been used to derive an LD50 value that can be used as a surrogate for a single-dose LAO LD50. To account for the difference in exposure between the two study types, the comparison between the LAO and Day 8 LD50 from LCO studies values are made using a converted daily dose, where dosing is normalized to essentially an equivalent per day basis (μg/bee/day). We report that LD50 endpoints from LCO studies were more sensitive relative to LD50 values from LAO studies . The endpoints used in this analysis were all definitive. Despite being primarily used for determining chronic NOAEL values, LCO studies can yield LD50 values that are lower and protective of those calculated in LAO studies. It is important to consider that this comparison was limited to only fifteen pesticides, and that two of the chemicals resulted in more sensitive LD50 values generated from the LAO study. The inclusion of a greater number of pesticides and MOAs would strengthen the understanding of this relationship. However, based on our current dataset the LCO appears to generate LD50 endpoints which can be considered protective relative to the LAO LD50 values.While the primary aim of larval acute oral toxicity studies (LAO) is to establish an LDi.e., insecticides, herbicides, fungicides, and other) using acute toxicity classifications . Conversely, larval chronic (LCO) LD50 values were generally more sensitive than the corresponding adult values in 88% of comparisons , either 3/8 or 5/8 of the studies give a ratio below 0.42, indicating a greater risk for larval honey bees. However, the limited dataset will need to be expanded to determine if the larval honey bees are indeed more sensitive than the adults across broader pesticide and MOA groupings. This observation of greater larval sensitivity was also observed in the chronic toxicity studies, discussed below. We also report that thiamethoxam had the largest difference between adult and larval endpoints  and larval chronic oral (LCO) NOAEL values were compared. The NOAEL is defined as the highest tested dose level which does not yield a significant effect relative to the control group and consequently, both the biological response and selected test concentrations can influence this endpoint. A variety of considerations are made when selecting dose level in a chronic toxicity study such as the estimated environmental concentrations of a pesticide or the inclusion of a “limit dose.” The impact of these factors on test concentration selection undoubtedly influenced the endpoints included in our dataset such that many chemicals reported NOAELs without having a definitive LOAEL. For these reasons, selected dose-levels may not always identify the exposures at which a chronic effect may begin to occur but are useful when establishing exposures which are unlikely to elicit an effect in risk assessment. Ultimately, dosage-level selection may have impacted the interpretation of 12 of the 29 compared ACO and LCO pairs as one or both of the studies had reported no observed effects at the maximum doses tested. Given this assumption, the analysis indicates that larval chronic mortality NOAELs were generally more sensitive (lower) than the corresponding adult values . Researc50 values more sensitive than the adult values. Therefore, in a risk assessment the likely result would be a greater estimation of risk for larvae  versus larval honey bees.Chronic mortality endpoints followed the same pattern as the acute toxicity studies regarding differences among types of pesticides. Insecticides, herbicides, and fungicides  were morr larvae . Four ner larvae , but thei.e., LD50 data) and the chronic data are unavailable  acute toxicity data exist . In comparison to the NOAEL from the same study, the NOAEL was 195 times more sensitive than the repeat dose LD50. The adult ACR was 2, which also indicates a more sensitive endpoint in the chronic study, but the difference was far less extreme.Larval ACRs were calculated for 23 and 31 pesticides for LAO and LCO-derived LDhttps://cfpub.epa.gov/ecotox/). Despite having a large honey bee toxicity database with relevant endpoints, the ability to generate direct comparisons across specific chemicals in this retrospective was limited by the extent of non-definitive values. Non-definitive values are useful for identifying dosages which are unlikely to elicit an effect for risk assessment purposes, but non-definitive values have limited utility in statistical analyses and direct comparisons across life stages. Another limitation of the available data for use in comparisons across tests and life stages is that resulting from studies that were conducted with a TEP as opposed to TGAI. The TEP studies represent approximately one third of all available adult contact and adult oral acute toxicity data. Spruill et al. [Insect pollinator testing is required to support risk assessment for the registration and re-registration of conventional pesticides in the United States (See FIFRA and 40CFR158). As a result, USEPA maintains one of the most comprehensive honey bee toxicity databases, containing toxicity endpoint data on both adult and larval life stages , as well as the importance of having captured both acute and chronic responses to a pesticide exposure. Moreover, the relationships between study endpoints identified in these analyses may help inform future efforts to streamline pollinator toxicity data needs and reduce future animal testing.The evaluation of data submitted subsequent to the release of USEPA’s  to Bees  and the S1 TableReferences for each endpoint are provided in (XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


Recessive Dystrophic Epidermolysis Bullosa (RDEB) is a devastating skin blistering disease caused by mutations in the gene encoding type VII collagen (C7), leading to epidermal fragility, trauma-induced blistering, and long term, hard-to-heal wounds. Fibrosis develops rapidly in RDEB skin and contributes to both chronic wounds, which emerge after cycles of repetitive wound and scar formation, and squamous cell carcinoma—the single biggest cause of death in this patient group. The molecular pathways disrupted in a broad spectrum of fibrotic disease are also disrupted in RDEB, and squamous cell carcinomas arising in RDEB are thus far molecularly indistinct from other sub-types of aggressive squamous cell carcinoma (SCC). Collectively these data demonstrate RDEB is a model for understanding the molecular basis of both fibrosis and rapidly developing aggressive cancer. A number of studies have shown that RDEB pathogenesis is driven by a radical change in extracellular matrix (ECM) composition and increased transforming growth factor-beta (TGFβ) signaling that is a direct result of C7 loss-of-function in dermal fibroblasts. However, the exact mechanism of how C7 loss results in extensive fibrosis is unclear, particularly how TGFβ signaling is activated and then sustained through complex networks of cell-cell interaction not limited to the traditional fibrotic protagonist, the dermal fibroblast. Continued study of this rare disease will likely yield paradigms relevant to more common pathologies. Wound healing is the body’s natural process to restore tissue function and integrity after mechanical or pathological insult. Unresolved wound healing leads to prolonged inflammation, extensive scarring and disrupted tissue architecture, which ultimately results in fibrosis and often leads to organ failure and associated morbidities, including cancer . FibrosiCOL7A1, the gene encoding type VII collagen (C7) [RDEB is a rare yet devastating skin-blistering disease caused by loss of function mutations in gen (C7) . RDEB isgen (C7) . Clinicagen (C7)  and, altgen (C7) . RDEB isgen (C7) .Historically, lack of epidermal—dermal adhesion was thought to be the primary pathology driving disease severity in RDEB . HoweverArguably, impaired wound healing is the most debilitating pathology in patients with RDEB and is driven by compromised epidermal-dermal adhesion as well as aberrant signaling. In the most comprehensive study of wound healing in an RDEB mouse model to date, major contributions from both the epidermal layer and dermal layer were identified. Delayed migration of keratinocytes was attributed to disorganized laminin-332—integrin a6b4—and subsequent signaling and delayed dermal healing, characterized by abnormal ECM expression, abnormal localization of myofibroblasts, and prolonged presence of inflammatory cells . These oInflammation occurs soon after injury when swelling from the blood vessel exudate accumulates. The fluid promotes healing and guides inflammatory cells, first neutrophils in large numbers followed by macrophages, to the wound site to prevent infection and control bleeding. The inflammatory stage persists through the proliferation stage and resolves before the final stage, maturation, is complete. As such unresolved inflammation is a constant to non-healing wounds and therefore a major focus of the wound healing field. Dogma describes macrophage clearance of short-lived neutrophils as essential for wound resolution, and chronic wounds often exhibit reduced markers of macrophages and increased or persistent evidence of neutrophils ,39,40,41Typically, once the wound has formed clots and is filled with inflammatory cells, the extracellular collagen bed will start rebuilding the new tissue during the proliferation stage of wound healing. The collagen-secreting fibroblasts in the fibrin clot differentiate into alpha-smooth muscle actin (α-SMA) expressing myofibroblasts and contribute to contraction to facilitate new tissue construction. Re-epithelialization of proliferating and migrating keratinocytes on the surface occurs and is expedited by hydrated wound beds from occlusive dressings . In the Finally, the maturation step of wound healing is also called the remodeling stage, in which the wound fully closes, all inflammatory cells and myofibroblasts are removed via apoptosis or macrophage clearance, and the ECM is remodeled to resemble homeostatic tissue. The thick collagen matrix bed from the proliferation phase contains cross-linked collagen fibers that contribute to firmer skin over the wounded area, even though the healed skin is still weaker than intact skin . When thRDEB is unique in being a disease where tissue damage, continued wound healing, bacterial challenge, and fibrosis lead to inevitable and lethal cancers . Animal TGFβ belongs to a large superfamily of activins and bone morphogenetic proteins that play an important role in the cellular synthesis of ECM proteins, proliferation, and wound healing . Three sIn the context of acute injury, TGFβ is released from the ECM through a wide variety of mechanisms, such as platelet secretion of TSP1, mechanical strain, or reactive oxygen species (ROS) generation ,69. TGFβRecent studies have suggested multiple pathological pathways activating TGFβ signaling in RDEB skin. TSP1 has higher bioavailability to activate TGFβ ligands in the ECM of RDEB patients since binding between C7 and TSP1 prevents TSP1 from activating the TGFβ pathway . In addiPrevious attempts to globally block the TGFβ ligand or receptors for the treatment of other diseases have resulted in developmental defects in vivo, chronic inflammation, and increased cancer risk . Given tSCCs arising in stratifying epithelia  contribute substantial cancer incidence and mortality yearly, with large numbers in lung cancer as well as esophageal and head neck cancers . CutaneoCOL7A1 mutation are not at increased risk of developing cancer, and COL7A1 mutation has not been associated with any non-RDEB cancer to date), the incidence of SCC in RDEB seems not to be driven by cell-intrinsic effects of mutation in COL7A1 but rather extrinsic effects of lack of C7.While the incidence of SCC in RDEB increases with increasing disease severity , mortality tracks incidence , suggestCOL7A1 mutation, has distinguished RDEB SCC from other SCC [CASP8 [CASP8 mutation does not explain the aggressive nature of RDEB SCC, it does point to RDEB SCC being “immune hot,” which has been linked to immune checkpoint success [As with all cancer, exceptions to this rule exist, and we are aware of a number of RDEB patients who have had multiple cSCC develop over many years without succumbing to metastatic disease, which in itself speaks to genetic modifiers or specific exposures that are protective or induction of metastasis. However, to date, no unique genetic differences have been identified in RDEB SCC that explain the aggressive nature—all driver gene mutations are shared with other SCC and no genetic element, other than arising on a background of ther SCC . One SCCC [CASP8 , a gene C [CASP8 . While C success   identified most similarity with head and neck SCC (HNSCC). This similarity was closest to the mesenchymal and basal sub-types of HNSCC as determined from bulk RNA-sequencing ,85. ThesTherapeutic development is still at an early stage, and no approved therapies exist specifically for RDEB SCC. Similarities identified between RDEB SCC and other forms of SCC do support the use of therapies approved for SCC . In thisOne recent study used unrestricted somatic stem cells (USSCs), thought to be precursors of mesenchymal stem cells derived from human cord blood, to try and suppress fibrosis and malignant progression of SCC in an RDEB animal model . In thisIn the general population, cSCC rates of incidence are increasing, especially in aged populations . In RDEB


RHOD in overall and ER+ breast cancers  per standard deviation (SD) increase in expression level 1.06;  1.03, 1.09; P = 5.65 × 10–5) and OR 1.22  in normal breast tissue and blood respectively). There was a consistent direction of association for ER− breast cancer, although the effect-estimate was imprecisely estimated. Using eQTLs from breast cancer tissue and normal blood there was some evidence that CDC42 was negatively associated with overall and ER + breast cancer risk. The evidence from colocalization analyses strongly supported our MR results particularly for RHOD. Our study suggests a potential causal role of increased RHOD gene expression, and, although the evidence is weaker, a potential protective role for CDC42 gene expression, in overall and ER+ breast cancers. These finding warrant validation in independent samples and further biological investigation to assess whether they may be suitable targets for drug targeting.The Rho GTPase family consists of 20 genes encoding intracellular signalling proteins that influence cytoskeletal dynamics, cell migration and cell cycle progression. They are implicated in breast cancer progression but their role in breast cancer aetiology is unknown. As aberrant Rho GTPase activity could be associated with breast cancer, we aimed to determine the potential for a causal role of Rho GTPase gene expression in breast cancer risk, using two-sample Mendelian randomization (MR). MR was undertaken in 122,977 breast cancer cases and 105,974 controls, including 69,501 estrogen receptor positive (ER+) cases and 105,974 controls, and 21,468 ER negative (ER−) cases and 105,974 controls. Single nucleotide polymorphisms (SNPs) underlying expression quantitative trait loci (eQTLs) obtained from normal breast tissue, breast cancer tissue and blood were used as genetic instruments for Rho GTPase expression. As a sensitivity analysis, we undertook co-localisation to examine whether findings reflected shared causal variants or genomic confounding. We identified genetic instruments for 14 of the 20 human Rho GTPases. Using eQTLs obtained from normal breast tissue and normal blood, we identified evidence of a causal role of  There are 20 Rho family genes in humans2  robust association of the genetic instrument with the exposure of interest; (ii) no confounding of the instrument-outcome relationship; and (iii) lack of an alternative pathway through which an instrument influences the outcome except through the exposure8. The feasiblity, precision and statistical power of MR analysis can be increased by using a “two-sample MR” framework in which summary genetic association data from independent samples representing firstly, genetic variant-exposure and secondly, genetic variant-outcome associations are combined in order to assess causal effects10.Mendelian randomization (MR) uses germline genetic variants as instruments (“proxies”) to generate evidence for an association of potentially modifiable extrinsic risk factors and intrinsic metabolic processes on disease outcomesThe aim of our study was to assess whether a potential association exists between the expression of genes encoding Rho GTPases and risk of overall, estrogen receptor-positive (ER+) and estrogen receptor-negative (ER−) breast cancer.11. All participating studies in BCAC were approved by their appropriate ethics review board and all subjects provided informed consent and all the methods were performed in accordance with the relevant guidelines and regulations. Full details of the 78 studies that contributed data to this BCAC analysis and their ethical approval committees are listed in11.Summary data were obtained from a genome-wide association study (GWAS) of 122,977 overall breast cancer cases  and 105,974 controls of European ancestry from the Breast Cancer Association Consortium (BCAC)In studies that participated in BCAC, the ER status provided by each individual study was usually from either; (1) clinical records, (2) immunohistochemistry (IHC) whole sections, (3) IHC stain of Tissue Micro Arrays (TMAs), (4) derived from Ariol data of TMAs (a high throughput automated imaging system) (5) derived from semi-quantitative IHC stain data (not defined whether from whole sections or TMAs), and (6) other (not defined). Sometimes, the source is unknown.A diagrammatic representation of the included datasets and the methodology is shown as a flow diagram Fig. .Figure 2https://gtexportal.org/home/)12 and selected the top SNP associated with the gene expression . Second, we extracted eQTLs  from the eQTLGen consortium (https://www.eqtlgen.org/) which has performed cis- and trans-eQTL analysis in blood from 31,684 individuals13 of largely European ancestry. The consortium defined the cis-eQTLs as every SNP-gene combination with a distance < 1 Mb from the center of the gene and were tested in at least 2 cohorts. Third, we obtained breast cancer tissue eQTLs from The Cancer Genome Atlas (TCGA)  which has systematically performed eQTL analyses across 24 human cancer types14. Finally, we selected cis-SNPs (within 1 Mb of the target gene) that were associated with gene expression level at a P-value threshold of P < 5 × 10–08 based on summary data available on the three platforms. To retain only independent SNPs, we used linkage disequilibrium [LD] clumping with a threshold of r2 ≤ 0.01 based on the 1000 Genomes European ancestry reference panel data15.To generate genetic instruments to proxy for Rho GTPase gene expression, we performed a multi-step approach. First, single nucleotide polymorphisms (SNPs) marking expression quantitative trait loci (eQTLs) underlying expression of the genes encoding 20 Rho GTPases were obtained from normal breast tissue, breast cancer tissue and blood from patients without breast cancer. We obtained normal breast tissue specific eQTLs by searching for the expression of each gene in the Genotype-Tissue Expression (GTEx) project (v8) 17 was only available in the eQTLGen consortium dataset.In sensitivity analyses, 2 and F-statistics to assess for both the strength of the genetic instruments and for weak instrument bias using previously reported methods18. Exposure and outcome data were harmonised such that the effect of each SNP on the outcome and exposure was relative to the same allele19.We extracted the following information for each selected eQTL—effect allele, other allele, beta coefficient and standard error—and calculated the proportion of variance in gene expression explained by the SNP. We calculated RYG/βXG . In secondary analyses, when the genetic instrument consisted of multiple SNPs , we used the inverse-variance weighted (IVW) method, which performs an inverse variance weighted meta-analysis of each Wald ratio for each SNP20. By default our inverse-variance weighted (IVW) Mendelian randomisation analyses were based on random effects models. If under dispersion in these IVW models was detected, i.e., if the residual standard error of the IVW model was less than 1, the standard errors of the regression coefficients were corrected by dividing by 1 rather the by the residual standard error21.For our primary analyses using the top eQTL, we used the Wald ratio method, equivalent to β22 to investigate the probability that the genetic associations with both gene expression level and risk of breast cancer shared the same underlying causal variants. Here, we used the SNPs that were located within 1 Mb windows of the eQTL studied in the MR analysis.We used summary genetic association data (beta coefficients and standard errors) and conducted colocalisation analysis, Cochran’s Q was computed to quantify heterogeneity across the individual causal effects of SNPs and for an instrument with ≥ 3 independent SNPs, weighted median23, weighted mode24 and MR-Egger regression25 methods were applied. Violations of the MR ‘no horizontal pleiotropy’ assumption (where a locus influences the outcome through independent pathways separate to the exposure)26) were assessed by visual inspection of plots constituting a multi-allelic instrument .For multi-allelic instruments, it was possible to perform sensitivity analyses to assess whether there was any evidence of violations of the MR assumption of no pleiotropic effects. For an instrument made up of ≥ 2 independent SNPsP-value thresholds for strong evidence  and suggestive evidence (0.004 < P < 0.05) of a causal effect.To account for multiple testing, Bonferroni corrections were used to establish 19, http://www.mrbase.org. The study was in accordance with relevant guidelines and regulations.All analyses were carried out using the TwoSampleMR and MRInstruments R packages, curated by the latest version of MR-Base (0.5.4)Of the 20 genes of the Rho GTPase family, 14 could be analysed using MR as they had at least one strongly associated SNP in at least one of the three databases that were searched Fig. .Table 2Mras homolog family member D (RHOD) was positively associated with overall and ER+ breast cancer risk  per standard deviation (SD) increase in expression level 1.06;  1.03, 1.09; P = 5.65 × 10–5) and OR 1.22  in normal breast tissue and blood respectively. ER+ breast cancer: OR per SD increase in expression level was 1.08  and 1.32  in normal breast tissue and blood respectively).Using eQTLs obtained from both normal breast tissue and blood, increased expression of RHOD from both breast tissue and blood, and none from breast cancer tissue, we were unable to perform multiple SNP sensitivity analyses.The direction of association was consistent for ER− breast cancer but the evidence of association was suggestive  and OR per SD increase in expression level 1.19  in normal breast tissue and blood respectively). As we obtained only one SNP for the eQTL for cell division cycle 42 (CDC42) was inversely associated with overall and ER+ breast cancer risk.  and OR per SD increase in expression level 0.96  using eQTLs obtained from breast cancer tissue and blood in general population respectively. ER+ breast cancer: OR per SD increase in expression level 0.90  and 0.95  using eQTLs obtained from breast cancer tissue and blood, respectively). The direction of association was consistent for ER− breast cancer using eQTL from breast cancer but the evidence of association was weak ). Using an eQTL from blood, the evidence of association was inconclusive ).There was some suggestive evidence that increased expression of 18. The power to detect the odds ratio of 1.2  was > 99% for RHOD in overall, ER+ and ER− breast cancer using eQTL obtained from breast tissue and ≥ 30% using eQTL obtained from blood  of 1.2 (or conversely a protective OR of 0.80) given an alpha level of 0.05, the variance explained in the expression level of the gene by the SNP instrument and the sample size of the outcome dataset against overall, ER+ and ER− breast cancer risk, as described previouslyCDC42 on overall and ER+ breast cancer were consistent across the various sensitivity analyses . Using multiple SNPs obtained from blood, there was evidence of protective association with overall  and ER+ breast cancer  consistent to single SNP analyses. The evidence of association was inconclusive for ER− breast cancer risk . For multiple SNP sensitivity analyses, the results for the effect of RHOD (using summary data from the GTEx platform) the posterior probability of colocalization  was 84% for overall breast cancer risk and 98% for ER+ breast cancer risk suggesting that breast cancer risk and RHOD expression are both associated and share a single causal variant (Table RHOD eQTLs (9%). There was weaker evidence of colocalization of the CDC42 expression (using summary data from the eQTLGen platform) and breast cancer risk signals  within KM Plotter and splitting patients by an auto-select best cut off , we found that increased RHOD expression was associated with an improved Recurrence Free Survival (RFS) in overall breast cancer (Hazard Ratio (HR) 0.86, , P = 0.0042) but a worsening trend towards overall survival , P = 0.072) , p = 0.08) and worse OS (HR 1.44 (95% CI 1.05–1.98) p = 0.025). We then assessed the relationship between PAM50 subtype, RHOD expression and RFS and OS, demonstrating conflicting results between OS and RFS. For increased RHOD expression the results were: Luminal A breast cancer, a protective effect on both OS  and RFS 0.8, 95% CI 0.65–0.99, p = 0.039)); Luminal B a worse OS  but a trend towards improved RFS ); Her2 positive, a worse OS  but improved PFS ); and lastly Basal where there was a worse OS  and a trend towards worsening PFS ). These results highlight that further work is needed in larger datasets or with functional laboratory experiments to investigate the underlying biology by manipulating RHOD in representative cell lines.We then assessed the prognostic role of increased RHOD using cBioPortal29 and The Cancer Genome Atlas dataset30 and found a low percentage of amplification events across this dataset . This varied by molecular subtype of breast cancer, ranging from 2.3% for basal-like breast cancer to 8.7% in the Luminal B (ER+ with aggressive features) subgroup  in OD Table .Table 4ARHOD expression with a known breast cancer-associated gene, we chose TP53, a well-known tumor suppressor31. Somatic mutations affecting the TP53 gene (tumor protein p53) have been reported to be altered in breast cancer in approximately 20–40% of all cases, although this depends on the size of the tumor, molecular subtype and disease stage32. MR results showed evidence of a negative association between increased expression of TP53 and ER+ breast cancer risk  using eQTLs obtained from blood. The direction of effect was consistent with overall breast cancer risk, but the evidence was weak . However, a positive association between TP53 expression and ER− breast cancer was observed  consistent with recent literature  and contributes to the trafficking of tyrosine kinases such as SRC family and the PDGFRβ that are implicated in breast cancer progression37. It has also been reported to regulate several other cellular responses that are important for cellular transformation and early cancer development, including cell cycle progression, cytoskeletal dynamics, cell motility and centrosome duplication39.To our knowledge, RHOD , but some results for RFS.were conflicting. There are numerous caveats and considerations that need to be taken into account when examining RFS and OS in this context—including the lack of detailed information as to the treatment that the patients included in these datasets received, the longer relapse times that we typically see in oestrogen receptor positive breast cancer (meaning that relationships often take many years to observe) and the fact that overall survival data assesses all causes of death including those unrelated to breast cancer.. Further work with larger numbers of women will be needed to assess whether the relationship between RHOD and RFS and OS is truly in opposite directions, with a focus on more aggressive breast cancer subtypes.Our results using publicly available datasets show a relatively low frequency of amplifications and copy number alterations within TGCA for D Tables  and 5 ancer Fig. . These dTP53 expression on ER+ breast cancer risk, consistent with the known tumor suppressor role for TP5331. By contrast, the opposite effect was observed for ER− breast cancer. The relationship between germline and somatic changes affecting intra-tumoral TP53 activity is complex and is altered dependent upon the rate of somatic mutations in TP53 (approximately 80% in ER− and 20% in ER+ breast cancer). A discussion around this relationship and the effects of TP53 on breast cancer risk has been recently published17 but interestingly the strength of effect on breast cancer risk we report with RHOD is even stronger than that of a well-established target (rs78378222 at TP53) on breast cancer risk.Our results demonstrated a protective effect of increased RHOD may play an important role in breast cancer aetiology and the mechanisms through which RHOD could drive breast cancer formation merit further investigation.Together, our results suggest that CDC42 is a key regulator of both cell motility and cell cycle progression40 as well as in establishing normal epithelial cell polarity and promoting migratory polarity7. Compared to other Rho GTPases, CDC42 is relatively less studied in cancer41. In single-cell in vitro experiments it promotes a mesenchymal phenotype with cellular invasion42 but its relationship with breast cancer phenotypes is complex. Previous reports have demonstrated overexpression in 42–57% of human breast cancers on a protein level associated with more aggressive clinical behaviour, ductal carcinomas and a poorer prognosis with increased cytoplasmic expression but the opposite with nuclear expression43. There are also previous reports suggesting that CDC42 activation leads to a decreased migratory phenotype in breast cancer cell lines45. A genomic and transcriptomic analysis by the Molecular Taxonomy of the Breast Cancer International Consortium (METABRIC) demonstrated that less aggressive, ER+ tumours were enriched for altered expression of genes in the CDC42 pathway4. Despite this, mutations in CDC42-related genes are very low at between 0.1 and 1.7% and the elevated CDC42 expression in breast cancer is thought to be due to activation of oncogenes or cell surface receptors ) that lead to CDC42 upregulation46. Differences in tissue-specific CDC42 expression biasing the result are unlikely as the effects of SNPs for CDC42 were derived from both breast cancer tissue and from blood and were in concordance. The more plausible explanation for the apparent protective effect of CDC42 is that CDC42 maintains epithelial polarity48 and hence protects against cancer initiation. At later stages of breast cancer development, increased CDC42 expression could promote cancer progression via its effects on cell cycle progression and invasion3. The activity of most Rho GTPases, including RHOD and CDC42, is also controlled by over 70 guanine nucleotide exchange factors (GEFs), 60 GTPase-activating proteins (GAPs) and 3 Rho GDI proteins (guanine–nucleotide-dissociation inhibitors) that switch the Rho GTPases between active and inactive forms39. Interestingly, several GAPs are upregulated in basal-like breast cancers and contribute to breast cancer cell growth49.RHOD, suggesting that our MR findings could not be driven by genetic confounding through LD between eQTLs and other disease-causal SNPs strengthening the evidence of causality. Evidence of colocalization thus served as a complementary approach to reinforce the MR finding for RHOD.We performed sensitivity analyses to disentangle the causal effects of gene expression from associations driven by horizontal pleiotropy, reverse causation, and genetic confounding through LD. We found robust evidence of colocalization for RHOD. Although we could not detect strong evidence of effects for Rho GTPases for the ER− breast cancer subtype, this could be due to a lack of power to detect smaller effect sizes in this cohort. Larger studies with matched germline genotype and tissue-specific normal and tumour gene expression will be required to improve the statistical power of similar MR analyses in the future and would help to causally link other members of the Rho GTPase pathway with breast cancer risk.We have tested the effects of Rho GTPases in human samples rather than cancer-derived cell lines or animal models that often give variable and inconsistent results. In contrast to conventional observational studies, MR is less susceptible to problems of confounding, reverse causation and measurement error. The use of two-sample MR enabled us to use the largest GWAS of breast cancer to date. Ideally, we would have liked to examine protein-level expression of the Rho GTPases as well as gene expression, but there are very few small studies on protein levels compared to the large datasets available for normal breast, breast cancer and blood-based transcriptomic profiles, and none to our knowledge for RHOD expression may be causally and positively related to breast cancer risk, and that CDC42 may potentially be causally and negatively related to breast cancer risk. Given that the activity of RHOD and CDC42 proteins is regulated by a variety of other proteins, it will be interesting to determine whether any of the genes encoding these regulators are also associated with breast cancer risk. The role of RHOD warrants further biological investigation to assess its role in breast carcinogenesis.We found robust evidence that Supplementary Table 1.


Andes virus, an orthohantavirus endemic to South America, causes severe hantavirus cardiopulmonary syndrome associated with human-to-human transmission. No approved treatments or vaccines against this virus are available. We show that a combined treatment with 2 monoclonal antibodies protected Syrian hamsters when administered at midstage or late-stage disease. Oligoryzomys longicaudatus long-tailed pygmy rice rat (Hantavirus cardiopulmonary syndrome (HCPS) is a severe disease caused by infection with pathogenic New World orthohantaviruses, including Andes virus (ANDV). ANDV is transmitted to humans via the aerosolized excrement of the rodent reservoir and vector, the ANDV infection has a long incubation period of 2–3 weeks, followed by a 3- to 5-day prodrome phase characterized by fever, headache and gastrointestinal symptoms. HCPS develops over a 2–7 day period characterized by falling blood pressure, lung edema or failure, cardiac shock, and death in a substantial number of patients (Our group has previously reported that mAbs isolated from HCPS survivors (clones JL16 and MIB22) protected hamsters from lethal ANDV challenge when mAb treatment was initiated early postinfection, suggesting potent postexposure efficacy  and administered mAbs (MIB22 + JL16) directed against ANDV glycoprotein  to a treatment group (n = 12), compared with a control group (n = 12) treated with isotype antibody , panel ATo further assess the efficacy of the mAb cocktail against ANDV, we evaluated the mAb cocktail treatment at an advanced stage of ANDV infection by treating the animals at 8 and 10 dpi (8+10) , panel AOur results demonstrate that the human mAb cocktail containing JL16 and MIB22 is able to completely or partially protect Syrian hamsters against lethal ANDV challenge when administered as a 2-dose regimen at midstage (5 and 9 dpi) and late-stage (8 and 10 dpi) disease. To date, the Syrian hamster is the only ANDV preclinical disease model that is appropriate to evaluate the efficacy of therapeutic and prophylactic countermeasures. Thus, our antibody cocktail study meets the Food and Drug Administration animal rule, which requires evidence of efficacy of a countermeasure in a well-established and evaluated animal model indicating potential benefit for human use (Fine-tuning the dosing and more effective combinations of mAbs will likely extend the therapeutic window even further. However, the 100% midstage and 50% late-stage protection observed in these experiments are very encouraging in the endeavor to find a specific treatment for human HCPS caused by ANDV infection.Additional information about human monoclonal antibody treatment for Andes virus infection in Syrian hamsters.


It is estimated that 1–13% of cases of bronchiectasis in adults globally are attributable to primary ciliary dyskinesia (PCD) but many adult patients with bronchiectasis have not been investigated for PCD. PCD is a disorder caused by mutations in genes required for motile cilium structure or function, resulting in impaired mucociliary clearance. Symptoms appear in infancy but diagnosis is often late or missed, often due to the lack of a “gold standard” diagnostic tool and non-specific symptoms. Mutations in > 50 genes account for around 70% of cases, with additional genes, and non-coding, synonymous, missense changes or structural variants (SVs) in known genes presumed to account for the missing heritability.UK patients with no identified genetic confirmation for the cause of their PCD or bronchiectasis were eligible for whole genome sequencing (WGS) in the Genomics England Ltd 100,000 Genomes Project. 21 PCD probands and 52 non-cystic fibrosis (CF) bronchiectasis probands were recruited in Wessex Genome Medicine Centre (GMC). We carried out analysis of single nucleotide variants (SNVs) and SVs in all families recruited in Wessex GMC.IFT140 and PLK4) in 2 probands in the PCD cohort. 3/52 probands in the non-CF bronchiectasis cohort received a confirmed (n = 2) or possible (n = 1) diagnosis of PCD. We identified variants in novel PCD candidate genes (CFAP53 and CEP164) in 2 further probands in the non-CF bronchiectasis cohort.16/21 probands in the PCD cohort received confirmed (n = 9), probable (n = 4) or possible (n = 3) diagnosis from WGS, although 13/16 of these could have been picked up by current standard of care gene panel testing. In the other cases, SVs were identified which were missed by panel testing. We identified variants in novel PCD candidate genes (Genetic testing is an important component of diagnosing PCD, especially in cases of atypical disease history. WGS is effective in cases where prior gene panel testing has found no variants or only heterozygous variants. In these cases it may detect SVs and is a powerful tool for novel gene discovery.The online version contains supplementary material available at 10.1186/s12920-021-01084-w. CFTR gene is the most common genetic cause (≈1:2500 European Caucasians), and is usually picked up before bronchiectasis is established by new-born screening where it is available. PCD is less common , primary ciliary dyskinesia (PCD) and primary immunodeficiency disorders are common causes of bronchiectasis. CF, caused by mutations in the h Asians . PCD symA combination of investigations is usually required to make a diagnosis of PCD , 5. WhilMutations that cause PCD have been reported in > 50 genes . These aDNAH11, 7/21 had been tested against a gene panel which included 19 known PCD genes  comprised patients from the PCD Adult and Paediatric Centre at University Hospital Southampton (UHS) who had no genetic diagnosis of PCD, and their first-degree relatives. 9/21 probands had no prior genetic testing. 1/21 probands had previously had targeted sequencing of PCD diagnostic testing was undertaken for all participants in the PCD cohort prior to recruitment to 100,000 Genomes Project. Participants in the non-CF bronchiectasis cohort were invited for PCD functional testing and biomedical imaging if the WGS found variants in PCD-related genes. A detailed clinical history was recorded using a proforma. PCD diagnostic testing included nasal nitric oxide (nNO), high-speed video microscopy (HSVM) analysis , transmihttps://www.genomicsengland.co.uk/wp-content/uploads/2017/03/GenomicEnglandProtocol_151117-v4-Wales.pdf. In brief, DNA was extracted and stored in a central bioresource, PCR-free libraries prepared and sequenced using Illumina short-read technology, sequence data aligned to the human reference genome, followed by variant calling and annotation. Genomics England Ltd performed variant filtering through an automated analysis pipeline to identify potentially diagnostic small nucleotide variants (SNVs) and structural variants (SVs), which were “tiered” according to likelihood of being the pathogenic cause of disease if in clinically relevant genes .The 100,000 Genomes Project recruited 118 PCD patients nationally . 21 PCD probands were recruited in Wessex GMC (41 participants including family members) including 9 singletons, 4 duos and 8 trios. We first describe the results returned in the clinical tiering analysis, and then the results of our independent research analysis.DRC1, DNAI1, DNAH11 (× 2) and DNAH5 (× 2). Of the 6 confirmed cases, 4 had not undergone prior testing but the variants were all identifiable by standard panel testing. A diagnosis was now possible in the 2 cases that had undergone prior testing because either additional cases were available in the literature or parental testing demonstrated that the variants were in trans ; WGS did not identify any additional variants.Tier 1 or tier 2 variants were found in 12/21 patients. ACMG variant classification confirmed a diagnosis of PCD in 6 cases  (Table DNAI1 and DNAH11 (× 2). All had undergone prior targeted DNAH11 or gene panel testing and received the same findings. Re-analysis of the VUS did not result in reclassification, and so the diagnosis remains as probable but not confirmed. WGS did not provide useful additional information in these cases but confirmed findings from gene panel testing.A further 3 cases received a probable diagnosis   in a known PCD gene)  in one family. Manual inspection of DNAH5 sequence data identified a stop gain in trans with the SV providing an additional confirmed diagnosis , DNAH11 (× 5) and DNAH5 (× 3). These were new findings in 6/13 cases and in 7/13 cases confirmed results from prior panel testing.In summary, 13/21 participants received confirmed, probable or possible diagnostic results from the initial clinical analysis of tiered data and SVsGenomics England Ltd. The causative genes were 8/21 participants did not receive a result from the initial analysis of tiered variants.DNAAF4, DNAH11, HYDIN and CCDC114. One of these had undergone prior gene panel testing that had identified the single heterozygous SNV in DNAAF4. We then visually analysed the alignment files of these participants in IGV to identify any SVs. This identified that 3 of the cases had biallelic SNVs and SVs in PCD genes which were not picked up by the tiering pipeline, as they were < 10 kb):DNAAF4 deleting exon 7 , and with the second pathogenic SNV in CCDC114 this provides a probable diagnosis following ACMG guidelines. However, ERS PCD Diagnostic guidelines say “Genetic diagnosis has to be consistent with the clinical and TEM/IF/HSVA phenotype, or diagnosis reconsidered if the picture is inconsistent” and so, on balance, we class this as unresolved, with additional work (RNA studies) required to further investigate this case.No SVs were found in SpliceAI . SegregaIFT140, which has been reported in isolated retinitis pigmentosa (RP) [PLK4 which has been associated with microcephaly and chorioretinopathy [IFT140 variants are both missense variants; a rare p.(Leu693Phe) which is predicted by PolyPhen to be tolerated and by SIFT to be benign, and a rare p.(Lys390Arg) which is predicted by PolyPhen to be tolerated and by SIFT to be benign. The PLK4 variants are a frameshift loss-of-function and a -5 splice variant which is predicted to cause loss of the splice donor site, with a SpliceAI donor loss delta score of 0.47 . In order to validate PLK4 as the causative gene, RNA analysis will need to be carried out. In these patients, WGS will have proved invaluable if our further research work can confirm diagnoses in these cases. In the remaining two cases no candidate variants were identified and re-review of the clinical phenotype information indicated that historical diagnostics were not suggestive of PCD, and these patients were inappropriately recruited within the PCD disease category. In these cases WGS analysis was useful in confirming that these patients had no genetic cause of PCD, although this could have been concluded through re-review of their clinical notes.This left 4/21 additional unsolved PCD cases, 2 of whom had undergone prior gene panel testing. In these cases we studied tier 3 variants, applying a functional candidate gene approach by using an updated version of the Syscilia Gold Standard list of known cilia genes  and Ciliosa (RP) , 28 and osa (RP)  and seveosa (RP) –32 and Pinopathy . The IFTCCDC114, where ODA defects would be expected on TEM but were not seen. Following ERS PCD diagnostic guidelines this case remains unresolved. 13 of the diagnoses were provided by Genomics England Ltd tiering analysis and 3 were obtained through further research analysis of the WGS data. 3/16 patients had homozygous SNVs, 13/16 patients were compound heterozygous and in 4 of these patients one of the variants was a SV. Only 1 of these SVs was reported by Genomics England Ltd, as it was > 10 kb. The other 3 were found manually and were all < 10 kb. Furthermore, research analysis identified variants in candidate PCD genes (IFT140 and PLK4) in 2 cases. Thorough genetic analysis and diagnostic imaging found no evidence of PCD in 2 cases. In the 16 cases which received a diagnosis, the causative genes were: DNAAF1, DNAAF4, DRC1, DNAI1 (× 3), DNAH11 (× 6), DNAH5 (× 3) and HYDIN ; a gene described to cause PCD in 2013 [A 34-year-old man from a non-consanguineous background presented with a persistent wet cough since childhood, sino-rhinitis, glue ear and bronchiectasis. He had a PICADAR score [proteins . Genetic in 2013 .DRC1. In this patient nNO levels were normal, although they have previously been reported as abnormally low in patients with mutations in DRC1. We were not using immunofluorescent analyses at the time the patient was diagnosed, but would anticipate absence of GAS8 localisation in the cilia, as DRC1 and GAS8 are both components of the nexin-dynein regulatory complex (N-DRC) in the cilium and mutations in DRC1 cause N-DRC defects which can be observed as absence of GAS8 localisation from the cilium [Therefore, although functional and imaging tests were abnormal, they did not confirm a definite diagnosis of PCD. Using high speed video and TEM the abnormalities were subtle, likely to be missed by non-specialists. Indeed the literature sometimes describes high speed video and TEM as normal in patients with mutations in e cilium . This ca52 non-CF bronchiectasis probands were recruited in Wessex GMC (69 participants including family members), including 44 singletons. Between 2 and 9 different PanelApp panels were applied to these cases, with an average of 2.5 panels. None had prior genetic testing for PCD. We first describe the results of the analysis carried out by Genomics England Ltd and reviewed in the GMC, and then describe the results of our independent research analysis.DNA1 and DNAH5) and the diagnosis of PCD was possible in 1/3 individuals (causative gene RPGR)  Table , Fig. 5.PCD Fig. .Table 4GDNAI1 patient had a typical clinical history . This patient was referred for PCD diagnostics, which was typical for a person with DNAH1 disease . Similarly the DNAH5 patient had a classical clinical history and diagnostic findings , TEM showed outer dynein arm defects and IF showed absence of DNAH5 from the cilium).The RPGR patient’s clinical history was typical for PCD, an ophthalmologist confirmed the patient’s description of no eye disease, despite the association of RPGR variants with X-linked retinitis pigmentosa. This patient subsequently underwent PCD diagnostics, which showed a low nNO, abnormal HSVM before and after culture at air–liquid interface (ALI), dyskinetic throughout. TEM showed normal cilia ultrastructure, but IF imaging showed absence of RPGR from the cilium . We aim to repeat HSVM on a primary nasal epithelium brushing at the earliest opportunity. We suggest that biallelic mutations in CFAP53 cause congenital situs defects, but may also be responsible for subtle respiratory cilia defects manifesting as adult-onset respiratory problems, although this will require further investigation since the lung disease may have a different aetiology. CFAP53 has not currently been considered in the PCD panel in PanelApp but several other CFAP genes are rated amber in the PCD panel.One individual had biallelic patients , 38 but utations . Howeverant mice . In thesCEP164. nNO was in the normal range, but HSVM analysis showed reduced amplitude of ciliary beating and some long cilia, with 19% of cilia showing microtubular disorganisation, mostly rearrangements. CEP164 is not recognised as a PCD gene, but has been reported in a case of dual Bardet-Biedl syndrome (BBS) and PCD presentation [The other individual had compound heterozygous stop gain variants in entation  and our Our data show that WGS testing in a clinically well-characterised PCD cohort has a high pick-up rate (16/21 patients received confirmed (n = 9)/probable (n = 4)/possible (n = 3) diagnosis) although 12/16 of these could have been picked up by current gene panel testing (Genomic Medicine Service PCD panel (R189), 46 green genes). Most cases were recruited and sequenced as trios (proband and parents), which was generally not required, as a diagnosis could have been achieved by singleton analysis with targeted sequencing of parents to determine phase in a small subset of cases. This suggests that WGS was useful but not cost-effective in 13/16 cases. WGS was chosen over WES in the 100,000 Genomes Project in an attempt to identify which conditions and cases most benefit from WGS over WES in clinical diagnostics, and to provide a large dataset of WGS data for future research. Our study suggests that in the case of PCD, WGS has little advantage over gene panel testing, except in unresolved cases where gene panel testing has not provided genetic diagnoses. In our opinion, gene panel testing is a more sensible first line of testing, followed by WES in unresolved cases. The impact of the 100,000 Genomes Project for PCD testing is that it confirms the efficiency and cost effectiveness of gene panel testing. WGS will unlikely become a frontline diagnostic test for PCD, even in the most well-resourced healthcare systems, but remains an extremely valuable research tool.in trans with pathogenic/likely pathogenic coding SNVs. In some cases these coding SNVs were detected by prior gene panel testing but SV/intronic variants were not detected. 3 of these 4 diagnoses in the PCD cohort were obtained through research analysis of unsolved patients involving extraction of heterozygous SNVs followed by analysis of intronic variants and SVs. The current Genomics England Ltd clinical analysis pipeline does not tier deep intronic SNVs, nor SVs < 10 kb, and is not well optimised to detect cases of SNVs and SVs in trans. Heterozygous SNVs are not tiered in recessive disease, and SVs < 10 kb are not tiered by Genomics England Ltd yet 3 of the 4 diagnostic SVs that we found were < 10 kb. The amount of variant data generated by WGS requires filtering, but this needs to be done very carefully to avoid losing relevant variants. Our findings suggest that heterozygous SNVs should be tiered to maximise diagnostic return in clinically well-defined recessive diseases with established genotype/phenotype correlations such as PCD, and SVs should be tiered alongside SNVs in the Genomics England Ltd clinical analysis pipeline.In 4/16 diagnoses WGS provided results which would have been missed by gene panel testing, through detection of SVs CCDC114 splice donor site variant alongside a novel deep intronic VUS highlights that we are likely missing diagnoses by continuing to focus on coding regions in our variant analyses despite sequencing the whole genome. In order to more meaningfully study non-coding regions and synonymous changes we need better tools to predict the effect of such changes on splicing, and allow effective filtering of these. Unless intronic sequences can be screened efficiently and accurately, then WGS may have little advantage over WES . SpliceAI is a tool with higher sensitivity (0.8987) and specificity (0.9162) for predicting the effect of genetic variants on splicing than any previous tool, but still has false positive and false negative rates of around 10% [The identification of a heterozygous ound 10% . We needhttps://cftr2.org/), a public repository for reporting CFTR variants found in CF patients. The BEATPCD consortium is currently working on such a resource, called ‘CilioVar’ (https://beat-pcd.squarespace.com/working-groups-summary). As a frontline test, WGS provides much greater scope for generating new diagnoses than WES or gene panel testing, as iterative re-analysis would include newly identified disease genes. However, WGS reanalysis brings resource  implications for storing and analysing large volumes of data. Furthermore, the efficient use of resources also needs to be considered to balance analytical work with diagnostic yield. Although the standardised Genomics England Ltd WGS data analysis pipeline has made significant steps towards streamlining and automating the process of prioritisation of variants likely to be clinically significant, the requirement to carry out expert clinical variant classification to confirm diagnoses remains the rate-limiting step for the implementation of large-scale WGS. Unfortunately, this was poorly resourced in the 100,000 Genomes Project, leading to delays in return of results. It is clear from the 100,000 Genomes Project that adequate funding of data analysis and interpretation is a critical and indispensable component for delivering a WGS-based diagnostic service.Two of the patients who received a ‘confirmed diagnosis’ of PCD based on SNVs in known PCD genes had previously received ‘probable diagnosis’ on the basis of the same variants found in prior gene panel testing. This reclassification of probable to confirmed diagnosis could have been achieved independently with re-review of existing data and targeted gene sequencing in parents. In cases where two variants in a known disease gene have been identified but one or both are VUS re-review of panel/WES data is more useful than further sequencing by WGS, especially if the VUS is in combination with a pathogenic/likely pathogenic variant and phenotype data support the gene of interest. It is clear that re-review of prior testing results is useful to improve diagnoses, and this process would greatly benefit from a motile cilia disease-specific public resource for depositing clinical variant data from PCD patients, similar to CFTR2  where gene agnostic approaches can be used.DRC1 case we present demonstrates the important role that genetic testing plays as an additional diagnostic test in cases of PCD where patients do not have a strong history . Therefore, there are likely to be many patients with PCD in adult pulmonology clinics- if clinicians do not revisit the early life history, they may miss patients with a history suggesting a genetic cause. The identification of candidate gene variants in 2 patients in the non-CF bronchiectasis cohort suggests that novel disease genes may be discovered by investigating cases with atypical PCD and that the phenotypic spectrum of PCD may be broader than previously described.RPGR case to provide further evidence that this gene can be a cause of PCD. To be rated green on PanelApp pathogenic variants need to be identified in ≥ 3 independent families, so identification and publication of additional novel cases in rare/amber genes is important.Finally, we present a case of PCD without ophthalmological involvement, associated with a hemizygous variant in DRC1 case we present.PCD is a difficult condition to diagnose as there is no “gold standard” diagnostic tool. Genetic testing is useful to confirm a diagnosis of PCD,especially in cases which do not have a typical history, such as in the PCD diagnoses continue to be missed even in large adult bronchiectasis centres. WGS in adults with non-CF bronchiectasis is useful for detecting missed diagnoses of PCD in this group of patients, and trio analysis is useful in this cohort.WGS is a useful diagnostic test in a PCD cohort but is only an effective use of resources where patients have received no findings or have only had heterozygous variants found from prior gene panel testing. A significant proportion of diagnoses were missed through the automated Genomics England Ltd tiering pipeline, and were only picked up with additional labour-intensive manual analysis of patient’s genome data.Proband-only gene panel/WGS testing followed by targeted testing of parents where required is sufficient for diagnosis of PCD in most cases, and is more cost-effective.Heterozygous SNVs and SVs from WGS should not be filtered out of analysis in clinically well-defined recessive diseases with established genotype/phenotype correlations such as PCD.WGS is a powerful tool for gene discovery. We identify 2 novel candidate PCD genes in our PCD cohort and another 2 in our non-CF bronchiectasis cohort.The advantages of WGS over gene panel testing will be more apparent when we have better tools for intronic variant filtering and automated systems for clinical variant classification and periodic re-review of data.Additional file 1. Table 1: Genes on 19 and 29 gene next generation sequencing panel used for PCD genetic testing in patients in the Wessex PCD cohort prior to WGS through the 100,000 Genomes ProjectAdditional file 2. Additional information on 100,000 Genomes Project recruitment, sequencing, sequence analysis and variant filtering and tiering performed by Genomics England Ltd.


To date, mechanistic treatments targeting the initial cause of Parkinson's disease (PD) are limited due to the underlying biological cause(s) been unclear. Endosomes and their associated cellular homeostasis processes have emerged to have a significant role in the pathophysiology associated with PD. Several variants within retromer complex have been identified and characterised within familial PD patients. The retromer complex represents a key sorting platform within the endosomal system that regulates cargo sorting that maintains cellular homeostasis. In this review, we summarise the current understandings of how PD-associated retromer variants disrupt cellular trafficking and how the retromer complex can interact with other PD-associated genes to contribute to the disease progression. Retromer protein complex, a key endosomal protein trafficking sorting platform, has been investigated in detail , establiCI-M6PR, a type I transmembrane protein, has a pivotal role in the delivery of newly synthesised lysosomal hydrolase precursor from Golgi to endosomal lumen, whereas the unoccupied CI-M6PR from the endosome can be retrieved back to the TGN for reuse. Retrograde trafficking of CI-M6PR from the endosome to the TGN can be regulated by multiple endosomal machineries including the retromer complex . The WLMThe formation of one type of retrograde endosome transport carriers (ETCs) is dependent on retromer . CurrentThe interaction of the core retromer complex with the PX- BAR domains-containing SNXs has been proposed in the formation of ETCs in eukaryotes. The BAR domains of SNX-BAR proteins can stabilise and generate the high curvature of endosomal tubule structures by the regulation of membrane deformation . HoweverBesides retrograde transport from endosomes to the TGN, retromer can also mediate the recycling of cargo from the endosomes to the cell surface. Retromer associates with another PX domain containing protein SNX27 that contains a FERM domain at its carboxyl terminus region and a PDZ domain. SNX27's association with endosomes is mediated by the PX domain to recognise the PI3P , and theRecently, there is a ‘retromer-like’ protein complex, named the retriever complex which displays structural similarity to the retromer complex was discovered ,38,39. TGenetic predisposition plays a critical part in the disease progression. It is estimated that ∼15 percent of people with PD have a family history of this disorder caused by genetic variants within the PD loci from Parkinson Disease 1 (PARK1) to PARK23 . ParticuIn vitro isothermal titration calorimetry and affinity immunoprecipitation experiments clearly demonstrate that Vps35 D620N variant has no effect on assembly of the retromer core trimer formation [Recently it has been directly demonstrated the Vps35 D620N variant is deficient in the formation of retrograde ETC  48]. Ho. Ho48]. ormation ,51. The ormation ,52. Struormation . This coormation . The WASormation ,54. The ormation . DnaJ hoormation ,57. In aormation . Expressormation .Despite numerous cargo proteins dependent on retromer being reported from several proteome studies in established cell models ,37,64, oA significant decrease in the protein expression of dopamine transporter 1 (DAT1), a key transporter responsible for dopamine uptake into presynaptic terminal, is consistently found in the PD patients , and a dExperimentally, many cellular pathways have already been implicated in the retromer-dysfunction associated with PD but their relevance is often questionable. Do they mimic the pathobiology of the disease or simply reflect an experimentally induced shift in cellular homeostasis able to cause PD associated symptoms? PD is a late onset, taking over 10–15 years to present clinically in humans and only affects a few cell types. Therefore, any predisposition to the disease caused by the genetic variant associated with familial PD can only cause subtle changes in functional capacity at the cellular level. These issues have created significant contention in the field and moving forward we need to determine the direct mechanistic molecular details that underpin the initiation of PD. α-synuclein aggregation, the major component of PD-associated Lewy bodies and associated with neuron death, represents a hallmark cellular phenotype for PD, whereas the defects on the retrograde trafficking caused by Vps35 D620N may act as one of the key drivers for the onset of the PD. Expression of Vps35 D620N variant reduces the cells ability to clear these intracellular aggregates due to the impaired endo/lysosomal functions and autophagy homeostasis ,78. Firsc [Another major cellular defect caused by Vps35 D620N variant was associated with the changes on mitochondria homeostasis. Vps35 D620N variant was reported to increase its binding with dynamin-like protein 1 (DLP1), a key regulator for the mitochondria fission ,82. Intec . The VpsAccumulated evidence indicates molecular interactions between retromer and other genes associated with familial PD can modify cellular homeostasis and contribute to the early-onset of disease. These include PARK1 , PARK2 (parkin), PARK6  and PARK8 . Expression of Vps35 D620N variant results in the accumulations of intracellular α-synuclein aggregates, most likely due to defects in autophagy ,78,81,85PINK1 (PARK2) coordinates with Parkin (PARK6) within the quality control pathway that monitors mitochondria integrity. PINK1 phosphorylates and recruits Parkin from the cytosol to damaged mitochondria, where Parkin functions as an E3 ubiquitin ligase to ubiquitinate protein substrates for proteasomal degradation which facilitates the selective remove the damaged mitochondria via mitophagy . Parkin LRRK2 (PARK8) is considering as one of the most important genetic factors contributing to PD progression. LRRK2 is a large protein containing multiple functional domains, including a kinase domain and a GTPase domain. Although LRRK2 is mainly localised to cytosol, it can be recruited to multiple intracellular compartments, including endosome, lysosome, mitochondria, ER and the TGN, from which LRRK2 mediates multiple cellular processes, such as vesicular trafficking, mitochondria homeostasis, protein synthesis and inflammatory processes . ServingOverall, retromer interacts with a number of proteins encoded by other PD associated genes. These interactions are fundamentally important and contribute to the regulation of intracellular trafficking and cellular homeostasis.The deficiency of retromer dependent protein trafficking associated with the Vps35 D620N variant could be modulated therapeutically. Several retromer stabillisers have been developed including R55 a pharmacological chaperon that stabilises the association between Vps35 and Vps29. R55 treatment within cell models reduces the level of α-synuclein aggregation in cells expressing the Vps35 D620N variant . RetromeRetromer complex is a key endosomal trafficking hub that mediates cargo trafficking which maintains endo-lysosomal functions and cellular homeostasis.Familial PD associated retromer variants have a reduced capacity to generate a single type of endosome transport carrier.The PD-associated retromer Vps35 D620N variant has a reduced association of the WASH complex with the retromer complex.Identification of the individual cargo proteins that have modified protein trafficking itineraries in PD is incomplete. This is important as any subtle changes in trafficking itinerary of individual cargo proteins has the potential to alter various associated cellular homeostatic states thereby facilitating the initiation of PD.As our better understanding of retromer biology continues, consideration of retromer as a therapeutic target for PD and other neurodegenerative diseases increases.